Network Analyses Predict Small RNAs That Might Modulate Gene Expression in the Testis and Epididymis of Bos indicus Bulls

• Autor(a) principal: de Lima, Andressa O. [UNESP]
• Data de Publicação: 2021
• Outros Autores: Afonso, Juliana, Edson, Janette, Marcellin, Esteban, Palfreyman, Robin, Porto-Neto, Laercio R., Reverter, Antonio, Fortes, Marina R. S.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.3389/fgene.2021.610116; http://hdl.handle.net/11449/206350
• topic: bovine; bta-mir-2886; miRNA; RNA-sequencing; small RNAs; spermatogenesis; spermatozoa; systems biology

Spermatogenesis relies on complex molecular mechanisms, essential for the genesis and differentiation of the male gamete. Germ cell differentiation starts at the testicular parenchyma and finishes in the epididymis, which has three main regions: head, body, and tail. RNA-sequencing data of the testicular parenchyma (TP), head epididymis (HE), and tail epididymis (TE) from four bulls (three biopsies per bull: 12 samples) were subjected to differential expression analyses, functional enrichment analyses, and co-expression analyses. The aim was to investigate the co-expression and infer possible regulatory roles for transcripts involved in the spermatogenesis of Bos indicus bulls. Across the three pairwise comparisons, 3,826 differentially expressed (DE) transcripts were identified, of which 384 are small RNAs. Functional enrichment analysis pointed to gene ontology (GO) terms related to ion channel activity, detoxification of copper, neuroactive receptors, and spermatogenesis. Using the regulatory impact factor (RIF) algorithm, we detected 70 DE small RNAs likely to regulate the DE transcripts considering all pairwise comparisons among tissues. The pattern of small RNA co-expression suggested that these elements are involved in spermatogenesis regulation. The 3,826 DE transcripts (mRNAs and small RNAs) were further subjected to co-expression analyses using the partial correlation and information theory (PCIT) algorithm for network prediction. Significant correlations underpinned the co-expression network, which had 2,216 transcripts connected by 158,807 predicted interactions. The larger network cluster was enriched for male gamete generation and had 15 miRNAs with significant RIF. The miRNA bta-mir-2886 showed the highest number of connections (601) and was predicted to down-regulate ELOVL3, FEZF2, and HOXA13 (negative co-expression correlations and confirmed with TargetScan). In short, we suggest that bta-mir-2886 and other small RNAs might modulate gene expression in the testis and epididymis, in Bos indicus cattle.