Genes Linked to Heat Stress Response in Lactating Mothers

Greg Howard
14th May, 2024

Genes Linked to Heat Stress Response in Lactating Mothers

Image Source: Natural Science News, 2024

Key Findings

  • The study, conducted at the Federal University of Viçosa, aimed to identify genetic markers for heat stress response in lactating sows
  • Researchers analyzed 18 traits and genomic data from 1,645 sows, using over 7 million SNPs after quality control
  • They identified several genomic regions and candidate genes significantly associated with heat stress response traits
  • The study found pleiotropic variants, which influence multiple traits, providing insights for optimizing genetic selection for heat tolerance
Heat stress (HS) poses significant threats to the sustainability of livestock production. Genetically improving heat tolerance could enhance animal welfare and minimize production losses during HS events. Measuring phenotypic indicators of HS response and understanding their genetic background are crucial steps to optimize breeding schemes for improved climatic resilience. The identification of genomic regions and candidate genes influencing the traits of interest, including variants with pleiotropic effects, enables the refinement of genotyping panels used to perform genomic prediction of breeding values and contributes to unraveling the biological mechanisms influencing heat stress response. Therefore, the main objectives of this study were to identify genomic regions, candidate genes, and potential pleiotropic variants significantly associated with indicators of HS response in lactating sows using imputed whole-genome sequence (WGS) data. Phenotypic records for 18 traits and genomic information from 1,645 lactating sows were available for the study. The genotypes from the PorcineSNP50K panel containing 50,703 single nucleotide polymorphisms (SNPs) were imputed to WGS and after quality control, 1,622 animals and 7,065,922 SNPs were included in the analyses. Heat stress (HS) is a growing concern for livestock production, particularly as climate change exacerbates temperature extremes. This study, conducted by researchers at the Federal University of Viçosa, aims to address this problem by identifying the genetic basis of heat tolerance in lactating sows[1]. The findings could significantly enhance breeding programs aimed at producing more heat-resilient livestock, thereby improving animal welfare and production efficiency. The researchers focused on identifying genomic regions and candidate genes associated with heat stress response traits in sows. This involved analyzing phenotypic records for 18 different traits and genomic data from 1,645 lactating sows. The genotypes were derived from the PorcineSNP50K panel, which contains over 50,000 single nucleotide polymorphisms (SNPs). After quality control, data from 1,622 animals and over 7 million SNPs were included in the analysis. Pleiotropy, where a single gene affects multiple traits, is a key concept in this study. Understanding pleiotropic effects can help refine genotyping panels and enhance genomic predictions for breeding[2]. The study's focus on identifying pleiotropic variants aligns with the broader goal of understanding how multiple traits can be optimized simultaneously through genetic selection. Heat stress impacts livestock by reducing milk yield, meat production, and fertility, thereby threatening food security[3]. Identifying genetic markers for heat tolerance is crucial for developing climate-resilient livestock. The use of mixed models in genome-wide association studies (GWAS) has been shown to improve the statistical power for identifying nucleotide variants associated with quantitative traits[4]. This study employs similar methodologies to ensure robust findings. The researchers utilized imputed whole-genome sequence (WGS) data to increase the resolution of their genetic analysis. Imputation is a statistical technique that infers missing genotypes, thereby enhancing the accuracy of genomic data. This approach allowed the researchers to identify more genetic variants associated with heat stress response traits. The study found several genomic regions and candidate genes significantly associated with heat stress response traits. These findings contribute to a better understanding of the biological mechanisms underlying heat tolerance. By identifying pleiotropic variants, the study also provides valuable insights into how multiple traits can be simultaneously optimized through genetic selection. The statistical power of GWAS is influenced by factors such as heritability, the number of causal variants, and polygenic variance[4][5]. This study took these factors into account to ensure robust and reliable results. The findings are expected to improve the design of future GWAS for traits related to heat stress and other environmental challenges. In summary, this study by the Federal University of Viçosa provides valuable insights into the genetic basis of heat tolerance in lactating sows. By identifying genomic regions, candidate genes, and pleiotropic variants associated with heat stress response traits, the research offers a pathway to developing more climate-resilient livestock. This is crucial for sustaining livestock production in the face of climate change, thereby ensuring food security and animal welfare.

GeneticsBiochemAnimal Science

References

Main Study

1) Genomic regions, candidate genes, and pleiotropic variants associated with physiological and anatomical indicators of heat stress response in lactating sows

Published 13th May, 2024

https://doi.org/10.1186/s12864-024-10365-4

Related Studies

2) One hundred years of pleiotropy: a retrospective.

https://doi.org/10.1534/genetics.110.122549

3) Review: Adaptation of animals to heat stress.

https://doi.org/10.1017/S1751731118001945

4) Statistical power for identifying nucleotide markers associated with quantitative traits in genome-wide association analysis using a mixed model.

https://doi.org/10.1016/j.ygeno.2014.11.001

5) The statistical power of genome-wide association studies for threshold traits with different frequencies of causal variants.

https://doi.org/10.1007/s10709-021-00140-8


Related Articles

An unhandled error has occurred. Reload 🗙