Evolution of alternative splicing regulation: changes in predicted exonic splicing regulators are not associated with changes in alternative splicing levels in primates

Abstract

Alternative splicing is tightly regulated in a spatio-temporal and quantitative manner. This regulation is achieved by a complex interplay between spliceosomal (trans) factors that bind to different sequence (cis) elements. cis-elements reside in both introns and exons and may either enhance or silence splicing. Differential combinations of cis-elements allows for a huge diversity of overall splicing signals, together comprising a complex 'splicing code'. Many cis-elements have been identified, and their effects on exon inclusion levels demonstrated in reporter systems. However, the impact of interspecific differences in these elements on the evolution of alternative splicing levels has not yet been investigated at genomic level. Here we study the effect of interspecific differences in predicted exonic splicing regulators (ESRs) on exon inclusion levels in human and chimpanzee. For this purpose, we compiled and studied comprehensive datasets of predicted ESRs, identified by several computational and experimental approaches, as well as microarray data for changes in alternative splicing levels between human and chimpanzee. Surprisingly, we found no association between changes in predicted ESRs and changes in alternative splicing levels. This observation holds across different ESR exon positions, exon lengths, and 5' splice site strengths. We suggest that this lack of association is mainly due to the great importance of context for ESR functionality: many ESR-like motifs in primates may have little or no effect on splicing, and thus interspecific changes at short-time scales may primarily occur in these effectively neutral ESRs. These results underscore the difficulties of using current computational ESR prediction algorithms to identify truly functionally important motifs, and provide a cautionary tale for studies of the effect of SNPs on splicing in human disease.

Figure 1. eneral lack of association between ESR changes and AS variation.

In blue, percentage of exons with (A) ESR-altering changes between human and chimpanzee, (B) ESR-disrupting changes, or (C) ESR-disrupting changes in all overlapping hexamers, for the different datasets, that show high level of exon inclusion level interspecific changes, for different cutoffs (y-axis, >20% difference in inclusion levels, >25% or >30%). In red, the percentage of exons without changes at predicted ESRs showing high level of AS variation. The similar percentage of exons with high AS variation indicates a lack of general association between changes in predicted ESRs and AS levels. Right-hand side panels show the percentage of the all exons that have changes in ESRs for the different available datasets.

Figure 2. ercentage of exons showing ESR-altering changes for different groups of AS level variation for brain context (left) and heart (right).

These results correspond to ESRs from Ke et al.'s dataset, and they are similar for the other available dataset and overall nucleotide change (data not shown).

Figure 3. ack of association between ESR changes and changes in AS level at different exon positions and for different groups of exon lengths and 5′ss strengths.

(A) Percentage of exons with ESR-altering changes (blue) and without changes in ESRs (red) at the 10 or 25 nucleotides next to the 5′ and 3′ splice sites for different cutoffs of AS variation (y-axis, >20%, >25% or >30% difference in inclusion levels) between human and chimp and datasets. (B and C) Percentage of exons with ESR-altering changes (blue) and without changes in ESRs (red) for short and long exons (B) and weak and strong 5′ss (C) for different cutoffs of AS variation (y-axis, >20%, >25% or >30% difference in inclusion levels) between human and chimpanzee. Right-hand side panels show the percentage of the total exons that have changes in ESRs for the different tests. These results correspond to ESRs from Ke et al.'s dataset, and they are similar for the other available dataset and global nucleotide change (data not shown).

Figure 4. ercentage of exons showing ESR changes and high AS variation at different cutoffs with overall net ESE/ESS composition change consistent with the increase/decrease of exon inclusion level (green) or ‘inverse’ (red).

Boxes show the number of exons in each category.