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      Potential of rice landraces with strong culms as genetic resources for improving lodging resistance against super typhoons

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          Abstract

          It is generally believed that rice landraces with long culms are susceptible to lodging, and have not been utilized for breeding to improve lodging resistance. However, little is known about the structural culm strength of landraces and their beneficial genetic loci. Therefore, in this study, genome-wide association studies (GWAS) were performed using a rice population panel including Japanese rice landraces to identify beneficial loci associated with strong culms. As a result, the landraces were found to have higher structural culm strength and greater diversity than the breeding varieties. Genetic loci associated with strong culms were identified, and it was demonstrated that haplotypes with positive effects of those loci were present in a high proportion of these landraces. These results indicated that the utilization of the strong culm-associated loci present in Japanese rice landraces may further improve the lodging resistance of modern breeding varieties that have relied on semi-dwarfism.

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          A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3.

          We describe a new computer program, SnpEff, for rapidly categorizing the effects of variants in genome sequences. Once a genome is sequenced, SnpEff annotates variants based on their genomic locations and predicts coding effects. Annotated genomic locations include intronic, untranslated region, upstream, downstream, splice site, or intergenic regions. Coding effects such as synonymous or non-synonymous amino acid replacement, start codon gains or losses, stop codon gains or losses, or frame shifts can be predicted. Here the use of SnpEff is illustrated by annotating ~356,660 candidate SNPs in ~117 Mb unique sequences, representing a substitution rate of ~1/305 nucleotides, between the Drosophila melanogaster w(1118); iso-2; iso-3 strain and the reference y(1); cn(1) bw(1) sp(1) strain. We show that ~15,842 SNPs are synonymous and ~4,467 SNPs are non-synonymous (N/S ~0.28). The remaining SNPs are in other categories, such as stop codon gains (38 SNPs), stop codon losses (8 SNPs), and start codon gains (297 SNPs) in the 5'UTR. We found, as expected, that the SNP frequency is proportional to the recombination frequency (i.e., highest in the middle of chromosome arms). We also found that start-gain or stop-lost SNPs in Drosophila melanogaster often result in additions of N-terminal or C-terminal amino acids that are conserved in other Drosophila species. It appears that the 5' and 3' UTRs are reservoirs for genetic variations that changes the termini of proteins during evolution of the Drosophila genus. As genome sequencing is becoming inexpensive and routine, SnpEff enables rapid analyses of whole-genome sequencing data to be performed by an individual laboratory.
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            A framework for variation discovery and genotyping using next-generation DNA sequencing data

            Recent advances in sequencing technology make it possible to comprehensively catalogue genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (1) initial read mapping; (2) local realignment around indels; (3) base quality score recalibration; (4) SNP discovery and genotyping to find all potential variants; and (5) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We discuss the application of these tools, instantiated in the Genome Analysis Toolkit (GATK), to deep whole-genome, whole-exome capture, and multi-sample low-pass (~4×) 1000 Genomes Project datasets.
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              Food security: the challenge of feeding 9 billion people.

              Continuing population and consumption growth will mean that the global demand for food will increase for at least another 40 years. Growing competition for land, water, and energy, in addition to the overexploitation of fisheries, will affect our ability to produce food, as will the urgent requirement to reduce the impact of the food system on the environment. The effects of climate change are a further threat. But the world can produce more food and can ensure that it is used more efficiently and equitably. A multifaceted and linked global strategy is needed to ensure sustainable and equitable food security, different components of which are explored here.
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                Author and article information

                Contributors
                ookawa@cc.tuat.ac.jp
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                4 August 2021
                4 August 2021
                2021
                : 11
                : 15780
                Affiliations
                [1 ]GRID grid.136594.c, Graduate School of Agriculture, , Tokyo University of Agriculture and Technology, ; 3-5-8 Saiwai-cho, Fuchu, Tokyo 183-8509 Japan
                [2 ]GRID grid.27476.30, ISNI 0000 0001 0943 978X, Bioscience and Biotechnology Center, , Nagoya University, ; Furo-cho, Chikusa, Nagoya 464-8601 Japan
                [3 ]GRID grid.509456.b, Statistical Genetics Team, , RIKEN Center for Advanced Intelligence Project, ; Nihonbashi 1-chome Mitsui Building, 15th floor, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027 Japan
                [4 ]GRID grid.410773.6, ISNI 0000 0000 9949 0476, College of Agriculture, , Ibaraki University, ; 3-21-1 Chuo, Ami, Inashiki, Ibaraki 300-0393 Japan
                [5 ]GRID grid.433436.5, ISNI 0000 0001 2289 885X, Global Wheat Program, , International Maize and Wheat Improvement Center (CIMMYT), ; Texcoco, Mexico 56237 Mexico
                Article
                95268
                10.1038/s41598-021-95268-0
                8339031
                34349177
                79a62a9e-cdc4-47b7-aeb8-6e385220c217
                © The Author(s) 2021

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 12 May 2021
                : 16 July 2021
                Funding
                Funded by: JSPS Grant-in-Aid for JSPS Fellows
                Award ID: 20J13277
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                genetics,plant sciences
                Uncategorized
                genetics, plant sciences

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