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全基因组关联分析鉴定出控制玉米中汞积累的基因座。

Genome-wide association analysis identifies loci governing mercury accumulation in maize.

机构信息

Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, Zhengzhou, 450002, China.

Maize Research Institute, Chongqing Academy of Agricultural Sciences, Chongqing, 401329, China.

出版信息

Sci Rep. 2017 Mar 21;7(1):247. doi: 10.1038/s41598-017-00189-6.

Abstract

Owing to the rapid development of urbanisation and industrialisation, heavy metal pollution has become a widespread environmental problem. Maize planted on mercury (Hg)-polluted soil can absorb and accumulate Hg in its edible parts, posing a potential threat to human health. To understand the genetic mechanism of Hg accumulation in maize, we performed a genome-wide association study using a mixed linear model on an association population consisting of 230 maize inbred lines with abundant genetic variation. The order of relative Hg concentrations in different maize tissues was as follows: leaves > bracts > stems > axes > kernels. Combined two locations, a total of 37 significant single-nucleotide polymorphisms (SNPs) associated with kernels, 12 with axes, 13 with stems, 27 with bracts and 23 with leaves were detected with p < 0.0001. Each significant SNP was calculated and the SNPs significant associated with kernels, axes, stems, bracts and leaves explained 6.96%-10.56%, 7.19%-15.87%, 7.11%-10.19%, 7.16%-8.71% and 6.91%-9.17% of the phenotypic variation, respectively. Among the significant SNPs, nine co-localised with previously detected quantitative trait loci. This study will aid in the selection of Hg-accumulation inbred lines that satisfy the needs for pollution-safe cultivars and maintaining maize production.

摘要

由于城市化和工业化的快速发展,重金属污染已成为一个广泛存在的环境问题。种植在汞(Hg)污染土壤上的玉米可以吸收和积累其可食用部分的汞,对人类健康构成潜在威胁。为了了解玉米中汞积累的遗传机制,我们使用混合线性模型在一个包含 230 个具有丰富遗传变异的玉米自交系的关联群体上进行了全基因组关联研究。不同玉米组织中相对汞浓度的顺序如下:叶片>苞叶>茎>轴>穗。在两个地点的综合分析中,共检测到与穗粒相关的 37 个显著单核苷酸多态性(SNP),与轴相关的 12 个,与茎相关的 13 个,与苞叶相关的 27 个,与叶片相关的 23 个,p 值均小于 0.0001。对每个显著 SNP 进行计算,与穗粒、轴、茎、苞叶和叶片显著相关的 SNP 分别解释了表型变异的 6.96%-10.56%、7.19%-15.87%、7.11%-10.19%、7.16%-8.71%和 6.91%-9.17%。在显著 SNP 中,有 9 个与先前检测到的数量性状位点共定位。这项研究将有助于选择满足污染安全品种需求和维持玉米生产的汞积累自交系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3985/5427852/d2b8eff5137a/41598_2017_189_Fig1_HTML.jpg

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