Dataset Information

Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population.

ABSTRACT:

Background

Human demand for wheat will continue to increase together with the continuous global population growth. Agronomic traits in wheat are susceptible to environmental conditions. Therefore, in breeding practice, priority is given to QTLs of agronomic traits that can be stably detected across multiple environments and over many years.

Results

In this study, QTL analysis was conducted for eight agronomic traits using an introgression line population across eight environments (drought stressed and well-watered) for 5 years. In total, 44 additive QTLs for the above agronomic traits were detected on 15 chromosomes. Among these, qPH-6A, qHD-1A, qSL-2A, qHD-2D and qSL-6A were detected across seven, six, five, five and four environments, respectively. The means in the phenotypic variation explained by these five QTLs were 12.26, 9.51, 7.77, 7.23, and 8.49%, respectively.

Conclusions

We identified five stable QTLs, which includes qPH-6A, qHD-1A, qSL-2A, qHD-2D and qSL-6A. They play a critical role in wheat agronomic traits. One of the dwarf genes Rht14, Rht16, Rht18 and Rht25 on chromosome 6A might be the candidate gene for qPH-6A. The qHD-1A and qHD-2D were novel stable QTLs for heading date and they differed from known vernalization genes, photoperiod genes and earliness per se genes.

SUBMITTER: Chen W

PROVIDER: S-EPMC7296640 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population.

Chen Weiguo W Sun Daizhen D Li Runzhi R Wang Shuguang S Shi Yugang Y Zhang Wenjun W Jing Ruilian R

BMC plant biology 20200615 1

<h4>Background</h4>Human demand for wheat will continue to increase together with the continuous global population growth. Agronomic traits in wheat are susceptible to environmental conditions. Therefore, in breeding practice, priority is given to QTLs of agronomic traits that can be stably detected across multiple environments and over many years.<h4>Results</h4>In this study, QTL analysis was conducted for eight agronomic traits using an introgression line population across eight environments ...[more]

PMID: 32539793

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Dataset Information

Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population.

Background

Results

Conclusions

Publications

Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population.

Similar Datasets

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