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玉米的抽穗期、穗长和穗粒数的 QTL 定位

Teosinte-Derived Advanced Backcross Population Harbors Genomic Regions for Grain Yield Attributing Traits in Maize.

机构信息

ICAR-Indian Institute of Maize Research, Ludhiana 141004, India.

ICAR-Indian Agricultural Research Institute Regional Station, Karnal 132001, India.

出版信息

Int J Mol Sci. 2024 Sep 25;25(19):10300. doi: 10.3390/ijms251910300.

DOI:10.3390/ijms251910300
PMID:39408630
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11476406/
Abstract

Maize is a highly versatile crop holding significant importance in global food, feed and nutritional security. Grain yield is a complex trait and difficult to improve without targeting the improvement of grain yield attributing traits, which are relatively less complex in nature. Hence, considering the erosion in genetic diversity, there is an urgent need to use wild relatives for genetic diversification and unravel the genomic regions for grain yield attributing traits in maize. Thus, the current study aimed to identify quantitative trait loci (QTLs) linked with grain yield and yield attributing traits. Two BCF populations developed from the cross of LM13 with (population 1) and LM14 with (population 2) were genotyped and phenotyped in field conditions in the kharif season. BCF lines in both populations were phenotyped again for grain yield and attributing traits in the spring season. In total, three QTLs each for ear height (EH), two QTLs for flag leaf length (FLL) and one QTL each for ear diameter (ED), plant height, flag leaf length (FLL), flag leaf width and 100 kernel-weight were identified in population 1. In population 2, two QTLs for kernel row per ear (KRPE) and one QTL for FLL were detected in. QTLs for EH, FLL and KPRE showed consistency across seasons. Among the identified QTLs, six QTLs were found to be co-localized near identified genomic regions in previous studies, validating their potential in contributing to trait expression. The identified QTLs can be utilized for marker assisted selection, transferring favorable alleles from wild relatives in modern maize.

摘要

玉米是一种用途广泛的作物,在全球粮食、饲料和营养安全方面具有重要意义。籽粒产量是一个复杂的性状,如果不针对提高与产量相关的性状进行改良,就很难提高产量,而这些性状在本质上相对不太复杂。因此,考虑到遗传多样性的侵蚀,迫切需要利用野生近缘种进行遗传多样化,并阐明玉米产量相关性状的基因组区域。因此,本研究旨在鉴定与籽粒产量和产量相关性状相关的数量性状位点(QTL)。从 LM13 与 (群体 1)和 LM14 与 (群体 2)杂交产生的两个 BCF 群体在雨季的田间条件下进行了基因型和表型分析。在春季,两个群体中的 BCF 系再次对籽粒产量和相关性状进行了表型分析。总共在群体 1 中鉴定到了 3 个与穗高(EH)相关的 QTL、2 个与旗叶长度(FLL)相关的 QTL 和 1 个与穗径(ED)、株高、旗叶长度(FLL)、旗叶宽度和 100 粒重相关的 QTL。在群体 2 中,鉴定到了 2 个与每穗粒行数(KRPE)相关的 QTL 和 1 个与 FLL 相关的 QTL。EH、FLL 和 KPRE 的 QTL 在不同季节具有一致性。在所鉴定的 QTL 中,有 6 个 QTL 被发现在先前研究中鉴定到的基因组区域附近存在共定位,这验证了它们在促进性状表达方面的潜力。所鉴定的 QTL 可用于标记辅助选择,将有利的等位基因从野生近缘种转移到现代玉米中。

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本文引用的文献

1
Identification of Candidate QTLs and Genes for Ear Diameter by Multi-Parent Population in Maize.利用玉米多亲本群体鉴定穗粗的候选 QTL 和基因。
Genes (Basel). 2023 Jun 20;14(6):1305. doi: 10.3390/genes14061305.
2
Maize plant architecture trait QTL mapping and candidate gene identification based on multiple environments and double populations.基于多环境和双群体的玉米植株结构性状 QTL 定位和候选基因鉴定。
BMC Plant Biol. 2022 Mar 11;22(1):110. doi: 10.1186/s12870-022-03470-7.
3
Mapping of QTL for agronomic traits using high-density SNPs with an RIL population in maize.
利用玉米 RIL 群体高密度 SNP 进行农艺性状 QTL 定位。
Genes Genomics. 2021 Dec;43(12):1403-1411. doi: 10.1007/s13258-021-01169-x. Epub 2021 Sep 30.
4
Dominance Effects and Functional Enrichments Improve Prediction of Agronomic Traits in Hybrid Maize.杂种玉米农艺性状预测的优势效应和功能富集改善
Genetics. 2020 May;215(1):215-230. doi: 10.1534/genetics.120.303025. Epub 2020 Mar 9.
5
Mapping quantitative trait loci for yield-related traits and predicting candidate genes for grain weight in maize.定位与产量相关性状的数量性状位点,并预测玉米粒重的候选基因。
Sci Rep. 2019 Nov 6;9(1):16112. doi: 10.1038/s41598-019-52222-5.
6
Construction of genetic linkage map and identification of QTLs related to agronomic traits in DH population of maize (Zea mays L.) using SSR markers.利用 SSR 标记构建玉米(Zea mays L.)DH 群体的遗传连锁图谱和鉴定与农艺性状相关的 QTL。
Genes Genomics. 2019 Jun;41(6):667-678. doi: 10.1007/s13258-019-00813-x. Epub 2019 Apr 5.
7
Genetic mapping of QTL for maize leaf width combining RIL and IF2 populations.利用重组自交系群体和加倍单倍体群体对玉米叶宽进行QTL基因定位
PLoS One. 2017 Dec 12;12(12):e0189441. doi: 10.1371/journal.pone.0189441. eCollection 2017.
8
High Density Linkage Map Construction and Mapping of Yield Trait QTLs in Maize () Using the Genotyping-by-Sequencing (GBS) Technology.利用简化基因组测序(GBS)技术构建玉米高密度连锁图谱及产量性状QTL定位
Front Plant Sci. 2017 May 8;8:706. doi: 10.3389/fpls.2017.00706. eCollection 2017.
9
QTL analysis and dissection of panicle components in rice using advanced backcross populations derived from Oryza Sativa cultivars HR1128 and 'Nipponbare'.利用源自水稻品种 HR1128 和 'Nipponbare' 的高级回交群体进行水稻穗部成分的 QTL 分析和剖析。
PLoS One. 2017 Apr 19;12(4):e0175692. doi: 10.1371/journal.pone.0175692. eCollection 2017.
10
Combined Linkage and Association Mapping Reveals QTL and Candidate Genes for Plant and Ear Height in Maize.联合连锁与关联作图揭示玉米株高和穗位高的QTL及候选基因
Front Plant Sci. 2016 Jun 15;7:833. doi: 10.3389/fpls.2016.00833. eCollection 2016.