Literature DB >> 35939183

Genome wide association mapping of yield and various desirable agronomic traits in Rice.

Muhammad Ashfaq1, Abdul Rasheed2, Muhammad Sajjad3, Muhammad Ali4,5, Bilal Rasool6, Muhammad Arshad Javed2, Sami Ul Allah7, Shabnum Shaheen8, Alia Anwar2, Muhammad Shafiq Ahmad2, Urooj Mubashar9.   

Abstract

BACKGROUND: Rice (Oryza sativa L.) is one of the staple foods worldwide. To feed the growing population, the improvement of rice cultivars is important. To make the improvement in the rice breeding program, it is imperative to understand the similarities and differences of the existing rice accessions to find out the genetic diversity. Previous studies demonstrated the existence of abundant elite genes in rice landraces. A genome-wide association study (GWAS) was performed for yield and yield related traits to find the genetic diversity.
DESIGN: Experimental study. METHODS AND
RESULTS: A total of 204 SSRs markers were used among 17 SSRs found to be located on each chromosome in the rice genome. The diversity was analyzed using different genetic characters i.e., the total number of alleles (TNA), polymorphic information content (PIC), and gene diversity by Power markers, and the values for each genetic character per marker ranged from 2 to 9, 0.332 to 0.887 and 0.423 to 0.900 respectively across the whole genome. The results of population structure identified four main groups. MTA identified several markers associated with many agronomically important traits. These results will be very useful for the selection of potential parents, recombinants, and MTAs that govern the improvements and developments of new high yielding rice varieties.
CONCLUSIONS: Analysis of diversity in germplasm is important for the improvement of cultivars in the breeding program. In the present study, the diversity was analyzed with different methods and found that enormous diversity was present in the studied rice germplasm. The structure analysis found the presence of 4 genetic groups in the existing germplasm. A total of 129 marker-trait associations (MTAs) have been found in this study.
© 2022. The Author(s), under exclusive licence to Springer Nature B.V.

Entities:  

Keywords:  Agronomic traits; GWAS; Germplasm; PIC; QTLs; Rice; SSR

Year:  2022        PMID: 35939183     DOI: 10.1007/s11033-022-07687-5

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


  12 in total

1.  Linkage disequilibrium mapping of yield and yield stability in modern spring barley cultivars.

Authors:  Arnold T W Kraakman; Rients E Niks; Petra M M M Van den Berg; Piet Stam; Fred A Van Eeuwijk
Journal:  Genetics       Date:  2004-09       Impact factor: 4.562

2.  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

3.  A unified mixed-model method for association mapping that accounts for multiple levels of relatedness.

Authors:  Jianming Yu; Gael Pressoir; William H Briggs; Irie Vroh Bi; Masanori Yamasaki; John F Doebley; Michael D McMullen; Brandon S Gaut; Dahlia M Nielsen; James B Holland; Stephen Kresovich; Edward S Buckler
Journal:  Nat Genet       Date:  2005-12-25       Impact factor: 38.330

4.  Principal components analysis corrects for stratification in genome-wide association studies.

Authors:  Alkes L Price; Nick J Patterson; Robert M Plenge; Michael E Weinblatt; Nancy A Shadick; David Reich
Journal:  Nat Genet       Date:  2006-07-23       Impact factor: 38.330

5.  Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice.

Authors:  Kenji Yano; Eiji Yamamoto; Koichiro Aya; Hideyuki Takeuchi; Pei-Ching Lo; Li Hu; Masanori Yamasaki; Shinya Yoshida; Hidemi Kitano; Ko Hirano; Makoto Matsuoka
Journal:  Nat Genet       Date:  2016-06-20       Impact factor: 38.330

6.  Molecular genetic diversity of Punica granatum L. (pomegranate) as revealed by microsatellite DNA markers (SSR).

Authors:  Nejib Hasnaoui; Anna Buonamici; Federico Sebastiani; Messaoud Mars; Dapeng Zhang; Giovanni G Vendramin
Journal:  Gene       Date:  2011-11-20       Impact factor: 3.688

7.  Development and mapping of 2240 new SSR markers for rice (Oryza sativa L.).

Authors:  Susan R McCouch; Leonid Teytelman; Yunbi Xu; Katarzyna B Lobos; Karen Clare; Mark Walton; Binying Fu; Reycel Maghirang; Zhikang Li; Yongzhong Xing; Qifa Zhang; Izumi Kono; Masahiro Yano; Robert Fjellstrom; Genevieve DeClerck; David Schneider; Samuel Cartinhour; Doreen Ware; Lincoln Stein
Journal:  DNA Res       Date:  2002-12-31       Impact factor: 4.458

8.  Genetic linkage map of EST-SSR and SRAP markers in the endangered Chinese endemic herb Dendrobium (Orchidaceae).

Authors:  J J Lu; S Wang; H Y Zhao; J J Liu; H Z Wang
Journal:  Genet Mol Res       Date:  2012-12-21

9.  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

10.  Genetic diversity and population structure of the major peanut (Arachis hypogaea L.) cultivars grown in China by SSR markers.

Authors:  Xiaoping Ren; Huifang Jiang; Zhongyuan Yan; Yuning Chen; Xiaojing Zhou; Li Huang; Yong Lei; Jiaquan Huang; Liying Yan; Yue Qi; Wenhui Wei; Boshou Liao
Journal:  PLoS One       Date:  2014-02-10       Impact factor: 3.240

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