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三个优异陆地棉(Gossypium hirsutum)品种:ZR014121、CCRI60 和 EZ60 的 lint percentage 和 boll weight QTL 分析。

Lint percentage and boll weight QTLs in three excellent upland cotton (Gossypium hirsutum): ZR014121, CCRI60, and EZ60.

机构信息

State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Institute of Cotton Research, The Ministry of Agriculture, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China.

Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, Henan, China.

出版信息

BMC Plant Biol. 2023 Apr 5;23(1):179. doi: 10.1186/s12870-023-04147-5.

DOI:10.1186/s12870-023-04147-5
PMID:37020180
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10074700/
Abstract

BACKGROUND

Upland cotton (Gossypium hirsutum L.) is the most economically important species in the cotton genus (Gossypium spp.). Enhancing the cotton yield is a major goal in cotton breeding programs. Lint percentage (LP) and boll weight (BW) are the two most important components of cotton lint yield. The identification of stable and effective quantitative trait loci (QTLs) will aid the molecular breeding of cotton cultivars with high yield.

RESULTS

Genotyping by target sequencing (GBTS) and genome-wide association study (GWAS) with 3VmrMLM were used to identify LP and BW related QTLs from two recombinant inbred line (RIL) populations derived from high lint yield and fiber quality lines (ZR014121, CCRI60 and EZ60). The average call rate of a single locus was 94.35%, and the average call rate of an individual was 92.10% in GBTS. A total of 100 QTLs were identified; 22 of them were overlapping with the reported QTLs, and 78 were novel QTLs. Of the 100 QTLs, 51 QTLs were for LP, and they explained 0.29-9.96% of the phenotypic variation; 49 QTLs were for BW, and they explained 0.41-6.31% of the phenotypic variation. One QTL (qBW-E-A10-1, qBW-C-A10-1) was identified in both populations. Six key QTLs were identified in multiple-environments; three were for LP, and three were for BW. A total of 108 candidate genes were identified in the regions of the six key QTLs. Several candidate genes were positively related to the developments of LP and BW, such as genes involved in gene transcription, protein synthesis, calcium signaling, carbon metabolism, and biosynthesis of secondary metabolites. Seven major candidate genes were predicted to form a co-expression network. Six significantly highly expressed candidate genes of the six QTLs after anthesis were the key genes regulating LP and BW and affecting cotton yield formation.

CONCLUSIONS

A total of 100 stable QTLs for LP and BW in upland cotton were identified in this study; these QTLs could be used in cotton molecular breeding programs. Putative candidate genes of the six key QTLs were identified; this result provided clues for future studies on the mechanisms of LP and BW developments.

摘要

背景

陆地棉(Gossypium hirsutum L.)是棉花属(Gossypium spp.)中经济上最重要的物种。提高棉花产量是棉花育种计划的主要目标。皮棉百分率(LP)和铃重(BW)是棉花皮棉产量的两个最重要组成部分。鉴定稳定和有效的数量性状位点(QTL)将有助于培育具有高产的棉花品种。

结果

利用目标测序(GBTS)和基于 3VmrMLM 的全基因组关联研究(GWAS),从高皮棉产量和纤维品质品系(ZR014121、CCRI60 和 EZ60)衍生的两个重组自交系(RIL)群体中鉴定出与 LP 和 BW 相关的 QTL。单个位点的平均测序率为 94.35%,个体的平均测序率为 92.10%。在 GBTS 中共鉴定出 100 个 QTL,其中 22 个与报道的 QTL 重叠,78 个是新的 QTL。这 100 个 QTL 中,51 个与 LP 有关,占表型变异的 0.29-9.96%;49 个与 BW 有关,占表型变异的 0.41-6.31%。在两个群体中均鉴定到 1 个 QTL(qBW-E-A10-1,qBW-C-A10-1)。在多个环境中鉴定到 6 个关键 QTL,其中 3 个与 LP 有关,3 个与 BW 有关。在 6 个关键 QTL 区域共鉴定到 108 个候选基因。一些候选基因与 LP 和 BW 的发育呈正相关,如参与基因转录、蛋白质合成、钙信号、碳代谢和次生代谢物生物合成的基因。预测到 7 个主要候选基因形成了一个共表达网络。在授粉后,6 个 QTL 的 6 个显著高表达候选基因是调节 LP 和 BW 以及影响棉花产量形成的关键基因。

结论

本研究共鉴定到陆地棉 LP 和 BW 的 100 个稳定 QTL,这些 QTL 可用于棉花分子育种计划。鉴定到 6 个关键 QTL 的假定候选基因,为研究 LP 和 BW 发育的机制提供了线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/5b63a1772d7e/12870_2023_4147_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/519a8b244943/12870_2023_4147_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/747333a0ed32/12870_2023_4147_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/684f340c2c72/12870_2023_4147_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/8da7fda35cf8/12870_2023_4147_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/234511e94f6a/12870_2023_4147_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/5b63a1772d7e/12870_2023_4147_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/519a8b244943/12870_2023_4147_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/0e08b6de0301/12870_2023_4147_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/e701302d5c68/12870_2023_4147_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/747333a0ed32/12870_2023_4147_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/684f340c2c72/12870_2023_4147_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/8da7fda35cf8/12870_2023_4147_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/234511e94f6a/12870_2023_4147_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/10074700/5b63a1772d7e/12870_2023_4147_Fig8_HTML.jpg

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