Literature DB >> 22437490

Genetic structure and linkage disequilibrium pattern of a rapeseed (Brassica napus L.) association mapping panel revealed by microsatellites.

Yingjie Xiao1, Dongfang Cai, Wei Yang, Wei Ye, Muhammad Younas, Jiangsheng Wu, Kede Liu.   

Abstract

Understanding the population structure and linkage disequilibrium (LD) is a prerequisite for association mapping of complex traits in a target population. In this study, we assessed the genetic diversity, population structure and the extent of LD in a panel of 192 inbred lines of Brassica napus from all over the world using 451 single-locus microsatellite markers. The inbred lines could be divided into P1 and P2 groups by a model-based population structure analysis. Out of the 142 inbred lines in the P1 group, 126 lines were from China and Japan, and the remaining 16 lines were from Europe, Canada and Australia. In the P2 group, 33 out of the 50 lines were from Europe, Canada, and Australia, and the remaining 17 lines were from China. Structure analysis further divided each group into two subgroups. AMOVA, pairwise F (ST) and neutrality analyses confirmed the differentiation between groups and subgroups. More than 80 % of the pairwise kinship estimates between inbred lines were <0.05, indicating that relative kinship is weak in our panel. Only 6 % linked marker pairs showed LD, suggesting the low level of LD in this association panel. The LD decayed within 0.5-1 cM at the genome level, and varied considerably across each group and subgroup, due to the population size, genetic background and genetic drift. The characterization of the population structure and LD patterns would be useful for performing association studies for complex agronomic traits in rapeseed.

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Year:  2012        PMID: 22437490     DOI: 10.1007/s00122-012-1843-5

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


  42 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

Review 3.  Structure of linkage disequilibrium in plants.

Authors:  Sherry A Flint-Garcia; Jeffry M Thornsberry; Edward S Buckler
Journal:  Annu Rev Plant Biol       Date:  2003       Impact factor: 26.379

4.  Genome-wide association studies of 14 agronomic traits in rice landraces.

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Journal:  Nat Genet       Date:  2010-10-24       Impact factor: 38.330

5.  Association mapping for phenological, morphological, and quality traits in canola quality winter rapeseed (Brassica napus L.).

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Review 6.  Association mapping: critical considerations shift from genotyping to experimental design.

Authors:  Sean Myles; Jason Peiffer; Patrick J Brown; Elhan S Ersoz; Zhiwu Zhang; Denise E Costich; Edward S Buckler
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7.  Mapping of quantitative trait loci and development of allele-specific markers for seed weight in Brassica napus.

Authors:  Chuchuan Fan; Guangqin Cai; Jie Qin; Qingyuan Li; Minggui Yang; Jianzhong Wu; Tingdong Fu; Kede Liu; Yongming Zhou
Journal:  Theor Appl Genet       Date:  2010-06-24       Impact factor: 5.699

8.  Rare genetic variation at Zea mays crtRB1 increases beta-carotene in maize grain.

Authors:  Jianbing Yan; Catherine Bermudez Kandianis; Carlos E Harjes; Ling Bai; Eun-Ha Kim; Xiaohong Yang; Debra J Skinner; Zhiyuan Fu; Sharon Mitchell; Qing Li; Maria G Salas Fernandez; Maria Zaharieva; Raman Babu; Yang Fu; Natalia Palacios; Jiansheng Li; Dean Dellapenna; Thomas Brutnell; Edward S Buckler; Marilyn L Warburton; Torbert Rocheford
Journal:  Nat Genet       Date:  2010-03-21       Impact factor: 38.330

9.  Genomewide SNP variation reveals relationships among landraces and modern varieties of rice.

Authors:  Kenneth L McNally; Kevin L Childs; Regina Bohnert; Rebecca M Davidson; Keyan Zhao; Victor J Ulat; Georg Zeller; Richard M Clark; Douglas R Hoen; Thomas E Bureau; Renee Stokowski; Dennis G Ballinger; Kelly A Frazer; David R Cox; Badri Padhukasahasram; Carlos D Bustamante; Detlef Weigel; David J Mackill; Richard M Bruskiewich; Gunnar Rätsch; C Robin Buell; Hei Leung; Jan E Leach
Journal:  Proc Natl Acad Sci U S A       Date:  2009-07-13       Impact factor: 11.205

10.  Development and genetic mapping of microsatellite markers from genome survey sequences in Brassica napus.

Authors:  Xiaomao Cheng; Jinsong Xu; Shu Xia; Jianxun Gu; Yuan Yang; Jie Fu; Xiaoju Qian; Shunchang Zhang; Jiangsheng Wu; Kede Liu
Journal:  Theor Appl Genet       Date:  2009-02-04       Impact factor: 5.699

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  43 in total

1.  Association mapping of six yield‑related traits in rapeseed (Brassica napus L.).

Authors:  Dongfang Cai; Yingjie Xiao; Wei Yang; Wei Ye; Bo Wang; Muhammad Younas; Jiangsheng Wu; Kede Liu
Journal:  Theor Appl Genet       Date:  2014-01       Impact factor: 5.699

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Authors:  Udita Basu; Hari D Upadhyaya; Rishi Srivastava; Anurag Daware; Naveen Malik; Akash Sharma; Deepak Bajaj; Laxmi Narnoliya; Virevol Thakro; Alice Kujur; Shailesh Tripathi; Chellapilla Bharadwaj; V S Hegde; Ajay K Pandey; Ashok K Singh; Akhilesh K Tyagi; Swarup K Parida
Journal:  Plant Physiol       Date:  2019-02-08       Impact factor: 8.340

3.  Development of a core set of single-locus SSR markers for allotetraploid rapeseed (Brassica napus L.).

Authors:  Haitao Li; Muhammad Younas; Xiaofeng Wang; Xuemin Li; Lin Chen; Bo Zhao; Xun Chen; Jinsong Xu; Fan Hou; Baohua Hong; Gang Liu; Hongyang Zhao; Xueli Wu; Hongzhi Du; Jiangsheng Wu; Kede Liu
Journal:  Theor Appl Genet       Date:  2012-12-13       Impact factor: 5.699

4.  Genetic diversity, population structure and association analysis in cut chrysanthemum (Chrysanthemum morifolium Ramat.).

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5.  High-density SNP-based genetic map development and linkage disequilibrium assessment in Brassica napus L.

Authors:  Régine Delourme; Cyril Falentin; Berline Fopa Fomeju; Marie Boillot; Gilles Lassalle; Isabelle André; Jorge Duarte; Valérie Gauthier; Nicole Lucante; Amandine Marty; Maryline Pauchon; Jean-Philippe Pichon; Nicolas Ribière; Gwenn Trotoux; Philippe Blanchard; Nathalie Rivière; Jean-Pierre Martinant; Jérôme Pauquet
Journal:  BMC Genomics       Date:  2013-02-22       Impact factor: 3.969

6.  Population structure and genetic diversity characterization of a sunflower association mapping population using SSR and SNP markers.

Authors:  Carla V Filippi; Natalia Aguirre; Juan G Rivas; Jeremias Zubrzycki; Andrea Puebla; Diego Cordes; Maria V Moreno; Corina M Fusari; Daniel Alvarez; Ruth A Heinz; Horacio E Hopp; Norma B Paniego; Veronica V Lia
Journal:  BMC Plant Biol       Date:  2015-02-13       Impact factor: 4.215

7.  Genome-wide high-throughput SNP discovery and genotyping for understanding natural (functional) allelic diversity and domestication patterns in wild chickpea.

Authors:  Deepak Bajaj; Shouvik Das; Saurabh Badoni; Vinod Kumar; Mohar Singh; Kailash C Bansal; Akhilesh K Tyagi; Swarup K Parida
Journal:  Sci Rep       Date:  2015-07-24       Impact factor: 4.379

8.  Genetic Structure and Relationship Analysis of an Association Population in Jute (Corchorus spp.) Evaluated by SSR Markers.

Authors:  Liwu Zhang; Minhang Yuan; Aifen Tao; Jiantang Xu; Lihui Lin; Pingping Fang; Jianmin Qi
Journal:  PLoS One       Date:  2015-06-02       Impact factor: 3.240

9.  Genetic characterization of a core collection of flax (Linum usitatissimum L.) suitable for association mapping studies and evidence of divergent selection between fiber and linseed types.

Authors:  Braulio J Soto-Cerda; Axel Diederichsen; Raja Ragupathy; Sylvie Cloutier
Journal:  BMC Plant Biol       Date:  2013-05-06       Impact factor: 4.215

10.  The Natural Variation of Seed Weight Is Mainly Controlled by Maternal Genotype in Rapeseed (Brassica napus L.).

Authors:  Na Li; Wei Peng; Jiaqin Shi; Xinfa Wang; Guihua Liu; Hanzhong Wang
Journal:  PLoS One       Date:  2015-04-27       Impact factor: 3.240

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