Literature DB >> 33398500

Evolutionary QTL-allele changes in main stem node number among geographic and seasonal subpopulations of Chinese cultivated soybeans.

Abbas Muhammad Fahim1,2,3,4,5, Fangdong Liu1,2,3,4,5, Jianbo He1,2,3,4,5, Wubing Wang1,2,3,4,5, Guangnan Xing1,2,3,4,5, Junyi Gai6,7,8,9,10.   

Abstract

The main stem node number (MSN) is a trait related to geographic adaptation, plant architecture and yield potential of soybean. The QTL-allele constitution of the Chinese Cultivated Soybean Population (CCSP) was identified using the RTM-GWAS (restricted two-stage multi-locus genome-wide association study) procedure, from which a QTL-allele matrix was established and then separated into submatrices to explore the genetic structure, evolutionary differentiation, breeding potential and candidate genes of MSN in CCSP. The MSN of 821 accessions varied from 8.8 to 31.1, with an average of 16.3 in Nanjing, China (32.07° N, 118.62° E), where the MSNs of all the materials could be evaluated in a standardized manner. Among the six geo-seasonal subpopulations, the MSN varied from 21.7 in a southern summer-autumn-sowing subpopulation (SA-IV) down to 13.5 in a northeastern spring-sowing subpopulation (SP-I). The materials were genotyped with restriction site-associated DNA-sequencing. Totally 142 main-effect QTLs (73.24% new) with 560 alleles contributing 72.98% to the phenotypic variance were identified. The evolutionary QTL-allele changes in MSN from SA-IV through SP-I showed that inheritance (78.93% of alleles) was the primary factor influencing the evolution of this trait, followed by allele emergence (19.64% alleles), allele exclusion (1.43% alleles), and recombination among retained alleles. In the evolutionary changes, 70 QTLs, including 12 newly emerged QTLs, with 118 alleles were involved. An increase potential of 2-8 nodes was predicted and 112 candidate genes were annotated and preliminarily verified with χ2-tests in the CCSP. The RTM-GWAS showed powerful in detecting QTL-allele system, assessing evolution factors, predicting optimal crosses and identifying candidate genes in a germplasm population.

Entities:  

Keywords:  Geo-seasonal differentiation; Main stem node number (MSN); Population evolution; QTL-allele matrix; Restricted two-stage multi-locus genome-wide association study (RTM-GWAS); Soybean (Glycine max (L.) Merrill.)

Year:  2021        PMID: 33398500     DOI: 10.1007/s00438-020-01748-9

Source DB:  PubMed          Journal:  Mol Genet Genomics        ISSN: 1617-4623            Impact factor:   3.291


  1 in total

1.  Adverse Drug Reaction Discovery Using a Tumor-Biomarker Knowledge Graph.

Authors:  Meng Wang; Xinyu Ma; Jingwen Si; Hongjia Tang; Haofen Wang; Tunliang Li; Wen Ouyang; Liying Gong; Yongzhong Tang; Xi He; Wei Huang; Xing Liu
Journal:  Front Genet       Date:  2021-01-12       Impact factor: 4.599

  1 in total
  1 in total

1.  Transgressive Potential Prediction and Optimal Cross Design of Seed Protein Content in the Northeast China Soybean Population Based on Full Exploration of the QTL-Allele System.

Authors:  Weidan Feng; Lianshun Fu; Mengmeng Fu; Ziqian Sang; Yanping Wang; Lei Wang; Haixiang Ren; Weiguang Du; Xiaoshuai Hao; Lei Sun; Jiaoping Zhang; Wubin Wang; Guangnan Xing; Jianbo He; Junyi Gai
Journal:  Front Plant Sci       Date:  2022-07-12       Impact factor: 6.627

  1 in total

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