Literature DB >> 35106687

GWAS to spot candidate genes associated with grain quality traits in diverse rice accessions of North East India.

Rahul K Verma1, S K Chetia2, Vinay Sharma3, Samindra Baishya4, Himanshu Sharma5, M K Modi6.   

Abstract

INTRODUCTION: North East (NE) India is the second centre for the origin of rice and is enriched with a diverse collection of traditional rice accessions. These genotypes possess unique traits of breeding interest and are rich in grain nutritional and cooking qualities. Therefore, quantitative trait loci (QTLs)/genes associated with the various quality traits may be identified through genome-wide association studies (GWAS) and used in crop improvement programmes. METHODS AND
RESULTS: A pool of 526 unique rice accessions from Assam, North East (NE) India were characterized by using 9 grain-quality traits and grouped into 16 clusters. Among these, the highest number of 156 (29.65%) genotypes belongs to diverse phenotypic classes; Sali, Lahi, and Chokuwa were grouped into cluster 6. The first three principal components showed 54.76% of morphological variability with Eigenvalue >1. Genome-wide association studies (GWAS) was performed in 103 rice accessions using 42,446 SNP markers. A total of 11 significant marker-trait associations were detected for 5 grain-quality traits, explaining 0.22-8.86% of phenotypic variation (PV). In-silico mining of QTLs detected 'candidate genes' associated with the quality traits.
CONCLUSIONS: The phenotypic diversity among the 526 rice accessions of NE India was studied using grain quality traits and grouped into 16 significantly different clusters. The QTLs, or candidate genes identified for various grain quality traits, may be used in breeding programmes for the development of improved rice varieties.
© 2021. The Author(s), under exclusive licence to Springer Nature B.V.

Entities:  

Keywords:  Candidate genes; Grain quality traits; Marker-trait associations; Rice

Mesh:

Year:  2022        PMID: 35106687     DOI: 10.1007/s11033-021-07113-2

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.742


  16 in total

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

Authors:  Xuehui Huang; Xinghua Wei; Tao Sang; Qiang Zhao; Qi Feng; Yan Zhao; Canyang Li; Chuanrang Zhu; Tingting Lu; Zhiwu Zhang; Meng Li; Danlin Fan; Yunli Guo; Ahong Wang; Lu Wang; Liuwei Deng; Wenjun Li; Yiqi Lu; Qijun Weng; Kunyan Liu; Tao Huang; Taoying Zhou; Yufeng Jing; Wei Li; Zhang Lin; Edward S Buckler; Qian Qian; Qi-Fa Zhang; Jiayang Li; Bin Han
Journal:  Nat Genet       Date:  2010-10-24       Impact factor: 38.330

2.  GAPIT: genome association and prediction integrated tool.

Authors:  Alexander E Lipka; Feng Tian; Qishan Wang; Jason Peiffer; Meng Li; Peter J Bradbury; Michael A Gore; Edward S Buckler; Zhiwu Zhang
Journal:  Bioinformatics       Date:  2012-07-13       Impact factor: 6.937

3.  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

4.  Genome-wide association studies for agronomical traits in winter rice accessions of Assam.

Authors:  Rahul K Verma; S K Chetia; P C Dey; Anjum Rahman; Sandhani Saikia; Vinay Sharma; Himanshu Sharma; P Sen; M K Modi
Journal:  Genomics       Date:  2021-01-19       Impact factor: 5.736

5.  A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species.

Authors:  Robert J Elshire; Jeffrey C Glaubitz; Qi Sun; Jesse A Poland; Ken Kawamoto; Edward S Buckler; Sharon E Mitchell
Journal:  PLoS One       Date:  2011-05-04       Impact factor: 3.240

6.  Mapping QTLs underpin nutrition components in aromatic rice germplasm.

Authors:  M Z Islam; M Arifuzzaman; S Banik; M A Hossain; J Ferdous; M Khalequzzaman; B R Pittendrigh; M Tomita; M P Ali
Journal:  PLoS One       Date:  2020-06-11       Impact factor: 3.240

Review 7.  From GWAS to Function: Using Functional Genomics to Identify the Mechanisms Underlying Complex Diseases.

Authors:  Eddie Cano-Gamez; Gosia Trynka
Journal:  Front Genet       Date:  2020-05-13       Impact factor: 4.599

8.  Fast and accurate short read alignment with Burrows-Wheeler transform.

Authors:  Heng Li; Richard Durbin
Journal:  Bioinformatics       Date:  2009-05-18       Impact factor: 6.937

9.  Genomic variation in 3,010 diverse accessions of Asian cultivated rice.

Authors:  Wensheng Wang; Ramil Mauleon; Zhiqiang Hu; Dmytro Chebotarov; Shuaishuai Tai; Zhichao Wu; Min Li; Tianqing Zheng; Roven Rommel Fuentes; Fan Zhang; Locedie Mansueto; Dario Copetti; Millicent Sanciangco; Kevin Christian Palis; Jianlong Xu; Chen Sun; Binying Fu; Hongliang Zhang; Yongming Gao; Xiuqin Zhao; Fei Shen; Xiao Cui; Hong Yu; Zichao Li; Miaolin Chen; Jeffrey Detras; Yongli Zhou; Xinyuan Zhang; Yue Zhao; Dave Kudrna; Chunchao Wang; Rui Li; Ben Jia; Jinyuan Lu; Xianchang He; Zhaotong Dong; Jiabao Xu; Yanhong Li; Miao Wang; Jianxin Shi; Jing Li; Dabing Zhang; Seunghee Lee; Wushu Hu; Alexander Poliakov; Inna Dubchak; Victor Jun Ulat; Frances Nikki Borja; John Robert Mendoza; Jauhar Ali; Jing Li; Qiang Gao; Yongchao Niu; Zhen Yue; Ma Elizabeth B Naredo; Jayson Talag; Xueqiang Wang; Jinjie Li; Xiaodong Fang; Ye Yin; Jean-Christophe Glaszmann; Jianwei Zhang; Jiayang Li; Ruaraidh Sackville Hamilton; Rod A Wing; Jue Ruan; Gengyun Zhang; Chaochun Wei; Nickolai Alexandrov; Kenneth L McNally; Zhikang Li; Hei Leung
Journal:  Nature       Date:  2018-04-25       Impact factor: 49.962

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