Genomic Evaluation of Harvest Weight Uniformity in <i>Penaeus vannamei</i> Under a 3FAM Design Incorporating Indirect Genetic Effect
Harvest weight uniformity is a critical economic trait in the production of Pacific white shrimp (<i>Penaeus vannamei</i>). Social interactions among individuals can significantly influence both uniformity and productivity in aquaculture. To improve harvest weight uniformity through sele...
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2025-03-01
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| author | Siqi Gao Yan Xia Jie Kong Xianhong Meng Kun Luo Juan Sui Ping Dai Jian Tan Xupeng Li Jiawang Cao Baolong Chen Qiang Fu Qun Xing Yi Tian Junyu Liu Sheng Luan |
| author_facet | Siqi Gao Yan Xia Jie Kong Xianhong Meng Kun Luo Juan Sui Ping Dai Jian Tan Xupeng Li Jiawang Cao Baolong Chen Qiang Fu Qun Xing Yi Tian Junyu Liu Sheng Luan |
| author_sort | Siqi Gao |
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| description | Harvest weight uniformity is a critical economic trait in the production of Pacific white shrimp (<i>Penaeus vannamei</i>). Social interactions among individuals can significantly influence both uniformity and productivity in aquaculture. To improve harvest weight uniformity through selective breeding, it is essential to accurately partition the genetic component of social effects, known as an indirect genetic effect (IGE), from purely environmental factors. Since IGEs cannot be estimated when all individuals are kept in a single group, a specialized experimental design, such as the grouping design with three families per group (3FAM), is required. With this experimental design, the shrimp population is divided into multiple groups (cages), each containing three families. Individuals from each family are then evenly subdivided and placed in three cages, thereby enabling the estimation of both direct and social genetic effects. Additionally, integrating genomic information instead of relying solely on pedigree data improves the accuracy of genetic relatedness among individuals, leading to more precise genetic evaluation. This study employed a 3FAM experimental design involving 40 families (36 individuals per family) to estimate the contribution of direct and indirect genetic effects on harvest weight uniformity. The genotypes of all tested individuals obtained using the 55K SNP panel were incorporated into a hierarchical generalized linear model to predict direct genetic effects and indirect genetic effects (IGE) separately. The results revealed that the heritability of harvest weight uniformity was low (0.005 to 0.017). However, the genetic coefficient of variation (0.340 to 0.528) indicates that using the residual variance in harvest weight as a selection criterion for improving uniformity is feasible. Incorporating IGE into the model increased heritability estimates for uniformity by 150% to 240% and genetic coefficient of variation for uniformity by 32.11% to 55.29%, compared to the model without IGE. Moreover, the genetic correlation between harvest weight and its uniformity shifted from a strongly negative value (−0.862 to −0.683) to a weakly positive value (0.203 to 0.117), suggesting an improvement in the genetic relationship between the traits and better separation of genetic and environmental effects. The inclusion of genomic data enhanced the prediction ability of single-step best linear unbiased prediction for both harvest weight and uniformity by 6.35% and 10.53%, respectively, compared to the pedigree-based best linear unbiased prediction. These findings highlight the importance of incorporating IGE and utilizing genomic selection methods to enhance selection accuracy for obtaining harvest weight uniformity. This approach provides a theoretical foundation for guiding uniformity improvements in shrimp breeding programs and offers potential applications in other food production systems. |
| format | Article |
| id | doaj-art-66fe5778604e4b299c9c258456e65b2f |
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| spelling | doaj-art-66fe5778604e4b299c9c258456e65b2f2025-08-20T02:17:24ZengMDPI AGBiology2079-77372025-03-0114432810.3390/biology14040328Genomic Evaluation of Harvest Weight Uniformity in <i>Penaeus vannamei</i> Under a 3FAM Design Incorporating Indirect Genetic EffectSiqi Gao0Yan Xia1Jie Kong2Xianhong Meng3Kun Luo4Juan Sui5Ping Dai6Jian Tan7Xupeng Li8Jiawang Cao9Baolong Chen10Qiang Fu11Qun Xing12Yi Tian13Junyu Liu14Sheng Luan15College of Fisheries and Life Science, Dalian Ocean University, Dalian 116023, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaBLUP Aquabreed Co., Ltd., Weifang 261311, ChinaCollege of Fisheries and Life Science, Dalian Ocean University, Dalian 116023, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, ChinaHarvest weight uniformity is a critical economic trait in the production of Pacific white shrimp (<i>Penaeus vannamei</i>). Social interactions among individuals can significantly influence both uniformity and productivity in aquaculture. To improve harvest weight uniformity through selective breeding, it is essential to accurately partition the genetic component of social effects, known as an indirect genetic effect (IGE), from purely environmental factors. Since IGEs cannot be estimated when all individuals are kept in a single group, a specialized experimental design, such as the grouping design with three families per group (3FAM), is required. With this experimental design, the shrimp population is divided into multiple groups (cages), each containing three families. Individuals from each family are then evenly subdivided and placed in three cages, thereby enabling the estimation of both direct and social genetic effects. Additionally, integrating genomic information instead of relying solely on pedigree data improves the accuracy of genetic relatedness among individuals, leading to more precise genetic evaluation. This study employed a 3FAM experimental design involving 40 families (36 individuals per family) to estimate the contribution of direct and indirect genetic effects on harvest weight uniformity. The genotypes of all tested individuals obtained using the 55K SNP panel were incorporated into a hierarchical generalized linear model to predict direct genetic effects and indirect genetic effects (IGE) separately. The results revealed that the heritability of harvest weight uniformity was low (0.005 to 0.017). However, the genetic coefficient of variation (0.340 to 0.528) indicates that using the residual variance in harvest weight as a selection criterion for improving uniformity is feasible. Incorporating IGE into the model increased heritability estimates for uniformity by 150% to 240% and genetic coefficient of variation for uniformity by 32.11% to 55.29%, compared to the model without IGE. Moreover, the genetic correlation between harvest weight and its uniformity shifted from a strongly negative value (−0.862 to −0.683) to a weakly positive value (0.203 to 0.117), suggesting an improvement in the genetic relationship between the traits and better separation of genetic and environmental effects. The inclusion of genomic data enhanced the prediction ability of single-step best linear unbiased prediction for both harvest weight and uniformity by 6.35% and 10.53%, respectively, compared to the pedigree-based best linear unbiased prediction. These findings highlight the importance of incorporating IGE and utilizing genomic selection methods to enhance selection accuracy for obtaining harvest weight uniformity. This approach provides a theoretical foundation for guiding uniformity improvements in shrimp breeding programs and offers potential applications in other food production systems.https://www.mdpi.com/2079-7737/14/4/328<i>Penaeus vannamei</i>harvest weight uniformityindirect genetic effectsH matrixgenetic parameters |
| spellingShingle | Siqi Gao Yan Xia Jie Kong Xianhong Meng Kun Luo Juan Sui Ping Dai Jian Tan Xupeng Li Jiawang Cao Baolong Chen Qiang Fu Qun Xing Yi Tian Junyu Liu Sheng Luan Genomic Evaluation of Harvest Weight Uniformity in <i>Penaeus vannamei</i> Under a 3FAM Design Incorporating Indirect Genetic Effect Biology <i>Penaeus vannamei</i> harvest weight uniformity indirect genetic effects H matrix genetic parameters |
| title | Genomic Evaluation of Harvest Weight Uniformity in <i>Penaeus vannamei</i> Under a 3FAM Design Incorporating Indirect Genetic Effect |
| title_full | Genomic Evaluation of Harvest Weight Uniformity in <i>Penaeus vannamei</i> Under a 3FAM Design Incorporating Indirect Genetic Effect |
| title_fullStr | Genomic Evaluation of Harvest Weight Uniformity in <i>Penaeus vannamei</i> Under a 3FAM Design Incorporating Indirect Genetic Effect |
| title_full_unstemmed | Genomic Evaluation of Harvest Weight Uniformity in <i>Penaeus vannamei</i> Under a 3FAM Design Incorporating Indirect Genetic Effect |
| title_short | Genomic Evaluation of Harvest Weight Uniformity in <i>Penaeus vannamei</i> Under a 3FAM Design Incorporating Indirect Genetic Effect |
| title_sort | genomic evaluation of harvest weight uniformity in i penaeus vannamei i under a 3fam design incorporating indirect genetic effect |
| topic | <i>Penaeus vannamei</i> harvest weight uniformity indirect genetic effects H matrix genetic parameters |
| url | https://www.mdpi.com/2079-7737/14/4/328 |
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