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  Deep sequencing to reveal new variants in pooled DNA samples

Out, A., van Minderhout, I., Goeman, J., Ariyurek, Y., Ossowski, S., Schneeberger, K., et al. (2009). Deep sequencing to reveal new variants in pooled DNA samples. Human Mutations, 30(12), 1703-1712. doi:10.1002/humu.21122.

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 Creators:
Out, AA, Author
van Minderhout, IJHM, Author
Goeman, JJ, Author
Ariyurek, Y, Author
Ossowski, S1, Author           
Schneeberger, K1, Author           
Weigel, D1, Author                 
van Galen, M, Author
Taschner, PEM, Author
Tops, CMJ, Author
Breuning, MH, Author
van Ommen, G-JB, Author
den Dunnen, JT, Author
Devilee, P, Author
Hes, FJ, Author
Affiliations:
1Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society, ou_3375790              

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 Abstract: We evaluated massive parallel sequencing and long-range PCR (LRP) for rare variant detection and allele frequency estimation in pooled DNA samples. Exons 2 to 16 of the MUTYH gene were analyzed in breast cancer patients with Illumina's (Solexa) technology. From a pool of 287 genomic DNA samples we generated a single LRP product, while the same LRP was performed on 88 individual samples and the resulting products then pooled. Concentrations of constituent samples were measured with fluorimetry for genomic DNA and high-resolution melting curve analysis (HR-MCA) for LRP products. Illumina sequencing results were compared to Sanger sequencing data of individual samples. Correlation between allele frequencies detected by both methods was poor in the first pool, presumably because the genomic samples amplified unequally in the LRP, due to DNA quality variability. In contrast, allele frequencies correlated well in the second pool, in which all expected alleles at a frequency of 1% and higher were reliably detected, plus the majority of singletons (0.6% allele frequency). We describe custom bioinformatics and statistics to optimize detection of rare variants and to estimate required sequencing depth. Our results provide directions for designing high-throughput analyses of candidate genes.

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 Dates: 2009-12
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1002/humu.21122
PMID: 19842214
 Degree: -

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Title: Human Mutations
  Other : Hum Mut
Source Genre: Journal
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Publ. Info: New York, N.Y. : Wiley-Liss
Pages: - Volume / Issue: 30 (12) Sequence Number: - Start / End Page: 1703 - 1712 Identifier: ISSN: 1059-7794
CoNE: https://pure.mpg.de/cone/journals/resource/954925597586