|FANG, LINGZHAO - University Of Maryland|
|SORENSEN, PETER - Aarhus University|
|SAHANA, GOUTAM - Aarhus University|
|PANITZ, FRANK - Aarhus University|
|SU, GUOSHENG - Aarhus University|
|ZHANG, SHENGLI - China Agricultural University|
|YU, YING - China Agricultural University|
|LI, BINGJIE - Aarhus University|
|MA, LI - University Of Maryland|
|Liu, Ge - George|
|LUND, MOGENS SANDO - Aarhus University|
|THOMSEN, BO - Aarhus University|
Submitted to: Scientific Reports
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/6/2018
Publication Date: 6/19/2018
Citation: Fang, L., Sorensen, P., Sahana, G., Panitz, F., Su, G., Zhang, S., Yu, Y., Li, B., Ma, L., Liu, G., Lund, M., Thomsen, B. 2018. MicroRNA-guided prioritization of genome-wide association signals reveals the importance of microRNA-target gene networks for complex traits in cattle. Scientific Reports. 8(1):9345. https://doi.org/doi:10.1038/s41598-018-27729-y.
Interpretive Summary: MicroRNA (miRNA) is a master modulator of expression of many genes. We investigated the enrichments of association signals in miRNAs and miRNA-target networks using marker-set test. Our results revealed the significant impact of miRNAs, particularly in the context of miRNA-target networks, on studying the genetic architecture of complex traits. Farmers, scientist, and policy planners who need improve animal health and production based on genome-enable animal selection will benefit from this study.
Technical Abstract: Studying the genetic architecture of complex traits contributes to precision medicine, agriculture and understanding adaptive evolution. MicroRNA (miRNA) is a master modulator of expression of many genes in the vertebrate genome, hence, fine-tuning multiple complex phenotypes. Here, we hypothesized causal variants of complex traits are likely to cluster in miRNAs and miRNA-target networks. We first conducted genome-wide association study (GWAS) using imputed sequence variants (13~15 million) for seven complex traits (i.e., milk, fat and protein yields, body conformation, mastitis, health and fertility) in three cattle breeds (i.e., Holstein (HOL), Nordic red cattle (RDC) and Jersey (JER)) including > 10,000 animals. We then investigated the enrichments of association signals in miRNAs and miRNA-target networks using marker-set test. Our results demonstrated miRNAs were significantly (P < 0.05 in three breeds) enriched with milk production traits and mastitis, and the enrichments with miRNA-target networks were significantly higher than random target-sets across all seven traits in three breeds, except for health and fertility in HOL. Furthermore, most between-trait and across-breed correlations with miRNA-target networks were significantly greater than random target-sets, suggesting miRNAs’ pleiotropic effects and evolutionarily conserved properties. We provided a list of significant miRNA-target networks for complex traits being studied, and a following integrative infection-induced transcriptome analysis supported the significant miRNA-target networks in mastitis, which also provided novel insights into the genetic and biological basis underpinning mastitis etiology. Interestingly, during infection the up- and down- regulated targets of bta-miR-10a/b and bta-miR-6525 were associated with mastitis and milk yield, respectively. All the findings here were consistent across three breeds. Our study suggested the significant impact of miRNAs, particularly in the context of miRNA-target networks, on studying the genetic architecture of complex traits, providing valuable information for miRNA therapeutics in human and for balanced animal and plant breeding.