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Multiplexed Microsatellite Recovery Using Massively Parallel Sequencing

dataset
posted on 2024-06-11, 07:19 authored by USDA Forest Service, United States of America
Conservation and management of natural populations requires accurate and inexpensive genotyping methods. Traditional microsatellite, or simple sequence repeat (SSR), marker analysis remains a popular genotyping method due to the comparatively low cost of marker development, ease of analysis, and high power of genotype discrimination. With the availability of massively parallel sequencing (MPS), it is now possible to sequence microsatellite-enriched genomic libraries in multiplex pools. To test this approach, we prepared seven microsatellite enriched, barcoded genomic libraries from diverse taxa (two conifers trees, five birds) and sequenced these on one lane of the Illumina Genome Analyzer using paired-end 80 bp reads. In this experiment, we recovered 6.1 million sequences, 1.4 million of which contained dinucleotide microsatellites. Examination of four species shows that our conversion rate from raw sequences to polymorphic markers compares favorably to Sanger- and 454-based methods. The advantage of multiplexed MPS is that the staggering sequence capacity of modern sequencing is spread across many libraries; this reduces sample preparation and sequencing costs to less than $500 (USD) per species. This price is sufficiently low that microsatellite libraries could be prepared and sequenced for all 1373 organisms listed as .threatened. and .endangered. in the United States for under $0.7M.

History

Data contact name

BioProject Curation Staff

Publisher

National Center for Biotechnology Information

Temporal Extent Start Date

2011-04-25

Theme

  • Non-geospatial

ISO Topic Category

  • biota

National Agricultural Library Thesaurus terms

genetics

Pending citation

  • No

Public Access Level

  • Public

Accession Number

PRJEB2513

Preferred dataset citation

It is recommended to cite the accession numbers that are assigned to data submissions, e.g. the GenBank, WGS or SRA accession numbers. If individual BioProjects need to be referenced, state that "The data have been deposited with links to BioProject accession number PRJNA204293 in the NCBI BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/)."

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