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      Open access resources for genome-wide association mapping in rice

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          Abstract

          Increasing food production is essential to meet the demands of a growing human population, with its rising income levels and nutritional expectations. To address the demand, plant breeders seek new sources of genetic variation to enhance the productivity, sustainability and resilience of crop varieties. Here we launch a high-resolution, open-access research platform to facilitate genome-wide association mapping in rice, a staple food crop. The platform provides an immortal collection of diverse germplasm, a high-density single-nucleotide polymorphism data set tailored for gene discovery, well-documented analytical strategies, and a suite of bioinformatics resources to facilitate biological interpretation. Using grain length, we demonstrate the power and resolution of our new high-density rice array, the accompanying genotypic data set, and an expanded diversity panel for detecting major and minor effect QTLs and subpopulation-specific alleles, with immediate implications for rice improvement.

          Abstract

          Understanding the link between genotype and phenotype can facilitate efforts by breeders to utilize natural variation and develop new crop varieties. Here the authors present a diverse germplasm collection, a high-density genotyping array and a set of bioinformatic tools to enable association mapping in rice.

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          Most cited references63

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

          Population stratification--allele frequency differences between cases and controls due to systematic ancestry differences-can cause spurious associations in disease studies. We describe a method that enables explicit detection and correction of population stratification on a genome-wide scale. Our method uses principal components analysis to explicitly model ancestry differences between cases and controls. The resulting correction is specific to a candidate marker's variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. Our simple, efficient approach can easily be applied to disease studies with hundreds of thousands of markers.
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            A draft sequence of the rice genome (Oryza sativa L. ssp. indica).

            J. Yu (2002)
            We have produced a draft sequence of the rice genome for the most widely cultivated subspecies in China, Oryza sativa L. ssp. indica, by whole-genome shotgun sequencing. The genome was 466 megabases in size, with an estimated 46,022 to 55,615 genes. Functional coverage in the assembled sequences was 92.0%. About 42.2% of the genome was in exact 20-nucleotide oligomer repeats, and most of the transposons were in the intergenic regions between genes. Although 80.6% of predicted Arabidopsis thaliana genes had a homolog in rice, only 49.4% of predicted rice genes had a homolog in A. thaliana. The large proportion of rice genes with no recognizable homologs is due to a gradient in the GC content of rice coding sequences.
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              A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase.

              Grain weight is one of the most important components of grain yield and is controlled by quantitative trait loci (QTLs) derived from natural variations in crops. However, the molecular roles of QTLs in the regulation of grain weight have not been fully elucidated. Here, we report the cloning and characterization of GW2, a new QTL that controls rice grain width and weight. Our data show that GW2 encodes a previously unknown RING-type protein with E3 ubiquitin ligase activity, which is known to function in the degradation by the ubiquitin-proteasome pathway. Loss of GW2 function increased cell numbers, resulting in a larger (wider) spikelet hull, and it accelerated the grain milk filling rate, resulting in enhanced grain width, weight and yield. Our results suggest that GW2 negatively regulates cell division by targeting its substrate(s) to proteasomes for regulated proteolysis. The functional characterization of GW2 provides insight into the mechanism of seed development and is a potential tool for improving grain yield in crops.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group
                2041-1723
                04 February 2016
                2016
                : 7
                : 10532
                Affiliations
                [1 ]School of Integrative Plant Sciences, Plant Breeding and Genetics section, Cornell University , Ithaca, 14850 New York, USA
                [2 ]Department of Biological Statistics and Computational Biology, Cornell University , Ithaca, 14850 New York, USA
                [3 ]International Rice Research Institute , DAPO Box 7777, 1301 Metro Manila, Philippines
                [4 ]School of Food Science, University of Queensland , St Lucia, 4072 Queensland, Australia
                [5 ]Transnational Learning Center, Cornell University , Ithaca, 14850 New York, USA
                [6 ]National Institute of Agrobiological Sciences , 2-1-2 Kannondai, Tsukuba, 305-8602 Ibaraki, Japan
                [7 ]USDA–ARS Dale Bumpers National Rice Research Center , 2890 Hwy. 130 E., Stuttgart, Arkansas 72160, USA
                Author notes
                [*]

                These authors contributed equally to this work

                [†]

                Present address: Department of Genetics, Stanford School of Medicine, Stanford, California 94305, USA

                [‡]

                Present address: Department of Agronomy, National Taiwan University, 106 Taipei, Taiwan

                [§]

                Present address: Mann Library, Cornell University, Ithaca, New York 14850, USA

                [∥]

                Present address: Embrapa Agriculture Informatics, 13083-886 Campinas, Brazil.

                Article
                ncomms10532
                10.1038/ncomms10532
                4742900
                26842267
                95624598-15d2-479b-8b40-07e3d75ec602
                Copyright © 2016, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 04 March 2015
                : 22 December 2015
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