Friday, July 14, 2017

Revisiting the genetic load argument with Dan Graur

The genetic load argument is one of the oldest arguments for junk DNA and it's one of the most powerful arguments that most of our genome must be junk. The concept dates back to J.B.S. Haldane in the late 1930s but the modern argument traditionally begins with Hermann Muller's classic paper from 1950. It has been extended and refined by him and many others since then (Muller, 1950; Muller, 1966).

Several prominent scientists have used the genetic load data to argue that most of our genome must be junk (King and Jukes, 1969; Ohta and Kimura, 1971; Ohno, 1972). Ohno concluded in in 1972 that ...
... all in all, it appears that calculations made by Muller, Kimora and others are not far off the mark in that at least 90% of our genome is 'junk' or 'garbage' of various sorts.
It's important to keep in mind that the genetic load argument is one of the Five Things You Should Know if You Want to Participate in the Junk DNA Debate. It's also very important to understand that this is positive evidence for junk DNA based on fundamental population genetics. It refutes the popular view that the idea of junk DNA is just based on not knowing all the functions of our genome. There's delicious irony in being accused of argumentum ad ignorantiam by those who are ignorant.

I've discussed gentic load several times on this blog (e.g. Genetic Load, Neutral Theory, and Junk DNA) but a recent paper by Dan Graur provides a good opportunity to explain it once more. The basic idea of Genetic Load is that a population can only tolerate a finite number of deleterious mutations before going extinct. The theory is sound but many of the variables are not known with precision.

Let's see how Dan handles them in his paper (Graur, 2017). In order to calculate the genetic load (or mutation load), we need to know the size of the genome, the mutation rate, and the percentage of mutations that are deleterious. Dan Graur assumes that the diploid genome size is 6.114 × 109 bp based on accurate cytology measurements from 2010. I think the DNA sequence data is more accurate so I would use 6.4 Gb. The difference isn't important.

There's a huge literature on mutation rates in humans. We don't know the exact value because there's a fair bit of controversy in the scientific literature. The values range from about 70 new mutations per generation to about 150 [see: Human mutation rates - what's the right number?]. Graur uses a range of mutation rates covering these values. He expresses them as mutations per site per generation which translates to values from 1.0 × 10-8 to 2.5 × 10-8. As we shall see, he calculates the genetic load for a range of mutation rates order to get an upper limit to the amount of functional DNA in our genome.

The most difficult part of these calculations is estimating the percentage of mutations that are beneficial, neutral, and deleterious. Population geneticists have rightly assumed that the number of beneficial (selected) mutations is insignificant so they concentrate on the number of deleterious mutations. The estimates range from about 4% of the total mutations to about 40% of the total based on the analysis of mutations in coding regions.

Most scientists assume that the correct value is about 10% of the total. What this means is that if there are 100 new mutations in every newborn there will be about 10 deleterious mutations if the entire genome is functional. If only 10% is functional then there will be only 1 deleterious mutation per generation. A mutation load of about one deleterious mutation per generation is the limit that a population can tolerate. Graur assumes 0.99. Others have proposed that the mutation load could be higher (Lynch, 2010; Agrawal and Whitlock, 2012) but it's unlikely to be more than 1.5. The difference isn't important.

Graur calculates a range of deleterious mutation rates (μdel) based on multiplying the percentage of deleterious mutations times the total number of mutations.

The other variable is the replacement level fertility of humans (F). Think of it this way: if every child has a significant number of deleterious mutations then the population can still survive if every couple has a huge number of children. Statistically, some of them will have fewer deleterious mutations and those ones will survive. If F = 50 then in order to get one survivor each person needs to have 50 children (or each couple needs to have 100 children).

Historical data suggests that the range of values goes from 1.05 to 1.75 per person (2.1 to 3.5 children per couple). Graur makes the reasonable assumption that the maximum sustainable replacement level fertility rate is 1.8 per person in human populations over the past million years or so.

The important part of the Graur paper is the table he constructs where he estimates the number of deleterious mutations by combining the mutation rate and the percentage of deleterious mutations on the y-axis and the fraction of the genome that may be functional on the x-axis. At the intersection of each value he calculates the minimum replacement level fertility values required to sustain the population.

Let's look at the first line in this table. The deleterious mutation rate is calculated using the lowest possible mutation rate and the smallest percentage of deleterious mutations (4%). Under these conditions, the human population could survive with a fertility value of 1.8 as long as less than 25% of the genome is functional (i.e. 75% junk) (red circle). That's the UPPER LIMIT on the functional fraction of the human genome.

But that limit is quite unreasonable. It's more reasonable to assume about 100 new mutations per generation with about 10% deleterious. Using these assumptions, only 10% of the genome could be functional with a fertility value of 1.8 (green circle).

Whatever the exact percentage of junk DNA it's clear that the available data and population genetics point to a genome that's mostly junk DNA. If you want to argue for more functionality then you have to refute this data.

Note: Strictly speaking, the genetic load argument only applies to sequence-specific DNA where mutations have a direct effect on function. Some DNA serves as necessary spacers between functional sequences and this DNA will only be affected by deletion mutations. This is a small percentage of the genome. However, there are bulk DNA hypotheses that attribute non-sequence specific function to most of the genome and if they are correct the genetic load argument carries no weight. So far, there is no good evidence that these bulk DNA hypotheses are valid and most objections to junk DNA are based on sequence-specific functions.

Agrawal, A. F., and Whitlock, M. C. (2012) Mutation load: the fitness of individuals in populations where deleterious alleles are abundant. Annual Review of Ecology, Evolution, and Systematics, 43:115-135. [doi: 10.1146/annurev-ecolsys-110411-160257]

Graur, D. (2017) An upper limit on the functional fraction of the human genome. Genome Biol Evol evx121 [doi: 10.1093/gbe/evx121]

King, J.L., and Jukes, T.H. (1969) Non-darwinian evolution. Science, 164:788-798. [PDF]

Lynch, M. (2010) Rate, molecular spectrum, and consequences of human mutation. Proceedings of the National Academy of Sciences, 107:961-968. [doi: 10.1073/pnas.0912629107]

Muller, H.J. (1950) Our load of mutations. American journal of human genetics, 2:111-175. [PDF]

Muller, H.J. (1966) The gene material as the initiator and the organizing basis of life. American Naturalist, 100:493-517. [PDF]

Ohno, S. (1972) An argument for the genetic simplicity of man and other mammals. Journal of Human Evolution, 1(6), 651-662. doi: [doi: 10.1016/0047-2484(72)90011-5]

Ohta, T., and Kimura, M. (1971) Functional organization of genetic material as a product of molecular evolution. Nature, 233:118-119. [PDF]


  1. Although this doesn't use the phrase "genetic load," it seems to be addressing the same topic to I think greatly different effect. Any comment?

  2. To me this shows that the word junk is bad in describing these part of the genome. It should be called the buffer area or something like that.

    1. About 90% of our genome is nonfunctional DNA. We've been calling it "junk" for the past 45 years Why would you want to call this nonfunctional DNA "buffer" unless you have evidence that it has such a function?

    2. Good post. I've always thought mutational load argument merited more emphasis as strong support for lots of junk DNA in 3+ Gb mammalian genomes.

  3. If I am understanding the data correctly, what it actually points to is the maximum size of human functional genome. Humans could have a genome that is nearly >90% functional if the genome was about 600 kbp.

    On the flip side, if the size of the human functional genome was larger, say 1.2 Mbp, then this would tend to select for lower mutation rates. There might be a balancing act between the size of the functional genome and the fidelity of DNA replication during meiosis.

    1. There is no evidence to support your bizarre speculation.

      BTW, the vast majority of mutations we are discussing occur during mitosis, not meiosis.

    2. Dr. Moran,

      Correct me if I am wrong, but if we took out all of the junk DNA and were left with a 600 million base diploid genome the number of mutations within the functional part of the genome would be the same since the number of mutations scales with genome size.

      As to mitosis v. meiosis, you are probably right on that one. Most mutations come from the father, and those mutations occur in sperm progenitor cells during mitosis. I guess what I was getting at is that the mutations occur in germ line cells, not somatic cells.

    3. If only 10% of our genome is functional then there are about 10 mutations per generation in the functional part of the genome. If we eliminate all the junk DNA there will still be 10 mutations per generation in the functional part of the genome.

  4. Humans have a haploid life stage, which may be important in removing deleterious mutations. Data on other eukaryotes seems to indicate that selection in the haploid life stage does have F1 and longer effects.

    Presumably these effects would be important in humans; in both haploid gametes.

    If I may speculate, senescence in haploid gametes may be a low-cost “feature” that culls deleterious mutations from the F1 generation. Senescence in the adult (observed in essentially all organisms with a haploid life stage) may be an unavoidable consequence of senescence of haploid gametes.

    1. The mutation rates are based on actual data. Even if your speculation were true it has no effect on the rate calculated from actually looking at the number of mutations per generation.

    2. Maybe not on the mutation rate per se, but perhaps on how many of the mutations that show up in the F1 generation are deleterious.

  5. Why are people so averse to the idea of junk DNA? Other than creationists, of course. I know why they don't like the idea.

    1. There are many reasons. Here's one ...

      The Deflated Ego Problem

      But the main reason is that many scientists don't understand evolution. They believe that everything is shaped by natural selection. This means that every transcript must have a purpose or it would have been eliminated by natural selection. The idea of junk DNA doesn't fit with their (false) worldview. They have no satisfactory explanation for junk.

      The other (related) problem is that they don't understand the sloppiness of biochemistry. They haven't assimilated the idea that RNA polymerase can make mistakes, the spliceosome can screw up, and some transcription factors can bind nonproductively. They tend to have a Swiss watch view of biochemistry where everything is precisely tuned to regulate and control basic cellular processes.

  6. Transcriptional landscape of repetitive elements in normal and cancer human cells

    Article · July 2014 with 46 Reads
    DOI: 10.1186/1471-2164-15-583 · Source: PubMed

    Cancer cells are acting similar to how cells behave during embryo development. This paper show increased activity of repeat sequences in cancer cells. The DNA that appears to be junk when measured in adult cells maybe very active during embryo development. If DNA was degrading due to generational mutation why would their be conservation of repetitive sequences?

    1. Nothing you said made any sense. Evolutionary Conservation is an indication the sequences aren't junk. So if they really are conserved, then no-one here is claiming it's junk DNA.

      Also, mutation in junk-DNA can create activities in that junk DNA that makes in interfere with normal cellular processes. In effect, the accumulation of mutations makes the "junk DNA" functional but in a deleterious way. For that reason, the mere fact that some piece of DNA is involved in disease like cancer doesn't actually indicate that it isn't junk-DNA.

    2. "Nothing you said made any sense. Evolutionary Conservation is an indication the sequences aren't junk. So if they really are conserved, then no-one here is claiming it's junk DNA."

      If repeat counts are not junk then Larry's estimates are off by a lot.

      ". For that reason, the mere fact that some piece of DNA is involved in disease like cancer doesn't actually indicate that it isn't junk-DNA."

      It is evidence of function during embryo development.

    3. The paper refers to transcription of retrotransposon sequences. This is not evidence of function. It's almost certainly spurious transcription of bits and pieces of transposons that still retain promoter sequences in the LTR remnants.

    4. You seem to be confused about what this study is showing. With some exceptions, transcription of TEs is generally harmful, which is why organisms need mechanisms for repressing TE activity.

      Tumors are obviously cases in which the normal cellular processes have gone awry. One aspect of this abnormal behavior is de-repression of TE activity.

  7. "Cancer cell lines display increased RNA Polymerase II binding to retrotransposons than cell lines derived from normal tissue. Consistent with increased transcriptional activity of retrotransposons in cancer cells we found significantly higher levels of L1 retrotransposon RNA expression in prostate tumors compared to normal-matched controls.

    Our results support increased transcription of retrotransposons in transformed cells, which may explain the somatic retrotransposition events recently reported in several types of cancers."

    Increased expression levels shows a changed based on the cell being in cancer or rapid cell division mode. This is usually accompanied by activation of embryonic pathways. The question is if increased expression levels is indicative of function during cell division?

    1. Do you know what "cancer" is, Bill? It's a disease, often a really, really bad one.

  8. This paper shows increase activity during embryo development. Again embryo pathways are activated in cancer cells.

    Exploratory bioinformatics investigation reveals importance of “junk” DNA in early embryo development
    Steven Xijin GeEmail author
    BMC Genomics201718:200
    DOI: 10.1186/s12864-017-3566-0© The Author(s). 2017
    Received: 13 October 2016Accepted: 7 February 2017Published: 23 February 2017

    Instead of testing predefined hypotheses, the goal of exploratory data analysis (EDA) is to find what data can tell us. Following this strategy, we re-analyzed a large body of genomic data to study the complex gene regulation in mouse pre-implantation development (PD).

    Starting with a single-cell RNA-seq dataset consisting of 259 mouse embryonic cells derived from zygote to blastocyst stages, we reconstructed the temporal and spatial gene expression pattern during PD. The dynamics of gene expression can be partially explained by the enrichment of transposable elements in gene promoters and the similarity of expression profiles with those of corresponding transposons. Long Terminal Repeats (LTRs) are associated with transient, strong induction of many nearby genes at the 2-4 cell stages, probably by providing binding sites for Obox and other homeobox factors. B1 and B2 SINEs (Short Interspersed Nuclear Elements) are correlated with the upregulation of thousands of nearby genes during zygotic genome activation. Such enhancer-like effects are also found for human Alu and bovine tRNA SINEs. SINEs also seem to be predictive of gene expression in embryonic stem cells (ESCs), raising the possibility that they may also be involved in regulating pluripotency. We also identified many potential transcription factors underlying PD and discussed the evolutionary necessity of transposons in enhancing genetic diversity, especially for species with longer generation time.

    Together with other recent studies, our results provide further evidence that many transposable elements may play a role in establishing the expression landscape in early embryos. It also demonstrates that exploratory bioinformatics investigation can pinpoint developmental pathways for further study, and serve as a strategy to generate novel insights from big genomic data.


    Single-cell RNA-seq Exploratory data analysis Pre-implantation development Early embryogenesis Transposons Repetitive DNA"

  9. Larry writes:

    > Let's look at the first line in this table. The deleterious mutation rate is calculated using the lowest possible mutation rate and the smallest percentage of deleterious mutations (4%).

    If μdel in this row is calculated based on the smallest percentage of deleterious mutations (4%) then aren't we already assuming for this row that the functional fraction of the genome is 4%? Why do we then go on to compare this value of μdel to other functional fractions of the genome?

    That is the one thing thing I don't understand about this paper - it seems that the variable μdel already incorporates the functional fraction of the genome into it - yet in the table, it is plotted against the functional fraction of the genome.

    1. We know that mutations occur and we know the approximate rate. What we don't know is what percentage of mutations in FUNCTIONAL DNA are deleterious and what percentage are neutral or beneficial.

      It's safe to ignore the beneficial mutations since those are rare. The fraction of deleterious mutations in functional DNA can be estimated from looking at coding regions where we have a pretty good idea about which mutations can be harmful. Those estimates say that more than half of the mutations are likely neutral in effect. The upper estimate of the fraction of deleterious mutations is 40% and the lowest estimate is 4%.

      If there are 100 new mutations per genome and 4% are deleterious then this means that each individual in each generation will acquire 4 deleterious mutations. That's an intolerable genetic load; it suggests that most of our genome is not a target (i.e. not functional).

      The fraction of all mutations in functional DNA that are deleterious not the same as the fraction of the genome that is junk.

  10. [T]here are bulk DNA hypotheses that attribute non-sequence specific function to most of the genome and if they are correct the genetic load argument carries no weight. So far, there is no good evidence that these bulk DNA hypotheses are valid and most objections to junk DNA are based on sequence-specific functions.

    Is there a way to tell the difference between "bulk" DNA that serves a function, albeit non-sequence-specific, and junk that is there by accident (and because effective population sizes aren't large enough) but serves at least to give mutations a somewhat safer place to go?

    I can think of widely varying genome size in reasonably closely related species. Anything else?

    1. Data on genome sizes in closely related species suggests that some species can harbor a great deal of nonfunctional (junk) DNA. This is the so-called C-Value Paradox argument. It demonstrates that there are genomes that are mostly junk.

      It's very difficult to distinguish between junk and DNA sequences that are required to bulk up the genome for some reason. The problem right now is that there are no compelling reasons to assume that such bulk DNA is necessary.

    2. I was thinking the C-Value Paradox would indicate that between among related species in similar environments, some of these species appear not to have any need for "bulk" DNA, suggesting the reason other species have it isn't due to any "bulk" function but rather simple accident of inheritance.

  11. I blame ENCODE for offering up such provocative findings that are contingent upon the interpretability of such an ambiguous term. And, while I generally agree with Grauer's thesis, I think in the end he (like ENCODE) is arguing more about semantics rather than biology. His points are good but their significance will be lost because the words being used are contextually defined and re-defined from study-to-study.

    In common parlance, I don't think that even SJ Gould would deny that spandrels (literal or biologic) served *some* "function" at *some* level (i.e., you cannot have an functional arch without the spandrels). However, I believe Gould's larger caution is very much in play in the current debate--namely that by trying to ascribe "function" to genomic regions in order to then *deduce* function is destined to result in an untestable tautology rather than a testable hypothesis.

    1. I don't think that it can be dismissed as semantics. As Larry as mentioned several times, ones choice of interpretation vastly alters their investigative approach. Assuming that all any transcribed RNAs have sequence specific biological functions often leads to a lot of wasteful research being performed. It's all too common to see months or years of time and money poured into the study of such sequences without ever first rigorously testing that said sequences have meaningful physiological or pathological functions.

    2. It is a matter of semantics. You can prove that simply by realizing that a) there is anything but consensus on what "function" means and b) authors are always compelled to offer their own definition of "function" that carries no application beyond the study at hand. Here Graur offers a definition that is indeed very well delineated--I buy it. However it is not a definition that most biologists will intuitively embrace. Too late now, but ENCODE should never have been so free with the term "functional" and Ohno should never have used the work "junk" Using common words that already carry a ton of often irrelevant baggage only muddies the waters of discourse.

    3. > However it is not a definition that most biologists will intuitively embrace

      What is wrong with a definition of function that relates it to the genetic fitness of an organism or its offspring? This seems to me to be the only obvious definition.

      I also don't understand why you think the term "junk" shouldn't be used if it is literally referring to sequences that can be removed without any effect on the organism?

    4. Ace
      "I also don't understand why you think the term "junk" shouldn't be used if it is literally referring to sequences that can be removed without any effect on the organism?"

      So do you consider genes that were required for embryo development but are since inactive junk?

    5. Bill,

      So do you consider raising absurd straw men a legitimate form of argument?

    6. John
      "So do you consider raising absurd straw men a legitimate form of argument?"
      This is not an argument. I am asking to get definitional clarification. I perviously answered a question about introns. Are they junk if their sequence is not important yet their length is. This question Larry already answered that he does not consider an intron where length matters junk.

    7. Bill,

      Then the answer to your question is "no", and it was a question that showed you have no understanding of the subject, as many of your questions and statements do.

      And I believe Larry said that he considers that intron mostly junk, unless the exact length is important, which is very unlikely.

    8. John
      "Then the answer to your question is "no", and it was a question that showed you have no understanding of the subject, as many of your questions and statements do."
      "I also don't understand why you think the term "junk" shouldn't be used if it is literally referring to sequences that can be removed without any effect on the organism?""

      So how would you validate junk DNA based on Ace's definition.

    9. Bill,

      Ah, so it was an attempt at "gotcha" after all. You must understand that the embryo is a stage of the organism, and that knockouts are not done on adult organisms but in the single-celled stage. If a bit that was knocked out turned out to be necessary for development that would be noticed, generally by having the embryo die. That's the ignorance I was talking about. Now, ignorance is no sin. The sin is in being proud of ignorance and making no attempt to repair it.

    10. Really, John? So you mean knockout organisms are not created by painstakingly going thru every single cell of an adult, and removing the specific gene one by one? Imagine that. You learn something knew every day. When one is as ignorant as Bill Cole, that is.

    11. John,

      My question is not a "gotcha" its to stimulate conversation and real discussion about the issue. Now that you have informed me of my ignorance, no actually you have assumed ignorance again just like you continually assume UCD, lets talk about other stages where the cell changes expression levels and activates non coding genes. Apoptosis, DNA repair, hypoxia are just a few examples where DNA which during resting cell measurements would appear non functional or have low expression levels. I honestly don't care how much DNA is actually functional but have found this to be a discussion about measuring ignorance. Larry is at 10% the NIH is at 80% so I guess we have a 70% ignorance factor or perhaps 90% if the NIH's figure is conservative.

    12. I can see how you might take offense when someone says you're ignorant. But stop for a minute and ask yourself whether you really are. Your question assumed, somehow, that "removed without any effect on the organism" referred to the adult organism only, or to some particular stage of development. Yes, that is indeed ignorance on display. Rather than get all huffy, just accept it. The ignorance being measured here is yours, personally, not that of anyone else.

      Now once again you make the assumption that any sequence whose function we don't know is assumed to be junk, when Larry's post to which that was a supposed comment is right there at the top of the page to point out that no, that isn't the reason. 90% of your genome is junk because of the genetic load argument, the non-conservation argument, the fugu argument, and a number of others that you are apparently incapable of noticing even when they're in front of your face (or at the top of a page).

  12. On the contrary, while authors may quibble over the specifics over the exact criteria used to categorize sequences there is a clear distinction between function as dependent on sequence specificity and the generic "functionality" of encode.

    Such a broad definition of functionality renders the term meaningless.

    Also junk was chosen as a descriptor precisely because the lay meaning is an apt metaphor. Junk DNA has the potential to see use someday, but at present sits idle taking up genomic space.