Abstract
The nearly neutral theory predicts that small effective population size provides the conditions for weakened selection. This is postulated to explain why our genome is more "bloated" than that of, for example, yeast, ours having large introns and large intergene spacer. If a bloated genome is also an error prone genome might it, however, be the case that selection for error-mitigating properties is stronger in our genome? We examine this notion using splicing as an exemplar, not least because large introns can predispose to noisy splicing. We thus ask whether, owing to genomic decay, selection for splice error-control mechanisms is stronger, not weaker, in species with large introns and small populations. In humans much information defining splice sites is in cis-exonic motifs, most notably exonic splice enhancers (ESEs). These act as splice-error control elements. Here then we ask whether within and between-species intron size is a predictor of the commonality of exonic cis-splicing motifs. We show that, as predicted, the proportion of synonymous sites that are ESE-associated and under selection in humans is weakly positively correlated with the size of the flanking intron. In a phylogenetically controlled framework, we observe, also as expected, that mean intron size is both predicted by Ne.μ and is a good predictor of cis-motif usage across species, this usage coevolving with splice site definition. Unexpectedly, however, across taxa intron density is a better predictor of cis-motif usage than intron size. We propose that selection for splice-related motifs is driven by a need to avoid decoy splice sites that will be more common in genes with many and large introns. That intron number and density predict ESE usage within human genes is consistent with this, as is the finding of intragenic heterogeneity in ESE density. As intronic content and splice site usage across species is also well predicted by Ne.μ, the result also suggests an unusual circumstance in which selection (for cis-modifiers of splicing) might be stronger when population sizes are smaller, as here splicing is noisier, resulting in a greater need to control error-prone splicing.