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烟草(L.)主流烟气中九种有害成分性状的遗传结构剖析

Dissection of genetic architecture of nine hazardous component traits of mainstream smoke in tobacco ( L.).

作者信息

Xu Manling, Tong Zhijun, Jin Chengting, Zhang Qixin, Lin Feng, Fang Dunhuang, Chen Xuejun, Zhu Tianneng, Lou Xiangyang, Xiao Bingguang, Xu Haiming

机构信息

Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang, China.

Key Laboratory of Tobacco Biotechnological Breeding, National Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming, Yunnan, China.

出版信息

Front Plant Sci. 2024 May 8;15:1358953. doi: 10.3389/fpls.2024.1358953. eCollection 2024.

Abstract

Tobacco ( L.) use is the leading cause of preventable death, due to deleterious chemical components and smoke from tobacco products, and therefore reducing harmful chemical components in tobacco is one of the crucial tobacco breeding targets. However, due to complexity of tobacco smoke and unavailability of high-density genetic maps, the genetic architecture of representative hazardous smoke has not been fully dissected. The present study aimed to explore the genetic architecture of nine hazardous component traits of mainstream smoke through QTL mapping using 271 recombinant inbred lines (RILs) derived from K326 and Y3 in multiple environments. The analysis of genotype and genotype by environment interaction () revealed substantially greater heritability over 95% contributed mostly by interaction effects. We also observed strong genetic correlations among most studied hazardous smoke traits, with the highest correlation coefficient of 0.84 between carbon monoxide and crotonaldehyde. Based on a published high-density genetic map, a total of 19 novel QTLs were detected for eight traits using a full QTL model, of which 17 QTLs showed significant additive effects, six showed significant additive-by-environment interaction effects, and one pair showed significant epistasis-by-environment interaction effect. Bioinformatics analysis of sequence in QTL region predicted six genes as candidates for four traits, of which , , and had pleiotropic effects on PHE and TAR.

摘要

烟草(L.)的使用是可预防死亡的主要原因,这归因于烟草制品中的有害化学成分和烟雾,因此减少烟草中的有害化学成分是烟草育种的关键目标之一。然而,由于烟草烟雾的复杂性以及高密度遗传图谱的缺乏,代表性有害烟雾的遗传结构尚未得到充分解析。本研究旨在通过在多个环境中对由K326和Y3衍生的271个重组自交系(RIL)进行QTL定位,探索主流烟雾中九种有害成分性状的遗传结构。基因型分析以及基因型与环境互作()分析表明,遗传力显著超过95%,主要由互作效应贡献。我们还观察到大多数研究的有害烟雾性状之间存在很强的遗传相关性,一氧化碳和巴豆醛之间的相关系数最高,为0.84。基于已发表的高密度遗传图谱,使用完整QTL模型对八个性状共检测到19个新的QTL,其中17个QTL表现出显著的加性效应,6个表现出显著的加性×环境互作效应,一对表现出显著的上位性×环境互作效应。对QTL区域序列的生物信息学分析预测了六个基因作为四个性状的候选基因,其中,和对PHE和TAR具有多效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de4b/11109366/979398cddaed/fpls-15-1358953-g001.jpg

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