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QTL Detection for Internode Component Index in Wheat Using a RIL Mapping Population

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Abstract

Plant height (PH) is one of the most important traits related to plant architecture in wheat. Together, the lengths of individual internodes determine plant height and have a great influence on lodging resistance. To specify the genetic basis of wheat internode characteristics, we identified quantitative trait loci (QTLs) for each internode component index (ICI) and plant height component index (PHCI) using a recombinant inbred line (RIL) mapping population derived from ‘Kenong 9204’ (‘KN9204’) × ‘Jing 411’ (‘J411’). Up to 57 putative additive QTLs for the four ICIs and PHCI were detected, which together covered 20 of the 21 wheat chromosomes, with the exception of chromosome 1B. Among them, eight QTLs were major, stable QTLs with a logarithm-of-odds (LOD) score of ≥ 3.0 and a phenotypic variance explained (PVE) of ≥ 7.0%. In the epistatic analysis, only one pair of epistatic QTLs was identified for the first internode component index (FIITCI) and three pairs of epistatic QTLs for the third internode component index (TITCI). A total of 20 of the 57 detected QTLs (35.1%) were co-localized QTLs for PH, spike length, and internode lengths, indicating that those traits have their own individual genetic basis in most cases. Moreover, 12 QTL clusters for PHCI/ICIs and yield-related traits were identified, indicating that plant architecture plays a potential role in the formation of yield in wheat. The plant architecture with gradually bottom-up shortened internode lengths tends to be high-yielding potential, especially for the uppermost internode. This study may provide useful information for understanding the genetic basis of plant height components and to accelerate the genetic improvement of plant ideotypes designed to increase yield.

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Funding

This research was supported by the Agricultural Variety Improvement Project of Shandong Province, China (2019LZGC016), the Major Basic Research Project of Natural Science Foundation of Shandong Province, China (ZR2019ZD16), the Agricultural Variety Improvement Project of Shandong Province, China (2021LZGC009), the National Natural Science Foundation of China (31871612, 32072051, 32101726), the Youth Innovation Technology Support Planning Project for Institution of Higher Education of Shandong Province, China (2019KJF002), and Yantai New and Old Kinetic Energy Conversion Research Institute and Yantai Science and Technology Achievement Transfer Demonstration Base Funded Project (2019XJDN007).

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  1. Ran Qin and Tianhang Ma contributed equally to this work.

Authors and Affiliations

  1. Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, School of Agriculture, Ludong University, Yantai, 264025, Shandong, China

    Ran Qin, Tianhang Ma, Mingsu Cao, Xijian Liu, Xiaohan Zhou, Guimei Hu, Jingguo Xiao, Jiajin Dong, Wenchao Kong, Chunhua Zhao, Yongzhen Wu, Han Sun & Fa Cui

  2. Shandong Seed Administration Station, Jinan, 250100, Shandong, China

    Wen Zhong

  3. Yantai Academy of Agricultural Sciences, Yantai, 264025, Shandong, China

    Xiaohui Sun

  4. Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050022, Hebei, China

    Jun Ji

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  1. Ran Qin
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Contributions

Cui F, Ji J, and Qin R designed the research; Ji J and Cui F developed the KJ-RIL population; Ma TH, Cao MS, Liu XJ, Zhou XH, Hu GM, Zhong W, and Sun XH conducted phenotyping of the KJ-RIL population; Cui F and Ji J conducted genotyping of the KJ-RIL population; Qin R, Ma TH, Xiao JG, Dong JJ, Kong WC, Zhao CH, Wu YZ, and Sun H analyzed the data; Qin R, Ma TH, and Cui F wrote and revised the paper; all authors read and approved the final manuscript.

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Correspondence to Jun Ji or Fa Cui.

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Key Message

QTLs for each internode component index (ICI) and plant height component index (PHCI) were identified using a recombinant inbred line (RIL) mapping population. The QTL clusters for PHCI/ICI and plant height and plant height components together with yield-related traits were simultaneously analyzed in the present study.

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Qin, R., Ma, T., Cao, M. et al. QTL Detection for Internode Component Index in Wheat Using a RIL Mapping Population. Plant Mol Biol Rep 41, 195–208 (2023). https://doi.org/10.1007/s11105-022-01359-1

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