《Table 2–Evaluation of the effects of genetic relationship on prediction accuracy.》
本系列图表出处文件名:随高清版一同展现
《Factors affecting genomic selection revealed by empirical evidence in maize》
aTraining-breeding population set:training population is given at the left of the hyphen“-”,the breeding population is included at the right.The natural population(NAT)was used as the training population to estimate GEBVs for the RIL&DH population.RIL
The estimates of rMGcontinuously increased as marker density and population size increased until they reached plateaux.For example,in the natural population,only a non-significant increase was obtained on rMGfor yield-related traits,when the number of SNPs increased from 7000 to 30,000,and the rMG estimate based on 37,803 markers was similar to that from 7000high-quality markers selected randomly(Fig.1a,c).However,only a slight gain in rMGwas obtained when the number of markers increased from 1000 to 8000 in the RIL&DH population,showing that 1000 markers were enough to achieve a reasonable accuracy in biparental populations(Fig.1b,d).As the population size increased,rMGincreased,and a slight gain in rMGwas obtained when the population size reached 250(Fig.2).Generally,targeted traits with high h2showed high prediction accuracies.The correlation coefficients between rMGand heritability among traits were 0.83(P=0.04),0.89(P=0.02)and 0.95(P<0.01)in natural,RIL&DH and F2:3populations,respectively(Table 1).Further improvement on prediction accuracy could be achieved with increased h2.
图表编号 | XD0012325900 严禁用于非法目的 |
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绘制时间 | 2018.08.01 |
作者 | Xiaogang Liu、Hongwu Wang、Hui Wang、Zifeng Guo、Xiaojie Xu、Jiacheng Liu、Shanhong Wang、Wen-Xue Li、Cheng Zou、Boddupalli M.Prasanna、Michael S.Olsen、Changling Huang、Yunbi Xu |
绘制单位 | Institute of Crop Science, National Key Facility of Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences、Institute of Crop Science, National Key Facility of Crop Gene Resources and Genetic Improvement, Chinese Academy of A |
更多格式 | 高清、无水印(增值服务) |
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