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Functional Annotation of the Transcriptome of the Pig, Sus scrofa, Based Upon Network Analysis of an RNAseq Transcriptional Atlas

Authors :
Kim M. Summers
Stephen J. Bush
Chunlei Wu
Andrew I. Su
Charity Muriuki
Emily L. Clark
Heather A. Finlayson
Lel Eory
Lindsey A. Waddell
Richard Talbot
Alan L. Archibald
David A. Hume
Source :
Frontiers in Genetics, Vol 10 (2020)
Publication Year :
2020
Publisher :
Frontiers Media S.A., 2020.

Abstract

The domestic pig (Sus scrofa) is both an economically important livestock species and a model for biomedical research. Two highly contiguous pig reference genomes have recently been released. To support functional annotation of the pig genomes and comparative analysis with large human transcriptomic data sets, we aimed to create a pig gene expression atlas. To achieve this objective, we extended a previous approach developed for the chicken. We downloaded RNAseq data sets from public repositories, down-sampled to a common depth, and quantified expression against a reference transcriptome using the mRNA quantitation tool, Kallisto. We then used the network analysis tool Graphia to identify clusters of transcripts that were coexpressed across the merged data set. Consistent with the principle of guilt-by-association, we identified coexpression clusters that were highly tissue or cell-type restricted and contained transcription factors that have previously been implicated in lineage determination. Other clusters were enriched for transcripts associated with biological processes, such as the cell cycle and oxidative phosphorylation. The same approach was used to identify coexpression clusters within RNAseq data from multiple individual liver and brain samples, highlighting cell type, process, and region-specific gene expression. Evidence of conserved expression can add confidence to assignment of orthology between pig and human genes. Many transcripts currently identified as novel genes with ENSSSCG or LOC IDs were found to be coexpressed with annotated neighbouring transcripts in the same orientation, indicating they may be products of the same transcriptional unit. The meta-analytic approach to utilising public RNAseq data is extendable to include new data sets and new species and provides a framework to support the Functional Annotation of Animals Genomes (FAANG) initiative.

Details

Language :
English
ISSN :
16648021
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Frontiers in Genetics
Publication Type :
Academic Journal
Accession number :
edsdoj.25da115ca6484bc797b527448cbfb964
Document Type :
article
Full Text :
https://doi.org/10.3389/fgene.2019.01355