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PLoS One. 2015 Apr 29;10(4):e0124617. doi: 10.1371/journal.pone.0124617. eCollection 2015.

Whole genome sequencing of elite rice cultivars as a comprehensive information resource for marker assisted selection.

Author information

1
Agrobiodiversity research area, International Center for Tropical Agriculture, Cali, Colombia.
2
Rice Research Station, Louisiana State University Agricultural Center, Rayne, Louisiana, United States of America.
3
Agrobiodiversity research area, International Center for Tropical Agriculture, Cali, Colombia; Plant Diversity Adaptation and Development Research Unit, Institut de Recherche pour le Développement, Montpellier, France.
4
Genomics and Bioinformatics Research Unit, Agricultural Research Service, United States Department of Agriculture, Jamie Whitten Delta States Research Center, Stoneville, Mississippi, United States of America.
5
National Center for Genome Resources, Santa Fe, New Mexico, United States of America.

Abstract

Current advances in sequencing technologies and bioinformatics revealed the genomic background of rice, a staple food for the poor people, and provided the basis to develop large genomic variation databases for thousands of cultivars. Proper analysis of this massive resource is expected to give novel insights into the structure, function, and evolution of the rice genome, and to aid the development of rice varieties through marker assisted selection or genomic selection. In this work we present sequencing and bioinformatics analyses of 104 rice varieties belonging to the major subspecies of Oryza sativa. We identified repetitive elements and recurrent copy number variation covering about 200 Mbp of the rice genome. Genotyping of over 18 million polymorphic locations within O. sativa allowed us to reconstruct the individual haplotype patterns shaping the genomic background of elite varieties used by farmers throughout the Americas. Based on a reconstruction of the alleles for the gene GBSSI, we could identify novel genetic markers for selection of varieties with high amylose content. We expect that both the analysis methods and the genomic information described here would be of great use for the rice research community and for other groups carrying on similar sequencing efforts in other crops.

PMID:
25923345
PMCID:
PMC4414565
DOI:
10.1371/journal.pone.0124617
[Indexed for MEDLINE]
Free PMC Article

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