小麦品质性状QTL元分析及候选基因挖掘OACSTPCD
Meta-analysis of QTL and Mining of Candidate Genes for Quality Traits in Wheat(Triticum aestivum)
小麦(Triticum aestivum)品质性状是多基因控制的复杂数量性状,深入挖掘重要基因组区域和候选基因对小麦品质分子遗传改良具有重要意义.本研究从31个独立数量性状位点(quantitative traits locus,QTL)定位研究中,对293个控制小麦品质性状的初始QTL进行了图谱整合和QTL元分析,获得40个一致性QTL(meta quantitative trait loci,MQTL)位点,其中35个MQTL与籽粒硬度(grain hardness,GH)相关,23个MQTL与沉降值(sedimentation value,SV)相关,16个MQTL与淀粉含量(starch content,SC)相关.这些MQTL平均置信区间(confidence interval,CI)为3.87 cM,比初始QTL(14.80 cM)缩小3.82倍,特别是5个核心MQTL平均CI缩小至0.80 cM.通过同源比对和植物基因组数据库序列信息,在40个MQTL区间内共获得839个候选基因.借助转录组数据,筛选出113个在籽粒胚乳和糊粉层中高表达候选基因.本研究所获得的小麦品质性状重要基因组区域和候选基因将为小麦品质性状的分子遗传改良提供理论依据.
Wheat(Triticum aestivum)quality trait is a complex quantitative trait controlled by multiple genes.It is of great significance to explore the important genomic regions and candidate genes of wheat quality for molecular genetic improvement.In this study,the mapping integration and meta-analysis were conducted of 293 initial QTLs for quality traits from 31 QTL mapping studies in wheat,and 40 meta quantitative trait loci(MQTLs)were predicted which included 35 MQTLs for grain hardness(GH),23 MQTLs for sedimentation value(SV)and 16 MQTLs for starch content(SC).The average confidence interval of these MQTLs was 3.87 cM,which was 3.82 times smaller than the average confidence interval of the initial QTL(14.80 cM),The average confidence interval of the 5 core MQTLs was reduced to 0.80 cM.A total of 839 candidate genes were obtained from the 40 MQTLs intervals by homology alignment and Ensembl Plants sequence information.Based on transcriptome date,113 candidate genes with high expression in grain endosperm and aleurone layer were screened.The important genomic regions and candidate genes obtained in this study will provide a theoretical basis for the molecular genetic improvement of quality traits in wheat.
李娜;王鹏;孔斌雪;马靖福;窦佳欣;陈涛;张沛沛;刘媛;杨德龙
甘肃农业大学生命科学技术学院,兰州 730070干旱生境作物学国家重点实验室,兰州 730070甘肃农业大学生命科学技术学院,兰州 730070||干旱生境作物学国家重点实验室,兰州 730070
农业科学
小麦品质性状元分析候选基因
WheatQuality traitsMeta-analysisCandidate genes
《农业生物技术学报》 2024 (001)
11-25 / 15
甘肃省农业重点研发计划(21YF5NA089);中央引导地方科技发展资金(23ZYQA0322);甘肃省高等学校产业支撑计划(2022CYZC-44);甘肃省自然科学基金(21JR7RA828);甘肃省高等学校创新基金(2021B-125)
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