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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Format: | Article |
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Frontiers Media S.A.
2020-05-01
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Series: | Frontiers in Genetics |
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Online Access: | https://www.frontiersin.org/article/10.3389/fgene.2020.00481/full |
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doaj-8362a516425b460fab1697dfe1468983 |
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record_format |
Article |
collection |
DOAJ |
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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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 |