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

NCJ Number
249285
Journal
BMC Genomics Volume: 16 Dated: January 2015
Date Published
January 2015
Author(s)
Seung Bum Seo; Xiangpei Zeng; Jonathan L. King; Bobby L. Larue; Mourad Assidi; Mohamed H. Al-Qahtani; Antti Sajantila; Bruce Budowle
Length
0 pages
Annotation
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 the current study, whole genomes of human mitochondria (mtGenome) were sequenced on the Personal Genome Machine (PGMTM) (Life Technologies, San Francisco, CA), the out data were assessed, and the results were compared with data previously generated on the MiSeqTM (Illumina, San Diego, CA). The objectives of this paper were to determine the feasibility, accuracy, and reliability of sequence data obtained from the PGM.
Abstract

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. 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. (Publisher abstract modified)

Date Published: January 1, 2015

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