Protein-coding sequences can arise either from duplication and divergence of existing sequences, or de novo from noncoding DNA. Unfortunately, recently evolved de novo genes can be hard to distinguish from false positives, making their study difficult. Here, we study a more tractable version of the process of conversion of noncoding sequence into coding: the co-option of short segments of noncoding sequence into the C-termini of existing proteins via the loss of a stop codon. Because we study recent additions to potentially old genes, we are able to apply a variety of stringent quality filters to our annotations of what is a true protein-coding gene, discarding the putative proteins of unknown function that are typical of recent fully de novo genes. We identify 54 examples of C-terminal extensions in Saccharomyces and 28 in Drosophila, all of them recent enough to still be polymorphic. We find one putative gene fusion that turns out, on close inspection, to be the product of replicated assembly errors, further highlighting the issue of false positives in the study of rare events. Four of the Saccharomyces C-terminal extensions (to ADH1, ARP8, TPM2, and PIS1) that survived our quality filters are predicted to lead to significant modification of a protein domain structure.
The existence of complex (multiple-step) genetic adaptations that are irreducible (i.e., all partial combinations are less fit than the original genotype) is one of the longest standing problems in evolutionary biology. In standard genetics parlance, these adaptations require the crossing of a wide adaptive valley of deleterious intermediate stages. Here, we demonstrate, using a simple model, that evolution can cross wide valleys to produce irreducibly complex adaptations by making use of previously cryptic mutations. When revealed by an evolutionary capacitor, previously cryptic mutants have higher initial frequencies than do new mutations, bringing them closer to a valley-crossing saddle in allele frequency space. Moreover, simple combinatorics implies an enormous number of candidate combinations exist within available cryptic genetic variation. We model the dynamics of crossing of a wide adaptive valley after a capacitance event using both numerical simulations and analytical approximations. Although individual valley crossing events become less likely as valleys widen, by taking the combinatorics of genotype space into account, we see that revealing cryptic variation can cause the frequent evolution of complex adaptations.
Population genetics is often taught in introductory biology classes, starting with the Hardy-Weinberg principle (HWP) and genetic drift. Here I argue that teaching these two topics first aligns neither with current expert knowledge, nor with good pedagogy. Student difficulties with mathematics in general, and probability in particular, make population genetics difficult to teach and learn. I recommend an alternative, historically inspired ordering of population genetics topics, based on progressively increasing mathematical difficulty. This progression can facilitate just-in-time math instruction. This alternative ordering includes, but does not privilege, the HWP and genetic drift. Stochastic events whose consequences are felt within a single generation, and the deterministic accumulation of the effects of selection across multiple generations, are both taught before tackling the stochastic accumulation of the effects of accidents of sampling. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
PMID: 15911577;PMCID: PMC1451192;Abstract:
Evolutionary capacitors phenotypically reveal a stock of cryptic genetic variation in a reversible fashion. The sudden and reversible revelation of a range of variation is fundamentally different from the gradual introduction of variation by mutation. Here I study the invasion dynamics of modifiers of revelation. A modifier with the optimal rate of revelation mopt has a higher probability of invading any other population than of being counterinvaded. mopt varies with the population size N and the rate θ at which environmental change makes revelation adaptive. For small populations less than a minimum cutoff Nmin, all revelation is selected against. Nmin is typically quite small and increases only weakly, with θ-1/2. For large populations with N > 1/θ, mopt is ∼1/N. Selection for the optimum is highly effective and increases in effectiveness with larger N ≫ 1/θ. For intermediate values of N, mopt is typically a little less than θ and is only weakly favored over less frequent revelation. The model is analogous to a two-locus model for the evolution of a mutator allele. It is a fully stochastic model and so is able to show that selection for revelation can be strong enough to overcome random drift. Copyright © 2005 by the Genetics Society of America.