FBIP: scallop population genetics

出現紀錄
最新版本 published by South African National Biodiversity Institute on 九月 26, 2019 South African National Biodiversity Institute
發布日期:
2019年9月26日
授權條款:
CC-BY 4.0

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說明

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.

資料紀錄

此資源出現紀錄的資料已發佈為達爾文核心集檔案(DwC-A),其以一或多組資料表構成分享生物多樣性資料的標準格式。 核心資料表包含 37 筆紀錄。

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版本

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如何引用

研究者應依照以下指示引用此資源。:

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

權利

研究者應尊重以下權利聲明。:

此資料的發布者及權利單位為 South African National Biodiversity Institute。 This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.

GBIF 註冊

此資源已向GBIF註冊,並指定以下之GBIF UUID: b5899cfd-0acd-4179-8ca2-bb6fb1873941。  South African National Biodiversity Institute 發佈此資源,並經由South African Biodiversity Information Facility同意向GBIF註冊成為資料發佈者。

關鍵字

Occurrence; Specimen

聯絡資訊

Rouvay Roodt-Wilding
  • 元數據提供者
  • 出處
  • 連絡人
Associate Professor
Stellenbosch University
Department of Genetics, Private Bag X1, Matieland 
7602 Stellenbosch
Western Cape
0218085831
Mahlatse Kgatla
  • 內容提供者
FBIP Data Specialist
SANBI
2 Cussonia Avenue, Brummeria
0184 Pretoria
Gauteng
ZA
0128435196

地理涵蓋範圍

South Africa, Western Cape, False Bay

界定座標範圍 緯度南界 經度西界 [-34.191, 18.641], 緯度北界 經度東界 [-34.191, 18.641]

分類群涵蓋範圍

All scallops identified to species

Species Pecten sulcicostatus

時間涵蓋範圍

起始日期 2014-10-31

計畫資料

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.

計畫名稱 Scallop population genetics
辨識碼 IBSG13052118234
經費來源 Foundational Biodiversity Information Programme
研究區域描述 South Africa, Western Cape, False Bay
研究設計描述 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.

參與計畫的人員:

Rouvay Roodt-Wilding
  • 研究主持人

取樣方法

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

研究範圍 False Bay, 20-40m depth

方法步驟描述:

  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.