Published August 10, 2016 | Version v1
Dataset Open

Data from: High-throughput microsatellite genotyping in ecology: improved accuracy, efficiency, standardization and success with low-quantity and degraded DNA

  • 1. Centre national de la recherche scientifique
  • 2. Laboratoire d'Écologie Alpine
  • 3. Norwegian University of Life Sciences

Description

Microsatellite markers have played a major role in ecological, evolutionary and conservation research during the past 20 years. However, technical constrains related to the use of capillary electrophoresis and a recent technological revolution that has impacted other marker types have brought to question the continued use of microsatellites for certain applications. We present a study for improving microsatellite genotyping in ecology using high-throughput sequencing (HTS). This approach entails selection of short markers suitable for HTS, sequencing PCR-amplified microsatellites on an Illumina platform and bioinformatic treatment of the sequence data to obtain multilocus genotypes. It takes advantage of the fact that HTS gives direct access to microsatellite sequences, allowing unambiguous allele identification and enabling automation of the genotyping process through bioinformatics. In addition, the massive parallel sequencing abilities expand the information content of single experimental runs far beyond capillary electrophoresis. We illustrated the method by genotyping brown bear samples amplified with a multiplex PCR of 13 new microsatellite markers and a sex marker. HTS of microsatellites provided accurate individual identification and parentage assignment and resulted in a significant improvement of genotyping success (84%) of faecal degraded DNA and costs reduction compared to capillary electrophoresis. The HTS approach holds vast potential for improving success, accuracy, efficiency and standardization of microsatellite genotyping in ecological and conservation applications, especially those that rely on profiling of low-quantity/quality DNA and on the construction of genetic databases. We discuss and give perspectives for the implementation of the method in the light of the challenges encountered in wildlife studies.

Notes

Files

obitools_script.txt

Files (5.1 GB)

Name Size Download all
md5:dd269f44832b32d3cc2ba089c6fdaf6c
166.4 MB Download
md5:24b394346c853e2d86fef0833b89efa3
5.9 kB Preview Download
md5:0d2daaebc6fcdca0d2853124d3ccd9f1
165.4 kB Preview Download
md5:9bd0de0d4eb7253946fe15c82c777742
1.2 GB Download
md5:109fc8059d781715f1a55c85b77789c7
1.4 GB Download
md5:557383946cb9581bd930192489e91c1c
20.5 kB Download
md5:79699a6d33e4f2711dfc41c37941817d
1.1 GB Download
md5:b666c8e177e76752caf8afb18209a34c
1.2 GB Download
md5:0c0c188ba3302bfcb53f01414b745bfd
371 Bytes Preview Download

Additional details

Related works

Is cited by
10.1111/1755-0998.12594 (DOI)