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      Correction: Genomewide Association Studies for 50 Agronomic Traits in Peanut Using the ‘Reference Set’ Comprising 300 Genotypes from 48 Countries of the Semi-Arid Tropics of the World

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          Abstract

          The legends for Figures 3 and 4 are incorrectly switched. The legend that appears for Figure 3 should be the legend for Figure 4, and the legend that appears for Figure 4 should be the legend for Figure 3. The figures appear in the correct order. Please view Figures 3 and 4 here. 10.1371/journal.pone.0105228.g003 Figure 3 Global distribution of genotypes containing linked-marker allele(s) for different economically important traits in peanut. An attempt has been made to show passport-based geographical distribution of genotypes that had favourable alleles for markers showing association and explaining >20% phenotypic variation for the trait. Genotypes containing favourable alleles for different traits have been represented by circles in different colors. 10.1371/journal.pone.0105228.g004 Figure 4 Genomewide distribution of trait-associated markers for different traits. Mapped SSR markers that showed trait association are represented on linkage groups (A01 to A10 and B01 to B10) while unmapped DArT features are assigned to A0 linkage group for representation.

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          Genomewide Association Studies for 50 Agronomic Traits in Peanut Using the ‘Reference Set’ Comprising 300 Genotypes from 48 Countries of the Semi-Arid Tropics of the World

          Peanut is an important and nutritious agricultural commodity and a livelihood of many small-holder farmers in the semi-arid tropics (SAT) of world which are facing serious production threats. Integration of genomics tools with on-going genetic improvement approaches is expected to facilitate accelerated development of improved cultivars. Therefore, high-resolution genotyping and multiple season phenotyping data for 50 important agronomic, disease and quality traits were generated on the ‘reference set’ of peanut. This study reports comprehensive analyses of allelic diversity, population structure, linkage disequilibrium (LD) decay and marker-trait association (MTA) in peanut. Distinctness of all the genotypes can be established by using either an unique allele detected by a single SSR or a combination of unique alleles by two or more than two SSR markers. As expected, DArT features (2.0 alleles/locus, 0.125 PIC) showed lower allele frequency and polymorphic information content (PIC) than SSRs (22.21 alleles /locus, 0.715 PIC). Both marker types clearly differentiated the genotypes of diploids from tetraploids. Multi-allelic SSRs identified three sub-groups (K = 3) while the LD simulation trend line based on squared-allele frequency correlations (r2) predicted LD decay of 15–20 cM in peanut genome. Detailed analysis identified a total of 524 highly significant MTAs (pvalue >2.1×10–6) with wide phenotypic variance (PV) range (5.81–90.09%) for 36 traits. These MTAs after validation may be deployed in improving biotic resistance, oil/ seed/ nutritional quality, drought tolerance related traits, and yield/ yield components.
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            Journal
            PLoS One
            PLoS ONE
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, USA )
            1932-6203
            2014
            6 November 2014
            : 9
            : 11
            : e113326
            Article
            PONE-D-14-48543
            10.1371/journal.pone.0113326
            4223048
            25375346
            9cbe7a17-27f9-45d7-a890-eecd4c4c4f0f
            Copyright @ 2014

            This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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