Record Details

Genome-wide generation and use of informative intron-spanning and intron-length polymorphism markers for high-throughput genetic analysis in rice

NIPGR Digital Knowledge Repository (NDKR)

View Archive Info
 
 
Field Value
 
Title Genome-wide generation and use of informative intron-spanning and intron-length polymorphism markers for high-throughput genetic analysis in rice
 
Creator Badoni, Saurabh
Das, Sweta
Sayal, Yogesh K.
Gopalakrishnan, S.
Singh, Ashok K.
Rao, Atmakuri R.
Agarwal, Pinky
Parida, Swarup K.
Tyagi, Akhilesh K.
 
Subject Genetic markers
Agricultural genetics
Genetic linkage study
 
Description Accepted date: 11 March 2016
We developed genome-wide 84634 ISM (intron-spanning marker) and 16510 InDel-fragment length polymorphism-based ILP (intron-length polymorphism) markers from genes physically mapped on 12 rice chromosomes. These genic markers revealed much higher amplification-efficiency (80%) and polymorphic-potential (66%) among rice accessions even by a cost-effective agarose gel-based assay. A wider level of functional molecular diversity (17–79%) and well-defined precise admixed genetic structure was assayed by 3052 genome-wide markers in a structured population of indica, japonica, aromatic and wild rice. Six major grain weight QTLs (11.9–21.6% phenotypic variation explained) were mapped on five rice chromosomes of a high-density (inter-marker distance: 0.98 cM) genetic linkage map (IR 64 x Sonasal) anchored with 2785 known/candidate gene-derived ISM and ILP markers. The designing of multiple ISM and ILP markers (2 to 4 markers/gene) in an individual gene will broaden the user-preference to select suitable primer combination for efficient assaying of functional allelic variation/diversity and realistic estimation of differential gene expression profiles among rice accessions. The genomic information generated in our study is made publicly accessible through a user-friendly web-resource, “Oryza ISM-ILP marker” database. The known/candidate gene-derived ISM and ILP markers can be enormously deployed to identify functionally relevant trait-associated molecular tags by optimal-resource expenses, leading towards genomics-assisted crop improvement in rice.
The authors gratefully acknowledge the financial support for this study provided by a research grant from
the Department of Biotechnology (DBT), Government of India (102/IFD/SAN/2161/2013-14). Sweta Das
acknowledges the University Grants Commission (UGC) for Senior Research Fellowship award.
 
Date 2016-04-04T09:09:42Z
2016-04-04T09:09:42Z
2016
 
Type Article
 
Identifier Scientific Reports, 6: 23765
2045-2322
http://172.16.0.77:8080/jspui/handle/123456789/632
http://www.nature.com/articles/srep23765
10.1038/srep23765
 
Language en_US
 
Publisher Nature Publishing Group