Literature DB >> 25572236

Population structure and association mapping studies for important agronomic traits in soybean.

Bhupender Kumar1, Akshay Talukdar, Indu Bala, Khushbu Verma, Sanjay Kumar Lal, Ramesh Lal Sapra, B Namita, Subhash Chander, Reshu Tiwari.   

Abstract

The present study was carried out with a set of 96 diverse soybean genotypes with the objectives of analysing the population structure and to identify molecular markers associated with important agronomic traits. Large phenotypic variability was observed for the agronomic traits under study indicating suitability of the genotypes for association studies. The maximum values for plant height, pods per plant, seeds per pod, 100-seed weight and seed yield per plant were approximately two and half to three times more than the minimum values for the genotypes. Seed yield per plant was found to be significantly correlated with pods per plant (r = 0.77), 100-seed weight (r = 0.35) and days to maturity (r = 0.23). The population structure studies depicted the presence of seven subpopulations which nearly corresponded with the source of geographical origin of the genotypes. Linkage disequilibrium (LD) between the linked markers decreased with the increased distance, and a substantial drop in LD decay values was observed between 30 and 35 cM. Genomewide marker-traits association analysis carried out using general linear (GLM) and mixed linear models (MLM) identified six genomic regions (two of them were common in both) on chromosomes 6, 7, 8, 13, 15 and 17, which were found to be significantly associated with various important traits viz., plant height, pods per plant, 100-seed weight, plant growth habit, average number of seeds per pod, days to 50% flowering and days to maturity. The phenotypic variation explained by these loci ranged from 6.09 to 13.18% and 4.25 to 9.01% in the GLM and MLM studies, respectively. In conclusion, association mapping (AM) in soybean could be a viable alternative to conventional QTL mapping approach.

Entities:  

Mesh:

Year:  2014        PMID: 25572236

Source DB:  PubMed          Journal:  J Genet        ISSN: 0022-1333            Impact factor:   1.166


  30 in total

1.  Inference of population structure using multilocus genotype data.

Authors:  J K Pritchard; M Stephens; P Donnelly
Journal:  Genetics       Date:  2000-06       Impact factor: 4.562

2.  Structure of linkage disequilibrium and phenotypic associations in the maize genome.

Authors:  D L Remington; J M Thornsberry; Y Matsuoka; L M Wilson; S R Whitt; J Doebley; S Kresovich; M M Goodman; E S Buckler
Journal:  Proc Natl Acad Sci U S A       Date:  2001-09-18       Impact factor: 11.205

3.  Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies.

Authors:  Daniel Falush; Matthew Stephens; Jonathan K Pritchard
Journal:  Genetics       Date:  2003-08       Impact factor: 4.562

4.  Believe it or not, QTLs are accurate!

Authors:  Adam H Price
Journal:  Trends Plant Sci       Date:  2006-04-17       Impact factor: 18.313

Review 5.  Genetic architecture of complex traits in plants.

Authors:  James B Holland
Journal:  Curr Opin Plant Biol       Date:  2007-02-08       Impact factor: 7.834

6.  TASSEL: software for association mapping of complex traits in diverse samples.

Authors:  Peter J Bradbury; Zhiwu Zhang; Dallas E Kroon; Terry M Casstevens; Yogesh Ramdoss; Edward S Buckler
Journal:  Bioinformatics       Date:  2007-06-22       Impact factor: 6.937

7.  Variation explained in mixed-model association mapping.

Authors:  G Sun; C Zhu; M H Kramer; S-S Yang; W Song; H-P Piepho; J Yu
Journal:  Heredity (Edinb)       Date:  2010-02-10       Impact factor: 3.821

8.  Association analysis of candidate genes for maysin and chlorogenic acid accumulation in maize silks.

Authors:  S J Szalma; E S Buckler; M E Snook; M D McMullen
Journal:  Theor Appl Genet       Date:  2005-04-02       Impact factor: 5.699

9.  Determination of the genetic architecture of seed size and shape via linkage and association analysis in soybean (Glycine max L. Merr.).

Authors:  Zhenbin Hu; Huairen Zhang; Guizhen Kan; Deyuan Ma; Dan Zhang; Guixia Shi; Delin Hong; Guozheng Zhang; Deyue Yu
Journal:  Genetica       Date:  2013-06-11       Impact factor: 1.082

10.  Analysis of molecular diversity, population structure and linkage disequilibrium in a worldwide survey of cultivated barley germplasm (Hordeum vulgare L.).

Authors:  Lyudmyla V Malysheva-Otto; Martin W Ganal; Marion S Röder
Journal:  BMC Genet       Date:  2006-01-24       Impact factor: 2.797

View more
  7 in total

Review 1.  Quantitative trait loci from identification to exploitation for crop improvement.

Authors:  Jitendra Kumar; Debjyoti Sen Gupta; Sunanda Gupta; Sonali Dubey; Priyanka Gupta; Shiv Kumar
Journal:  Plant Cell Rep       Date:  2017-03-28       Impact factor: 4.570

2.  Analysis of spatial distribution of genetic diversity and validation of Indian foxtail millet core collection.

Authors:  Subhash Chander; K V Bhat; Ratna Kumari; Sanjay Sen; A B Gaikwad; M V C Gowda; N Dikshit
Journal:  Physiol Mol Biol Plants       Date:  2017-05-18

3.  Population Structure Analysis and Association Mapping for Turcicum Leaf Blight Resistance in Tropical Maize Using SSR Markers.

Authors:  Bhupender Kumar; Mukesh Choudhary; Pardeep Kumar; Krishan Kumar; Sonu Kumar; Brijesh Kumar Singh; Chayanika Lahkar; Pushpendra Kumar; Zahoor Ahmed Dar; Rakesh Devlash; Karambir Singh Hooda; Satish Kumar Guleria; Sujay Rakshit
Journal:  Genes (Basel)       Date:  2022-03-29       Impact factor: 4.141

4.  Genome-wide associations and epistatic interactions for internode number, plant height, seed weight and seed yield in soybean.

Authors:  Teshale Assefa; Paul I Otyama; Anne V Brown; Scott R Kalberer; Roshan S Kulkarni; Steven B Cannon
Journal:  BMC Genomics       Date:  2019-06-26       Impact factor: 3.969

Review 5.  Advances and Challenges for QTL Analysis and GWAS in the Plant-Breeding of High-Yielding: A Focus on Rapeseed.

Authors:  Shahid Ullah Khan; Sumbul Saeed; Muhammad Hafeez Ullah Khan; Chuchuan Fan; Sunny Ahmar; Osvin Arriagada; Raheel Shahzad; Ferdinando Branca; Freddy Mora-Poblete
Journal:  Biomolecules       Date:  2021-10-15

6.  Identification of candidate genes and natural allelic variants for QTLs governing plant height in chickpea.

Authors:  Alice Kujur; Hari D Upadhyaya; Deepak Bajaj; C L L Gowda; Shivali Sharma; Akhilesh K Tyagi; Swarup K Parida
Journal:  Sci Rep       Date:  2016-06-20       Impact factor: 4.379

Review 7.  Photosynthesis in a Changing Global Climate: Scaling Up and Scaling Down in Crops.

Authors:  Marouane Baslam; Toshiaki Mitsui; Michael Hodges; Eckart Priesack; Matthew T Herritt; Iker Aranjuelo; Álvaro Sanz-Sáez
Journal:  Front Plant Sci       Date:  2020-07-06       Impact factor: 5.753

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.