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The Next Generation of Molecular Markers From Massively Parallel Sequencing of Pooled DNA Samples

Open access
Futschik, Andreas, Schlötterer, Christian·2010·Genetics

Abstract

Next generation sequencing (NGS) is about to revolutionize genetic analysis. Currently NGS techniques are mainly used to sequence individual genomes. Due to the high sequence coverage required, the costs for population-scale analyses are still too high to allow an extension to nonmodel organisms. Here, we show that NGS of pools of individuals is often more effective in SNP discovery and provides more accurate allele frequency estimates, even when taking sequencing errors into account. We modify the population genetic estimators Tajima's π and Watterson's θ to obtain unbiased estimates from NGS pooling data. Given the same sequencing effort, the resulting estimators often show a better performance than those obtained from individual sequencing. Although our analysis also shows that NGS of pools of individuals will not be preferable under all circumstances, it provides a cost-effective approach to estimate allele frequencies on a genome-wide scale.

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Metadata

Authors
Futschik, A., & Schlötterer, C.
Venue
Genetics
Published
2010-09-01
Volume
186
Issue
1
Pages
207-218
ISSN
  • 0016-6731 (ISSN-L)
  • 1943-2631
OpenAlex
W2133372013
Cited by
373
References
12
FWCI
10.40
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: The Next Generation of Molecular Markers From Massively Parallel Sequencing of Pooled DNA Samples. https://app.cochat.ai/papers/10.1534/genetics.110.114397
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Futschik, A., & Schlötterer, C. (2010). The Next Generation of Molecular Markers From Massively Parallel Sequencing of Pooled DNA Samples. Genetics. https://doi.org/10.1534/genetics.110.114397

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.