Literature DB >> 24413764

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

Sarika Gupta1, Kajal Kumari, Mehanathan Muthamilarasan, Swarup Kumar Parida, Manoj Prasad.   

Abstract

Association analyses accounting for population structure and relative kinship identified eight SSR markers ( p < 0.01) showing significant association ( R (2) = 18 %) with nine agronomic traits in foxtail millet. Association mapping is an efficient tool for identifying genes regulating complex traits. Although association mapping using genomic simple sequence repeat (SSR) markers has been successfully demonstrated in many agronomically important crops, very few reports are available on marker-trait association analysis in foxtail millet. In the present study, 184 foxtail millet accessions from diverse geographical locations were genotyped using 50 SSR markers representing the nine chromosomes of foxtail millet. The genetic diversity within these accessions was examined using a genetic distance-based and a general model-based clustering method. The model-based analysis using 50 SSR markers identified an underlying population structure comprising five sub-populations which corresponded well with distance-based groupings. The phenotyping of plants was carried out in the field for three consecutive years for 20 yield contributing agronomic traits. The linkage disequilibrium analysis considering population structure and relative kinship identified eight SSR markers (p < 0.01) on different chromosomes showing significant association (R (2) = 18 %) with nine agronomic traits. Four of these markers were associated with multiple traits. The integration of genetic and physical map information of eight SSR markers with their functional annotation revealed strong association of two markers encoding for phospholipid acyltransferase and ubiquitin carboxyl-terminal hydrolase located on the same chromosome (5) with flag leaf width and grain yield, respectively. Our findings on association mapping is the first report on Indian foxtail millet germplasm and this could be effectively applied in foxtail millet breeding to further uncover marker-trait associations with a large number of markers.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 24413764     DOI: 10.1007/s00299-014-1564-0

Source DB:  PubMed          Journal:  Plant Cell Rep        ISSN: 0721-7714            Impact factor:   4.570


  47 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

Review 2.  Estimating F-statistics.

Authors:  B S Weir; W G Hill
Journal:  Annu Rev Genet       Date:  2002-06-11       Impact factor: 16.830

3.  Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies.

Authors:  Daniel Falush; Matthew Stephens; Jonathan K Pritchard
Journal:  Genetics       Date:  2003-08       Impact factor: 4.562

Review 4.  Genetic association mapping and genome organization of maize.

Authors:  Jianming Yu; Edward S Buckler
Journal:  Curr Opin Biotechnol       Date:  2006-02-28       Impact factor: 9.740

5.  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 6.  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

7.  Association mapping of yellow pigment in an elite collection of durum wheat cultivars and breeding lines.

Authors:  S Reimer; C J Pozniak; F R Clarke; J M Clarke; D J Somers; R E Knox; A K Singh
Journal:  Genome       Date:  2008-12       Impact factor: 2.166

8.  Development of eSSR-Markers in Setaria italica and Their Applicability in Studying Genetic Diversity, Cross-Transferability and Comparative Mapping in Millet and Non-Millet Species.

Authors:  Kajal Kumari; Mehanathan Muthamilarasan; Gopal Misra; Sarika Gupta; Alagesan Subramanian; Swarup Kumar Parida; Debasis Chattopadhyay; Manoj Prasad
Journal:  PLoS One       Date:  2013-06-21       Impact factor: 3.240

9.  Genetic diversity and population structure of Chinese foxtail millet [Setaria italica (L.) Beauv.] landraces.

Authors:  Chunfang Wang; Guanqing Jia; Hui Zhi; Zhengang Niu; Yang Chai; Wei Li; Yongfang Wang; Haiquan Li; Ping Lu; Baohua Zhao; Xianmin Diao
Journal:  G3 (Bethesda)       Date:  2012-07-01       Impact factor: 3.154

10.  Development of Simple Sequence Repeats (SSR) markers in Setaria italica (Poaceae) and cross-amplification in related species.

Authors:  Heng-Sheng Lin; Chih-Yun Chiang; Song-Bin Chang; Chang-Sheng Kuoh
Journal:  Int J Mol Sci       Date:  2011-11-11       Impact factor: 5.923

View more
  24 in total

1.  C2H2 type of zinc finger transcription factors in foxtail millet define response to abiotic stresses.

Authors:  Mehanathan Muthamilarasan; Venkata Suresh Bonthala; Awdhesh Kumar Mishra; Rohit Khandelwal; Yusuf Khan; Riti Roy; Manoj Prasad
Journal:  Funct Integr Genomics       Date:  2014-06-11       Impact factor: 3.410

2.  Identification of QTLs for 14 Agronomically Important Traits in Setaria italica Based on SNPs Generated from High-Throughput Sequencing.

Authors:  Kai Zhang; Guangyu Fan; Xinxin Zhang; Fang Zhao; Wei Wei; Guohua Du; Xiaolei Feng; Xiaoming Wang; Feng Wang; Guoliang Song; Hongfeng Zou; Xiaolei Zhang; Shuangdong Li; Xuemei Ni; Gengyun Zhang; Zhihai Zhao
Journal:  G3 (Bethesda)       Date:  2017-05-05       Impact factor: 3.154

3.  Analysis of spatial distribution of genetic diversity and validation of Indian foxtail millet core collection.

Authors:  Subhash Chander; K V Bhat; Ratna Kumari; Sanjay Sen; A B Gaikwad; M V C Gowda; N Dikshit
Journal:  Physiol Mol Biol Plants       Date:  2017-05-18

Review 4.  Advances in Setaria genomics for genetic improvement of cereals and bioenergy grasses.

Authors:  Mehanathan Muthamilarasan; Manoj Prasad
Journal:  Theor Appl Genet       Date:  2014-09-20       Impact factor: 5.699

Review 5.  Genetic diversity and genomic resources available for the small millet crops to accelerate a New Green Revolution.

Authors:  Travis L Goron; Manish N Raizada
Journal:  Front Plant Sci       Date:  2015-03-24       Impact factor: 5.753

6.  Microsatellite Variations of Elite Setaria Varieties Released during Last Six Decades in China.

Authors:  Guanqing Jia; Xiaotong Liu; James C Schnable; Zhengang Niu; Chunfang Wang; Yuhui Li; Shujun Wang; Suying Wang; Jinrong Liu; Erhu Guo; Hui Zhi; Xianmin Diao
Journal:  PLoS One       Date:  2015-05-01       Impact factor: 3.240

7.  Tracing QTLs for Leaf Blast Resistance and Agronomic Performance of Finger Millet (Eleusine coracana (L.) Gaertn.) Genotypes through Association Mapping and in silico Comparative Genomics Analyses.

Authors:  M Ramakrishnan; S Antony Ceasar; V Duraipandiyan; K K Vinod; Krishnan Kalpana; N A Al-Dhabi; S Ignacimuthu
Journal:  PLoS One       Date:  2016-07-14       Impact factor: 3.240

8.  Identification of QTL related to anther color and hull color by RAD sequencing in a RIL population of Setaria italica.

Authors:  Huifang Xie; Junliang Hou; Nan Fu; Menghan Wei; Yunfei Li; Kang Yu; Hui Song; Shiming Li; Jinrong Liu
Journal:  BMC Genomics       Date:  2021-07-20       Impact factor: 3.969

9.  A high density genetic map and QTL for agronomic and yield traits in Foxtail millet [Setaria italica (L.) P. Beauv].

Authors:  Xiaomei Fang; Kongjun Dong; Xiaoqin Wang; Tianpeng Liu; Jihong He; Ruiyu Ren; Lei Zhang; Rui Liu; Xueying Liu; Man Li; Mengzhu Huang; Zhengsheng Zhang; Tianyu Yang
Journal:  BMC Genomics       Date:  2016-05-04       Impact factor: 3.969

10.  Molecular Approaches to Understand Nutritional Potential of Coarse Cereals.

Authors:  Amit Kumar Singh; Rakesh Singh; Rajkumar Subramani; Rajesh Kumar; Dhammaprakash P Wankhede
Journal:  Curr Genomics       Date:  2016-06       Impact factor: 2.236

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.