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      A cattle graph genome incorporating global breed diversity

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          Abstract

          Despite only 8% of cattle being found in Europe, European breeds dominate current genetic resources. This adversely impacts cattle research in other important global cattle breeds, especially those from Africa for which genomic resources are particularly limited, despite their disproportionate importance to the continent’s economies. To mitigate this issue, we have generated assemblies of African breeds, which have been integrated with genomic data for 294 diverse cattle into a graph genome that incorporates global cattle diversity. We illustrate how this more representative reference assembly contains an extra 116.1 Mb (4.2%) of sequence absent from the current Hereford sequence and consequently inaccessible to current studies. We further demonstrate how using this graph genome increases read mapping rates, reduces allelic biases and improves the agreement of structural variant calling with independent optical mapping data. Consequently, we present an improved, more representative, reference assembly that will improve global cattle research.

          Abstract

          Cattle reference genomes are valuable resources but are currently heavily biased towards European breeds. Here the authors integrate assemblies for African breeds into a more representative cattle graph genome capturing global breed diversity.

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          Most cited references33

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          Fast and accurate short read alignment with Burrows–Wheeler transform

          Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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            BEDTools: a flexible suite of utilities for comparing genomic features

            Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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              Minimap2: pairwise alignment for nucleotide sequences

              Heng Li (2018)
              Recent advances in sequencing technologies promise ultra-long reads of ∼100 kb in average, full-length mRNA or cDNA reads in high throughput and genomic contigs over 100 Mb in length. Existing alignment programs are unable or inefficient to process such data at scale, which presses for the development of new alignment algorithms.
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                Author and article information

                Contributors
                Andrea.Talenti@ed.ac.uk
                James.Prendergast@roslin.ed.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                17 February 2022
                17 February 2022
                2022
                : 13
                : 910
                Affiliations
                [1 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, The Roslin Institute, Royal (Dick) School of Veterinary Studies, , University of Edinburgh, Easter Bush Campus, ; Midlothian, EH25 9RG UK
                [2 ]GRID grid.419369.0, ISNI 0000 0000 9378 4481, The International Livestock Research Institute, ; PO Box 30709 Nairobi, Kenya
                [3 ]Centre for Tropical Livestock Genetics and Health, Easter Bush, Midlothian, EH25 9RG UK
                [4 ]GRID grid.419369.0, ISNI 0000 0000 9378 4481, Centre for Tropical Livestock Genetics and Health, ILRI Kenya, ; Nairobi, 30709-00100 Kenya
                [5 ]GRID grid.10757.34, ISNI 0000 0001 2108 8257, Department of Veterinary Pathology and Microbiology, , University of Nigeria, ; Nsukka, Enugu State Nigeria
                [6 ]GRID grid.419813.6, Biotechnology Division, , National Veterinary Research Institute, ; Vom, Plateau State Nigeria
                [7 ]GRID grid.510328.d, Biomedical Research Centre, Ghent University Global Campus, Songdo, ; Incheon, South Korea
                [8 ]International Livestock Research Institute (ILRI) PO, 5689 Addis Ababa, Ethiopia
                [9 ]Centre for Tropical Livestock Genetics and Health (CTLGH), ILRI Ethiopia, PO Box 5689 Addis Ababa, Ethiopia
                [10 ]GRID grid.11899.38, ISNI 0000 0004 1937 0722, Ribeirão Preto College of Nursing, , University of Sao Paulo, ; Ribeirão Preto, SP Brazil
                [11 ]GRID grid.411749.e, ISNI 0000 0001 0221 6962, Faculty of Veterinary and Animal Sciences, , Gomal University, ; Dera Ismail Khan, Pakistan
                Author information
                http://orcid.org/0000-0003-1309-3667
                http://orcid.org/0000-0003-2474-2570
                http://orcid.org/0000-0001-8764-4156
                http://orcid.org/0000-0001-6081-8363
                http://orcid.org/0000-0003-1524-2232
                http://orcid.org/0000-0001-6026-492X
                http://orcid.org/0000-0002-0793-9059
                http://orcid.org/0000-0002-8380-6565
                http://orcid.org/0000-0002-6781-2236
                http://orcid.org/0000-0001-5783-9630
                http://orcid.org/0000-0001-8916-018X
                Article
                28605
                10.1038/s41467-022-28605-0
                8854726
                35177600
                90b383d4-d00e-4dcb-bd75-206931816a66
                © The Author(s) 2022

                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
                : 29 October 2020
                : 20 January 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000268, RCUK | Biotechnology and Biological Sciences Research Council (BBSRC);
                Award ID: BB/T019468/1
                Award ID: BBS/E/D/10002070
                Award ID: BB/R015155/1
                Award ID: BB/P024025/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000278, Department for International Development (Department for International Development, UK);
                Award ID: OPP1127286
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000865, Bill and Melinda Gates Foundation (Bill & Melinda Gates Foundation);
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                animal breeding,genomics
                Uncategorized
                animal breeding, genomics

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