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      Deciphering the genetic basis of root morphology, nutrient uptake, yield, and yield-related traits in rice under dry direct-seeded cultivation systems

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          Abstract

          In the face of global water scarcity, a successful transition of rice cultivation from puddled to dry direct-seeded rice (DDSR) is a future need. A genome-wide association study was performed on a complex mapping population for 39 traits: 9 seedling-establishment traits, 14 root and nutrient-uptake traits, 5 plant morphological traits, 4 lodging resistance traits, and 7 yield and yield-contributing traits. A total of 10 significant marker-trait associations (MTAs) were found along with 25 QTLs associated with 25 traits. The percent phenotypic variance explained by SNPs ranged from 8% to 84%. Grain yield was found to be significantly and positively correlated with seedling-establishment traits, root morphological traits, nutrient uptake-related traits, and grain yield-contributing traits. The genomic colocation of different root morphological traits, nutrient uptake-related traits, and grain-yield-contributing traits further supports the role of root morphological traits in improving nutrient uptake and grain yield under DDSR. The QTLs/candidate genes underlying the significant MTAs were identified. The identified promising progenies carrying these QTLs may serve as potential donors to be exploited in genomics-assisted breeding programs for improving grain yield and adaptability under DDSR.

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          Most cited references 81

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          A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences.

           Motoo Kimura (1980)
          Some simple formulae were obtained which enable us to estimate evolutionary distances in terms of the number of nucleotide substitutions (and, also, the evolutionary rates when the divergence times are known). In comparing a pair of nucleotide sequences, we distinguish two types of differences; if homologous sites are occupied by different nucleotide bases but both are purines or both pyrimidines, the difference is called type I (or "transition" type), while, if one of the two is a purine and the other is a pyrimidine, the difference is called type II (or "transversion" type). Letting P and Q be respectively the fractions of nucleotide sites showing type I and type II differences between two sequences compared, then the evolutionary distance per site is K = -(1/2) ln [(1-2P-Q) square root of 1-2Q]. The evolutionary rate per year is then given by k = K/(2T), where T is the time since the divergence of the two sequences. If only the third codon positions are compared, the synonymous component of the evolutionary base substitutions per site is estimated by K'S = -(1/2) ln (1-2P-Q). Also, formulae for standard errors were obtained. Some examples were worked out using reported globin sequences to show that synonymous substitutions occur at much higher rates than amino acid-altering substitutions in evolution.
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            TASSEL: software for association mapping of complex traits in diverse samples.

            Association analyses that exploit the natural diversity of a genome to map at very high resolutions are becoming increasingly important. In most studies, however, researchers must contend with the confounding effects of both population and family structure. TASSEL (Trait Analysis by aSSociation, Evolution and Linkage) implements general linear model and mixed linear model approaches for controlling population and family structure. For result interpretation, the program allows for linkage disequilibrium statistics to be calculated and visualized graphically. Database browsing and data importation is facilitated by integrated middleware. Other features include analyzing insertions/deletions, calculating diversity statistics, integration of phenotypic and genotypic data, imputing missing data and calculating principal components.
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              Genome-wide association studies of 14 agronomic traits in rice landraces.

              Uncovering the genetic basis of agronomic traits in crop landraces that have adapted to various agro-climatic conditions is important to world food security. Here we have identified ∼ 3.6 million SNPs by sequencing 517 rice landraces and constructed a high-density haplotype map of the rice genome using a novel data-imputation method. We performed genome-wide association studies (GWAS) for 14 agronomic traits in the population of Oryza sativa indica subspecies. The loci identified through GWAS explained ∼ 36% of the phenotypic variance, on average. The peak signals at six loci were tied closely to previously identified genes. This study provides a fundamental resource for rice genetics research and breeding, and demonstrates that an approach integrating second-generation genome sequencing and GWAS can be used as a powerful complementary strategy to classical biparental cross-mapping for dissecting complex traits in rice.
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                Author and article information

                Contributors
                a.kumar@irri.org
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 June 2019
                27 June 2019
                2019
                : 9
                Affiliations
                [1 ]ISNI 0000 0001 0729 330X, GRID grid.419387.0, Rice Breeding Platform, , International Rice Research Institute, ; Metro Manila, Philippines
                [2 ]ISNI 0000 0000 9323 1772, GRID grid.419337.b, International Rice Research Institute, , South Asia Hub, ICRISAT, ; Patancheru, Hyderabad India
                [3 ]ISNI 0000 0000 9323 1772, GRID grid.419337.b, Center of Excellence in Genomics and System Biology, , International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), ; Patancheru Hyderabad, India
                [4 ]ICAR Research Complex for Eastern Region, Patna, Bihar India
                [5 ]ISNI 0000 0004 1787 6463, GRID grid.418317.8, Bihar Agricultural University, ; Sabour, Bhagalpur, Bihar India
                [6 ]GRID grid.460993.1, Agriculture and Forestry University, ; Rampur, Chitwan Nepal
                [7 ]National Rice Research Program, Hardinath, Nepal
                [8 ]ISNI 0000 0001 2176 2352, GRID grid.412577.2, Punjab Agricultural University, ; Ludhiana, India
                Article
                45770
                10.1038/s41598-019-45770-3
                6597570
                31249338
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                Funding
                Funded by: FundRef https://doi.org/10.13039/100004425, Asian Development Bank (ADB);
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                © The Author(s) 2019

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                genome-wide association studies, genomics

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