Incorporating Genome Annotation Into Genomic Prediction for Carcass Traits in Chinese Simmental Beef Cattle

Various methods have been proposed for genomic prediction (GP) in livestock. These methods have mainly focused on statistical considerations and did not include genome annotation information. In this study, to improve the predictive performance of carcass traits in Chinese Simmental beef cattle, we...

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Main Authors: Ling Xu, Ning Gao, Zezhao Wang, Lei Xu, Ying Liu, Yan Chen, Lingyang Xu, Xue Gao, Lupei Zhang, Huijiang Gao, Bo Zhu, Junya Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-05-01
Series:Frontiers in Genetics
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fgene.2020.00481/full
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language English
format Article
sources DOAJ
author Ling Xu
Ning Gao
Zezhao Wang
Lei Xu
Ying Liu
Yan Chen
Lingyang Xu
Xue Gao
Lupei Zhang
Huijiang Gao
Huijiang Gao
Bo Zhu
Bo Zhu
Junya Li
Junya Li
spellingShingle Ling Xu
Ning Gao
Zezhao Wang
Lei Xu
Ying Liu
Yan Chen
Lingyang Xu
Xue Gao
Lupei Zhang
Huijiang Gao
Huijiang Gao
Bo Zhu
Bo Zhu
Junya Li
Junya Li
Incorporating Genome Annotation Into Genomic Prediction for Carcass Traits in Chinese Simmental Beef Cattle
Frontiers in Genetics
genomic prediction
genome annotation
haplotype
Chinese Simmental beef cattle
prediction accuracy
author_facet Ling Xu
Ning Gao
Zezhao Wang
Lei Xu
Ying Liu
Yan Chen
Lingyang Xu
Xue Gao
Lupei Zhang
Huijiang Gao
Huijiang Gao
Bo Zhu
Bo Zhu
Junya Li
Junya Li
author_sort Ling Xu
title Incorporating Genome Annotation Into Genomic Prediction for Carcass Traits in Chinese Simmental Beef Cattle
title_short Incorporating Genome Annotation Into Genomic Prediction for Carcass Traits in Chinese Simmental Beef Cattle
title_full Incorporating Genome Annotation Into Genomic Prediction for Carcass Traits in Chinese Simmental Beef Cattle
title_fullStr Incorporating Genome Annotation Into Genomic Prediction for Carcass Traits in Chinese Simmental Beef Cattle
title_full_unstemmed Incorporating Genome Annotation Into Genomic Prediction for Carcass Traits in Chinese Simmental Beef Cattle
title_sort incorporating genome annotation into genomic prediction for carcass traits in chinese simmental beef cattle
publisher Frontiers Media S.A.
series Frontiers in Genetics
issn 1664-8021
publishDate 2020-05-01
description Various methods have been proposed for genomic prediction (GP) in livestock. These methods have mainly focused on statistical considerations and did not include genome annotation information. In this study, to improve the predictive performance of carcass traits in Chinese Simmental beef cattle, we incorporated the genome annotation information into GP. Single nucleotide polymorphisms (SNPs) were annotated to five genomic classes: intergenic, gene, exon, protein coding sequences, and 3′/5′ untranslated region. Haploblocks were constructed for all markers and these five genomic classes by defining a biologically functional unit, and haplotype effects were modeled in both numerical dosage and categorical coding strategies. The first-order epistatic effects among SNPs and haplotypes were modeled using a categorical epistasis model. For all makers, the extension from the SNP-based model to a haplotype-based model improved the accuracy by 5.4–9.8% for carcass weight (CW), live weight (LW), and striploin (SI). For the five genomic classes using the haplotype-based prediction model, the incorporation of gene class information into the model improved the accuracies by an average of 1.4, 2.1, and 1.3% for CW, LW, and SI, respectively, compared with their corresponding results for all markers. Including the first-order epistatic effects into the prediction models improved the accuracies in some traits and genomic classes. Therefore, for traits with moderate-to-high heritability, incorporating genome annotation information of gene class into haplotype-based prediction models could be considered as a promising tool for GP in Chinese Simmental beef cattle, and modeling epistasis in prediction can further increase the accuracy to some degree.
topic genomic prediction
genome annotation
haplotype
Chinese Simmental beef cattle
prediction accuracy
url https://www.frontiersin.org/article/10.3389/fgene.2020.00481/full
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spelling doaj-8362a516425b460fab1697dfe14689832020-11-25T02:20:13ZengFrontiers Media S.A.Frontiers in Genetics1664-80212020-05-011110.3389/fgene.2020.00481519544Incorporating Genome Annotation Into Genomic Prediction for Carcass Traits in Chinese Simmental Beef CattleLing Xu0Ning Gao1Zezhao Wang2Lei Xu3Ying Liu4Yan Chen5Lingyang Xu6Xue Gao7Lupei Zhang8Huijiang Gao9Huijiang Gao10Bo Zhu11Bo Zhu12Junya Li13Junya Li14Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, ChinaState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, ChinaLaboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, ChinaLaboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, ChinaLaboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, ChinaLaboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, ChinaLaboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, ChinaLaboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, ChinaLaboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, ChinaLaboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, ChinaNational Centre of Beef Cattle Genetic Evaluation, Beijing, ChinaLaboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, ChinaNational Centre of Beef Cattle Genetic Evaluation, Beijing, ChinaLaboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, ChinaNational Centre of Beef Cattle Genetic Evaluation, Beijing, ChinaVarious methods have been proposed for genomic prediction (GP) in livestock. These methods have mainly focused on statistical considerations and did not include genome annotation information. In this study, to improve the predictive performance of carcass traits in Chinese Simmental beef cattle, we incorporated the genome annotation information into GP. Single nucleotide polymorphisms (SNPs) were annotated to five genomic classes: intergenic, gene, exon, protein coding sequences, and 3′/5′ untranslated region. Haploblocks were constructed for all markers and these five genomic classes by defining a biologically functional unit, and haplotype effects were modeled in both numerical dosage and categorical coding strategies. The first-order epistatic effects among SNPs and haplotypes were modeled using a categorical epistasis model. For all makers, the extension from the SNP-based model to a haplotype-based model improved the accuracy by 5.4–9.8% for carcass weight (CW), live weight (LW), and striploin (SI). For the five genomic classes using the haplotype-based prediction model, the incorporation of gene class information into the model improved the accuracies by an average of 1.4, 2.1, and 1.3% for CW, LW, and SI, respectively, compared with their corresponding results for all markers. Including the first-order epistatic effects into the prediction models improved the accuracies in some traits and genomic classes. Therefore, for traits with moderate-to-high heritability, incorporating genome annotation information of gene class into haplotype-based prediction models could be considered as a promising tool for GP in Chinese Simmental beef cattle, and modeling epistasis in prediction can further increase the accuracy to some degree.https://www.frontiersin.org/article/10.3389/fgene.2020.00481/fullgenomic predictiongenome annotationhaplotypeChinese Simmental beef cattleprediction accuracy