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      A haplotype-led approach to increase the precision of wheat breeding

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          Abstract

          Crop productivity must increase at unprecedented rates to meet the needs of the growing worldwide population. Exploiting natural variation for the genetic improvement of crops plays a central role in increasing productivity. Although current genomic technologies can be used for high-throughput identification of genetic variation, methods for efficiently exploiting this genetic potential in a targeted, systematic manner are lacking. Here, we developed a haplotype-based approach to identify genetic diversity for crop improvement using genome assemblies from 15 bread wheat ( Triticum aestivum) cultivars. We used stringent criteria to identify identical-by-state haplotypes and distinguish these from near-identical sequences (~99.95% identity). We showed that each cultivar shares ~59 % of its genome with other sequenced cultivars and we detected the presence of extended haplotype blocks containing hundreds to thousands of genes across all wheat chromosomes. We found that genic sequence alone was insufficient to fully differentiate between haplotypes, as were commonly used array-based genotyping chips due to their gene centric design. We successfully used this approach for focused discovery of novel haplotypes from a landrace collection and documented their potential for trait improvement in modern bread wheat. This study provides a framework for defining and exploiting haplotypes to increase the efficiency and precision of wheat breeding towards optimising the agronomic performance of this crucial crop.

          Abstract

          Brinton, Uauy and colleagues utilize genomic data from the 10+ Wheat Genome Project to develop a useful tool for studying and generating new wheat cultivars. This framework uses advanced exploitation of wheat haplotypes to bring newfound precision and efficiency to wheat breeding.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              Basic local alignment search tool.

              A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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                Author and article information

                Contributors
                j.brinton@kew.org
                cristobal.uauy@jic.ac.uk
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                25 November 2020
                25 November 2020
                2020
                : 3
                : 712
                Affiliations
                [1 ]GRID grid.14830.3e, ISNI 0000 0001 2175 7246, John Innes Centre, Norwich Research Park, ; Norwich, NR4 7UH UK
                [2 ]Helmholtz Zentrum München – Research Center for Environmental Health, Neuherberg, Germany
                [3 ]GRID grid.25152.31, ISNI 0000 0001 2154 235X, University of Saskatchewan, Crop Development Centre, ; Saskatoon, Saskatchewan Canada
                [4 ]Grain Research Laboratory, Canadian Grain Commission, Winnipeg, MB Canada
                [5 ]GRID grid.4903.e, ISNI 0000 0001 2097 4353, Present Address: Department of Natural Capital and Plant Health, Royal Botanic Gardens, Kew, ; Richmond, UK
                Author information
                http://orcid.org/0000-0001-5745-7085
                http://orcid.org/0000-0002-9814-1770
                Article
                1413
                10.1038/s42003-020-01413-2
                7689427
                33239669
                e920ed30-086c-4e92-941f-09c286268bcc
                © The Author(s) 2020

                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/.

                History
                : 13 July 2020
                : 15 October 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000268, RCUK | Biotechnology and Biological Sciences Research Council (BBSRC);
                Award ID: BB/P016855/1
                Award ID: BB/P013511/1
                Award Recipient :
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                © The Author(s) 2020

                plant breeding,plant genetics
                plant breeding, plant genetics

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