Literature DB >> 20234878

Association mapping of stigma and spikelet characteristics in rice (Oryza sativa L.).

Wen Gui Yan, Yong Li, Hesham A Agrama, Dagang Luo, Fangyuan Gao, Xianjun Lu, Guangjun Ren.   

Abstract

Stigma and spikelet characteristics play an essential role in hybrid seed production. A mini-core of 90 accessions developed from USDA rice core collection was phenotyped in field grown for nine traits of stigma and spikelet and genotyped with 109 DNA markers, 108 SSRs plus an indel. Three major clusters were built upon Rogers' genetic distance, indicative of indicas, and temperate and tropical japonicas. A mixed linear model combining PC-matrix and K-matrix was adapted for mapping marker-trait associations. Resulting associations were adjusted using false discovery rate technique. We identified 34 marker-trait associations involving 22 SSR markers for eight traits. Four markers were associated with single stigma exsertion (SStgE), six with dual exsertion (DStgE) and five with total exsertion. RM5_Chr1 played major role indicative of high regression with not only DStgE but also SStgE. Four markers were associated with spikelet length, three with width and seven with L/W ratio. Numerous markers were co-associated with multiple traits that were phenotypically correlated, i.e. RM12521_Chr2 associated with all three correlated spikelet traits. The co-association should improve breeding efficiency because single marker could be used to assist breeding for multiple traits. Indica entry 1032 (cultivar 50638) and japonica entry 671 (cultivar Linia 84 Icar) with 80.65 and 75.17% of TStgE, respectively are recommended to breeder for improving stigma exsertion. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11032-009-9290-y) contains supplementary material, which is available to authorized users.

Entities:  

Year:  2009        PMID: 20234878      PMCID: PMC2837221          DOI: 10.1007/s11032-009-9290-y

Source DB:  PubMed          Journal:  Mol Breed        ISSN: 1380-3743            Impact factor:   2.589


  16 in total

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Authors:  Anat Reiner; Daniel Yekutieli; Yoav Benjamini
Journal:  Bioinformatics       Date:  2003-02-12       Impact factor: 6.937

Review 2.  The complex interplay among factors that influence allelic association.

Authors:  Krina T Zondervan; Lon R Cardon
Journal:  Nat Rev Genet       Date:  2004-02       Impact factor: 53.242

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

Review 5.  Linkage disequilibrium in humans: models and data.

Authors:  J K Pritchard; M Przeworski
Journal:  Am J Hum Genet       Date:  2001-06-14       Impact factor: 11.025

6.  Genetic structure and diversity in Oryza sativa L.

Authors:  Amanda J Garris; Thomas H Tai; Jason Coburn; Steve Kresovich; Susan McCouch
Journal:  Genetics       Date:  2005-01-16       Impact factor: 4.562

7.  Marker-assisted selection and evaluation of the QTL for stigma exsertion under japonica rice genetic background.

Authors:  Maiko Miyata; Toshio Yamamoto; Toshiyuki Komori; Naoto Nitta
Journal:  Theor Appl Genet       Date:  2006-11-25       Impact factor: 5.699

8.  Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars.

Authors:  Flavio Breseghello; Mark E Sorrells
Journal:  Genetics       Date:  2005-08-03       Impact factor: 4.562

9.  Mapping QTLs influencing rice floral morphology using recombinant inbred lines derived from a cross between Oryza sativa L. and Oryza rufipogon Griff.

Authors:  Y Uga; Y Fukuta; H W Cai; H Iwata; R Ohsawa; H Morishima; T Fujimura
Journal:  Theor Appl Genet       Date:  2003-03-21       Impact factor: 5.699

10.  Population structure and eigenanalysis.

Authors:  Nick Patterson; Alkes L Price; David Reich
Journal:  PLoS Genet       Date:  2006-12       Impact factor: 5.917

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  38 in total

1.  Genotypic and phenotypic characterization of genetic differentiation and diversity in the USDA rice mini-core collection.

Authors:  Xiaobai Li; Wengui Yan; Hesham Agrama; Biaolin Hu; Limeng Jia; Melissa Jia; Aaron Jackson; Karen Moldenhauer; Anna McClung; Dianxing Wu
Journal:  Genetica       Date:  2010-11-16       Impact factor: 1.082

2.  Genetic diversity, population structure and association analysis in linseed (Linum usitatissimum L.).

Authors:  Neha Singh; Rajendra Kumar; Sujit Kumar; P K Singh; V K Yadav; S A Ranade; Hemant Kumar Yadav
Journal:  Physiol Mol Biol Plants       Date:  2017-01-04

3.  Population structure in a wheat core collection and genomic loci associated with yield under contrasting environments.

Authors:  Miroslav Zorić; Dejan Dodig; Borislav Kobiljski; Steve Quarrie; Jeremy Barnes
Journal:  Genetica       Date:  2012-09-12       Impact factor: 1.082

Review 4.  Hybrid breeding in autogamous cereals.

Authors:  Carl Friedrich Horst Longin; Jonathan Mühleisen; Hans Peter Maurer; Hongliang Zhang; Manje Gowda; Jochen Christoph Reif
Journal:  Theor Appl Genet       Date:  2012-08-24       Impact factor: 5.699

5.  Population structure and association mapping of yield contributing agronomic traits in foxtail millet.

Authors:  Sarika Gupta; Kajal Kumari; Mehanathan Muthamilarasan; Swarup Kumar Parida; Manoj Prasad
Journal:  Plant Cell Rep       Date:  2014-01-12       Impact factor: 4.570

6.  Metabolome-wide association studies for agronomic traits of rice.

Authors:  Julong Wei; Aiguo Wang; Ruidong Li; Han Qu; Zhenyu Jia
Journal:  Heredity (Edinb)       Date:  2017-12-11       Impact factor: 3.821

7.  Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism.

Authors:  Wei Chen; Yanqiang Gao; Weibo Xie; Liang Gong; Kai Lu; Wensheng Wang; Yang Li; Xianqing Liu; Hongyan Zhang; Huaxia Dong; Wan Zhang; Lejing Zhang; Sibin Yu; Gongwei Wang; Xingming Lian; Jie Luo
Journal:  Nat Genet       Date:  2014-06-08       Impact factor: 38.330

8.  Mapping QTLs for improving grain yield using the USDA rice mini-core collection.

Authors:  Xiaobai Li; Wengui Yan; Hesham Agrama; Limeng Jia; Xihong Shen; Aaron Jackson; Karen Moldenhauer; Kathleen Yeater; Anna McClung; Dianxing Wu
Journal:  Planta       Date:  2011-04-10       Impact factor: 4.116

9.  Genomic diversity and introgression in O. sativa reveal the impact of domestication and breeding on the rice genome.

Authors:  Keyan Zhao; Mark Wright; Jennifer Kimball; Georgia Eizenga; Anna McClung; Michael Kovach; Wricha Tyagi; Md Liakat Ali; Chih-Wei Tung; Andy Reynolds; Carlos D Bustamante; Susan R McCouch
Journal:  PLoS One       Date:  2010-05-24       Impact factor: 3.240

10.  Genetic diversity and association mapping of seed vigor in rice (Oryza sativa L.).

Authors:  Xiaojing Dang; Thu Giang Tran Thi; Guanshan Dong; Hui Wang; Wisdom Mawuli Edzesi; Delin Hong
Journal:  Planta       Date:  2014-03-26       Impact factor: 4.116

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