Genomic selection strategies to overcome genotype by environment interactions in biosecurity-based aquaculture breeding programs
Abstract Background Family-based selective breeding programs typically employ both between-family and within-family selection in aquaculture. However, these programs may exhibit a reduced genetic gain in the presence of a genotype by environment interactions (G × E) when employing biosecurity-based...
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2025-01-01
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| Series: | Genetics Selection Evolution |
| Online Access: | https://doi.org/10.1186/s12711-025-00949-3 |
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| author | Ziyi Kang Jie Kong Qi Li Juan Sui Ping Dai Kun Luo Xianhong Meng Baolong Chen Jiawang Cao Jian Tan Qiang Fu Qun Xing Sheng Luan |
| author_facet | Ziyi Kang Jie Kong Qi Li Juan Sui Ping Dai Kun Luo Xianhong Meng Baolong Chen Jiawang Cao Jian Tan Qiang Fu Qun Xing Sheng Luan |
| author_sort | Ziyi Kang |
| collection | DOAJ |
| description | Abstract Background Family-based selective breeding programs typically employ both between-family and within-family selection in aquaculture. However, these programs may exhibit a reduced genetic gain in the presence of a genotype by environment interactions (G × E) when employing biosecurity-based breeding schemes (BS), compared to non-biosecurity-based breeding schemes (NBS). Fortunately, genomic selection shows promise in improving genetic gain by taking within-family variance into account. Stochastic simulation was employed to evaluate genetic gain and G × E trends in BS for improving the body weight of L. vannamei, considering selective genotyping strategies for test group (TG) at a commercial farm environment (CE), the number individuals of the selection group (SG) genotyped at nucleus breeding center (NE), and varying levels of G × E. Results The loss of genetic gain in BS ranged from 9.4 to 38.9% in pedigree-based selection and was more pronounced when G × E was stronger, as quantified by a lower genetic correlation for body weight between NE and CE. Genomic selection, particularly with selective genotyping of TG individuals with extreme performance, effectively offset the loss of genetic gain. With a genetic correlation of 0.8, genotyping 20 SG individuals in each candidate family achieved 93.2% of the genetic gain observed for NBS. However, when the genetic correlation fell below 0.5, the number of genotyped SG individuals per family had to be increased to 50 or more. Genetic gain improved by on average 9.4% when the number of genotyped SG individuals rose from 20 to 50, but the increase in genetic gain averaged only 2.4% when expanding from 50 to 80 individuals genotyped. In addition, the genetic correlation decreased by on average 0.13 over 30 generations of selection when performing BS and the genetic correlation fluctuated across generations. Conclusions Genomic selection can effectively compensate for the loss of genetic gain in BS due to G × E. However, the number of genotyped SG individuals and the level of G × E significantly affected the extra genetic gain from genomic selection. A family-based BS selective breeding program should monitor the level of G × E and genotyping 50 SG individuals per candidate family to minimize the loss of genetic gain due to G × E, unless the level of G × E is confirmed to be low. |
| format | Article |
| id | doaj-art-1d5cf4ef30c54a87818b0169a46f72ac |
| institution | Kabale University |
| issn | 1297-9686 |
| language | deu |
| publishDate | 2025-01-01 |
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| series | Genetics Selection Evolution |
| spelling | doaj-art-1d5cf4ef30c54a87818b0169a46f72ac2025-01-26T12:10:15ZdeuBMCGenetics Selection Evolution1297-96862025-01-0157111510.1186/s12711-025-00949-3Genomic selection strategies to overcome genotype by environment interactions in biosecurity-based aquaculture breeding programsZiyi Kang0Jie Kong1Qi Li2Juan Sui3Ping Dai4Kun Luo5Xianhong Meng6Baolong Chen7Jiawang Cao8Jian Tan9Qiang Fu10Qun Xing11Sheng Luan12State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery SciencesState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery SciencesOcean University of China, Fisheries CollegeState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery SciencesState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery SciencesState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery SciencesState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery SciencesState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery SciencesState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery SciencesState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery SciencesState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery SciencesBLUP Aquabreed Co., Ltd.State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery SciencesAbstract Background Family-based selective breeding programs typically employ both between-family and within-family selection in aquaculture. However, these programs may exhibit a reduced genetic gain in the presence of a genotype by environment interactions (G × E) when employing biosecurity-based breeding schemes (BS), compared to non-biosecurity-based breeding schemes (NBS). Fortunately, genomic selection shows promise in improving genetic gain by taking within-family variance into account. Stochastic simulation was employed to evaluate genetic gain and G × E trends in BS for improving the body weight of L. vannamei, considering selective genotyping strategies for test group (TG) at a commercial farm environment (CE), the number individuals of the selection group (SG) genotyped at nucleus breeding center (NE), and varying levels of G × E. Results The loss of genetic gain in BS ranged from 9.4 to 38.9% in pedigree-based selection and was more pronounced when G × E was stronger, as quantified by a lower genetic correlation for body weight between NE and CE. Genomic selection, particularly with selective genotyping of TG individuals with extreme performance, effectively offset the loss of genetic gain. With a genetic correlation of 0.8, genotyping 20 SG individuals in each candidate family achieved 93.2% of the genetic gain observed for NBS. However, when the genetic correlation fell below 0.5, the number of genotyped SG individuals per family had to be increased to 50 or more. Genetic gain improved by on average 9.4% when the number of genotyped SG individuals rose from 20 to 50, but the increase in genetic gain averaged only 2.4% when expanding from 50 to 80 individuals genotyped. In addition, the genetic correlation decreased by on average 0.13 over 30 generations of selection when performing BS and the genetic correlation fluctuated across generations. Conclusions Genomic selection can effectively compensate for the loss of genetic gain in BS due to G × E. However, the number of genotyped SG individuals and the level of G × E significantly affected the extra genetic gain from genomic selection. A family-based BS selective breeding program should monitor the level of G × E and genotyping 50 SG individuals per candidate family to minimize the loss of genetic gain due to G × E, unless the level of G × E is confirmed to be low.https://doi.org/10.1186/s12711-025-00949-3 |
| spellingShingle | Ziyi Kang Jie Kong Qi Li Juan Sui Ping Dai Kun Luo Xianhong Meng Baolong Chen Jiawang Cao Jian Tan Qiang Fu Qun Xing Sheng Luan Genomic selection strategies to overcome genotype by environment interactions in biosecurity-based aquaculture breeding programs Genetics Selection Evolution |
| title | Genomic selection strategies to overcome genotype by environment interactions in biosecurity-based aquaculture breeding programs |
| title_full | Genomic selection strategies to overcome genotype by environment interactions in biosecurity-based aquaculture breeding programs |
| title_fullStr | Genomic selection strategies to overcome genotype by environment interactions in biosecurity-based aquaculture breeding programs |
| title_full_unstemmed | Genomic selection strategies to overcome genotype by environment interactions in biosecurity-based aquaculture breeding programs |
| title_short | Genomic selection strategies to overcome genotype by environment interactions in biosecurity-based aquaculture breeding programs |
| title_sort | genomic selection strategies to overcome genotype by environment interactions in biosecurity based aquaculture breeding programs |
| url | https://doi.org/10.1186/s12711-025-00949-3 |
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