Dataset Information

Evaluation of the 2b-RAD method for genomic selection in scallop breeding.

ABSTRACT: The recently developed 2b-restriction site-associated DNA (2b-RAD) sequencing method provides a cost-effective and flexible genotyping platform for aquaculture species lacking sufficient genomic resources. Here, we evaluated the performance of this method in the genomic selection (GS) of Yesso scallop (Patinopecten yessoensis) through simulation and real data analyses using six statistical models. Our simulation analysis revealed that the prediction accuracies obtained using the 2b-RAD markers were slightly lower than those obtained using all polymorphic loci in the genome. Furthermore, a small subset of markers obtained from a reduced tag representation (RTR) library presented comparable performance to that obtained using all markers, making RTR be an attractive approach for GS purpose. Six GS models exhibited variable performance in prediction accuracy depending on the scenarios (e.g., heritability, sample size, population structure), but Bayes-alphabet and BLUP-based models generally outperformed other models. Finally, we performed the evaluation using an empirical dataset composed of 349 Yesso scallops that were derived from five families. The prediction accuracy for this empirical dataset could reach 0.4 based on optimal GS models. In summary, the genotyping flexibility and cost-effectiveness make 2b-RAD be an ideal genotyping platform for genomic selection in aquaculture breeding programs.

SUBMITTER: Dou J

PROVIDER: S-EPMC4709697 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Evaluation of the 2b-RAD method for genomic selection in scallop breeding.

Dou Jinzhuang J Li Xue X Fu Qiang Q Jiao Wenqian W Li Yangping Y Li Tianqi T Wang Yangfan Y Hu Xiaoli X Wang Shi S Bao Zhenmin Z

Scientific reports 20160112

The recently developed 2b-restriction site-associated DNA (2b-RAD) sequencing method provides a cost-effective and flexible genotyping platform for aquaculture species lacking sufficient genomic resources. Here, we evaluated the performance of this method in the genomic selection (GS) of Yesso scallop (Patinopecten yessoensis) through simulation and real data analyses using six statistical models. Our simulation analysis revealed that the prediction accuracies obtained using the 2b-RAD markers w ...[more]

PMID: 26754638

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Project description:Gilthead sea bream (Sparus aurata) is a species of paramount importance to the Mediterranean aquaculture industry, with an annual production exceeding 140,000 metric tonnes. Pasteurellosis due to the Gram-negative bacterium Photobacterium damselae subsp. piscicida (Phdp) causes significant mortality, especially during larval and juvenile stages, and poses a serious threat to bream production. Selective breeding for improved resistance to pasteurellosis is a promising avenue for disease control, and the use of genetic markers to predict breeding values can improve the accuracy of selection, and allow accurate calculation of estimated breeding values (EBV) of non-challenged animals. In the current study, a population of 825 sea bream juveniles, originating from a factorial cross between 67 broodfish (32 sires; 35 dams), were challenged by 30 min immersion with 1 × 10(5) CFU virulent Phdp. Mortalities and survivors were recorded and sampled for genotyping by sequencing. The 2b-RAD sequencing approach was used to generate genome-wide SNP genotypes for all samples. A high-density linkage map containing 12,085 SNPs grouped into 24 linkage groups (consistent with the karyotype) was constructed. The heritability of surviving days (censored data) was 0.22 (95% highest density interval: 0.11-0.36) and 0.28 (95% highest density interval: 0.17-0.4) using the pedigree and the genomic relationship matrix respectively. A genome wide association study did not reveal individual SNPs significantly associated with resistance at a genome wide significance level. Genomic prediction approaches were tested to investigate the potential of the SNPs obtained by 2bRAD for estimating breeding values for resistance. The accuracy of the genomic prediction models (r = 0.38 - 0.46) outperformed the traditional BLUP approach based on pedigree records (r = 0.30). Overall results suggest that major quantitative trait loci (QTL) affecting resistance to pasteurellosis were not present in this population, but highlight the effectiveness of 2b-RAD genotyping by sequencing for genomic selection in a mass spawning fish species.

Project description:Key messageWe evaluated genomic selection across five breeding cycles of bread wheat breeding. Bias of within-cycle cross-validation and methods for improving the prediction accuracy were assessed. The prospect of genomic selection has been frequently shown by cross-validation studies using the same genetic material across multiple environments, but studies investigating genomic selection across multiple breeding cycles in applied bread wheat breeding are lacking. We estimated the prediction accuracy of grain yield, protein content and protein yield of 659 inbred lines across five independent breeding cycles and assessed the bias of within-cycle cross-validation. We investigated the influence of outliers on the prediction accuracy and predicted protein yield by its components traits. A high average heritability was estimated for protein content, followed by grain yield and protein yield. The bias of the prediction accuracy using populations from individual cycles using fivefold cross-validation was accordingly substantial for protein yield (17-712 %) and less pronounced for protein content (8-86 %). Cross-validation using the cycles as folds aimed to avoid this bias and reached a maximum prediction accuracy of [Formula: see text] = 0.51 for protein content, [Formula: see text] = 0.38 for grain yield and [Formula: see text] = 0.16 for protein yield. Dropping outlier cycles increased the prediction accuracy of grain yield to [Formula: see text] = 0.41 as estimated by cross-validation, while dropping outlier environments did not have a significant effect on the prediction accuracy. Independent validation suggests, on the other hand, that careful consideration is necessary before an outlier correction is undertaken, which removes lines from the training population. Predicting protein yield by multiplying genomic estimated breeding values of grain yield and protein content raised the prediction accuracy to [Formula: see text] = 0.19 for this derived trait.

Project description:BACKGROUND: In breeding programs for layers, selection of hens and cocks is based on recording phenotypic data from hens in different housing systems. Genomic information can provide additional information for selection and/or allow for a strong reduction in the generation interval. In this study, a typical conventional layer breeding program using a four-line cross was modeled and the expected genetic progress was derived deterministically with the software ZPLAN+. This non-genomic reference scenario was compared to two genomic breeding programs to determine the best strategy for implementing genomic information in layer breeding programs. RESULTS: In scenario I, genomic information was used in addition to all other information available in the conventional breeding program, so the generation interval was the same as in the reference scenario, i.e. 14.5 months. Here, we assumed that either only young cocks or young cocks and hens were genotyped as selection candidates. In scenario II, we assumed that breeders of both sexes were used at the biologically earliest possible age, so that at the time of selection only performance data of the parent generation and genomic information of the selection candidates were available. In this case, the generation interval was reduced to eight months. In both scenarios, the number of genotyped male selection candidates was varied between 800 and 4800 males and two sizes of the calibration set (500 or 2000 animals) were considered. All genomic scenarios increased the expected genetic gain and the economic profit of the breeding program. In scenario II, the increase was much more pronounced and even in the most conservative implementation led to a 60% improvement in genetic gain and economic profit. This increase was in all cases associated with higher breeding costs. CONCLUSIONS: While genomic selection is shown to have the potential to improve genetic gain in layer breeding programs, its implementation remains a business decision of the breeding company; the possible extra profit for the breeding company depends on whether the customers of breeding stock are willing to pay more for improved genetic quality.

Dataset Information

Evaluation of the 2b-RAD method for genomic selection in scallop breeding.

Publications

Evaluation of the 2b-RAD method for genomic selection in scallop breeding.

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