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      Differentiation, evolution and utilization of natural alleles for cold adaptability at the reproductive stage in rice

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          Abstract

          Genetic studies on cold tolerance at the reproductive stage in rice could lead to significant reductions in yield losses. However, knowledge about the genetic basis and adaptive differentiation, as well as the evolution and utilization of the underlying natural alleles, remains limited. Here, 580 rice accessions in two association panels were used to perform genome‐wide association study, and 156 loci associated with cold tolerance at the reproductive stage were identified. Os01g0923600 and Os01g0923800 were identified as promising candidate genes in qCTB1t, a major associated locus. Through population genetic analyses, 22 and 29 divergent regions controlling cold adaptive differentiation inter‐subspecies ( Xian/ Indica and Geng/ Japonica) and intra‐ Geng, respectively, were identified. Joint analyses of four cloned cold‐tolerance genes showed that they had different origins and utilizations under various climatic conditions. bZIP73 and OsAPX1 differentiating inter‐subspecies evolved directly from wild rice, whereas the novel mutations CTB4a and Ctb1 arose in Geng during adaptation to colder climates. The cold‐tolerant Geng accessions have undergone stronger selection under colder climate conditions than other accessions during the domestication and breeding processes. Additive effects of dominant allelic variants of four identified genes have been important in adaptation to cold in modern rice varieties. Therefore, this study provides valuable information for further gene discovery and pyramiding breeding to improve cold tolerance at the reproductive stage in rice.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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            PLINK: a tool set for whole-genome association and population-based linkage analyses.

            Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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              The variant call format and VCFtools

              Summary: The variant call format (VCF) is a generic format for storing DNA polymorphism data such as SNPs, insertions, deletions and structural variants, together with rich annotations. VCF is usually stored in a compressed manner and can be indexed for fast data retrieval of variants from a range of positions on the reference genome. The format was developed for the 1000 Genomes Project, and has also been adopted by other projects such as UK10K, dbSNP and the NHLBI Exome Project. VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API. Availability: http://vcftools.sourceforge.net Contact: rd@sanger.ac.uk
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                Author and article information

                Contributors
                lijinjie@cau.edu.cn
                lizichao@cau.edu.cn
                Journal
                Plant Biotechnol J
                Plant Biotechnol J
                10.1111/(ISSN)1467-7652
                PBI
                Plant Biotechnology Journal
                John Wiley and Sons Inc. (Hoboken )
                1467-7644
                1467-7652
                24 June 2020
                December 2020
                : 18
                : 12 ( doiID: 10.1111/pbi.v18.12 )
                : 2491-2503
                Affiliations
                [ 1 ] State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement College of Agronomy and Biotechnology China Agricultural University Beijing China
                [ 2 ] Biotechnology and Genetic Resources Institute Yunnan Academy of Agricultural Sciences Kunming China
                [ 3 ] State Key Laboratory of Systematic and Evolutionary Botany Institute of Botany Chinese Academy of Sciences Beijing China
                Author notes
                [*] [* ] Correspondence (Tel +86 010 62731414; fax +86 010 62731414; email lijinjie@ 123456cau.edu.cn ; lizichao@ 123456cau.edu.cn )

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-8594-7716
                https://orcid.org/0000-0002-3186-1132
                Article
                PBI13424
                10.1111/pbi.13424
                7680545
                32490579
                2b2b1b77-525a-410f-947b-6ff2ac4729da
                © 2020 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 10 February 2020
                : 28 April 2020
                : 19 May 2020
                Page count
                Figures: 6, Tables: 0, Pages: 13, Words: 9078
                Funding
                Funded by: Ministry of Science and Technology of China , open-funder-registry 10.13039/501100002855;
                Award ID: 2016YFD0100101‐09
                Funded by: National Natural Science Foundation of China , open-funder-registry 10.13039/501100001809;
                Award ID: 31671649
                Award ID: 31771753
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                December 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.4 mode:remove_FC converted:22.11.2020

                Biotechnology
                adaptive differentiation,cold tolerance,gwas,breeding
                Biotechnology
                adaptive differentiation, cold tolerance, gwas, breeding

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