Development, Validation, and Implementation of an Augmented Multiwell, Multitarget Quantitative PCR-Human Papillomavirus Genotyping Analysis through Software Automation, Data Science, and Artificial Intelligence.

The value of human papillomavirus (HPV) testing for cervical cancer screening is well established, where its use as a primary screening option or as a reflex test after atypical cytology results has recently gained wide acceptance. The importance of full genotyping and viral load determination has been demonstrated to enhance the clinical understanding of the viral infection progression during follow-up or after treatment, thereby providing clinicians with supplementary tools for optimized patient management. In this study, a new analysis method for the RIATOL quantitative PCR assay was developed, validated, and implemented in the laboratory of clinical molecular pathology at AML, under national accreditation and following the International Organization for Standardization guidelines. It presents the successful validation of a high-throughput, multitarget HPV analysis method, with enhanced accuracy on both qualitative and quantitative end results. This is achieved by software standardization and automation of PCR curve analysis and interpretation, using data science and artificial intelligence. Moreover, the user-centric functionality of the platform was demonstrated to enhance both staff training and routine analysis workflows, thereby saving time and laboratory personnel resources. Overall, the integration of the FastFinder plugin semi-automatic analysis algorithm with the RIATOL real-time quantitative PCR assay proved to be a remarkable advancement in high-throughput HPV quantification, with demonstrated capability to provide highly accurate clinical-grade results and to reduce manual variability and analysis time.

Reliable and Scalable SARS-CoV-2 qPCR Testing at a High Sample Throughput: Lessons Learned from the Belgian Initiative.

We present our approach to rapidly establishing a standardized, multi-site, nation-wide COVID-19 screening program in Belgium. Under auspices of a federal government Task Force responsible for upscaling the country's testing capacity, we were able to set up a national testing initiative with readily available resources, putting in place a robust, validated, high-throughput, and decentralized qPCR molecular testing platform with embedded proficiency testing. We demonstrate how during an acute scarcity of equipment, kits, reagents, personnel, protective equipment, and sterile plastic supplies, we introduced an approach to rapidly build a reliable, validated, high-volume, high-confidence workflow based on heterogeneous instrumentation and diverse assays, assay components, and protocols. The workflow was set up with continuous quality control monitoring, tied together through a clinical-grade information management platform for automated data analysis, real-time result reporting across different participating sites, qc monitoring, and making result data available to the requesting physician and the patient. In this overview, we address challenges in optimizing high-throughput cross-laboratory workflows with minimal manual intervention through software, instrument and assay validation and standardization, and a process for harmonized result reporting and nation-level infection statistics monitoring across the disparate testing methodologies and workflows, necessitated by a rapid scale-up as a response to the pandemic.

Somatic Tumor Variant Filtration Strategies to Optimize Tumor-Only Molecular Profiling Using Targeted Next-Generation Sequencing Panels.

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.

Critical points for an accurate human genome analysis.

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 whole-genome sequencing (WES/WGS) analyses. With further advances in sequencing technology and concomitant price reductions, 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.

The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data.

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.

An update on ECARUCA, the European Cytogeneticists Association Register of Unbalanced Chromosome Aberrations.

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.

Phenotypic information in genomic variant databases enhances clinical care and research: the International Standards for Cytogenomic Arrays Consortium experience.

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 chromosomal 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 are essential for the interpretation of genomic variants, the ISCA Consortium has developed tools to facilitate the collection of these 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, identification of candidate regions for particular phenotypes, or 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.

Diagnostic interpretation of array data using public databases and internet sources.

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.

Collaboratively charting the gene-to-phenotype network of human congenital heart defects.

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.

An experimental loop design for the detection of constitutional chromosomal aberrations by array CGH.

BACKGROUND: Comparative genomic hybridization microarrays for the detection of constitutional chromosomal aberrations is the application of microarray technology coming fastest into routine clinical application. Through genotype-phenotype association, it is also an important technique towards the discovery of disease causing genes and genomewide functional annotation in human. When using a two-channel microarray of genomic DNA probes for array CGH, the basic setup consists in hybridizing a patient against a normal reference sample. Two major disadvantages of this setup are (1) the use of half of the resources to measure a (little informative) reference sample and (2) the possibility that deviating signals are caused by benign copy number variation in the "normal" reference instead of a patient aberration. Instead, we apply an experimental loop design that compares three patients in three hybridizations. RESULTS: We develop and compare two statistical methods (linear models of log ratios and mixed models of absolute measurements). In an analysis of 27 patients seen at our genetics center, we observed that the linear models of the log ratios are advantageous over the mixed models of the absolute intensities. CONCLUSION: The loop design and the performance of the statistical analysis contribute to the quick adoption of array CGH as a routine diagnostic tool. They lower the detection limit of mosaicisms and improve the assignment of copy number variation for genetic association studies.

DECIPHER: Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources.

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.

Comparison of vocabularies, representations and ranking algorithms for gene prioritization by text mining.

MOTIVATION: Computational gene prioritization methods are useful to help identify susceptibility genes potentially being involved in genetic disease. Recently, text mining techniques have been applied to extract prior knowledge from text-based genomic information sources and this knowledge can be used to improve the prioritization process. However, the effect of various vocabularies, representations and ranking algorithms on text mining for gene prioritization is still an issue that requires systematic and comparative studies. Therefore, a benchmark study about the vocabularies, representations and ranking algorithms in gene prioritization by text mining is discussed in this article. RESULTS: We investigated 5 different domain vocabularies, 2 text representation schemes and 27 linear ranking algorithms for disease gene prioritization by text mining. We indexed 288 177 MEDLINE titles and abstracts with the TXTGate text pro.ling system and adapted the benchmark dataset of the Endeavour gene prioritization system that consists of 618 disease-causing genes. Textual gene pro.les were created and their performance for prioritization were evaluated and discussed in a comparative manner. The results show that inverse document frequency-based representation of gene term vectors performs better than the term-frequency inverse document-frequency representation. The eVOC and MESH domain vocabularies perform better than Gene Ontology, Online Mendelian Inheritance in Man's and London Dysmorphology Database. The ranking algorithms based on 1-SVM, Standard Correlation and Ward linkage method provide the best performance. AVAILABILITY: The MATLAB code of the algorithm and benchmark datasets are available by request. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

ENDEAVOUR update: a web resource for gene prioritization in multiple species.

Endeavour (http://www.esat.kuleuven.be/endeavourweb; this web site is free and open to all users and there is no login requirement) is a web resource for the prioritization of candidate genes. Using a training set of genes known to be involved in a biological process of interest, our approach consists of (i) inferring several models (based on various genomic data sources), (ii) applying each model to the candidate genes to rank those candidates against the profile of the known genes and (iii) merging the several rankings into a global ranking of the candidate genes. In the present article, we describe the latest developments of Endeavour. First, we provide a web-based user interface, besides our Java client, to make Endeavour more universally accessible. Second, we support multiple species: in addition to Homo sapiens, we now provide gene prioritization for three major model organisms: Mus musculus, Rattus norvegicus and Caenorhabditis elegans. Third, Endeavour makes use of additional data sources and is now including numerous databases: ontologies and annotations, protein-protein interactions, cis-regulatory information, gene expression data sets, sequence information and text-mining data. We tested the novel version of Endeavour on 32 recent disease gene associations from the literature. Additionally, we describe a number of recent independent studies that made use of Endeavour to prioritize candidate genes for obesity and Type II diabetes, cleft lip and cleft palate, and pulmonary fibrosis.

A novel genomic disorder: a deletion of the SACS gene leading to spastic ataxia of Charlevoix-Saguenay.

We report a Belgian patient with early-onset cerebellar ataxia, progressive spasticity, learning difficulties and moderate perceptive hearing loss. Array-Comparative Genomic Hybridisation (aCGH) detected a 1.54 Mb deletion on chromosome 13q12.12. This microdeletion occurred de novo and encompasses the SACS gene. Mutations in SACS are known to cause a recessive condition, similar to the patient's phenotype, called autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS). Sequencing of the remaining SACS allele revealed a hemizygous mutation c.10517T>C in exon 9, resulting in an amino-acid substitution (p.F3506S). This is the first patient with ARSACS that carries a de novo chromosomal deletion comprising SACS. We demonstrate the presence of homologous segmental duplications at the breakpoint-containing regions. This suggests non-allelic homologous recombination as the mechanism generating this deletion and explains the previous description of copy number variations of this region. This finding confirms the contribution of aCGH to gene identification in autosomal recessive disorders.

Text-mining assisted regulatory annotation.

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.

Autosomal-dominant microtia linked to five tandem copies of a copy-number-variable region at chromosome 4p16.

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.

A framework for elucidating regulatory networks based on prior information and expression data.

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 comparative genomic hybridization and computational genome annotation in constitutional cytogenetics: suggesting candidate genes for novel submicroscopic chromosomal imbalance syndromes.

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.

Mapping biomedical concepts onto the human genome by mining literature on chromosomal aberrations.

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/.

arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays.

BACKGROUND: The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH). One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. RESULTS: We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment) supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. CONCLUSION: ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.