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      Emerging Genomic Tools for Legume Breeding: Current Status and Future Prospects

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          Abstract

          Legumes play a vital role in ensuring global nutritional food security and improving soil quality through nitrogen fixation. Accelerated higher genetic gains is required to meet the demand of ever increasing global population. In recent years, speedy developments have been witnessed in legume genomics due to advancements in next-generation sequencing (NGS) and high-throughput genotyping technologies. Reference genome sequences for many legume crops have been reported in the last 5 years. The availability of the draft genome sequences and re-sequencing of elite genotypes for several important legume crops have made it possible to identify structural variations at large scale. Availability of large-scale genomic resources and low-cost and high-throughput genotyping technologies are enhancing the efficiency and resolution of genetic mapping and marker-trait association studies. Most importantly, deployment of molecular breeding approaches has resulted in development of improved lines in some legume crops such as chickpea and groundnut. In order to support genomics-driven crop improvement at a fast pace, the deployment of breeder-friendly genomics and decision support tools seems appear to be critical in breeding programs in developing countries. This review provides an overview of emerging genomics and informatics tools/approaches that will be the key driving force for accelerating genomics-assisted breeding and ultimately ensuring nutritional and food security in developing countries.

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          Yield Trends Are Insufficient to Double Global Crop Production by 2050

          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.
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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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              QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations.

              The majority of agronomically important crop traits are quantitative, meaning that they are controlled by multiple genes each with a small effect (quantitative trait loci, QTLs). Mapping and isolation of QTLs is important for efficient crop breeding by marker-assisted selection (MAS) and for a better understanding of the molecular mechanisms underlying the traits. However, since it requires the development and selection of DNA markers for linkage analysis, QTL analysis has been time-consuming and labor-intensive. Here we report the rapid identification of plant QTLs by whole-genome resequencing of DNAs from two populations each composed of 20-50 individuals showing extreme opposite trait values for a given phenotype in a segregating progeny. We propose to name this approach QTL-seq as applied to plant species. We applied QTL-seq to rice recombinant inbred lines and F2 populations and successfully identified QTLs for important agronomic traits, such as partial resistance to the fungal rice blast disease and seedling vigor. Simulation study showed that QTL-seq is able to detect QTLs over wide ranges of experimental variables, and the method can be generally applied in population genomics studies to rapidly identify genomic regions that underwent artificial or natural selective sweeps. © 2013 The Authors The Plant Journal © 2013 Blackwell Publishing Ltd.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                02 May 2016
                2016
                : 7
                : 455
                Affiliations
                [1] 1International Crops Research Institute for the Semi-Arid Tropics Hyderabad, India
                [2] 2The University of Western Australia Crawley, WA, Australia
                Author notes

                Edited by: Paul Gepts, University of California, Davis, USA

                Reviewed by: Ramanjulu Sunkar, Oklahoma State University, USA; Swarup Kumar Parida, National Institute of Plant Genome Research, India

                *Correspondence: Rajeev K. Varshney, r.k.varshney@ 123456cgiar.org ; Manish K. Pandey, m.pandey@ 123456cgiar.org

                These authors have contributed equally to this work.

                This article was submitted to Plant Genetics and Genomics, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2016.00455
                4852475
                27199998
                c84c31ee-6bc3-4a4f-88fd-e5ed2cb3f3ca
                Copyright © 2016 Pandey, Roorkiwal, Singh, Ramalingam, Kudapa, Thudi, Chitikineni, Rathore and Varshney.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 24 November 2015
                : 24 March 2016
                Page count
                Figures: 1, Tables: 0, Equations: 0, References: 168, Pages: 18, Words: 0
                Categories
                Plant Science
                Review

                Plant science & Botany
                trait mapping,gene discovery,genomics-assisted breeding,high-throughput genotyping,next-generation sequencing

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