If one studies a genome sequence and comes across a region that is of the length and arrangement of a protein-encoding gene, and is enclosed but not interrupted by start and stop codons, then one can reasonably infer that this sequence is likely to be functional, even if no other evidence is yet in hand for what its potential protein product may do. If someone doubted that this were actually a protein-coding gene, then additional evidence would be expected to show this, for example by showing that it is really an artifact, or a pseudogene, or indicating that it is probably not functional despite the characteristics that suggest that it is.

Many non-genic sequences that are conserved across taxa or which exhibit characteristics consistent with regulatory regions or binding sites or structural components may be treated in the same way as finding an open reading frame as noted above. For most non-coding DNA, there is no such evidence of probable function, however. In fact, as the Sandwalk series on “junk DNA” notes, most non-coding DNA is of a type for which there is little reason to expect function. Inactive vestiges of transposable elements and pseudogenes may occasionally be functional, but there is no reason to assume that they all are given what we know about how they form. Moreover, the massive differences in genome size (i.e., amount of non-genic DNA) among taxa, including species that would be expected to have similar regulatory, mutational buffering, or structural requirements, suggests that much of it is indeed lacking in a universally applied function.

The default assumption by those who accept non-adaptive evolutionary outcomes is that much or even most of a larger genome is not functional for the cell or organism level. This is because of what we do know about these sequences, not because of what we don’t know. Therefore the burden of providing evidence to the contrary is on those who argue that all or even a large percentage of non-coding DNA has a function, which requires an explanation for the variation in DNA amount among eukaryotes in addition to empirical evidence for function at least in general terms, if not as an indication of what the function probably is.

I first became interested in genome size because of its tie-ins with important evolutionary questions in which I was (and still am) interested, such as punctuated vs. gradual patterns, levels of selection, and adaptive vs. non-adaptive processes. What I didn’t realize was that one component of the question, the quantity of DNA that is non-functional (but not necessarily inconsequential) with regard to the phenotype of the organism, is such a hot-button issue. I had vague inklings at first that young-earth creationists would object to the idea of non-functional DNA — because God, as they say, don’t make no junk. (Why intelligent design proponents, who purport to take a strictly scientific view of the question, also assume that non-coding DNA cannot be non-functional remains unstated). And of course there has always been a persistent undertone in biology that non-coding DNA must be doing something or it would have been deleted. This latter view, which derives directly from a hardcore adaptationist approach, destroys the argument by creationists that “Darwinism” has prevented researchers from considering functions for non-coding DNA. Indeed, the main motivation for the early papers on “selfish DNA” was to counter this adaptationist assumption (Doolittle and Sapienza 1980).

Creationist nonsense about DNA does not surprise me. What has intrigued me much more is the debate among biologists about this, and the rather questionable claims, suppositions, and extrapolations that get made not just by the media but by various scientists themselves.

Take Francis Collins. He’s a major player in genome biology and led the charge by the public Human Genome Project. And yet, he makes claims that non-coding DNA may be present in the genome “just in case” it needs to be put to use in the future. This makes no sense from an evolutionary perspective. It would be tempting to attribute this to Collins’s adherence to the notion of theistic evolution, but in fact one can find this sort of fuzzy foresight argument being brought up by lots of authors. I suppose it’s just disappointing that there is not better communication between genome biology and evolutionary biology.

The case that frustrates me most is that of John Mattick. He of the worst figure ever is one of the primary promulgators of the view that scientists have overlooked possible function for non-coding DNA and that this is “one of the biggest mistakes in the history of molecular biology” that can only be corrected by a “new paradigm”, and so on. Basically, the argument seems to be that much of the non-coding portion of a given genome is involved in regulation and such. In the past, Mattick has refrained from pinning down an estimate of how much non-coding DNA he believes is functional, but his presentation of (extremely selective) data left little doubt that he considers more non-coding DNA to be correlated with greater complexity. But now we’re starting to get some more explicit and increasingly bold claims.

As Check (2007) pointed out in a news article in Nature,

Mattick thinks scientists are vastly underestimating how much of the genome is functional. He and Birney have placed a bet on the question. Mattick thinks at least 20% of possible functional elements in our genome will eventually be proven useful. Birney thinks fewer are functional.

Now consider this quote by Comings (1972), who was the first person to use the term “junk DNA” extensively (even before Ohno’s (1972) coinage appeared in print):

These considerations suggest that up to 20% of the genome is actively used and the remaining 80+% is junk. But being junk doesn’t mean it is entirely useless. Common sense suggests that anything that is completely useless would be discarded. There are several possible functions for junk DNA.

So, even if Mattick is right about 20% of the human genome being functional, which is considered a rather high estimate on the basis of available data, he still would be merely agreeing with the author of the first major discussion about junk DNA.

Now, I should point out that I do not have a vested interest in how much of the human genome is functional. 5%? Fine. 20%? Fine. 50%? Ok. I will go where the data indicate. My reason for rejecting the notion of “more complexity means more DNA” is comparative: I refer you to the “onion test” for a simple illustration. However, as readers of Genomicron already know, I find it rather irksome when people take any new finding about (potential) function in some part of the human genome and extrapolate this to mean that all DNA in every genome must be serving some role.

Anyway, back to what Mattick suggests. As noted, for the most part he has gone about arguing for large-scale function more by hint than by direct claim. However, finally he says the following (Phaesant and Mattick 2007).

Thus, although admittedly on the basis of as yet limited evidence, it is quite plausible that many, if not the majority, of the expressed transcripts are functional and that a major component of genomic information is rapidly evolving regulatory DNA and RNA. Consequently, it is possible that much if not most of the human genome may be functional. This possibility cannot be ruled out on the available evidence, either from conservation analysis or from genetic studies, but does challenge current conceptions of the extent of functionality of the human genome and the nature of the genetic programming of humans and other complex organisms. [Emphasis added]

It seems to me that “we can’t rule this out” is not a reason to think that something is plausible, let alone true. In fact, the existence of mechanisms such as transposable element spread and the pseudogenization of duplicate genes suggests that there is good reason to expect much (probably most) of the genome to be non-functional unless data show otherwise. Some TEs have taken on a function, some cause disease, some are merely benign or only slightly detrimental. The proportions of non-coding elements in each of these categories remain to be determined, but they are not all equally likely by default.

The question of which sequences are functional, and in what way, is one of the more contentious and therefore interesting ones in genome biology. On the one hand, new information from various sources including the ENCODE project indicates that much non-coding is transcribed, though it remains an open question whether this has to do with function or noise. On the other hand, a recent analysis has suggested that as many as 4,000 sequences within the human genome initially thought to be genes are not really genes after all (Clamp et al. 2007), bringing the total count down to around 20,000.

Some people, mostly creationists and strict adaptationists (strange bedfellows, I agree) desperately want the vast non-coding majority of eukaryote DNA to have a function. They latch onto any new discovery of function in some segment of the genome or another (or indeed, any mere restatement of what many authors have been saying since the 1970s) and consider their position supported. The rest of us will just have to wait and see.

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References

Check, E. (2007). Genome project turns up evolutionary surprises. Nature 447: 760-761.

Clamp, M., B. Fry, M. Kamal, X. Xie, J. Cuff, M.F. Lin, M. Kellis, K. Lindblad-Toh, and E.S. Lander (2007). Distinguishing protein-coding and noncoding genes in the human genome. Proceedings of the National Academy of Sciences USA 104: 19428-19433.

Comings, D.E. 1972. The structure and function of chromatin. Advances in Human Genetics 3: 237-431.

Doolittle, W.F. and C. Sapienza. 1980. Selfish genes, the phenotype paradigm and genome evolution. Nature 284: 601-603.

Ohno, S. 1972. So much “junk” DNA in our genome. In Evolution of Genetic Systems (ed. H.H. Smith), pp. 366-370. Gordon and Breach, New York.

Phaesant, M. and J.S. Mattick (2007). Raising the estimate of functional human sequences. Genome Research 17: 1245-1253.

I recently did an interview with New Scientist for what, I am happy to say, was one of the most reasonable popular reviews of “junk DNA” that has appeared in recent times (Pearson 2007). My small section appeared in a box entitled “Survival of the fattest”, in which most of the discussion related to diversity in genome size and its causes and consequences. It even included mention of “the onion test“, which I proposed as a tonic for anyone who thinks they have discovered “the” functional explanation for the existence of vast amounts of non-coding DNA within eukaryotic genomes. Also thrown in, though not because I said anything about it, was a brief analogy to computer code: “Computer scientists who use a technique called genetic programming to ‘evolve’ software also find their pieces of code grow ever larger — a phenomenon called code bloat or ‘survival of the fattest'”.

I do not follow the literature of computer science, though I am aware that “genetic algorithms” (i.e., program evolution by mutation and selection) is a useful approach to solving complex puzzles. When I read the line about code bloat, my impression was that it probably gave other readers an interesting, though obviously tangential, analogy by which to understand the fact that streamlined efficiency of any coding system, genetic or computational, is not a given when it is the product of a messy process like evolution.

More recently, I have been made aware of an electronic article published in the (non-peer-reviewed) online repository known as arXiv (pr. “archive”; the “X” is really “chi”) that takes this analogy to an entirely different level. Indeed, the authors of the paper (Feverati and Musso 2007) claim to use a computer model to provide insights into how some eukaryotic genomes become so bloated. That is, instead of applying biological observations (i.e., naturally evolving genomes can become large) to a computational phenomenon (i.e., programs evolved in silico can become large, too), the authors flipped the situation around and decided that a computer model could provide substantive information about how genomes evolve in nature.

I will state up front that I am rarely (read: never) convinced by proof-by-analogy studies. Yes, modeling can be helpful if it provides a simplified way to test the influence of individual parameters in complex systems, but only insofar as the conclusions are then compared against reality. When it comes to something like genome size evolution, which applies to millions of species (billions if you consider that every species that has ever lived, about 99% of which are extinct, had a genome) and billions of years, one should be very skeptical of a model that involves only a handful of simplified parameters. This is especially true if no effort is made to test the model in the one way that counts: by asking if it conforms to known facts about the real world.

The abstract of the Feverati and Musso (2007) article says the following:

The development of a large non-coding fraction in eukaryotic DNA and the phenomenon of the code-bloat in the field of evolutionary computations show a striking similarity. This seems to suggest that (in the presence of mechanisms of code growth) the evolution of a complex code can’t be attained without maintaining a large inactive fraction. To test this hypothesis we performed computer simulations of an evolutionary toy model for Turing machines, studying the relations among fitness and coding/non-coding ratio while varying mutation and code growth rates. The results suggest that, in our model, having a large reservoir of non-coding states constitutes a great (long term) evolutionary advantage.

I will not embarrass myself by trying to address the validity of the computer model itself — I am but a layman in this area, and I am happy to assume for the sake of argument that it is the single greatest evolutionary toy model for Turing machines ever developed. It does not follow, however, that the authors are correct in their assertion that they “have developed an abstract model mimicking biological evolution”.

As I understand it, the simulation is based on devising a pre-defined “goal” sequence, similarity to which forms the basis of selecting among randomly varying algorithms. As algorithms undergo evolution by selection, they tend to accumulate more non-coding elements, and the ones that reach the goal most effectively turn out to be those with an “optimal coding/non-coding ratio” which, in this case, was less than 2%. The implication, not surprisingly, is that genomes evolve to become larger because this improves long-term evolvability by providing fodder for the emergence of new genes.

Before discussing this conclusion, it is worth considering the assumptions that were built into the model. The authors note that:

For the sake of simplicity, we imposed various restrictions on our model that can be relinquished to make the model more realistic from a biological point of view. In particular we decided that:

1. non-coding states accumulate at a constant rate (determined by the state-increase rate p_i) without any deletion mechanism [this is actually two distinct claims rolled into one],
2. there is no selective disadvantage associated with the accumulation of both coding and non-coding states,
3. the only mutation mechanism is given by point mutation and it also occurs at a constant rate (determined by the mutation rate p_m),
4. there is a unique ecological niche (defined by the target tape),
5. population is constant,
6. reproduction is asexual.

As noted, I am fine with considering this a fantastic computer simulation — it just isn’t a simulation that has any resemblance to the biological systems that it purports to mimic. Consider the following:

• Although some authors have suggested that non-coding DNA accumulates at a constant rate (e.g., Martin and Gordon 1995), this is clearly not generally true. All extant lineages can trace their ancestries back to a single common ancestor, and thus all living lineages (though not necessarily all taxonomic groups) have existed for exactly the same amount of time. And yet the amount of non-coding DNA varies dramatically among lineages, even among closely related ones. Ergo, the rate of accumulation of non-coding DNA differs among lineages. Premise 1 is rejected.
• The insertion of non-coding elements can be selectively relevant not only in terms of effects on protein-coding genes (many transposable elements are, after all, disease-causing mutagens), but also in terms of bulk effects on cell division, cell size, and associated organism-level traits (Gregory 2005). Premise 2 is rejected.
• The accumulation of non-coding DNA in eukaryotes does not occur by point mutation, except in the sense that genes that are duplicated may become pseudogenized by this mechanism. Indeed, the model seems only to involve a switch between coding and non-coding elements without the addition of new “nucleotides”, which makes it even more distant from true genomes. Moreover, the primary mechanisms of DNA insertion, including gene duplication and inactivation, transposable element insertion, and replication and recombination errors, do not occur at a constant rate. In fact, the presence of some non-coding DNA can have a feedback effect in which the likelihood of additional change is increased, be it by insertions (e.g., into non-coding regions, such that mutational consequences are minimized) or deletions (e.g., illegitimate recombination among LTR elements) or both (e.g., unequal crossing over or replication slippage enhanced by the presence of repetitive sequences). Premise 3 is rejected.
• Evolution does not have a pre-defined goal. Evolutionary change occurs along trajectories that are channeled by constraints and history, but not by foresight. As long as a given combination of features allows an organism to fill some niche better than alternatives, it will persist. Not only this, but models like the one being discussed are inherently limited in that they include only one evolutionary process: adaptation. Evolution in the biological world also occurs by non-adaptive processes, and this is perhaps particularly true of the evolution of non-coding DNA. It is on these points that the analogy between evolutionary computation and biological evolution fundamentally breaks down. Premise 4 is rejected in the strongest possible terms.
• Real populations of organisms are not constant in size, though one could argue that in some cases they are held close to the carrying capacity of an available niche. However, this assumes the existence of only one conceivable niche. Real populations can evolve to exploit different niches. Premise 5 is rejected.
• With a few exceptions (e.g., DNA transposons), transposable elements are sexually transmitted parasites of the genome, and these elements make up the single largest portion of eukaryotic genomes (roughly half of the human genome, for example). Ignoring this fact makes the model inapplicable to the very question it seeks to address. Premise 6 is rejected.

The main problem with proofs-by-analogy such as this is that they disregard most of the characteristics that make biological questions complex in the first place. Non-coding DNA evolves not as part of a simple, goal-directed, constant-rate process, but one typified by the influence of non-adaptive processes (e.g., gene duplication and pseudogenization), selection at multiple levels (e.g, both intragenomic and organismal), and open-ended trajectories. An “evolutionary” simulation this may be, but a model of biological evolution it is not.

Finally, it is essential to note that “non-coding elements make future evolution possible” explanations, though invoked by an alarming number of genome biologists, contradict basic evolutionary principles. Natural selection cannot favour a feature, especially a potentially costly one such as the presence of large amounts of non-coding DNA, because it may be useful down the line. Selection occurs in the here and now, and is based on reproductive success relative to competing alternatives. Long-term consequences are not part of the equation except in artificial situations where there is a pre-determined finish line to which variants are made to race.

That said, there can be long-term consequences in which inter-lineage sorting plays a role. In terms of processes such as alternative splicing and exon shuffling, which rely on the existence of non-coding introns, an effect on evolvability is plausible and may help to explain why lineages of eukaryotes with introns are so common (Doolittle 1987; Patthy 1999; Carroll 2002). However, this is not necessarily linked to total non-coding DNA amount. For a process of inter-lineage sorting to affect genome size more generally, large amounts of non-coding DNA would have to be insufficiently detrimental in the short term to be removed by organism-level selection, and would have to improve lineage survival and/or enhance speciation rates, such that over time one would observe a world dominated by lineages with huge genomes. In principle, this would be compatible with the conclusions of the model under discussion, at least in broad outline. In practice, however, this is undone by evidence that lineages with exorbitant genomes are restricted to narrower habitats (e.g., Knight et al. 2005), are less speciose (e.g., Olmo 2006), and may be more prone to extinction (e.g., Vinogradov 2003) than those with smaller genomes.

Non-coding DNA does not accumulate “so that” it will result in longer-term evolutionary advantage. And even if this explanation made sense from an evolutionary standpoint, it is not the effect that is observed in any case. No computer simulation changes this.

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References

Carroll, R.L. 2002. Evolution of the capacity to evolve. Journal of Evolutionary Biology 15: 911-921.

Doolittle, W.F. 1987. What introns have to tell us: hierarchy in genome evolution. Cold Spring Harbor Symposia on Quantitative Biology 52: 907-913.

Feverati, G. and F. Musso. 2007. An evolutionary model with Turing machines. arXiv.0711.3580v1.

Gregory, T.R. 2005. Genome size evolution in animals. In: The Evolution of the Genome (edited by T.R. Gregory). Elsevier, San Diego, pp. 3-87.

Knight, C.A., N.A. Molinari, and D.A. Petrov. 2005. The large genome constraint hypothesis: evolution, ecology and phenotype. Annals of Botany 95: 177-190.

Martin, C.C. and R. Gordon. 1995. Differentiation trees, a junk DNA molecular clock, and the evolution of neoteny in salamanders. Journal of Evolutionary Biology 8: 339-354.

Olmo, E. 2006. Genome size and evolutionary diversification in vertebrates. Italian Journal of Zoology 73: 167-171.

Patthy, L. 1999. Genome evolution and the evolution of exon shuffling — a review. Gene 238: 103-114.

Pearson, A, 2007. Junking the genome. New Scienist 14 July: 42-45.

Vinogradov, A.E. 2003. Selfish DNA is maladaptive: evidence from the plant Red List. Trends in Genetics 19: 609-614.

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Update: The author’s responses are posted and addressed here.

I have a request that I hope some readers can help me with. I am looking for examples from the literature (rather than any “general sense”) of people who claimed that “junk DNA” or “selfish DNA” was totally non-functional. I am particularly interested in peer-reviewed primary articles, but media reports and textbooks are of interest too. Anything from the 1970s to the present would be useful, especially pre-2000 publications. I suspect that the assumption that junk = totally functionless arose sometime in the 1990s, and hardly qualifies as a long-held view. I would also be interested to see references in which people suggest that the term “junk” was meant only to reflect our ignorance about what non-coding DNA is doing in the genome. Post your examples (with a quote and full reference info) in the comments. (Please don’t list Ohno 1972).

There has been a lot of discussion regarding discoveries in genomics, in terms of both genes (especially their number) and non-coding DNA (in particular whether any of it is functional and how much of it is transcribed). All of this supposedly contradicts long-held assumptions about genomes, especially those attributed to the early proponents of “junk DNA” or “selfish DNA” such as that all non-coding elements must be totally non-functional.

I thought I would share some quotes about this topic that I found interesting.

The observation that up to 25% of the genome of fetal mice is transcribed into rapidly labeled RNA, despite the fact that probably less than half this much of the genome serves a useful function, indicates that much of the junk DNA must be transcribed. It is thus not too surprising that much of this is rapidly broken down within the nucleus. There are several possible reasons why it is transcribed: (1) it may serve some unknown, obscure purpose; (2) it may play a role in gene regulation; or (3) the promoters which allow its transcription may remain sufficiently intact to allow RNA transcription long after the structural genes have become degenerate. [1]

These considerations suggest that up to 20% of the genome is actively used and the remaining 80+% is junk. But being junk doesn’t mean it is entirely useless. Common sense suggests that anything that is completely useless would be discarded. There are several possible functions for junk DNA. [1]

The observations on a number of structural gene loci of man, mice and other organisms revealed that each locus has a 10^-5 per generation probability of sustaining a deleterious mutation. It then follows that the moment we acquire 10⁵ gene loci, the overall deleterious mutation rate per generation becomes 1.0 which appears to represent an unbearably heavy genetic load. Taking into consideration the fact that deleterious mutations can be dominant or recessive, the total number of gene loci of man has been estimated to be about 3×10⁴. [2]

The creation of every new gene must have been accompanied by many other redundant copies joining the ranks of silent DNA base sequences, and these silent DNA base sequences may now be serving the useful but negative function of spacing those which have succeeded. [2]

It would be surprising if the host genome did not occasionally find some use for particular selfish DNA sequences, especially if there were many different sequences widely distributed over the chromosomes. One obvious use … would be for control purposes at one level or another. [3]

It seems that what the new publications do, rather than overturning any previous claims, is indicate that some authors don’t read the literature that they cite.

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Part of the Quotes of interest series.
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References

1. Comings, D.E. 1972. The structure and function of chromatin. Advances in Human Genetics 3: 237-431.

2. Ohno, S. 1972. So much “junk” DNA in our genome. In Evolution of Genetic Systems (ed. H.H. Smith), pp. 366-370. Gordon and Breach, New York.

3. Orgel, L.E. and F.H.C. Crick. 1980. Selfish DNA: the ultimate parasite. Nature 284: 604-607.
3: 237-431.