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      SNP-Seek database of SNPs derived from 3000 rice genomes

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          Abstract

          We have identified about 20 million rice SNPs by aligning reads from the 3000 rice genomes project with the Nipponbare genome. The SNPs and allele information are organized into a SNP-Seek system ( http://www.oryzasnp.org/iric-portal/), which consists of Oracle database having a total number of rows with SNP genotypes close to 60 billion (20 M SNPs × 3 K rice lines) and web interface for convenient querying. The database allows quick retrieving of SNP alleles for all varieties in a given genome region, finding different alleles from predefined varieties and querying basic passport and morphological phenotypic information about sequenced rice lines. SNPs can be visualized together with the gene structures in JBrowse genome browser. Evolutionary relationships between rice varieties can be explored using phylogenetic trees or multidimensional scaling plots.

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          Yield Trends Are Insufficient to Double Global Crop Production by 2050

          Deepak Ray, Nathaniel D. Mueller, Paul C West … (2013)
          Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops—maize, rice, wheat, and soybean—that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands.
          Article 0 comments Cited 922 times – based on 0 reviews     Review now
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            Genetic engineering and breeding of drought-resistant crops.

            Honghong Hu, Lizhong Xiong (2014)
            Drought is one of the most important environmental stresses affecting the productivity of most field crops. Elucidation of the complex mechanisms underlying drought resistance in crops will accelerate the development of new varieties with enhanced drought resistance. Here, we provide a brief review on the progress in genetic, genomic, and molecular studies of drought resistance in major crops. Drought resistance is regulated by numerous small-effect loci and hundreds of genes that control various morphological and physiological responses to drought. This review focuses on recent studies of genes that have been well characterized as affecting drought resistance and genes that have been successfully engineered in staple crops. We propose that one significant challenge will be to unravel the complex mechanisms of drought resistance in crops through more intensive and integrative studies in order to find key functional components or machineries that can be used as tools for engineering and breeding drought-resistant crops.
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              The genes of the Green Revolution.

              Peter Hedden (2002)
              The spectacular increases in wheat and rice yields during the 'Green Revolution', were enabled by the introduction of dwarfing traits into the plants. Now, identification of the genes responsible for these traits shows that they interfere with the action or production of the gibberellin (GA) plant hormones. We knew that the wheat Rht genes encode growth repressors that are normally suppressed by GA, and recent work shows that the rice sd1 gene encodes a defective enzyme in the GA-biosynthetic pathway.
              Article 0 comments Cited 156 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (hwp): nar
                Journal ID (publisher-id): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date (Print): 28 January 2015
                Publication date (Electronic): 27 November 2014
                Publication date PMC-release: 27 November 2014
                Volume: 43
                Issue: Database issue , Database issue
                Pages: D1023-D1027
                Affiliations
                [1 ]T.T.Chang Genetic Resources Center, IRRI, Los Baños, Laguna 4031, Philippines
                [2 ]BGI, Shenzhen 518083, China
                [3 ]Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, 100081
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +63 2 580-5600; Fax: +63 2 580-5699; Email: n.alexandrov@ 123456irri.org
                Correspondence may also be addressed to Gengyun Zhang. Enail: zhanggengyun@ 123456genomics.cn
                Correspondence may also be addressed to Zhikang Li. Email: lizhikang@ 123456caas.cn
                Article
                DOI: 10.1093/nar/gku1039
                PMC ID: 4383887
                PubMed ID: 25429973
                SO-VID: dfeb6cfd-b059-4b54-8799-8f02f3d4bae4
                Copyright © © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date accepted : 10 October 2014
                Date revision received : 10 October 2014
                Date received : 08 September 2014
                Page count
                Pages: 5
                Categories
                Subject: Database Issue
                Custom metadata
                cover-date 28 January 2015

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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