A systems biology framework to shed light on sperm quality in swineIntegrating GWAS and RNA-seq data for the first time in this field, a new collaborative work analyses the genetic and molecular mechanisms that determine sperm quality in pigs
A new study led by researchers at CRAG identifies a set of genetic markers that shape sperm quality in boars and proposes a model with a promising potential for optimizing the sustainability of pig breeding and production. These results, published at the scientific journal Genetics Selection Evolution, are fruit of an unprecedented systems biology approach in this field that integrates data obtained from multiple techniques; a method that opens new paths to improve complex genetic traits that are relevant for the animal breeding industry.
Investigating the genetic and molecular mechanisms that control sperm quality has become a focus of interest in livestock breeders, including swine, for its relevance on selecting studs to optimize fertility rates. Artificial insemination farms regularly evaluate sperm quality in boar studs to predict their fertilizing ability, but current assessment tools need further development since boar replacement due to insufficient sperm quality remains an economic hurdle for the sector.
An integrative approach
Sperm carries the paternal genome and a wide repertoire of molecules including RNAs, which are essential for fertilization and the development of a new organism. Aiming to unravel the complex genetic basis of semen quality, this new collaborative work is the first to integrate both genome-wide association studies (GWAS) and RNA-seq data in order to identify the genes, pathways and DNA variants that determine sperm quality in swine.
“We collected samples from 300 different Pietrain boars, in which we measured sperm quality traits such as concentration, morphology, motility and RNA abundances. We then analysed these samples using GWAS and RNA-seq techniques to determine which genetic variants and RNA abundances were associated with the observed traits”, explains Marta Gòdia, researcher at CRAG and first author of the paper. “We considered the genes and interactions that were present in both analyses to build a robust gene interaction network that we additionally enriched with supplementary data, thus pinpointing the key genetic players in shaping the complex inheritance of sperm quality traits”, she adds.
A SNP panel to predict sperm quality
Although SNPs -a type of genetic variant- have become the marker of choice for the genetic improvement of livestock species, the development of a SNP array for the prediction of boar sperm quality remains to be done. Using the systems biology approach developed in this new work, researchers were able to design a panel with 73 SNPs that explains a substantial part (more than 30%) of the variance in sperm traits, a promising model to improve swine fertility.
“Additional research is still required, but the integrative framework that we propose for ultimately building a SNP array provides compelling results of its application to any type of complex trait with a genetic basis. This opens another avenue to improve traits that are influenced by several genes that are of interest for the animal breeding industry”, adds Àlex Clop, CSIC researcher at CRAG and leader of the study. “The implications of this research are broad, ranging from applications to livestock breeding strategies to modelling the biology of infertility in mammals”, he concludes.
Genetics Selection Evolution 52, Article number: 72 (2020) https://doi.org/10.1186/s12711-020-00592-0. A systems biology framework integrating GWAS and RNA-seq to shed light on the molecular basis of sperm quality in swine. Marta Gòdia, Antonio Reverter, Rayner González-Prendes, Yuliaxis Ramayo-Caldas, Anna Castelló, Joan-Enric Rodríguez-Gil, Armand Sánchez & Alex Clop.
About the authors and the funding of the study
In addition to CRAG researchers, the authors of this study include researchers from the Institute for Agrifood Research and Technology (IRTA Torre Marimon, Spain), the Autonomous University of Barcelona (UAB, Spain), the CSIRO Agriculture and Food (Australia) and the Wageningen University & Research (the Netherlands).This work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grants AGL2013-44978-R and AGL2017-86946-R [the latter also funded by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERDF)], by the CERCA Programme/Generalitat de Catalunya, by the Agency for Management of University and Research Grants (AGAUR) of the Generalitat de Catalunya (grants 2014 SGR 1528 and 2017 SGR 1060) and by MINECO for the Center of Excellence Severo Ochoa 2016–2019 grant awarded to CRAG (SEV-2015-0533). Marta Gòdia performed this work within the frame of a PhD studentship (BES-2014-070560) and a Short-Stay fellowship (EEBB-I-18-12860), both from MINECO.