Transcriptomic meta-analysis reveals unannotated long non-coding RNAs related to the immune response in sheep

Abstract

Long non-coding RNAs (lncRNAs) are involved in several biological processes, including the immune system response to pathogens and vaccines. The annotation and functional characterization of lncRNAs is more advanced in humans than in livestock species. Here, we take advantage of the increasing number of high-throughput functional experiments deposited in public databases in order to uniformly analyse, profile unannotated lncRNAs and integrate 422 ovine RNA-seq samples from the ovine immune system. We identified 12302 unannotated lncRNA genes with support from independent CAGE-seq and histone modification ChIP-seq assays. Unannotated lncRNAs showed low expression levels and sequence conservation across other mammal species. There were differences in expression levels depending on the genomic location-based lncRNA classification. Differential expression analyses between unstimulated and samples stimulated with pathogen infection or vaccination resulted in hundreds of lncRNAs with changed expression. Gene co-expression analyses revealed immune gene-enriched clusters associated with immune system activation and related to interferon signalling, antiviral response or endoplasmic reticulum stress. Besides, differential co-expression networks were constructed in order to find condition-specific relationships between coding genes and lncRNAs. Overall, using a diverse set of immune system samples and bioinformatic approaches we identify several ovine lncRNAs associated with the response to an external stimulus. These findings help in the improvement of the ovine lncRNA catalogue and provide sheep-specific evidence for the implication in the general immune response for several lncRNAs.

Identifying transcriptomic profiles in ovine spleen after repetitive vaccination

“…We analyzed lncRNA and protein coding gene detection and differential expression using two annotations (Refseq and an extended Ensembl annotation). This would serve to check the completeness of these annotations in terms of lncRNA genes and to validate in an independent dataset the set of unannotated lncRNAs from a previous study ( 17 ). In samples quantified using the Ensembl extended annotation 21688 genes remained after the minimum expression filter and ribosomal gene filters.…”

“…In this work, we used the newly improved genome sequence and annotation for sheep ARS-UI_Ramb_v2.0 (RefSeq annotation) and the previous Oar_rambouillet_v1.0 assembly with the Ensembl annotation extended with 12302 extra lncRNA genes ( 17 ) to quantify gene expression. ARS-UI_Ramb_v2.0 annotation had greater transcriptome pseudo-alignment rates, even after the inclusion of extra lncRNAs in the Oar_rambouillet_v1.0 annotation, which reflects its better quality.…”

“…For differential lncRNA expression analysis, transcripts were also quantified in parallel using the Oar_rambouillet_v1.0 sheep genome and annotation from Ensembl release 103 ( https://www.ensembl.org/index.html ). The Ensembl annotation was extended using the unannotated lncRNAs identified in a study by our laboratory group ( 17 ).…”