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      Phylogenomic delineation of Physcomitrium (Bryophyta: Funariaceae) based on targeted sequencing of nuclear exons and their flanking regions rejects the retention of Physcomitrella , Physcomitridium and Aphanorrhegma

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          Hidden Markov model speed heuristic and iterative HMM search procedure

          Background Profile hidden Markov models (profile-HMMs) are sensitive tools for remote protein homology detection, but the main scoring algorithms, Viterbi or Forward, require considerable time to search large sequence databases. Results We have designed a series of database filtering steps, HMMERHEAD, that are applied prior to the scoring algorithms, as implemented in the HMMER package, in an effort to reduce search time. Using this heuristic, we obtain a 20-fold decrease in Forward and a 6-fold decrease in Viterbi search time with a minimal loss in sensitivity relative to the unfiltered approaches. We then implemented an iterative profile-HMM search method, JackHMMER, which employs the HMMERHEAD heuristic. Due to our search heuristic, we eliminated the subdatabase creation that is common in current iterative profile-HMM approaches. On our benchmark, JackHMMER detects 14% more remote protein homologs than SAM's iterative method T2K. Conclusions Our search heuristic, HMMERHEAD, significantly reduces the time needed to score a profile-HMM against large sequence databases. This search heuristic allowed us to implement an iterative profile-HMM search method, JackHMMER, which detects significantly more remote protein homologs than SAM's T2K and NCBI's PSI-BLAST.
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            Data access for the 1,000 Plants (1KP) project

            The 1,000 plants (1KP) project is an international multi-disciplinary consortium that has generated transcriptome data from over 1,000 plant species, with exemplars for all of the major lineages across the Viridiplantae (green plants) clade. Here, we describe how to access the data used in a phylogenomics analysis of the first 85 species, and how to visualize our gene and species trees. Users can develop computational pipelines to analyse these data, in conjunction with data of their own that they can upload. Computationally estimated protein-protein interactions and biochemical pathways can be visualized at another site. Finally, we comment on our future plans and how they fit within this scalable system for the dissemination, visualization, and analysis of large multi-species data sets.
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              HybPiper: Extracting coding sequence and introns for phylogenetics from high-throughput sequencing reads using target enrichment1

              Premise of the study: Using sequence data generated via target enrichment for phylogenetics requires reassembly of high-throughput sequence reads into loci, presenting a number of bioinformatics challenges. We developed HybPiper as a user-friendly platform for assembly of gene regions, extraction of exon and intron sequences, and identification of paralogous gene copies. We test HybPiper using baits designed to target 333 phylogenetic markers and 125 genes of functional significance in Artocarpus (Moraceae). Methods and Results: HybPiper implements parallel execution of sequence assembly in three phases: read mapping, contig assembly, and target sequence extraction. The pipeline was able to recover nearly complete gene sequences for all genes in 22 species of Artocarpus. HybPiper also recovered more than 500 bp of nontargeted intron sequence in over half of the phylogenetic markers and identified paralogous gene copies in Artocarpus. Conclusions: HybPiper was designed for Linux and Mac OS X and is freely available at https://github.com/mossmatters/HybPiper.
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                Author and article information

                Journal
                Journal of Systematics and Evolution
                Jnl of Sytematics Evolution
                Wiley
                1674-4918
                1759-6831
                August 09 2019
                July 2019
                July 29 2019
                July 2019
                : 57
                : 4
                : 404-417
                Affiliations
                [1 ]Ecology and Evolutionary BiologyUniversity of Connecticut 75N Eagleville Rd. Storrs CT 06269‐3043 USA
                [2 ]Department of BiologyAugustana College 639 38th Street Rock Island IL 61201 USA
                [3 ]Plant ScienceChicago Botanic Garden 1000 Lake Cook Road Glencoe IL 60022 USA
                [4 ]Department of Biological SciencesTexas Tech University 2901 Main Street Lubbock TX 79409‐43131 USA
                [5 ]Key Laboratory of Southern Subtropical Plant DiversityShenzhen Fairy Lake Botanical Garden Shenzhen 518004 China
                [6 ]China National GeneBankBGI‐Shenzhen Shenzhen 518120 China
                [7 ]Department of BiologyDuke University Durham NC 27708 USA
                Article
                10.1111/jse.12516
                284bd3f7-9848-4f12-bf42-1c32f7f515e7
                © 2019

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                http://doi.wiley.com/10.1002/tdm_license_1.1

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