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A common approach in clinical diagnostic laboratories to variant assessment from tumor molecular profiling is sequencing of genomic DNA extracted from both tumor (somatic) and normal (germline) tissue, with subsequent variant comparison to identify true somatic variants with potential impact on patient treatment or prognosis. However, challenges exist in paired tumor-normal testing, including increased cost of dual sample testing and identification of germline cancer predisposing variants. Alternatively, somatic variants can be identified by in silico tumor-only variant filtration precluding the need for matched normal testing. The barrier to tumor-only variant filtration is defining a reliable approach, with high sensitivity and specificity to identify somatic variants. In this study, we used retrospective data sets from paired tumor-normal samples tested on small (48 gene) and large (555 gene) targeted next-generation sequencing panels, to model algorithms for tumor-only variants classification. The optimal algorithm required an ordinal filtering approach using information from variant population databases (1000 Genomes Phase 3, ESP6500, ExAC), clinical mutation databases (ClinVar), and information on recurring clinically relevant somatic variants. Overall the tumor-only variant filtration strategy described in this study can define clinically relevant somatic variants from tumor-only analysis with sensitivity of 97% to 99% and specificity of 87% to 94%, and with significant potential utility for clinical laboratories implementing tumor-only molecular profiling.

Next-generation sequencing is radically changing how DNA diagnostic laboratories operate. What started as a single-gene profession is now developing into gene panel sequencing and whole exome and genome sequencing (WES/WGS) analyses. With further advances in sequencing technology and concomitant price reductions, whole genome sequencing (WGS) will soon become the standard and be routinely offered. Here we focus on the critical steps involved in performing WGS, with a particular emphasis on points where WGS differs from WES, the important variables that should be taken into account, and the quality control measures that can be taken to monitor the process. The points discussed here, combined with recent publications on guidelines for reporting variants, will facilitate the routine implementation of WGS into a diagnostic setting. This article is protected by copyright. All rights reserved. ispartof: Human Mutation vol:38 issue:8 pages:912-921 ispartof: location:United States status: published

Whole genome analysis, now including whole genome sequencing, is moving rapidly into the clinical setting, leading to detection of human variation on a broader scale than ever before. Interpreting this information will depend on the availability of thorough and accurate phenotype information, and the ability to curate, store, and access data on genotype-phenotype relationships. This idea has already been demonstrated within the context of chromosome microarray (CMA) testing. The International Standards for Cytogenomic Arrays (ISCA) Consortium promotes standardization of variant interpretation for this technology through its initiatives, including the formation of a publicly available database housing clinical CMA data. Recognizing that phenotypic data is essential for the interpretation of genomic variants, the ISCA Consortium has developed tools to facilitate the collection of this data and its deposition in a standardized, structured format within the ISCA Consortium database. This rich source of phenotypic data can also be used within broader applications, such as developing phenotypic profiles of emerging genomic disorders, the identification of candidate regions for particular phenotypes, or the creation of tools for use in clinical practice. We summarize the ISCA experience as a model for ongoing efforts incorporating phenotype data with genotype data to improve the quality of research and clinical care in human genetics.

The range of commercially available array platforms and analysis software packages is expanding and their utility is improving, making reliable detection of copy-number variants (CNVs) relatively straightforward. Reliable interpretation of CNV data, however, is often difficult and requires expertise. With our knowledge of the human genome growing rapidly, applications for array testing continuously broadening, and the resolution of CNV detection increasing, this leads to great complexity in interpreting what can be daunting data. Correct CNV interpretation and optimal use of the genotype information provided by single-nucleotide polymorphism probes on an array depends largely on knowledge present in various resources. In addition to the availability of host laboratories' own datasets and national registries, there are several public databases and Internet resources with genotype and phenotype information that can be used for array data interpretation. With so many resources now available, it is important to know which are fit-for-purpose in a diagnostic setting. We summarize the characteristics of the most commonly used Internet databases and resources, and propose a general data interpretation strategy that can be used for comparative hybridization, comparative intensity, and genotype-based array data. Hum Mutat 33: 930-940, 2012. (C) 2012 Wiley Periodicals, Inc.

Genome-wide array comparative genomic hybridization screening is uncovering pathogenic submicroscopic chromosomal imbalances in patients with developmental disorders. In those patients, imbalances appear now to be scattered across the whole genome, and most patients carry different chromosomal anomalies. Screening patients with developmental disorders can be considered a forward functional genome screen. The imbalances pinpoint the location of genes that are involved in human development. Because most imbalances encompass regions harboring multiple genes, the challenge is to (1) identify those genes responsible for the specific phenotype and (2) disentangle the role of the different genes located in an imbalanced region. In this review, we discuss novel tools and relevant databases that have recently been developed to aid this gene discovery process. Identification of the functional relevance of genes will not only deepen our understanding of human development but will, in addition, aid in the data interpretation and improve genetic counseling.

Biomedical literature provides a rich but unstructured source of associations between chromosomal regions and biomedical concepts. By mining MEDLINE abstracts, we annotate the human genome at the level of cytogenetic bands. Our method creates a set of chromosomal aberration maps that associate cytogenetic bands to biomedical concepts from a variety of controlled vocabularies, including disease, dysmorphology, anatomy, development and Gene Ontology branches. The association between a band (e.g. 4p16.3) and a concept (e.g. microcephaly) is assessed by the statistical overrepresentation of this concept in the abstracts relating to this band. Our method is validated using existing genome annotation resources and known chromosomal aberration maps and is further illustrated through a case study on heart disease. Our chromosomal aberration maps provide diagnostics support to clinical geneticists, aid cytogeneticists to interpret and report cytogenetic findings and support researchers interested in human gene function. The method is available as a web application, aBandApart, at http://www.esat.kuleuven.be/abandapart/.

The European Cytogeneticists Association Register of Unbalanced Chromosome Aberrations (ECARUCA, www.ecaruca.net) is an online database initiated in 2003 that collects and provides detailed, curated clinical and molecular information on rare unbalanced chromosome aberrations. ECARUCA now contains over 4800 cases with a total of more than 6600 genetic aberrations and has over 3000 account holders worldwide. Recently, the ECARUCA web site was renewed, including the presentation of interesting case reports in collaboration with the European Journal of Medical Genetics. This article gives an overview of the current status and future plans of the online ECARUCA database. (c) 2013 Elsevier Masson SAS. All rights reserved.

Many patients suffering from developmental disorders harbor submicroscopic deletions or duplications that, by affecting the copy number of dosage-sensitive genes or disrupting normal gene expression, lead to disease. However, many aberrations are novel or extremely rare, making clinical interpretation problematic and genotype-phenotype correlations uncertain. Identification of patients sharing a genomic rearrangement and having phenotypic features in common leads to greater certainty in the pathogenic nature of the rearrangement and enables new syndromes to be defined. To facilitate the analysis of these rare events, we have developed an interactive web-based database called DECIPHER (Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources) which incorporates a suite of tools designed to aid the interpretation of submicroscopic chromosomal imbalance, inversions, and translocations. DECIPHER catalogs common copy-number changes in normal populations and thus, by exclusion, enables changes that are novel and potentially pathogenic to be identified. DECIPHER enhances genetic counseling by retrieving relevant information from a variety of bioinformatics resources. Known and predicted genes within an aberration are listed in the DECIPHER patient report, and genes of recognized clinical importance are highlighted and prioritized. DECIPHER enables clinical scientists worldwide to maintain records of phenotype and chromosome rearrangement for their patients and, with informed consent, share this information with the wider clinical research community through display in the genome browser Ensembl. By sharing cases worldwide, clusters of rare cases having phenotype and structural rearrangement in common can be identified, leading to the delineation of new syndromes and furthering understanding of gene function. ispartof: American Journal of Human Genetics vol:84 issue:4 pages:524-533 ispartof: location:United States status: published

Text-mining technologies can be integrated with genome annotation systems, increasing the availability of annotated cis-regulatory data., Background Decoding transcriptional regulatory networks and the genomic cis-regulatory logic implemented in their control nodes is a fundamental challenge in genome biology. High-throughput computational and experimental analyses of regulatory networks and sequences rely heavily on positive control data from prior small-scale experiments, but the vast majority of previously discovered regulatory data remains locked in the biomedical literature. Results We develop text-mining strategies to identify relevant publications and extract sequence information to assist the regulatory annotation process. Using a vector space model to identify Medline abstracts from papers likely to have high cis-regulatory content, we demonstrate that document relevance ranking can assist the curation of transcriptional regulatory networks and estimate that, minimally, 30,000 papers harbor unannotated cis-regulatory data. In addition, we show that DNA sequences can be extracted from primary text with high cis-regulatory content and mapped to genome sequences as a means of identifying the location, organism and target gene information that is critical to the cis-regulatory annotation process. Conclusion Our results demonstrate that text-mining technologies can be successfully integrated with genome annotation systems, thereby increasing the availability of annotated cis-regulatory data needed to catalyze advances in the field of gene regulation.

Elucidating regulatory networks is an intensively studied topic in bioinformatics. Integration of different sources of information could facilitate this task. We propose to incorporate these information sources in the structure prior of a Bayesian network. We are currently investigating two complementary sources of information: PubMed abstracts combined with publicly available taxonomies or ontologies, and known protein-DNA interactions. These priors, either separately or combined, have the potential of reducing the complexity of reverse-engineering regulatory networks while creating more robust and reliable models. Moreover this approach can easily be extended with other data sources. In such a way Bayesian networks provide a powerful framework for data integration and regulatory network modeling.

Array CGH (comparative genomic hybridization) enables the identification of chromosomal copy number changes. The availability of clone sets covering the human genome opens the possibility for the widespread use of array CGH for both research and diagnostic purposes. In this manuscript we report on the parameters that were critical for successful implementation of the technology, assess quality criteria, and discuss the potential benefits and pitfalls of the technology for improved pre- and postnatal constitutional genetic diagnosis. We propose to name the genome-wide array CGH “molecular karyotyping,” in analogy with conventional karyotyping that uses staining methods to visualize chromosomes.

We implemented a framework called TXTGate that combines literature indices of selected public biological resources in a flexible text-mining system designed towards the analysis of groups of genes. By means of tailored vocabularies, term- as well as gene-centric views are offered on selected textual fields and MEDLINE abstracts used in LocusLink and the Saccharomyces Genome Database. Subclustering and links to external resources allow for in-depth analysis of the resulting term profiles.

Recently, large-scale benign copy-number variations (CNVs)--encompassing over 12% of the genome and containing genes considered to be dosage tolerant for human development--were uncovered in the human population. Here we present a family with a novel autosomal-dominantly inherited syndrome characterized by microtia, eye coloboma, and imperforation of the nasolacrimal duct. This phenotype is linked to a cytogenetically visible alteration at 4pter consisting of five copies of a copy-number-variable region, encompassing a low-copy repeat (LCR)-rich sequence. We demonstrate that the approximately 750 kb amplicon occurs in exact tandem copies. This is the first example of an amplified CNV associated with a Mendelian disorder, a discovery that implies that genome screens for genetic disorders should include the analysis of so-called benign CNVs and LCRs. ispartof: American Journal of Human Genetics vol:82 issue:1 pages:181-187 ispartof: location:United States status: published

Background How to efficiently integrate the daily practice of molecular biologists, geneticists, and clinicians with the emerging computational strategies from systems biology is still much of an open question. Description We built on the recent advances in Wiki-based technologies to develop a collaborative knowledge base and gene prioritization portal aimed at mapping genes and genomic regions, and untangling their relations with corresponding human phenotypes, congenital heart defects (CHDs). This portal is not only an evolving community repository of current knowledge on the genetic basis of CHDs, but also a collaborative environment for the study of candidate genes potentially implicated in CHDs - in particular by integrating recent strategies for the statistical prioritization of candidate genes. It thus serves and connects the broad community that is facing CHDs, ranging from the pediatric cardiologist and clinical geneticist to the basic investigator of cardiogenesis. Conclusions This study describes the first specialized portal to collaboratively annotate and analyze gene-phenotype networks. Of broad interest to the biological community, we argue that such portals will play a significant role in systems biology studies of numerous complex biological processes. CHDWiki is accessible at http://www.esat.kuleuven.be/~bioiuser/chdwiki ispartof: Genome Medicine vol:2 issue:3 pages:1-9 ispartof: location:England status: published