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Comparison of sequencing platforms for single nucleotide variant calls in a human sample.

ABSTRACT: Next-generation sequencings platforms coupled with advanced bioinformatic tools enable re-sequencing of the human genome at high-speed and large cost savings. We compare sequencing platforms from Roche/454(GS FLX), Illumina/HiSeq (HiSeq 2000), and Life Technologies/SOLiD (SOLiD 3 ECC) for their ability to identify single nucleotide substitutions in whole genome sequences from the same human sample. We report on significant GC-related bias observed in the data sequenced on Illumina and SOLiD platforms. The differences in the variant calls were investigated with regards to coverage, and sequencing error. Some of the variants called by only one or two of the platforms were experimentally tested using mass spectrometry; a method that is independent of DNA sequencing. We establish several causes why variants remained unreported, specific to each platform. We report the indel called using the three sequencing technologies and from the obtained results we conclude that sequencing human genomes with more than a single platform and multiple libraries is beneficial when high level of accuracy is required.

SUBMITTER: Ratan A

PROVIDER: S-EPMC3566181 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Comparison of sequencing platforms for single nucleotide variant calls in a human sample.

Ratan Aakrosh A Miller Webb W Guillory Joseph J Stinson Jeremy J Seshagiri Somasekar S Schuster Stephan C SC

PloS one 20130206 2

Next-generation sequencings platforms coupled with advanced bioinformatic tools enable re-sequencing of the human genome at high-speed and large cost savings. We compare sequencing platforms from Roche/454(GS FLX), Illumina/HiSeq (HiSeq 2000), and Life Technologies/SOLiD (SOLiD 3 ECC) for their ability to identify single nucleotide substitutions in whole genome sequences from the same human sample. We report on significant GC-related bias observed in the data sequenced on Illumina and SOLiD plat ...[more]

PMID: 23405114

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Project description:BackgroundThe targeted capture and sequencing of genomic regions has rapidly demonstrated its utility in genetic studies. Inherent in this technology is considerable heterogeneity of target coverage and this is expected to systematically impact our sensitivity to detect genuine polymorphisms. To fully interpret the polymorphisms identified in a genetic study it is often essential to both detect polymorphisms and to understand where and with what probability real polymorphisms may have been missed.ResultsUsing down-sampling of 30 deeply sequenced exomes and a set of gold-standard single nucleotide variant (SNV) genotype calls for each sample, we developed an empirical model relating the read depth at a polymorphic site to the probability of calling the correct genotype at that site. We find that measured sensitivity in SNV detection is substantially worse than that predicted from the naive expectation of sampling from a binomial. This calibrated model allows us to produce single nucleotide resolution SNV sensitivity estimates which can be merged to give summary sensitivity measures for any arbitrary partition of the target sequences (nucleotide, exon, gene, pathway, exome). These metrics are directly comparable between platforms and can be combined between samples to give "power estimates" for an entire study. We estimate a local read depth of 13X is required to detect the alleles and genotype of a heterozygous SNV 95% of the time, but only 3X for a homozygous SNV. At a mean on-target read depth of 20X, commonly used for rare disease exome sequencing studies, we predict 5-15% of heterozygous and 1-4% of homozygous SNVs in the targeted regions will be missed.ConclusionsNon-reference alleles in the heterozygote state have a high chance of being missed when commonly applied read coverage thresholds are used despite the widely held assumption that there is good polymorphism detection at these coverage levels. Such alleles are likely to be of functional importance in population based studies of rare diseases, somatic mutations in cancer and explaining the "missing heritability" of quantitative traits.

Project description:BackgroundTo promote the clinical application of next-generation sequencing, it is important to obtain accurate and consistent variants of target genomic regions at low cost. Ion Proton, the latest updated semiconductor-based sequencing instrument from Life Technologies, is designed to provide investigators with an inexpensive platform for human whole exome sequencing that achieves a rapid turnaround time. However, few studies have comprehensively compared and evaluated the accuracy of variant calling between Ion Proton and Illumina sequencing platforms such as HiSeq 2000, which is the most popular sequencing platform for the human genome. The Ion Proton sequencer combined with the Ion TargetSeq Exome Enrichment Kit together make up TargetSeq-Proton, whereas SureSelect-Hiseq is based on the Agilent SureSelect Human All Exon v4 Kit and the HiSeq 2000 sequencer.ResultsHere, we sequenced exonic DNA from four human blood samples using both TargetSeq-Proton and SureSelect-HiSeq. We then called variants in the exonic regions that overlapped between the two exome capture kits (33.6 Mb). The rates of shared variant loci called by two sequencing platforms were from 68.0 to 75.3% in four samples, whereas the concordance of co-detected variant loci reached 99%. Sanger sequencing validation revealed that the validated rate of concordant single nucleotide polymorphisms (SNPs) (91.5%) was higher than the SNPs specific to TargetSeq-Proton (60.0%) or specific to SureSelect-HiSeq (88.3%). With regard to 1-bp small insertions and deletions (InDels), the Sanger sequencing validated rates of concordant variants (100.0%) and SureSelect-HiSeq-specific (89.6%) were higher than those of TargetSeq-Proton-specific (15.8%).ConclusionsIn the sequencing of exonic regions, a combination of using of two sequencing strategies (SureSelect-HiSeq and TargetSeq-Proton) increased the variant calling specificity for concordant variant loci and the sensitivity for variant loci called by any one platform. However, for the sequencing of platform-specific variants, the accuracy of variant calling by HiSeq 2000 was higher than that of Ion Proton, specifically for the InDel detection. Moreover, the variant calling software also influences the detection of SNPs and, specifically, InDels in Ion Proton exome sequencing.

Dataset Information

Comparison of sequencing platforms for single nucleotide variant calls in a human sample.

Publications

Comparison of sequencing platforms for single nucleotide variant calls in a human sample.

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