Carl Zimmer writes about AlphaGenome

We may not know a lot about how artificial intelligence (AI) algorithms work but the one thing we do know is that they are only as good as their databases. If you ask an AI program to tell you when Charles Darwin was born then chances are good it's going to give you the correct answer because that information is in Wikipedia and lots of other reliable online sources.

However, if you ask it to tell you how many genes are in the human genome it will not give you the correct answer. The correct answer is that we don't know for sure because it depends on how you define a gene and how many non-coding genes there are using various definitions. That's not the answer you will get. (I personally believe that there are only about 1000 non-coding genes but I don't expect a good "intelligence" program to favor my view over others. I DO expect it to not favor other opinions over mine.)

I just asked ChatGPT and it told me that there are tens of thousands of non-coding genes based on the Human Genome Project plus GENCODE and Ensemble annotations. This is correct ... and misleading. It's giving the best answer it can based on the databases it searches. However, many of us are skeptical of the GENCODE and Ensemble annotations and for good reason. They tend to err on the side of inclusion in order to avoid false negatives. In other words, they don't want to risk ignoring a real biologically relevant feature for lack of evidence so they deliberately risk including a lot of false positives. This is why those databases include a lot of questionable features such as non-coding genes, multiple transcription start sites, multiple splice variants, and tons of potential regulatory elements.

Along comes AlphaGenome. It's an AI program designed to scan those GENCODE and Ensemble databases to identify important features that might play a role in genetic diseases. What could possibly go wrong? [How intelligent is artificial intelligence?] [Will AlphaGenome from Google DeepMind help us understand the human genome?]

The average science writer jumped all over the original announcement of AlphGenome to let us all know that artificial intelligence was going to solve the problem of the mysterious genome. Apparently the complexity of the human genome has astonished scientists ever since the first human genome sequence was published 25 years ago.¹ The typical article on AlphaGenome fits nicely into the common theme that AI is soon going to rule the world.

That's why I was excited to pick up my copy of the New York Times yesterday and see that Carl Zimmer had written about AlphaGenome. Finally, an intelligent, highly respected, science writer was going to give us the truth. Here's the article that I saw in my version of the paper. (It was originally published several weeks ago on January 28, 2026.)

What a disappointment! Zimmer goes with the hype about AlphaGenome and repeats some of the tropes that he has avoided in the past. For example, he writes about how alternative splicing can create hundreds of different proteins from a single gene and how regulatory sequences can lie thousands or million of base pairs away from a gene. (There's no question that this is true for a small number of transcription factor binding sites but the vast majority are close to the promoter.)

Zimmer gives an example showing that AlphaGenome identified a regulatory sequence for a gene called TAL1, implying that the program will help decipher the rest of the genome. The general tone of the newspaper article is that AlphaGenome will be of great help to scientists who want to understand the human genome.

I checked the online version of Carl Zimmer's article in order to prepare for this blog post. I was surprised to see that there were lots of things in the online version that weren't in the newspaper article. For example, Zimmer quotes my colleague Alex Palazzo saying that everybody uses AlphaFold to study proteins then later on in the article Zimmer notes that, "But the more scientists studied the human genome, the more complicated and messy it turned out to be." The newspaper article left out the words "and messy" and that's significant because junk DNA supporters like Alex Palazzo often refer to the human genome as "messy" and full of junk DNA and that's a very different perspective than opponents of junk DNA who emphasize things like "complicated" and "mysterious."²

Zimmer has an even more revealing section that's in the online version but not the newspaper version.

Peter Koo, a computational biologist at Cold Spring Harbor Laboratory in New York who was not involved in the project, said that AlphaGenome represented an important step forward in applying artificial intelligence to the genome. “It’s an engineering marvel,” he said.

But Dr. Koo and other outside experts cautioned that it represented just one step on a long road ahead. “This is not AlphaFold, and it’s not going to win the Nobel Prize,” said Mark Gerstein, a computational biologist at Yale.

AlphaGenome will be useful. Dr. Gerstein said that he would probably add it to his toolbox for exploring DNA, and others expect to follow suit. But not all scientists trust A.I. programs like AlphaGenome to help them understand the genome.

“I see no value in them at all right now,” said Steven Salzberg, a computational biologist at Johns Hopkins University. “I think there are a lot of smart people wasting their time.”

The end of the online article is quite different from the final paragraphs of the newspaper article. In the newspaper article, Zimmer describes the TAL1 result then ends it with the paragraph starting with "In reality." I've highlighted that paragraph in the quotations below from the online version.

The AlphaGenome researchers shared their TAL1 predictions with Dr. Marc Mansour, a hematologist at University College London who spent years uncovering the leukemia-driving mutations with lab experiments.

“It was quite mind-blowing,” Dr. Mansour said. “It really showed how powerful this is.”

But, Dr. Mansour noted, AlphaGenome’s predictive powers fade the farther its gaze strays from a particular gene. He is now using AlphaGenome in his cancer research but does not blindly accept its results.

“These prediction tools are still prediction tools,” he said. “We still need to go to the lab.”

Dr. Salzberg of Johns Hopkins is less sanguine about AlphaGenome, in part because he thinks its creators put too much trust in the data they trained it on. Scientists who study splice sites don’t agree on which sites are real and which are genetic mirages. As a result, they have created databases that contain different catalogs of splice sites.

“The community has been working for 25 years to try to figure out what are all the splice sites in the human genome, and we’re still not really there,” Dr. Salzberg said. “We don’t have an agreed-upon gold-standard set.”

Dr. Pollard also cautioned that AlphaGenome was a long way from being a tool that doctors could use to scan the genomes of patients for threats to their health. It predicts only the effects of a single mutation on one standard human genome.

In reality, any two people have millions of genetic differences in their DNA. Assessing the effects of all those variations throughout a patient’s body remains far beyond AlphaGenome’s industrial-strength power.

“It is a much, much harder problem — and yet that’s the problem we need to solve if we want to use a model like this for health care,” Dr. Pollard said.

The net effect of these differences is to transform the article from one that promotes AlphaGenome in the newspaper version to one that's far more skeptical in the online version. I believe that the online version is far more accurate and reflects the high standard that I expect from Carl Zimmer. I'm assuming that the newspaper article was edited for the New York Times supplement that I read and I'm assuming that Zimmer did not approve of that edit.

Note: The cartoon was generated by ChatGPT in response to the request, "draw a cartoon illustrating GIGO - garbage in garbage out."

Note: The photo is from 10 years ago when Carl was in Toronto working on his junk DNA article for The New York Times [Is Most of Our DNA Garbage?]. That's Alex Palazzo on the left, then me, Ryan Gregory, and Carl Zimmer on the right.

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1. Most knowledgeable scientists were not astonished to learn that 90% of our genome really is junk and there are fewer than 30,000 genes.

2. See the last chapter of my book: "Chapter 11: Zen and the Art of Coping with a Sloppy Genome."

How intelligent is artificial intelligence?

Over the past few years I've been assessing AI algorithms to see if they can answer difficult questions about junk DNA, alternative splicing, evolution, epigenetics and a number of other topics. As a general rule, these AI algorithms are good at searching the internet and returning a consensus view of what's out there. Unfortunately, the popular view on some of these topics is wrong and most AI algorithms are incapable of sorting the wheat from the chaff.

In most cases, they aren't even capable of recognizing that there's a controversy and that their preferred answer might not be correct. They are quite capable of getting their answer from known kooks and unreliable, non-scientific, websites, [The scary future of AI is revealed by how it deals with junk DNA].

Others have now recognized that there's a problem with AI so they devised a set of expert questions that have definitive, correct, answers but the answers cannot be retrieved by simple internet searches. The idea is to test whether AI algorithms are actually intelligent or just very fast search engines that can summarize the data they retrieve and create an intelligent-sounding output.

Is epigenetics one of the best ideas of the 21st century?

New Scientist has produced a special issue on the best ideas of the 21st century. Here's the complete list.

The Third Way Evolution Conference

The Third Way of Evolution is a strange organization composed of mavericks who think they're not getting enough attention. Here's how they describe their movement.

The vast majority of people believe that there are only two alternative ways to explain the origins of biological diversity. One way is Creationism that depends upon intervention by a divine Creator. That is clearly unscientific because it brings an arbitrary supernatural force into the evolution process. The commonly accepted alternative is Neo-Darwinism, which is clearly naturalistic science but ignores much contemporary molecular evidence and invokes a set of unsupported assumptions about the accidental nature of hereditary variation. Neo-Darwinism ignores important rapid evolutionary processes such as symbiogenesis, horizontal DNA transfer, action of mobile DNA and epigenetic modifications. Moreover, some Neo-Darwinists have elevated Natural Selection into a unique creative force that solves all the difficult evolutionary problems without a real empirical basis. Many scientists today see the need for a deeper and more complete exploration of all aspects of the evolutionary process.

Answers in Genesis uses the latest DNA research to destroy evolutionary proof (not!)

There's been so much bad news this week that I though you might enjoy a little humor to lighten your day. Here are some devout Young Earth Creationists making fun of some stupid comments they've found on the internet and calling on some professor to "destroy" evolutionists who believe in junk DNA [Latest in DNA Research Destroys Evolutionary “Proof”].

Even more regulatory elements?

The expression of genes is regulated at many levels but one of the most important is regulation at the level of transcription. Transcription initiation is controlled by transcription factors that bind to sequences near the promoter and either activate or repress transcription.

A lot of work has been done on transcription regulation in mammals over the past 40 years. The general impression from these detailed studies of individual genes is that regulation usually involves a relatively small number of transcription factors that bind to sequences within 1000 bp or so of the transcription start site.

This model was challenged by the ENCODE studies in 2012. ENCODE researchers claimed to have discovered hundreds of thousands of cis-regulatory elements (CRE's) covering a substantial percentage of the genome. If they are correct, then this means that there are dozens of transcription factors controlling the expression of every gene.

Will AlphaGenome from Google DeepMind help us understand the human genome?

I recently reported that Google's AI program does a horrible job of summarizing the junk DNA controversy. [The scary future of AI is revealed by how it deals with junk DNA] That led to a discussion about the "intelligence" in artificial intelligence and whether AI was capable of distinguishing between accurate and inaccurate data.

Google DeepMind is an artificial intelligence research laboratory headquartered in London, UK. Two of its programmers, Demis Hassabis and John Jumper, were awarded the 2024 Nobel Prize in Chemistry for developing AlphaFold, a program that predicts the tertiary structure of proteins.

The activity of "random" DNA supports the junk DNA model

I complain a lot about the quality of science writing but today's post is very different. I want to highlight an article by Michael Le Page that he just published in New Scientist. It's one of the best articles on junk DNA that I've ever seen in popular science magazines and newspapers [Human-plant hybrid cells reveal truth about dark DNA in our genome].

I've admired Michael Le Page for many years because of his articles on climate change and evolution. It doesn't surprise me that he's right about junk DNA.

The scary future of AI is revealed by how it deals with junk DNA

Today I did a Google search for the term "JUNK DNA" and, as usual, the first thing I saw was the Google AI description of junk DNA. It's wrong, but that's not the scary part. The most frightening thing about the AI description is that it promotes three videos that misrepresent science and two of them are from well known kooks.

What does this tell you about current versions of AI? It tells you that it is not intelligent in any meaningful sense of the word. It tells you that Google AI is incapable of distinguishing between scientific facts and ignorance. It tilts toward the loudest voices on the internet and, as we all know, those voices are frequently wrong.

How many lncRNA genes in the human genome? (2025)

There is considerable controversy over the total number of genes in the human genome. The number of protein-coding genes is pretty well established at somewhere between 19,500 and 20,000. It's the number of non-coding genes that's disputed.

There's general agreement on the number of well-defined small RNA genes such as snRNAs, snoRNA, microRNAs etc. Similarly, the number of ribosomal RNA and tRNA genes is known. The problem is with identifying genuine long non-coding RNA genes (lncRNA genes). Estimates vary from less than 20,000 to more than 200,000 but most of these estimates fail to define what they mean by "gene." Many scientists seem to think that any detectable transcript must come from a gene.

This doesn't make any sense since we know that spurious transcripts exist and they don't come from genes by any meaningful definition of gene. The only reasonable definition of a molecular gene is a DNA sequence that's transcribed to produce a functional product.¹

The idea that spurious, non-functional, transcripts exist has been described in the scientific literature for many decades. One of my favorites is in a paper by Ponting and Haerty (2022) quoting another paper from thirteen years ago by Ulitsky and Bartel.

The cellular transcriptional machinery does not perfectly discriminate cryptic promoters from functional gene promoters. This machinery is abundant and so can engage sites momentarily depleted of nucleosomes and rapidly initiate transcription. The chance occurrence of splice sites can then facilitate the capping, splicing, and polyadenylation of long transcripts. A very large number of such rare RNA species are detectable in RNA-sequencing experiments whose properties are virtually indistinguishable from those of bona fide lncRNAs. Consequently, “a sensible [null] hypothesis is that most of the currently annotated long (typically >200 nt) noncoding RNAs are not functional, i.e., most impart no fitness advantage, however slight” (Ulitsky and Bartel, 2013: p. 26).

The important point here is that the correct null hypothesis is that these transcripts don't have a biologically relevant function and the burden of proof is on researchers to demonstrate function before assigning them to a genuine gene. My colleagues at the University of Toronto made the same point in a paper published in 2015.

In the absence of sufficient evidence, a given ncRNA should be provisionally labeled as non-functional. Subsequently, if the ncRNA displays features/activities beyond what one would expect for the null hypothesis, then we can reclassify the ncRNA in question as being functional. (Palazzo and Lee, 2015)

There are a number of well-defined lncRNAs that have been shown to have distinct reproducible functions. The key question is how many of these biologically relevant lncRNA genes exist in the human genome. I struggled with the answer to this question when I was writing my book. I finally decided to make a generous estimate of 5000 non-coding genes and that implies several thousand lncRNA genes (p. 127). I now think that estimate was far too generous and there are probably fewer than 1000 genuine lncRNA genes.

I have not scoured the literature for all the examples of human lncRNAs having good evidence of function but my impression is that there are only a few hundred. This post was incited by a recent publication by researchers from the Hospital for Sick Children and the University of Toronto (Toronto, Canada) who characterized another functional lncRNA called CISTR-ACT that plays a role in regulating cell size (Kiriakopulos et al., 2025).

I was prompted to revisit this controversy by the accompanying press release that said ...

Unlike genes that encode for proteins, CISTR-ACT is a long non-coding RNA (or lncRNA) and is part of the non-coding genome, the largely unexplored part that makes up 98 per cent of our DNA. This research helps show that the non-coding genome, often dismissed as ‘junk DNA’, plays an important role in how cells function.

We're used to this kind of misinformation² in press releases but I thought it would be a good idea to read the paper. As I expected, there's nothing in the paper about junk DNA but here's the first sentence of the introduction.

The human genome contains more long non-coding RNAs (lncRNAs) than protein-coding genes (GENCODE v49) which regulate genes and chromatin scaffolding.

The latest version of GENCODE Release 49 claims that there are 35,899 lncRNA genes. This is the only reference in the Kiriakopulos et al. paper to the number of lncRNA genes. There's no mention of the controversy and none of the papers that discuss the controversy are referenced.

The GENCODE number is close to the latest version of Ensembl, which lists 35,042 lncRNA genes. I couldn't find any good explanation for these numbers or for the definition of "gene" that they are using but what's interesting is how these numbers are climbing every year; for example, a paper from two years ago listed a number of sources and you can see that the RefSeq and GENCODE numbers are much smaller than today's numbers (Amaral et al., 2023).³

We intend to provoke alternative interpretation of questionable evidence and thorough inquiry into unsubstantiated claims.

Ponting and Haerty (2022)

It's perfectly acceptable to state your preferred view on lncRNAs when you publish a paper. The authors of the recent paper may want to believe that there are more lncRNA genes than protein-coding genes but I think it's important for them to define what they mean by "gene" when they make such a claim. What's not acceptable, in my opinion, is to ignore a genuine scientific controversy by not mentioning in the introduction that there are other legitimate views.

It's a shame that they didn't do that because their paper is a good example of the hard work that needs to be done in order to demonstrate that a particular lncRNA has a biologically relevant function.

In closing, I want to emphasize the recent review by Ponting and Haerty (2022)⁴ that points out the importance of the problem and the kinds of experiments that need to be done in order to establish that a given RNA comes from a real gene. This is how a scientific controversy should be addressed. Here's the abstract of that paper ...

Do long noncoding RNAs (lncRNAs) contribute little or substantively to human biology? To address how lncRNA loci and their transcripts, structures, interactions, and functions contribute to human traits and disease, we adopt a genome-wide perspective. We intend to provoke alternative interpretation of questionable evidence and thorough inquiry into unsubstantiated claims. We discuss pitfalls of lncRNA experimental and computational methods as well as opposing interpretations of their results. The majority of evidence, we argue, indicates that most lncRNA transcript models reflect transcriptional noise or provide minor regulatory roles, leaving relatively few human lncRNAs that contribute centrally to human development, physiology, or behavior. These important few tend to be spliced and better conserved but lack a simple syntax relating sequence to structure and mechanism, and so resist simple categorization. This genome-wide view should help investigators prioritize individual lncRNAs based on their likely contribution to human biology.

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1. See Wikipedia: Gene; What Is a Gene?; Definition of a gene (again); Must a Gene Have a Function?.

2. No knowledgeable scientist ever said that all non-coding DNA was junk. We've known about non-coding genes for more than half-a-century.

3. See How many genes in the human genome (2023)?

4. See Most lncRNAs are junk

Amaral, P., Carbonell-Sala, S., De La Vega, F.M., Faial, T., Frankish, A., Gingeras, T., Guigo, R., Harrow, J.L., Hatzigeorgiou, A.G., Johnson, R. et al. (2023) The status of the human gene catalogue. Nature 622:41-47. [doi: 10.1038/s41586-023-06490-x]

Kiriakopulos et al. (2025) LncRNA CISTR-ACT regulates cell size in human and mouse by guiding FOSL2. Nature communications: (in press). [doi: 10.1038/s41467-025-67591-x]

Palazzo, A.F. and Lee, E.S. (2015) Non-coding RNA: what is functional and what is junk? Frontiers in genetics 6:2(1-11). [doi: 10.3389/fgene.2015.00002]

Ponting, C.P. and Haerty, W. (2022) Genome-Wide Analysis of Human Long Noncoding RNAs: A Provocative Review. Annual review of genomics and human genetics 23. [doi: 10.1146/annurev-genom-112921-123710

Ulitsky, I. and Bartel, D.P. (2013) lincRNAs: genomics, evolution, and mechanisms. Cell 154:26-46. [doi: 10.1016/j.cell.2013.06.020]

How many regulatory sites in the human genome?

The current best model of the human genome is that only 10% is functional and 90% is junk. This model was first developed over half a century ago (see Junk DNA). From the very beginning, the model recognized that regulatory sequences would make up a significant proportion of the functional elements but early suggestions that most of the repetitive DNA would turn out to be involved in regulation were rejected.

As more and more data accumulated on regulatory sequences, it became apparent that most regulatory sequences of pol II (RNA polymerase II) genes could be found in relatively short regions of DNA just upstream of the transcription start site. It also became apparent that for each transcription factor there were thousands of transcription factor binding sites even though only a small number were actually involved in genuine gene regulation.¹

Google AI references a "Biblical Genetics" video in claiming that junk DNA is no longer considered junk

90% of the human genome is junk DNA.

Today I did a routine search for "junk DNA" "2025" to see if misinformation is still dominating the web. It is, but that's not the most surprising thing I discovered. Here's what Google AI told me at the top of the search page.

In 2025, "junk DNA" is no longer considered junk, as new studies show it plays vital roles in gene regulation and development. Research from 2025 indicates that these sequences, many of which come from ancient viruses, can act as "genetic switches" that influence how genes are turned on or off and how cells respond to their environment. This has led to potential breakthroughs in regenerative medicine and cancer treatment by providing new therapeutic targets.

This video explains how what was once considered junk DNA has been found to contain thousands of new genes:

The video is by Robert Carter who has a Ph.D. in molecular biology. His site is called Biblical Genetics. He also posts on creation.com

Carter sounds like he knows what he's talking about but he's just parroting all the misinformation that permeates the scientific literature. The main message of this video is that scientists were shocked to discover that the human genome only had 20,000 protein coding genes but we now know (no, we don't) that each gene makes many different proteins and that accounts for the "missing" complexity that all the experts had expected.¹

We also "know" (no, we don't) that scientists have discovered tens of thousands of new protein coding genes that make small proteins. He references a Science article by Elizabeth Pennisi who has been spreading misinformation about the human genome for more than 25 years.

It's not surprising that Robert Carter wants to discredit the idea of junk DNA. What's surprising is that Google AI is directing readers to a creationist video.

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1. The knowledgeable experts predicted that the human genome would have fewer than 30,000 genes and that's exactly what was found when the human genome sequence was published.

Wednesday talk at the University of Toronto: Larry Moran on "What's in Your Genome"

I'm giving a talk next Wednesday (October 1st) to the members of the Senior College (retired faculty). It's at the University of Toronto Faculty Club at 10am. I'll talk for 50 mins then there's a coffee break followed by 50 mins of questions and discussion.

Guests are welcome but you'll have to pay $10 to cover the cost of coffee and cookies. You can also register to watch my talk on Zoom. You can also stay for lunch at the Faculty CLub but you'll have to let me know so I can put you down as a guest.

Here's the link to register: What's in Your Genome?

 

Wednesday Talk: Wednesday, October 1, 2025, 10am-12pm.

In-person at the Faculty Club and on Zoom

Larry Moran, Biochemistry, University of Toronto

Title: “What’s in Your Genome?”

Abstract: Scientists have been studying the human genome for more than 70 years but today there is considerable controversy about what’s in our genome. The publication of the complete sequence of the human genome in 2001 did nothing to resolve the controversy. For many scientists, the data confirmed their predictions that we have about 30,000 genes and most of our genome is useless junk DNA. Other scientists were shocked to learn that we have so few genes so they began the search for other explanations. Today, the majority of molecular biologists and biochemists believe that most of our genome is functional and there may be as many as 100,000 extra genes that weren’t identified in 2001. The majority of experts in molecular evolution disagree —they believe that 90% of our genome is junk DNA. I will summarize the data from both sides of the controversy and discuss the role that science journalism has played in misrepresenting scientific discoveries about the human genome.

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Endogenous retrovirus sequences can be transcriptionally active: the reality vs. the hype

A recent paper on characterizing endogenous retrovirus sequences has attracted some attention because of a press release from Kyoto University that focused on refuting junk DNA. But it turns out that there's no mention of junk DNA in the published paper.

Let's start with a little background. Retroviruses are RNA viruses that go though a stage where their RNA genomes are copied into DNA by reverse transcriptase. The virus may integrate into the host genome and be carried along for many generations producing low levels of virus particles [Retrotransposons/Endogenous Retroviruses]. The integrated copies are called endogenous retroviruses (ERVs).

Our genome contains about 31 different families of ERVS that have integrated over millions of years. Most of the original virus genomes have acquired mutations, including insertions and deletions, and they are no longer active. These sequences account for about 8% of our genome.

Predatory journals are helping to spread misinformation in the scientific literature

At the end of last year (2024) I posted an article about distinguished molecular biologist William Hasletine who published an article in Forbes about A New Dogma Of Molecular Biology: A Paradigm Shift. The article was about overthrowing the Central Dogma of Molecular Biology because of the discovery of thousands of non-coding genes. There is no paradigm shift. It's a paradigm shaft. [William Haseltine misrepresents molecular biology and calls for a paradigm shift]

Is AI really "intelligent"? Here are 13 biology questions to test the latest AI algorithms.

Last night I attended a talk by Chris DiCarlo who warned us about the dangers of AI. I'm sure he's right to be worried but I'm skeptical about some of the hype surrounding AI. For example, Chris said that just a few years ago the best AI algorithms were performing at high school level but now they are at Ph.D. level. The implication is that it won't be long before AI is smarter than humans.

Here's the problem. I can only access the cheap versions of AI such as ChatGPT and Scite Assistant but I can also see the results of Google's Generative AI whenever I do a Google search. Chris has access to more sophisticated versions so that's what he might be referring to when he says they operate at the Ph.D. level of intelligence.

A new higher mutation rate in humans includes indels in repetitive DNA regions

Theme

Mutation

-definition
-mutation types
-mutation rates
-phylogeny
-controversies

There are three ways of estimating the human mutation rate. The Biochemical Method is based on the known error rate of DNA replication and the average number of cell divisions between generations. It gives a rate of about 130 mutations per generation.

The Phylogenetic Method assumes that a large fraction of mammalian genomes is evolving at the neutral rate because it is junk DNA. Since we know that the rate of fixation of neutral alleles is equal to the mutation rate, we can estimate the mutation rate if we know the total number of nucleotide difference between two species (e.g. humans and chimpanzees) and the approximate time of divergence from a common ancestor. This gives an estimate of about 112 mutations per generation.

L'ADN poubelle: Junk DNA

This is a podcast in French on the topic of junk DNA. The moderator is Thomas C. Durand of La Tronche en Biais, a YouTube channel that focuses on critical thinking. Durand interviews two scientists from l’Université Paris Cité (City University of Paris), Didier Casane and Patrick Laurenti.

It's a two hour video that discusses all the relevant topics on the human genome and junk DNA. The most exciting part for me comes at 56 mins when the moderator asks Casane and Laurenti to recommend a book on the subject (see screenshot on right). Patrick Laurenti suggests that my book should be translated into French but I don't think that's going to happen.

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American Society of Human Genetics DNA Day essay contest winners

The American Society of Human Genetics sponsors an annual DNA Day Essay Contest. It's for grade 9-12 students from anywhere in the world.

This year's question is ...

Templeton Foundation funds a grant on transposons

The John Templeton Foundation supports "interdisciplinary research and catalyze conversations that enable people to pursue lives of meaning and purpose." Many of these projects have religious themes or religious implications. The foundation is well-known for its support of projects that promote the compatibility of science and religion. You can see a list of recent grants here.

Templeton recently awarded a grant of $607,686 (US) to study the role of transposons in the human genome. The project leader is Stefan Linquist, a philosopher from the University of Guelph (Guelph, Ontario, Canada). Stefan has published a number of papers on junk DNA and he promotes the definition of functional DNA as DNA that is subject to purifying selection [The function wars are over]. Other members of the team include Ryan Gregory and Ford Doolittle who are prominent supporters of junk DNA.