VARIANT: Command Line, Web service and Web interface for fast and accurate functional characterization of variants found by Next-Generation Sequencing

Jointly Integrating VCF-Based Variants and OWL-Based Biomedical Ontologies in MongoDB

The development of the next-generation sequencing (NGS) technologies has led to massive amounts of VCF (Variant Call Format) files, which have been the standard formats developed with 1000 Genomes Project. At the same time, with the widespread use of biomedical ontologies in the biomedical community, more and more applications have accepted the Web Ontology Language (OWL) as the dominant data format for the specifications of biomedical ontology descriptions, leading to the rapid growth of OWL-based biomedical ontology scale. In this paper, we seek to explore an effective method for the management of VCF-based genetic variants and OWL-based biological ontologies using the MongoDB database. Considering many current applications (such as the short genetic variations database dbSNP, etc.) are transitioning to the new design by using JSON (JavaScript Object Notation) to support future massive data expansion and interchanges. We firstly propose a series of rules for the mapping from VCF and OWL files to JSON files, and then present rule-based algorithms for transforming VCF-based genetic variants and OWL-based biological ontologies into JSON objects. On this basis, we introduce effective approaches of integrating the mapped JSON files in MongoDB. Finally, we complement this work with a set of experiments to show the performance of our proposed approaches. The source code of the proposed approaches could be freely available at https://github.com/lyotvincent/AJIA.

Identification of the Photoreceptor Transcriptional Co-Repressor SAMD11 as Novel Cause of Autosomal Recessive Retinitis Pigmentosa

Retinitis pigmentosa (RP), the most frequent form of inherited retinal dystrophy is characterized by progressive photoreceptor degeneration. Many genes have been implicated in RP development, but several others remain to be identified. Using a combination of homozygosity mapping, whole-exome and targeted next-generation sequencing, we found a novel homozygous nonsense mutation in SAMD11 in five individuals diagnosed with adult-onset RP from two unrelated consanguineous Spanish families. SAMD11 is ortholog to the mouse major retinal SAM domain (mr-s) protein that is implicated in CRX-mediated transcriptional regulation in the retina. Accordingly, protein-protein network analysis revealed a significant interaction of SAMD11 with CRX. Immunoblotting analysis confirmed strong expression of SAMD11 in human retina. Immunolocalization studies revealed SAMD11 was detected in the three nuclear layers of the human retina and interestingly differential expression between cone and rod photoreceptors was observed. Our study strongly implicates SAMD11 as novel cause of RP playing an important role in the pathogenesis of human degeneration of photoreceptors.

267 Spanish Exomes Reveal Population-Specific Differences in Disease-Related Genetic Variation

Recent results from large-scale genomic projects suggest that allele frequencies, which are highly relevant for medical purposes, differ considerably across different populations. The need for a detailed catalog of local variability motivated the whole-exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population. Like in other studies, a considerable number of rare variants were found (almost one-third of the described variants). There were also relevant differences in allelic frequencies in polymorphic variants, including ∼10,000 polymorphisms private to the Spanish population. The allelic frequencies of variants conferring susceptibility to complex diseases (including cancer, schizophrenia, Alzheimer disease, type 2 diabetes, and other pathologies) were overall similar to those of other populations. However, the trend is the opposite for variants linked to Mendelian and rare diseases (including several retinal degenerative dystrophies and cardiomyopathies) that show marked frequency differences between populations. Interestingly, a correspondence between differences in allelic frequencies and disease prevalence was found, highlighting the relevance of frequency differences in disease risk. These differences are also observed in variants that disrupt known drug binding sites, suggesting an important role for local variability in population-specific drug resistances or adverse effects. We have made the Spanish population variant server web page that contains population frequency information for the complete list of 170,888 variant positions we found publicly available (http://spv.babelomics.org/), We show that it if fundamental to determine population-specific variant frequencies to distinguish real disease associations from population-specific polymorphisms.

Gene Variant Databases and Sharing: Creating a Global Genomic Variant Database for Personalized Medicine

Revolutionary changes in sequencing technology and the desire to develop therapeutics for rare diseases have led to the generation of an enormous amount of genomic data in the last 5 years. Large-scale sequencing done in both research and diagnostic laboratories has linked many new genes to rare diseases, but has also generated a number of variants that we cannot interpret today. It is clear that we remain a long way from a complete understanding of the genomic variation in the human genome and its association with human health and disease. Recent studies identified susceptibility markers to infectious diseases and also the contribution of rare variants to complex diseases in different populations. The sequencing revolution has also led to the creation of a large number of databases that act as "keepers" of data, and in many cases give an interpretation of the effect of the variant. This interpretation is based on reports in the literature, prediction models, and in some cases is accompanied by functional evidence. As we move toward the practice of genomic medicine, and consider its place in "personalized medicine," it is time to ask ourselves how we can aggregate this wealth of data into a single database for multiple users with different goals.

Assessment of Targeted Next-Generation Sequencing as a Tool for the Diagnosis of Charcot-Marie-Tooth Disease and Hereditary Motor Neuropathy

Charcot-Marie-Tooth disease is characterized by broad genetic heterogeneity with >50 known disease-associated genes. Mutations in some of these genes can cause a pure motor form of hereditary motor neuropathy, the genetics of which are poorly characterized. We designed a panel comprising 56 genes associated with Charcot-Marie-Tooth disease/hereditary motor neuropathy. We validated this diagnostic tool by first testing 11 patients with pathological mutations. A cohort of 33 affected subjects was selected for this study. The DNAJB2 c.352+1G>A mutation was detected in two cases; novel changes and/or variants with low frequency (<1%) were found in 12 cases. There were no candidate variants in 18 cases, and amplification failed for one sample. The DNAJB2 c.352+1G>A mutation was also detected in three additional families. On haplotype analysis, all of the patients from these five families shared the same haplotype; therefore, the DNAJB2 c.352+1G>A mutation may be a founder event. Our gene panel allowed us to perform a very rapid and cost-effective screening of genes involved in Charcot-Marie-Tooth disease/hereditary motor neuropathy. Our diagnostic strategy was robust in terms of both coverage and read depth for all of the genes and patient samples. These findings demonstrate the difficulty in achieving a definitive molecular diagnosis because of the complexity of interpreting new variants and the genetic heterogeneity that is associated with these neuropathies.

Screening of CD96 and ASXL1 in 11 patients with Opitz C or Bohring-Opitz syndromes

Opitz C trigonocephaly (or Opitz C syndrome, OTCS) and Bohring-Opitz syndrome (BOS or C-like syndrome) are two rare genetic disorders with phenotypic overlap. The genetic causes of these diseases are not understood. However, two genes have been associated with OTCS or BOS with dominantly inherited de novo mutations. Whereas CD96 has been related to OTCS (one case) and to BOS (one case), ASXL1 has been related to BOS only (several cases). In this study we analyze CD96 and ASXL1 in a group of 11 affected individuals, including 2 sibs, 10 of them were diagnosed with OTCS, and one had a BOS phenotype. Exome sequences were available on six patients with OTCS and three parent pairs. Thus, we could analyze the CD96 and ASXL1 sequences in these patients bioinformatically. Sanger sequencing of all exons of CD96 and ASXL1 was carried out in the remaining patients. Detailed scrutiny of the sequences and assessment of variants allowed us to exclude putative pathogenic and private mutations in all but one of the patients. In this patient (with BOS) we identified a de novo mutation in ASXL1 (c.2100dupT). By nature and location within the gene, this mutation resembles those previously described in other BOS patients and we conclude that it may be responsible for the condition. Our results indicate that in 10 of 11, the disease (OTCS or BOS) cannot be explained by small changes in CD96 or ASXL1. However, the cohort is too small to make generalizations about the genetic etiology of these diseases.

Next-generation-based targeted sequencing as an efficient tool for the study of the genetic background in Hirschsprung patients

BACKGROUND

The development of next-generation sequencing (NGS) technologies has a great impact in the human variation detection given their high-throughput. These techniques are particularly helpful for the evaluation of the genetic background in disorders of complex genetic etiology such as Hirschsprung disease (HSCR). The purpose of this study was the design of a panel of HSCR associated genes as a rapid and efficient tool to perform genetic screening in a series of patients.

METHODS

We have performed NGS-based targeted sequencing (454-GS Junior) using a panel containing 26 associated or candidate genes for HSCR in a group of 11 selected HSCR patients.

RESULTS

The average percentage of covered bases was of 97%, the 91.4% of the targeted bases were covered with depth above 20X and the mean coverage was 422X. In addition, we have found a total of 13 new coding variants and 11 new variants within regulatory regions among our patients. These outcomes allowed us to re-evaluate the genetic component associated to HSCR in these patients.

CONCLUSIONS

Our validated NGS panel constitutes an optimum method for the identification of new variants in our patients. This approach could be used for a fast, reliable and more thorough genetic screening in future series of patients.

Genomic variant annotation and prioritization with ANNOVAR and wANNOVAR

Recent developments in sequencing techniques have enabled rapid and high-throughput generation of sequence data, democratizing the ability to compile information on large amounts of genetic variations in individual laboratories. However, there is a growing gap between the generation of raw sequencing data and the extraction of meaningful biological information. Here, we describe a protocol to use the ANNOVAR (ANNOtate VARiation) software to facilitate fast and easy variant annotations, including gene-based, region-based and filter-based annotations on a variant call format (VCF) file generated from human genomes. We further describe a protocol for gene-based annotation of a newly sequenced nonhuman species. Finally, we describe how to use a user-friendly and easily accessible web server called wANNOVAR to prioritize candidate genes for a Mendelian disease. The variant annotation protocols take 5-30 min of computer time, depending on the size of the variant file, and 5-10 min of hands-on time. In summary, through the command-line tool and the web server, these protocols provide a convenient means to analyze genetic variants generated in humans and other species.

Dissecting ancestry genomic background in substance dependence genome-wide association studies

AIMS

To understand the role of ancestral genomic background in substance dependence (SD) genome-wide association studies (GWAS), we analyzed population diversity at genetic loci associated with SD traits and evaluated its effect on GWAS outcomes.

MATERIALS & METHODS

We investigated 24 genes with variants associated with SD by GWAS; and 82 loci with putative subordinate roles with respect to SD-associated genes.

RESULTS

We observed high ancestry-related frequency differences in common functional alleles in GWAS relevant genes and their interactive partners. Common functional alleles with high frequency differences demonstrated significant effects on the GWAS outcomes.

CONCLUSION

Population differences in SD GWAS outcomes seem not to be influenced by general variation across the genome, but by ancestry-related local haplotype structures at SD-associated loci.

Assessing the impact of mutations found in next generation sequencing data over human signaling pathways

Modern sequencing technologies produce increasingly detailed data on genomic variation. However, conventional methods for relating either individual variants or mutated genes to phenotypes present known limitations given the complex, multigenic nature of many diseases or traits. Here we present PATHiVar, a web-based tool that integrates genomic variation data with gene expression tissue information. PATHiVar constitutes a new generation of genomic data analysis methods that allow studying variants found in next generation sequencing experiment in the context of signaling pathways. Simple Boolean models of pathways provide detailed descriptions of the impact of mutations in cell functionality so as, recurrences in functionality failures can easily be related to diseases, even if they are produced by mutations in different genes. Patterns of changes in signal transmission circuits, often unpredictable from individual genes mutated, correspond to patterns of affected functionalities that can be related to complex traits such as disease progression, drug response, etc. PATHiVar is available at: http://pathivar.babelomics.org.

Scripps Genome ADVISER: Annotation and Distributed Variant Interpretation SERver

Interpretation of human genomes is a major challenge. We present the Scripps Genome ADVISER (SG-ADVISER) suite, which aims to fill the gap between data generation and genome interpretation by performing holistic, in-depth, annotations and functional predictions on all variant types and effects. The SG-ADVISER suite includes a de-identification tool, a variant annotation web-server, and a user interface for inheritance and annotation-based filtration. SG-ADVISER allows users with no bioinformatics expertise to manipulate large volumes of variant data with ease--without the need to download large reference databases, install software, or use a command line interface. SG-ADVISER is freely available at genomics.scripps.edu/ADVISER.

Novel RP1 mutations and a recurrent BBS1 variant explain the co-existence of two distinct retinal phenotypes in the same pedigree

Background

Molecular diagnosis of Inherited Retinal Dystrophies (IRD) has long been challenging due to the extensive clinical and genetic heterogeneity present in this group of disorders. Here, we describe the clinical application of an integrated next-generation sequencing approach to determine the underlying genetic defects in a Spanish family with a provisional clinical diagnosis of autosomal recessive Retinitis Pigmentosa (arRP).

Results

Exome sequencing of the index patient resulted in the identification of the homozygous BBS1 p.M390R mutation. Sanger sequencing of additional members of the family showed lack of co-segregation of the p.M390R variant in some individuals. Clinical reanalysis indicated co-ocurrence of two different phenotypes in the same family: Bardet-Biedl syndrome in the individual harboring the BBS1 mutation and non-syndromic arRP in extended family members. To identify possible causative mutations underlying arRP, we conducted disease-targeted gene sequencing using a panel of 26 IRD genes. The in-house custom panel was validated using 18 DNA samples known to harbor mutations in relevant genes. All variants were redetected, indicating a high mutation detection rate. This approach allowed the identification of two novel heterozygous null mutations in RP1 (c.4582_4585delATCA; p.I1528Vfs*10 and c.5962dupA; p.I1988Nfs*3) which co-segregated with the disease in arRP patients. Additionally, a mutational screening in 96 patients of our cohort with genetically unresolved IRD revealed the presence of the c.5962dupA mutation in one unrelated family.

Conclusions

The combination of molecular findings for RP1 and BBS1 genes through exome and gene panel sequencing enabled us to explain the co-existence of two different retinal phenotypes in a family. The identification of two novel variants in RP1 suggests that the use of panels containing the prevalent genes of a particular population, together with an optimized data analysis pipeline, is an efficient and cost-effective approach that can be reliably implemented into the routine diagnostic process of diverse inherited retinal disorders. Moreover, the identification of these novel variants in two unrelated families supports the relatively high prevalence of RP1 mutations in Spanish population and the role of private mutations for commonly mutated genes, while extending the mutational spectrum of RP1.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-014-0143-2) contains supplementary material, which is available to authorized users.

ITScan: a web-based analysis tool for Internal Transcribed Spacer (ITS) sequences

Background

Studies on fungal diversity and ecology aim to identify fungi and to investigate their interactions with each other and with the environment. DNA sequence-based tools are essential for these studies because they can speed up the identification process and access greater fungal diversity than traditional methods. The nucleotide sequence encoding for the internal transcribed spacer (ITS) of the nuclear ribosomal RNA has recently been proposed as a standard marker for molecular identification of fungi and evaluation of fungal diversity. However, the analysis of large sets of ITS sequences involves many programs and steps, which makes this task intensive and laborious.

Findings

We developed the web-based pipeline ITScan, which automates the analysis of fungal ITS sequences generated either by Sanger or Next Generation Sequencing (NGS) platforms. Validation was performed using datasets containing ca. 2,000 to 40,000 sequences each.

Conclusions

ITScan is an online and user-friendly automated pipeline for fungal diversity analysis and identification based on ITS sequences. It speeds up a process which would otherwise be repetitive and time-consuming for users. The ITScan tool and documentation are available at http://evol.rc.unesp.br:8083/itscan.

Current trend of annotating single nucleotide variation in humans--A case study on SNVrap

As high throughput methods, such as whole genome genotyping arrays, whole exome sequencing (WES) and whole genome sequencing (WGS), have detected huge amounts of genetic variants associated with human diseases, function annotation of these variants is an indispensable step in understanding disease etiology. Large-scale functional genomics projects, such as The ENCODE Project and Roadmap Epigenomics Project, provide genome-wide profiling of functional elements across different human cell types and tissues. With the urgent demands for identification of disease-causal variants, comprehensive and easy-to-use annotation tool is highly in demand. Here we review and discuss current progress and trend of the variant annotation field. Furthermore, we introduce a comprehensive web portal for annotating human genetic variants. We use gene-based features and the latest functional genomics datasets to annotate single nucleotide variation (SNVs) in human, at whole genome scale. We further apply several function prediction algorithms to annotate SNVs that might affect different biological processes, including transcriptional gene regulation, alternative splicing, post-transcriptional regulation, translation and post-translational modifications. The SNVrap web portal is freely available at http://jjwanglab.org/snvrap.

The role of the interactome in the maintenance of deleterious variability in human populations

Recent genomic projects have revealed the existence of an unexpectedly large amount of deleterious variability in the human genome. Several hypotheses have been proposed to explain such an apparently high mutational load. However, the mechanisms by which deleterious mutations in some genes cause a pathological effect but are apparently innocuous in other genes remain largely unknown. This study searched for deleterious variants in the 1,000 genomes populations, as well as in a newly sequenced population of 252 healthy Spanish individuals. In addition, variants causative of monogenic diseases and somatic variants from 41 chronic lymphocytic leukaemia patients were analysed. The deleterious variants found were analysed in the context of the interactome to understand the role of network topology in the maintenance of the observed mutational load. Our results suggest that one of the mechanisms whereby the effect of these deleterious variants on the phenotype is suppressed could be related to the configuration of the protein interaction network. Most of the deleterious variants observed in healthy individuals are concentrated in peripheral regions of the interactome, in combinations that preserve their connectivity, and have a marginal effect on interactome integrity. On the contrary, likely pathogenic cancer somatic deleterious variants tend to occur in internal regions of the interactome, often with associated structural consequences. Finally, variants causative of monogenic diseases seem to occupy an intermediate position. Our observations suggest that the real pathological potential of a variant might be more a systems property rather than an intrinsic property of individual proteins.

A web tool for the design and management of panels of genes for targeted enrichment and massive sequencing for clinical applications

Disease targeted sequencing is gaining importance as a powerful and cost-effective application of high throughput sequencing technologies to the diagnosis. However, the lack of proper tools to process the data hinders its extensive adoption. Here we present TEAM, an intuitive and easy-to-use web tool that fills the gap between the predicted mutations and the final diagnostic in targeted enrichment sequencing analysis. The tool searches for known diagnostic mutations, corresponding to a disease panel, among the predicted patient's variants. Diagnostic variants for the disease are taken from four databases of disease-related variants (HGMD-public, HUMSAVAR, ClinVar and COSMIC.) If no primary diagnostic variant is found, then a list of secondary findings that can help to establish a diagnostic is produced. TEAM also provides with an interface for the definition of and customization of panels, by means of which, genes and mutations can be added or discarded to adjust panel definitions. TEAM is freely available at: http://team.babelomics.org.

A web-based interactive framework to assist in the prioritization of disease candidate genes in whole-exome sequencing studies

Whole-exome sequencing has become a fundamental tool for the discovery of disease-related genes of familial diseases and the identification of somatic driver variants in cancer. However, finding the causal mutation among the enormous background of individual variability in a small number of samples is still a big challenge. Here we describe a web-based tool, BiERapp, which efficiently helps in the identification of causative variants in family and sporadic genetic diseases. The program reads lists of predicted variants (nucleotide substitutions and indels) in affected individuals or tumor samples and controls. In family studies, different modes of inheritance can easily be defined to filter out variants that do not segregate with the disease along the family. Moreover, BiERapp integrates additional information such as allelic frequencies in the general population and the most popular damaging scores to further narrow down the number of putative variants in successive filtering steps. BiERapp provides an interactive and user-friendly interface that implements the filtering strategy used in the context of a large-scale genomic project carried out by the Spanish Network for Research in Rare Diseases (CIBERER) in which more than 800 exomes have been analyzed. BiERapp is freely available at: http://bierapp.babelomics.org/

AVIA: an interactive web-server for annotation, visualization and impact analysis of genomic variations

MOTIVATION

The plethora of information that emerges from large-scale genome characterization studies has triggered the development of computational frameworks and tools for efficient analysis, interpretation and visualization of genomic data. Functional annotation of genomic variations and the ability to visualize the data in the context of whole genome and/or multiple genomes has remained a challenging task. We have developed an interactive web-based tool, AVIA (Annotation, Visualization and Impact Analysis), to explore and interpret large sets of genomic variations (single nucleotide variations and insertion/deletions) and to help guide and summarize genomic experiments. The annotation, summary plots and tables are packaged and can be downloaded by the user from the email link provided.

AVAILABILITY AND IMPLEMENTATION

http://avia.abcc.ncifcrf.gov.

INsPeCT: INtegrative Platform for Cancer Transcriptomics

The emergence of transcriptomics, fuelled by high-throughput sequencing technologies, has changed the nature of cancer research and resulted in a massive accumulation of data. Computational analysis, integration, and data visualization are now major bottlenecks in cancer biology and translational research. Although many tools have been brought to bear on these problems, their use remains unnecessarily restricted to computational biologists, as many tools require scripting skills, data infrastructure, and powerful computational facilities. New user-friendly, integrative, and automated analytical approaches are required to make computational methods more generally useful to the research community. Here we present INsPeCT (INtegrative Platform for Cancer Transcriptomics), which allows users with basic computer skills to perform comprehensive in-silico analyses of microarray, ChIP-seq, and RNA-seq data. INsPeCT supports the selection of interesting genes for advanced functional analysis. Included in its automated workflows are (i) a novel analytical framework, RMaNI (regulatory module network inference), which supports the inference of cancer subtype-specific transcriptional module networks and the analysis of modules; and (ii) WGCNA (weighted gene co-expression network analysis), which infers modules of highly correlated genes across microarray samples, associated with sample traits, eg survival time. INsPeCT is available free of cost from Bioinformatics Resource Australia-EMBL and can be accessed at http://inspect.braembl.org.au.

Two novel mutations in the BCKDK (branched-chain keto-acid dehydrogenase kinase) gene are responsible for a neurobehavioral deficit in two pediatric unrelated patients

Inactivating mutations in the BCKDK gene, which codes for the kinase responsible for the negative regulation of the branched-chain α-keto acid dehydrogenase complex (BCKD), have recently been associated with a form of autism in three families. In this work, two novel exonic BCKDK mutations, c.520C>G/p.R174G and c.1166T>C/p.L389P, were identified at the homozygous state in two unrelated children with persistently reduced body fluid levels of branched-chain amino acids (BCAAs), developmental delay, microcephaly, and neurobehavioral abnormalities. Functional analysis of the mutations confirmed the missense character of the c.1166T>C change and showed a splicing defect r.[520c>g;521_543del]/p.R174Gfs1*, for c.520C>G due to the presence of a new donor splice site. Mutation p.L389P showed total loss of kinase activity. Moreover, patient-derived fibroblasts showed undetectable (p.R174Gfs1*) or barely detectable (p.L389P) levels of BCKDK protein and its phosphorylated substrate (phospho-E1α), resulting in increased BCKD activity and the very rapid BCAA catabolism manifested by the patients' clinical phenotype. Based on these results, a protein-rich diet plus oral BCAA supplementation was implemented in the patient homozygous for p.R174Gfs1*. This treatment normalized plasma BCAA levels and improved growth, developmental and behavioral variables. Our results demonstrate that BCKDK mutations can result in neurobehavioral deficits in humans and support the rationale for dietary intervention.

Combined genetic and high-throughput strategies for molecular diagnosis of inherited retinal dystrophies

Most diagnostic laboratories are confronted with the increasing demand for molecular diagnosis from patients and families and the ever-increasing genetic heterogeneity of visual disorders. Concerning Retinal Dystrophies (RD), almost 200 causative genes have been reported to date, and most families carry private mutations. We aimed to approach RD genetic diagnosis using all the available genetic information to prioritize candidates for mutational screening, and then restrict the number of cases to be analyzed by massive sequencing. We constructed and optimized a comprehensive cosegregation RD-chip based on SNP genotyping and haplotype analysis. The RD-chip allows to genotype 768 selected SNPs (closely linked to 100 RD causative genes) in a single cost-, time-effective step. Full diagnosis was attained in 17/36 Spanish pedigrees, yielding 12 new and 12 previously reported mutations in 9 RD genes. The most frequently mutated genes were USH2A and CRB1. Notably, RD3–up to now only associated to Leber Congenital Amaurosis– was identified as causative of Retinitis Pigmentosa. The main assets of the RD-chip are: i) the robustness of the genetic information that underscores the most probable candidates, ii) the invaluable clues in cases of shared haplotypes, which are indicative of a common founder effect, and iii) the detection of extended haplotypes over closely mapping genes, which substantiates cosegregation, although the assumptions in which the genetic analysis is based could exceptionally lead astray. The combination of the genetic approach with whole exome sequencing (WES) greatly increases the diagnosis efficiency, and revealed novel mutations in USH2A and GUCY2D. Overall, the RD-chip diagnosis efficiency ranges from 16% in dominant, to 80% in consanguineous recessive pedigrees, with an average of 47%, well within the upper range of massive sequencing approaches, highlighting the validity of this time- and cost-effective approach whilst high-throughput methodologies become amenable for routine diagnosis in medium sized labs.

Exon identity crisis: disease-causing mutations that disrupt the splicing code

Cis-acting RNA elements control the accurate expression of human multi-exon protein coding genes. Single nucleotide variants altering the fidelity of this regulatory code and, consequently, pre-mRNA splicing are expected to contribute to the etiology of numerous human diseases.

Computational approaches to identify functional genetic variants in cancer genomes

The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype.

Deciphering intrafamilial phenotypic variability by exome sequencing in a Bardet-Biedl family

Bardet-Biedl syndrome (BBS) is a model ciliopathy characterized by a wide range of clinical variability. The heterogeneity of this condition is reflected in the number of underlying gene defects and the epistatic interactions between the proteins encoded. BBS is generally inherited in an autosomal recessive trait. However, in some families, mutations across different loci interact to modulate the expressivity of the phenotype. In order to investigate the magnitude of epistasis in one BBS family with remarkable intrafamilial phenotypic variability, we designed an exome sequencing-based approach using SOLID 5500xl platform. This strategy allowed the reliable detection of the primary causal mutations in our family consisting of two novel compound heterozygous mutations in McKusick-Kaufman syndrome (MKKS) gene (p.D90G and p.V396F). Additionally, exome sequencing enabled the detection of one novel heterozygous NPHP4 variant which is predicted to activate a cryptic acceptor splice site and is only present in the most severely affected patient. Here, we provide an exome sequencing analysis of a BBS family and show the potential utility of this tool, in combination with network analysis, to detect disease-causing mutations and second-site modifiers. Our data demonstrate how next-generation sequencing (NGS) can facilitate the dissection of epistatic phenomena, and shed light on the genetic basis of phenotypic variability.

SeqReporter: automating next-generation sequencing result interpretation and reporting workflow in a clinical laboratory

A wide repertoire of bioinformatics applications exist for next-generation sequencing data analysis; however, certain requirements of the clinical molecular laboratory limit their use: i) comprehensive report generation, ii) compatibility with existing laboratory information systems and computer operating system, iii) knowledgebase development, iv) quality management, and v) data security. SeqReporter is a web-based application developed using ASP.NET framework version 4.0. The client-side was designed using HTML5, CSS3, and Javascript. The server-side processing (VB.NET) relied on interaction with a customized SQL server 2008 R2 database. Overall, 104 cases (1062 variant calls) were analyzed by SeqReporter. Each variant call was classified into one of five report levels: i) known clinical significance, ii) uncertain clinical significance, iii) pending pathologists' review, iv) synonymous and deep intronic, and v) platform and panel-specific sequence errors. SeqReporter correctly annotated and classified 99.9% (859 of 860) of sequence variants, including 68.7% synonymous single-nucleotide variants, 28.3% nonsynonymous single-nucleotide variants, 1.7% insertions, and 1.3% deletions. One variant of potential clinical significance was re-classified after pathologist review. Laboratory information system-compatible clinical reports were generated automatically. SeqReporter also facilitated quality management activities. SeqReporter is an example of a customized and well-designed informatics solution to optimize and automate the downstream analysis of clinical next-generation sequencing data. We propose it as a model that may envisage the development of a comprehensive clinical informatics solution.

CPAP: Cancer Panel Analysis Pipeline

Targeted sequencing using next-generation sequencing technologies is currently being rapidly adopted for clinical sequencing and cancer marker tests. However, no existing bioinformatics tool is available for the analysis and visualization of multiple targeted sequencing datasets. In the present study, we use cancer panel targeted sequencing datasets generated by the Life Technologies Ion Personal Genome Machine Sequencer as an example to illustrate how to develop an automated pipeline for the comparative analyses of multiple datasets. Cancer Panel Analysis Pipeline (CPAP) uses standard output files from variant calling software to generate a distribution map of SNPs among all of the samples in a circular diagram generated by Circos. The diagram is hyperlinked to a dynamic HTML table that allows the users to identify target SNPs by using different filters. CPAP also integrates additional information about the identified SNPs by linking to an integrated SQL database compiled from SNP-related databases, including dbSNP, 1000 Genomes Project, COSMIC, and dbNSFP. CPAP only takes 17 min to complete a comparative analysis of 500 datasets. CPAP not only provides an automated platform for the analysis of multiple cancer panel datasets but can also serve as a model for any customized targeted sequencing project.

Genomics and transcriptomics in drug discovery

The popularization of genomic high-throughput technologies is causing a revolution in biomedical research and, particularly, is transforming the field of drug discovery. Systems biology offers a framework to understand the extensive human genetic heterogeneity revealed by genomic sequencing in the context of the network of functional, regulatory and physical protein-drug interactions. Thus, approaches to find biomarkers and therapeutic targets will have to take into account the complex system nature of the relationships of the proteins with the disease. Pharmaceutical companies will have to reorient their drug discovery strategies considering the human genetic heterogeneity. Consequently, modeling and computational data analysis will have an increasingly important role in drug discovery.

Genome Maps, a new generation genome browser

Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org.

A survey of tools for variant analysis of next-generation genome sequencing data

Recent advances in genome sequencing technologies provide unprecedented opportunities to characterize individual genomic landscapes and identify mutations relevant for diagnosis and therapy. Specifically, whole-exome sequencing using next-generation sequencing (NGS) technologies is gaining popularity in the human genetics community due to the moderate costs, manageable data amounts and straightforward interpretation of analysis results. While whole-exome and, in the near future, whole-genome sequencing are becoming commodities, data analysis still poses significant challenges and led to the development of a plethora of tools supporting specific parts of the analysis workflow or providing a complete solution. Here, we surveyed 205 tools for whole-genome/whole-exome sequencing data analysis supporting five distinct analytical steps: quality assessment, alignment, variant identification, variant annotation and visualization. We report an overview of the functionality, features and specific requirements of the individual tools. We then selected 32 programs for variant identification, variant annotation and visualization, which were subjected to hands-on evaluation using four data sets: one set of exome data from two patients with a rare disease for testing identification of germline mutations, two cancer data sets for testing variant callers for somatic mutations, copy number variations and structural variations, and one semi-synthetic data set for testing identification of copy number variations. Our comprehensive survey and evaluation of NGS tools provides a valuable guideline for human geneticists working on Mendelian disorders, complex diseases and cancers.

SNVDis: a proteome-wide analysis service for evaluating nsSNVs in protein functional sites and pathways

Amino acid changes due to non-synonymous variation are included as annotations for individual proteins in UniProtKB/Swiss-Prot and RefSeq which present biological data in a protein- or gene-centric fashion. Unfortunately, proteome-wide analysis of non-synonymous single-nucleotide variations (nsSNVs) is not easy to perform because information on nsSNVs and functionally important sites are not well integrated both within and between databases and their search engines. We have developed SNVDis that allows evaluation of proteome-wide nsSNV distribution in functional sites, domains and pathways. More specifically, we have integrated human-specific data from major variation databases (UniProtKB, dbSNP and COSMIC), comprehensive sequence feature annotation from UniProtKB, Pfam, RefSeq, Conserved Domain Database (CDD) and pathway information from Protein ANalysis THrough Evolutionary Relationships (PANTHER) and mapped all of them in a uniform and comprehensive way to the human reference proteome provided by UniProtKB/Swiss-Prot. Integrated information of active sites, pathways, binding sites, domains, which are extracted from a number of different sources, provides a detailed overview of how nsSNVs are distributed over the human proteome and pathways and how they intersect with functional sites of proteins. Additionally, it is possible to find out whether there is an over- or under-representation of nsSNVs in specific domains, pathways or user-defined protein lists. The underlying datasets are updated once every 3months. SNVDis is freely available at http://hive.biochemistry.gwu.edu/tool/snvdis.