Livestock genome annotation: transcriptome and chromatin structure profiling in cattle, goat, chicken and pig.

Sarah Djebali-Quelen (INRA GenPhySE)
Thursday, March 14, 2019 - 10:30 to 12:00
Room Aurigny
Talk abstract: 

Functional annotation of livestock genomes is a critical step to decipher the genotype-to-phenotype relationship underlying complex traits. As part of the Functional Annotation of Animal Genomes (FAANG) action, the FR-AgENCODE project aims at profiling the landscape of transcription (RNA-seq) and chromatin accessibility and conformation (ATAC-seq and Hi-C) in four livestock species representing ruminants (cattle, goat), monogastrics (pig) and birds (chicken), using three target samples related to metabolism (liver) and immunity (CD4+ and CD8+ T cells). Standardized protocols were applied to produce transcriptome and chromatin datasets for the four species. RNA-seq assays allowed to considerably extend the available catalog of protein-coding and non-coding transcripts. Gene expression profiles were consistent with known metabolic/immune functions and revealed differentially expressed transcripts with unknown function, including new lncRNAs in syntenic regions. The majority of ATAC-seq peaks of chromatin accessibility mapped to putative regulatory regions, with an enrichment of predicted transcription factor binding sites in differentially accessible peaks. Hi-C provided the first set of genome-wide maps of three-dimensional interactions across livestock and showed consistency with results from gene expression and chromatin accessibility in topological compartments of the genomes. We report the first multi-species and multi-assay genome annotation results obtained by a FAANG pilot project. The global consistency between gene expression and chromatin structure data in these four livestock species adds up to previous findings in model animals. Overall, these results emphasize the value of FAANG for the research on domesticated animals and strengthen the importance of future meta-analyses of the reference datasets being generated by this community on different species.