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Potential of Association Mapping and Genomic Selection to Explore PI 88788 Derived Soybean Cyst Nematode Resistance

机译:关联映射和基因组选择的潜力,以探索PI 88788衍生的大豆囊肿线虫抗性

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The potential of association mapping (AM) and genomic selection (GS) has not yet been explored for investigating resistance to soybean cyst nematode (SCN), the most destructive pest affecting soybean. We genotyped 282 representative accessions from the University of Minnesota soybean breeding program using a genome-wide panel of 1536 single nucleotide polymorphism (SNP) markers and evaluated plant responses to SCN HG type 0. After adjusting for population structure, AM detected significant signals at two loci corresponding to rhg1 and FGAM1 plus a third locus located at the opposite end of chromosome 18. Our analysis also identified a discontinuous long-range haplotype of over 600 kb around rhg1 locus associated with resistance to SCN HG type 0. The same phenotypic and genotypic datasets were then used to access GS accuracy for prediction of SCN resistance in the presence of major genes through a sixfold cross-validation study. Genomic selection using the full marker set produced average prediction accuracy ranging from 0.59 to 0.67 for SCN resistance, significantly more accurate than marker-assisted selection (MAS) strategies using two rhg1-associated DNA makers. Reducing the number of markers to 288 SNPs in the GS training population had little effect on genomic prediction accuracy. This study demonstrates that AM can be an effective genomic tool for identifying genes of interest in diverse germplasm. The results also indicate that improved MAS and GS can enhance breeding efficiency for SCN resistance in existing soybean improvement programs.
机译:尚未研究出关联作图(AM)和基因组选择(GS)的潜力来研究对大豆囊肿线虫(SCN)的抗性,大豆胞囊线虫是最具破坏力的大豆害虫。我们使用1536个单核苷酸多态性(SNP)标记的全基因组面板对明尼苏达大学大豆育种计划的282个代表性种进行了基因分型,并评估了植物对SCN HG 0型的反应。调整种群结构后,AM检测到两个显着信号对应于rhg1和FGAM1的基因座,加上位于18号染色体相对末端的第三个基因座。我们的分析还确定了rhg1基因座周围600 kb以上的不连续远程单倍型,与对SCN HG 0型的抗性相关。相同的表型和基因型然后,通过六重交叉验证研究,使用数据集访问GS准确性以预测存在主要基因时的SCN抗性。使用完整标记集的基因组选择产生的SCN抗性平均预测准确度范围从0.59到0.67,比使用两个rhg1相关DNA标记物的标记辅助选择(MAS)策略准确得多。将GS训练人群中的标记数量减少到288个SNP对基因组预测准确性的影响很小。这项研究表明AM可以是一种有效的基因组工具,可用于识别各种种质中的目标基因。结果还表明,在现有的大豆改良计划中,改良的MAS和GS可以提高抗SCN的育种效率。

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