http://lod.bco-dmo.org/id/dataset/671662
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2016-12-28
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Best toll-like receptors (TLR) genes from Lophotrochozoa BLASTP search, from Table 3, Halanych and Kocot (2014) Biol. Bull. (Antarctic Inverts project)
2016-12-27
publication
2016-12-27
revision
BCO-DMO Linked Data URI
2016-12-27
creation
http://lod.bco-dmo.org/id/dataset/671662
Kenneth M. Halanych
Auburn University
principalInvestigator
Andrew Mahon
Central Michigan University
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Halanych, K. M., Mahon, A. (2016) Best toll-like receptors (TLR) genes from Lophotrochozoa BLASTP search, from Table 3, Halanych and Kocot (2014) Biol. Bull. (Antarctic Inverts project). Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2016-12-27 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/671662 [access date]
Best toll-like receptors (TLR) genes from Lophotrochozoa BLASTP search Dataset Description: Methods and Sampling: <p>From Halanych and Kocot (2014):</p>
<p><em><strong>Taxon sampling</strong><br />
Transcriptomes were obtained for the 18 invertebrate species listed in Table 1. For most animals, adult body wall (epidermis, muscles, and underlying tissue) was used for transcriptomes. For entoprocts and small brachiopods (Novocrania anomala and Macandrevia cranium), whole-body tissue was employed; for larger brachiopods (Glottidia pyramidata, Hemithris psittacea, and Laqueus californicus), extractions focused on mantle and muscle; for the solenogaster (a.k.a neomenioid) aplacophoran mollusc Proneomenia custodiens, unhatched juveniles were used. Collection locality information is also given in Table 1. The three annelid transcriptomes (Magelona beckleyi, Paramphinome jeffreysii, and Phyllochaetopterus prolifica) have been previously published (Weigert et al., 2014) in a phylogenomics paper detailing basal annelid relations. The remainder were part of a phylogenomics project on lophotrochozoan relationships (Kocot, 2013).</em></p>
<p><em><strong>Transcriptomic data collection</strong><br />
We follow the methods described in Weigert et al. (2014) and Kocot (2013), which are briefly summarized here. RNA was extracted with TRIzol (Invitrogen) and purified with the RNeasy kit (Qiagen; Valencia, CA) using oncolumn DNAse digestion. In the case of the small juveniles of Proneomenia custodiens, RNA was extracted with the RNeasy Micro kit (Qiagen; Valencia, CA). The SMART cDNA library construction kit (Clontech Laboratories, Mountain View, CA) was used to construct cDNA libraries. These libraries were sequenced by The Genomic Services Lab at the Hudson Alpha Institute in Huntsville, Alabama, on the Illumina (San Diego, CA) HiSeq 2000 platform with 2x100 paired-end sequencing. To reduce memory usage during transcriptome assembly, sequencing data were digitally normalized to a k-mer coverage depth of 30 using the normalize-by-median.py script (Brown et al., 2012). Data were then assembled using Trinity (Grabherr et al., 2011; 8 June 2012 version) with default settings.</em></p>
<p><em><strong>Identification of genes</strong><br />
UniProt accession numbers for human toll-like receptor genes were obtained from InnateDB (Innate DB, 2014; Lynn et al., 2008; Breuer et al., 2013). Amino acid sequences for TLR1-TLR10 were obtained from then National Center for Biotechnology Information (NCBI; Table 2) and used for bait in a TBLASTN search (Altschul et al., 1990) against the assembled nucleotide transcriptomes. For these searches, an e-value of 10^-5 was employed and only top hits longer than 800 nucleotides (to filter out smaller gene fragments) were retained. Significant hits were translated to amino acid sequences with TransDecoder in the Trinity package (Grabherr et al., 2011), and redundant sequences were removed with cd-hit (Li and Godzik, 2006) using an identity (-c flag) of 1.0. To further confirm their identity, the translated hits were searched against the Swiss Prot database using BLASTP with an e-value cutoff of 10^-5. As TransDecoder can yield multiple translations per nucleotide sequence, all translations were subject to BLASTP, and only the best hits were retained. Sequences that returned the top hit with a significant e-value and matched to a TLR gene were retained and compared to the SMART database (SMART, 2014; Schultz et al., 1998; Letunic et al., 2012) using the "normal" search setting to identify protein domains.</em></p>
<p><em>Previous phylogenetic analyses (e.g., Zheng et al., 2005; Davidson et al., 2008) on TLR genes typically used only the TIR domain for analyses. These analyses are limited to about 140-180 amino acids in length. Here, we aligned recovered TLR contigs from lophotrochozoans and Priapulus with human and Drosophilia TLR genes using MAFFT ver. 7 (Katoh and Standley, 2013). Even after reducing the alignment to the conserved TIR domain, sequences were highly variable, resulting in a questionable alignment. Considering that the TIR domain is shared among several gene families (Aravind et al., 2001) and the variability of the alignment, we question whether a tree produced from these sequences accurately represents gene genealogy. This suspicion was confirmed by using the T-REX server (Boc et al., 2012) for a RAxML-VI-HPC (Stamatakis, 2006) analysis (parameters included PROTGAMMA, WAG, 100 bootstraps) that yielded a tree with very low nodal support value. Roughly 50% of the nodes reported a bootstrap value less than 40%, and exploring different parameters did little to improve results. We used a much broader taxon sampling than for previous TIR trees, which likely influenced variability of the alignment. Due to the questionable reliability of such a phylogenetic analysis, results are not included herein.</em></p>
Funding provided by NSF Office of Polar Programs (formerly NSF PLR) (NSF OPP) Award Number: PLR-1043745 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1043745
Funding provided by NSF Office of Polar Programs (formerly NSF PLR) (NSF OPP) Award Number: PLR-1043670 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1043670
onGoing
Kenneth M. Halanych
Auburn University
334-844-3222
101 Life Sciences Building Department of Biological Sciences, Auburn University
Auburn
AL
36849
USA
ken@auburn.edu
pointOfContact
Andrew Mahon
Central Michigan University
989-774-6777
Office of Research & Graduate St
Mount Pleasant
MI
48859-0001
USA
mahon2a@cmich.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
taxon1
E_Value
taxon2
BLASTP_Query
TBLAST_Bait
Hit_Name
Description
Species_best_hit
Start_Methionine
AA_length
Stop_codon
Illumina (San Diego, CA) HiSeq 2000 platform at The Genomic Services Lab at the Hudson Alpha Institute in Huntsville, Alabama,
theme
None, User defined
taxon
No BCO-DMO term
species scientific name (binomial)
featureType
BCO-DMO Standard Parameters
Automated DNA Sequencer
Thermal Cycler
instrument
BCO-DMO Standard Instruments
Halanych_lab_2011-16
service
Deployment Activity
laboratory studies
place
Locations
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Genetic connectivity and biogeographic patterns of Antarctic benthic invertebrates
https://osprey.bco-dmo.org/project/665837
Genetic connectivity and biogeographic patterns of Antarctic benthic invertebrates
<p><em>Extracted from the NSF award abstract:</em></p>
<p>The research will explore the genetics, diversity, and biogeography of Antarctic marine benthic invertebrates, seeking to overturn the widely accepted suggestion that benthic fauna do not constitute a large, panmictic population. The investigators will sample adults and larvae from undersampled regions of West Antarctica that, combined with existing samples, will provide significant coverage of the western hemisphere of the Southern Ocean. The objectives are: 1) To assess the degree of genetic connectivity (or isolation) of benthic invertebrate species in the Western Antarctic using high-resolution genetic markers. 2) To begin exploring planktonic larvae spatial and bathymetric distributions for benthic shelf invertebrates in the Bellinghausen, Amundsen and Ross Seas. 3) To continue to develop a Marine Antarctic Genetic Inventory (MAGI) that relates larval and adult forms via DNA barcoding. </p>
Antarctic Inverts
largerWorkCitation
project
eng; USA
biota
oceans
laboratory studies
2016-12-27
Antarctica
0
BCO-DMO catalogue of parameters from Best toll-like receptors (TLR) genes from Lophotrochozoa BLASTP search, from Table 3, Halanych and Kocot (2014) Biol. Bull. (Antarctic Inverts project)
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/845093.rdf
Name: taxon1
Units: unitless
Description: <p>clade Lophotrochozoa or Ecdysozoa</p>
http://lod.bco-dmo.org/id/dataset-parameter/845094.rdf
Name: E_Value
Units: unitless
Description: <p>description</p>
http://lod.bco-dmo.org/id/dataset-parameter/845095.rdf
Name: taxon2
Units: unitless
Description: <p>more specific taxonomic group</p>
http://lod.bco-dmo.org/id/dataset-parameter/845096.rdf
Name: BLASTP_Query
Units: unitless
Description: <p>description</p>
http://lod.bco-dmo.org/id/dataset-parameter/845097.rdf
Name: TBLAST_Bait
Units: unitless
Description: <p>description</p>
http://lod.bco-dmo.org/id/dataset-parameter/845098.rdf
Name: Hit_Name
Units: unitless
Description: <p>description</p>
http://lod.bco-dmo.org/id/dataset-parameter/845099.rdf
Name: Description
Units: unitless
Description: <p>description</p>
http://lod.bco-dmo.org/id/dataset-parameter/845100.rdf
Name: Species_best_hit
Units: unitless
Description: <p>description</p>
http://lod.bco-dmo.org/id/dataset-parameter/845101.rdf
Name: Start_Methionine
Units: unitless
Description: <p>description</p>
http://lod.bco-dmo.org/id/dataset-parameter/845102.rdf
Name: AA_length
Units: base pairs?
Description: <p>description</p>
http://lod.bco-dmo.org/id/dataset-parameter/845103.rdf
Name: Stop_codon
Units: unitless
Description: <p>yes/no whether stop codon is present</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
3705
https://datadocs.bco-dmo.org/file/XYYPvD8in7p7wP/Hal_Kocot_2014_T3.csv
Hal_Kocot_2014_T3.csv
Primary data file for dataset ID 671662
download
https://osprey.bco-dmo.org/dataset/671662/data/download
download
onLine
dataset
<p>From Halanych and Kocot (2014):</p>
<p><em><strong>Taxon sampling</strong><br />
Transcriptomes were obtained for the 18 invertebrate species listed in Table 1. For most animals, adult body wall (epidermis, muscles, and underlying tissue) was used for transcriptomes. For entoprocts and small brachiopods (Novocrania anomala and Macandrevia cranium), whole-body tissue was employed; for larger brachiopods (Glottidia pyramidata, Hemithris psittacea, and Laqueus californicus), extractions focused on mantle and muscle; for the solenogaster (a.k.a neomenioid) aplacophoran mollusc Proneomenia custodiens, unhatched juveniles were used. Collection locality information is also given in Table 1. The three annelid transcriptomes (Magelona beckleyi, Paramphinome jeffreysii, and Phyllochaetopterus prolifica) have been previously published (Weigert et al., 2014) in a phylogenomics paper detailing basal annelid relations. The remainder were part of a phylogenomics project on lophotrochozoan relationships (Kocot, 2013).</em></p>
<p><em><strong>Transcriptomic data collection</strong><br />
We follow the methods described in Weigert et al. (2014) and Kocot (2013), which are briefly summarized here. RNA was extracted with TRIzol (Invitrogen) and purified with the RNeasy kit (Qiagen; Valencia, CA) using oncolumn DNAse digestion. In the case of the small juveniles of Proneomenia custodiens, RNA was extracted with the RNeasy Micro kit (Qiagen; Valencia, CA). The SMART cDNA library construction kit (Clontech Laboratories, Mountain View, CA) was used to construct cDNA libraries. These libraries were sequenced by The Genomic Services Lab at the Hudson Alpha Institute in Huntsville, Alabama, on the Illumina (San Diego, CA) HiSeq 2000 platform with 2x100 paired-end sequencing. To reduce memory usage during transcriptome assembly, sequencing data were digitally normalized to a k-mer coverage depth of 30 using the normalize-by-median.py script (Brown et al., 2012). Data were then assembled using Trinity (Grabherr et al., 2011; 8 June 2012 version) with default settings.</em></p>
<p><em><strong>Identification of genes</strong><br />
UniProt accession numbers for human toll-like receptor genes were obtained from InnateDB (Innate DB, 2014; Lynn et al., 2008; Breuer et al., 2013). Amino acid sequences for TLR1-TLR10 were obtained from then National Center for Biotechnology Information (NCBI; Table 2) and used for bait in a TBLASTN search (Altschul et al., 1990) against the assembled nucleotide transcriptomes. For these searches, an e-value of 10^-5 was employed and only top hits longer than 800 nucleotides (to filter out smaller gene fragments) were retained. Significant hits were translated to amino acid sequences with TransDecoder in the Trinity package (Grabherr et al., 2011), and redundant sequences were removed with cd-hit (Li and Godzik, 2006) using an identity (-c flag) of 1.0. To further confirm their identity, the translated hits were searched against the Swiss Prot database using BLASTP with an e-value cutoff of 10^-5. As TransDecoder can yield multiple translations per nucleotide sequence, all translations were subject to BLASTP, and only the best hits were retained. Sequences that returned the top hit with a significant e-value and matched to a TLR gene were retained and compared to the SMART database (SMART, 2014; Schultz et al., 1998; Letunic et al., 2012) using the "normal" search setting to identify protein domains.</em></p>
<p><em>Previous phylogenetic analyses (e.g., Zheng et al., 2005; Davidson et al., 2008) on TLR genes typically used only the TIR domain for analyses. These analyses are limited to about 140-180 amino acids in length. Here, we aligned recovered TLR contigs from lophotrochozoans and Priapulus with human and Drosophilia TLR genes using MAFFT ver. 7 (Katoh and Standley, 2013). Even after reducing the alignment to the conserved TIR domain, sequences were highly variable, resulting in a questionable alignment. Considering that the TIR domain is shared among several gene families (Aravind et al., 2001) and the variability of the alignment, we question whether a tree produced from these sequences accurately represents gene genealogy. This suspicion was confirmed by using the T-REX server (Boc et al., 2012) for a RAxML-VI-HPC (Stamatakis, 2006) analysis (parameters included PROTGAMMA, WAG, 100 bootstraps) that yielded a tree with very low nodal support value. Roughly 50% of the nodes reported a bootstrap value less than 40%, and exploring different parameters did little to improve results. We used a much broader taxon sampling than for previous TIR trees, which likely influenced variability of the alignment. Due to the questionable reliability of such a phylogenetic analysis, results are not included herein.</em></p>
Specified by the Principal Investigator(s)
<p><strong>BCO-DMO Processing notes:</strong><br />
- added conventional header with dataset name, PI name, version date<br />
- modified parameter names to conform with BCO-DMO naming conventions<br />
- reformatted to flat table by adding columns for taxon1 and taxon2</p>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
Illumina (San Diego, CA) HiSeq 2000 platform at The Genomic Services Lab at the Hudson Alpha Institute in Huntsville, Alabama,
Illumina (San Diego, CA) HiSeq 2000 platform at The Genomic Services Lab at the Hudson Alpha Institute in Huntsville, Alabama,
PI Supplied Instrument Name: Illumina (San Diego, CA) HiSeq 2000 platform at The Genomic Services Lab at the Hudson Alpha Institute in Huntsville, Alabama, Instrument Name: Automated DNA Sequencer Instrument Short Name:Automated Sequencer Instrument Description: A DNA sequencer is an instrument that determines the order of deoxynucleotides in deoxyribonucleic acid sequences.
PI Supplied Instrument Name: Instrument Name: Thermal Cycler Instrument Short Name:Thermal Cycler Instrument Description: A thermal cycler or "thermocycler" is a general term for a type of laboratory apparatus, commonly used for performing polymerase chain reaction (PCR), that is capable of repeatedly altering and maintaining specific temperatures for defined periods of time. The device has a thermal block with holes where tubes with the PCR reaction mixtures can be inserted. The cycler then raises and lowers the temperature of the block in discrete, pre-programmed steps. They can also be used to facilitate other temperature-sensitive reactions, including restriction enzyme digestion or rapid diagnostics.
(adapted from http://serc.carleton.edu/microbelife/research_methods/genomics/pcr.html)
Deployment: Halanych_lab_2011-16
Halanych_lab_2011-16
Auburn University lab
laboratory
Halanych_lab_2011-16
Kenneth M. Halanych
Auburn University
Auburn University lab
laboratory