Accessions and links for DNA sequences for three genes (COI, 16S, H3) from 18 species in order Sacoglossa (Gastropoda) from Krug et al (2011) Invert. Syst. (PLDvFST project)

Website: https://www.bco-dmo.org/dataset/682221
Data Type: Other Field Results
Version:
Version Date: 2017-02-14

Project
» Quantifying larval behavior to reconcile genetic connectivity with biophysical model predictions (PLDvFST)
ContributorsAffiliationRole
Krug, PatrickCalifornia State University Los Angeles (Cal State LA)Principal Investigator
Copley, NancyWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager


Dataset Description

Sequences were generated for 18 other species in clade Sacoglossa sampled globally. Collection information, accessions and links to the GenBank pages are provided.

Related Reference: Krug, P.J., Händeler, K., and J.E. Vendetti. 2011. Genes, morphology, development and photosynthetic ability support the resurrection of Elysia cornigera (Heterobranchia: Plakobranchoidea) as distinct from the solar-powered sea slug E. timida. Invertebrate Systematics, 25: 477–489. doi: 0.1071/IS11026. (print publication in 2012)


Methods & Sampling

Purified PCR products were directly cycle-sequenced in both directions using PCR primers and Big Dye Terminator 3.1 Cycle Sequencing chemistry at the High-Throughput Genomics Unit, University of Washington or on an ABI PrismTM 377 DNA Sequencer (Applied Biosystems).  Chromatograms were edited and primer sequences removed in GeneiousPro 4.8 software.

For full details on sampling and analytical methodology, see Krug et al (2011)


Data Processing Description

Sequences were edited to remove primer sequences.

BCO-DMO Processing notes:
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
- added links to NCBI accessions
- spelled out genus names
- replaced hyphens with 'did_not_amplify'


[ table of contents | back to top ]

Data Files

File
dataset3_Supp1_Krug_2011.csv
(Comma Separated Values (.csv), 14.98 KB)
MD5:5b5523a5ef8fc479c4c0d15f28167dd7
Primary data file for dataset ID 682221

[ table of contents | back to top ]

Parameters

ParameterDescriptionUnits
species

species name

unitless
sample_code

sample identifier

unitless
collection_locality

place of collection

unitless
collector

collector's name

unitless
date_collected

date collected

unitless
accession_COI

COI gene GenBank accession number

unitless
accession_16S

16S gene GenBank accession number

unitless
accession_H3

H3 gene GenBank accession number

unitless
accession_COI_link

link to COI gene GenBank accession page

unitless
accession_16S_link

link to 16S gene GenBank accession page

unitless
accession_H3_link

link to H3 gene GenBank accession page

unitless


[ table of contents | back to top ]

Instruments

Dataset-specific Instrument Name
Generic Instrument Name
Automated DNA Sequencer
Dataset-specific Description
Big Dye Terminator 3.1 Cycle Sequencing chemistry at the High-Throughput Genomics Unit, University of Washington or on an ABI PrismTM 377 DNA Sequencer (Applied Biosystems).
Generic Instrument Description
General term for a laboratory instrument used for deciphering the order of bases in a strand of DNA. Sanger sequencers detect fluorescence from different dyes that are used to identify the A, C, G, and T extension reactions. Contemporary or Pyrosequencer methods are based on detecting the activity of DNA polymerase (a DNA synthesizing enzyme) with another chemoluminescent enzyme. Essentially, the method allows sequencing of a single strand of DNA by synthesizing the complementary strand along it, one base pair at a time, and detecting which base was actually added at each step.

Dataset-specific Instrument Name
Generic Instrument Name
Thermal Cycler
Generic 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)


[ table of contents | back to top ]

Deployments

Krug_lab

Website
Platform
Cal State LA
Start Date
2011-09-01
End Date
2016-07-31
Description
Studies on ecology and evolution of marine animals, focusing on larval stages.


[ table of contents | back to top ]

Project Information

Quantifying larval behavior to reconcile genetic connectivity with biophysical model predictions (PLDvFST)

Coverage: Florida and Caribbean


Dispersal is a critical life-history trait linking ecological and evolutionary processes. Transport of planktonic larvae affects colonization success and population persistence for benthic animals, and influences genetic subdivision of populations, local adaptation, and speciation. However, recent studies question the long-held assumption that pelagic larval duration (PLD) determines how far larvae are advected. This has applied significance, as oceanographic models used to predict exchange among marine protected areas often use PLD as the key larval parameter. The investigators' data for Caribbean gastropods show genetic breaks that are not congruent with model predictions, and levels of structure that are inconsistent with larval lifespan, highlighting a need for new theory.

This research will integrate molecular and larval ecology to test the link between dispersal and larval duration in a phylogenetic framework, and determine whether Individual Based Models (IBMs) accurately predict exchange for Caribbean reef ecosystems. The PI will collect multi-locus genetic data and quantify larval behavior for 14 related, ecologically similar species of sea slugs with PLDs from 0-30 days. The PI predicts that larval behavior explains why some species are under- or over-dispersed relative to their PLD; this work will reveal key parameters needed for biophysical-coupling models to predict connectivity for coastal invertebrates. The proposal will address 3 inter-related objectives: (1) Are genetic connectivity estimates from mtDNA and nuclear markers congruent, and consistent with model predictions? Data for mitochondrial and nuclear loci will be used to test for selection on mtDNA, estimate rates of gene flow and times of divergence, and assess levels of connectivity within each species. Matrices of model-predicted exchange will be compared with genetic similarity matrices to test whether breaks in gene flow occur where predicted. (2) Are genetic connectivity and PLD correlated? More broadly, the PI will test the assumption that larval period determines dispersal, using comparative methods in a phylogenetic framework to correct for effects of relatedness among species. The PI will compare models of trait evolution with Bayesian Markov chain Monte Carlo (MCMC) methods to determine if gene flow is correlated or uncorrelated with PLD, using a molecular phylogeny and multi-locus genetic data. (3) Does larval behavior explain genetic structure in species with long PLD? At least two of the focal species selected for this study are under-dispersed, with genetically isolated demes despite a 30-day PLD. Conversely, at least one short-PLD species has no genetic structure over large regions of the Caribbean. The PI will build on past work quantifying larval behavior to ask if species-specific differences in larval swimming facilitate local retention, making species deviate from expected connectivity patterns. The PI will also test whether pre-competent larvae respond to habitat cues in a way that influences dispersal, as occurs in fish. This work will reconcile life-history theory, oceanographic models, and genetics by mechanistically explaining breaks in connectivity; the results will deepen our understanding of how larval behavior can determine the pace of divergence among populations.

 



[ table of contents | back to top ]

Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)

[ table of contents | back to top ]