DNA RESEQUENCING continued
quantification will always be more accurate and specific (measuring DNA only).
Analytical variability
Sequencing MiSeq (Illumina, San Diego, Calif.) and Ion Personal Genome Medicine (PGM) (Ion Torrent/ Life Technologies, Carlsbad, Calif.) benchtop sequencers are often used for the analysis of patient-derived samples.2
Optimal sequencing
depth, or coverage, is critical: if there is not sufficient coverage of the position(s) of inter- est during sequencing, it may be difficult or impossible to interpret the results.
The Quantitative Multiplex reference standard was sequenced using the AmpliSeq Cancer Hotspot Panel V2 (Life Technologies, Carlsbad, Calif.) by three different NGS laboratories (see Table 2). For the 11 engineered, validated mutations present in the sample, those below 5% were routinely not detected. Even in the laboratory of Partner C, where the highest aver- age coverage was achieved, the 5% KRAS G12D mutation was not detected. A second NGS plat- form and/or entire workflow is commonly used to validate detected mutations and their allelic frequencies. This helps to account for inher- ent biases associated with each platform (i.e., homopolymer errors), and allows confirmation of variants outside of the limit of detection of Sanger (approximately 20%).3
Bioinformatics The databases, algorithms and operators employed during informatics can have a sig- nificant influence on the resulting data. This is demonstrated by results compiled by research- ers from the Genome in a Bottle Consortium, a public/private/academic collaboration hosted by the National Institute of Standards and Technologies (NIST), which aims to standardize and improve human whole genome sequenc- ing (see Figure 2).4
Data was analyzed from 15 exomes, with five alignment and variant-calling pipelines, and significant differences were observed: less than 60% of calls were shared by all pipelines.4 As seen for the molecular side of the assay, a well-characterized reference standard with known allelic frequencies allows clinicians to ensure that the informatics are not introduc- ing unwanted bias, and that changes made
10% 20% 30% 40% 50% 60% 70%
0% Kit A (n=12) Kit B (n=6) Kit C (n=6) Kit D (n=6) Kit E (n=6) Extraction Kit
Figure 1 – DNA recovery from total theoretical yield from FFPE reference standards. Table 2 – NGS sequencing results*
to the pipeline over time (e.g., as software is upgraded) do not affect downstream results.
Once generated, short sequencing reads are first evaluated for quality (using a Q score, simi- lar to a Phred score) before being aligned to a
AMERICAN LABORATORY • 16 • AUGUST 2015
human reference genome. Alignment of these short reads to a reference sequence allows for the identification of single-nucleotide poly- morphisms (SNPs) and insertions/deletions (INDELs). In brief, a common bioinformatics
Average Percentage DNA Recovered
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