A RNA-Seq Analysis to Describe the Boar Sperm Transcriptome and Its Seasonal Changes

Abstract

Understanding the molecular basis of cell function and ultimate phenotypes is crucial for the development of biological markers. With this aim, several RNA-seq studies have been devoted to the characterization of the transcriptome of ejaculated spermatozoa in relation to sperm quality and fertility. Semen quality follows a seasonal pattern and decays in the summer months in several animal species. The aim of this study was to deeply profile the transcriptome of the boar sperm and to evaluate its seasonal changes. We sequenced the total and the short fractions of the sperm RNA from 10 Pietrain boars, 5 collected in summer and 5 five sampled in winter, and identified a complex and rich transcriptome with 4,436 coding genes of moderate to high abundance. Transcript fragmentation was high but less obvious in genes related to spermatogenesis, chromatin compaction and fertility. Short non-coding RNAs mostly included piwi-interacting RNAs, transfer RNAs and microRNAs. We also compared the transcriptome of the summer and the winter ejaculates and identified 34 coding genes and 7 microRNAs with a significantly distinct distribution. These genes were mostly related to oxidative stress, DNA damage and autophagy. This is the deepest characterization of the boar sperm transcriptome and the first study linking the transcriptome and the seasonal variability of semen quality in animals. The annotation described here can be used as a reference for the identification of markers of sperm quality in pigs.

Keywords: RNA-seq; differential gene expression; sperm; sperm RNA element; sperm seasonality; transcript integrity.

FIGURE 1

Cumulative abundance of the porcine SREs. The black dots indicate the log10 of the RNA abundance of each SRE. SREs are sorted in a decreasing order by their RNA abundance in the X-axis. The red line represents the total number of SREs for each abundance decile group. The first decile of the most abundant SREs accounted for 65% of the total read abundance. RPKM, reads per kilobase per million mapped reads; SRE, sperm RNA element.

FIGURE 2

Read mapping distribution of the short non-coding RNA types and piRNA distribution within the Repetitive Element classes. (A) Proportion of reads mapping to each short non-coding RNA type. (B) Distribution within each Repetitive Element class of the piRNA cluster reads overlapping with Repetitive Elements.