Mammalian keratin associated proteins (KRTAPs) subgenomes: disentangling hair diversity and adaptation to terrestrial and aquatic environments

Abstract

BackgroundAdaptation of mammals to terrestrial life was facilitated by the unique vertebrate trait of body hair, which occurs in a range of morphological patterns. Keratin associated proteins (KRTAPs), the major structural hair shaft proteins, are largely responsible for hair variation.ResultsWe exhaustively characterized the KRTAP gene family in 22 mammalian genomes, confirming the existence of 30 KRTAP subfamilies evolving at different rates with varying degrees of diversification and homogenization. Within the two major classes of KRTAPs, the high cysteine (HS) subfamily experienced strong concerted evolution, high rates of gene conversion/recombination and high GC content. In contrast, high glycine-tyrosine (HGT) KRTAPs showed evidence of positive selection and low rates of gene conversion/recombination. Species with more hair and of higher complexity tended to have more KRATP genes (gene expansion). The sloth, with long and coarse hair, had the most KRTAP genes (175 with 141 being intact). By contrast, the “hairless” dolphin had 35 KRTAPs and the highest pseudogenization rate (74% relative to the 19% mammalian average). Unique hair-related phenotypes, such as scales (armadillo) and spines (hedgehog), were correlated with changes in KRTAPs. Gene expression variation probably also influences hair diversification patterns, for example human have an identical KRTAP repertoire as apes, but much less hair.ConclusionsWe hypothesize that differences in KRTAP gene repertoire and gene expression, together with distinct rates of gene conversion/recombination, pseudogenization and positive selection, are likely responsible for micro and macro-phenotypic hair diversification among mammals in response to adaptations to ecological pressures.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-779) contains supplementary material, which is available to authorized users.

REDHORSE-REcombination and Double crossover detection in Haploid Organisms using next-geneRation SEquencing data

“…The simulated dataset allows one to introduce different features into the recombinants and to study how individual algorithms perform. The dataset from chromosome VIII of Toxoplasma gondii (described in an accompanying paper, [9]) allowed us to demonstrate the pipeline using NGS data.…”

“…A representative chromosome VIII from the two parental strains (ME49 and VAND) of Toxoplasma gondii and three hybrids (see section Datasets) from a recently described genetic cross [9] were used to demonstrate the utility of REDHORSE on NGS datasets. By showing its utility on a representative data, we intend to demonstrate that our pipeline can be applied to frameworks involving similar NGS data.…”

“…The choice of 5000 bp was based on our observations from the real data (see companion manuscript [9]).…”

“…Here we sought to implement techniques using NGS data to generate new genetic maps. Although a complete summary of these findings appears separately [9], here we described the development of software tools to analyze genetic crosses between haploid genomes that is illustrated using chr VIII of T. gondii .…”

“…In contrast, other algorithms were designed for lower resolution data such as from RFLP [7] and microarrays [8] and their applicability for NGS data has not been thoroughly tested. Most of these algorithms could not handle markers from all the chromosomes for our NGS data [9]. 3) REDHORSE compares hybrids against only the parental lines to determine the break points.…”