Combining multi-OMICs information to identify key-regulator genes for pleiotropic effect on fertility and production traits in beef cattle.

PLoS ONE. 2018;13(10):e0205295 DOI 10.1371/journal.pone.0205295


Journal Homepage

Journal Title: PLoS ONE

ISSN: 1932-6203 (Online)

Publisher: Public Library of Science (PLoS)

LCC Subject Category: Medicine | Science

Country of publisher: United States

Language of fulltext: English

Full-text formats available: PDF, HTML, XML



Pablo Augusto de Souza Fonseca

Samir Id-Lahoucine

Antonio Reverter

Juan F Medrano

Marina S Fortes

Joaquim Casellas

Filippo Miglior

Luiz Brito

Maria Raquel S Carvalho

Flávio S Schenkel

Loan T Nguyen

Laercio R Porto-Neto

Milton G Thomas

Angela Cánovas


Peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 24 weeks


Abstract | Full Text

The identification of biological processes related to the regulation of complex traits is a difficult task. Commonly, complex traits are regulated through a multitude of genes contributing each to a small part of the total genetic variance. Additionally, some loci can simultaneously regulate several complex traits, a phenomenon defined as pleiotropy. The lack of understanding on the biological processes responsible for the regulation of these traits results in the decrease of selection efficiency and the selection of undesirable hitchhiking effects. The identification of pleiotropic key-regulator genes can assist in developing important tools for investigating biological processes underlying complex traits. A multi-breed and multi-OMICs approach was applied to study the pleiotropic effects of key-regulator genes using three independent beef cattle populations evaluated for fertility traits. A pleiotropic map for 32 traits related to growth, feed efficiency, carcass and meat quality, and reproduction was used to identify genes shared among the different populations and breeds in pleiotropic regions. Furthermore, data-mining analyses were performed using the Cattle QTL database (CattleQTLdb) to identify the QTL category annotated in the regions around the genes shared among breeds. This approach allowed the identification of a main gene network (composed of 38 genes) shared among breeds. This gene network was significantly associated with thyroid activity, among other biological processes, and displayed a high regulatory potential. In addition, it was possible to identify genes with pleiotropic effects related to crucial biological processes that regulate economically relevant traits associated with fertility, production and health, such as MYC, PPARG, GSK3B, TG and IYD genes. These genes will be further investigated to better understand the biological processes involved in the expression of complex traits and assist in the identification of functional variants associated with undesirable phenotypes, such as decreased fertility, poor feed efficiency and negative energetic balance.