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      Genetic Basis and Evolution of Structural Color Polymorphism in an Australian Songbird

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          Abstract

          Island organisms often evolve phenotypes divergent from their mainland counterparts, providing a useful system for studying adaptation under differential selection. In the white-winged fairywren ( Malurus leucopterus), subspecies on two islands have a black nuptial plumage whereas the subspecies on the Australian mainland has a blue nuptial plumage. The black subspecies have a feather nanostructure that could in principle produce a blue structural color, suggesting a blue ancestor. An earlier study proposed independent evolution of melanism on the islands based on the history of subspecies divergence. However, the genetic basis of melanism and the origin of color differentiation in this group are still unknown. Here, we used whole-genome resequencing to investigate the genetic basis of melanism by comparing the blue and black M. leucopterus subspecies to identify highly divergent genomic regions. We identified a well-known pigmentation gene ASIP and four candidate genes that may contribute to feather nanostructure development. Contrary to the prediction of convergent evolution of island melanism, we detected signatures of a selective sweep in genomic regions containing ASIP and SCUBE2 not in the black subspecies but in the blue subspecies, which possesses many derived SNPs in these regions, suggesting that the mainland subspecies has re-evolved a blue plumage from a black ancestor. This proposed re-evolution was likely driven by a preexisting female preference. Our findings provide new insight into the evolution of plumage coloration in island versus continental populations, and, importantly, we identify candidate genes that likely play roles in the development and evolution of feather structural coloration.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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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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              The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

              Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                Mol Biol Evol
                Mol Biol Evol
                molbev
                Molecular Biology and Evolution
                Oxford University Press (US )
                0737-4038
                1537-1719
                March 2024
                28 February 2024
                28 February 2024
                : 41
                : 3
                : msae046
                Affiliations
                School of Biological Sciences, The University of Hong Kong , Hong Kong, China
                Department of Organismic and Evolutionary Biology, Harvard University , Cambridge, MA 02138, USA
                School of Biological Sciences, The University of Hong Kong , Hong Kong, China
                School of Biological Sciences, The University of Hong Kong , Hong Kong, China
                School of Biological Sciences, The University of Hong Kong , Hong Kong, China
                Department of Ecology and Evolutionary Biology, Tulane University , New Orleans, LA 70118, USA
                Department of Ecology and Evolutionary Biology, Tulane University , New Orleans, LA 70118, USA
                Cornell Lab of Ornithology and Department of Neurobiology and Behavior, Cornell University , Ithaca, NY 14853, USA
                Department of Organismic and Evolutionary Biology, Harvard University , Cambridge, MA 02138, USA
                Author notes

                Simon Yung Wa Sin and Fushi Ke contributed equally.

                Corresponding author: E-mail: yungwa.sin@ 123456gmail.com .
                Author information
                https://orcid.org/0000-0003-2484-2897
                https://orcid.org/0000-0002-5837-7260
                https://orcid.org/0000-0001-8275-7194
                https://orcid.org/0000-0003-1349-628X
                https://orcid.org/0000-0001-8201-9992
                https://orcid.org/0000-0001-7585-4578
                https://orcid.org/0000-0003-2535-6217
                Article
                msae046
                10.1093/molbev/msae046
                10962638
                38415852
                504bf557-402c-4651-aebd-4db49112234d
                © The Author(s) 2024. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.

                History
                : 13 November 2023
                : 02 February 2024
                : 22 February 2024
                : 25 March 2024
                Page count
                Pages: 18
                Categories
                Discoveries
                AcademicSubjects/SCI01130
                AcademicSubjects/SCI01180

                Molecular biology
                white-winged fairywren,male ornamentation,color genetics,feather coloration,structural color,avian plumage color

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