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与小麦多种非生物胁迫耐受性相关的共识基因组区域及其在小麦育种中的意义。

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding.

机构信息

Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India.

Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99163, USA.

出版信息

Sci Rep. 2022 Aug 11;12(1):13680. doi: 10.1038/s41598-022-18149-0.

DOI:10.1038/s41598-022-18149-0
PMID:35953529
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9372038/
Abstract

In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.

摘要

在小麦中,使用先前与干旱胁迫(DS)、热胁迫(HS)、盐胁迫(SS)、水涝胁迫(WS)、收获前发芽(PHS)和铝胁迫(AS)相关的已鉴定 QTL 进行了荟萃分析,共预测了 134 个元 QTL(MQTL),这些 QTL 涉及至少 28 个一致且稳定的 MQTL,赋予对研究中的五种或所有六种非生物胁迫的耐受性。在 132 个物理锚定的 MQTL 中,有 76 个也通过全基因组关联研究得到了验证。大约 43%的 MQTL 具有小于 1cM 和 5Mb 的遗传和物理置信区间。因此,在一些选定的 MQTL 中鉴定出 539 个基因,这些基因赋予对 5 种或所有 6 种非生物胁迫的耐受性。对 MQTL 下的基因与四个基于 RNA-seq 的转录组数据集的比较分析揭示了总共 189 个差异表达基因,其中至少包括 11 个在不同数据集中常见的最有希望的候选基因。启动子分析表明,这些基因的启动子包含许多应激反应顺式调控元件,如 ARE、MBS、TC-rich 重复、As-1 元件、STRE、LTR、WRE3 和 WUN-motif 等。此外,一些 MQTL 还与多达 34 个已知的非生物胁迫耐受性基因重叠。此外,在小麦、玉米和水稻基因组中还发现了许多同源 MQTL。这些发现有助于对多个非生物胁迫耐受性进行精细图谱绘制和基因克隆,以及标记辅助育种。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac2d/9372038/efbea4418fe7/41598_2022_18149_Fig7_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac2d/9372038/270cfbe05cb0/41598_2022_18149_Fig5_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac2d/9372038/efbea4418fe7/41598_2022_18149_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac2d/9372038/88097d02ede6/41598_2022_18149_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac2d/9372038/ee19b0566fa8/41598_2022_18149_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac2d/9372038/d882c6e456eb/41598_2022_18149_Fig3_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac2d/9372038/270cfbe05cb0/41598_2022_18149_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac2d/9372038/c4a9de59f057/41598_2022_18149_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac2d/9372038/efbea4418fe7/41598_2022_18149_Fig7_HTML.jpg

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