FBIP: scallop population genetics

データ レコード

この オカレンス（観察データと標本) リソース内のデータは、1 つまたは複数のデータ テーブルとして生物多様性データを共有するための標準化された形式であるダーウィン コア アーカイブ (DwC-A) として公開されています。 コア データ テーブルには、37 レコードが含まれています。

この IPT はデータをアーカイブし、データ リポジトリとして機能します。データとリソースのメタデータは、 ダウンロード セクションからダウンロードできます。 バージョン テーブルから公開可能な他のバージョンを閲覧でき、リソースに加えられた変更を知ることができます。

バージョン

次の表は、公にアクセス可能な公開バージョンのリソースのみ表示しています。

引用方法

研究者はこの研究内容を以下のように引用する必要があります。:

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

権利

研究者は権利に関する下記ステートメントを尊重する必要があります。:

パブリッシャーとライセンス保持者権利者は South African National Biodiversity Institute。 This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.

GBIF登録

このリソースをはGBIF と登録されており GBIF UUID: b5899cfd-0acd-4179-8ca2-bb6fb1873941が割り当てられています。   South African Biodiversity Information Facility によって承認されたデータ パブリッシャーとして GBIF に登録されているSouth African National Biodiversity Institute が、このリソースをパブリッシュしました。

キーワード

Occurrence; Specimen

連絡先

地理的範囲

South Africa, Western Cape, False Bay

生物分類学的範囲

All scallops identified to species

時間的範囲

プロジェクトデータ

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.

プロジェクトに携わる要員:

収集方法

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

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.

追加のメタデータ