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      Opportunities and Challenges for Genomic Data Analyses in Biobanks: A Call for Papers

      The GSA Journals are calling for submissions of papers on biobank-scale genomic data analyses. The closing date for submissions is May 31 2024.

      Discover more and submit today

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      CRISpy-Pop: A Web Tool for Designing CRISPR/Cas9-Driven Genetic Modifications in Diverse Populations

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          Abstract

          CRISPR/Cas9 is a powerful tool for editing genomes, but design decisions are generally made with respect to a single reference genome. With population genomic data becoming available for an increasing number of model organisms, researchers are interested in manipulating multiple strains and lines. CRISpy-pop is a web application that generates and filters guide RNA sequences for CRISPR/Cas9 genome editing for diverse yeast and bacterial strains. The current implementation designs and predicts the activity of guide RNAs against more than 1000 Saccharomyces cerevisiae genomes, including 167 strains frequently used in bioenergy research. Zymomonas mobilis, an increasingly popular bacterial bioenergy research model, is also supported. CRISpy-pop is available as a web application ( https://CRISpy-pop.glbrc.org/) with an intuitive graphical user interface. CRISpy-pop also cross-references the human genome to allow users to avoid the selection of guide RNAs with potential biosafety concerns. Additionally, CRISpy-pop predicts the strain coverage of each guide RNA within the supported strain sets, which aids in functional population genetic studies. Finally, we validate how CRISpy-pop can accurately predict the activity of guide RNAs across strains using population genomic data.

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          Most cited references30

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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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              A global reference for human genetic variation

              The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
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                Author and article information

                Journal
                G3 (Bethesda)
                Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes|Genomes|Genetics
                Genetics Society of America
                2160-1836
                21 September 2020
                November 2020
                : 10
                : 11
                : 4287-4294
                Affiliations
                [* ]DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, WI 53726
                []Laboratory of Genetics, Center for Genomic Science Innovation, University of Wisconsin-Madison WI 53726
                []Wisconsin Energy Institute, University of Wisconsin-Madison, WI 53726
                [§ ]J. F. Crow Institute for the Study of Evolution, University of Wisconsin-Madison, WI 53726
                [** ]Université Côte d’Azur, CNRS, INSERM, IRCAN, Nice, France
                [†† ]Université de Strasbourg, CNRS, GMGM UMR 7156, Strasbourg, France
                [‡‡ ]Institut Universitaire de France (IUF), Paris, France
                [§§ ]Department of Biochemistry, University of Wisconsin-Madison, WI 53706
                [*** ]Department of Bacteriology, University of Wisconsin-Madison, WI 53706
                Author notes
                [1 ]Corresponding author: 1552 University Avenue, Madison, WI 53726. E-mail: cthittinger@ 123456wisc.edu
                Author information
                http://orcid.org/0000-0002-3796-2284
                http://orcid.org/0000-0002-5309-6718
                http://orcid.org/0000-0003-1014-350X
                http://orcid.org/0000-0002-2318-0775
                http://orcid.org/0000-0002-5042-0383
                http://orcid.org/0000-0002-8182-257X
                http://orcid.org/0000-0001-6592-9337
                http://orcid.org/0000-0001-5088-7461
                Article
                GGG_401498
                10.1534/g3.120.401498
                7642938
                32963084
                acff8da8-a8a3-41c9-89bd-5a0753320715
                Copyright © 2020 Stoneman et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 June 2020
                : 21 September 2020
                Page count
                Figures: 5, Tables: 2, Equations: 0, References: 32, Pages: 8
                Funding
                Funded by: Great Lakes Bioenergy Research Center
                Award ID: DE-SC0018409
                Funded by: National Science Foundation, DOI https://doi.org/10.13039/100000001;
                Award ID: DEB-1442148
                Funded by: USDA National Institute of Food and Agriculture
                Award ID: Hatch Project 1020204
                Award ID: Pew Scholar in the Biomedical Sciences
                Award ID: H. I. Romnes Faculty Fellow
                Funded by: Pew Charitable Trusts, DOI https://doi.org/10.13039/100000875;
                Funded by: Office of the Vice Chancellor for Research and Graduate Education with funding from the Wisconsin Alumni Research Foundation
                Categories
                Investigations

                Genetics
                crispr/cas9,sgrna,genome editing,population genomics,yeast
                Genetics
                crispr/cas9, sgrna, genome editing, population genomics, yeast

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