{"data":{"id":"10.5061/dryad.ksn02v751","type":"dois","attributes":{"doi":"10.5061/dryad.ksn02v751","prefix":"10.5061","suffix":"dryad.ksn02v751","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Chase, Kevin","nameType":"Personal","givenName":"Kevin","familyName":"Chase","affiliation":["University of Utah"],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9968-1437","nameIdentifierScheme":"ORCID"}]},{"name":"Watkins, Maren","nameType":"Personal","givenName":"Maren","familyName":"Watkins","affiliation":["University of Utah"],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4127-1961","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"Integrating venom peptide libraries into a phylogenetic and broader biological framework"}],"publisher":"Dryad","container":{},"publicationYear":2022,"subjects":[{"subject":"FOS: Basic medicine","schemeUri":"https://web-archive.oecd.org/2012-06-15/138575-38235147.pdf","subjectScheme":"fos"},{"subject":"FOS: Basic medicine","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2021-09-27T20:13:04Z","dateType":"Submitted"},{"date":"2021-10-07T00:00:00Z","dateType":"Issued"},{"date":"2021-10-07T00:00:00Z","dateType":"Available"},{"date":"2022-01-05T00:00:00Z","dateType":"Updated"}],"language":"en","types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","relatedIdentifier":"10.3389/fmolb.2022.784419","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["1611514 bytes"],"formats":[],"version":"5","rightsList":[{"rights":"Creative Commons Zero v1.0 Universal","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc0-1.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"The venomous marine snails are conventionally divided into three groups,\n the cone snails (family Conidae), the auger snails (family Terebridae) and\n the turrids (formerly all assigned to a single family, Turridae). In this\n study, a library of venom peptides from species conventionally assigned to\n the genus Turris was correlated to a phylogenetic analysis. Nucleotide\n sequences of multiple genes from transcriptomes were used to assess the\n phylogenic relationships across a diverse set of species. The resulting\n tree shows that as conventionally defined, the Conoidean genus Turris, is\n polyphyletic. We describe a new genus, Purpuraturris gen. nov., that\n comprises the outlier species. In addition to morphological distinctions,\n molecular data reveal that this group are more closely related to\n Unedogemmula and Turridrupa than to Turris sensu stricto. The correlation\n between phylogenetic information and multiple peptide sequences from the\n library of venom peptides was used to highlight those peptides mostly\n likely to be unique and intimately associated with biological diversity.\n The plethora of peptide sequences available requires two prioritization\n decisions: which subset of peptides to initially characterize, and after\n these are characterized, which to comprehensively investigate for\n potential biomedical applications such as drug developments.","descriptionType":"Abstract"},{"description":"Adapter clipping and quality trimming of raw reads were performed\n using fqtrim software (Version 0.9.4, ) and PRINSEQ (Version 0.20.4).\n After processing, sequences shorter than 70 bps and those containing more\n than 5% ambiguous bases (Ns) were discarded. De novo transcriptome\n assembly was performed using Trinity Version 2.0.5 with a kmer size for\n building De Bruijn Graphs of 31, a minimum kmer coverage of 10, and a\n minimum glue of 10. Assembled transcripts were annotated using Blastx\n (NCBI-Blast-2.2.28+) against conotoxin sequences extracted from the\n ConoServer and UniProt databases.  Common genes that were shared between\n all datasets were identified using the blast identities of assembled\n contigs (e \u0026lt; 10-4).\u003cbr\u003e Fasta contig sequences were aligned\n using mafft v7.222 (with the “auto” flag).  For each alignment file we\n used the RAxML (Stamatakis 2006) program with a GTRGAMMA model\n (unpartitioned) to determine the “best” tree. Each zip\n file is a compressed folder.\u003cbr\u003e fasta.zip has the contiq sequences\n from each sample grouped by blast identity gene name.  Each file is named\n according to the Swiss-Prot identifier.\u003cbr\u003e aligned.zip has mafft\n aligned sequences from all samples in fasta format.\u003cbr\u003e bestTree.zip\n has has the “best” RaxML trees for all genes.","descriptionType":"Methods"}],"geoLocations":[],"fundingReferences":[{"schemeUri":"https://ror.org","funderName":"National Institute of General Medical Sciences","awardNumber":"GM048677","funderIdentifier":"https://ror.org/04q48ey07","funderIdentifierType":"ROR"},{"schemeUri":"https://ror.org","funderName":"United States Department of Defense","awardNumber":"W81XWH-17-1-0413","funderIdentifier":"https://ror.org/0447fe631","funderIdentifierType":"ROR"}],"xml":"<?xml version="1.0" encoding="UTF-8"?>
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  <identifier identifierType="DOI">10.5061/DRYAD.KSN02V751</identifier>
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    <creator>
      <creatorName nameType="Personal">Chase, Kevin</creatorName>
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      <affiliation affiliationIdentifier="https://ror.org/03r0ha626" affiliationIdentifierScheme="ROR" schemeURI="https://ror.org">University of Utah</affiliation>
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    <creator>
      <creatorName nameType="Personal">Watkins, Maren</creatorName>
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      <affiliation affiliationIdentifier="https://ror.org/03r0ha626" affiliationIdentifierScheme="ROR" schemeURI="https://ror.org">University of Utah</affiliation>
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  <titles>
    <title>
      Integrating venom peptide libraries into a phylogenetic and broader
      biological framework
    </title>
  </titles>
  <publisher publisherIdentifier="https://ror.org/00x6h5n95" publisherIdentifierScheme="ROR" schemeURI="https://ror.org/">Dryad</publisher>
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  </subjects>
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    <fundingReference>
      <funderName>National Institute of General Medical Sciences</funderName>
      <funderIdentifier funderIdentifierType="ROR">https://ror.org/04q48ey07</funderIdentifier>
      <awardNumber>GM048677</awardNumber>
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      <funderName>United States Department of Defense</funderName>
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      <awardNumber>W81XWH-17-1-0413</awardNumber>
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    <date dateType="Submitted">2021-09-27T20:13:04Z</date>
    <date dateType="Issued">2021-10-07T00:00:00Z</date>
    <date dateType="Available">2021-10-07T00:00:00Z</date>
    <date dateType="Updated">2022-01-05T00:00:00Z</date>
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  <language>en</language>
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    <description descriptionType="Abstract">
      The venomous marine snails are conventionally divided into three groups,
      the cone snails (family Conidae), the auger snails (family Terebridae) and
      the turrids (formerly all assigned to a single family, Turridae). In this
      study, a library of venom peptides from species conventionally assigned to
      the genus Turris was correlated to a phylogenetic analysis. Nucleotide
      sequences of multiple genes from transcriptomes were used to assess the
      phylogenic relationships across a diverse set of species. The resulting
      tree shows that as conventionally defined, the Conoidean genus Turris, is
      polyphyletic. We describe a new genus, Purpuraturris gen. nov., that
      comprises the outlier species. In addition to morphological distinctions,
      molecular data reveal that this group are more closely related to
      Unedogemmula and Turridrupa than to Turris sensu stricto. The correlation
      between phylogenetic information and multiple peptide sequences from the
      library of venom peptides was used to highlight those peptides mostly
      likely to be unique and intimately associated with biological diversity.
      The plethora of peptide sequences available requires two prioritization
      decisions: which subset of peptides to initially characterize, and after
      these are characterized, which to comprehensively investigate for
      potential biomedical applications such as drug developments.
    </description>
    <description descriptionType="Methods">
      &lt;p&gt;Adapter clipping and quality trimming of raw reads were performed
      using fqtrim software (Version 0.9.4, ) and PRINSEQ (Version 0.20.4).
      After processing, sequences shorter than 70 bps and those containing more
      than 5% ambiguous bases (Ns) were discarded. De novo transcriptome
      assembly was performed using Trinity Version 2.0.5 with a kmer size for
      building De Bruijn Graphs of 31, a minimum kmer coverage of 10, and a
      minimum glue of 10. Assembled transcripts were annotated using Blastx
      (NCBI-Blast-2.2.28+) against conotoxin sequences extracted from the
      ConoServer and UniProt databases.  Common genes that were shared between
      all datasets were identified using the blast identities of assembled
      contigs (e &amp;lt; 10-4).&lt;br&gt; Fasta contig sequences were aligned
      using mafft v7.222 (with the “auto” flag).  For each alignment file we
      used the RAxML (Stamatakis 2006) program with a GTRGAMMA model
      (unpartitioned) to determine the “best” tree.&lt;/p&gt; &lt;p&gt;Each zip
      file is a compressed folder.&lt;br&gt; fasta.zip has the contiq sequences
      from each sample grouped by blast identity gene name.  Each file is named
      according to the Swiss-Prot identifier.&lt;br&gt; aligned.zip has mafft
      aligned sequences from all samples in fasta format.&lt;br&gt; bestTree.zip
      has has the “best” RaxML trees for all genes.&lt;/p&gt;
    </description>
  </descriptions>
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