PCR-Free Enrichment of Mitochondrial DNA from Human Blood and Cell Lines for High Quality Next-Generation DNA Sequencing

Recent advances in sequencing technology allow for accurate detection of mitochondrial sequence variants, even those in low abundance at heteroplasmic sites. Considerable sequencing cost savings can be achieved by enriching samples for mitochondrial (relative to nuclear) DNA. Reduction in nuclear DNA (nDNA) content can also help to avoid false positive variants resulting from nuclear mitochondrial sequences (numts). We isolate intact mitochondrial organelles from both human cell lines and blood components using two separate methods: a magnetic bead binding protocol and differential centrifugation. DNA is extracted and further enriched for mitochondrial DNA (mtDNA) by an enzyme digest. Only 1 ng of the purified DNA is necessary for library preparation and next generation sequence (NGS) analysis. Enrichment methods are assessed and compared using mtDNA (versus nDNA) content as a metric, measured by using real-time quantitative PCR and NGS read analysis. Among the various strategies examined, the optimal is differential centrifugation isolation followed by exonuclease digest. This strategy yields >35% mtDNA reads in blood and cell lines, which corresponds to hundreds-fold enrichment over baseline. The strategy also avoids false variant calls that, as we show, can be induced by the long-range PCR approaches that are the current standard in enrichment procedures. This optimization procedure allows mtDNA enrichment for efficient and accurate massively parallel sequencing, enabling NGS from samples with small amounts of starting material. This will decrease costs by increasing the number of samples that may be multiplexed, ultimately facilitating efforts to better understand mitochondria-related diseases.     

Reconstructing mitochondrial genomes directly from genomic next-generation sequencing reads—a baiting and iterative mapping approach

We present an in silico approach for the reconstruction of complete mitochondrial genomes of non-model organisms directly from next-generation sequencing (NGS) data—mitochondrial baiting and iterative mapping (MITObim). The method is straightforward even if only (i) distantly related mitochondrial genomes or (ii) mitochondrial barcode sequences are available as starting-reference sequences or seeds, respectively. We demonstrate the efficiency of the approach in case studies using real NGS data sets of the two monogenean ectoparasites species Gyrodactylus thymalli and Gyrodactylus derjavinoides including their respective teleost hosts European grayling (Thymallus thymallus) and Rainbow trout (Oncorhynchus mykiss). MITObim appeared superior to existing tools in terms of accuracy, runtime and memory requirements and fully automatically recovered mitochondrial genomes exceeding 99.5% accuracy from total genomic DNA derived NGS data sets in <24 h using a standard desktop computer. The approach overcomes the limitations of traditional strategies for obtaining mitochondrial genomes for species with little or no mitochondrial sequence information at hand and represents a fast and highly efficient in silico alternative to laborious conventional strategies relying on initial long-range PCR. We furthermore demonstrate the applicability of MITObim for metagenomic/pooled data sets using simulated data. MITObim is an easy to use tool even for biologists with modest bioinformatics experience. The software is made available as open source pipeline under the MIT license at https://github.com/chrishah/MITObim.     

Whole-Exome Sequencing to Decipher the Genetic Heterogeneity of Hearing Loss in a Chinese Family with Deaf by Deaf Mating

Inherited deafness has been shown to have high genetic heterogeneity. For many decades, linkage analysis and candidate gene approaches have been the main tools to elucidate the genetics of hearing loss. However, this associated study design is costly, time-consuming, and unsuitable for small families. This is mainly due to the inadequate numbers of available affected individuals, locus heterogeneity, and assortative mating. Exome sequencing has now become technically feasible and a cost-effective method for detection of disease variants underlying Mendelian disorders due to the recent advances in next-generation sequencing (NGS) technologies. In the present study, we have combined both the Deafness Gene Mutation Detection Array and exome sequencing to identify deafness causative variants in a large Chinese composite family with deaf by deaf mating. The simultaneous screening of the 9 common deafness mutations using the allele-specific PCR based universal array, resulted in the identification of the 1555A>G in the mitochondrial DNA (mtDNA) 12S rRNA in affected individuals in one branch of the family. We then subjected the mutation-negative cases to exome sequencing and identified novel causative variants in the MYH14 and WFS1 genes. This report confirms the effective use of a NGS technique to detect pathogenic mutations in affected individuals who were not candidates for classical genetic studies.     

Customisation of the exome data analysis pipeline using a combinatorial approach

The advent of next generation sequencing (NGS) technologies have revolutionised the way biologists produce, analyse and interpret data. Although NGS platforms provide a cost-effective way to discover genome-wide variants from a single experiment, variants discovered by NGS need follow up validation due to the high error rates associated with various sequencing chemistries. Recently, whole exome sequencing has been proposed as an affordable option compared to whole genome runs but it still requires follow up validation of all the novel exomic variants. Customarily, a consensus approach is used to overcome the systematic errors inherent to the sequencing technology, alignment and post alignment variant detection algorithms. However, the aforementioned approach warrants the use of multiple sequencing chemistry, multiple alignment tools, multiple variant callers which may not be viable in terms of time and money for individual investigators with limited informatics know-how. Biologists often lack the requisite training to deal with the huge amount of data produced by NGS runs and face difficulty in choosing from the list of freely available analytical tools for NGS data analysis. Hence, there is a need to customise the NGS data analysis pipeline to preferentially retain true variants by minimising the incidence of false positives and make the choice of right analytical tools easier. To this end, we have sampled different freely available tools used at the alignment and post alignment stage suggesting the use of the most suitable combination determined by a simple framework of pre-existing metrics to create significant datasets.     

Mitochondrial DNA mutations and human disease

Mitochondrial disorders are a group of clinically heterogeneous diseases, commonly defined by a lack of cellular energy due to oxidative phosphorylation (OXPHOS) defects. Since the identification of the first human pathological mitochondrial DNA (mtDNA) mutations in 1988, significant efforts have been spent in cataloguing the vast array of causative genetic defects of these disorders. Currently, more than 250 pathogenic mtDNA mutations have been identified. An ever-increasing number of nuclear DNA mutations are also being reported as the majority of proteins involved in mitochondrial metabolism and maintenance are nuclear-encoded. Understanding the phenotypic diversity and elucidating the molecular mechanisms at the basis of these diseases has however proved challenging. Progress has been hampered by the peculiar features of mitochondrial genetics, an inability to manipulate the mitochondrial genome, and difficulties in obtaining suitable models of disease. In this review, we will first outline the unique features of mitochondrial genetics before detailing the diseases and their genetic causes, focusing specifically on primary mtDNA genetic defects. The functional consequences of mtDNA mutations that have been characterised to date will also be discussed, along with current and potential future diagnostic and therapeutic advances.     

一种基于二代测序辨识短串联重复序列长度变异的新方法及其在人类遗传疾病研究中的应用

二代测序技术的涌现推动了基因组学研究,特别是在疾病相关的遗传变异研究中发挥了重要作用．虽然大多数遗传变异类型都可以借助于各种二代测序分析工具进行检测,但是仍然存在局限性,比如短串联重复序列的长度变异．许多遗传疾病是由短串联重复序列的长度扩张导致的,尤其是亨廷顿病等多种神经系统疾病．然而,现在几乎没有工具能够利用二代测序检测长度大于测序读长的短串联重复序列变异．为了突破这一限制,我们开发了一个全新的方法,该方法基于双末端二代测序辨识短串联重复序列长度变异,并可估计其扩张长度,将其应用于一项基于全外显子组测序的运动神经元疾病临床研究中,成功地鉴定出致病的短串联重复序列长度扩张．该方法首次原创性地利用测序读长覆盖深度特征来解决短串联重复序列变异检测问题,在人类遗传疾病研究中具有广泛的应用价值,并且对于其他二代测序分析方法的开发具有启发性意义．     

Complete mitochondrial genome sequencing reveals novel haplotypes in a Polynesian population

The high risk of metabolic disease traits in Polynesians may be partly explained by elevated prevalence of genetic variants involved in energy metabolism. The genetics of Polynesian populations has been shaped by island hoping migration events which have possibly favoured thrifty genes. The aim of this study was to sequence the mitochondrial genome in a group of Maoris in an effort to characterise genome variation in this Polynesian population for use in future disease association studies. We sequenced the complete mitochondrial genomes of 20 non-admixed Maori subjects using Affymetrix technology. DNA diversity analyses showed the Maori group exhibited reduced mitochondrial genome diversity compared to other worldwide populations, which is consistent with historical bottleneck and founder effects. Global phylogenetic analysis positioned these Maori subjects specifically within mitochondrial haplogroup--B4a1a1. Interestingly, we identified several novel variants that collectively form new and unique Maori motifs--B4a1a1c, B4a1a1a3 and B4a1a1a5. Compared to ancestral populations we observed an increased frequency of non-synonymous coding variants of several mitochondrial genes in the Maori group, which may be a result of positive selection and/or genetic drift effects. In conclusion, this study reports the first complete mitochondrial genome sequence data for a Maori population. Overall, these new data reveal novel mitochondrial genome signatures in this Polynesian population and enhance the phylogenetic picture of maternal ancestry in Oceania. The increased frequency of several mitochondrial coding variants makes them good candidates for future studies aimed at assessment of metabolic disease risk in Polynesian populations.     

Human mitochondrial DNA diseases and Drosophila models

Mutations that disrupt the mitochondrial genome cause a number of human diseases whose phenotypic presentation varies widely among tissues and individuals. This variability owes in part to the unconventional genetics of mitochondrial DNA(mtDNA), which includes polyploidy, maternal inheritance and dependence on nuclear-encoded factors. The recent development of genetic tools for manipulating mitochondrial genome in Drosophila melanogaster renders this powerful model organism an attractive alternative to mammalian systems for understanding mtDNA-related diseases. In this review, we summarize mtDNA genetics and human mtDNA-related diseases. We highlight existing Drosophila models of mtDNA mutations and discuss their potential use in advancing our knowledge of mitochondrial biology and in modeling human mitochondrial disorders. We also discuss the potential and present challenges of gene therapy for the future treatment of mtDNA diseases.     

VCF2CAPS–A high-throughput CAPS marker design from VCF files and its test-use on a genotyping-by-sequencing (GBS) dataset

Next-generation sequencing (NGS) is a powerful tool for massive detection of DNA sequence variants such as single nucleotide polymorphisms (SNPs), multi-nucleotide polymorphisms (MNPs) and insertions/deletions (indels). For routine screening of numerous samples, these variants are often converted into cleaved amplified polymorphic sequence (CAPS) markers which are based on the presence versus absence of restriction sites within PCR products. Current computational tools for SNP to CAPS conversion are limited and usually infeasible to use for large datasets as those generated with NGS. Moreover, there is no available tool for massive conversion of MNPs and indels into CAPS markers. Here, we present VCF2CAPS–a new software for identification of restriction endonucleases that recognize SNP/MNP/indel-containing sequences from NGS experiments. Additionally, the program contains filtration utilities not available in other SNP to CAPS converters–selection of markers with a single polymorphic cut site within a user-specified sequence length, and selection of markers that differentiate up to three user-defined groups of individuals from the analyzed population. Performance of VCF2CAPS was tested on a thoroughly analyzed dataset from a genotyping-by-sequencing (GBS) experiment. A selection of CAPS markers picked by the program was subjected to experimental verification. CAPS markers, also referred to as PCR-RFLPs, belong to basic tools exploited in plant, animal and human genetics. Our new software–VCF2CAPS–fills the gap in the current inventory of genetic software by high-throughput CAPS marker design from next-generation sequencing (NGS) data. The program should be of interest to geneticists involved in molecular diagnostics. In this paper we show a successful exemplary application of VCF2CAPS and we believe that its usefulness is guaranteed by the growing availability of NGS services.

This is a PLOS Computational Biology Software paper.

     

Mitochondrial genome analysis in penile carcinoma

Penile cancer is a rare neoplasm that seems to be linked to socio-economic differences. Mitochondrial genome alterations are common in many tumors types and are reported as regulating oxidative metabolism and impacting tumorigenesis. In this study, we evaluate for the first time the mitochondrial genome in penile carcinoma (PeCa), aiming to evaluate heteroplasmy, mitochondrial DNA (mtDNA) mutational load and mtDNA content in Penile tumors. Using next generation sequencing (NGS), we sequenced the mitochondrial genome of 13 penile tumors and 12 non-neoplastic tissue samples, which allowed us to identify mtDNA variants and heteroplasmy. We further evaluated variant’s pathogenicity using Mutpred predictive software and calculated mtDNA content using quantitative PCR. Mitochondrial genome sequencing revealed an increase number of non-synonymous variants in the tumor tissue, along with higher frequency of heteroplasmy and mtDNA depletion in penile tumors, suggesting an increased mitochondrial instability in penile tumors. We also described a list of mitochondrial variants found in penile tumor and normal tissue, including five novel variants found in the tumoral tissue. Our results showed an increased mitochondrial genome instability in penile tumors. We also suggest that mitochondrial DNA copy number (mtDNAcn) and mtDNA variants may act together to imbalance mitochondrial function in PeCa. The better understanding of mitochondrial biology can bring new insights on mechanisms and open a new field for therapy in PeCa.     

Automating the identification of DNA variations using quality-based fluorescence re-sequencing: analysis of the human mitochondrial genome.

Diagnostic re-sequencing plays a central role in medical and evolutionary genetics. In this report we describe a process that applies fluorescence-based re-sequencing and an integrated set of analysis tools to automate and simplify the identification of DNA variations using the human mitochondrial genome as a model system. Two programs used in genome sequence analysis (Phred, a base-caller, and Phrap, a sequence assembler) are applied to assess the quality of each base call across the sequence. Potential DNA variants are automatically identified and 'tagged' by comparing the assembled sequence with a reference sequence. We also show that employing the Consed program to display a set of highly annotated reference sequences greatly simplifies data analysis by providing a visual database containing information on the location of the PCR primers, coding and regulatory sequences and previously known DNA variants. Among the 12 genomes sequenced 378 variants including 29 new variants were identified along with two heteroplasmic sites, automatically detected by the PolyPhred program. Overall we document the ease and speed of performing high quality and accurate fluorescence-based re-sequencing on long tracts of DNA as well as the application of new approaches to automatically find and view DNA variants among these sequences.     

Improving mapping and SNP-calling performance in multiplexed targeted next-generation sequencing

ABSTRACT: BACKGROUND: Compared to classical genotyping, targeted next-generation sequencing (tNGS) can be custom-designed to interrogate entire genomic regions of interest, in order to detect novel as well as known variants. To bring down the per-sample cost, one approach is to pool barcoded NGS libraries before sample enrichment. Still, we lack a complete understanding of how this multiplexed tNGS approach and the varying performance of the ever-evolving analytical tools can affect the quality of variant discovery. Therefore, we evaluated the impact of different software tools and analytical approaches on the discovery of single nucleotide polymorphisms (SNPs) in multiplexed tNGS data. To generate our own test model, we combined a sequence capture method with NGS in three experimental stages of increasing complexity (E. coli genes, multiplexed E. coli, and multiplexed HapMap BRCA1/2 regions). RESULTS: We successfully enriched barcoded NGS libraries instead of genomic DNA, achieving reproducible coverage profiles (Pearson correlation coefficients of up to 0.99) across multiplexed samples, with <10% strand bias. However, the SNP calling quality was substantially affected by the choice of tools and mapping strategy. With the aim of reducing computational requirements, we compared conventional whole-genome mapping and SNP-calling with a new faster approach: target-region mapping with subsequent 'read-backmapping' to the whole genome to reduce the false detection rate. Consequently, we developed a combined mapping pipeline, which includes standard tools (BWA, SAMtools, etc.), and tested it on public HiSeq2000 exome data from the 1000 Genomes Project. Our pipeline saved 12 hours of run time per Hiseq2000 exome sample and detected ~5% more SNPs than the conventional whole genome approach. This suggests that more potential novel SNPs may be discovered using both approaches than with just the conventional approach. CONCLUSIONS: We recommend applying our general 'two-step' mapping approach for more efficient SNP discovery in tNGS. Our study has also shown the benefit of computing inter-sample SNP-concordances and inspecting read alignments in order to attain more confident results.     

QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data

Array-based technologies have been used to detect chromosomal copy number changes (aneuploidies) in the human genome. Recent studies identified numerous copy number variants (CNV) and some are common polymorphisms that may contribute to disease susceptibility. We developed, and experimentally validated, a novel computational framework (QuantiSNP) for detecting regions of copy number variation from BeadArray SNP genotyping data using an Objective Bayes Hidden-Markov Model (OB-HMM). Objective Bayes measures are used to set certain hyperparameters in the priors using a novel re-sampling framework to calibrate the model to a fixed Type I (false positive) error rate. Other parameters are set via maximum marginal likelihood to prior training data of known structure. QuantiSNP provides probabilistic quantification of state classifications and significantly improves the accuracy of segmental aneuploidy identification and mapping, relative to existing analytical tools (Beadstudio, Illumina), as demonstrated by validation of breakpoint boundaries. QuantiSNP identified both novel and validated CNVs. QuantiSNP was developed using BeadArray SNP data but it can be adapted to other platforms and we believe that the OB-HMM framework has widespread applicability in genomic research. In conclusion, QuantiSNP is a novel algorithm for high-resolution CNV/aneuploidy detection with application to clinical genetics, cancer and disease association studies.     

First insights into the metagenome of Egyptian mummies using next-generation sequencing

We applied, for the first time, next-generation sequencing (NGS) technology on Egyptian mummies. Seven NGS datasets obtained from five randomly selected Third Intermediate to Graeco-Roman Egyptian mummies (806 BC–124AD) and two unearthed pre-contact Bolivian lowland skeletons were generated and characterised. The datasets were contrasted to three recently published NGS datasets obtained from cold-climate regions, i.e. the Saqqaq, the Denisova hominid and the Alpine Iceman. Analysis was done using one million reads of each newly generated or published dataset. Blastn and megablast results were analysed using MEGAN software. Distinct NGS results were replicated by specific and sensitive polymerase chain reaction (PCR) protocols in ancient DNA dedicated laboratories. Here, we provide unambiguous identification of authentic DNA in Egyptian mummies. The NGS datasets showed variable contents of endogenous DNA harboured in tissues. Three of five mummies displayed a human DNA proportion comparable to the human read count of the Saqqaq permafrost-preserved specimen. Furthermore, a metagenomic signature unique to mummies was displayed. By applying a “bacterial fingerprint”, discrimination among mummies and other remains from warm areas outside Egypt was possible. Due to the absence of an adequate environment monitoring, a bacterial bloom was identified when analysing different biopsies from the same mummies taken after a lapse of time of 1.5 years. Plant kingdom representation in all mummy datasets was unique and could be partially associated with their use in embalming materials. Finally, NGS data showed the presence of Plasmodium falciparum and Toxoplasma gondii DNA sequences, indicating malaria and toxoplasmosis in these mummies. We demonstrate that endogenous ancient DNA can be extracted from mummies and serve as a proper template for the NGS technique, thus, opening new pathways of investigation for future genome sequencing of ancient Egyptian individuals.     

Combinatorial analysis and algorithms for quasispecies reconstruction using next-generation sequencing

Background  

Next-generation sequencing (NGS) offers a unique opportunity for high-throughput genomics and has potential to replace Sanger sequencing in many fields, including de-novo sequencing, re-sequencing, meta-genomics, and characterisation of infectious pathogens, such as viral quasispecies. Although methodologies and software for whole genome assembly and genome variation analysis have been developed and refined for NGS data, reconstructing a viral quasispecies using NGS data remains a challenge. This application would be useful for analysing intra-host evolutionary pathways in relation to immune responses and antiretroviral therapy exposures. Here we introduce a set of formulae for the combinatorial analysis of a quasispecies, given a NGS re-sequencing experiment and an algorithm for quasispecies reconstruction. We require that sequenced fragments are aligned against a reference genome, and that the reference genome is partitioned into a set of sliding windows (amplicons). The reconstruction algorithm is based on combinations of multinomial distributions and is designed to minimise the reconstruction of false variants, called in-silico recombinants.     

Family-based association studies for next-generation sequencing

An individual's disease risk is determined by the compounded action of both common variants, inherited from remote ancestors, that segregated within the population and rare variants, inherited from recent ancestors, that segregated mainly within pedigrees. Next-generation sequencing (NGS) technologies generate high-dimensional data that allow a nearly complete evaluation of genetic variation. Despite their promise, NGS technologies also suffer from remarkable limitations: high error rates, enrichment of rare variants, and a large proportion of missing values, as well as the fact that most current analytical methods are designed for population-based association studies. To meet the analytical challenges raised by NGS, we propose a general framework for sequence-based association studies that can use various types of family and unrelated-individual data sampled from any population structure and a universal procedure that can transform any population-based association test statistic for use in family-based association tests. We develop family-based functional principal-component analysis (FPCA) with or without smoothing, a generalized T(2), combined multivariate and collapsing (CMC) method, and single-marker association test statistics. Through intensive simulations, we demonstrate that the family-based smoothed FPCA (SFPCA) has the correct type I error rates and much more power to detect association of (1) common variants, (2) rare variants, (3) both common and rare variants, and (4) variants with opposite directions of effect from other population-based or family-based association analysis methods. The proposed statistics are applied to two data sets with pedigree structures. The results show that the smoothed FPCA has a much smaller p value than other statistics.     

MitoLSDB: A Comprehensive Resource to Study Genotype to Phenotype Correlations in Human Mitochondrial DNA Variations

Human mitochondrial DNA (mtDNA) encodes a set of 37 genes which are essential structural and functional components of the electron transport chain. Variations in these genes have been implicated in a broad spectrum of diseases and are extensively reported in literature and various databases. In this study, we describe MitoLSDB, an integrated platform to catalogue disease association studies on mtDNA (http://mitolsdb.igib.res.in). The main goal of MitoLSDB is to provide a central platform for direct submissions of novel variants that can be curated by the Mitochondrial Research Community. MitoLSDB provides access to standardized and annotated data from literature and databases encompassing information from 5231 individuals, 675 populations and 27 phenotypes. This platform is developed using the Leiden Open (source) Variation Database (LOVD) software. MitoLSDB houses information on all 37 genes in each population amounting to 132397 variants, 5147 unique variants. For each variant its genomic location as per the Revised Cambridge Reference Sequence, codon and amino acid change for variations in protein-coding regions, frequency, disease/phenotype, population, reference and remarks are also listed. MitoLSDB curators have also reported errors documented in literature which includes 94 phantom mutations, 10 NUMTs, six documentation errors and one artefactual recombination. MitoLSDB is the largest repository of mtDNA variants systematically standardized and presented using the LOVD platform. We believe that this is a good starting resource to curate mtDNA variants and will facilitate direct submissions enhancing data coverage, annotation in context of pathogenesis and quality control by ensuring non-redundancy in reporting novel disease associated variants.     

Combined hybridization capture and shotgun sequencing for ancient DNA analysis of extinct wild and domestic dromedary camel

The performance of hybridization capture combined with next‐generation sequencing (NGS) has seen limited investigation with samples from hot and arid regions until now. We applied hybridization capture and shotgun sequencing to recover DNA sequences from bone specimens of ancient‐domestic dromedary (Camelus dromedarius) and its extinct ancestor, the wild dromedary from Jordan, Syria, Turkey and the Arabian Peninsula, respectively. Our results show that hybridization capture increased the percentage of mitochondrial DNA (mtDNA) recovery by an average 187‐fold and in some cases yielded virtually complete mitochondrial (mt) genomes at multifold coverage in a single capture experiment. Furthermore, we tested the effect of hybridization temperature and time by using a touchdown approach on a limited number of samples. We observed no significant difference in the number of unique dromedary mtDNA reads retrieved with the standard capture compared to the touchdown method. In total, we obtained 14 partial mitochondrial genomes from ancient‐domestic dromedaries with 17–95% length coverage and 1.27–47.1‐fold read depths for the covered regions. Using whole‐genome shotgun sequencing, we successfully recovered endogenous dromedary nuclear DNA (nuDNA) from domestic and wild dromedary specimens with 1–1.06‐fold read depths for covered regions. Our results highlight that despite recent methodological advances, obtaining ancient DNA (aDNA) from specimens recovered from hot, arid environments is still problematic. Hybridization protocols require specific optimization, and samples at the limit of DNA preservation need multiple replications of DNA extraction and hybridization capture as has been shown previously for Middle Pleistocene specimens.     

Technology-specific error signatures in the 1000 Genomes Project data

Next-generation sequencing (NGS) will likely facilitate a better understanding of the causes and consequences of human genetic variability. In this context, the validity of NGS-inferred single-nucleotide variants (SNVs) is of paramount importance. We therefore developed a statistical framework to assess the fidelity of three common NGS platforms. Using aligned DNA sequence data from two completely sequenced HapMap samples as included in the 1000 Genomes Project, we unraveled remarkably different error profiles for the three platforms. Compared to confirmed HapMap variants, newly identified SNVs included a substantial proportion of false positives (3–17%). Consensus calling by more than one platform yielded significantly lower error rates (1–4%). This implies that the use of multiple NGS platforms may be more cost-efficient than relying upon a single technology alone, particularly in physically localized sequencing experiments that rely upon small error rates. Our study thus highlights that different NGS platforms suit different practical applications differently well, and that NGS-based studies require stringent data quality control for their results to be valid.     

BlackOPs: increasing confidence in variant detection through mappability filtering

Identifying variants using high-throughput sequencing data is currently a challenge because true biological variants can be indistinguishable from technical artifacts. One source of technical artifact results from incorrectly aligning experimentally observed sequences to their true genomic origin (‘mismapping’) and inferring differences in mismapped sequences to be true variants. We developed BlackOPs, an open-source tool that simulates experimental RNA-seq and DNA whole exome sequences derived from the reference genome, aligns these sequences by custom parameters, detects variants and outputs a blacklist of positions and alleles caused by mismapping. Blacklists contain thousands of artifact variants that are indistinguishable from true variants and, for a given sample, are expected to be almost completely false positives. We show that these blacklist positions are specific to the alignment algorithm and read length used, and BlackOPs allows users to generate a blacklist specific to their experimental setup. We queried the dbSNP and COSMIC variant databases and found numerous variants indistinguishable from mapping errors. We demonstrate how filtering against blacklist positions reduces the number of potential false variants using an RNA-seq glioblastoma cell line data set. In summary, accounting for mapping-caused variants tuned to experimental setups reduces false positives and, therefore, improves genome characterization by high-throughput sequencing.