BDATA

BIODIVERSITY DATA

FBIP: scallop population genetics

Latest version published by South African National Biodiversity Institute on Sep 26, 2019 South African National Biodiversity Institute

The study focused on genomic resource development for Pecten sulcicostatus followed by the quantification of genetic diversity within a single natural population, namely the False Bay Pecten sulcicostatus population. The data set represents a list of tissue samples and DNA extracts taken from live specimens and their haplotype for the 16S gene. The 16S rRNA sequences generated in this project have been submitted to GenBank to allow other researchers to access this information.

Data Records

The data in this occurrence resource has been published as a Darwin Core Archive (DwC-A), which is a standardized format for sharing biodiversity data as a set of one or more data tables. The core data table contains 37 records.

This IPT archives the data and thus serves as the data repository. The data and resource metadata are available for download in the downloads section. The versions table lists other versions of the resource that have been made publicly available and allows tracking changes made to the resource over time.

Downloads

Download the latest version of this resource data as a Darwin Core Archive (DwC-A) or the resource metadata as EML or RTF:

Data as a DwC-A file download 37 records in English (5 KB) - Update frequency: unknown
Metadata as an EML file download in English (12 KB)
Metadata as an RTF file download in English (11 KB)

Versions

The table below shows only published versions of the resource that are publicly accessible.

How to cite

Researchers should cite this work as follows:

Roodt-Wilding R (2019): FBIP: scallop population genetics. v1.0. South African National Biodiversity Institute. Dataset/Occurrence. http://ipt.sanbi.org.za/iptsanbi/resource?r=fbip_scallop_population_genetics&v=1.0

Rights

Researchers should respect the following rights statement:

The publisher and rights holder of this work is South African National Biodiversity Institute. This work is licensed under a Creative Commons Attribution (CC-BY) 4.0 License.

GBIF Registration

This resource has been registered with GBIF, and assigned the following GBIF UUID: b5899cfd-0acd-4179-8ca2-bb6fb1873941.  South African National Biodiversity Institute publishes this resource, and is itself registered in GBIF as a data publisher endorsed by South African Biodiversity Information Facility.

Keywords

Occurrence; Specimen

Contacts

Who created the resource:

Rouvay Roodt-Wilding
Associate Professor
Stellenbosch University Department of Genetics, Private Bag X1, Matieland  7602 Stellenbosch Western Cape 0218085831
http://www.sun.ac.za/english/faculty/agri/genetics/staff-students/academic-staff

Who can answer questions about the resource:

Rouvay Roodt-Wilding
Associate Professor
Stellenbosch University Department of Genetics, Private Bag X1, Matieland  7602 Stellenbosch Western Cape 0218085831
http://www.sun.ac.za/english/faculty/agri/genetics/staff-students/academic-staff

Who filled in the metadata:

Rouvay Roodt-Wilding
Associate Professor
Stellenbosch University Department of Genetics, Private Bag X1, Matieland  7602 Stellenbosch Western Cape 0218085831
http://www.sun.ac.za/english/faculty/agri/genetics/staff-students/academic-staff

Who else was associated with the resource:

Content Provider
Mahlatse Kgatla
FBIP Data Specialist
SANBI 2 Cussonia Avenue, Brummeria 0184 Pretoria Gauteng ZA 0128435196
http://fbip.co.za/contact/

Geographic Coverage

South Africa, Western Cape, False Bay

Bounding Coordinates South West [-34.191, 18.641], North East [-34.191, 18.641]

Taxonomic Coverage

All scallops identified to species

Species  Pecten sulcicostatus

Temporal Coverage

Start Date 2014-10-31

Project Data

The study focused on genomic resource development for Pecten sulcicostatus followed by the quantification of genetic diversity within a single natural population, namely the False Bay Pecten sulcicostatus population. The data set represents a list of tissue samples and DNA extracts taken from live specimens and their haplotype for the 16S gene. The 16S rRNA sequences generated in this project have been submitted to GenBank to allow other researchers to access this information.

Title Scallop population genetics
Identifier IBSG13052118234
Funding Foundational Biodiversity Information Programme
Study Area Description South Africa, Western Cape, False Bay
Design Description 16S rRNA mitochondrial sequences were generated for Pecten sulcicostatus specimens collected at False Bay by scuba. Samples were collected from live specimens in their natural habitat using non-lethal methods.

The personnel involved in the project:

Principal Investigator
Rouvay Roodt-Wilding

Sampling Methods

-Study populations and specimen collection. -Establishment of genomic resources and molecular marker development. -Population genetic analyses.

Study Extent False Bay, 20-40m depth

Method step description:

  1. Study populations and specimen collection (6 months: January 2014 - June 2014): This study will focus on the broad geographic distribution of Pecten sulcicostatus within its natural distribution range, taking into account the three marine bio-geographical provinces of South Africa and major barriers to gene flow. Specimens will be collected from False bay, representing the western geographical distribution extreme (west of the Agulhas upwelling; a major bio-geographical barrier to many marine species around the South African coast); Mossel bay (south coast sampling location, between the Agulhas upwelling and thermal front at Algoa bay); Algoa bay, representing a secondary bio-geographical barrier (thermal front) and East London, representing the eastern geographical distribution extreme (east of the thermal front at Algoa bay). Fifty specimens will be collected from each of the four sampling locations, 200 specimens in total. Establishment of genomic resources and molecular marker development (5 months: February 2014 - June 2014): The FIASCO/454 microsatellite-marker isolation technique that has been shown to be a high-throughput, time- and cost-effective protocol for marker development in uncharacterized species will be employed: Firstly, a genomic library enriched for microsatellite repeat motifs will be generated via the FIASCO protocol. This will be followed by next generation, pyrosequencing (454 – GS FLX system) to determine the nucleotide composition and sequence of the genomic fragments. Raw sequence data will be subject to quality control and individual reads will be assembled into contigs to eliminate sequence redundancy. Using appropriate algorithms, contigs and singleton reads will be screened for repetitive microsatellite motifs. Primers will be designed and optimized for PCR amplification of each microsatellite locus. Polymorphism will be tested by means of polyacrylamide gel electrophoresis. Finally, primers for polymorphic loci will be labelled with fluorescent dyes for genotyping using capillary electrophoresis and optimized into multiplex reactions for diagnostic standardization. Population genetic analyses (6 months: July 2014 - December 2014): Each individual within the study cohort will be genotyped for each of the developed microsatellite markers. The genotype data will be employed to evaluate panmixia, population differentiation and the compartmentalization of intra- and interspecific genetic diversity. In order to evaluate intraspecific genetic diversity the following estimates will be calculated for each population: heterozygosity, number of alleles, effective number of alleles and information (Shannon-Weaver) index. In order to assess interspecific population diversity, pairwise Fst and analogous statistics will be estimated, as well as the following analyses: analysis of molecular variance (AMOVA) and principle coordinate analysis (PCoA). To further evaluate the genetic relationship amongst populations, population-trees (using genetic distance estimates and phylogenetic clustering algorithms) will be constructed and a Bayesian clustering algorithm will be implemented to evaluate the number of distinct genetic populations. Contemporary population size and evidence for population expansions or contractions will also be investigated to obtain a understanding of how demographic factors may influence genetic diversity.