FBIP: scallop population genetics

Registros de Dados

Os dados deste recurso de ocorrência foram publicados como um Darwin Core Archive (DwC-A), que é o formato padronizado para compartilhamento de dados de biodiversidade como um conjunto de uma ou mais tabelas de dados. A tabela de dados do núcleo contém 37 registros.

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

Baixe a última versão do recurso de dados, como um Darwin Core Archive (DwC-A) ou recurso de metadados, como EML ou RTF:

Versões

A tabela abaixo mostra apenas versões de recursos que são publicamente acessíveis.

Como citar

Pesquisadores deveriam citar esta obra da seguinte maneira:

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

Direitos

Pesquisadores devem respeitar a seguinte declaração de direitos:

O editor e o detentor dos direitos deste trabalho é South African National Biodiversity Institute. This work is licensed under a Creative Commons Attribution (CC-BY) 4.0 License.

GBIF Registration

Este recurso foi registrado no GBIF e atribuído ao seguinte GBIF UUID: b5899cfd-0acd-4179-8ca2-bb6fb1873941.  South African National Biodiversity Institute publica este recurso, e está registrado no GBIF como um publicador de dados aprovado por South African Biodiversity Information Facility.

Palavras-chave

Occurrence; Specimen

Contatos

Cobertura Geográfica

South Africa, Western Cape, False Bay

Cobertura Taxonômica

All scallops identified to species

Cobertura Temporal

Dados Sobre o Projeto

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.

O pessoal envolvido no projeto:

Métodos de Amostragem

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

Descrição dos passos do método:

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.

Metadados Adicionais