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全基因组关联研究和基因组预测热带玉米(Zea mays L.)秸秆品质性状。

Genome wide association study and genomic prediction for stover quality traits in tropical maize (Zea mays L.).

机构信息

Centro Internacional de Mejoramiento de Maíz y Trigo (CIMMYT), c/o ICRISAT, Patancheru, 502324, India.

Corteva Agrisciences, Multi Crop Research Centre, Hyderabad, India.

出版信息

Sci Rep. 2021 Jan 12;11(1):686. doi: 10.1038/s41598-020-80118-2.

Abstract

Maize is rapidly replacing traditionally cultivated dual purpose crops of South Asia, primarily due to the better economic remuneration. This has created an impetus for improving maize for both grain productivity and stover traits. Molecular techniques can largely assist breeders in determining approaches for effectively integrating stover trait improvement in their existing breeding pipeline. In the current study we identified a suite of potential genomic regions associated to the two major stover quality traits-in-vitro organic matter digestibility (IVOMD) and metabolizable energy (ME) through genome wide association study. However, considering the fact that the loci identified for these complex traits all had smaller effects and accounted only a small portion of phenotypic variation, the effectiveness of following a genomic selection approach for these traits was evaluated. The testing set consists of breeding lines recently developed within the program and the training set consists of a panel of lines from the working germplasm comprising the founder lines of the newly developed breeding lines and also an unrelated diversity set. The prediction accuracy as determined by the Pearson's correlation coefficient between observed and predicted values of these breeding lines were high even at lower marker density (200 random SNPs), when the training and testing set were related. However, the accuracies were dismal, when there was no relationship between the training and the testing set.

摘要

玉米正在迅速取代南亚传统的兼用作物,主要是因为其经济效益更好。这就促使人们既要提高玉米的粮食产量,又要改善其秸秆特性。分子技术在很大程度上可以帮助育种家确定在现有育种途径中有效整合秸秆特性改良的方法。在本研究中,我们通过全基因组关联研究,鉴定了与两个主要秸秆品质特性(体外有机物消化率(IVOMD)和可代谢能(ME))相关的一套潜在的基因组区域。然而,考虑到这些复杂特性的位点都只有较小的效应,并且只占表型变异的一小部分,因此,评估了对这些特性采用基因组选择方法的效果。测试集由该计划中最近开发的育种系组成,而训练集则由工作种质资源组成,包括新开发的育种系的原始系,以及一个无关的多样性系。当训练集和测试集相关时,通过观察值和预测值之间的皮尔逊相关系数来确定的预测准确性很高,即使在较低的标记密度(200 个随机 SNP)下也是如此。然而,当训练集和测试集之间没有关系时,准确性就很差。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fe7/7804097/f01c298a98f2/41598_2020_80118_Fig1_HTML.jpg

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