Literature DB >> 30353473

Genetic diversity, linkage disequilibrium, and population structure in a panel of Brazilian rice accessions.

Eduardo Venske1, Cássia Fernanda Stafen1, Victoria Freitas de Oliveira1, Luciano Carlos da Maia1, Ariano Martins de Magalhães Junior2, Kenneth L McNally3, Antonio Costa de Oliveira4, Camila Pegoraro1.   

Abstract

Narrowing of genetic diversity and the quantitative nature of most agronomic traits is a challenge for rice breeding. Genome-wide association studies have a great potential to identify important variation in loci underlying quantitative and complex traits; however, before performing the analysis, it is important to assess parameters of the genotypic data and population under study, to improve the accuracy of the genotype-phenotype associations. The aim of this study was to access the genetic diversity, linkage disequilibrium, and population structure of a working panel of Brazilian and several introduced rice accessions, which are currently being phenotyped for a vast number of traits to undergo association mapping. Ninety-four accessions were genotyped with 7098 SNPs, and after filtering for higher call rates and removing rare variants, 93 accessions and 4973 high-quality SNPs remained for subsequent analyses and association studies. The overall mean of the polymorphic information content, heterozygosity, and gene diversity of the SNPs was comparable to other rice panels. The r2 measure of linkage disequilibrium decayed to 0.25 in approximately 150 kb, a slow decay, explained by the autogamous nature of rice and the small size of the panel. Regarding population structure, eight groups were formed according to Bayesian clustering. Principle components and neighbor-joining analyses were able to distinguish part of the groups formed, mainly regarding the sub-species indica and japonica. Our results demonstrate that the population and SNPs are of high quality for association mapping.

Entities:  

Keywords:  Association mapping; Genomic tools; Genotypic parameters

Mesh:

Year:  2018        PMID: 30353473     DOI: 10.1007/s13353-018-0475-0

Source DB:  PubMed          Journal:  J Appl Genet        ISSN: 1234-1983            Impact factor:   3.240


  14 in total

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Journal:  Annu Rev Plant Biol       Date:  2003       Impact factor: 26.379

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Journal:  Proc Natl Acad Sci U S A       Date:  2015-09-10       Impact factor: 11.205

3.  PowerMarker: an integrated analysis environment for genetic marker analysis.

Authors:  Kejun Liu; Spencer V Muse
Journal:  Bioinformatics       Date:  2005-02-10       Impact factor: 6.937

4.  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

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Journal:  Theor Appl Genet       Date:  2011-06-18       Impact factor: 5.699

6.  The extent of linkage disequilibrium in rice (Oryza sativa L.).

Authors:  Kristie A Mather; Ana L Caicedo; Nicholas R Polato; Kenneth M Olsen; Susan McCouch; Michael D Purugganan
Journal:  Genetics       Date:  2007-10-18       Impact factor: 4.562

7.  Genome-wide association mapping of salinity tolerance in rice (Oryza sativa).

Authors:  Vinod Kumar; Anshuman Singh; S V Amitha Mithra; S L Krishnamurthy; Swarup K Parida; Sourabh Jain; Kapil K Tiwari; Pankaj Kumar; Atmakuri R Rao; S K Sharma; Jitendra P Khurana; Nagendra K Singh; Trilochan Mohapatra
Journal:  DNA Res       Date:  2015-01-27       Impact factor: 4.458

8.  Analysis of Population Structure and Genetic Diversity in Rice Germplasm Using SSR Markers: An Initiative Towards Association Mapping of Agronomic Traits in Oryza Sativa.

Authors:  Vishnu Varthini Nachimuthu; Raveendran Muthurajan; Sudhakar Duraialaguraja; Rajeswari Sivakami; Balaji Aravindhan Pandian; Govinthraj Ponniah; Karthika Gunasekaran; Manonmani Swaminathan; Suji K K; Robin Sabariappan
Journal:  Rice (N Y)       Date:  2015-09-26       Impact factor: 4.783

9.  Genetic structure, linkage disequilibrium and association mapping of Verticillium wilt resistance in elite cotton (Gossypium hirsutum L.) germplasm population.

Authors:  Yunlei Zhao; Hongmei Wang; Wei Chen; Yunhai Li
Journal:  PLoS One       Date:  2014-01-23       Impact factor: 3.240

10.  fastSTRUCTURE: variational inference of population structure in large SNP data sets.

Authors:  Anil Raj; Matthew Stephens; Jonathan K Pritchard
Journal:  Genetics       Date:  2014-04-02       Impact factor: 4.562

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  1 in total

1.  An improved 7K SNP array, the C7AIR, provides a wealth of validated SNP markers for rice breeding and genetics studies.

Authors:  Karina Y Morales; Namrata Singh; Francisco Agosto Perez; John Carlos Ignacio; Ranjita Thapa; Juan D Arbelaez; Rodante E Tabien; Adam Famoso; Diane R Wang; Endang M Septiningsih; Yuxin Shi; Tobias Kretzschmar; Susan R McCouch; Michael J Thomson
Journal:  PLoS One       Date:  2020-05-14       Impact factor: 3.240

  1 in total

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