Characterising selection in Conserved Noncoding Elements (CNEs)

Abstract

Comparative genomic studies have identified noncoding regions of the genome which are often more highly conserved between species than protein-coding sequences. One possible explanation for this conservation of non-coding sequences is some form of selective constraint since sequence conservation at great evolutionary depths is a preliminary indication of functional constraint. Here, I consider nearly 2500 putative regulatory elements, termed Conserved Noncoding Elements (CNEs), that are conserved across seven vertebrate species (human, macaque, mouse, chicken, frog, zebrafish and fugu). I distinguish between CNEs that show accelerated rates of evolution and those that have remained more constrained throughout evolution, and identify CNEs that show higher than expected substitution rates in the human lineage that may be potential candidates of adaptive evolution. However, it is not trivial to demonstrate the action of selection on such sequences. It is relatively easier in the case of protein-coding DNA, since selection would be predicted to result in different rates of substitution for synonymous and non-synonymous sites. Hence, I use the same seven species to define phylogenetically invariant positions in CNEs in contrast to those that have at least one substitution and analyse them independently to determine if there is a positive correlation between evolutionary conservation and the strength of purifying selection at individual sites. In the 1000 Genomes, but not the HapMap, data I find a significant excess of rare derived alleles in CNEs relative to coding sequences. This excess of rare alleles can be best explained if selection is relatively consistent across sites, with most mutations resulting in a similar reduction in fitness. Finally, I explore patterns of variation in the allele-frequencies within human populations, however do not detect any significant differences in the underlying distribution of negatively selected variants among human populations.