Literature DB >> 33420806

Fine mapping QTL and mining genes for protein content in soybean by the combination of linkage and association analysis.

Xiyu Li1, Ping Wang1,2, Kaixin Zhang1, Shulin Liu3, Zhongying Qi1, Yanlong Fang1, Yue Wang1, Xiaocui Tian1, Jie Song1, Jiajing Wang1, Chang Yang1, Xu Sun1, Zhixi Tian3, Wen-Xia Li4, Hailong Ning5.   

Abstract

Soybean is one main source of dietary protein; therefore, improving protein content is an important objective in breeding programs. There is a significant negative correlation between protein and oil content, which influenced mapping quantitative trait locus (QTL) and quantitative trait nucleotides for these two traits. In this study, a linkage map was created with 2232 single-nucleotide polymorphism markers for the four-way recombinant inbred line (FW-RIL) population derived from the cross (Kenfeng 14 × Kenfeng 15) × (Heinong 48 × Kenfeng 19), and then conditional and unconditional QTL analyses were carried out by inclusive complete interval mapping based on the phenotypic data of protein and oil content collected in 10 different environments. As shown in the results of linkage analysis, a total of 85 QTL have been detected. We have performed association analysis using 109,676 markers after quality filtering for FW-RIL, and the results have shown that a total of 60 QTNs were detected. We have performed association analysis using 63,306 markers after quality filtering for resource population, and the results have shown that a total of 123 QTNs were detected. We have combined linkage and association analysis, and there are six QTNs verified by FW-RIL and resource population. We have performed pathway analysis on the genes in these six QTN attenuation regions, and the result shows that a total of four candidate genes are related to the synthesis or metabolism of soybean protein. These findings will facilitate marker-assisted selection and molecular breeding of soybean.

Entities:  

Year:  2021        PMID: 33420806     DOI: 10.1007/s00122-020-03756-0

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


  19 in total

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4.  Genetic basis of soybean adaptation to North American vs. Asian mega-environments in two independent populations from Canadian × Chinese crosses.

Authors:  M Eugenia Rossi; James H Orf; Li-Jun Liu; Zhimin Dong; Istvan Rajcan
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6.  Determination of the genetic architecture of seed size and shape via linkage and association analysis in soybean (Glycine max L. Merr.).

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Journal:  Genetica       Date:  2013-06-11       Impact factor: 1.082

7.  Seed and agronomic QTL in low linolenic acid, lipoxygenase-free soybean (Glycine max (L.) Merrill) germplasm.

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Journal:  Genome       Date:  2006-12       Impact factor: 2.166

8.  Relationship between asparagine metabolism and protein concentration in soybean seed.

Authors:  Sudhakar Pandurangan; Agnieszka Pajak; Stephen J Molnar; Elroy R Cober; Sangeeta Dhaubhadel; Cinta Hernández-Sebastià; Werner M Kaiser; Randall L Nelson; Steven C Huber; Frédéric Marsolais
Journal:  J Exp Bot       Date:  2012-02-22       Impact factor: 6.992

9.  Unconditional and conditional QTL analyses of seed fatty acid composition in Brassica napus L.

Authors:  Feng Chen; Wei Zhang; Kunjiang Yu; Lijie Sun; Jianqin Gao; Xiaoying Zhou; Qi Peng; Sanxiong Fu; Maolong Hu; Weihua Long; Huiming Pu; Song Chen; Xiaodong Wang; Jiefu Zhang
Journal:  BMC Plant Biol       Date:  2018-03-23       Impact factor: 4.215

10.  The Genetic Basis of Natural Variation in Kernel Size and Related Traits Using a Four-Way Cross Population in Maize.

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  2 in total

1.  Detecting QTL and Candidate Genes for Plant Height in Soybean via Linkage Analysis and GWAS.

Authors:  Jiajing Wang; Bo Hu; Yuliang Jing; Xiping Hu; Yue Guo; Jiankun Chen; Yuxi Liu; Jianhui Hao; Wen-Xia Li; Hailong Ning
Journal:  Front Plant Sci       Date:  2022-01-21       Impact factor: 5.753

Review 2.  Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and 'Omics' Tools.

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Journal:  Int J Mol Sci       Date:  2022-07-12       Impact factor: 6.208

  2 in total

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