Multivariate genome-wide associations for immune traits in two maternal pig lines

Abstract Background Immune traits are considered to serve as potential biomarkers for pig’s health. Medium to high heritabilities have been observed for some of the immune traits suggesting genetic variability of these phenotypes. Consideration of previously established genetic correlations between...

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Main Authors: Katharina Roth, Maren Julia Pröll-Cornelissen, Hubert Henne, Anne Kathrin Appel, Karl Schellander, Ernst Tholen, Christine Große-Brinkhaus
Format: Article
Language:English
Published: BMC 2023-08-01
Series:BMC Genomics
Subjects:
Online Access:https://doi.org/10.1186/s12864-023-09594-w
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author Katharina Roth
Maren Julia Pröll-Cornelissen
Hubert Henne
Anne Kathrin Appel
Karl Schellander
Ernst Tholen
Christine Große-Brinkhaus
author_facet Katharina Roth
Maren Julia Pröll-Cornelissen
Hubert Henne
Anne Kathrin Appel
Karl Schellander
Ernst Tholen
Christine Große-Brinkhaus
author_sort Katharina Roth
collection DOAJ
description Abstract Background Immune traits are considered to serve as potential biomarkers for pig’s health. Medium to high heritabilities have been observed for some of the immune traits suggesting genetic variability of these phenotypes. Consideration of previously established genetic correlations between immune traits can be used to identify pleiotropic genetic markers. Therefore, genome-wide association study (GWAS) approaches are required to explore the joint genetic foundation for health biomarkers. Usually, GWAS explores phenotypes in a univariate (uv), trait-by-trait manner. Besides two uv GWAS methods, four multivariate (mv) GWAS approaches were applied on combinations out of 22 immune traits for Landrace (LR) and Large White (LW) pig lines. Results In total 433 (LR: 351, LW: 82) associations were identified with the uv approach implemented in PLINK and a Bayesian linear regression uv approach (BIMBAM) software. Single Nucleotide Polymorphisms (SNPs) that were identified with both uv approaches (n = 32) were mostly associated with immune traits such as haptoglobin, red blood cell characteristics and cytokines, and were located in protein-coding genes. Mv GWAS approaches detected 647 associations for different mv immune trait combinations which were summarized to 133 Quantitative Trait Loci (QTL). SNPs for different trait combinations (n = 66) were detected with more than one mv method. Most of these SNPs are associated with red blood cell related immune trait combinations. Functional annotation of these QTL revealed 453 immune-relevant protein-coding genes. With uv methods shared markers were not observed between the breeds, whereas mv approaches were able to detect two conjoint SNPs for LR and LW. Due to unmapped positions for these markers, their functional annotation was not clarified. Conclusions This study evaluated the joint genetic background of immune traits in LR and LW piglets through the application of various uv and mv GWAS approaches. In comparison to uv methods, mv methodologies identified more significant associations, which might reflect the pleiotropic background of the immune system more accurately. In genetic research of complex traits, the SNP effects are generally small. Furthermore, one genetic variant can affect several correlated immune traits at the same time, termed pleiotropy. As mv GWAS methods consider strong dependencies among traits, the power to detect SNPs can be boosted. Both methods revealed immune-relevant potential candidate genes. Our results indicate that one single test is not able to detect all the different types of genetic effects in the most powerful manner and therefore, the methods should be applied complementary.
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spelling doaj.art-16947d685e2a41489abf066718ac52f12023-11-19T12:27:35ZengBMCBMC Genomics1471-21642023-08-0124111610.1186/s12864-023-09594-wMultivariate genome-wide associations for immune traits in two maternal pig linesKatharina Roth0Maren Julia Pröll-Cornelissen1Hubert Henne2Anne Kathrin Appel3Karl Schellander4Ernst Tholen5Christine Große-Brinkhaus6Institute of Animal Science, University of BonnInstitute of Animal Science, University of BonnBHZP GmbHBHZP GmbHInstitute of Animal Science, University of BonnInstitute of Animal Science, University of BonnInstitute of Animal Science, University of BonnAbstract Background Immune traits are considered to serve as potential biomarkers for pig’s health. Medium to high heritabilities have been observed for some of the immune traits suggesting genetic variability of these phenotypes. Consideration of previously established genetic correlations between immune traits can be used to identify pleiotropic genetic markers. Therefore, genome-wide association study (GWAS) approaches are required to explore the joint genetic foundation for health biomarkers. Usually, GWAS explores phenotypes in a univariate (uv), trait-by-trait manner. Besides two uv GWAS methods, four multivariate (mv) GWAS approaches were applied on combinations out of 22 immune traits for Landrace (LR) and Large White (LW) pig lines. Results In total 433 (LR: 351, LW: 82) associations were identified with the uv approach implemented in PLINK and a Bayesian linear regression uv approach (BIMBAM) software. Single Nucleotide Polymorphisms (SNPs) that were identified with both uv approaches (n = 32) were mostly associated with immune traits such as haptoglobin, red blood cell characteristics and cytokines, and were located in protein-coding genes. Mv GWAS approaches detected 647 associations for different mv immune trait combinations which were summarized to 133 Quantitative Trait Loci (QTL). SNPs for different trait combinations (n = 66) were detected with more than one mv method. Most of these SNPs are associated with red blood cell related immune trait combinations. Functional annotation of these QTL revealed 453 immune-relevant protein-coding genes. With uv methods shared markers were not observed between the breeds, whereas mv approaches were able to detect two conjoint SNPs for LR and LW. Due to unmapped positions for these markers, their functional annotation was not clarified. Conclusions This study evaluated the joint genetic background of immune traits in LR and LW piglets through the application of various uv and mv GWAS approaches. In comparison to uv methods, mv methodologies identified more significant associations, which might reflect the pleiotropic background of the immune system more accurately. In genetic research of complex traits, the SNP effects are generally small. Furthermore, one genetic variant can affect several correlated immune traits at the same time, termed pleiotropy. As mv GWAS methods consider strong dependencies among traits, the power to detect SNPs can be boosted. Both methods revealed immune-relevant potential candidate genes. Our results indicate that one single test is not able to detect all the different types of genetic effects in the most powerful manner and therefore, the methods should be applied complementary.https://doi.org/10.1186/s12864-023-09594-wImmune traitsPigsMultivariateGenome-wide Association StudiesImmunocompetenceAnimal Genetics
spellingShingle Katharina Roth
Maren Julia Pröll-Cornelissen
Hubert Henne
Anne Kathrin Appel
Karl Schellander
Ernst Tholen
Christine Große-Brinkhaus
Multivariate genome-wide associations for immune traits in two maternal pig lines
BMC Genomics
Immune traits
Pigs
Multivariate
Genome-wide Association Studies
Immunocompetence
Animal Genetics
title Multivariate genome-wide associations for immune traits in two maternal pig lines
title_full Multivariate genome-wide associations for immune traits in two maternal pig lines
title_fullStr Multivariate genome-wide associations for immune traits in two maternal pig lines
title_full_unstemmed Multivariate genome-wide associations for immune traits in two maternal pig lines
title_short Multivariate genome-wide associations for immune traits in two maternal pig lines
title_sort multivariate genome wide associations for immune traits in two maternal pig lines
topic Immune traits
Pigs
Multivariate
Genome-wide Association Studies
Immunocompetence
Animal Genetics
url https://doi.org/10.1186/s12864-023-09594-w
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