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      Rapid divergence of the male reproductive proteins in the Drosophila dunni group and implications for postmating incompatibilities between species

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          Abstract

          Proteins involved in post-copulatory interactions between males and females are among the fastest evolving genes in many species, usually attributed to their involvement in reproductive conflict. As a result, these proteins are thought to often be involved in the formation of postmating-prezygotic incompatibilities between species. The Drosophila dunni subgroup consists of a dozen recently diverged species found across the Caribbean islands with varying levels of hybrid incompatibility. We performed experimental crosses between species in the dunni group and see some evidence of hybrid incompatibilities. We also find evidence of reduced survival following hybrid mating, likely due to postmating-prezygotic incompatibilities. We assessed rates of evolution between these species genomes and find evidence of rapid evolution and divergence of some reproductive proteins, specifically the seminal fluid proteins. This work suggests the rapid evolution of seminal fluid proteins may be associated with postmating-prezygotic isolation, which acts as a barrier for gene flow between even the most closely related species.

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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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            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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              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
                Role: Editor
                Journal
                G3 (Bethesda)
                Genetics
                g3journal
                G3: Genes|Genomes|Genetics
                Oxford University Press
                2160-1836
                April 2021
                18 February 2021
                18 February 2021
                : 11
                : 4
                : jkab050
                Affiliations
                The Department of Molecular Biosciences, University of Kansas , Lawrence, KS 66045, USA
                Author notes
                Corresponding author: 4055 Haworth Hall, 1200 Sunnyside Avenue, Lawrence, KS 66045, USA. unckless@ 123456ku.edu .
                Author information
                https://orcid.org/0000-0001-8586-7137
                Article
                jkab050
                10.1093/g3journal/jkab050
                8759818
                33599779
                9c675039-feb8-4b70-ab54-ea7d953cb339
                © The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America.

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

                History
                : 19 November 2020
                : 17 February 2021
                : 28 January 2021
                Page count
                Pages: 14
                Funding
                Funded by: Kansas IDEA Network of Biomedical Research Excelllence;
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Award ID: P20 GM103418
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Award ID: R00 GM114714
                Categories
                Investigation
                AcademicSubjects/SCI01180
                AcademicSubjects/SCI01140
                AcademicSubjects/SCI00010
                AcademicSubjects/SCI00960

                Genetics
                drosophila,hybrid incompatibilities,genome evolution,seminal fluid proteins
                Genetics
                drosophila, hybrid incompatibilities, genome evolution, seminal fluid proteins

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