Integrating Gene Expression Data into Single-Step Method (ssBLUP) Improves Genomic Prediction Accuracy for Complex Traits of Duroc × Erhualian F<sub>2</sub> Pig Population
The development of multi-omics has increased the likelihood of further improving genomic prediction (GP) of complex traits. Gene expression data can directly reflect the genotype effect, and thus, they are widely used for GP. Generally, the gene expression data are integrated into multiple random ef...
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2024-12-01
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| author | Fangjun Xu Zhaoxuan Che Jiakun Qiao Pingping Han Na Miao Xiangyu Dai Yuhua Fu Xinyun Li Mengjin Zhu |
| author_facet | Fangjun Xu Zhaoxuan Che Jiakun Qiao Pingping Han Na Miao Xiangyu Dai Yuhua Fu Xinyun Li Mengjin Zhu |
| author_sort | Fangjun Xu |
| collection | DOAJ |
| description | The development of multi-omics has increased the likelihood of further improving genomic prediction (GP) of complex traits. Gene expression data can directly reflect the genotype effect, and thus, they are widely used for GP. Generally, the gene expression data are integrated into multiple random effect models as independent data layers or used to replace genotype data for genomic prediction. In this study, we integrated pedigree, genotype, and gene expression data into the single-step method and investigated the effects of this integration on prediction accuracy. The integrated single-step method improved the genomic prediction accuracy of more than 90% of the 54 traits in the Duroc × Erhualian F<sub>2</sub> pig population dataset. On average, the prediction accuracy of the single-step method integrating gene expression data was 20.6% and 11.8% higher than that of the pedigree-based best linear unbiased prediction (ABLUP) and genome-based best linear unbiased prediction (GBLUP) when the weighting factor (<i>w</i>) was set as 0, and it was 5.3% higher than that of the single-step best linear unbiased prediction (ssBLUP) under different <i>w</i> values. Overall, the analyses confirmed that the integration of gene expression data into a single-step method could effectively improve genomic prediction accuracy. Our findings enrich the application of multi-omics data to genomic prediction and provide a valuable reference for integrating multi-omics data into the genomic prediction model. |
| format | Article |
| id | doaj-art-e4dc306bd75b4e2b885602eee7b0a294 |
| institution | DOAJ |
| issn | 1467-3037 1467-3045 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Current Issues in Molecular Biology |
| spelling | doaj-art-e4dc306bd75b4e2b885602eee7b0a2942025-08-20T02:55:49ZengMDPI AGCurrent Issues in Molecular Biology1467-30371467-30452024-12-014612137131372410.3390/cimb46120819Integrating Gene Expression Data into Single-Step Method (ssBLUP) Improves Genomic Prediction Accuracy for Complex Traits of Duroc × Erhualian F<sub>2</sub> Pig PopulationFangjun Xu0Zhaoxuan Che1Jiakun Qiao2Pingping Han3Na Miao4Xiangyu Dai5Yuhua Fu6Xinyun Li7Mengjin Zhu8Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, ChinaKey Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, ChinaKey Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, ChinaKey Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, ChinaKey Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, ChinaKey Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, ChinaThe Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan 430070, ChinaThe Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan 430070, ChinaThe Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan 430070, ChinaThe development of multi-omics has increased the likelihood of further improving genomic prediction (GP) of complex traits. Gene expression data can directly reflect the genotype effect, and thus, they are widely used for GP. Generally, the gene expression data are integrated into multiple random effect models as independent data layers or used to replace genotype data for genomic prediction. In this study, we integrated pedigree, genotype, and gene expression data into the single-step method and investigated the effects of this integration on prediction accuracy. The integrated single-step method improved the genomic prediction accuracy of more than 90% of the 54 traits in the Duroc × Erhualian F<sub>2</sub> pig population dataset. On average, the prediction accuracy of the single-step method integrating gene expression data was 20.6% and 11.8% higher than that of the pedigree-based best linear unbiased prediction (ABLUP) and genome-based best linear unbiased prediction (GBLUP) when the weighting factor (<i>w</i>) was set as 0, and it was 5.3% higher than that of the single-step best linear unbiased prediction (ssBLUP) under different <i>w</i> values. Overall, the analyses confirmed that the integration of gene expression data into a single-step method could effectively improve genomic prediction accuracy. Our findings enrich the application of multi-omics data to genomic prediction and provide a valuable reference for integrating multi-omics data into the genomic prediction model.https://www.mdpi.com/1467-3045/46/12/819genomic predictiongene expression databest linear unbiased predictionsingle-step methodpig |
| spellingShingle | Fangjun Xu Zhaoxuan Che Jiakun Qiao Pingping Han Na Miao Xiangyu Dai Yuhua Fu Xinyun Li Mengjin Zhu Integrating Gene Expression Data into Single-Step Method (ssBLUP) Improves Genomic Prediction Accuracy for Complex Traits of Duroc × Erhualian F<sub>2</sub> Pig Population Current Issues in Molecular Biology genomic prediction gene expression data best linear unbiased prediction single-step method pig |
| title | Integrating Gene Expression Data into Single-Step Method (ssBLUP) Improves Genomic Prediction Accuracy for Complex Traits of Duroc × Erhualian F<sub>2</sub> Pig Population |
| title_full | Integrating Gene Expression Data into Single-Step Method (ssBLUP) Improves Genomic Prediction Accuracy for Complex Traits of Duroc × Erhualian F<sub>2</sub> Pig Population |
| title_fullStr | Integrating Gene Expression Data into Single-Step Method (ssBLUP) Improves Genomic Prediction Accuracy for Complex Traits of Duroc × Erhualian F<sub>2</sub> Pig Population |
| title_full_unstemmed | Integrating Gene Expression Data into Single-Step Method (ssBLUP) Improves Genomic Prediction Accuracy for Complex Traits of Duroc × Erhualian F<sub>2</sub> Pig Population |
| title_short | Integrating Gene Expression Data into Single-Step Method (ssBLUP) Improves Genomic Prediction Accuracy for Complex Traits of Duroc × Erhualian F<sub>2</sub> Pig Population |
| title_sort | integrating gene expression data into single step method ssblup improves genomic prediction accuracy for complex traits of duroc erhualian f sub 2 sub pig population |
| topic | genomic prediction gene expression data best linear unbiased prediction single-step method pig |
| url | https://www.mdpi.com/1467-3045/46/12/819 |
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