So, I’ve decided to try a slightly different approach for the next while—one that has these sorts of folks in mind. From time to time, you can still expect those more in-depth, technical articles, or perhaps a discussion of some new research that makes the popular press, or even an analysis of some new argument from the IDM or RTB. These will be breaks from the new routine, however. For the most part, we’re going to stick to the basics, much like you would if you took an introductory evolution course at a university. Don’t worry, though: this course doesn’t have any prerequisites! All that’s needed is a willingness to learn.

What you can expect

The goal of this course is straightforward: to provide evangelical Christians with a step-by-step introduction to the science of evolutionary biology.  This will provide benefits beyond just the joy of learning more about God’s wonderful creation. An understanding of the basic science of evolution is of great benefit for reflecting on its theological implications, since this reflection can then be done from a scientifically-informed perspective. From time to time we might comment briefly on some issues of theological interest (and suggest resources for those looking to explore those issues further), but for the most part, we’re going to focus on the science. For folks interested in the interaction between science and Christianity, I heartily recommend Ted Davis’ recent series as a fabulous introduction to the topic.

You can also expect a slow, patient pace. Since this course is intended for folks with little or no background in biology, we’re going to take our time to make sure no one gets left behind. This might be frustrating to folks who already know a fair bit about evolution. Hopefully even more knowledgeable readers will learn some new and interesting details along the way—but the goal will primarily be to help folks who are less well versed in evolution increase their understanding.

You can also expect a survey of many different areas that have some bearing on evolution. We’ll examine geology, paleontology, biogeography, genetics, and a host of other topics in order to provide a “big picture” overview. This broad-brush approach means that any given individual post will not necessarily be “convincing” to folks who have doubts about evolution. Think about assembling a large jigsaw puzzle: placing any individual piece, on its own, doesn’t convincingly demonstrate what the overall picture will show. This course will be like that. Each topic we cover will put a few pieces in place here and there, slowly building towards the final overall picture.

Since evolution is an active science, this process will also highlight where there are “missing pieces” that are still being sought by scientists. All of this is well and good, since the purpose of this course is not so much to convince anyone of the validity of evolutionary theory, but rather to inform readers about the nature and scope of evolution as a scientific theory in the present day. My goal is to provide readers with a basic understanding of what evolution is and how it works. Given that as the primary goal, if one finds the scope of the evidence ultimately convincing (or not) is somewhat beside the point. The intent here is to provide readers with information they can use to make their own, informed decision.

How you can help

First and foremost, you can help by spreading the word about this series to folks you think would be interested in learning more about evolution in a non-threatening environment. Secondly, you can help me by asking questions in the comments. One of the challenges of being a specialist is having the ability to put oneself in the shoes of someone just starting out. What might seem obvious to me may not seem obvious to you, and I hope you’ll feel that no question is too basic or too simplistic. If you’re wondering about something, it’s almost guaranteed that other folks are, too! So, please don’t be shy. I’ll do my best to answer questions in the comments, though I hope that some of our more skilled commenters will (respectfully!) help out here, as well. Finally, you can help by letting me know what broader areas of evolution you find confusing. I have my own ideas about what areas of evolution are commonly misunderstood, but I’d love to hear from readers about what areas they find difficult to understand. I’ll use this input to shape the topics I will cover as we go forward.

Getting started

In the next post in this course, we’ll dive into the course content by introducing two key areas: how scientific theories work in general, and how evolution in particular works as the current organizing theory of modern biology. 

Such remnants are also found in our genomes.  Humans, unlike most mammals, cannot synthesize (make) our own vitamin C, but we carry the genes for synthesizing vitamin C.  One of these genes encodes the GLO (L-gulonolactone oxidase) enzyme, and this gene in humans contains inactivating mutations and is therefore a “pseudogene.”  This pseudogene and the genes that encode the enzymes of the vitamin C biosynthetic pathway are the remnants of our own evolutionary lineage from an ancestor that was able to synthesize its own vitamin C.⁴ Furthermore, the GLO pseudogene is just one of a graveyard of inactivated genes, transposons, retroviruses and other non-functional sequences that litter our genome.  While some of these sequences have been co-opted for particular functions, many of them have no known function.⁵ We share many of these non-functional sequences with chimpanzees.  The very presence of these genomic and anatomical flotsam and jetsam only makes sense if evolution has occurred.⁶

A third piece of evidence for evolution comes from biogeography.⁷ The flora and fauna of islands such as those of the Galápagos and Hawaii are radically unbalanced in that they lack many types of plants and animals but contain a profusion of clusters of similar species.  Hawaii, for example, has no native mammals, reptiles, or amphibians, but a profusion of fruit flies and silversword plants.⁸ One third of the 2,000 species of fruit flies are found on the Hawaiian Islands, which only covers 2 percent of the land on earth.  These islands were never connected to the continents and arose as a result of volcanic activity and were, at least initially, completely uncolonized.  The colonization of these islands occurred by means of occasional introduction of creatures from the mainland that then rapidly speciated on these islands to fill every available ecological niche.  Thus, the organisms most closely related to island species come from the closest mainland areas, and often include those creatures most likely to find their way to islands, such as birds and flying insects. 

The Galápagos Islands provide an excellent example of how biogeography provides evidence for evolution. The Galápagos have fourteen species of finch whose closest relative is probably the South American grassquit (Tiaris), yet only four of these finch species feed on seeds as finches normally do, while two others feed on cacti, seven eat insects, and another eats almost exclusively leaves.⁹ Darwin, while visiting the Galápagos, still thought that species only varied within a particular kind (though he would not have used that terminology) but could adapt to various local environments and become particular subspecies. Therefore, he originally listed the warbler finch (Certhidea olivacea) as a wren and listed the small cactus finch (Geospiza scandens) as a member of the Icteridae or the family of meadowlarks and orioles.  Only after Darwin had deposited his Galápagos specimens with the British ornithologist John Gould did Darwin discover (in a meeting with Gould that occurred during March, 1877), that his finch collection included thirteen or fourteen species of unusual finches that were all so closely related, Gould classified them in a single group all their own.  This meeting showed Darwin that the immutable barrier between kinds of species did not exist.  The Galápagos Islands were not a distinct “center of creation,” but a workshop for evolution in which an ancestral species made it to the yet uncolonized island and underwent a massive degree of speciation to adapt to the environment of the island.¹⁰ This is precisely what one would expect if the species of islands had arisen by evolution. 

A scientific theory also allows scientists to make predictions, and good theories provide accurate predictions.  Can the theory of evolution allow accurate predictions?  The answer, once again, is yes.  Darwin himself predicted that the earth must be very old for evolution to occur.  He did not know the age of the earth, but further research has shown that the earth is 4.55 billion years old, which is plenty of time for evolution to occur.  Darwin also predicted that since plants on islands were most closely related to certain mainland plant species, the seeds of these plants should be able to withstand immersion in sea water for long periods of time, and again, Darwin was shown to be right.¹¹ Many decades after Darwin, we now know that variation in organisms is due to mutations in DNA and that these mutations are inherited, just as Darwin predicted.¹² Also, Darwin’s principle of natural selection predicts that particular sequences of DNA should behave in a manner that benefits only themselves and not their carriers, which modern research has thoroughly confirmed with the discovery of transposons and other types of “selfish DNA.”¹³

Is evolutionary theory a good scientific theory?  It has been repeatedly tested for over 150 years since its inception, and it has passed those tests successfully.  The theory has been modified in response to new data, but the outlines of the theory have remained largely intact.  It has existed at risk from new data.  During the molecular biology revolution that began with the discovery of the structure of DNA by Franklin, Watson and Crick in 1953, the explosion of new data could have shown contemporary evolutionary theory to be wrong.  However, some of the most powerful evidence for the theory of evolution has come from a field of science that did not even exist during Darwin’s time.  The ability of a theory to withstand such intense scrutiny is a clear sign it is robust and enduring.  As shown, the theory of evolution has predictive power, and it also integrates and makes sense of data from several fields of science, including ecology, paleontology, genetics, historical geology, paleoclimatology, and comparative anatomy and biochemistry.  The highly integrative nature of evolutionary theory makes it a fine theory by any measure. 

In conclusion, when measured against the standards of a good scientific theory, modern evolutionary biology clearly qualifies as good science.  Ongoing debates within evolutionary biology exist about mechanism, rates, and causes, but not over whether evolution occurred.  Such a question has been largely settled by the last 150 years’ worth of research.  The future certainly looks bright for this field of science and I cannot imagine a more exciting topic to study. 

Notes

1. Davit-Béal, Tiphaine,Abigail S. Tucker, and Jean-Yves Sire. “Loss of Teeth and Enamel in Tetrapods: Fossil Record, Genetic Data and Morphological Adaptations.” Journal of Anatomy 214, no. 4 (2009): 477–501. 

2. Tian, Natasha M. M.-L., and David J. Price. “Why Cavefish are Blind.” BioEssays 27 (2005): 235–38; Yamamoto Y, Stock DW, and Jeffery WR (2004) Hedgehog Signalling Controls Eye Degeneration in Blind Cavefish. Nature 431:844–7; Jeffery, W. R. “Adaptive Evolution of Eye Degeneration in the Mexican Blind Cavefish.” Journal of Heredity 96, no. 3 (2005): 185–196. 

3. Bejder, L., and B. K. Hall. “Limbs in Whales and Limblessness in Other Vertebrates: Mechanisms of Evolutionary and Developmental Transformation and Loss.” Evolution and Development 4, no. 6 (2002): 445–58. 

4. Lachapelle, M. Y., and G. Drouin. “Inactivation Dates of the Human and Guinea Pig Vitamin C Genes.” Genetica 139, no. 2 (2011): 199–207.

5. Avise, John C. Inside the Human Genome: A Case for Non-Intelligent Design. New York: Oxford University Press, 2010.   Romano, C. M., F. L. Melo, M. A. Corsini, E. C. Homes, and P. M. Zanotto.  “Demographic Histories of ERV-K in Humans, Chimpanzees and Rhesus Monkeys.” PLoS One 2, no. 10 (2007): e1026. http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0001026. 

6. Max, “Plagiarized Errors and Molecular Genetics,” http://www.talkorigins.org/faqs/molgen.

7. Coyne, Jerry A. “Intelligent Design: The Faith that Dare Not Peak Its Name.” In Intelligent Thought: Science Versus the Intelligent Design Movement, edited by John Brockman, 3–23. New York: Vintage, 2006. 

8. Kricher, John. Galápagos: A Natural History. Princeton, NJ:  Princeton University Press, 2006. 

9. Grant, Peter R., and Rosemary B. Grant. How and Why Species Multiply: The Radiation of Darwin’s Finches. Princeton, NJ: Princeton University Press, 2011. 

10. Sulloway, Frank J. “Why Darwin Rejected Intelligent Design.” In Intelligent Thought: Science Versus the Intelligent Design Movement, edited by John Brockman, 107–25. New York: Vintage, 2006. 

11. Darwin, Charles. “On the action of sea-water on the germination of seeds.” Journal of Proceedings of the Linnean Society of London (Botany). 1 (1857): 130–140.

12. Futuyma, Douglas J. Evolution. 3rd ed. Sundbury, MA: Sinauer Associates, 2013. 

13. Dawkins, Richard. The Selfish Gene. New York: Oxford University Press, 2006.

JIMMY LIN: Currently I’m on faculty at Washington University at St. Louis, where I am a research instructor in the pathology department. Also, a year and a half ago, I founded the Rare Genomics Institute (RGI)—a nonprofit that helps find cures for people with rare diseases.

ER: What qualifies as a “rare disease”?

JL: These are diseases like cystic fibrosis and Huntingdon’s disease—diseases that affect less than 200,000 Americans each year. There are over 7000 different rare diseases, and less than 5% of them have any therapy. Altogether, they affect about 25-30 million people.

This creates what we call a “long tail problem”—it’s hard for a top-down research system to create research programs for all 7000 rare diseases. So instead, we are creating a bottom-up platform from which the patients themselves can create research projects and help fund them. We connect patients with physicians and researchers, customize a research program with top medical universities, design the experiment, and then use an online fundraising platform to fund the study through [mostly] friends and family of the patient.

Basically, we create a “foundation in a box.” By partnering with the Rare Genomics Institute, patients and their friends and families who want to study rare diseases don’t have to go through the hoops of creating their own nonprofit or lab—we do that for them. So, instead of creating 7000 different nonprofits, we create a generalized platform from which studies can be conducted.

ER: Who qualifies for care through the Rare Genomics Institute?

JL: Anyone with a rare disease can come to us. The main thing we’re doing right now is diagnosis. When families come to us, they either don’t know the disease that’s affecting them or their child, or they don’t know the gene that’s wrong.

For instance, if a child had a condition that doctors couldn’t identify, his or her parents might come to us for help. What we’d do then is sequence the genes of the mother, father, and child, and compare them to reference genome to determine what mutations each of the parents have. Depending on what the disease is and what the gene causing it is, we can filter out mutations that don’t mean anything using the parents’ genomes—then, after filtering, we can potentially pinpoint the genes that fit the genetic pattern of the disease. This is the first step.

After that, we are building infrastructure to determine the effect of these changes and a way to help. For example, after looking at the literature, we can perhaps design experiments using cells extracted from the patient; this part of the process is different for every disease. Then, if we can determine that there is, for instance, a pathway missing a specific enzyme, we can try using drugs, a bone marrow transplant, or gene therapy to try to put healthy cells into the child… But there’s a variety of diseases, of course, so there’s a variety of different approaches—and we’re just starting to explore these aspects.

ER: How did RGI get started?

JL: It really started when I was in medical school at Johns Hopkins—there was this boy that came to our clinic to be seen. My research was in cancer genome sequencing, and the family had come to our department looking for answers about what was wrong with their son. At that point, the family was almost hopeless—they had gone to so many doctors, run so many tests—I decided I wanted to try to help children like this. That’s when my friends and I decided to start the Rare Genomics Institute.

Currently, there are about 50 researchers associated with the organization, and we are all volunteers. It’s growing much, much faster and been more amazing than we’ve ever imagined—we’re already making an impact. In May of last year, we were able to discover a new disease using the world’s first crowd-sourced, crowd-funded genome. Working with researchers at Yale, we delineated a disease of which our patient was the first identified.

Right now, we’re in the middle of raising funding and hiring staff to make this organization one that is self-sustaining, and to increase its impact even more.

Excerpts from Michael Hickerson Interview

MH: …you call yourself a doxologist. What’s the full term you used in your Jubilee bio?

JL: Medical and scientific doxologist.

MH: How did you decide on that term and what does it mean to you?

JL: I listen to a bunch of teaching by J.I. Packer , who teaches theology at Regent College and is one of the leading thinkers on these things. Interestingly, before any one of his classes, he says “Theology is for doxology,” and then the whole class sings the Doxology together out loud in class. I thought, “Wow, that is so great,” because everybody sometimes learns theology just for intellectual things [instead of for worship].

That’s not just true for theology, it’s for everything: biology is for doxology; chemistry is for doxology. That’s when I started to think, I should consider myself, first and foremost, as a person who praises God in what I do. And then no longer make “Christian” the adjective, right? “Doxologist” is the noun. But then what kind of doxologist am I? So I call myself a medical and scientist doxologist. I would call someone, for example, in the marketplace, a business doxologist. Or, someone who does art, an artistic doxologist. To really have the noun as our identity, and then our vocation as just a descriptor of how we do that.

MH: That’s a great point. A noun is always stronger than the adjective. So, you want that to be the focus, rather than the add-on.

JL: In our current culture, we’re defined by our jobs. It’s having a vocation. I wanted to shift away from that. I didn’t want to be a doctor first and foremost, or a scientist, but one who praises God. And evidently, within science you don’t want to call yourself a Christian Scientist. That’s another religion, so . . .

MH: [laughs] That’s right. I run into that, as well, when I’m teaching or talking about science to Christians. You always run into that stumbling block.

JL: With “scientific doxologist,” people don’t confuse them. You do have to explain what it means. And that gets in a little story actually, on what it means about vocation. It’s a small lesson — a teaching point when you do talk to people about vocation and calling. That’s why I use it.

MH: I guess my final question would be what spiritual practices help sustain you? What helps you stay in contact with God and keep a good foundation?

JL: First, I am interested in many, many different things. I sort of mix it up in terms of spiritual practices. Besides the fundamentals, of course, of quiet time, devotional reading, and scriptural reading, I do theological study because I have to do that academically. I find a lot of time with God through the spiritual disciplines, such as times of solitude — which is very interesting for someone who is in academics to no longer think about ideas but just to be quiet before God — how silence, time to think by yourself, or sitting in silence is also something you should foster.

In terms of spiritual formation, what you really need is definitely a good community of people. I have a very supportive community at my church. I’m the deacon of devotions, so that of course keeps me on track. It encourages me as I, in my own spiritual walk, encourage other people. Fundamentally, I think for all Christians, whether you are academic or no matter your vocation or calling, being in the Word and prayer are the most important things. Doing that and being spiritually fed is what is important.

DOUG LAUFFENBURGER: It could look like a lot of things. One way to envision what I mean is to put yourself back a hundred years. For instance, in 1913, an electronic computer was unimaginable. But using physics, quantum physics, leading to semiconductors and devices like that, people figured out over the next 20 to 30 years how you could build a machine to do calculations and so forth. And then, of course, all sorts of thing happened…

We’re roughly at that stage with biology, even though it seems like things are more imaginable because—and we don’t have to go strictly century by century here—because we can already guess the way some things might change, whereas in 1913 there was no inkling, really, as to what would happen in the computer revolution.

So, to enumerate some of the things that are conceivable—let’s just start with computers, because we were just there.

There’s a notion that computers get faster and cheaper by making their logic gates smaller, and how you improve a design with physics keeps bumping up against how you make these little units smaller. Well, using biology, the solution seems self-evident—you just line up the pieces of DNA, and if you put the right pieces of DNA in the right places, the resulting parts are so much smaller than the things we can do with physics. You can imagine, even though it’s just a theory now, computers continuing to become many times smaller and cheaper—and be made via environmentally benign manufacturing processes—through biomolecular construction.

Now that’s exciting from one point of view, but from another, it’s not that revolutionary, because you’re just using DNA as a piece of physics. It’s not really biology—it’s merely a biological molecule being used to make better physics.

For a different example, if you think about the way we make things, the way we manufacture plastics, gasoline, energy—we have to do all that using chemistry, and to make that chemistry happen, we have to input a lot of energy—in fact, one of the most costly industries in terms of energy usage is the energy industry. You have to put in so much energy to refine petroleum and things like that. And to make plastics, ceramics—things of that nature—is also very energy intensive, and it’s also where a lot of pollution comes from, because you’re mixing together all these chemicals that really didn’t want to be mixed together. You get what you want, but you get a lot of byproducts, toxins, etc.

Well, people have started to realize that a lot of this work can be redone through the use of biology. You can turn corn into fuel or plastic, and you can make magnetic or electrical storage devices out of biological units (viruses can pattern the crystals, so instead of using mixtures of toxic chemicals, you just pull the viruses with the right properties together). Right on this tabletop, you could make materials that by current manufacturing processes would otherwise cause a great amount of environmental hazard.

As for another exciting development—well, to preface, one of the problematic things about modern agriculture is the necessity of using fertilizers (there are insecticides to be concerned about, too), but fertilizer manufacturing is terrible for the environment. You have to make fertilizer out of ammonia and that’s a horribly polluting and energy-intensive manufacturing process. What you could potentially do, instead, is program into bacteria the genes that take nitrogen out of air, turning it into organic nitrogen then just scatter the bacteria onto the field—and you wouldn’t need to make ammonium using the current very caustic processes.

These are the sorts of things I mean—and we haven’t even touched on medicine, yet. People tend to think about medicinal advances, first, but before you even get to medicine, you can think about energy, manufacturing, materials, and agriculture. In 50 years, we should be able to do things in ways we don’t do them now, that will be cheaper, less toxic, less polluting, more efficient, and so forth.

ER: A lot of people are nervous about the idea of “programming” life. Can you respond to this fear as a Christian?

DL: As a Christian, I would say that God gave humankind dominion over the earth, to do good things—he gave us minds, a passion for understanding how things work, and then he put in this world all these fascinating processes, which, if we figured them out, we could do good things, could feed more people—could feed more people without causing extensive damage to the environment. And cure disease and injury. And the list goes on. I think all that is good, and that God would be pleased that we would be using His creation to live better—I’m not saying more luxuriously, but more happily, contentedly, with each other.

ER: But back to the topic—advances using biology in the next century. You had just mentioned medicine…

DL: So, yes, there’s also medicine. Now, obviously, in thinking about this, the use of stem cells comes to immediately the fore. There are a lot of diseases out there that you really do need to correct using cellular processes. Right now, we try to make these corrections through chemistry. For instance, we give you a pill, and that pill should interfere with something that’s going wrong in your body—and yet it’s really never adequate to just interfere with something that goes wrong in the body, because you don’t really set it right just by getting in the way of it.

The opportunity with stem cells is that you can say, “I’ll replace the cells in the body that are doing something wrong with cells that are actually doing it right again.” If you program cells to be neurons, heart cells, or bone cells, you can regenerate properly functioning physiology. Rather than, say, replacing a hip with a metal part, you could regenerate the bone, itself, or you could regenerate neurons in Alzheimer’s patients. Never in the past has medicine been able to regenerate a proper physiology; it’s only tried to replace it with an inadequate surrogate, or minimize how much damage a disease is doing. With the use of stem cells, you can actually imagine returning the body to its proper physiology.

A different use of stem cells is to generate human tissue in the laboratory for better studies of human physiology and pathology and improved testing of drug effectiveness and toxicity.  This will be a major advance over animal models, because of the significant disparities between animal physiology and human physiology.

A key point to emphasize is that there are different kinds of stem cells, which involve big differences in potential concerns. For Christians, clearly, stem cells derived from embryos present a tremendous ethical issue. Fortunately, a good proportion of stem cell technologies can be pursued using stem cells from adult tissue. These cells can be stimulated to develop into certain tissue-specific physiological behavior, or can now even be “re-programmed” to become quite similar to the more broadly flexible stem cells derived from embryos but now not requiring the embryonic source. Happily, the days of reliance on embryo-derived stem cells appear to be over for purposes of beneficial technologies.

We also should consider genomic medicine, and what’s attractive about that field is that with the way we do medicine now, which is chemistry-based—say you have a disease, and we might give you a pill to correct it—well, the biggest problem with that is that while I think this pill will help ameliorate your condition, maybe it won’t. Maybe that drug only works in ten percent of the patients and not ninety percent.

For example, consider cancer. You’ve got a particular kind of cancer, and we prescribe a certain treatment… well, hopefully you’re among the lucky ten percent, and you’ll be in much better shape in two or three years. If you’re not, then we’ve wasted your time. In fact, we’ve probably hurt you rather than helped you, because we’re using chemistry to interfere with things, and even though we might be reducing the damage of some things, we’re probably causing toxicity elsewhere in the system, because that same chemistry is also interfering over there.

So the value of genomic medicine is to get enough information about you through sequencing your genome that we can say, “Ah, for you this particular pill is not a good idea; it will actually do more damage than good. But for your brother, it’s likely to work, and the ratio of benefit to harm is much better.” This is the reason genomic medicine is more imminent—it’s what’s closest on the horizon to being realized—because we can use the same drugs we have now, we’ll just be using them more effectively. At the moment, we can sequence genomes, and we do have these treatments that help, and it’s just a matter of matching up these two technologies.

Now, on the other hand, when you think about genome sequencing, you can find out all sorts of things, and you have to decide, “What if I learn something negative?”

EDITOR’S NOTE: Join us next week as we continue the conversation about genomic medicine, bioengineering, and being a Christian in science.

About a year ago I posted the first article in this series, asking whether recent advances in genomics made any difference to the Judeo-Christian notion of humanity being made in the 'image of God'. That article focused on DNA sequencing data from our closest relatives. This article will focus on the issue of genetic determinism.

Theologians have spent many centuries mining the rich vein of the 'image of God' metaphor. Central to the idea is humanity with spiritual capabilities and responsibilities, equipped for moral decision-making and a relationally rich life in community. Historically, the idea has contributed to the conviction that each human individual has an absolute value, independent of their ethnicity, educational level, health status or income.

Do recent advances in genomics threaten or support such a view of humankind, or are they just neutral? Irrespective of one's belief in God, or not, this is of more than passing interest. Imagine the poor person wrestling for years with the great questions of life and finally deciding to become an atheist, only to then be informed that a cognitive bias derived from his particular set of genetic variants made that decision pretty much inevitable anyway. Such news might be equally unsettling for the person who had just struggled to faith following years of agnosticism. Our deepest human feelings are closely connected with the idea that we choose our own path through life.

The flourishing of genomics in the early part of the 21st century has certainly conveyed the message to many that one's destiny is written into one's genome. Whereas scientists are generally scrupulously careful not to give the impression that there is any such entity as a "gene for" some human trait, by the time the latest discovery appears in the media, such caution is often thrown to the winds. The past year has seen the trumpeting of a "gene for happiness," a "kindness gene" and a "believer gene." It is not even a question of education, but "genes are to decide" if you are a "caring person." Genetic testing websites assure us that "your genes are a road-map to better health," and we all know that road-maps are fixed. Small wonder that there is a creeping genetic fatalism around that subverts the idea of personal responsibility.

Fatalism in itself impacts on human behavior. Studies have shown that subjects exposed to the writings of authority figures doubting free-will are then more likely to cheat. Conversely, workers convinced of the reality of free-will are rated higher in the work-place than those whose beliefs tend more towards determinism.

The reality is that recent genetics research has continued to move steadily away from any notion of genetic fatalism, highlighting the sheer complexity of the genome, and providing some fascinating examples of the ways in which our choices impact upon our own genomes. There is no gene "for" any complex human trait because in fact genes encode proteins or other types of information-containing molecules, and thousands of genes collaborate together during human development in interaction with the environment to generate the unique human individual that each person represents. Those requiring an introduction for the non-specialist are referred to "The Language of Genetics."

Epigenetics adds further layers of variation and complexity. This refers to the chemical modifications of the DNA that cause genes to be switched on or off. It is such epigenetic modifications that generate the 220 specialized tissues of our bodies. Such acquired changes can even be inherited across several generations, certainly in plants and animals, and maybe in humans as well. In choosing to smoke, drink in excess, or take drugs, we also choose to modify our genomes.

So it turns out that even identical twins are not really genetically identical, developing different profiles of epigenetic modification as they go through life. This no doubt contributes to the otherwise surprising result that the age of death of identical twins, who share identical genomes, is comparable with that observed in non-identical twins, whose genomes are as different from each other as any two sibs. In one study of 184 pairs of twins in Spain, the difference in the age of death between the identical twin pairs was seven years on average, but such averages hide the fact that the age differences ranged from a couple of weeks to eighteen years. In the case of the non-identical twins, the difference in age at time of death was nine years, and the range was three to nineteen years. So there was really not that much in it.

What would happen if there was a genetic marker that identified nearly everyone in prison, marking them out as genetically distinct from half the world's population? What would that do to our ideas about genetic fatalism and convictions about moral responsibility? As it happens that marker already exists. Out of 131 countries worldwide, an average of 96 percent of the prisoners are male and, in this case, no complicated genetic studies are needed to know that the genetic marker that identifies this population is the Y chromosome. So universal is the correlation between the Y chromosome and criminality that we can safely say that no other genetic correlation will ever be found between a variant genome and criminality that surpasses this one. And yet we still hold nearly all males responsible for their criminal actions and put them in jail as soon as they're convicted. Furthermore, we note that most people who possess a Y chromosome go through life without committing a crime. So having a Y chromosome, with its unique set of genes, does not "determine" human criminality, although clearly we cannot go to the opposite extreme and say that it is completely irrelevant for patterns of human behavior.

The point in citing such examples is not to suggest that our genomes have nothing to do with our lives. They certainly do, not least in their significant contributions to our personality differences. The point rather is that the latest results in genetics provide no grounds for fatalism, instead highlighting the richness and diversity of the human population, and our own moral responsibilities, including the challenge to be good stewards of our genomes.

An argument for the existence of God this is not. But for those of us whose world-view is shaped by the conviction that we humanity are made in God's image, it is good to know that the latest genetics is consistent with such a perspective.

Behe and IC

Since we have previously explored Behe’s idea of irreducible complexity in an entire series, we will not revisit it here in great detail. It is important, however, to reemphasize how Behe defines irreducible complexity (IC). As we noted in the first part of that series, Behe frames his ideas on IC as a counter to Darwin’s ideas of gradualism.

For Behe, the argument for IC is a critique of gradual evolutionary processes, of the kind that Darwin saw as necessary for his theory to hold. When Behe introduces and defines IC in his book Darwin’s Black Box, he has a key quote from Darwin on gradualism explicitly in view:

Darwin knew that his theory of gradual evolution by natural selection carried a heavy burden: "If it could be demonstrated that any complex organ existed which could not possibly have been formed by numerous, successive, slight modifications, my theory would absolutely break down."

It is safe to say the most of the scientific skepticism about Darwinism in the past century has centered on this requirement… critics of Darwin have suspected that his criterion of failure had been met. But how can we be confident? What type of biological system could not be formed by “numerous, successive, slight modifications”?

Well, for starters, a system that is irreducibly complex. By irreducibly complex I mean a single system composed of several well-matched, interacting parts that contribute to the basic function, wherein the removal of any one of the parts causes the system to effectively cease functioning. An irreducibly complex system cannot be produced directly (that is, by continuously improving the initial function, which continues to work by the same mechanism) by slight, successive modifications of a precursor system, because any precursor to an irreducibly complex system that is missing a part is by definition nonfunctional. An irreducibly complex biological system, if there is such a thing, would be a powerful challenge to Darwinian evolution.

(Darwin’s Black Box, p. 39)

The definition of an IC system is thus straightforward: it is a matched group of components, where all the components are necessary for the function of the system. The necessity of each component can be demonstrated by attempting to remove it – if the system no longer works if even one component is removed, it is by definition IC.

Behe and exaptation

The standard response to Behe’s argument from IC is to discuss the evolutionary concept of exaptation: that new systems and functions are cobbled together from components that have functional roles in other systems already present in the cell. Behe discusses, and ultimately dismisses this idea in Darwin’s Black Box as follows:

In Chapter 2 I noted that one couldn’t take specialized parts of other complex systems (such as the spring from a grandfather clock) and use them directly as specialized parts of a second irreducible system (like a mousetrap) unless the parts were first extensively modified. Analogous parts playing roles in other systems cannot relieve the irreducible complexity of a new system; the focus simply shifts from “making” the components to “modifying” them. In either case, there is no new function unless an intelligent agent guides the setup.

So for Behe, two points are clear: parts selected for function in one system cannot be exapted for use in other systems since they would require too many modifications; and the emergence of a new function is the indication that an intelligent agent is guiding the process.

Behe has responded to my previous posts to claim that the tandem duplication event that brought about the Cit+ actualization event should not be considered a gain-of-FCT mutation under his criteria:

The gene duplication which brought an oxygen-tolerant promoter near to the citT gene did not make any new functional element. Rather, it simply duplicated existing features. The two FCTs comprising the oxygen tolerant citrate transporter locus -- the promoter and the gene -- were functional before the duplication and functional after. I had written in my review that one type of mutation that could be categorized as a gain-of-FCT was gene duplication with subsequent sequence modification, to allow the gene to specialize in some task. Venema thinks the mutation observed by Lenski is such an event. He has overlooked the fact that there was no subsequent sequence modification; a segment of DNA simply tandemly duplicated, bringing together two pre-existing FCTs.

As an aside, quibbling over whether this mutation constitutes a “genuine gain-of-FCT” mutation is not my purpose here, since the definition is Behe’s to define, and I am not aware of anyone else in the scientific literature who uses Behe’s definitions. That said, I consider it passing strange to claim that a series of events that produced a gene that has a new sequence and functional properties distinct from either of its component parts does not constitute the production of a new “functional coded element.” If nothing else, it is a functional coded element that has not previously existed, cobbled together from parts of other functional coded elements, displaying new, adaptive properties. If according to Behe’s definition that’s not “new” or a “gain” then I guess it’s not, but that seems to me to torture the words “new” and “gain” beyond recognition. But I digress.

The important point for our purposes, however, lies elsewhere. Note carefully how Behe describes the Cit+ actualization event. By dividing the new aerobic citrate transporter gene into two previously existing FCTs, Behe is describing an exaptation event. The one FCT (the aerobic promoter) starts off as a necessary component of a gene transcribed when oxygen is present. As such it is under selection for that function, which has nothing to do with expressing a citrate transporter. The second FCT (the citrate transporter amino acid coding sequence) is under selection to be a citrate transporter, which has nothing to do with the function of the gene the promoter comes from. The Cit+ actualization event, then, exapts these two FCTs by placing them together to create a new function (which Behe does not mention).

And here’s the kicker: the new system (expression of the citrate transporter when oxygen is present) requires both FCTs in order to work. It has become a system of “well matched, interacting parts that contribute to the basic function” (i.e. transporting citrate in the presence of oxygen) “wherein the removal of any one of the parts causes the system to effectively cease functioning.”

In other words, it is a new IC system – a small and relatively simple system, yes, but nonetheless IC. Now, I’m fairly sure that Behe would not define this system as IC, since the documentation of an IC system evolving would seriously undermine his thesis. I am interested, however, in how he will handle this development, on two fronts. First, he would need to explain specifically why two exapted FCTs that are required together for a basic function does not constitute an IC system (if indeed he wishes to preserve his definition). Secondly, given that he allows for exaptation in this case, he needs to explain how exaptation is not a threat to IC in general. In Darwin’s Black Box he disallows exaptation altogether, but that option is no longer on the table.

In the next post in this series, we’ll continue to explore the evidence for exaptation as a means to build new FCTs, and go on to examine the implications of this evidence for Douglas Axe’s proposed limit to evolutionary mechanisms.

For further reading:

Blount, Z.D., Barrick, J.E., Davidson, C.J. and Lenski, R.E. (2012). Genomic analysis of a key innovation in an experimental Escherichia coli population. Nature 489; 513- 518.

Michael J. Behe, Darwin’s Black Box: The Search for the Limits of Darwinism (New York: Free Press, 2006).

Michael J. Behe, The Edge of Evolution: The Search for the Limits of Darwinism (New York: Free Press, 2007).

Michael J. Behe (2010). Experimental evolution, loss-of-function mutations, and “The first rule of adaptive evolution”. The Quarterly Review of Biology 85(4); 419-445.

With the complete genome sequence in hand, we knew the sequence and location of our genes, but what we didn’t know was how all those genes are regulated: how do the trillions of cells in our bodies know when to turn on or off all those genes? How do the hundreds of distinct cell types develop and function together, when they are all running on the same DNA “operating system?”

That’s where the ENCODE (short for Encyclopedia of DNA Elements) project comes in. Launched in September 2003, shortly after the announced completion of the Human Genome Project, the goal of the ENCODE project is “to build a comprehensive parts list of functional elements in the human genome, including elements that act at the protein and RNA levels, and regulatory elements that control cells and circumstances in which a gene is active.” In other words, the project seeks to understand how the genome “works.”

Early this month, researchers from ENCODE released more than thirty papers presenting their findings. During a Science magazine online chat, the project’s data coordinator, Ewan Birney, explained the outcome:

The ENCODE project aimed to start our understanding of how the human genome works. We know that (nearly) all the information that determines a human is in the genome, as we all start off as single cell with this DNA. However, we had a patchy understanding of how it works, in particular away from protein coding genes.

To work out how the genome works, we used the fact there are many tiny machines (proteins and RNA - RNA is very like DNA) in each of our cells which know how to "read" parts of the genome. By monitoring where these little molecular machines are on the genome, or how parts of the DNA are copied into RNA (there are quite a few different types of RNA as well), we start to gain some insight into the genome.

We did many such experiments, across different cell types (eg, one cell type was very similar to a liver cell type; another was very similar to a white blood cell). This way not only can we see what is similar, we can also see differences between these cell types.

There is a lot more to get to know and understand here - this is definitely closer to the start than the end. But it is a substantial amount of data, and analysis, to start on this journey.

According to the abstract of one of the lead papers from Nature, this extraordinary glut of data “enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions.” Only 2% of the genome codes for proteins, but 80% or more has some biochemical function. As a Science news article put it, these 30 papers “sound the death knell for the idea that our DNA is mostly littered with useless bases.”

The pro-Intelligent Design organization The Discovery Institute has heralded the discovery as the “demise of junk DNA.” Casey Luskin writes for their blog Evolution News:

Let's simply observe that it provides a stunning vindication of the prediction of intelligent design that the genome will turn out to have mass functionality for so-called "junk" DNA. ENCODE researchers use words like "surprising" or "unprecedented." They talk about of how "human DNA is a lot more active than we expected." But under an intelligent design paradigm, none of this is surprising. In fact, it is exactly what ID predicted.

The extent to which the ENCODE project been able to identify function has been surprising—even exhilarating—though scientists have for some time been getting glimpses of the many ways in which segments of DNA can be “active.” Even in 1970 biologists knew that some non-coding DNA had function, and by 2003 there was a large body of work demonstrating that many non-coding elements acted as promoters, enhancers, insulators, and so on. Indeed, in recent years many have come to appreciate the fact that “junk” was never really an appropriate metaphor in the first place. Still, because sequencing of multiple genomes has shed such extraordinary light on key evolutionary mechanisms, many geneticists have focused on function primarily in terms of which regions do or do not contribute to the evolutionary fitness of their host, rather than whether they were merely "doing something" biochemically. What the impressive ENCODE project has done is open a treasure trove of new information that can only accelerate the pace at which researchers are able to explore the incredible subtlety and complexity of DNA, and refine the very concept of “functionality.”

So with all this in mind, is ENCODE a stunning victory for ID, as Luskin believes? Bryan College biologist Todd Wood thinks not. He writes, “I don't think that function equates to design, nor do I think that design requires or predicts function. They're not the same thing… my understanding of function does not require me to hypothesize God (or an anonymous designer, if you must) as the proximal cause.”

We agree. Indeed we would go on to say that evolution and design are not mutually exclusive. So while finding function is not sufficient to prove design, recognizing that function has arisen by way of evolution does not indicate that God was not at work. We at BioLogos believe God providentially works out his purposes—his designs—through the elegant processes of evolution, not in opposition to them.

Amazing as the new data are, it only strengthens and enhances our evidence for evolution. While much of the genome is “doing something” biochemically, it is still likely that the majority of the sequence is evolutionarily neutral (Senior Fellow Dennis Venema discusses the evidence for this “neutrality” in a post on our site, including a striking comparison between 29 different mammal genomes and the human genome). In fact, another ENCODE researcher participating in the Science magazine chat, John A. Stamatoyannopoulos of the University of Washington School of Medicine, thinks the findings align beautifully with evolutionary theory:

ENCODE's data provide a unique and powerful window through which to view evolutionary change. We can see those changes directly by lining up the genome sequences of many different organisms -- these line-ups have revealed millions of regions where all the genomes agree, indicating sequences that have been specially preserved by evolution while others have decayed away (ie freely changed their letter codes). We now see that a large proportion of these 'conserved' regions are lighted up by ENCODE annotations, indicating that they are marking spots in the genome that contain important instructions for cell function.

We’ve discussed “junk” DNA previously, including a multi-part series by Dennis Venema, and we’ve received many emails over the past few days asking for our comments on the ENCODE findings. On Monday and Tuesday, Dr. Venema will begin to offer his own thoughts on ENCODE.

A special thanks goes to Darrel Falk, Mark Sprinkle, Kathryn Applegate, Dennis Venema, and Tom Burnett for their contributions to this post.

The Denisovans, an extinct hominid group that interbred with modern humans, made the news again lately with the publication of a more detailed study of their genome. One of the many interesting findings was that the Denisovans share the same chromosome 2 fusion that modern humans have. In this post, I review what we know about the origins of human chromosome 2, and then discuss the new Denisovan findings and their implications.

The origins of human chromosome 2: a brief review

Though I have discussed the evidence for a fusion event leading to human chromosome 2 before, perhaps a brief review of the evidence is in order. The human genome is made up of 23 pairs of chromosomes (for a total of 46 chromosomes). This makes us something of an oddity among living great apes, all the rest of whom have 24 pairs of chromosomes (for a total of 48). Given that there are many independent lines of evidence that support the conclusion that we share a common ancestor with other great apes, this poses something of a conundrum: how is it that our species arrived at this specific chromosome number? If we were to represent this “problem” on a phylogeny, or tree of relatedness, it would look something like this (not to scale):

Our closest living relatives, chimpanzees and bonobos, both have 48 chromosomes, as do all other great apes such as gorillas and orangutans. This pattern has one of two explanations, one of which is much more likely than the other. Either the common ancestor to these species had 48 chromosomes, and there was an event that reduced that number to 46 specifically on the lineage leading to humans (option A), or the common ancestor species had 46 chromosomes, and there were independent, repeated events that increased chromosome number in all other great ape species (option B). We can compare these options by placing the required event(s) on the phylogeny (again, not to scale):

It should be obvious that the option that requires the fewest events is the more likely one – in this case option A with an event that reduces chromosome number in the lineage leading to humans. The other option, that of repeated, independent events to increase chromosome number, remains a formal, but unlikely, possibility. Events that reduce chromosome number are not frequent occurrences, so Option A is more likely than Option B.

We can also find further support for Option A, because it predicts a specific type of event, namely one that reduces chromosome number. Since loss of a large amount of chromosomal material is almost always detrimental, we need an event that reduces chromosome number without losing information. One way for this to happen is for two chromosomes to fuse together and become one. Initially, this event would produce an individual with 47 chromosomes, where two different chromosomes get stuck together. Contrary to what is often assumed, this individual would be fertile and able to interbreed with the others in his or her population (who continue to have 48 chromosomes). In a small population, over time, two relatives who both have one copy of the fusion chromosome may mate and produce some progeny with two copies of the fused chromosome, or the first individuals with 46 chromosomes. Since either a 48-pair set or a 46-pair set is preferable for ease of cell division, this population will either eventually get rid of the fusion variant (the most likely outcome), or by chance will switch over completely to the “new” form, with everyone bearing 46 chromosome pairs. While not overly likely, this type of event is not especially rare in mammals, and we have observed this sort of thing happening within recorded human history in other species. Some mammalian species even maintain distinct populations in the wild with differing chromosome numbers due to fusions, and these populations retain the ability to interbreed.

Further evidence for a fusion event in the lineage leading to modern humans comes from comparing synteny, or gene locations and orders on chromosomes within modern great apes – an issue we have discussed here before. In brief, what we see in human chromosome 2 is exactly what we would predict for a fusion event. When compared to other great apes, we see the genes on human chromosome 2 match up, in order, with two smaller ape chromosomes. We also see that sequences used at the tips of chromosomes are present at the proposed fusion site, and that human chromosome 2 has not one but two sites for the cell cytoskeleton to attach to for cell division – but that one of the sites is mutated and not functional, though it lines up precisely with the location of this site on the appropriate ape chromosome. Together, this evidence consistently supports both common ancestry for humans and great apes, and specifically that the difference we see in our chromosome numbers arose due to a single fusion event. I briefly discussed this evidence in my last post where I describe how I teach some of this material and the compelling impact it has on students exploring the evolution question for the first time.

Enter the Denisovans

With that as background, we are now prepared to appreciate a new finding that comes from genomics work done on the Denisovan hominids, an archaic species that is more closely related to Neanderthals than to us, but that nonetheless interbred with some anatomically modern humans as they migrated out of Africa and populated the globe. (For those not familiar with the Denisovans, or the evidence for our interbreeding with them, both Darrel Falk and I have written on this previously, here and here). Recently, a more detailed understanding of the Denisovan genome was published, and nested in the new information is the discovery that the Denisovans share the 46 chromosome set with the same fusion that we have. This strongly supports the hypothesis that the fusion event predates the separation of our species. If we were to represent this on a phylogeny, we can now place this event with more accuracy than before (as before, the phylogeny is not to scale):

Despite this new information, one obvious question remains. Did the Neanderthals also have the 46-pair set? From looking at the phylogeny above, we can see that the most likely answer is that they did, since the fact that the Denisovans had it strongly implies that the last common ancestor of humans and Neanderthals / Denisovans had it as well, and the Neanderthal-Denisovan split comes later. While the Denisovan DNA samples are of high enough quality to make this assessment, we do not yet have Neanderthal DNA of high enough quality to do the same analysis with current methods (though one additional feature of the new work on the Denisovan genome is developing more sensitive DNA sequencing techniques that may resolve this question in the future).

In other words, this fusion seems to be an ancient one, predating our species by several hundred thousand years. Present estimates of the last common ancestor between humans and Neanderthals / Denisovans range at about 800,000 years ago.

Implications for understanding our “becoming human”

The main implication from this work is that it places the fusion event well before the advent of our species. I’ve often chatted informally with Christians about evolution, and at times some have thought that this fusion event was what “started” our species, or made our species unable to interbreed with other groups. Some have even suggested that perhaps the fusion event was what produced the first human (i.e. Adam).

Note that thinking this way suggests a misunderstanding of how chromosome fusions occur and what effect they have on their hosts. A fusion does not precipitate a speciation event, but rather the individual with the fusion remains a part of his or her population, and able to interbreed, even if with reduced fertility. Also, there is no necessary biological effect or change that the fusion produces on the appearance of the organism. These misunderstandings aside, however,what this new evidence shows is that this fusion event took place long before modern humans arose at around 200,000 years ago. Indeed, the 800,000 years ago date for the last human - Denisovan common ancestor means that this is the most recent date possible for the fusion. While it is an interesting piece of our evolutionary history, it doesn’t seem to have much to do with how we came to acquire the traits that set us apart from, and ultimately outcompete, other similar species.

Recently, an elegant and powerful experiment was done to further investigate a question of interest to many evangelicals: how is it that we are so different from our closest biological relative (the chimpanzee) when our DNA is so very similar? Even when using estimates that maximize the differences, our genomes are 95% identical. The conclusion, that I have discussed here in the past is that a dispersed set of numerous small changes can have large effects on the form and function of an organism. Of course, small changes are what evolution specializes in: tinkering here and there, one mutation at a time, as we have directly observed in laboratory experiments. Before we discuss how this pivotal new study was done, however, a brief review of how genes work is in order.

Review: gene structure and function

If you’ve been following the ongoing Understanding Evolution series here at BioLogos, you will recall that we discussed gene structure and function not long ago, in the context of discussing non-functional DNA sequences (so-called “junk DNA”):

Genes have a typical structure (obviously simplified here somewhat). First off, there is the actual DNA sequence that specifies the protein product sequence (the so-called “coding sequence”, shown in blue). This sequence is usually broken up into segments in mammalian genes, and these sequences are spliced together when the DNA sequence of the gene is transcribed into a “working copy” called mRNA – a short duplicate of the code that can be used by the cell’s machinery to actually build the specified protein.

In addition to the actual coding sequences, other sequences are needed to tell the cell when and where certain genes should be transcribed into mRNA. Every cell in an organism has the same genes in their chromosomes, but not all are transcribed. Using different genes in different combinations is what makes cells take on distinct roles – for example, cells in your small intestine need different genes (for absorption of nutrients) than do cells of the immune system (for fighting off pathogens). Regulatory sequences make sure any given cell type has the right genes transcribed and made into protein products. Some of these sequences are part of the mRNA transcript (shown in red), and others are not transcribed but only part of the chromosomal DNA sequence (such as the “promoter” region that directs the enzymes responsible for making the mRNA transcript (shown in blue).

With this background in mind, we can now extend our understanding slightly further. DNA in cells is “packaged up” when not in use by winding it around a class of proteins called histones. This packaging keeps the DNA in a compact form, and it is useful in helping cells prevent genes they don’t need from being transcribed. For any given chromosome - which is one long strand of DNA – some regions will be packed away (and the genes there not transcribed), while other regions are unpacked (less tightly associated with histones) with the genes there actively undergoing transcription. The open regions allow for transcription because enzymes and other proteins needed for the process can gain access to the DNA there.

Comparing gene transcription across species at the genomic level

Because of the overwhelming similarity between the human and chimpanzee genomes (and the even greater similarity when examining only their protein-coding regions) it has long been hypothesized that changes in “where and when” genes are transcribed will be a major player in what makes our two species different (in contrast to the idea that we are different because of the relatively tiny changes in the coding regions of our genes). From an evolutionary point of view, there are a few ways to explore how differences in gene transcription arise once species go their separate ways, such as when our ancestors parted ways with our last common ancestor with chimps around 4-6 million years ago. The main idea is to compare the same cell type in both species: human skin cells versus chimp skin cells, for example. Determining what specific genes are transcribed (or not) in human cells and comparing the results to chimpanzee cells gives us an idea of how gene transcription differences arose in the two lineages since they last shared a common ancestor. The challenge, up until now, is that there was no easy way to indentify the changes in regulatory DNA that led to those differences in transcription. The problem arises because of the overwhelming similarities between our genomes: changes in transcription due to changes in DNA sequence are hard to find simply by looking for sequence differences, since in most cases the differences will be very small. There are also many small differences between our genomes that have no effect on gene transcription, so we cannot simply look for any difference at all. What we need is a way to identify which small changes led to differences in gene transcription.

Old hypotheses, new technology

Back in 2008, a method for addressing this issue was devised. As we have seen, DNA undergoing transcription is “unpacked” and accessible to enzymes. Researchers have long known about a certain enzyme, called DNAse I, that can cut exposed DNA but leave histone-packaged DNA alone. This means that DNA from any given cell type can be cut using this enzyme specifically at “DNAse I hypersensitive sites” (DHS’s) where regulatory DNA is unpackaged and a nearby gene is being transcribed. While this technique is decades old, what is new is a way to then go on to sequence the DNA next to each of these sites. This requires what is known as “next-generation” or “deep” DNA sequencing methods that can use a linker sequence to attach to the DNAse I cut sites and then amplify and sequence individual DNA fragments attached to the linker. Since we have the entire genome sequence of humans and chimps it is then trivial to take the sequencing results and map them to either genome. The results are a detailed map of what chromosome regions are unpacked and regulating transcription in each cell type. These maps can then be compared with related species across entire genomes.

It was only a matter of time before these powerful methods were applied to the human-chimp question, and the first results became available last month. The research group was of course interested in differences between the two species, and the results are fascinating. The researchers looked at several different cell types, and found similar results in all cases. The results for any given gene fall into one of several categories when compared to the human-chimp (H-C) last common ancestor:

• No differences in regulatory DNA relative to the H-C last common ancestor (1259 genes)
• Gain of regulatory DNA in humans relative to the H-C last common ancestor (836 genes)
• Loss of regulatory DNA in humans relative to the H-C last common ancestor (286 genes)
• Gain of regulatory DNA in chimpanzees relative to the H-C last common ancestor (676 genes)
• Loss of regulatory DNA in chimpanzees relative to the last common ancestor (211 genes)

While it was not surprising to find a significant percentage of unchanged genes, it was interesting to note the large percentage of differences in regulatory DNA, despite the overwhelming genomic similarity between the two species. Small changes had a large impact on gene regulation. The researchers went on to examine the new regulatory regions they had identified, and found that they showed evidence of being under natural selection. These mutations had not only brought change, but provided an advantage to their hosts.

These results underscore a few important points:

• Species become different because differences accumulate in both lineages once a common ancestral population splits into two. The differences we see in modern species are due to changes both species have accumulated over time.
• Tweaking the regulation of numerous genes appears to be a widespread mechanism for generating evolutionary novelty. Both gaining and losing regulatory sequences is common.
• These gains or losses in regulatory DNA require only very small changes at the DNA sequence level, but they can have profound impacts on how genes are transcribed.
• These changes appear to be widespread in genomes, and able to accrue in short evolutionary timescales.
• Small changes are exactly the sort of thing that evolution is known to be able to accomplish easily, one mutation at a time.
• These small changes bear the marks of natural selection, indicating that they were selected for as they arose.
• Anyone who wishes to call these differences “insignificant” will have to contend with the observation that the biological differences we observe between humans and chimpanzees are significant.
• Small, incremental changes at the genomic level fit nicely with the fossil evidence for human evolution, which, though fragmentary, indicates gradual changes in skeletal morphology over the same timescale.

Of course, this study is just the beginning, and future studies are sure to examine and compare additional cell types found in humans and our evolutionary cousins. These results have already added to the troubles of antievolutionary groups that wish to portray the differences between us as too great for evolutionary mechanisms to bridge. I suspect these troubles will only worsen in the coming years as these new techniques come into their own.

For further reading:

Shibata Y, Sheffield NC, Fedrigo O, Babbitt CC, Wortham M, et al. (2012). Extensive Evolutionary Changes in Regulatory Element Activity during Human Origins Are Associated with Altered Gene Expression and Positive Selection. PLoS Genetics 8(6): e1002789. doi:10.1371/journal.pgen.1002789

http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1002789

In the last post in this series, we introduced a paper by Chen and colleagues that sought to identify new genes in various Drosophila (fruit fly) species. The youngest (i.e. the most recently evolved) gene they found is one specific to Drosophila melanogaster, the species of fruit fly beloved by geneticists as a model organism. The gene is named “p24-2” (not the most imaginative name, but it serves its purpose) and the gene it is duplicated from is called “Éclair”. The Éclair gene is found in a number of Drosophila species. A simplified “family tree” of three Drosophila species (D. melanogaster, D. simulans and D. erecta) is shown below. The duplication event that generated the p24-2 gene happened within the lineage leading to D. melanogaster, but after D. melanogaster and D. simulans separated as distinct species:

Since the entire genomes of these species are now sequenced and available online, it is possible to look at the chromosome region where the Éclair gene is found in all three. By looking at this region in D. melanogaster, we see that the brand-new p24-2 gene is almost right next door to its “parent” gene, Éclair. Below is a screen shot taken when looking at this region using a Drosophila “genome browser” that is freely available online. The red arrow indicates the Éclair gene, and we can see p24-2 is just one gene over, and seems to be nested within another gene called “Unc-115b”. The green arrows are pointing to two different “versions” of how p24-2 is made into an mRNA working copy. The Unc-115b gene (blue arrow) has five different mRNA versions. (One of the p24-2 mRNA versions has a lot of Unc-115b sequence that is not used when the p24-2 protein is made).

(Click Image to Enlarge)

Finding a duplicated gene next door to the sequence it is copied from is pretty common in genomes – when chromosomes are copied or recombined during cell division, side-by-side copies of parts of chromosomes show up every now and then. It’s also not surprising to see a new gene cobbled together with another gene. In this case, Unc-115b and p24-2 are overlapping but separate functional entities: they each have their own protein sequences, but each includes the code of the other as a sequence that does not actually translate into protein. The details of how this “cobbling” happens aren’t important for this discussion, other than to note that the mechanisms are known and not rare. In the chart above, then, the orange sections indicate the active parts of the transcribed sequence, while the gray are sections that are included in the RNA molecule, but do not get used directly to code for the new protein.

When we look at this same chromosome region in D. simulans and D. erecta, however, p24-2 is missing. Éclair and Unc-115b are there, but p24-2 is not, since it arose after D. melanogaster separated from its common ancestors with the other species. (Note: this entire region is a mirror image in D. simulans and D. erecta when compared to D. melanogaster due to a large scale chromosome inversion that covers this whole area. So, while it looks “backwards” compared to the image above, that is not surprising, it’s expected):

(Click Image to Enlarge)

So, with the p24-2 gene in D. melanogaster, we have a bona-fide, recent gene duplication event. This gene is brand new, evolutionarily speaking (less than 3 million years old, given the calculated speciation times of D. melanogaster and D. simulans). Not only is it brand new, it is also essential for survival in D. melanogaster: if you remove it, the fly dies. Obviously, since every other Drosophila species lacks p24-2, this gene is not essential for survival for any other species. It’s new, and now it’s necessary.

Do new, essential genes refute the Intelligent Design (ID) argument from Irreducible Complexity (IC)?

So far, nothing we have discussed explicitly threatens the ID argument from IC, though it does threaten the ID argument that new information cannot arise through evolution, a topic we have discussed in detail before. Michael Behe, the main ID proponent of the argument from IC, has commented on this research by Chen and colleagues (thanks to commenter “Bilbo” for pointing this out). Behe’s rejoinder was to a blog post by biologist and atheist blogger Jerry Coyne, who used the paper by Chen and colleagues to attack Behe’s ideas. Since Behe’s reply deals with his understanding of how gene duplication relates to his argument from IC, I will quote it here at length:

I have never stated, nor do I think, that gene duplication and diversification cannot happen by Darwinian mechanisms, or that “they play almost no role at all” in the unfolding of life. (As a matter of fact, I discussed several examples of that in my 2007 book The Edge of Evolution. That would be silly — why would anyone with knowledge of basic biochemical mechanisms deny that, say, the two gamma-globin coding regions on human chromosome 11 resulted from the duplication of a single gamma-globin gene and then the alteration of a single codon? What I don’t think can happen is that duplication/ divergence by Darwinian mechanisms can build new, complex interactive molecular machines or pathways. Assuming (since he is in fact critiquing them) Professor Coyne has been attentive to my arguments, one background assumption that he may have left unexpressed is that he thinks the newer duplicated genes discovered by Professor Long’s excellent work represent such complex entities, or parts of them.

There is no reason to think so. A gene can duplicate and diversify without building a new machine or network, or even changing function much. The above example of the two gamma-globin genes shows that duplication does not necessarily result in change in function. The examples of delta- and epsilon-globin, which, like gamma-globin, presumably also resulted from the duplication of an ancestral beta-like globin gene, show that sequence can diversify further, but function remain very similar. Even myoglobin, which shares rather little sequence homology with the other globins, has not diverged much in biochemical function.

In his recent work Professor Long discovered that many of the new genes were essential for the viability of the organism — without the gene product, the fruitflies would die before maturity. Perhaps Professor Coyne thinks that that means the genes necessarily are parts of complex systems, or at least do something fundamentally new. Again, however, there is no reason to think so. The notion of “essential” genes is at best ambiguous. We know of examples of proteins that surely appear necessary, but whose genes are dispensable. The classic example is myoglobin. It is also easy to conceive of a simple route to an “essential” duplicate gene that does little new. Suppose, for example, that some gene was duplicated. Although the duplication caused the organism to express more of the protein than was optimum, subsequent mutations in the promoter or protein sequence of one or both of the copies decreased the total activity of the protein to pre-duplication levels. Now, however, if one of the copies is deleted, there is not enough residual protein activity for the organism to survive. The new copy is now “essential”, although it does nothing that the original did not do.

The main points of Behe’s reply can be summarized as follows:

1. Gene duplications and subsequent changes to the copies (diversification) can and do happen, but the results are nothing really “new”— no new molecular machines or pathways (nor parts of such pathways), nor much in the way of new functions.
2. Duplicated genes can become essential simply by “sharing” the original function, and then reducing their share to a minimum, perhaps through the amount of protein that each copy makes. Again, this is not anything really new, since the copy doesn’t do anything that the original didn’t do already. So, the finding that some gene copies are essential genes is not a threat to the IC argument.

Note that Behe’s reply makes predictions that can be tested with further research. These predictions might be summarized in this way:

1. If IC is correct, duplicated genes will not be part of new, complex molecular pathways or machines.
2. If IC is correct, duplicated genes that are both essential should “share” the original function.

Testing IC with new research

Behe’s reply to the Chen paper is of course hypothetical and speculative – as demonstrated by his own comment that “there is no reason to think” that the duplicated genes are components of new complex pathways or systems. Accordingly, the validity of Behe’s reply depends on its ability to hold up over time as more work is done. Of note, the functions of p24-2 and its parent gene Éclair have been studied intensively since 2010. These studies, as we shall see in the next post in this series, shed quite a bit of light on these questions.

For further reading:

Behe, M.J. Darwin’s Black Box: the Biochemical Challenge to Evolution. Free Press, New York, 1996.

Behe, M.J. The Edge of Evolution: the Search for the Limits of Darwinism. Free Press, New York, 2007.

Chen, S., Zhang, Y, and Long, M (2010). New genes in Drosophila quickly become essential. Science 330; 1682-1685.

In the previous post in this series, we explored how evolution can force science into making predictions that seem counter-intuitive. For cetacean (whale) evolution, we saw that the preliminary lines of evidence (the fact that whales are vertebrates, and mammals, for instance) pointed to the prediction that modern whales are descended from four-limbed, land-dwelling ancestors. As we then noted:

Instantly this prediction raises a host of uncomfortable questions: where did their hind limbs go? How did they acquire a blowhole on the top of their heads when other mammals have two nostrils on the front of their faces? How did they transition to giving birth in the water? What happened to the teeth of the baleen whales? What happened to the hair characteristic of mammals? and so on. In some ways, evolutionary thinking about whales creates more difficulties than it appears to solve.

And yet, these difficulties are the stuff of science. If indeed our “educated guess” of terrestrial, tetrapod ancestry for whales is correct, the evidence will show that these transitions, challenging though they may seem, did indeed occur on the road to becoming “truly cetacean”.

We have already discussed hind limb and hair loss in whales, citing evidence from embryonic development in modern whales that shows how hair and hind limbs develop early in their embryogenesis, but then are lost at later stages. We now turn to one of the remaining questions: tooth loss in the lineage leading to modern toothless whales (order Mysticeti). To obtain their food these whales pass seawater through a baleen, a large sieve-like structure that filters out plankton, small fish and other food items. Some recent genetics sleuthing has investigated a portion of this riddle, and adds further details to the story of how the baleen whales came to be.

Evolution: A Theory with Bite

If indeed modern whales are descended from ancestral, four-limbed, terrestrial ancestors, then those ancestors, like mammals in general, had teeth. Modern toothed whales (order Odontoceti) have retained those teeth to the present day, but baleen whales have adopted a new way of life as filter-feeders. Researchers were curious to see if traces of a “toothed past” could be found in the genomes of modern baleen whales, so they went hunting for remnants of genes devoted to making teeth. Such defective gene remnants would be examples of pseudogenes, and we have discussed pseudogenes previously in this series. While pseudogenes in and of themselves are powerful evidence for evolution, pseudogenes that are “out of place” are especially so. One such example we have seen before is the human vitellogenin pseudogene, the remains of a gene used for yolk production in egg-laying organisms found in the exact location in the genome that evolution would predict for it. As mammals that receive embryonic nourishment through a placenta, we have no need of egg-yolk genes. Similarly, baleen whales have no need for genes responsible for making teeth, and finding the remnants of such genes would make a strong case for an evolutionary origin of baleen whales as the modified descendents of toothed whale ancestors.

Independent Lines of Evidence, but Contradictory Stories?

Some of the genes known to be used in all mammals for tooth formation were the obvious candidate genes to start with: the products of the ameloblastin, amelogenin, and enamelin genes are all used in the formation of tooth enamel, the hardest structure in the vertebrate skeleton. Researchers went looking for these genes in several Mysticete (i.e. toothless whale) species. The results showed that all the species studied did indeed have these three genes present as pseudogenes (and more specifically, as unitary pseudogenes, a special class of pseudogene we have discussed in detail previously). Finding these genes as pseudogenes in toothless whales was exactly what evolution predicted, but there was a catch: none of the mutations that removed the functions of these three genes were shared between different species, suggesting that these genes lost their function independently in the species studied. This finding was at odds with data from the fossil record, which suggested that teeth were lost only once, and early in the lineage leading to all modern toothless whales. So, the researchers seemed to have two lines of evidence that at face value contradicted each other. The fossil record suggested that tooth loss occurred once in the common ancestor of all toothless whales, but these three genes seemed to have been inactivated independently, several times over, suggesting that loss of teeth should be happening later in Mysticete evolution, and more than once.

One proposed explanation for the apparent discrepancy (among several put forward) was to predict that a fourth gene required for enamel formation was lost early in Mysticete evolution. The loss of any one gene necessary for forming enamel would be enough to prevent the process altogether. In this case, the loss of this fourth gene would prevent tooth enamel from forming, even though the genetic sequences of the other three enamel genes would still be intact. Once enamel function was lost, random mutations in the remaining enamel genes could then accumulate later in Mysticete evolution after speciation in this group was already underway. To test this hypothesis, the research group went hunting for other enamel genes in toothless whales.

Signature in the SINE

The smoking gun for tooth loss in Mysticetes turned out to be exactly what was predicted: a fourth gene, necessary for enamel production, and mutated with the same inactivating mutation in all modern toothless whales. The gene in question, named enamelysin, was destroyed when a mobile genetic element called a SINE transposon inserted into it, breaking it into two halves and removing its function:

The fact that the same SINE insertion mutation at an identical location is found in all modern Mysticete species indicates that this mutation happened once in a common ancestor and then was inherited by the entire group. Since this must have occurred early in the evolution of toothless whales in order to happen in the common ancestor of the entire group, the picture from the genetics and the fossil record match. Once again, findings in one discipline (in this case, paleontology) can be used to make very detailed predictions about what another, unrelated discipline (comparative genomics) should reveal. These results are also entirely consistent with the observation, made in the 1920s, that toothless whales form tooth buds during embryogenesis that are later reabsorbed prior to the point when the deposition of enamel would begin. As with the hind limb story in whale evolution, lines of evidence from genetics, paleontology and embryology converge to support the hypothesis that modern toothless whales descend, through modification, from toothed ancestors.

In the next post in this series, we’ll examine a few more lines of evidence for whale evolution, and extend our discussion to converging lines of evidence for the evolution of our own species.

For further reading:

Meredith, R.W., Gatesy, J., Cjeng, J., and Springer, M.S. (2011). Pseudogenization of the tooth gene enamelysin (MMP20) in the common ancestor of extant baleen whales. Proceedings of the Royal Society B: 278 (1708); 993 – 1002. Available online: http://rspb.royalsocietypublishing.org/content/early/2010/09/16/rspb.2010.1280.full.pdf

Ridewood, W.G. (1923). Observations on the skull in foetal specimens of whales of the genera Megaptera and Balaenoptera. Philosophical Transactions of the Royal Society of London B: 211; 209 - 272. Available online: http://rstb.royalsocietypublishing.org/content/211/382-390/209.full.pdf

See Related Posts in the sidebar

Today's video is courtesy of filmmaker Ryan Pettey, director/editor of Satellite Pictures, and features Dr. Rick Colling, biologist and author of Random Designer.

In today’s video, Dr. Rick Colling states that one of the biggest difficulties in communicating compatibility between evolution and faith is a misunderstanding of what evolution is. Evolution is not, he says, about the imposition of death and destruction and survival of the fittest. Rather, it is about second chances. Our bodies contain thousands of genes, which duplicate like a computer back-up copy and can serve as raw material. When an organism encounters adverse environmental condition, this raw material can be used to help adapt and survive.

“God is so creative," says Colling, "that he’s actually put into place a mechanism to start doing these gene changes in advance before they’re even needed. And God has given us a second change through the evolutionary process of creating duplicate genes that give rise to new raw material that give rise to new possibilities, and that really more accurately describes the process of evolution. It’s redemption, it’s possibility, and it’s hope.”

Do genomes have non-functional sequences?

There are various ways to test the hypothesis that certain regions of DNA are non-functional, and in this series we will explore some of them. One way to estimate the fraction of non-functional DNA in a particular genome is to determine which portions of the genome can be freely altered by mutation without consequence to the organism. DNA sequences that cannot be mutated freely without a loss in function are said to be under purifying selection: as mutated forms of this sequence arise in a population, the loss of function associated with the mutated sequence reduces the likelihood that the organism will pass this mutation on to future generations. This type of mutation, in a functional sequence, has deleterious consequences. Another way to put it is that functional sequences are subject to natural selection, which acts as a filter to “purify” the genome at a particular location, but that non-functional sequences are free from the constraints of selection, and “anything goes” with respect to mutation.

Tell us again, Grandpa!

One way to think about this is to consider a humorous story that is told within an extended family (I think every family has these types of stories – I know my kids love to hear certain ones told and retold again). Certain incidental details of the story can be altered from telling to telling, and perhaps Uncle Joe tells it a certain way but Uncle Jeff tells it another with respect to those types of details. There are, however, certain features of the story that are absolutely non-negotiable, or the story doesn’t “work” (and telling these parts incorrectly will generate protests and corrections from the kids who know how the story goes and insist that you are not telling it correctly). These types of stories, like genomes, have some bits that can freely change and others that can’t. The bits that can’t change are under constraint and, in biological terms, subject to selection. The same factors apply in more concise form to jokes: some bits can change (and do, as the joke is told and retold) – but some bits cannot (for example, the punch line).

The best way to test for purifying selection is to compare the genomes of related organisms that have been separate species for some time. (To continue our analogy, you could determine what parts of the story are really important by comparing how each of the uncles tells it and listing out the parts that are the same in all the various versions). The genomes in the two species are modified versions of the same genome present in the common ancestor species: they started as virtually identical but have since experienced mutations in different locations over time. Mutations in functional sequences will have been subject to purifying selection to remove loss-of-function mutations, whereas mutations will have freely accumulated in non-functional sequences. The two genomes are thus a collection of similarities and differences, as we have discussed before:

In some ways, comparing the DNA sequence between related organisms is like reading alternative history novels. The hypothesis of common ancestry between similar organisms makes a very straightforward prediction about their genomes: it simply predicts that they were once the same genome, in the same ancestral species. This hypothesis also predicts that these two genomes, having gone their separate ways in the diverged species, will have accumulated changes once they separated. Like an alternative history, each genome has the same backstory, and then a history independent from the other after the point of separation.

These similarities and differences, however, will not be randomly distributed. Sequences subject to purifying selection will have fewer differences than sequences that can freely mutate. Accordingly, when compared side-by-side, the two genomes should have regions where differences are common, and where differences are rare. For example, consider a genome segment in two related species where there is one gene present. This gene has some regions that cannot be changed without significant consequences (the DNA letters that code for the amino acid sequence of the gene product, for example) and some regions that can be mutated without consequence (such as some sequences inside introns, the non-coding segments that separate gene coding segments and are spliced out of the final gene product):

What biologists observe when comparing sequences like this between two related organisms is that coding sequences, which obviously are required for the gene’s function, have far fewer differences between them than do sequences found in introns or in between genes. The idea is not that mutations are preferentially happening in those areas, but that mutations can occur everywhere in the genome, but are more likely to be selected out of populations if they alter functional sequences.

The expanding data set

This type of analysis gets easier to do the longer two species have been separated, and the more species one has to compare to each other. Very recently separated species will have a very high degree of genetic similarity simply because neither species has had appreciable mutations to a common ancestral genome. As such it is difficult to pick out the sequences that have been subject to selection, since functional and non-functional sequences are both still highly similar (virtually identical). It is only as species have been separated for a long time that a pattern begins to emerge: sequences that are functional remain “constrained” by purifying selection to remain more similar, and non-functional sequences accumulate mutations in the separate lineages that make them less and less alike.

Now that biologists have access to a wide range of mammalian genomes, this type of analysis has been done on the human genome with ever-increasing precision. Early studies comparing the human genome to other genomes, such as the mouse genome (compared in 2002) and dog genome (2005), suggested that only a small fraction of the human genome was subject to purifying selection (about 5%). Recent work published a few months ago has taken this approach to a whole new level: a genome-wide comparison of 29 mammalian species (!). These results are exciting from a biological perspective because this work helps scientists tease out what bits of the human genome are under selection, and what bits aren’t (which isn’t always obvious, because we don’t always know what sequences are functional or non-functional). This type of approach is non-biased: it requires no prior hypotheses of what types of sequences to look for, but rather simply looks for what has been selected to remain more similar over time. The results, based on the (very nearly) whole-genome sequences of 29 placental mammals, are in keeping with previous estimates: about 5-6% of the human genome is under purifying selection, and the rest appears to be rather free to accumulate changes. As a species, our genome seems to be about 95% incidental details and 5% punch line.

So, what sorts of things lurk out there in the “other” 95%? In the next post in this series, we’ll head out into the wilds of the human genome and have a look.

Editors Note: So now that you've read the essay, see if you can surmise the meaning of the figure at the top. This is a tiny stretch of DNA, 21 bases (units of code) long. Why do you think position #4 shows only an A and position #5 shows only a G, whereas other positions are not restricted in this manner? Pretend that you could represent the genome as a whole in this manner. Of the 3 billion bases in our genome, how many of them would be configured like position #4 or #5? What about the rest? Is the specific base (unit of code) functionally important for that set? Upon what, do you base your conclusions.? Finally do the presuppositions of the Intelligent Design Movement and Reasons to Believe pivot on how to interpret this data? How would such proponents interpret the data differently than mainstream biologists? Feel free to address these questions in the comment section or, if you prefer, just reflect on them.

For further reading:

Lindblad-Toh, K., et al. (2011). A high-resolution map of human evolutionary constraint using 29 mammals. Nature 478 (27), 476-482.
http://www.nature.com/nature/journal/v478/n7370/full/nature10530.html

In our previous BioLogos podcast, we looked at the question of transitional fossils, and how the transitional species story strongly supports evolutionary theory. In this podcast, we look at genetic evidence for evolution. The discovery of DNA has revolutionized our understanding of common descent, particularly in the past few decades. Mutated genes spread through populations over generations, leading to the change we know as evolution. Amazingly, deeper study of DNA lines up with Darwin's initial observations of the larger natural world. While it would take weeks to highlight all the genetic evidence for evolution, today we focus on a few specific examples: the similarity of genomes for related species, psuedogenes, and genetic markers left by retroviruses.

For more, be sure to read Dennis Venema's series "Signature in the Psuedogenes" and "Understanding Evolution".

From the AAAS/Science Magazine Podcast (August 26, 2011). Posted with permission from AAAS.

These are mind-boggling times for a geneticist many years into his career. As a graduate student attending a conference at the University of California, Berkeley almost forty years ago, I remember watching with bated breath while another young graduate student, Nancy Maizels of Harvard, presented the DNA sequence of the lactose operator. Using amazing technology, she and Walter Gilbert had unraveled a little stretch of 24 units of code.

We were in awe—absolute awe—partly because the sequence was beautiful (it exhibited perfect twofold bilateral symmetry) and partly because we were incredulous that anyone could have done it—24 bases of DNA! A secret that had been locked inside of cells for millions of years was there on the screen in front of us. For a biologist, this was better than going to the moon. Twenty-four bases of the 4,600,000 bases in E. coli had been sequenced: one small step for a molecular biologist, but one giant leap for humankind!

It was Berkeley. It was 1973. Biology, we thought, had reached its zenith. The possibility of someday sequencing the other 4,600,000 bases of the E. coli genome or, heaven forbid, the 3,500,000,000 bases in the human genome, was like picturing the construction of a rocket ship that would take you to the outer reaches of the universe. No one dared dream of it.

I remember the February day in a San Francisco hotel in 2001 when Francis Collins, wearing a business suit (there were no business suits at Berkeley in 1973), showed his analysis of the just-completed first draft, not of another 24 base segment, but of the entire 3.5 billion bases in the human genome. Craig Venter, wearing a tuxedo (there were no tuxedos either), did the same the next night. We were dazzled with the two successive presentations. Indeed as the second evening came to a conclusion, it seemed like we had been on a trip—this time not to the moon, but now to the other side of the universe…and back.

Genetics had changed. No longer in a Berkeley classroom with shorts, sandals, long hair, and chalk board, we were now on the other side of the Bay in a fancy hotel in downtown San Francisco, where champagne corks were popping. Molecular biology had made the big time. Still, the simple awe of having unraveled the beauty of the molecule’s secrets was not dimmed by the hype or the glitz. The majesty of the molecule spoke for itself and I felt just like I had 28 years earlier.

What, I wondered, would be next? What could top a trip to the other side of the universe and back? We all had dreams, but no one dared dream of what actually happened.

Even as that excitement was wooing us all, the next unbelievable trip was already unknowingly underway. Svante Paabo and colleagues were working out the techniques to extract and sequence DNA from 30,000(+) year old Neanderthal bones. Never, in my wildest imagination in 2001, would I have pictured the possibility of obtaining enough nuclear DNA from our long extinct relatives to sequence their genome too. But now, ten years later we have a draft (1.3 fold coverage) of the DNA instructions for building the body of a Neanderthal.

It doesn’t stop there though. The molecule keeps revealing its secrets. No sooner had I caught my breath from reading the details of the Neanderthal sequence, when the biggest shock of all was released last December. Found in a Siberian cave were the fossilized bones of a single finger of a female hominin (human relative) who lived between 30,000 and 50,000 years ago. Paabo’s group was able to isolate enough high quality DNA from that one pinky finger to sequence her entire genome. (Listen to the fascinating discussion of the discovery in the accompanying audio.) We now have a better draft (1.7 coverage) of the DNA from the bones of one “pinky” finger than we do of the all of the fossilized Neanderthal remains put together.

Prior to analyzing her genome, investigators expected to find that either she was a human being like us, or she was a Neanderthal. What they found, however, no one was prepared for. No one! The DNA in that finger was not ours, nor was it Neanderthal. This single finger was from a different hominin altogether. Now it is clear that we had relatives—known as the Denisovans—roaming the earth in the recent past who were as different from us as Neanderthals were. There would likely have been at least hundreds of thousands of these individuals that lived on Earth from the time of their inception to the time of their extinction. Yet all we have identified so far is one finger, two molar teeth (found in the same cave, but from a different individual) and a piece of a knuckle bone. It was their genome, not a fossil, which has told us of their existence. Without that we would not have known.

And I thought biology had gone to the moon when it revealed the 24 base sequence of the lactose operator! Now we have billions of bases sequenced and a draft of the instruction plans for building three different hominins, all of whom lived on this Earth at the same time, as recently as 30,000 years ago.

There are many ramifications of this discovery. First, we are in the unprecedented—and until now unimagined situation—of having the entire genome sequence of an organism for which we have virtually no fossil material. (One pinky, two molars and a part of a knuckle bone do not a full-fledged fossil make).

At BioLogos, we have said many times that we would expect to find significant gaps in the fossil record (see here for example). We understand the basis for the gaps. For one thing, fossilization is an exceedingly rare event, but there are other well-understood reasons as well. Paleontologists have scoured the world looking for hominin fossils. They are big and easy to spot should they be present in the area being searched, but the fossil record of these newest hominins was silent until recently. What ought that to tell us? How long will it take us to grasp that gaps in the fossil record are not surprising? The surprising thing is that we have as good a record of past events as we do. It’s that which should amaze us, not the absences.

Second, now that we have drafts of the instructions for building all three body types, we can determine how similar they are and when they would have last shared a common ancestor. Based on genetic analysis, the average gene difference points back to a common ancestor of all three groups who lived about 800,000 years ago.

The Neanderthal and the Denisovan are a little more closely related to each other than they are to modern humans. In their case, analysis of average gene difference suggests that they last shared a common ancestor about 400,000 years ago—though they are still very different from each other.

To give you a feeling for how similar and different they are from one another, consider human/chimpanzee differences. It’s been about 6,000,000 years since we had a common ancestor. On the other hand, our family tree is identical to that of the Denisovans and Neanderthals until about 800,000 years ago. We’ve only been diverging separately for a little over 10 percent of the time since the last common ancestor of chimps and humans. Of course, when one considers how different chimps are from humans, even ten percent of that for the human/Neanderthal or human/Denisovan comparisons is large. They were very different from us and it will be extremely interesting to analyze the differences gene by gene as the analysis continues in the coming years.

Third, we need to acknowledge that as the genetic and paleontological data keeps piling up, it is most important that the Church become engaged in thinking about its meaning. It is clear now that we can trace our lineage—in some cases gene by gene— with amazing precision. These are cousins of ours: the Neanderthals, Denisovans, and almost certainly others who occupied the Earth at the same time, some perhaps as recently as 17,000 years ago.

BioLogos exists to help Christians think carefully about the ramifications of these new data in light of long-standing traditional ways of viewing human creation. We have some re-thinking to do, but it can be done and will be done within the context of a Christian faith that is fully orthodox and thoroughly evangelical. Any time we draw closer to truth, to God’s truth, we have nothing to fear. There is still much to learn, but we can look back at what we have learned with awe—absolute awe.

I’m not at a Berkeley conference anymore, and I’m not in a cork-popping San Francisco hotel either. For me, however, this stage is the most thrilling of all because it takes us deeper—far deeper—than we could have ever imagined. Addressing the theological and philosophical questions that lie ahead will be rewarding to work through and will take us far outside the natural universe into the realm of the New Jerusalem—the supernatural world of heaven itself. This is God’s truth we are coming to understand. We must not leave this territory, which reveals so much about human nature, to the exploration of those who don’t believe there is a New Jerusalem. We as Christians ought to be at the forefront in thinking about the meaning of these new data and not turning our backs just because we find it so surprising (and to many, unsettling). As we begin an all-fulfilling journey across this new frontier together, I am confident we’ll go in the presence of God. The DNA molecule is God’s creation, after all, and the secrets it reveals to us are his truths, not ours.

The above audio, from the August 26th Science Magazine podcast, is a very engaging discussion of the science that has led to our current state of knowledge. We greatly appreciate the American Association of the Advancement of Science (AAAS) for granting us permission to post it here. Ann Gibbons, the interviewee, is a journalist at Science Magazine. For more about her work see http://www.anngibbons.com/bio/bio.shtml

Thomas a Kempis - Of the Imitation of Christ (c.1420)

Lost in (Sequence) Space

In Parts 2 and 3 of this series (see sidebar), we explored two concrete examples of how new structures and functions arose through mutation and natural selection: the ability of E. Coli to utilize citrate that appeared during a controlled laboratory experiment, and the duplication and divergence of a steroid hormone receptor gene that acquired a new hormone binding partner and went on to regulate new processes distinct from its predecessor.

Both of these examples were notable for their intricate level of detail that carefully teased out the intermediates on the path to new functions. Still, at the close of Part 3 we noted that

Over and against these lines of evidence, however, the Intelligent Design Movement claims that such novelty is inaccessible to random mutation and natural selection. Rather, they claim that functional protein shapes are incredibly rare and therefore so isolated from each other that random mutation and natural selection cannot bridge the vast gulfs between them.

The issue here is that functional proteins seem to be a very small subset of possible proteins. Proteins are chains of repeated structures (amino acids) that are typically one hundred or more repeats in length. There are 20 amino acids found in proteins, so at every position in a protein chain, there are 20 different possible choices. So, for a protein with only two amino acids (not even a realistic scenario) there are 20² possible combinations. For a protein with 100 amino acids, there are 20¹⁰⁰ combinations – a vast “sequence space” of possible states, of which only a relative few will be functional.

As we have seen in Parts 2 and 3, proteins “explore” their sequence space through random mutation. Mutation may produce protein forms that reduce or remove function, changes that are neutral with respect to function, or changes that improve function (or add new functions). Over time, evolution predicts that proteins will “branch” through sequence space – with each modern form connected to a previous form of which it is a modified descendant. The Intelligent Design Movement (IDM), as we have noted, predicts a different pattern: isolated, separately designed (created), functional proteins that lack prior transitional forms.

In other words, the IDM views protein sequence space to be like the diagram on the left. The brown spheres represent functional protein shapes (each of which allows for some small variation within the sphere). These are separated by large gaps of nonfunctional sequences. In contrast, an evolutionary model predicts that modern-day functional sequences (brown spheres) are connected in sequence space by functional intermediates across time (black lines).

The two examples we have already examined in parts 2 and 3 (citrate metabolism and novel hormone / receptor pairs; see sidebar for links) are strong support for the evolutionary model: in both cases new functions and structures were connected to prior forms (that had different functions) through a series of functional intermediates. The question remains, however: are all proteins so connected? Are these examples rare exceptions? Certainly if evolution has produced the diversity in protein form and function that we observe today this pattern should be common.

Welcome to the Neighborhood

That was the question that recently led two researchers to examine a large number of protein enzymes with known functions: 28,862 different proteins from a wide array of organisms, to be exact. Specifically, the researchers examined “genotype neighborhoods”: proteins that have similar amino acid sequences and group together in sequence space (such as those represented by the spheres in the diagram above). A two-dimensional cross-section of two such spheres can be represented as follows (redrawn from Figure 2 in Ferrada and Wagner, 2010):

Where each sphere has a radius (r), and the two are separated in sequence space by a distance (d). The radius and the distance are percent differences in amino acids. For example, we may consider all proteins that differ by at most 2% of their amino acids within the two neighborhoods (r=1 for both). The distance between the two neighborhoods (d) is also a percent difference in amino acids (for example, d could be 10%).

Since the data set used by the researchers was for enzymes with known functions, pairs of genotype neighborhoods were assessed to determine if they contained the same enzymatic functions, or distinct functions. For example, if neighborhood 1 contains enzyme functions A, B and C, and neighborhood 2 contains only enzyme functions A and B, then enzyme function C is unique to neighborhood 1. The fraction of unique functions for pairs of genotypic neighborhoods can thus be analyzed as functions of r and d.

In other words, how different do two genotype neighborhoods have to be before new functions are encountered in protein sequence space? Are existing protein families situated in protein space as isolated islands of (independently designed) function in a sea of nonfunctionality, as the IDM predicts? Or can new functions be reached as enzymes explore sequence space through random mutation and natural selection?

Not surprisingly, the researchers found that as the percent amino acid differences (d) increased between two genotype neighborhoods, the fraction of unique functions increased. What was interesting (in terms of assessing the claims of the IDM) was that unique functions can be readily observed even for low values of d. For example, genotype neighborhoods with a 20% difference in amino acids (d = 20) had unique functions over 45% of the time when r was held constant at a 5% difference. Smaller differences, such as d = 10, did not eliminate unique functions (nearly 20% had unique functions; see figures 3A and 3B in Ferrada and Wagner for results for the data set as a whole).

A second interesting result was that even when genotype neighborhoods overlap (i.e. d is less than the sum of the two radii), they still may have unique functions:

This simultaneously underscores two observations: that highly similar sequences may have different functions (as is well known from other studies), as well as the contingent nature of proteins exploring sequence space (even closely related proteins cannot reach the same potential functions via a short search, depending on their position in their genotype neighborhood). This result is also consistent with what we have seen previously in parts 2 and 3: neutral mutations that move a sequence within its genotype neighborhood can bring it into reach of new potential functional states. Such neutral mutations were key in opening up future possibilities both for the evolution of citrate metabolism in E. Coli as well as in for steroid hormone receptors in vertebrates.

Does maintaining a specific protein structure prevent exploration?

Having obtained this result, the researchers went on to add a constraint to the analysis: they restricted their data set to protein sequences known to fold into a specific structure (the data for the TIM barrel domain can be seen in Figures 4A and 4B; compare with 3A and 3B). They chose a very common protein fold (called a TIM barrel) that many protein sequences can fold into (4,132 sequences in the data set), and that performs many different enzymatic functions (53 distinct chemical reactions currently known). The amino acid sequences that form a TIM barrel can be 100% different (i.e. d = 100) or very similar (d ~ 0). As before, the researchers examined how functions are distributed in sequence space for pairs of genotype neighborhoods, but now restricted to this structure alone. Significantly, their results were the same as before. Genotypic neighborhoods close to each other still showed different functions, and overlapping neighborhoods contained unique functions. To be certain that this was not an effect specific to the TIM domain, the researchers repeated the analysis for 36 additional structures, all of which gave similar results.

Put another way, constraining a protein to a particular three-dimensional structure (i.e. protein fold) does not seem to hinder its ability to traverse sequence space and acquire new functions in the process.

Taken together, this paper demonstrates some key findings for how protein sequences, structures and functions are distributed in protein sequence space:

1. The distribution of protein sequences, structures and functions we observe is strongly consistent with the hypothesis that proteins traverse sequence space and acquire new functions over time through random mutation and selection.

2. Functional sequences in protein sequence space are distributed such that a significant subset of protein families are close to areas with new functions. In some cases, genotype neighborhoods can overlap where one neighborhood contains functions that the other does not.

3. Not all areas of a genotype neighborhood are equivalent: neutral mutations within a genotype neighborhood can move a sequence to regions where new functions can be reached, or into areas where those same functions are not accessible.

4. Constraint on protein structure is not a constraint on acquiring new functions. When the analysis was restricted to a common structure, the same results were obtained (consistent for 37 different structures).

Moreover, this work is based on the largest sample size examined to date (over 28,000 proteins), and thus is much more likely to apply to protein sequence space as a whole than studies (such as those performed by members of the IDM) that attempt to extrapolate from studies of one protein (or a handful of related proteins) to protein sequence space in general. Despite the claims of the IDM, proteins do not appear to be “lost” in sequence space.

In the next post in this series, we’ll examine another line of genomics-based evidence for proteins acquiring new functions over time: the distribution of gene copies with distinct functions (paralogs) in vertebrates.

Further reading:

Ferrada, E., and Wagner, A. (2010). Evolutionary innovations and the organization of protein functions in genotype space. PLoS ONE 5(11); e14172.

After the recent exchanges between Fazale Rana of Reasons to Believe (RTB) and myself, I had intended to move on to other important issues. However, Rana’s final response to my critique is so inaccurate - and so badly misleads his audience - that to not reply would be irresponsible. There is no room for a “pig-in-a-poke” in science or the church.

If you have been following this series, you will know that one of the strongest pieces of evidence in favor of common ancestry between humans and chimpanzees (and other organisms) is a large number of “broken” genes, otherwise known as pseudogenes. When they are damaged in exactly the same way and exactly the same spot in closely related organisms, by far the simplest explanation is that they are copies of a single gene that was damaged in a common ancestor.

One way of illustrating this is to think of a 25 page manuscript: pretend that there is a mistake of one letter out of the 75,000 letters. Let’s say that a “g” had been inadvertently removed from the word “missing”, so that it now reads “missin.” Now let’s say that you collect 10 copies of this manuscript from various people and five of them have exactly the same mistake—the word “missing” on page 22, line 15, word 7, is spelled “missin” instead of missing. Every one of the other 74,999 letters in the 25 pages is perfect. Would you not conclude that the five identically mistaken manuscripts are derived from a single source? Would you not have to strain very hard to come up with an alternative explanation?

Rana is similarly desperate. The RTB model—based as it is on their specific interpretation of scripture— requires that they find an alternative to the common descent model overwhelmingly accepted by biologists. Rana feels a need to respond to pseudogene evidence since it so powerfully supports the creation of humans through an evolutionary process. The fact that different mammalian species, including humans, have many pseudogenes with multiple identical abnormalities (mutations) shared between them is a problem for any sort of non-evolutionary, special independent creation model. The fact that shared mutations are present in patterns that match other independent lines of evidence such as sequence identity (see here and here) and shared synteny (see here) only makes matters worse. The data from these different areas are congruent and I am not aware of any paper in the peer-reviewed scientific literature that attempts to argue for a non-evolutionary interpretation of these data.*

The topic of Rana’s rebuttal is a single portion (termed the tenth exon) of a single pseudogene, the GLO pseudogene, which, when not broken, makes an enzyme required for vitamin C biosynthesis. In “dry-nosed” primates (a group which includes humans,) this gene is “broken.” It is because of this that we get scurvy if we do not ingest enough vitamin C in our diet. Many of the mutations in the GLO pseudogene are shared between humans and other primates, indicating that these mutations have been inherited from a common ancestor. The only other possible explanation is that a large number of identical mutations occurred independently in many species – something so improbable as to be not worth considering. Yet this is exactly the strained interpretation that Rana chooses to argue for:

Comparison of the rat’s exon X (10th exon) DNA sequence with those in humans, chimpanzees, and orangutans reveals a number of the same mutations in the same locations for the primate sequences. Of particular significance is position 97 in which it appears as if a deletion took place in the primate sequences. Evolutionary biologists argue that this deletion and the other shared mutations are clear evidence for common ancestry, with these changes having occurred before apes diverged from Old World monkeys.

The RTB genomics model offers a different explanation for the similarities in the primate DNA sequences. The shared features are interpreted as the outworking of nonrandom, reproducible changes that happened independently in humans, chimpanzees, and orangutans.

Rana then goes on to claim that there is empirical evidence for the RTB view. The GLO gene is also a pseudogene in guinea pigs, but this species lost GLO function independently of the primate common ancestor. Not surprisingly, the mutations in the guinea pig pseudogene are different from those in the primate pseudogene, but Rana claims that there are a few shared mutations between primates and guinea pigs in exon X:

Support for this interpretation comes from comparisons of the primate exon X sequences with the corresponding region of the guinea pig GLO pseudogene. The structure of the guinea pig GLO pseudogene is dramatically different than that of the human pseudogene. Presumably, guinea pigs and primates lost this gene independently. If mutations were random, then few if any of the changes in the primate and guinea pig exon X sequences would be the same. Yet, as biologist Peter Borger points out, fifty percent of the mutations in the primate and guinea pig exon X sequence are identical. In addition, the guinea pig exon X region shows a mutation at position 97, the location in the primate genomes where a deletion took place. These shared features could not have resulted because guinea pigs and primates shared a common ancestor. Instead, they must reflect nonrandom, reproducible changes.

In other words, the RTB genomics model can reasonably account for the shared features of the GLO pseudogene in primates without resorting to common ancestry as the explanation.

There are several problems with this argument, but none would be apparent to a non-specialist. On the face of it, it seems like a strong case. If indeed there are shared mutations in two independent gene-to-pseudogene conversion events, it would lend (some) credence to Rana’s assertion that all shared mutations are the result of non-random events. The GLO pseudogene sequences in question are as follows. At six sites (in yellow) the human and guinea pig sequences match each other but differ from the rat (purple). The anti-evolutionary source Rana cites (PDF) claims that these sites are the result of independent mutation to the same nucleotide. (Position 97, which has a single-nucleotide deletion in humans and other primates, is shown in blue.)

Despite Rana’s insistence that there is only one possible explanation for this pattern, there are two possibilities. The possibility that Rana does not discuss is this: the human and guinea pig sequences match because they are not mutations, but rather the original ancestral sequence of the functional GLO gene that was present in the last human – guinea pig common ancestor. This would make the rat sequence at these six positions the mutations, not the human / guinea pig sequences. There is a simple way to test this hypothesis, of course: examine the GLO sequence of other mammalian species in this region. If many other species match the human and guinea pig sequences, then we know this sequence is the ancestral sequence. If many other species match the rat sequence, the rat sequence is ancestral and the evidence supports multiple independent mutations in the primate and guinea pig lineages. Unfortunately for RTB, even a cursory examination of other species in this region demonstrates that the human / guinea pig sequence is ancestral. At each of the six positions, the consensus sequence matches the human / guinea pig sequence. The so-called “shared mutations” are not mutations at all:

The RTB model thus has no support for the proposal that shared mutations observed between species are the result of non-random, parallel mutation events. As such, Rana’s assertion that the RTB model adequately accounts for shared mutations in pseudogenes is incorrect. Unitary pseudogenes with shared mutations remain an insurmountable problem for RTB.

Beyond the scientific flaws in this argument, what I found troubling about Rana’s response is that this analysis I have presented here is nothing new – it has been known for years (see for example here and here). Rana should have known about this. But even if he didn’t the fact remains that it would have been easy for Rana to test the claims himself. For example, I assembled the alignments in this post using public databases and search tools freely available on the web. (It would have been possible simply to use figures presented elsewhere, but I wanted to (a) confirm the data myself, and (b) ensure that the relevant sequences have not been updated with corrections in the last few years). If I can do this, Rana should be able to do so as well, especially before presenting flawed arguments to non-specialists (such as RTB supporters or public in general) who will take him at his word.

As the young earth creationist, Todd Wood, pointed out in the conclusion to his recent series on RTB, the reasons behind this unfortunate pattern in RTB scholarship are somewhat irrelevant. What matters is that believers know that until RTB makes amends, their model is untrustworthy. Indeed, if RTB had developed a scientifically credible model to explain shared pseudogenes from an anti-common descent perspective, Todd Wood would be very interested (since he, being a young earth creationist, does not believe in common descent). Todd’s view of the RTB model, however, agrees with mine - and he too has called on RTB to correct their errors:

Venema and I have documented a sad but consistent and ongoing pattern of erroneous summaries of published works on the part of RTB (Rana and Ross, but mostly Rana).There's really no way to deny these mistakes have been made or to explain them away, so what are you going to do about them? I recommend apologizing for the mistakes, correcting them if you can, and instituting some kind of serious fact-checking filter on everything you publish…

As far as I'm concerned, RTB's credibility is completely shot. I would recommend that no one accept any of RTB's arguments without fact-checking their claims first. I do not know whether these problems are due to lazy scholarship, ignorance, intentional deception, or ideological blinders. What I do know is that you cannot trust Reasons to Believe.

Hopefully in the coming days RTB will follow Todd’s advice. Please, Dr. Rana, for the sake of RTB’s followers (and the church as a whole), let your audience know that you have made a mistake. Let them know that the RTB model is flawed. Admit that it misrepresents well-established science. Then start the work of making it right. This, after all is how real science works. We admit when old ideas don’t work anymore and we move on.

I would also suggest that you surround yourself with people who have expertise in this area of biology. Please have your ideas thoroughly vetted by those who know the field. As your brother in Christ, I would be happy to work with you in arranging that. While I cannot speak for Todd personally, I have every confidence that he too would be willing to help with an honest overhaul of the RTB model. Without that (significant) overhaul, however, the RTB model is a (guinea) pig in a poke. Caveat emptor.

* - “I previously stated in this post that I was convinced that no geneticist at a secular, research university would see this data differently. I have now received what I consider reliable information that this is not the case, but rather that there are at least a few biologists at secular institutions who privately hold to a young earth creationist view. As such, they do see the data differently, though for religious reasons. I should have been more clear: I am convinced that there is no biologist at a secular institution who objects to a common ancestry interpretation of these data for scientific reasons. Certainly, if there is such an individual, they have not made their case in the scientific literature, the proper place for contesting current scientific consensus.”

One serious critique of young-earth creationist attempts to explain the natural realm is that their explanations, typically rooted in religious dogma, have no flexibility to adapt and self-correct as knowledge increases.

-Hugh Ross
More Than a Theory, p. 20

Introduction

Reasons to Believe (RTB) is the most influential Old-Earth Creationist organization in North America. While RTB supports a mainstream scientific position on cosmology and the age of the earth, RTB rejects evolutionary biology. Specifically, RTB denies that humans share ancestry with other forms of life, such as Neandertals or chimpanzees. RTB also claims that all human are the descendents of a single, specially created couple who lived about 50,000 years ago. RTB has expounded a framework called the “Testable Creation Model” in three major books published in the last five years: Who Was Adam? was published in 2005; Creation as Science was published in 2006, and More Than a Theory was published in 2009. Furthermore, RTB claims that this model is scientifically robust.¹ This same period however, has also seen the publication of much genetic data relevant to assessing human common ancestry. This paper will examine the interaction between RTB literature and several lines of genetics-based evidence for common ancestry. In so doing, I will address the scientific robustness and reliability of the RTB model. RTB welcomes such critique from qualified scholars in their works as a means of improving their model.² This critique, while forthright, is offered without animosity and in good faith. It is my hope that RTB will find it useful for correcting several serious flaws in their approach to human origins.

A recent history of primate comparative genomics

When the human genome project (the endeavor to determine the complete DNA sequence of every human chromosome) was completed in 2003, the equivalent chimpanzee genome project was already underway. Just prior to the completion of the human project (from about 2002 on), detailed comparisons of large stretches of DNA between humans and chimpanzees became possible as both genome projects progressed. As the data came in, a range of estimates for the precise amount of identity between the two genomes was published in the mainstream scientific literature (Table 1).

Such estimates took two forms: measuring single-nucleotide differences in sequences found in both genomes while omitting inserted or deleted sequences (so-called “indel” mutations, because it may be difficult to determine if a difference is due to an insertion or deletion), or estimates combining both sources of variation. In the years preceding the completion of the chimpanzee genome in 2005, partial-genome comparisons repeatedly estimated the two genomes to be over 98% identical when omitting differences due to indels. Two pre-2005 studies took indels into consideration as well: Britten (2002) estimated the two genomes to be 95% identical, whereas Anzai et al. (2003) found only 87% identity. This paper examined a chromosomal region that contains immune system genes, and was not thought to be representative of the genome as a whole. This prediction was borne out in 2005 when the completed human and chimpanzee genomes were compared (2.9x10⁹ DNA base pairs). The final tally was 98.77% identical when indels were omitted and 95% identical when indels were included. A second paper published in 2005 examined 1.85x10⁷ DNA base pairs found in the portions of the chromosome that specify proteins, and found even higher identity (99.4%) in these sequences.

The RTB model and comparative primate homology: overview

A key tenet of the RTB model is that humans do not share ancestry with other forms of life. As such, RTB has invested considerable effort in reinterpreting human / chimpanzee genomic homology comparisons for their constituents. A notable feature of the RTB model is the claim that the whole-genome, human / chimpanzee homology value is in fact 85-90%, not 95-99%.³ As we have seen, comparisons between the human and chimpanzee genomes progressively improved in the early 2000s, culminating in the landmark whole-genome comparison of 2005. The fact that these data emerged over time allows us to investigate how RTB responded over the same time period, and as such examine the reliability of the RTB model as new data became available that were at odds with one of its non-negotiable claims.

The RTB model and primate genomics (2005): Who Was Adam?

Like comparative primate genomics, the RTB creation model also hit a milestone in 2005 with the publication of Who Was Adam? (WWA) by RTB scholars Fazale Rana and Hugh Ross. This book narrowly predates the pivotal 2005 whole-genome comparison paper. Unlike two later RTB books (see below) this book discusses research-to-date on human-chimpanzee comparative genetics in extensive detail. (p. 212-215) WWA carefully distinguishes between estimates based on including or excluding indels, as well as chromosomal or mitochondrial DNA. However, WWA made a questionable claim when it states:

“The most comprehensive genetic comparisons indicate that humans and chimpanzees share genetic similarity closer to about 85 percent than to 99 percent. From an evolutionary perspective, if a 99 percent genetic similarity reflects a close evolutionary connection, then an 85% genetic similarity distances humans from chimpanzees.”(p. 223)

This assertion, however, was already at odds with the conclusions of the 2004 Chromosome 22 Consortium paper (Table 1), a paper that is cited in WWA as support for differences in human-chimpanzee gene expression. (p. 222) At the time WWA was published, RTB expected future genomic comparisons to widen the gap between humans and chimpanzees. (p. 223)

The RTB model and primate genomics (2006): Creation as Science

In early September 2005, a full comparison between the completed chimpanzee genome and the human genome was published in the prestigious journal Nature. This landmark paper used a sample size of 2.9x10⁹ base pairs: it covered virtually the entire genomes of both species, dwarfing previous comparisons (Table 1). This comparison returned results consistent with previous studies: homology excluding indels was over 98%; including indels brought it down to 95%. As expected, the 2003 Anzai et al., paper (that found 87% homology including indels in one chromosomal region) was shown to be an inappropriate estimate for the genome as a whole. Beyond its wide impact in the biological sciences, this paper also received much attention from the mainstream media. This work, however, did not make any discernable difference to the RTB model. In 2006, another major RTB book, Creation as Science (CAS), appeared. In contrast to the lengthy, detailed discussion of human / chimpanzee comparative genomics in WWA, CAS has only a brief section as follows:

New research, however, indicates that the widely advertised 98 to 99 percent similarity between human and chimpanzee DNA is greatly exaggerated. Such claims are based on small segments of the human and chimpanzee genomes where common sense dictates that the similarities would be the greatest. While comparisons between the complete human genome and the complete chimpanzee genome have only recently begun, the most complete comparisons performed thus far indicate that the degree of similarity is more like 85 to 90 percent. (p. 156)

The above paragraph from CAS cites four research publications, each of which was previously cited in WWA: Anzai et al., 2003; Thomas et al, 2003; Arnason et al., 1996; and the Chromosome 22 Consortium paper of 2004 (Table 1). Surprisingly, CAS makes no mention of the actual whole-genome study published between WWA and CAS. On encountering this, I initially assumed that Ross and Rana were simply unaware at the time CAS went to press that the chimpanzee genome had been completed, or that perhaps they had mistaken the Anzai paper as a whole-genome analysis. Further investigation, however, failed to support these hypotheses. First, in an article published in 2004 in the RTB periodical Connections, Rana emphasizes that the Anzai paper is not a whole genome comparison and discusses its actual data set in detail:

Though these whole-genome comparisons are not yet possible, scientists are close, and preliminary results indicate that humans and chimpanzees are really not so genetically similar… another study found only 86.7% genetic similarity when segments of human and chimpanzee DNA (totaling 1,870,955 base pairs) were laid side by side.

Thus Rana correctly understands that the Anzai paper is not a whole-genome comparison. Secondly (and more significantly), Rana does mention the key 2005 whole-genome paper in the very first 2006 edition of Connections, and notes correctly that it is a whole-genome study:

Where were you on September 1, 2005? Perhaps you missed the announcement of a scientific breakthrough: the influential journal Nature published the completed sequence of the chimpanzee genome. This remarkable achievement received abundant publicity because it paved the way for biologists to conduct detailed genetic comparisons between humans and chimpanzees.

Rana uses this as an introduction to discuss another article from the same journal issue and does not discuss this key paper or its results, beyond a footnote referring readers to WWA. While this Connections article does not have a precise publication date, Rana cites accession of online material for this article as occurring on November 30, 2005. Other articles in this edition of Connections also cite access dates in late November 2005, suggesting that this volume was drafted in late 2005 for publication early in 2006. The chapter in CAS discussing human / chimpanzee genomics has references to online material cited as accessed in April 2006, indicating that this chapter was still in revision at this time. Taken together, these lines of evidence strongly suggest that RTB was aware of the key 2005 paper at the time the CAS chapter was in preparation, and that they correctly understood its significance as the first whole-genome comparison. The choice of language in CAS also supports this conclusion, since the chapter claims that “… comparisons between the complete human genome and the complete chimpanzee genome have only recently begun…” which makes sense only if both genomes were sequenced at the time of its writing. Despite this concession, CAS makes no mention of the key 2005 paper or its findings, and claims rather that “the most complete comparisons performed thus far” support homology values in the 85-90% range. In reality, only the Anzai paper, which covered a small chromosomal region expected to be disproportionately different between the two species, supports this value (Table 1).

The RTB model and primate genomics (2009): More Than a Theory

The next major RTB publication dealing with human - chimpanzee genomic comparisons was More Than a Theory (MTT) published in 2009. The relevant passage in MTT is a lightly reworked version of what appears in CAS, with only one notable change: whereas CAS acknowledges that comparisons between the completed genomes are underway, MTT claims they have not yet been done (Figure 1).

Like CAS, MTT claims “the most complete analyses performed so far” indicate homology values in the 85-90% range, makes no mention of the key 2005 whole-genome comparison paper, and again cites exactly the same references as CAS, the most recent being the 2004 consortium paper (Table 1). Thus, four years after they were aware of the key 2005 paper, there is still no mention of it to be found in the RTB framework; moreover, MTT claims such an analysis has never been performed.

The RTB model and primate genomics – present day

The pattern we have seen in the major RTB books continues into the present. Rana, for example, continues to argue that the best estimate of whole-genome human chimpanzee homology is at best 90%. For example, during a recent podcast discussion of the completed western clawed frog genome (Xenopus tropicalis) Rana claims: “It’s common parlance that humans and chimps have a 99% genetic similarity. The actual data indicates probably it’s closer to 90% similarity as opposed to 99% similarity” before going on to imply that the higher value can only be supported through comparisons of specific genes. He then goes on to claim that sequenced frog genome shows 80% similarity to the human genome based on “the same reasoning.” The argument he makes is an attempt to cast doubt on the relevance of the human / chimpanzee comparison: if humans and chimps are 90% similar and humans and frogs are 80% similar, Rana claims these “are not meaningful comparisons in a biological sense.” Rana’s argument, however, is deeply flawed in that he is comparing two very different measures of similarity and claiming they are equivalent. The human / chimpanzee value, as we have seen, is 95% genome-wide identity (including indels) for the completed genomes of both species compared across approximately three billion DNA base pairs (Table 1). The 80% value Rana touts for the human / frog comparison, however, is merely a measure of the percentage of genes in the frog genome that have a similar gene in humans implicated in a human disease. It is not even a measure of the genetic similarity of those genes, but merely a fraction of the genes identified in frog that might be useful for studying human diseases. Rana, however, presents these two values as equivalent measures in an attempt to disparage human / chimpanzee genomic similarity. In reality, the genome-wide homology between Xenopus tropicalis and humans is slightly over 30%.

Taken together, these findings demonstrate the following: (a) RTB carefully followed the primary literature on human / chimpanzee comparative genomics up until and including a major paper published in 2004, even if it represented such studies selectively to their constituents; (b) RTB was aware of the key 2005 whole-genome study and correctly understood its implications at the time the first 2006 edition of Connections was drafted in late 2005; (c) RTB has made no mention of this paper (nor any paper in this field published since 2004) in two major works published after this paper was available; (d) RTB continues to claim, five years after this paper was published, that the most recent and most extensive evidence supports their preferred value of 85-90% homology (and that higher values can only be supported with small, biased samples), despite the fact that this conclusion is starkly at odds with the best and most extensive study available, and is itself derived from a comparatively small, biased sample; and (e) RTB has shifted from acknowledging (in 2006) that whole-genome comparisons have been done to denying (in 2009) that they ever have.

In the second part of this series, Dr. Venema will continue his evaluation of the RTB model by examining how it approaches a second powerful line of evidence for human evolution: pseudogenes.

A Response from Dr. Rana: “Creation as Science (2006) was initially published by NavPress and More Than a Theory (2009) was published by Baker as a reworking of Creation as Science. There was an urgency to get More than a Theory to the publisher so that it would be released to coincide with the Darwin Day Celebration. Hugh Ross intended both books to be an overview and summarized material from Who Was Adam? (2005) which was published before the whole genome work on the chimpanzee was published. This explains why the work on the whole chimpanzee genome was not mentioned in More than a Theory. There was nothing done to be deliberately deceptive regarding the failure to mention the work on the whole genome of the chimpanzee.”

Notes

1. For a review of these lines of evidence, see Venema, D.R. (2010). Genesis and the genome: genomics evidence for human – ape common ancestry and ancestral hominid population sizes. Perspectives on Science and Christian Faith 62 (3), 166-178.
2. Ross, Hugh. More Than a Theory: Revealing a Testable Model for Creation. Grand Rapids: Baker Books, 2009, p. 21.
3. Rana, Fazale and Ross, Hugh. Who Was Adam? A Creation Model Approach to the Origin of Man. Colorado Springs: NavPress, 2005, p. 223; Ross, Hugh. Creation as Science: A Testable Model Approach to End the Creation / Evolution Wars. Colorado Springs: NavPress, 2006, p. 156; and More Than a Theory, p. 187-188.