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通过 MetaQTL 分析定义基因组景观,以鉴定与主要水稻病害相关的潜在候选抗性基因。

Defining genomic landscape for identification of potential candidate resistance genes associated with major rice diseases through MetaQTL analysis.

机构信息

College of Agriculture, Punjab Agricultural University, Ludhiana 141004, India.

出版信息

J Biosci. 2024;49.

Abstract

Rice production is severely affected by various diseases such as bacterial leaf blight (BLB), brown spot (BS), false smut (FS), foot rot (FR), rice blast (RB), and sheath blight (SB). In recent years, several quantitative trait loci (QTLs) studies involving different populations have been carried out, resulting in the identification of hundreds of resistance QTLs for each disease. These QTLs can be integrated and analyzed using meta-QTL (MQTL) analysis for better understanding of the genetic architecture underlying multiple disease resistance (MDR). This study involved an MQTL analysis on 661 QTLs (378, 161, 21, 41, 44, and 16 QTLs for SB, RB, BLB, BS, FS, and FR, respectively) retrieved from 50 individual studies published from 1995 to 2021. Of these, 503 QTLs were projected finally onto the consensus map saturated with 6,275 markers, resulting in 73 MQTLs, including 27 MDR-MQTLs conferring resistance to three or more diseases. Forty-seven MQTLs were validated using marker-trait associations identified in published genome-wide association studies. A total of 3,310 genes, including both R and defense genes, were also identified within some selected high-confidence MQTL regions that were investigated further for the syntenic relationship with barley, wheat, and maize genomes. Thirty-nine high-confidence candidate genes were selected based on their expression patterns and recommended for future studies involving functional validation, genetic engineering, and gene editing. Nineteen MQTLs were co-localized with 39 known R genes for BLB and RB diseases. These results could pave the way to utilize candidate genes in a marker-assisted breeding program for MDR in rice.

摘要

水稻生产受到各种病害的严重影响,如细菌性条斑病(BLB)、褐条病(BS)、假黑粉病(FS)、脚腐病(FR)、稻瘟病(RB)和纹枯病(SB)。近年来,针对不同群体进行了多项数量性状位点(QTL)研究,确定了数百个针对每种病害的抗性 QTL。可以使用元数量性状位点(MQTL)分析来整合和分析这些 QTL,以更好地理解多种病害抗性(MDR)的遗传结构。本研究对从 1995 年至 2021 年发表的 50 项独立研究中检索到的 661 个 QTL(SB、RB、BLB、BS、FS 和 FR 分别为 378、161、21、41、44 和 16 个 QTL)进行了 MQTL 分析。其中,最终有 503 个 QTL 被投射到 6275 个标记饱和的共识图谱上,产生了 73 个 MQTL,包括 27 个 MDR-MQTL,可抵抗三种或更多种病害。利用在已发表的全基因组关联研究中确定的标记-性状关联,验证了 47 个 MQTL。在一些选定的高置信度 MQTL 区域内,还鉴定了包括 R 基因和防御基因在内的共 3310 个基因,这些区域进一步调查了与大麦、小麦和玉米基因组的同源关系。根据表达模式选择了 39 个高置信度候选基因,并建议进一步进行功能验证、遗传工程和基因编辑等研究。19 个 MQTL 与 BLB 和 RB 疾病的 39 个已知 R 基因共定位。这些结果为利用候选基因在水稻 MDR 的标记辅助育种计划中铺平了道路。

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