Genes Integral to the Reproductive Function of Male Reproductive Tissues Drive Heterogeneity in Evolutionary Rates in Japanese Quail

Early comparative genomics studies originally uncovered a nonintuitive pattern; genes involved in reproduction appeared to evolve more rapidly than other classes of genes. Currently, the emerging consensus is that genes encoding reproductive proteins evolve under variable selective pressures, producing more heterogeneous divergence patterns than previously appreciated. Here, we investigate a facet of that heterogeneity and explore the factors that drive male reproductive tissue-based heterogeneity in evolutionary rates. In Japanese quail (Coturnix japonica), genes with enriched expression in the testes evolve much more rapidly than those enriched in the foam gland (FG), a novel gland that secretes an airy foam that males transfer to females during mating. We compared molecular evolutionary patterns among (1) genes with induced expression in breeding vs. wintering conditions for both tissues and (2) genes that encode foam proteins (FPs) vs. those with varying degrees of expression specificity in the FG. We report two major findings. First, genes upregulated in breeding condition testes evolve exceptionally rapidly, while those induced in breeding condition FGs evolve slowly. These differences hold even after correcting for hormonally-dependent gene expression and chromosomal location. Second, genes encoding FPs are extremely conserved in terms of gene identity and sequence. Together, these finding suggest that genes involved in the reproductive function of each tissue drive the marked rate of heterogeneity

Evolution of the Highly Repetitive PEVK Region of Titin Across Mammals

The protein titin plays a key role in vertebrate muscle where it acts like a giant molecular spring. Despite its importance and conservation over vertebrate evolution, a lack of high quality annotations in non-model species makes comparative evolutionary studies of titin challenging. The PEVK region of titin—named for its high proportion of Pro-Glu-Val-Lys amino acids—is particularly difficult to annotate due to its abundance of alternatively spliced isoforms and short, highly repetitive exons. To understand PEVK evolution across mammals, we developed a bioinformatics tool, PEVK_Finder, to annotate PEVK exons from genomic sequences of titin and applied it to a diverse set of mammals. PEVK_Finder consistently outperforms standard annotation tools across a broad range of conditions and improves annotations of the PEVK region in non-model mammalian species. We find that the PEVK region can be divided into two subregions (PEVK-N, PEVK-C) with distinct patterns of evolutionary constraint and divergence. The bipartite nature of the PEVK region has implications for titin diversification. In the PEVK-N region, certain exons are conserved and may be essential, but natural selection also acts on particular codons. In the PEVK-C, exons are more homogenous and length variation of the PEVK region may provide the raw material for evolutionary adaptation in titin function. The PEVK-C region can be further divided into a highly repetitive region (PEVK-CA) and one that is more variable (PEVK-CB). Taken together, we find that the very complexity that makes titin a challenge for annotation tools may also promote evolutionary adaptation

A Comparison of Next Generation Sequencing Technologies for Transcriptome Assembly and Utility for RNA-Seq in a Non-Model Bird

<div><p><i>De novo</i> assembled transcriptomes, in combination with RNA-Seq, are powerful tools to explore gene sequence and expression level in organisms without reference genomes. Investigators must first choose which high throughput sequencing platforms will provide data most suitable for their experimental goals. In this study, we explore the utility of 454 and Illumina sequences for <i>de novo</i> transcriptome assembly and downstream RNA-Seq applications in a reproductive gland from a non-model bird species, the Japanese quail (<i>Coturnix japonica</i>). Four transcriptomes composed of either pure 454 or Illumina reads or mixtures of read types were assembled and evaluated for the same cost. Illumina assemblies performed best for <i>de novo</i> transcriptome characterization in terms of contig length, transcriptome coverage, and complete assembly of gene transcripts. Improvements over the Hybrid assembly were marginal, with the exception that the addition of 454 data significantly increased the number of genes annotated. The Illumina assembly provided the best reference to align an independent set of RNA-Seq data as ∼84% of reads mapped to single genes in the transcriptome. Contigs constructed solely from 454 data may impose problems for RNA-Seq as our 454 transcriptome revealed a high number of indels and many ambiguously mapped reads. Correcting the 454 transcriptome with Illumina reads was an effective strategy to deal with indel and frameshift errors inherent to the 454 transcriptome, but at the cost of transcriptome coverage. In the absence of a reference genome, we find that Illumina reads alone produced a high quality transcriptome appropriate for RNA-Seq gene expression analyses.</p></div

Number and frequency of contigs with no open reading frames.

<p>Number and frequency of contigs with no open reading frames.</p

Distribution of contig lengths for each transcriptome assembly.

<p><b>a</b>) Histogram of contig lengths (natural-log transformed) in nucleotide base pairs of each of the transcriptome assemblies and the Chicken coding sequence set. <b>b</b>) Histogram of open reading frame lengths (natural-log transformed) in base pairs predicted for each of the transcriptome assemblies and the Chicken coding sequence set. Legend applies to both graphs.</p

Ortholog hit ratios for each transcriptome assembly.

<p>Histograms of ortholog hit ratios (<i>i.e.</i>, contig lengths relative to ortholog length) for contigs generated from the 454, Illumina, Corrected 454, and Hybrid transcriptome assemblies. Ratios equal to 1 indicate fully assembled transcripts. Values <1 signify partial transcripts and values >1 than represent contigs with insertions relative to orthologs. Orthologs were determined by 1∶1 reciprocal best blast hits with chicken.</p

Standard metrics of transcriptome assembly (lengths and N50 in base pairs).

<p>Standard metrics of transcriptome assembly (lengths and N50 in base pairs).</p

The number of deletions, and insertions per 100,000 bp identified between RNA-Seq and an assembly.

<p>The number of deletions, and insertions per 100,000 bp identified between RNA-Seq and an assembly.</p

Relationship between ortholog hit ratio and ortholog length for each transcriptome assembly.

<p>The ortholog hit ratio standardizes contig lengths relative to ortholog length. Contigs representing complete transcripts will have ratios equal to 1. Ortholog lengths are in amino acids and were log₁₀ transformed. Orthologs were determined by 1∶1 reciprocal best blast hits with chicken.</p

Role of foam in sperm competition dataset

Competitive reproductive performance in terms of number of fertilized eggs of a pair of males (manipulated and non-manipulated) mated to the same females. Males may (manipulated, sometimes) or may not (non-manipulated) have had their foam complements removed prior to mating. Mating order and foam complements were varied. Abbreviations as follows: Male_Pair: the id of the male pair; Group: trial sets for two different groups; Male_Pair_Full: a combination of male pair id and group; Manip_ID: id of the manipulated male, who may or may not have had his foam removed; NonManip_ID: id of the non-manipulated male, whose foam was never removed; Female_ID: id of the mated female; Manip_Posit; mating positior of the manipulated male, either first (1) or second (2); Foam_Manip: whether or not the manipulated male's foam was removed (absent) or not (present); Number_NonManip_Fert: number of eggs fertilized from the non-manipulated male; Number_Manip_Fert: number of eggs fertilized by the manipulated male; Total_Fert: total number of eggs fertilized for a given trial; NonManip_AnyFert: whether or not the non-manipulated male fertilized any eggs (1) or none (0); Manip_AnyFert: whether or not the manipulated male fertilized any eggs (1) or none (0); Manip_LastDayFert: the last day a manipulated male fertilized any eggs; Mixed: whether or not their was mixed paternity for a given matin