Cargando…

Estimating Allele Frequency from Next-Generation Sequencing of Pooled Mitochondrial DNA Samples

Background: Both common and rare mitochondrial DNA (mtDNA) variants may contribute to genetic susceptibility to some complex human diseases. Understanding of the role of mtDNA variants will provide valuable insights into the etiology of these diseases. However, to date, there have not been any large...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Tao, Pradhan, Kith, Ye, Kenny, Wong, Lee-Jun, Rohan, Thomas E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3268604/
https://www.ncbi.nlm.nih.gov/pubmed/22303347
http://dx.doi.org/10.3389/fgene.2011.00051
_version_ 1782222388980613120
author Wang, Tao
Pradhan, Kith
Ye, Kenny
Wong, Lee-Jun
Rohan, Thomas E.
author_facet Wang, Tao
Pradhan, Kith
Ye, Kenny
Wong, Lee-Jun
Rohan, Thomas E.
author_sort Wang, Tao
collection PubMed
description Background: Both common and rare mitochondrial DNA (mtDNA) variants may contribute to genetic susceptibility to some complex human diseases. Understanding of the role of mtDNA variants will provide valuable insights into the etiology of these diseases. However, to date, there have not been any large-scale, genome-wide association studies of complete mtDNA variants and disease risk. One reason for this might be the substantial cost of sequencing the large number of samples required for genetic epidemiology studies. Next-generation sequencing of pooled mtDNA samples will dramatically reduce the cost of such studies and may represent an appealing approach for large-scale genetic epidemiology studies. However, the performance of the different designs of sequencing pooled mtDNA has not been evaluated. Methods: We examined the approach of sequencing pooled mtDNA of multiple individuals for estimating allele frequency using the Illumina genome analyzer (GA) II sequencing system. In this study the pool included mtDNA samples of 20 subjects that had been sequenced previously using Sanger sequencing. Each pool was replicated once to assess variation of the sequencing error between pools. To reduce such variation, barcoding was used for sequencing different pools in the same lane of the flow cell. To evaluate the effect of different pooling strategies pooling was done at both the pre- and post-PCR amplification step. Results: The sequencing error rate was close to that expected based on the Phred score. When only reads with Phred ≥ 20 were considered, the average error rate was about 0.3%. However, there was significant variation of the base-calling errors for different types of bases or at different loci. Using the results of the Sanger sequencing as the standard, the sensitivity of single nucleotide polymorphism detection with post-PCR pooling (about 99%) was higher than that of the pre-PCR pooling (about 82%), while the two approaches had similar specificity (about 99%). Among a total of 298 variants in the sample, the allele frequencies of 293 variants (98%) were correctly estimated with post-PCR pooling, the correlation between the estimated and the true allele frequencies being >0.99, while only 206 allele frequencies (69%) were correctly estimated in the pre-PCR pooling, the correlation being 0.89. Conclusion: Sequencing of mtDNA pooled after PCR amplification is a viable tool for screening mitochondrial variants potentially related to human diseases.
format Online
Article
Text
id pubmed-3268604
institution National Center for Biotechnology Information
language English
publishDate 2011
publisher Frontiers Research Foundation
record_format MEDLINE/PubMed
spelling pubmed-32686042012-02-02 Estimating Allele Frequency from Next-Generation Sequencing of Pooled Mitochondrial DNA Samples Wang, Tao Pradhan, Kith Ye, Kenny Wong, Lee-Jun Rohan, Thomas E. Front Genet Genetics Background: Both common and rare mitochondrial DNA (mtDNA) variants may contribute to genetic susceptibility to some complex human diseases. Understanding of the role of mtDNA variants will provide valuable insights into the etiology of these diseases. However, to date, there have not been any large-scale, genome-wide association studies of complete mtDNA variants and disease risk. One reason for this might be the substantial cost of sequencing the large number of samples required for genetic epidemiology studies. Next-generation sequencing of pooled mtDNA samples will dramatically reduce the cost of such studies and may represent an appealing approach for large-scale genetic epidemiology studies. However, the performance of the different designs of sequencing pooled mtDNA has not been evaluated. Methods: We examined the approach of sequencing pooled mtDNA of multiple individuals for estimating allele frequency using the Illumina genome analyzer (GA) II sequencing system. In this study the pool included mtDNA samples of 20 subjects that had been sequenced previously using Sanger sequencing. Each pool was replicated once to assess variation of the sequencing error between pools. To reduce such variation, barcoding was used for sequencing different pools in the same lane of the flow cell. To evaluate the effect of different pooling strategies pooling was done at both the pre- and post-PCR amplification step. Results: The sequencing error rate was close to that expected based on the Phred score. When only reads with Phred ≥ 20 were considered, the average error rate was about 0.3%. However, there was significant variation of the base-calling errors for different types of bases or at different loci. Using the results of the Sanger sequencing as the standard, the sensitivity of single nucleotide polymorphism detection with post-PCR pooling (about 99%) was higher than that of the pre-PCR pooling (about 82%), while the two approaches had similar specificity (about 99%). Among a total of 298 variants in the sample, the allele frequencies of 293 variants (98%) were correctly estimated with post-PCR pooling, the correlation between the estimated and the true allele frequencies being >0.99, while only 206 allele frequencies (69%) were correctly estimated in the pre-PCR pooling, the correlation being 0.89. Conclusion: Sequencing of mtDNA pooled after PCR amplification is a viable tool for screening mitochondrial variants potentially related to human diseases. Frontiers Research Foundation 2011-08-17 /pmc/articles/PMC3268604/ /pubmed/22303347 http://dx.doi.org/10.3389/fgene.2011.00051 Text en Copyright © 2011 Wang, Pradhan, Ye, Wong and Rohan. http://www.frontiersin.org/licenseagreement This is an open-access article subject to a non-exclusive license between the authors and Frontiers Media SA, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and other Frontiers conditions are complied with.
spellingShingle Genetics
Wang, Tao
Pradhan, Kith
Ye, Kenny
Wong, Lee-Jun
Rohan, Thomas E.
Estimating Allele Frequency from Next-Generation Sequencing of Pooled Mitochondrial DNA Samples
title Estimating Allele Frequency from Next-Generation Sequencing of Pooled Mitochondrial DNA Samples
title_full Estimating Allele Frequency from Next-Generation Sequencing of Pooled Mitochondrial DNA Samples
title_fullStr Estimating Allele Frequency from Next-Generation Sequencing of Pooled Mitochondrial DNA Samples
title_full_unstemmed Estimating Allele Frequency from Next-Generation Sequencing of Pooled Mitochondrial DNA Samples
title_short Estimating Allele Frequency from Next-Generation Sequencing of Pooled Mitochondrial DNA Samples
title_sort estimating allele frequency from next-generation sequencing of pooled mitochondrial dna samples
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3268604/
https://www.ncbi.nlm.nih.gov/pubmed/22303347
http://dx.doi.org/10.3389/fgene.2011.00051
work_keys_str_mv AT wangtao estimatingallelefrequencyfromnextgenerationsequencingofpooledmitochondrialdnasamples
AT pradhankith estimatingallelefrequencyfromnextgenerationsequencingofpooledmitochondrialdnasamples
AT yekenny estimatingallelefrequencyfromnextgenerationsequencingofpooledmitochondrialdnasamples
AT wongleejun estimatingallelefrequencyfromnextgenerationsequencingofpooledmitochondrialdnasamples
AT rohanthomase estimatingallelefrequencyfromnextgenerationsequencingofpooledmitochondrialdnasamples