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| Meta-analysis of QTL and Mining of Candidate Genes for Quality Traits in Wheat (Triticum aestivum) |
| LI Na1, WANG Peng1, KONG Bin-Xue1, MA Jing-Fu1, DOU Jia-Xin1, CHEN Tao1, ZHANG Pei-Pei2, LIU Yuan1, YANG De-Long1,2,* |
1 College of Life Science and Technology, Gansu Agricultural University, Lanzhou 730070, China;
2 State Key Laboratory of Aridland Crop Science, Lanzhou 730070, China |
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Abstract 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.
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Received: 30 November 2022
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Corresponding Authors:
* yangdl@gsau.edu.cn
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