Genomic 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 ...Genomic 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 fi rst 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 specifi c length amplifi ed fragment sequencing(SLAF-seq)and phenotyped for body length and body weight.Three GS models(RR-BLUP,Bayes A,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 dif ferent 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 coeffi cients 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.展开更多
This study analyzed the impact of participatory plant breeding （PPB） and participatory variety selection （PVS） on the adoption of improved sweetpotato varieties （ISPV） in central Uganda. The study quantitatively...This study analyzed the impact of participatory plant breeding （PPB） and participatory variety selection （PVS） on the adoption of improved sweetpotato varieties （ISPV） in central Uganda. The study quantitatively assessed how the two approaches influence farmers＇ uptake of the improved sweetpotato varieties and also determined other factors influencing this adoption. This was done by estimating a robust standard errors logit model. Both PPB and PVS positively and significantly influenced the likelihood of adoption of improved sweetpotato varieties at 5% and 10% levels, respectively. Other variables that positively influenced the adoption are extension services, training in sweetpotato production, farming experience, and off-farm income of the household. Farmers who participated in the plant breeding and variety selection processes were 37 and 6.7 times more likely to adopt the improved sweetpotato varieties than those who had not, respectively. Farmers who were trained specifically in sweetpotato production were 8.8 times more likely to adopt the improved varieties than those who had not received this type of training.展开更多
基金Supported by the National High Technology Research and Development Program of China(863 Program)(No.2012AA10A404)the National Natural Science Foundation of China(No.31502161)Financially Supported by Qingdao National Laboratory for Marine Science and Technology(No.2015ASKJ02)
文摘Genomic 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 fi rst 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 specifi c length amplifi ed fragment sequencing(SLAF-seq)and phenotyped for body length and body weight.Three GS models(RR-BLUP,Bayes A,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 dif ferent 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 coeffi cients 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.
文摘This study analyzed the impact of participatory plant breeding （PPB） and participatory variety selection （PVS） on the adoption of improved sweetpotato varieties （ISPV） in central Uganda. The study quantitatively assessed how the two approaches influence farmers＇ uptake of the improved sweetpotato varieties and also determined other factors influencing this adoption. This was done by estimating a robust standard errors logit model. Both PPB and PVS positively and significantly influenced the likelihood of adoption of improved sweetpotato varieties at 5% and 10% levels, respectively. Other variables that positively influenced the adoption are extension services, training in sweetpotato production, farming experience, and off-farm income of the household. Farmers who participated in the plant breeding and variety selection processes were 37 and 6.7 times more likely to adopt the improved sweetpotato varieties than those who had not, respectively. Farmers who were trained specifically in sweetpotato production were 8.8 times more likely to adopt the improved varieties than those who had not received this type of training.
