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      In Silico Identification and Characterization of Satellite DNAs in 23 Drosophila Species from the Montium Group

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          Abstract

          Satellite DNA (satDNA) is a class of tandemly repeated non-protein coding DNA sequences which can be found in abundance in eukaryotic genomes. They can be functional, impact the genomic architecture in many ways, and their rapid evolution has consequences for species diversification. We took advantage of the recent availability of sequenced genomes from 23 Drosophila species from the montium group to study their satDNA landscape. For this purpose, we used publicly available whole-genome sequencing Illumina reads and the TAREAN (tandem repeat analyzer) pipeline. We provide the characterization of 101 non-homologous satDNA families in this group, 93 of which are described here for the first time. Their repeat units vary in size from 4 bp to 1897 bp, but most satDNAs show repeat units < 100 bp long and, among them, repeats ≤ 10 bp are the most frequent ones. The genomic contribution of the satDNAs ranges from ~1.4% to 21.6%. There is no significant correlation between satDNA content and genome sizes in the 23 species. We also found that at least one satDNA originated from an expansion of the central tandem repeats (CTRs) present inside a Helitron transposon. Finally, some satDNAs may be useful as taxonomic markers for the identification of species or subgroups within the group.

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          Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

          Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com
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            The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update

            Abstract Galaxy (homepage: https://galaxyproject.org, main public server: https://usegalaxy.org) is a web-based scientific analysis platform used by tens of thousands of scientists across the world to analyze large biomedical datasets such as those found in genomics, proteomics, metabolomics and imaging. Started in 2005, Galaxy continues to focus on three key challenges of data-driven biomedical science: making analyses accessible to all researchers, ensuring analyses are completely reproducible, and making it simple to communicate analyses so that they can be reused and extended. During the last two years, the Galaxy team and the open-source community around Galaxy have made substantial improvements to Galaxy's core framework, user interface, tools, and training materials. Framework and user interface improvements now enable Galaxy to be used for analyzing tens of thousands of datasets, and >5500 tools are now available from the Galaxy ToolShed. The Galaxy community has led an effort to create numerous high-quality tutorials focused on common types of genomic analyses. The Galaxy developer and user communities continue to grow and be integral to Galaxy's development. The number of Galaxy public servers, developers contributing to the Galaxy framework and its tools, and users of the main Galaxy server have all increased substantially.
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              MUSCLE: a multiple sequence alignment method with reduced time and space complexity

              Background In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUSCLE to achieve the highest scores reported to date on four alignment accuracy benchmarks. Here we present a more complete discussion of the algorithm, describing several previously unpublished techniques that improve biological accuracy and / or computational complexity. We introduce a new option, MUSCLE-fast, designed for high-throughput applications. We also describe a new protocol for evaluating objective functions that align two profiles. Results We compare the speed and accuracy of MUSCLE with CLUSTALW, Progressive POA and the MAFFT script FFTNS1, the fastest previously published program known to the author. Accuracy is measured using four benchmarks: BAliBASE, PREFAB, SABmark and SMART. We test three variants that offer highest accuracy (MUSCLE with default settings), highest speed (MUSCLE-fast), and a carefully chosen compromise between the two (MUSCLE-prog). We find MUSCLE-fast to be the fastest algorithm on all test sets, achieving average alignment accuracy similar to CLUSTALW in times that are typically two to three orders of magnitude less. MUSCLE-fast is able to align 1,000 sequences of average length 282 in 21 seconds on a current desktop computer. Conclusions MUSCLE offers a range of options that provide improved speed and / or alignment accuracy compared with currently available programs. MUSCLE is freely available at .
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                Author and article information

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                Journal
                GENEG9
                Genes
                Genes
                2073-4425
                February 2023
                January 23 2023
                : 14
                : 2
                : 300
                Article
                10.3390/genes14020300
                d44de726-9844-4f4b-a8e4-e4b589ee2067
                © 2023

                https://creativecommons.org/licenses/by/4.0/

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