Literature DB >> 34436627

A SNP-based GWAS and functional haplotype-based GWAS of flag leaf-related traits and their influence on the yield of bread wheat (Triticum aestivum L.).

Shulin Chen1, Fang Liu2, Wenxue Wu1, Yong Jiang2, Kehui Zhan3.   

Abstract

KEY MESSAGE: The genetic architecture of five flag leaf morphology traits was dissected by the functional haplotype-based GWAS and a standard SNP-based GWAS in a diverse population consisting of 197 varieties. Flag leaf morphology (FLM) is a critical factor affecting plant architecture and grain yield in wheat. The genetic architecture of FLM traits has been extensively studied with QTL mapping in bi-parental populations, while few studies exploited genome-wide association studies (GWAS) in diverse populations. In this study, a panel of 197 elite and historical varieties from China was evaluated for five FLM traits including the length (FLL), width (FLW), ratio (FLR), area (FLA) and angle (FLANG) as well as yield in nine environments. Based on the phenotypic correlation between yield and FLL (-0.43), FLA (- 0.32) and FLW (0.11), an empirical FLM index combining the three FLM traits proved to be a good predictor for yield. Two GWAS approaches were applied to dissect the genetic architecture of five FLM traits with a Wheat660K SNP array. The functional haplotype-based GWAS revealed 6, 5 and 7 QTL for FLANG, FLL and FLR, respectively, whereas two QTL for FLW and one for FLR were identified by the standard SNP-based GWAS. Due to co-localization, there were 18 independent QTL and 10 of them were close to known ones. One co-localized QTL on chromosome 5A was associated with FLL, FLANG and FLR. Moreover, both GWAS approaches identified a novel QTL for FLR on chromosome 6B which was not reported in previous studies. This study provides new insights into the relationship between FLM and yield and broadens our understanding of the genetic architecture of FLM traits in wheat.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Year:  2021        PMID: 34436627     DOI: 10.1007/s00122-021-03935-7

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  31 in total

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2.  FaST linear mixed models for genome-wide association studies.

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Journal:  Nat Methods       Date:  2011-09-04       Impact factor: 28.547

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Journal:  Theor Appl Genet       Date:  2010-06-05       Impact factor: 5.699

4.  Variances and covariances of squared linkage disequilibria in finite populations.

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Journal:  Theor Popul Biol       Date:  1988-02       Impact factor: 1.570

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Journal:  Heredity (Edinb)       Date:  2014-11-12       Impact factor: 3.821

6.  Mapping of quantitative trait loci determining agronomic important characters in hexaploid wheat ( Triticum aestivum L.).

Authors:  A. Börner; E. Schumann; A. Fürste; H. Cöster; B. Leithold; S. Röder; E. Weber
Journal:  Theor Appl Genet       Date:  2002-06-21       Impact factor: 5.699

7.  Mapping QTLs of yield-related traits using RIL population derived from common wheat and Tibetan semi-wild wheat.

Authors:  Gang Liu; Lijia Jia; Lahu Lu; Dandan Qin; Jinping Zhang; Panfeng Guan; Zhongfu Ni; Yingyin Yao; Qixin Sun; Huiru Peng
Journal:  Theor Appl Genet       Date:  2014-09-11       Impact factor: 5.699

8.  Identification of QTL underlying physiological and morphological traits of flag leaf in barley.

Authors:  Lipan Liu; Genlou Sun; Xifeng Ren; Chengdao Li; Dongfa Sun
Journal:  BMC Genet       Date:  2015-03-20       Impact factor: 2.797

9.  Associations of canopy leaf traits with SNP markers in durum wheat (Triticum turgidum L. durum (Desf.)).

Authors:  Sisi Huang; Longqing Sun; Xin Hu; Yanhong Wang; Yujuan Zhang; Eviatar Nevo; Junhua Peng; Dongfa Sun
Journal:  PLoS One       Date:  2018-10-23       Impact factor: 3.240

10.  Selection Signatures Underlying Dramatic Male Inflorescence Transformation During Modern Hybrid Maize Breeding.

Authors:  Joseph L Gage; Michael R White; Jode W Edwards; Shawn Kaeppler; Natalia de Leon
Journal:  Genetics       Date:  2018-09-26       Impact factor: 4.562

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