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Cited by 565

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

Multiplexed DNA Sequence Capture of Mitochondrial Genomes Using PCR Products

Open access
Maricic, Tomislav, Whitten, Mark, Pääbo, Svante·2010·PLoS ONE

Abstract

BACKGROUND: To utilize the power of high-throughput sequencers, target enrichment methods have been developed. The majority of these require reagents and equipment that are only available from commercial vendors and are not suitable for the targets that are a few kilobases in length. METHODOLOGY/PRINCIPAL FINDINGS: We describe a novel and economical method in which custom made long-range PCR products are used to capture complete human mitochondrial genomes from complex DNA mixtures. We use the method to capture 46 complete mitochondrial genomes in parallel and we sequence them on a single lane of an Illumina GA(II) instrument. CONCLUSIONS/SIGNIFICANCE: This method is economical and simple and particularly suitable for targets that can be amplified by PCR and do not contain highly repetitive sequences such as mtDNA. It has applications in population genetics and forensics, as well as studies of ancient DNA.

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Crossref · 10.1371/journal.pone.0014004

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Metadata

Authors
Maricic, T., Whitten, M., & Pääbo, S.
Venue
PLoS ONE
Published
2010-11-16
Volume
5
Issue
11
Pages
e14004
ISSN
1932-6203 (ISSN-L)
OpenAlex
W1975574050
Cited by
565
References
16
FWCI
10.63
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Multiplexed DNA Sequence Capture of Mitochondrial Genomes Using PCR Products. https://app.cochat.ai/papers/10.1371/journal.pone.0014004
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Maricic, T., Whitten, M., & Pääbo, S. (2010). Multiplexed DNA Sequence Capture of Mitochondrial Genomes Using PCR Products. PLoS ONE. https://doi.org/10.1371/journal.pone.0014004

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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