Multi-Trait Genomic Prediction of Meat Yield in Pacific Whiteleg Shrimp (<i>Penaeus vannamei</i>)

The meat yield (MY) is a key economic trait in Pacific whiteleg shrimp (<i>Penaeus vannamei</i>) breeding, necessitating accurate genomic prediction for efficient genetic improvement. In this study, we investigated single-trait (STGMs) and multi-trait genomic models (MTGMs) for predictin...

Full description

Saved in:
Bibliographic Details
Main Authors: Shiwei Zhang, Jie Kong, Jian Tan, Xianhong Meng, Ping Dai, Jiawang Cao, Kun Luo, Mianyu Liu, Qun Xing, Yi Tian, Juan Sui, Sheng Luan
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Animals
Subjects:
Online Access:https://www.mdpi.com/2076-2615/15/8/1165
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850143531788664832
author Shiwei Zhang
Jie Kong
Jian Tan
Xianhong Meng
Ping Dai
Jiawang Cao
Kun Luo
Mianyu Liu
Qun Xing
Yi Tian
Juan Sui
Sheng Luan
author_facet Shiwei Zhang
Jie Kong
Jian Tan
Xianhong Meng
Ping Dai
Jiawang Cao
Kun Luo
Mianyu Liu
Qun Xing
Yi Tian
Juan Sui
Sheng Luan
author_sort Shiwei Zhang
collection DOAJ
description The meat yield (MY) is a key economic trait in Pacific whiteleg shrimp (<i>Penaeus vannamei</i>) breeding, necessitating accurate genomic prediction for efficient genetic improvement. In this study, we investigated single-trait (STGMs) and multi-trait genomic models (MTGMs) for predicting MY and related traits, using two cross-validation strategies reflecting different data-availability scenarios. A total of 899 individuals from 63 full-sibling families were phenotyped for MY, net meat weight (MW), body weight (BW), body length (BL), and abdominal segment length (AL). We estimated the genomic heritability and genetic correlations of MY and related traits in <i>P. vannamei</i>, followed by comparing the prediction accuracy of STGMs and MTGMs for MY and MW. Two validation approaches were then applied: CV1 retained auxiliary traits in the validation sets, and CV2 excluded both target and auxiliary traits. Heritability estimates indicated that MY had low heritability (STGM: 0.160; MTGMs: 0.145–0.156), whereas MW, BW, BL, and AL showed low-to-moderate heritability (0.099–0.204). Genetic correlations revealed strong associations between MY and MW/BW/BL (<i>r<sub>g</sub></i> = 0.605–0.783), yet a low positive correlation with AL (<i>r<sub>g</sub></i> = 0.286). Across all comparisons, MTGMs consistently surpassed STGMs. For MY, MTGMs improved the accuracy by 4.8–58.8% relative to STGM (0.187), with the MY-MW model achieving the highest accuracy (0.297) under CV1. Similarly, MTGMs enhanced MW prediction by 36.6–138.2% over STGM (0.254), with the MW-BW model reaching the highest accuracy (0.605) under CV1. Notably, retaining auxiliary traits (CV1) boosted accuracy gains substantially (up to 138.2%), whereas excluding them (CV2) yielded only marginal improvements (≤8.6%). Moreover, incorporating AL as an auxiliary trait increased heritability estimates for MW, BW, and BL by 5.4–7.6%, indicating its synergistic value in MTGMs. Overall, these results demonstrate that MTGMs markedly enhance genomic prediction for carcass traits compared to STGMs, particularly when auxiliary trait data are accessible (CV1). The findings underscore the importance of maintaining auxiliary trait records in breeding populations, offering a robust framework for improving <i>P. vannamei</i> through multi-trait genomic prediction models.
format Article
id doaj-art-9bd4d2d503964a94a1e40ce8b29f0541
institution OA Journals
issn 2076-2615
language English
publishDate 2025-04-01
publisher MDPI AG
record_format Article
series Animals
spelling doaj-art-9bd4d2d503964a94a1e40ce8b29f05412025-08-20T02:28:40ZengMDPI AGAnimals2076-26152025-04-01158116510.3390/ani15081165Multi-Trait Genomic Prediction of Meat Yield in Pacific Whiteleg Shrimp (<i>Penaeus vannamei</i>)Shiwei Zhang0Jie Kong1Jian Tan2Xianhong Meng3Ping Dai4Jiawang Cao5Kun Luo6Mianyu Liu7Qun Xing8Yi Tian9Juan Sui10Sheng Luan11College 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 Science, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Science, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Science, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Science, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Science, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Science, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Science, 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 Science, Qingdao 266071, ChinaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Science, Qingdao 266071, ChinaThe meat yield (MY) is a key economic trait in Pacific whiteleg shrimp (<i>Penaeus vannamei</i>) breeding, necessitating accurate genomic prediction for efficient genetic improvement. In this study, we investigated single-trait (STGMs) and multi-trait genomic models (MTGMs) for predicting MY and related traits, using two cross-validation strategies reflecting different data-availability scenarios. A total of 899 individuals from 63 full-sibling families were phenotyped for MY, net meat weight (MW), body weight (BW), body length (BL), and abdominal segment length (AL). We estimated the genomic heritability and genetic correlations of MY and related traits in <i>P. vannamei</i>, followed by comparing the prediction accuracy of STGMs and MTGMs for MY and MW. Two validation approaches were then applied: CV1 retained auxiliary traits in the validation sets, and CV2 excluded both target and auxiliary traits. Heritability estimates indicated that MY had low heritability (STGM: 0.160; MTGMs: 0.145–0.156), whereas MW, BW, BL, and AL showed low-to-moderate heritability (0.099–0.204). Genetic correlations revealed strong associations between MY and MW/BW/BL (<i>r<sub>g</sub></i> = 0.605–0.783), yet a low positive correlation with AL (<i>r<sub>g</sub></i> = 0.286). Across all comparisons, MTGMs consistently surpassed STGMs. For MY, MTGMs improved the accuracy by 4.8–58.8% relative to STGM (0.187), with the MY-MW model achieving the highest accuracy (0.297) under CV1. Similarly, MTGMs enhanced MW prediction by 36.6–138.2% over STGM (0.254), with the MW-BW model reaching the highest accuracy (0.605) under CV1. Notably, retaining auxiliary traits (CV1) boosted accuracy gains substantially (up to 138.2%), whereas excluding them (CV2) yielded only marginal improvements (≤8.6%). Moreover, incorporating AL as an auxiliary trait increased heritability estimates for MW, BW, and BL by 5.4–7.6%, indicating its synergistic value in MTGMs. Overall, these results demonstrate that MTGMs markedly enhance genomic prediction for carcass traits compared to STGMs, particularly when auxiliary trait data are accessible (CV1). The findings underscore the importance of maintaining auxiliary trait records in breeding populations, offering a robust framework for improving <i>P. vannamei</i> through multi-trait genomic prediction models.https://www.mdpi.com/2076-2615/15/8/1165<i>Penaeus vannamei</i>meat yieldnet meat weightheritabilitymulti-trait genomic prediction
spellingShingle Shiwei Zhang
Jie Kong
Jian Tan
Xianhong Meng
Ping Dai
Jiawang Cao
Kun Luo
Mianyu Liu
Qun Xing
Yi Tian
Juan Sui
Sheng Luan
Multi-Trait Genomic Prediction of Meat Yield in Pacific Whiteleg Shrimp (<i>Penaeus vannamei</i>)
Animals
<i>Penaeus vannamei</i>
meat yield
net meat weight
heritability
multi-trait genomic prediction
title Multi-Trait Genomic Prediction of Meat Yield in Pacific Whiteleg Shrimp (<i>Penaeus vannamei</i>)
title_full Multi-Trait Genomic Prediction of Meat Yield in Pacific Whiteleg Shrimp (<i>Penaeus vannamei</i>)
title_fullStr Multi-Trait Genomic Prediction of Meat Yield in Pacific Whiteleg Shrimp (<i>Penaeus vannamei</i>)
title_full_unstemmed Multi-Trait Genomic Prediction of Meat Yield in Pacific Whiteleg Shrimp (<i>Penaeus vannamei</i>)
title_short Multi-Trait Genomic Prediction of Meat Yield in Pacific Whiteleg Shrimp (<i>Penaeus vannamei</i>)
title_sort multi trait genomic prediction of meat yield in pacific whiteleg shrimp i penaeus vannamei i
topic <i>Penaeus vannamei</i>
meat yield
net meat weight
heritability
multi-trait genomic prediction
url https://www.mdpi.com/2076-2615/15/8/1165
work_keys_str_mv AT shiweizhang multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii
AT jiekong multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii
AT jiantan multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii
AT xianhongmeng multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii
AT pingdai multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii
AT jiawangcao multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii
AT kunluo multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii
AT mianyuliu multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii
AT qunxing multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii
AT yitian multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii
AT juansui multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii
AT shengluan multitraitgenomicpredictionofmeatyieldinpacificwhitelegshrimpipenaeusvannameii