Campus Units

Agronomy

Document Type

Article

Publication Date

2017

Journal or Book Title

Frontiers in Plant Science

Volume

8

DOI

10.3389/fpls.2017.00813

Abstract

Deep-sowing is an effective measure to ensure seeds absorbing water from deep soil layer and emerging normally in arid and semiarid regions. However, existing varieties demonstrate poor germination ability in deep soil layer and some key quantitative trait loci (QTL) or genes related to deep-sowing germination ability remain to be identified and analyzed. In this study, a high-resolution genetic map based on 280 lines of the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population which comprised 6618 bin markers was used for the QTL analysis of deep-sowing germination related traits. The results showed significant differences in germination related traits under deep-sowing condition (12.5 cm) and standard-germination condition (2 cm) between two parental lines. In total, 8, 11, 13, 15, and 18 QTL for germination rate, seedling length, mesocotyl length, plumule length, and coleoptile length were detected for the two sowing conditions, respectively. These QTL explained 2.51–7.8% of the phenotypic variance with LOD scores ranging from 2.52 to 7.13. Additionally, 32 overlapping QTL formed 11 QTL clusters on all chromosomes except for chromosome 8, indicating the minor effect genes have a pleiotropic role in regulating various traits. Furthermore, we identified six candidate genes related to deep-sowing germination ability, which were co-located in the cluster regions. The results provide a basis for molecular marker assisted breeding and functional study in deep-sowing germination ability of maize.

Comments

This article is published as Liu, Hongjun, Lin Zhang, Jiechen Wang, Changsheng Li, Xing Zeng, Shupeng Xie, Yongzhong Zhang et al. "Quantitative Trait Locus Analysis for Deep-Sowing Germination Ability in the Maize IBM Syn10 DH Population." Frontiers in plant science 8 (2017). 10.3389/fpls.2017.00813. Posted with permission.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Copyright Owner

The Authors

Language

en

File Format

application/pdf

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