Estimating genomic diversity and population differentiation – an empirical comparison of microsatellite and SNP variation in Arabidopsis halleri
dc.contributor.author
Fischer, Martin C.
dc.contributor.author
Rellstab, Christian
dc.contributor.author
Leuzinger, Marianne
dc.contributor.author
Roumet, Marie
dc.contributor.author
Gugerli, Felix
dc.contributor.author
Shimizu, Kentaro K.
dc.contributor.author
Holderegger, Rolf
dc.contributor.author
Widmer, Alex
dc.date.accessioned
2018-10-22T12:40:06Z
dc.date.available
2017-06-12T18:07:10Z
dc.date.available
2018-10-22T12:40:06Z
dc.date.issued
2017-01
dc.identifier.issn
1471-2164
dc.identifier.other
10.1186/s12864-016-3459-7
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/125486
dc.identifier.doi
10.3929/ethz-b-000125486
dc.description.abstract
Background
Microsatellite markers are widely used for estimating genetic diversity within and differentiation among populations. However, it has rarely been tested whether such estimates are useful proxies for genome-wide patterns of variation and differentiation. Here, we compared microsatellite variation with genome-wide single nucleotide polymorphisms (SNPs) to assess and quantify potential marker-specific biases and derive recommendations for future studies. Overall, we genotyped 180 Arabidopsis halleri individuals from nine populations using 20 microsatellite markers. Twelve of these markers were originally developed for Arabidopsis thaliana (cross-species markers) and eight for A. halleri (species-specific markers). We further characterized 2 million SNPs across the genome with a pooled whole-genome re-sequencing approach (Pool-Seq).
Results
Our analyses revealed that estimates of genetic diversity and differentiation derived from cross-species and species-specific microsatellites differed substantially and that expected microsatellite heterozygosity (SSR-H e) was not significantly correlated with genome-wide SNP diversity estimates (SNP-H e and θ Watterson) in A. halleri. Instead, microsatellite allelic richness (A r) was a better proxy for genome-wide SNP diversity. Estimates of genetic differentiation among populations (F ST) based on both marker types were correlated, but microsatellite-based estimates were significantly larger than those from SNPs. Possible causes include the limited number of microsatellite markers used, marker ascertainment bias, as well as the high variance in microsatellite-derived estimates. In contrast, genome-wide SNP data provided unbiased estimates of genetic diversity independent of whether genome- or only exome-wide SNPs were used. Further, we inferred that a few thousand random SNPs are sufficient to reliably estimate genome-wide diversity and to distinguish among populations differing in genetic variation.
Conclusions
We recommend that future analyses of genetic diversity within and differentiation among populations use randomly selected high-throughput sequencing-based SNP data to draw conclusions on genome-wide diversity patterns. In species comparable to A. halleri, a few thousand SNPs are sufficient to achieve this goal.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
BioMed Central
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Microsatellites
en_US
dc.subject
SSR
en_US
dc.subject
Arabidopsis halleri
en_US
dc.subject
Genetic diversity
en_US
dc.subject
Expected heterozygosity
en_US
dc.subject
SNPs
en_US
dc.subject
Population genomics
en_US
dc.subject
Whole-genome re-sequencing
en_US
dc.subject
Pool-Seq
en_US
dc.subject
Conservation units
en_US
dc.title
Estimating genomic diversity and population differentiation – an empirical comparison of microsatellite and SNP variation in Arabidopsis halleri
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
BMC Genomics
ethz.journal.volume
18
en_US
ethz.journal.abbreviated
BMC Genomics
ethz.pages.start
69
en_US
ethz.size
15 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02720 - Institut für Integrative Biologie / Institute of Integrative Biology::03706 - Widmer, Alexander / Widmer, Alexander
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02720 - Institut für Integrative Biologie / Institute of Integrative Biology::03706 - Widmer, Alexander / Widmer, Alexander
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02720 - Institut für Integrative Biologie / Institute of Integrative Biology::03706 - Widmer, Alexander / Widmer, Alexander
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02720 - Institut für Integrative Biologie / Institute of Integrative Biology::03706 - Widmer, Alexander / Widmer, Alexander
ethz.date.deposited
2017-06-12T18:07:23Z
ethz.source
ECIT
ethz.identifier.importid
imp59365510d9b3191629
ethz.ecitpid
pub:188090
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-26T06:11:01Z
ethz.rosetta.lastUpdated
2023-02-06T16:04:24Z
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true
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true
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