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Underlying Data for Sequencing the Mitochondrial Genome with the Massively Parallel Sequencing Platform Ion Torrent(™) PGM(™)

BACKGROUND: Massively parallel sequencing (MPS) technologies have the capacity to sequence targeted regions or whole genomes of multiple nucleic acid samples with high coverage by sequencing millions of DNA fragments simultaneously. Compared with Sanger sequencing, MPS also can reduce labor and cost...

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Autores principales: Seo, Seung Bum, Zeng, Xiangpei, King, Jonathan L, Larue, Bobby L, Assidi, Mourad, Al-Qahtani, Mohamed H, Sajantila, Antti, Budowle, Bruce
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4315160/
https://www.ncbi.nlm.nih.gov/pubmed/25924014
http://dx.doi.org/10.1186/1471-2164-16-S1-S4
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author Seo, Seung Bum
Zeng, Xiangpei
King, Jonathan L
Larue, Bobby L
Assidi, Mourad
Al-Qahtani, Mohamed H
Sajantila, Antti
Budowle, Bruce
author_facet Seo, Seung Bum
Zeng, Xiangpei
King, Jonathan L
Larue, Bobby L
Assidi, Mourad
Al-Qahtani, Mohamed H
Sajantila, Antti
Budowle, Bruce
author_sort Seo, Seung Bum
collection PubMed
description BACKGROUND: Massively parallel sequencing (MPS) technologies have the capacity to sequence targeted regions or whole genomes of multiple nucleic acid samples with high coverage by sequencing millions of DNA fragments simultaneously. Compared with Sanger sequencing, MPS also can reduce labor and cost on a per nucleotide basis and indeed on a per sample basis. In this study, whole genomes of human mitochondria (mtGenome) were sequenced on the Personal Genome Machine (PGM(TM)) (Life Technologies, San Francisco, CA), the out data were assessed, and the results were compared with data previously generated on the MiSeq(TM) (Illumina, San Diego, CA). The objectives of this paper were to determine the feasibility, accuracy, and reliability of sequence data obtained from the PGM. RESULTS: 24 samples were multiplexed (in groups of six) and sequenced on the at least 10 megabase throughput 314 chip. The depth of coverage pattern was similar among all 24 samples; however the coverage across the genome varied. For strand bias, the average ratio of coverage between the forward and reverse strands at each nucleotide position indicated that two-thirds of the positions of the genome had ratios that were greater than 0.5. A few sites had more extreme strand bias. Another observation was that 156 positions had a false deletion rate greater than 0.15 in one or more individuals. There were 31-98 (SNP) mtGenome variants observed per sample for the 24 samples analyzed. The total 1237 (SNP) variants were concordant between the results from the PGM and MiSeq. The quality scores for haplogroup assignment for all 24 samples ranged between 88.8%-100%. CONCLUSIONS: In this study, mtDNA sequence data generated from the PGM were analyzed and the output evaluated. Depth of coverage variation and strand bias were identified but generally were infrequent and did not impact reliability of variant calls. Multiplexing of samples was demonstrated which can improve throughput and reduce cost per sample analyzed. Overall, the results of this study, based on orthogonal concordance testing and phylogenetic scrutiny, supported that whole mtGenome sequence data with high accuracy can be obtained using the PGM platform.
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spelling pubmed-43151602015-02-09 Underlying Data for Sequencing the Mitochondrial Genome with the Massively Parallel Sequencing Platform Ion Torrent(™) PGM(™) Seo, Seung Bum Zeng, Xiangpei King, Jonathan L Larue, Bobby L Assidi, Mourad Al-Qahtani, Mohamed H Sajantila, Antti Budowle, Bruce BMC Genomics Research BACKGROUND: Massively parallel sequencing (MPS) technologies have the capacity to sequence targeted regions or whole genomes of multiple nucleic acid samples with high coverage by sequencing millions of DNA fragments simultaneously. Compared with Sanger sequencing, MPS also can reduce labor and cost on a per nucleotide basis and indeed on a per sample basis. In this study, whole genomes of human mitochondria (mtGenome) were sequenced on the Personal Genome Machine (PGM(TM)) (Life Technologies, San Francisco, CA), the out data were assessed, and the results were compared with data previously generated on the MiSeq(TM) (Illumina, San Diego, CA). The objectives of this paper were to determine the feasibility, accuracy, and reliability of sequence data obtained from the PGM. RESULTS: 24 samples were multiplexed (in groups of six) and sequenced on the at least 10 megabase throughput 314 chip. The depth of coverage pattern was similar among all 24 samples; however the coverage across the genome varied. For strand bias, the average ratio of coverage between the forward and reverse strands at each nucleotide position indicated that two-thirds of the positions of the genome had ratios that were greater than 0.5. A few sites had more extreme strand bias. Another observation was that 156 positions had a false deletion rate greater than 0.15 in one or more individuals. There were 31-98 (SNP) mtGenome variants observed per sample for the 24 samples analyzed. The total 1237 (SNP) variants were concordant between the results from the PGM and MiSeq. The quality scores for haplogroup assignment for all 24 samples ranged between 88.8%-100%. CONCLUSIONS: In this study, mtDNA sequence data generated from the PGM were analyzed and the output evaluated. Depth of coverage variation and strand bias were identified but generally were infrequent and did not impact reliability of variant calls. Multiplexing of samples was demonstrated which can improve throughput and reduce cost per sample analyzed. Overall, the results of this study, based on orthogonal concordance testing and phylogenetic scrutiny, supported that whole mtGenome sequence data with high accuracy can be obtained using the PGM platform. BioMed Central 2015-01-15 /pmc/articles/PMC4315160/ /pubmed/25924014 http://dx.doi.org/10.1186/1471-2164-16-S1-S4 Text en Copyright © 2015 Seo et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Seo, Seung Bum
Zeng, Xiangpei
King, Jonathan L
Larue, Bobby L
Assidi, Mourad
Al-Qahtani, Mohamed H
Sajantila, Antti
Budowle, Bruce
Underlying Data for Sequencing the Mitochondrial Genome with the Massively Parallel Sequencing Platform Ion Torrent(™) PGM(™)
title Underlying Data for Sequencing the Mitochondrial Genome with the Massively Parallel Sequencing Platform Ion Torrent(™) PGM(™)
title_full Underlying Data for Sequencing the Mitochondrial Genome with the Massively Parallel Sequencing Platform Ion Torrent(™) PGM(™)
title_fullStr Underlying Data for Sequencing the Mitochondrial Genome with the Massively Parallel Sequencing Platform Ion Torrent(™) PGM(™)
title_full_unstemmed Underlying Data for Sequencing the Mitochondrial Genome with the Massively Parallel Sequencing Platform Ion Torrent(™) PGM(™)
title_short Underlying Data for Sequencing the Mitochondrial Genome with the Massively Parallel Sequencing Platform Ion Torrent(™) PGM(™)
title_sort underlying data for sequencing the mitochondrial genome with the massively parallel sequencing platform ion torrent(™) pgm(™)
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4315160/
https://www.ncbi.nlm.nih.gov/pubmed/25924014
http://dx.doi.org/10.1186/1471-2164-16-S1-S4
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