Estimating the prevalence of functional exonic splice regulatory information

Abstract

In addition to coding information, human exons contain sequences necessary for correct splicing. These elements are known to be under purifying selection and their disruption can cause disease. However, the density of functional exonic splicing information remains profoundly uncertain. Several groups have experimentally investigated how mutations at different exonic positions affect splicing. They have found splice information to be distributed widely in exons, with one estimate putting the proportion of splicing-relevant nucleotides at >90%. These results suggest that splicing could place a major pressure on exon evolution. However, analyses of sequence conservation have concluded that the need to preserve splice regulatory signals only slightly constrains exon evolution, with a resulting decrease in the average human rate of synonymous evolution of only 1-4%. Why do these two lines of research come to such different conclusions? Among other reasons, we suggest that the methods are measuring different things: one assays the density of sites that affect splicing, the other the density of sites whose effects on splicing are visible to selection. In addition, the experimental methods typically consider short exons, thereby enriching for nucleotides close to the splice junction, such sites being enriched for splice-control elements. By contrast, in part owing to correction for nucleotide composition biases and to the assumption that constraint only operates on exon ends, the conservation-based methods can be overly conservative.

Keywords: Exon Inclusion; Exonic Splice; Motif Density; Splice Assay; Synonymous Site.

Fig. 1

Percentage of splice-altering variants among variants tested (blue bars) or over-all percentage decrease in d _S (synonymous rate of evolution)/d ₄ (fourfold degenerate rate of evolution) attributed to the need to preserve splice control elements (orange bars). The light blue bars correspond to subtype 1 (at least some variants chosen because of disease association) and the dark blue bars to subtype 2 (largely unbiased selection of variants). There is a large discrepancy between blue (experimental) and orange (computational) bars. Note, however, that the figures are directly comparable only if one assumes that the selection detected in the computational studies is strong enough to preclude all substitutions at selected sites (see “It is uncertain how to infer the density of selected sites from the decrease in d_S”). Note also that the estimate from Savisaar and Hurst (2017) reflected selection on non-splice related RNA-binding protein target motifs as well

Fig. 2

The distribution of exon lengths in the human genome is shown in orange (see Online Resource 1 for data). The dashed line marks the median of this distribution. The asterisks mark the natural logs of the lengths of the exons used in the experimental studies (studies that used more than one exon have been excluded). Note that the majority of these values are below the genomic median, and the three subtype 2 studies (dark blue) correspond to particularly low figures

Fig. 3

Two models for the distribution of functional splice regulatory information along the exon. Under the first model, functional splice regulatory elements are rare but under strong purifying selection. Under the second model, functional splice regulatory elements are frequent but only weakly constrained. Intermediate scenarios are also possible