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利用全基因组关联研究解析玉米(Zea mays L.)微量元素性状。

Genetic dissection of maize (Zea maysL.) trace element traits using genome-wide association studies.

机构信息

Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China.

Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China.

出版信息

BMC Plant Biol. 2023 Dec 8;23(1):631. doi: 10.1186/s12870-023-04643-8.

Abstract

Maize (Zea mays L.) is an important food and feed crop worldwide and serves as a a vital source of biological trace elements, which are important breeding targets. In this study, 170 maize materials were used to detect QTNs related to the content of Mn, Fe and Mo in maize grains through two GWAS models, namely MLM_Q + K and MLM_PCA + K. The results identified 87 (Mn), 205 (Fe), and 310 (Mo) QTNs using both methods in the three environments. Considering comprehensive factors such as co-location across multiple environments, strict significance threshold, and phenotypic value in multiple environments, 8 QTNs related to Mn, 10 QTNs related to Fe, and 26 QTNs related to Mo were used to identify 44 superior alleles. Consequently, three cross combinations with higher Mn element, two combinations with higher Fe element, six combinations with higher Mo element, and two combinations with multiple element (Mn/Fe/Mo) were predicted to yield offspring with higher numbers of superior alleles, thereby increasing the likelihood of enriching the corresponding elements. Additionally, the candidate genes identified 100 kb downstream and upstream the QTNs featured function and pathways related to maize elemental transport and accumulation. These results are expected to facilitate the screening and development of high-quality maize varieties enriched with trace elements, establish an important theoretical foundation for molecular marker assisted breeding and contribute to a better understanding of the regulatory network governing trace elements in maize.

摘要

玉米(Zea mays L.)是世界范围内重要的粮食和饲料作物,也是生物微量元素的重要来源,这些微量元素是重要的育种目标。本研究利用两种 GWAS 模型,即 MLM_Q + K 和 MLM_PCA + K,对 170 份玉米材料进行分析,以检测与玉米籽粒中 Mn、Fe 和 Mo 含量相关的 QTNs。在三种环境下,两种方法共鉴定到 87 个(Mn)、205 个(Fe)和 310 个(Mo)QTNs。综合考虑多个环境下的共定位、严格的显著性阈值以及多个环境下的表型值等综合因素,共鉴定到与 Mn 相关的 8 个 QTNs、与 Fe 相关的 10 个 QTNs和与 Mo 相关的 26 个 QTNs,这些 QTNs对应的 44 个有利等位基因被用来鉴定。因此,预测到三个 Mn 元素含量较高的杂交组合、两个 Fe 元素含量较高的杂交组合、六个 Mo 元素含量较高的杂交组合和两个 Mn/Fe/Mo 多元素含量较高的杂交组合,这些组合的后代可能具有更多的有利等位基因,从而增加了相应元素的富集可能性。此外,还在 QTN 上下游 100kb 范围内鉴定到候选基因,这些基因与玉米元素转运和积累的功能和途径有关。这些结果有望促进高微量元素玉米品种的筛选和开发,为分子标记辅助育种奠定重要的理论基础,并有助于深入了解玉米中微量元素的调控网络。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edfa/10704835/17080fe33b0f/12870_2023_4643_Fig1_HTML.jpg

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