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Predictive ability of genomic selection models for breeding value estimation on growth traits of Pacific white shrimp Litopenaeus vannamei
WANG Quanchao1,2; Yu Yang1; Li Fuhua1,3; Zhang Xiaojun1; Xiang Jianhai1
2017-09-01
Source PublicationCHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY
Volume35Issue:5Pages:1221-1229
SubtypeArticle
AbstractGenomic selection (GS) can be used to accelerate genetic improvement by shortening the selection interval. The successful application of GS depends largely on the accuracy of the prediction of genomic estimated breeding value (GEBV). This study is a first attempt to understand the practicality of GS in Litopenaeus vannamei and aims to evaluate models for GS on growth traits. The performance of GS models in L. vannamei was evaluated in a population consisting of 205 individuals, which were genotyped for 6 359 single nucleotide polymorphism (SNP) markers by specific length amplified fragment sequencing (SLAF-seq) and phenotyped for body length and body weight. Three GS models (RR-BLUP, BayesA, and Bayesian LASSO) were used to obtain the GEBV, and their predictive ability was assessed by the reliability of the GEBV and the bias of the predicted phenotypes. The mean reliability of the GEBVs for body length and body weight predicted by the different models was 0.296 and 0.411, respectively. For each trait, the performances of the three models were very similar to each other with respect to predictability. The regression coefficients estimated by the three models were close to one, suggesting near to zero bias for the predictions. Therefore, when GS was applied in a L. vannamei population for the studied scenarios, all three models appeared practicable. Further analyses suggested that improved estimation of the genomic prediction could be realized by increasing the size of the training population as well as the density of SNPs.
KeywordGenomic Selection Model Prediction Growth Traits Penaeid Shrimp
DOI10.1007/s00343-017-6038-0
Indexed BySCI
Language英语
WOS IDWOS:000410093300025
Citation statistics
Document Type期刊论文
Version出版稿
Identifierhttp://ir.qdio.ac.cn/handle/337002/143188
Collection实验海洋生物学重点实验室
Affiliation1.Chinese Acad Sci, Inst Oceanol, Key Lab Expt Marine Biol, Qingdao 266071, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Qingdao Natl Lab Marine Sci & Technol, Qingdao 266071, Peoples R China
First Author Affilication中国科学院海洋研究所
Recommended Citation
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WANG Quanchao,Yu Yang,Li Fuhua,et al. Predictive ability of genomic selection models for breeding value estimation on growth traits of Pacific white shrimp Litopenaeus vannamei[J]. CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY,2017,35(5):1221-1229.
APA WANG Quanchao,Yu Yang,Li Fuhua,Zhang Xiaojun,&Xiang Jianhai.(2017).Predictive ability of genomic selection models for breeding value estimation on growth traits of Pacific white shrimp Litopenaeus vannamei.CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY,35(5),1221-1229.
MLA WANG Quanchao,et al."Predictive ability of genomic selection models for breeding value estimation on growth traits of Pacific white shrimp Litopenaeus vannamei".CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY 35.5(2017):1221-1229.
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