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小麦千粒重的Meta-QTL定位

Meta-QTL mapping for wheat thousand kernel weight.

作者信息

Tan Chao, Guo Xiaojiang, Dong Huixue, Li Maolian, Chen Qian, Cheng Mengping, Pu Zhien, Yuan Zhongwei, Wang Jirui

机构信息

State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China.

出版信息

Front Plant Sci. 2024 Dec 16;15:1499055. doi: 10.3389/fpls.2024.1499055. eCollection 2024.

DOI:10.3389/fpls.2024.1499055
PMID:39737382
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11682887/
Abstract

Wheat domestication and subsequent genetic improvement have yielded cultivated species with larger seeds compared to wild ancestors. Increasing thousand kernel weight (TKW) remains a crucial goal in many wheat breeding programs. To identify genomic regions influencing TKW across diverse genetic populations, we performed a comprehensive meta-analysis of quantitative trait loci (MQTL), integrating 993 initial QTL from 120 independent mapping studies over recent decades. We refined 242 loci into 66 MQTL, with an average confidence interval (CI) 3.06 times smaller than that of the original QTL. In these 66 MQTL regions, a total of 4,913 candidate genes related to TKW were identified, involved in ubiquitination, phytohormones, G-proteins, photosynthesis, and microRNAs. Expression analysis of the candidate genes showed that 95 were specific to grain and might potentially affect TKW at different seed development stages. These findings enhance our understanding of the genetic factors associated with TKW in wheat, providing reliable MQTL and potential candidate genes for genetic improvement of this trait.

摘要

与野生祖先相比，小麦驯化及随后的遗传改良产生了种子更大的栽培品种。提高千粒重（TKW）仍然是许多小麦育种计划的关键目标。为了在不同遗传群体中鉴定影响TKW的基因组区域，我们对数量性状位点（MQTL）进行了全面的荟萃分析，整合了近几十年来来自120项独立定位研究的993个初始QTL。我们将242个位点精炼为66个MQTL，平均置信区间（CI）比原始QTL小3.06倍。在这66个MQTL区域中，共鉴定出4913个与TKW相关的候选基因，涉及泛素化、植物激素、G蛋白、光合作用和微小RNA。候选基因的表达分析表明，其中95个基因在籽粒中具有特异性，可能在种子发育的不同阶段影响TKW。这些发现增强了我们对小麦中与TKW相关的遗传因素的理解，为该性状的遗传改良提供了可靠的MQTL和潜在的候选基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/2bfc6553d3ef/fpls-15-1499055-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/838367da17ae/fpls-15-1499055-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/e455ea3bb159/fpls-15-1499055-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/70db32938487/fpls-15-1499055-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/3d0eb76a0eb9/fpls-15-1499055-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/c57cb39b5cf9/fpls-15-1499055-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/2bfc6553d3ef/fpls-15-1499055-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/838367da17ae/fpls-15-1499055-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/e455ea3bb159/fpls-15-1499055-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/70db32938487/fpls-15-1499055-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/3d0eb76a0eb9/fpls-15-1499055-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/c57cb39b5cf9/fpls-15-1499055-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11682887/2bfc6553d3ef/fpls-15-1499055-g006.jpg

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本文引用的文献

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Nat Plants. 2023 Jun;9(6):965-977. doi: 10.1038/s41477-023-01432-x. Epub 2023 Jun 5.
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Identification of quantitative trait loci (QTL) and meta-QTL analysis for kernel size-related traits in wheat (Triticum aestivum L.).鉴定小麦（Triticum aestivum L.）粒形相关性状的数量性状位点（QTL）和元数量性状位点（Meta-QTL）分析。
BMC Plant Biol. 2022 Dec 23;22(1):607. doi: 10.1186/s12870-022-03989-9.
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Consensus genomic regions associated with grain protein content in hexaploid and tetraploid wheat.
六倍体和四倍体小麦中与籽粒蛋白质含量相关的共有基因组区域。
Front Genet. 2022 Sep 28;13:1021180. doi: 10.3389/fgene.2022.1021180. eCollection 2022.
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Unravelling consensus genomic regions associated with quality traits in wheat using meta-analysis of quantitative trait loci.利用数量性状位点的荟萃分析揭示与小麦品质性状相关的共识基因组区域。
Planta. 2022 May 5;255(6):115. doi: 10.1007/s00425-022-03904-4.
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Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis.通过QTL连锁图谱和荟萃分析揭示的小麦粒重主要基因组区域
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