Aakilah S Hernandez, Gabriel A Zayas, Eduardo E Rodriguez, Kaitlyn M Sarlo Davila, Fahad Rafiq, Andrea N Nunez, Cristiane Gonçalves Titto, Raluca G Mateescu
{"title":"Exploring the genetic control of sweat gland characteristics in beef cattle for enhanced heat tolerance.","authors":"Aakilah S Hernandez, Gabriel A Zayas, Eduardo E Rodriguez, Kaitlyn M Sarlo Davila, Fahad Rafiq, Andrea N Nunez, Cristiane Gonçalves Titto, Raluca G Mateescu","doi":"10.1186/s40104-024-01025-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Thermal stress in subtropical regions is a major limiting factor in beef cattle production systems with around $369 million being lost annually due to reduced performance. Heat stress causes numerous physiological and behavioral disturbances including reduced feed intake and decreased production levels. Cattle utilize various physiological mechanisms such as sweating to regulate internal heat. Variation in these traits can help identify genetic variants that control sweat gland properties and subsequently allow for genetic selection of cattle with greater thermotolerance.</p><p><strong>Methods: </strong>This study used 2,401 Brangus cattle from two commercial ranches in Florida. Precise phenotypes that contribute to an animal's ability to manage heat stress were calculated from skin biopsies and included sweat gland area, sweat gland depth, and sweat gland length. All animals were genotyped with the Bovine GGP F250K, and BLUPF90 software was used to estimate genetic parameters and for Genome Wide Association Study.</p><p><strong>Results: </strong>Sweat gland phenotypes heritability ranged from 0.17 to 0.42 indicating a moderate amount of the phenotypic variation is due to genetics, allowing producers the ability to select for favorable sweat gland properties. A weighted single-step GWAS using sliding 10 kb windows identified multiple quantitative trait loci (QTLs) explaining a significant amount of genetic variation. QTLs located on BTA7 and BTA12 explained over 1.0% of genetic variance and overlap the ADGRV1 and CCDC168 genes, respectively. The variants identified in this study are implicated in processes related to immune function and cellular proliferation which could be relevant to heat management. Breed of Origin Alleles (BOA) were predicted using local ancestry in admixed populations (LAMP-LD), allowing for identification of markers' origin from either Brahman or Angus ancestry. A BOA GWAS was performed to identify regions inherited from particular ancestral breeds that might have a significant impact on sweat gland phenotypes.</p><p><strong>Conclusions: </strong>The results of the BOA GWAS indicate that both Brahman and Angus alleles contribute positively to sweat gland traits, as evidenced by favorable marker effects observed from both genetic backgrounds. Understanding and utilizing genetic traits that confer better heat tolerance is a proactive approach to managing the impacts of climate change on livestock farming.</p>","PeriodicalId":64067,"journal":{"name":"Journal of Animal Science and Biotechnology","volume":"15 1","pages":"66"},"PeriodicalIF":6.3000,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11077762/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Animal Science and Biotechnology","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.1186/s40104-024-01025-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, DAIRY & ANIMAL SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Thermal stress in subtropical regions is a major limiting factor in beef cattle production systems with around $369 million being lost annually due to reduced performance. Heat stress causes numerous physiological and behavioral disturbances including reduced feed intake and decreased production levels. Cattle utilize various physiological mechanisms such as sweating to regulate internal heat. Variation in these traits can help identify genetic variants that control sweat gland properties and subsequently allow for genetic selection of cattle with greater thermotolerance.
Methods: This study used 2,401 Brangus cattle from two commercial ranches in Florida. Precise phenotypes that contribute to an animal's ability to manage heat stress were calculated from skin biopsies and included sweat gland area, sweat gland depth, and sweat gland length. All animals were genotyped with the Bovine GGP F250K, and BLUPF90 software was used to estimate genetic parameters and for Genome Wide Association Study.
Results: Sweat gland phenotypes heritability ranged from 0.17 to 0.42 indicating a moderate amount of the phenotypic variation is due to genetics, allowing producers the ability to select for favorable sweat gland properties. A weighted single-step GWAS using sliding 10 kb windows identified multiple quantitative trait loci (QTLs) explaining a significant amount of genetic variation. QTLs located on BTA7 and BTA12 explained over 1.0% of genetic variance and overlap the ADGRV1 and CCDC168 genes, respectively. The variants identified in this study are implicated in processes related to immune function and cellular proliferation which could be relevant to heat management. Breed of Origin Alleles (BOA) were predicted using local ancestry in admixed populations (LAMP-LD), allowing for identification of markers' origin from either Brahman or Angus ancestry. A BOA GWAS was performed to identify regions inherited from particular ancestral breeds that might have a significant impact on sweat gland phenotypes.
Conclusions: The results of the BOA GWAS indicate that both Brahman and Angus alleles contribute positively to sweat gland traits, as evidenced by favorable marker effects observed from both genetic backgrounds. Understanding and utilizing genetic traits that confer better heat tolerance is a proactive approach to managing the impacts of climate change on livestock farming.