A bioinformatic filter for improved base-call accuracy and polymorphism detection using the Affymetrix GeneChip whole-genome resequencing platform

How industrial bacterial cultures can be kept stable over time

The tremendous variation that exists between bacterial species illustrates the power of evolution, which is the continuous process of mutation and selection over time. Even within a bacterial species, individual members can harbour an impressive degree of genetic variation, depending on the species. The question then arises how similar the offspring of a given bacterial cell over time is, and how long it takes before differences are noticeable? Here we show that on the one hand one can expect random mutations to arise, as a result of various mechanisms. On the other hand, there are forces at play that keep the offspring of a cell genetically relatively constant, unless there is selection for a particular characteristic. The most common mechanisms behind mutations that can appear in a bacterial population are briefly introduced. Next, it is explained why nevertheless such mutations are rarely observed, as long as single colonies are randomly selected, unless selective pressures apply. Since quality control of industrial bacterial cultures is likely to depend heavily on genome sequencing in the near future, the accuracy of whole‐genomic sequencing technologies is also discussed. It can be concluded that the bacteriologists who started picking single colonies from agar plates more than hundred years ago were unknowingly ingeneous, as their practice maintains a bacterial culture stable over time.

Significance and Impact of Study

The questions addressed here are relevant for industries that depend on live bacteria for (manufacturing of) their products, as they have to guard their bacterial cultures that remain unchanged over time. The explanation why randomly selection of single colonies keeps a population stable can be of use in bacteriology courses. The limitations of whole‐genome sequencing are relevant to legislators to avoid overinterpretation of those data.

Development of a high-throughput resequencing array for the detection of pathogenic mutations in osteogenesis imperfecta

Objective

Osteogenesis imperfecta (OI) is a rare inherited skeletal disease, characterized by bone fragility and low bone density. The mutations in this disorder have been widely reported to be on various exonal hotspots of the candidate genes, including COL1A1, COL1A2, CRTAP, LEPRE1, and FKBP10, thus creating a great demand for precise genetic tests. However, large genome sizes make the process daunting and the analyses, inefficient and expensive. Therefore, we aimed at developing a fast, accurate, efficient, and cheaper sequencing platform for OI diagnosis; and to this end, use of an advanced array-based technique was proposed.

Method

A CustomSeq Affymetrix Resequencing Array was established for high-throughput sequencing of five genes simultaneously. Genomic DNA extraction from 13 OI patients and 85 normal controls and amplification using long-range PCR (LR-PCR) were followed by DNA fragmentation and chip hybridization, according to standard Affymetrix protocols. Hybridization signals were determined using GeneChip Sequence Analysis Software (GSEQ). To examine the feasibility, the outcome from new resequencing approach was validated by conventional capillary sequencing method.

Result

Overall call rates using resequencing array was 96–98% and the agreement between microarray and capillary sequencing was 99.99%. 11 out of 13 OI patients with pathogenic mutations were successfully detected by the chip analysis without adjustment, and one mutation could also be identified using manual visual inspection.

Conclusion

A high-throughput resequencing array was developed that detects the disease-associated mutations in OI, providing a potential tool to facilitate large-scale genetic screening for OI patients. Through this method, a novel mutation was also found.

Cancer Genomics: Technology, Discovery, and Translation

In recent years, the increasing awareness that somatic mutations and other genetic aberrations drive human malignancies has led us within reach of personalized cancer medicine (PCM). The implementation of PCM is based on the following premises: genetic aberrations exist in human malignancies; a subset of these aberrations drive oncogenesis and tumor biology; these aberrations are actionable (defined as having the potential to affect management recommendations based on diagnostic, prognostic, and/or predictive implications); and there are highly specific anticancer agents available that effectively modulate these targets. This article highlights the technology underlying cancer genomics and examines the early results of genome sequencing and the challenges met in the discovery of new genetic aberrations. Finally, drawing from experiences gained in a feasibility study of somatic mutation genotyping and targeted exome sequencing led by Princess Margaret Hospital–University Health Network and the Ontario Institute for Cancer Research, the processes, challenges, and issues involved in the translation of cancer genomics to the clinic are discussed.

High-throughput retina-array for screening 93 genes involved in inherited retinal dystrophy

PURPOSE

Retinal dystrophy (RD) is a broad group of hereditary disorders with heterogeneous genotypes and phenotypes. Current available genetic testing for these diseases is complicated, time consuming, and expensive. This study was conducted to develop and apply a microarray-based, high-throughput resequencing system to detect sequence alterations in genes related to inherited RD.

METHODS

A customized 300-kb resequencing chip, Retina-Array, was developed to detect sequence alterations of 267,550 bases of both sense and antisense sequence in 1470 exons spanning 93 genes involved in inherited RD. Retina-Array was evaluated in 19 patient samples with inherited RD provided by the eyeGENE repository and four Centre d'Etudes du Polymorphisme Humaine reference samples through a high-throughput experimental approach that included an automated PCR assay setup and quantification, efficient post-quantification data processing, optimized pooling and fragmentation, and standardized chip processing.

RESULTS

The performance of the chips demonstrated that the average base pair call rate and accuracy were 93.56% and 99.86%, respectively. In total, 304 candidate variations were identified using a series of customized screening filters. Among 174 selected variations, 123 (70.7%) were further confirmed by dideoxy sequencing. Analysis of patient samples using Retina-Array resulted in the identification of 10 known mutations and 12 novel variations with high probability of deleterious effects.

CONCLUSIONS

This study suggests that Retina-Array might be a valuable tool for the detection of disease-causing mutations and disease severity modifiers in a single experiment. Retinal-Array may provide a powerful and feasible approach through which to study genetic heterogeneity in retinal diseases.

Insights into N-calls of mitochondrial DNA sequencing using MitoChip v2.0

Background

Developments in DNA resequencing microarrays include mitochondrial DNA (mtDNA) sequencing and mutation detection. Failure by the microarray to identify a base, compared to the reference sequence, is designated an 'N-call.' This study re-examined the N-call distribution of mtDNA samples sequenced by the Affymetrix MitoChip v.2.0, based on the hypothesis that N-calls may represent insertions or deletions (indels) in mtDNA.

Findings

We analysed 16 patient mtDNA samples using MitoChip. N-calls by the proprietary GSEQ software were significantly reduced when either of the freeware on-line algorithms ResqMi or sPROFILER was utilized. With sPROFILER, this decrease in N-calls had no effect on the homoplasmic or heteroplasmic mutation levels compared to GSEQ software, but ResqMi produced a significant change in mutation load, as well as producing longer N-cell stretches. For these reasons, further analysis using ResqMi was not attempted. Conventional DNA sequencing of the longer N-calls stretches from sPROFILER revealed 7 insertions and 12 point mutations. Moreover, analysis of single-base N-calls of one mtDNA sample found 3 other point mutations.

Conclusions

Our study is the first to analyse N-calls produced from GSEQ software for the MitoChipv2.0. By narrowing the focus to longer stretches of N-calls revealed by sPROFILER, conventional sequencing was able to identify unique insertions and point mutations. Shorter N-calls also harboured point mutations, but the absence of deletions among N-calls suggests that probe confirmation affects binding and thus N-calling. This study supports the contention that the GSEQ is more capable of assigning bases when used in conjunction with sPROFILER.

Mitochondrial genome sequence analysis: a custom bioinformatics pipeline substantially improves Affymetrix MitoChip v2.0 call rate and accuracy

Background

Mitochondrial genome sequence analysis is critical to the diagnostic evaluation of mitochondrial disease. Existing methodologies differ widely in throughput, complexity, cost efficiency, and sensitivity of heteroplasmy detection. Affymetrix MitoChip v2.0, which uses a sequencing-by-genotyping technology, allows potentially accurate and high-throughput sequencing of the entire human mitochondrial genome to be completed in a cost-effective fashion. However, the relatively low call rate achieved using existing software tools has limited the wide adoption of this platform for either clinical or research applications. Here, we report the design and development of a custom bioinformatics software pipeline that achieves a much improved call rate and accuracy for the Affymetrix MitoChip v2.0 platform. We used this custom pipeline to analyze MitoChip v2.0 data from 24 DNA samples representing a broad range of tissue types (18 whole blood, 3 skeletal muscle, 3 cell lines), mutations (a 5.8 kilobase pair deletion and 6 known heteroplasmic mutations), and haplogroup origins. All results were compared to those obtained by at least one other mitochondrial DNA sequence analysis method, including Sanger sequencing, denaturing HPLC-based heteroduplex analysis, and/or the Illumina Genome Analyzer II next generation sequencing platform.

Results

An average call rate of 99.75% was achieved across all samples with our custom pipeline. Comparison of calls for 15 samples characterized previously by Sanger sequencing revealed a total of 29 discordant calls, which translates to an estimated 0.012% for the base call error rate. We successfully identified 4 known heteroplasmic mutations and 24 other potential heteroplasmic mutations across 20 samples that passed quality control.

Conclusions

Affymetrix MitoChip v2.0 analysis using our optimized MitoChip Filtering Protocol (MFP) bioinformatics pipeline now offers the high sensitivity and accuracy needed for reliable, high-throughput and cost-efficient whole mitochondrial genome sequencing. This approach provides a viable alternative of potential utility for both clinical diagnostic and research applications to traditional Sanger and other emerging sequencing technologies for whole mitochondrial genome analysis.

Large scale mtDNA sequencing reveals sequence and functional conservation as major determinants of homoplasmic mtDNA variant distribution

The mitochondrial DNA (mtDNA) is highly variable, containing large numbers of pathogenic mutations and neutral polymorphisms. The spectrum of homoplasmic mtDNA variation was characterized in 730 subjects and compared with known pathogenic sites. The frequency and distribution of variants in protein coding genes were inversely correlated with conservation at the amino acid level. Analysis of tRNA secondary structures indicated a preference of variants for the loops and some acceptor stem positions. This comprehensive overview of mtDNA variants distinguishes between regions and positions which are likely not critical, mainly conserved regions with pathogenic mutations and essential regions containing no mutations at all.

Monitoring the long-term molecular epidemiology of the pneumococcus and detection of potential 'vaccine escape' strains

BACKGROUND

While the pneumococcal protein conjugate vaccines reduce the incidence in invasive pneumococcal disease (IPD), serotype replacement remains a major concern. Thus, serotype-independent protection with vaccines targeting virulence genes, such as PspA, have been pursued. PspA is comprised of diverse clades that arose through recombination. Therefore, multi-locus sequence typing (MLST)-defined clones could conceivably include strains from multiple PspA clades. As a result, a method is needed which can both monitor the long-term epidemiology of the pneumococcus among a large number of isolates, and analyze vaccine-candidate genes, such as pspA, for mutations and recombination events that could result in 'vaccine escape' strains.

METHODOLOGY

We developed a resequencing array consisting of five conserved and six variable genes to characterize 72 pneumococcal strains. The phylogenetic analysis of the 11 concatenated genes was performed with the MrBayes program, the single nucleotide polymorphism (SNP) analysis with the DNA Sequence Polymorphism program (DnaSP), and the recombination event analysis with the recombination detection package (RDP).

RESULTS

The phylogenetic analysis correlated with MLST, and identified clonal strains with unique PspA clades. The DnaSP analysis correlated with the serotype-specific diversity detected using MLST. Serotypes associated with more than one ST complex had a larger degree of sequence polymorphism than a serotype associated with one ST complex. The RDP analysis confirmed the high frequency of recombination events in the pspA gene.

CONCLUSIONS

The phylogenetic tree correlated with MLST, and detected multiple PspA clades among clonal strains. The genetic diversity of the strains and the frequency of recombination events in the mosaic gene, pspA were accurately assessed using the DnaSP and RDP programs, respectively. These data provide proof-of-concept that resequencing arrays could play an important role within research and clinical laboratories in both monitoring the molecular epidemiology of the pneumococcus and detecting 'vaccine escape' strains among vaccine-candidate genes.

Identification of rare DNA variants in mitochondrial disorders with improved array-based sequencing

A common goal in the discovery of rare functional DNA variants via medical resequencing is to incur a relatively lower proportion of false positive base-calls. We developed a novel statistical method for resequencing arrays (SRMA, sequence robust multi-array analysis) to increase the accuracy of detecting rare variants and reduce the costs in subsequent sequence verifications required in medical applications. SRMA includes single and multi-array analysis and accounts for technical variables as well as the possibility of both low- and high-frequency genomic variation. The confidence of each base-call was ranked using two quality measures. In comparison to Sanger capillary sequencing, we achieved a false discovery rate of 2% (false positive rate 1.2 × 10⁻⁵, false negative rate 5%), which is similar to automated second-generation sequencing technologies. Applied to the analysis of 39 nuclear candidate genes in disorders of mitochondrial DNA (mtDNA) maintenance, we confirmed mutations in the DNA polymerase gamma POLG in positive control cases, and identified novel rare variants in previously undiagnosed cases in the mitochondrial topoisomerase TOP1MT, the mismatch repair enzyme MUTYH, and the apurinic-apyrimidinic endonuclease APEX2. Some patients carried rare heterozygous variants in several functionally interacting genes, which could indicate synergistic genetic effects in these clinically similar disorders.

Large-scale evolutionary surveillance of the 2009 H1N1 influenza A virus using resequencing arrays

In April 2009, a new influenza A (H1N1 2009) virus emerged that rapidly spread around the world. While current variants of this virus have caused widespread disease, particularly in vulnerable groups, there remains the possibility that future variants may cause increased virulence, drug resistance or vaccine escape. Early detection of these virus variants may offer the chance for increased containment and potentially prevention of the virus spread. We have developed and field-tested a resequencing kit that is capable of interrogating all eight segments of the 2009 influenza A(H1N1) virus genome and its variants, with added focus on critical regions such as drug-binding sites, structural components and mutation hotspots. The accompanying base-calling software (EvolSTAR) introduces novel methods that utilize neighbourhood hybridization intensity profiles and substitution bias of probes on the microarray for mutation confirmation and recovery of ambiguous base queries. Our results demonstrate that EvolSTAR is highly accurate and has a much improved call rate. The high throughput and short turn-around time from sample to sequence and analysis results (30 h for 24 samples) makes this kit an efficient large-scale evolutionary biosurveillance tool.

High-throughput detection of mutations responsible for childhood hearing loss using resequencing microarrays

BACKGROUND

Despite current knowledge of mutations in 45 genes that can cause nonsyndromic sensorineural hearing loss (SNHL), no unified clinical test has been developed that can comprehensively detect mutations in multiple genes. We therefore designed Affymetrix resequencing microarrays capable of resequencing 13 genes mutated in SNHL (GJB2, GJB6, CDH23, KCNE1, KCNQ1, MYO7A, OTOF, PDS, MYO6, SLC26A5, TMIE, TMPRSS3, USH1C). We present results from hearing loss arrays developed in two different research facilities and highlight some of the approaches we adopted to enhance the applicability of resequencing arrays in a clinical setting.

RESULTS

We leveraged sequence and intensity pattern features responsible for diminished coverage and accuracy and developed a novel algorithm, sPROFILER, which resolved >80% of no-calls from GSEQ and allowed 99.6% (range: 99.2-99.8%) of sequence to be called, while maintaining overall accuracy at >99.8% based upon dideoxy sequencing comparison.

CONCLUSIONS

Together, these findings provide insight into critical issues for disease-centered resequencing protocols suitable for clinical application and support the use of array-based resequencing technology as a valuable molecular diagnostic tool for pediatric SNHL and other genetic diseases with substantial genetic heterogeneity.

Whole genome single nucleotide polymorphism based phylogeny of Francisella tularensis and its application to the development of a strain typing assay

BACKGROUND

A low genetic diversity in Francisella tularensis has been documented. Current DNA based genotyping methods for typing F. tularensis offer a limited and varying degree of subspecies, clade and strain level discrimination power. Whole genome sequencing is the most accurate and reliable method to identify, type and determine phylogenetic relationships among strains of a species. However, lower cost typing schemes are necessary in order to enable typing of hundreds or even thousands of isolates.

RESULTS

We have generated a high-resolution phylogenetic tree from 40 Francisella isolates, including 13 F. tularensis subspecies holarctica (type B) strains, 26 F. tularensis subsp. tularensis (type A) strains and a single F. novicida strain. The tree was generated from global multi-strain single nucleotide polymorphism (SNP) data collected using a set of six Affymetrix GeneChip resequencing arrays with the non-repetitive portion of LVS (type B) as the reference sequence complemented with unique sequences of SCHU S4 (type A). Global SNP based phylogenetic clustering was able to resolve all non-related strains. The phylogenetic tree was used to guide the selection of informative SNPs specific to major nodes in the tree for development of a genotyping assay for identification of F. tularensis subspecies and clades. We designed and validated an assay that uses these SNPs to accurately genotype 39 additional F. tularensis strains as type A (A1, A2, A1a or A1b) or type B (B1 or B2).

CONCLUSION

Whole-genome SNP based clustering was shown to accurately identify SNPs for differentiation of F. tularensis subspecies and clades, emphasizing the potential power and utility of this methodology for selecting SNPs for typing of F. tularensis to the strain level. Additionally, whole genome sequence based SNP information gained from a representative population of strains may be used to perform evolutionary or phylogenetic comparisons of strains, or selection of unique strains for whole-genome sequencing projects.

VarDetect: a nucleotide sequence variation exploratory tool

Background

Single nucleotide polymorphisms (SNPs) are the most commonly studied units of genetic variation. The discovery of such variation may help to identify causative gene mutations in monogenic diseases and SNPs associated with predisposing genes in complex diseases. Accurate detection of SNPs requires software that can correctly interpret chromatogram signals to nucleotides.

Results

We present VarDetect, a stand-alone nucleotide variation exploratory tool that automatically detects nucleotide variation from fluorescence based chromatogram traces. Accurate SNP base-calling is achieved using pre-calculated peak content ratios, and is enhanced by rules which account for common sequence reading artifacts. The proposed software tool is benchmarked against four other well-known SNP discovery software tools (PolyPhred, novoSNP, Genalys and Mutation Surveyor) using fluorescence based chromatograms from 15 human genes. These chromatograms were obtained from sequencing 16 two-pooled DNA samples; a total of 32 individual DNA samples. In this comparison of automatic SNP detection tools, VarDetect achieved the highest detection efficiency.

Availability

VarDetect is compatible with most major operating systems such as Microsoft Windows, Linux, and Mac OSX. The current version of VarDetect is freely available at .