Posted on 06/07/2005 10:25:32 AM PDT by <1/1,000,000th%
Convergent evolution occurs on all levels of biological organization, from organ systems to proteins. For instance, eyes and wings have evolved independently multiple times, and many aquatic vertebrates share a streamlined shape, despite their independent evolutionary origins. On the smaller scale of proteins, lysozymes have been recruited independently for foregut fermentation in bovids, colubine monkeys and a bird. Antifreeze glycoproteins in antarctic notothenioids and northern cod (living at opposite ends of the globe) have independently evolved similar amino acid sequences.
Recent studies have identified abundant genetic circuit motifs in transcriptional regulation networks of the yeast S. cerevisiae and the bacterium E. coli. These circuit motifs include regulatory chains, feed-forward circuits and a 'bi-fan' (Fig. 1). Such motifs may have had two principal evolutionary origins. First, they may have come about through the random duplication and subsequent diversification of a few ancestral circuits. Given the high frequency at which genes and genomes undergo duplication, this is a plausible scenario. It is equally possible, however, that these circuits arose independently by recruitment of unrelated genes. If such convergent circuit evolution is prevalent, then these circuits owe their abundance to the action of natural selection.
To determine the evolutionary origin of transcriptional regulation circuits, we defined two indicators of common circuit ancestry, A and Fmax. Consider a genome containing n regulatory circuits, each with k genes and identical topology (for details see Supplementary Methods online). A pair of circuits shares a common ancestor if all k gene pairs in the circuit pair are gene duplicates. We next defined a 'circuit graph' whose n nodes represent the n circuits and where an edge connects two nodes (circuits) if the circuits have a common ancestor. Our first indicator, A, of common circuit ancestry, is equal to A = 1 - (C/n), where C is the number of components in the graph (Fig. 1a). The greater A is, the greater is the fraction of circuits sharing a common ancestor. Our second indicator is Fmax, the size of the largest family of circuits with common ancestry (Fig. 1a).
We identified duplicate genes using BLASTP at a significance threshold of E 10-5 (E values between 10-3 and 10-11 yield the same results). Using this criterion, neither of two circuit types in E. coli showed evidence of common ancestry (A = 0 and Fmax = 1 for both; Fig. 1b). We also studied 18 yeast circuit types, and only three (feed-forward loops, multi-input modules of size 2 and bi-fans) showed evidence of common ancestry (A > 0 and Fmax > 1; Fig. 1b). This may be due to chance alone, however, simply because duplicate genes are abundant in the yeast genome. Therefore, we used permutation tests (described in Supplementary Methods online) to assess the statistical evidence of A and Fmax. For no circuit type was A significantly different from the chance expectation. For example, yeast contains 542 bi-fan motifs with A = 0.197. The probability of observing A = 0.197 by chance is P = 0.18: too large to reject the null hypothesis. We observed a marginally significant value of Fmax = 5 for feed-forward loops (P = 0.05). Even for this circuit type, however, most circuits (43 of 48) showed independent ancestry.
Our analysis of yeast circuits rests on genome-scale chromatin precipitation experiments that use a statistical error threshold (Pe) to identify true regulatory interactions5. The results reported in Figure 1b are based on Pe = 10-3, but we found the same results when varying Pe between 10-2 and 10-5. As above, only feed-forward loops yielded a marginally significant value of A = 0.11 (P = 0.03) and Fmax = 3 (P = 0.03) at Pe 10-4. Lowering Pe further to Pe = 10-5 yielded A = 0 and Fmax = 1.
We also asked whether members of one gene family preferentially occurred in one type of gene circuit. This would be expected if many circuits originated through duplication. Specifically, we asked whether the likelihood of a gene occurring in a given circuit type increases if one of its duplicates occurs in that type. The answer is no (Table 1).
In sum, we found no common ancestry among the E. coli circuit types, the yeast regulatory chains or the yeast multi-input motifs with more than two regulators. Of the remaining three yeast circuit types, two showed common ancestry indistinguishable from that expected by chance. Only feed-forward loops showed marginally significant values of either A or Fmax, but this finding is not statistically robust. Moreover, most (43 of 48) feed-forward loops have clearly independent origins. We also note that the probability of falsely identifying a pair of circuits as duplicates decreases with increasing circuit size. The larger a circuit is, the less evidence of duplication it shows in our analysis.
Multiple lines of evidence indicate that duplicate genes diverge rapidly in function. Our findings that gene circuits do not share common ancestry and that duplicate regulatory genes are randomly distributed across gene circuit types underscore this point, because they imply that duplicate transcriptional regulators can readily evolve new interactions. The short DNA binding sites of transcriptional regulators account for much of this plasticity. In microbes like yeast and E. coli, new regulatory interactions can arise rapidly, even on the time scale of laboratory evolution experiments. Transcriptional regulation circuits are thus ideal systems for studying convergent evolution, because natural selection has much raw material (variation in regulatory interactions) to shape such circuits.
The finding that gene circuits have evolved repeatedly makes a strong case for their optimal design. For example, the design of a feed-forward loop may serve to activate the regulated (downstream) genes only if the farthest-upstream regulator is persistently activated. Moreover, the same design rapidly deactivates genes once this regulator is shut off. Our results also suggest that convergent evolution, probably rare in protein sequences, may have an important role in the higher organizational level of gene circuits. Stephen Jay Gould famously asked what would be conserved if life's tape, its evolutionary history, was replayed. Transcriptional regulation circuits, it seems, might come out just about the same.
There's a similar article on gene networks from the European Molecular Biology Organization (EMBO) floating around here at work but I couldn't find it on-line. This is an older article but similar theme.
The figures and table are on the site.
Warm summer day ping!
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Got to love it. ID dittos.
Thanks for the ping!
This one may be of interest to you
Thanks for the ping!
Genetics Ping
You're right. But this is the language these folks typically use.
I also disagree with the ID hijacking of the word design. I don't want to get to the stage where saying something is designed implies intelligence directing the designing. The evolutionary process designs without intelligence within the process.
Design implies purpose and direction, evolution implies neither. Nobody has hijacked anything unless your trying to tell me that evolution has both purpose and direction.
Word lawyers vs. people just trying to put an idea into words.
So what is the distinction between intelligent design and design?
Wrong.
Nobody has hijacked anything unless your trying to tell me that evolution has both purpose and direction.
It does. The purpose is survival. The direction is increased fitness to survive.
Why don't you go learn something about evolutionary biology before you attempt to critique it?
Try reading the article again. It was designed by evolution, not by the "I" in "ID".
"So what is the distinction between intelligent design and design?"
I would guess that "intelligent design" means something that was designed by an agent capable of thought (i.e. humans). Whereas "design" in the article's context simply means shape or structure.
"The evolutionary process designs without intelligence within the process."
I agree and disagree.
I would say intelligence designed specific rules of physics, chemistry, et al, that result in evolution working as it works.
Excuse me. Says who? You? Now run along and play and get back to your cutting and pasting.
It may imply that, but it doesn't require that interpretation. Evolution designs without external intelligence. Natural selection is a form of intelligence. It employs change and feedback, just as brains do.
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