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Databases with variant and phenotype information are essential for advancing research and improving the health and welfare of individuals. These resources require data to be collected, curated, and shared among relevant specialties to maximize impact. The increasing generation of data which must be shared both nationally and globally for maximal effect presents important ethical and privacy concerns. Database curators need to ensure that their work conform to acceptable ethical standards. A Working Group of the Human Variome Project had the task of updating and streamlining ethical guidelines for locus-specific/gene variant database curators. In this article, we present practical and achievable steps which should assist database curators in carrying out their responsibilities within acceptable ethical norms., (© 2019 Wiley Periodicals, Inc.)

Accurate prediction of the impact of genomic variation on phenotype is a major goal of computational biology and an important contributor to personalized medicine. Computational predictions can lead to a better understanding of the mechanisms underlying genetic diseases, including cancer, but their adoption requires thorough and unbiased assessment. Cystathionine-beta-synthase (CBS) is an enzyme that catalyzes the first step of the transsulfuration pathway, from homocysteine to cystathionine, and in which variations are associated with human hyperhomocysteinemia and homocystinuria. We have created a computational challenge under the CAGI framework to evaluate how well different methods can predict the phenotypic effect(s) of CBS single amino acid substitutions using a blinded experimental data set. CAGI participants were asked to predict yeast growth based on the identity of the mutations. The performance of the methods was evaluated using several metrics. The CBS challenge highlighted the difficulty of predicting the phenotype of an ex vivo system in a model organism when classification models were trained on human disease data. We also discuss the variations in difficulty of prediction for known benign and deleterious variants, as well as identify methodological and experimental constraints with lessons to be learned for future challenges., (© 2019 Wiley Periodicals, Inc.)

Computational tools are widely used for ranking and prioritizing variants for characterizing their disease relevance. Since numerous tools have been developed, they have to be properly assessed before being applied. Critical Assessment of Genome Interpretation (CAGI) experiments have significantly contributed toward the assessment of prediction methods for various tasks. Within and outside the CAGI, we have addressed several questions that facilitate development and assessment of variation interpretation tools. These areas include collection and distribution of benchmark datasets, their use for systematic large-scale method assessment, and the development of guidelines for reporting methods and their performance. For us, CAGI has provided a chance to experiment with new ideas, test the application areas of our methods, and network with other prediction method developers. In this article, we discuss our experiences and lessons learned from the various CAGI challenges. We describe our approaches, their performance, and impact of CAGI on our research. Finally, we discuss some of the possibilities that CAGI experiments have opened up and make some suggestions for future experiments., (© 2017 Wiley Periodicals, Inc.)

Correct phenotypic interpretation of variants of unknown significance for cancer-associated genes is a diagnostic challenge as genetic screenings gain in popularity in the next-generation sequencing era. The Critical Assessment of Genome Interpretation (CAGI) experiment aims to test and define the state of the art of genotype-phenotype interpretation. Here, we present the assessment of the CAGI p16INK4a challenge. Participants were asked to predict the effect on cellular proliferation of 10 variants for the p16INK4a tumor suppressor, a cyclin-dependent kinase inhibitor encoded by the CDKN2A gene. Twenty-two pathogenicity predictors were assessed with a variety of accuracy measures for reliability in a medical context. Different assessment measures were combined in an overall ranking to provide more robust results. The R scripts used for assessment are publicly available from a GitHub repository for future use in similar assessment exercises. Despite a limited test-set size, our findings show a variety of results, with some methods performing significantly better. Methods combining different strategies frequently outperform simpler approaches. The best predictor, Yang&Zhou lab, uses a machine learning method combining an empirical energy function measuring protein stability with an evolutionary conservation term. The p16INK4a challenge highlights how subtle structural effects can neutralize otherwise deleterious variants., (© 2017 Wiley Periodicals, Inc.)

Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype-phenotype relationships., (© 2017 Wiley Periodicals, Inc.)

Genes and proteins are known to have differences in their sensitivity to alterations. Despite numerous sequencing studies, proportions of harmful and harmless substitutions are not known for proteins and groups of proteins. To address this question, we predicted the outcome for all possible single amino acid substitutions (AASs) in nine representative protein groups by using the PON-P2 method. The effects on 996 proteins were studied and vast differences were noticed. Proteins in the cancer group harbor the largest proportion of harmful variants (42.1%), whereas the non-disease group of proteins not known to have a disease association and not involved in the housekeeping functions had the lowest number of harmful variants (4.2%). Differences in the proportions of the harmful and benign variants are wide within each group, but they still show clear differences between the groups. Frequently appearing protein domains show a wide spectrum of variant frequencies, whereas no major protein structural class-specific differences were noticed. AAS types in the original and variant residues showed distinctive patterns, which are shared by all the protein groups. The observations are relevant for understanding genetic bases of diseases, variation interpretation, and for the development of methods for that purpose., (© 2017 Wiley Periodicals, Inc.)

Most diseases, including those of genetic origin, express a continuum of severity. Clinical interventions for numerous diseases are based on the severity of the phenotype. Predicting severity due to genetic variants could facilitate diagnosis and choice of therapy. Although computational predictions have been used as evidence for classifying the disease relevance of genetic variants, special tools for predicting disease severity in large scale are missing. Here, we manually curated a dataset containing variants leading to severe and less severe phenotypes and studied the abilities of variation impact predictors to distinguish between them. We found that these tools cannot separate the two groups of variants. Then, we developed a novel machine-learning-based method, PON-PS (http://structure.bmc.lu.se/PON-PS), for the classification of amino acid substitutions associated with benign, severe, and less severe phenotypes. We tested the method using an independent test dataset and variants in four additional proteins. For distinguishing severe and nonsevere variants, PON-PS showed an accuracy of 61% in the test dataset, which is higher than for existing tolerance prediction methods. PON-PS is the first generic tool developed for this task. The tool can be used together with other evidence for improving diagnosis and prognosis and for prioritization of preventive interventions, clinical monitoring, and molecular tests., (© 2017 WILEY PERIODICALS, INC.)

Scientific and clinical communities produce ever increasing amounts of data and details about health and disease. Our ability to understand and utilize this information is limited because of imprecise language and lack of well-defined concepts. This problem involves also the principal concepts of health, disease, and pathogenicity. Here, a systematic model is presented for pathogenicity, as well as for health and disease. It has three components: extent, modulation, and severity, which jointly define the continuum of pathogenicity. The model is population based, and once implemented, it can be used for numerous purposes such as diagnosis, patient stratification, prognosis, finding phenotype-genotype correlations, or explaining adverse drug reactions. The new model has several benefits including health economy by allowing evidence-based personalized/precision medicine., (© 2016 WILEY PERIODICALS, INC.)

Next-generation sequencing methods have revolutionized the speed of generating variation information. Sequence data have a plethora of applications and will increasingly be used for disease diagnosis. Interpretation of the identified variants is usually not possible with experimental methods. This has caused a bottleneck that many computational methods aim at addressing. Fast and efficient methods for explaining the significance and mechanisms of detected variants are required for efficient precision/personalized medicine. Computational prediction methods have been developed in three areas to address the issue. There are generic tolerance (pathogenicity) predictors for filtering harmful variants. Gene/protein/disease-specific tools are available for some applications. Mechanism and effect-specific computer programs aim at explaining the consequences of variations. Here, we discuss the different types of predictors and their applications. We review available variation databases and prediction methods useful for variation interpretation. We discuss how the performance of methods is assessed and summarize existing assessment studies. A brief introduction is provided to the principles of the methods developed for variation interpretation as well as guidelines for how to choose the optimal tools and where the field is heading in the future., (© 2016 WILEY PERIODICALS, INC.)

Numerous databases containing information about DNA, RNA, and protein variations are available. Gene-specific variant databases (locus-specific variation databases, LSDBs) are typically curated and maintained for single genes or groups of genes for a certain disease(s). These databases are widely considered as the most reliable information source for a particular gene/protein/disease, but it should also be made clear they may have widely varying contents, infrastructure, and quality. Quality is very important to evaluate because these databases may affect health decision-making, research, and clinical practice. The Human Variome Project (HVP) established a Working Group for Variant Database Quality Assessment. The basic principle was to develop a simple system that nevertheless provides a good overview of the quality of a database. The HVP quality evaluation criteria that resulted are divided into four main components: data quality, technical quality, accessibility, and timeliness. This report elaborates on the developed quality criteria and how implementation of the quality scheme can be achieved. Examples are provided for the current status of the quality items in two different databases, BTKbase, an LSDB, and ClinVar, a central archive of submissions about variants and their clinical significance., (© 2016 WILEY PERIODICALS, INC.)

The Variation Ontology (VariO) is used for describing and annotating types, effects, consequences, and mechanisms of variations. To facilitate easy and consistent annotations, the online application VariOtator was developed. For variation type annotations, VariOtator is fully automated, accepting variant descriptions in Human Genome Variation Society (HGVS) format, and generating VariO terms, either with or without full lineage, that is, all parent terms. When a coding DNA variant description with a reference sequence is provided, VariOtator checks the description first with Mutalyzer and then generates the predicted RNA and protein descriptions with their respective VariO annotations. For the other sublevels, function, structure, and property, annotations cannot be automated, and VariOtator generates annotation based on provided details. For VariO terms relating to structure and property, one can use attribute terms as modifiers and evidence code terms for annotating experimental evidence. There is an online batch version, and stand-alone batch versions to be used with a Leiden Open Variation Database (LOVD) download file. A SOAP Web service allows client programs to access VariOtator programmatically. Thus, systematic variation effect and type annotations can be efficiently generated to allow easy use and integration of variations and their consequences., (© 2016 WILEY PERIODICALS, INC.)

Variations in mismatch repair (MMR) system genes are causative of Lynch syndrome and other cancers. Thousands of variants have been identified in MMR genes, but the clinical relevance is known for only a small proportion. Recently, the InSiGHT group classified 2,360 MMR variants into five classes. One-third of variants, majority of which is nonsynonymous variants, remain to be of uncertain clinical relevance. Computational tools can be used to prioritize variants for disease relevance investigations. Previously, we classified 248 MMR variants as likely pathogenic and likely benign using PON-MMR. We have developed a novel tool, PON-MMR2, which is trained on a larger and more reliable dataset. In performance comparison, PON-MMR2 outperforms both generic tolerance prediction methods as well as methods optimized for MMR variants. It achieves accuracy and MCC of 0.89 and 0.78, respectively, in cross-validation and 0.86 and 0.69, respectively, on an independent test dataset. We classified 354 class 3 variants in InSiGHT database as well as all possible amino acid substitutions in four MMR proteins. Likely harmful variants mainly appear in the protein core, whereas likely benign variants are on the surface. PON-MMR2 is a highly reliable tool to prioritize variants for functional analysis. It is freely available at http://structure.bmc.lu.se/PON-MMR2/., (© 2015 WILEY PERIODICALS, INC.)

Knowledge about features distinguishing deleterious and neutral variations is crucial for interpretation of novel variants. Bruton tyrosine kinase (BTK) contains the highest number of unique disease-causing variations among the human protein kinases, still it is just 10% of all the possible single-nucleotide substitution-caused amino acid variations (SNAVs). In the BTK kinase domain (BTK-KD) can appear altogether 1,495 SNAVs. We investigated them all with bioinformatic and protein structure analysis methods. Most disease-causing variations affect conserved and buried residues disturbing protein stability. Minority of exposed residues is conserved, but strongly tied to pathogenicity. Sixty-seven percent of variations are predicted to be harmful. In 39% of the residues, all the variants are likely harmful, whereas in 10% of sites, all the substitutions are tolerated. Results indicate the importance of the entire kinase domain, involvement in numerous interactions, and intricate functional regulation by conformational change. These results can be extended to other protein kinases and organisms., (© 2015 WILEY PERIODICALS, INC.)

For development and evaluation of methods for predicting the effects of variations, benchmark datasets are needed. Some previously developed datasets are available for this purpose, but newer and larger benchmark sets for benign variants have largely been missing. VariSNP datasets are selected from dbSNP. These subsets were filtered against disease-related variants in the ClinVar, UniProtKB/Swiss-Prot, and PhenCode databases, to identify neutral or nonpathogenic cases. All variant descriptions include mapping to reference sequences on chromosomal, genomic, coding DNA, and protein levels. The datasets will be updated with automated scripts on a regular basis and are freely available at http://structure.bmc.lu.se/VariSNP., (© 2014 WILEY PERIODICALS, INC.)

Computational tools are essential for most of our research. To use these tools, one needs to know how they work. Problems in application of computational methods to variation analysis can appear at several stages and affect, for example, the interpretation of results. Such cases are discussed along with suggestions how to avoid them. The applications include incomplete reporting of methods, especially about the use of prediction tools; method selection on unscientific grounds and without consulting independent method performance assessments; extending application area of methods outside their intended purpose; use of the same data several times for obtaining majority vote; and filtering of datasets so that variants of interest are excluded. All these issues can be avoided by discontinuing the use software tools as black boxes., (© 2014 WILEY PERIODICALS, INC.)

Many proteins contain intrinsically disordered regions, which may be crucial for function, but on the other hand be related to the pathogenicity of variants. Prediction programs have been developed to detect disordered regions from sequences and used to predict the consequences of variants, although their performance for this task has not been assessed. We tested the performance of protein disorder prediction programs in detecting changes to disorder caused by amino acid substitutions. We assessed the performance of 29 protein disorder predictors and versions with 101 amino acid substitutions, whose effects have been experimentally validated. Disorder predictors detected the true positives at most with 6% success rate and true negatives with 34% rate for variants. The corresponding rates for the wild-type forms are 7% and 90%, respectively. The analysis revealed that disorder programs cannot reliably predict the effects of substitutions; consequently, the tested methods, and possibly similar programs, cannot be recommended for variant analysis without other information indicating to the relevance of disorder. These results inspired us to develop a new method, PON-Diso (http://structure.bmc.lu.se/PON-Diso), for disorder-related amino acid substitutions. With 50% success rate for independent test set and 70.5% rate in cross-validation, it outperforms the evaluated methods., (© 2014 WILEY PERIODICALS, INC.)

Computational prediction methods are widely used for the analysis of human genome sequence variants and their effects on gene/protein function, splice site aberration, pathogenicity, and disease risk. New methods are frequently developed. We believe that guidelines are essential for those writing articles about new prediction methods, as well as for those applying these tools in their research, so that the necessary details are reported. This will enable readers to gain the full picture of technical information, performance, and interpretation of results, and to facilitate comparisons of related methods. Here, we provide instructions on how to describe new methods, report datasets, and assess the performance of predictive tools. We also discuss what details of predictor implementation are essential for authors to understand. Similarly, these guidelines for the use of predictors provide instructions on what needs to be delineated in the text, as well as how researchers can avoid unwarranted conclusions. They are applicable to most prediction methods currently utilized. By applying these guidelines, authors will help reviewers, editors, and readers to more fully comprehend prediction methods and their use., (© 2012 Wiley Periodicals, Inc.)

Several computational methods have been developed for predicting the effects of rapidly expanding variation data. Comparison of the performance of tools has been very difficult as the methods have been trained and tested with different datasets. Until now, unbiased and representative benchmark datasets have been missing. We have developed a benchmark database suite, VariBench, to overcome this problem. VariBench contains datasets of experimentally verified high-quality variation data carefully chosen from literature and relevant databases. It provides the mapping of variation position to different levels (protein, RNA and DNA sequences, protein three-dimensional structure), along with identifier mapping to relevant databases. VariBench contains the first benchmark datasets for variation effect analysis, a field which is of high importance and where many developments are currently going on. VariBench datasets can be used, for example, to test performance of prediction tools as well as to train novel machine learning-based tools. New datasets will be included and the community is encouraged to submit high-quality datasets to the service. VariBench is freely available at http://structure.bmc.lu.se/VariBench., (© 2012 Wiley Periodicals, Inc.)

The Human Variome Project (http://www.humanvariomeproject.org) is an international effort aiming to systematically collect and share information on all human genetic variation. The two main pillars of this effort are gene/disease-specific databases and a network of Human Variome Project Country Nodes. The latter are nationwide efforts to document the genomic variation reported within a specific population. The development and successful operation of the Human Variome Project Country Nodes are of utmost importance to the success of Human Variome Project's aims and goals because they not only allow the genetic burden of disease to be quantified in different countries, but also provide diagnosticians and researchers access to an up-to-date resource that will assist them in their daily clinical practice and biomedical research, respectively. Here, we report the discussions and recommendations that resulted from the inaugural meeting of the International Confederation of Countries Advisory Council, held on 12th December 2011, during the 2011 Human Variome Project Beijing Meeting. We discuss the steps necessary to maximize the impact of the Country Node effort for developing regional and country-specific clinical genetics resources and summarize a few well-coordinated genetic data collection initiatives that would serve as paradigms for similar projects., (© 2012 Wiley Periodicals, Inc.)

Genetic, transcript, and protein level variations have important functional and evolutionary consequences. We performed systematic data collection and analysis of copy-number variations, single-nucleotide polymorphisms, disease-causing variations, messenger RNA splicing variants, and protein posttranslational modifications for the genes and proteins essential for human immune system. Information about polymorphic and evolutionarily fixed genetic variations was used to group immunome genes to the most conserved and the most quickly changing ones under directed selection during the recent immunome evolution. Gene Ontology terms related to adaptive immunity are associated with gene groups subject to recent directing selection. In addition, several other characteristics of the immunome genes and proteins in these two categories have statistically significant differences. The presented findings question the usability of directed mouse genes as models for human diseases and conditions and shed light on the fine tuning of human immunity and its diverse functions., (© 2012 Wiley Periodicals, Inc.)

High-throughput sequencing data generation demands the development of methods for interpreting the effects of genomic variants. Numerous computational methods have been developed to assess the impact of variations because experimental methods are unable to cope with both the speed and volume of data generation. To harness the strength of currently available predictors, the Pathogenic-or-Not-Pipeline (PON-P) integrates five predictors to predict the probability that nonsynonymous variations affect protein function and may consequently be disease related. Random forest methodology-based PON-P shows consistently improved performance in cross-validation tests and on independent test sets, providing ternary classification and statistical reliability estimate of results. Applied to missense variants in a melanoma cancer cell line, PON-P predicts variants in 17 genes to affect protein function. Previous studies implicate nine of these genes in the pathogenesis of various forms of cancer. PON-P may thus be used as a first step in screening and prioritizing variants to determine deleterious ones for further experimentation., (© 2012 Wiley Periodicals, Inc.)

Numerous mismatch repair (MMR) gene variants have been identified in Lynch syndrome and other cancer patients, but knowledge about their pathogenicity is frequently missing. The diagnosis and treatment of patients would benefit from knowing which variants are disease related. Bioinformatic approaches are well suited to the problem and can handle large numbers of cases. Functional effects were revealed based on literature for 168 MMR missense variants. Performance of numerous prediction methods was tested with this dataset. Among the tested tools, only the results of tolerance prediction methods correlated to functional information, however, with poor performance. Therefore, a novel consensus-based predictor was developed. The novel prediction method, pathogenic-or-not mismatch repair (PON-MMR), achieved accuracy of 0.87 and Matthews correlation coefficient of 0.77 on the experimentally verified variants. When applied to 616 MMR cases with unknown effects, 81 missense variants were predicted to be pathogenic and 167 neutral. With PON-MMR, the number of MMR missense variants with unknown effect was reduced by classifying a large number of cases as likely pathogenic or benign. The results can be used, for example, to prioritize cases for experimental studies and assist in the classification of cases., (© 2012 Wiley Periodicals, Inc.)

Gene variant databases or Locus-Specific DataBases (LSDBs) are used to collect and display information on sequence variants on a gene-by-gene basis. Their most frequent use is in relation to DNA-based diagnostics, giving clinicians and scientists easy access to an up-to-date overview of all gene variants identified worldwide and whether they influence the function of the gene ("pathogenic or not"). While literature on gene variant databases is extensive, little has been published on the process of database curation itself. Based on our extensive experience as LSDB curators and our contributions to database curation courses, we discuss the subject of database curation. We describe the tasks involved, the steps to take, and the issues that might occur. Our overview is a first step toward establishing overall guidelines for database curation and ultimately covers one aspect of establishing quality-assured gene variant databases., (© 2011 Wiley Periodicals, Inc.)

Information about genetic variation has been collected for some 20 years into registries, known as locus specific databases (LSDBs), which nowadays often contain information in addition to the actual genetic variation. Several issues have to be taken into account when considering establishing and maintaining LSDBs and these have been discussed previously in a number of articles describing guidelines and recommendations. This information is widely scattered and, for a newcomer, it would be difficult to obtain the latest information and guidance. Here, a sequence of steps essential for establishing an LSDB is discussed together with guidelines for each step. Curators need to collect information from various sources, code it in systematic way, and distribute to the research and clinical communities. In doing this, ethical issues have to be taken into account. To facilitate integration of information to, for example, analyze genotype-phenotype correlations, systematic data representation using established nomenclatures, data models, and ontologies is essential. LSDB curation and maintenance comprises a number of tasks that can be managed by following logical steps. These resources are becoming ever more important and new curators are essential to ensure that we will have expertly curated databases for all disease-related genes in the near future., (© 2011 Wiley Periodicals, Inc.)

Single nucleotide polymorphisms (SNPs) are the most common form of genetic variation in humans. The number of SNPs identified in the human genome is growing rapidly, but attaining experimental knowledge about the possible disease association of variants is laborious and time-consuming. Several computational methods have been developed for the classification of SNPs according to their predicted pathogenicity. In this study, we have evaluated the performance of nine widely used pathogenicity prediction methods available on the Internet. The evaluated methods were MutPred, nsSNPAnalyzer, Panther, PhD-SNP, PolyPhen, PolyPhen2, SIFT, SNAP, and SNPs&GO. The methods were tested with a set of over 40,000 pathogenic and neutral variants. We also assessed whether the type of original or substituting amino acid residue, the structural class of the protein, or the structural environment of the amino acid substitution, had an effect on the prediction performance. The performances of the programs ranged from poor (MCC 0.19) to reasonably good (MCC 0.65), and the results from the programs correlated poorly. The overall best performing methods in this study were SNPs&GO and MutPred, with accuracies reaching 0.82 and 0.81, respectively., (© 2011 Wiley-Liss, Inc.)

Stability is a fundamental property affecting function, activity, and regulation of biomolecules. Stability changes are often found for mutated proteins involved in diseases. Stability predictors computationally predict protein-stability changes caused by mutations. We performed a systematic analysis of 11 online stability predictors' performances. These predictors are CUPSAT, Dmutant, FoldX, I-Mutant2.0, two versions of I-Mutant3.0 (sequence and structure versions), MultiMutate, MUpro, SCide, Scpred, and SRide. As input, 1,784 single mutations found in 80 proteins were used, and these mutations did not include those used for training. The programs' performances were also assessed according to where the mutations were found in the proteins, that is, in secondary structures and on the surface or in the core of a protein, and according to protein structure type. The extents to which the mutations altered the occupied volumes at the residue sites and the charge interactions were also characterized. The predictions of all programs were in line with the experimental data. I-Mutant3.0 (utilizing structural information), Dmutant, and FoldX were the most reliable predictors. The stability-center predictors performed with similar accuracy. However, at best, the predictions were only moderately accurate ( approximately 60%) and significantly better tools would be needed for routine analysis of mutation effects.

CD40 is a costimulatory protein expressed on the surface of many different cells. It delivers signals regulating diverse cellular responses, including proliferation, differentiation, growth suppression, and cell death. In this study, we report a novel CD40 mutant (c.234C>A or p.H78Q) that is expressed in the U266 cell line and in freshly isolated tumor cells. Three-dimensional structural model and Scatchard analysis revealed that the mutated residue located in a region is important for binding to CD40L (CD154). Functional analysis indicated that the mutated CD40 was translocated to the CD40 signalosome and involved in CD40 signal transduction. In conclusion, the mutation in CD40 can lead to an alteration of function, including the change of antigen epitope and the binding affinity with CD40L.

We report the structure of a novel tetrameric form of the lactose repressor (LacI) protein from Escherichia coli refined to 2.1 A resolution. The tetramer is bound to 1.6-hexanediol present in the crystallization solution and the final R(free) for the structure is 0.201. The structure confirms previously reported structures on the monomer level. However, the tetramer is much more densely packed. This adds a new level of complexity to the interpretation of mutational effects and challenges details in the current model for LacI function. Several amino acids, previously associated with changes in function but unexplained at the structural level, appear in a new structural context in this tetramer which provides new implications for their function.

Many gene defects are relatively easy to identify experimentally, but obtaining information about the effects of sequence variations and elucidation of the detailed molecular mechanisms of genetic diseases will be among the next major efforts in mutation research. Amino acid substitutions may have diverse effects on protein structure and function; thus, a detailed analysis of the mutations is essential. Experimental study of the molecular effects of mutations is laborious, whereas useful and reliable information about the effects of amino acid substitutions can readily be obtained by theoretical methods. Experimentally defined structures and molecular modeling can be used as a basis for interpretation of the mutations. The effects of missense mutations can be analyzed even when the 3D structure of the protein has not been determined, although structure-based analyses are more reliable. Structural analyses include studies of the contacts between residues, their implication for the stability of the protein, and the effects of the introduced residues. Investigations of steric and stereochemical consequences of substitutions provide insights on the molecular fit of the introduced residue. Mutations that change the electrostatic surface potential of a protein have wide-ranging effects. Analyses of the effects of mutations on interactions with ligands and partners have been performed for elucidation of functional mutations. We have employed numerous methods for predicting the effects of amino acid substitutions. We discuss the applicability of these methods in the analysis of genes, proteins, and diseases to reveal protein structure-function relationships, which is essential to gain insights into disease genotype-phenotype correlations., (Copyright 2009 Wiley-Liss, Inc.)

Several Locus-Specific DataBases (LSDBs) have recently been approached by larger, more general data repositories (including NCBI and UCSC) with the request to share the DNA variant data they have collected. Within the Human Genome Variation Society (HGVS) a document was generated summarizing the issues related to these requests. The document has been circulated in the HGVS/LSDB community and was discussed extensively. Here we summarize these discussions and present the concluded recommendations for LSDB data sharing with central repositories., ((c) 2009 Wiley-Liss, Inc.)

There are currently less than 40 locus-specific databases (LSDBs) and one large general database that curate data on somatic mutations in human cancer genes. These databases have different scope and use different annotation standards and database systems, resulting in duplicated efforts in data curation, and making it difficult for users to find clear and consistent information. As data related to somatic mutations are generated at an increasing pace it is urgent to create a framework for improving the collecting of this information and making it more accessible to clinicians, scientists, and epidemiologists to facilitate research on biomarkers. Here we propose a data flow for improving the connectivity between existing databases and we provide practical guidelines for data reporting, database contents, and annotation standards. These proposals are based on common standards recommended by the Human Genome Variation Society (HGVS) with additions related to specific requirements of somatic mutations in cancer. Indeed, somatic mutations may be used in molecular pathology and clinical studies to characterize tumor types, help treatment choice, predict response to treatment and patient outcome, or in epidemiological studies as markers for tumor etiology or exposure assessment. Thus, specific annotations are required to cover these diverse research topics. This initiative is meant to promote collaboration and discussion on these issues and the development of adequate resources that would avoid the loss of extremely valuable information generated by years of basic and clinical research., (2008 Wiley-Liss, Inc.)

The authors have made a genome-wide analysis of mutations in Src homology 2 (SH2) domains associated with human disease. Disease-causing mutations have been detected in the SH2 domains of cytoplasmic signaling proteins Bruton tyrosine kinase (BTK), SH2D1A, Ras GTPase activating protein (RasGAP), ZAP-70, SHP-2, STAT1, STAT5B, and the p85alpha subunit of the PIP3. Mutations in the BTK, SH2D1A, ZAP70, STAT1, and STAT5B genes have been shown to cause diverse immunodeficiencies, whereas the mutations in RASA1 and PIK3R1 genes lead to basal carcinoma and diabetes, respectively. PTPN11 mutations cause Noonan sydrome and different types of cancer, depending mainly on whether the mutation is inherited or sporadic. We collected and analyzed all known pathogenic mutations affecting human SH2 domains by bioinformatics methods. Among the investigated protein properties are sequence conservation and covariance, structural stability, side chain rotamers, packing effects, surface electrostatics, hydrogen bond formation, accessible surface area, salt bridges, and residue contacts. The majority of the mutations affect positions essential for phosphotyrosine ligand binding and specificity. The structural basis of the SH2 domain diseases was elucidated based on the bioinformatic analysis., ((c) 2008 Wiley-Liss, Inc.)

Expert curation and complete collection of mutations in genes that affect human health is essential for proper genetic healthcare and research. Expert curation is given by the curators of gene-specific mutation databases or locus-specific databases (LSDBs). While there are over 700 such databases, they vary in their content, completeness, time available for curation, and the expertise of the curator. Curation and LSDBs have been discussed, written about, and protocols have been provided for over 10 years, but there have been no formal recommendations for the ideal form of these entities. This work initiates a discussion on this topic to assist future efforts in human genetics. Further discussion is welcome., ((c) 2007 Wiley-Liss, Inc.)

Researchers and clinicians ideally need instant access to all the variation in their gene/locus of interest to efficiently conduct their research and genetic healthcare to the highest standards. Currently much key data resides in the laboratory books or patient records around the world, as there are many impediments to submitting this data. It would be ideal therefore if a semiautomated pathway was available, with a minimum of effort, to make the deidentified data publicly available for others to use. The Human Variome Project (HVP) meeting listed 96 recommendations to work toward this situation. This article is planned to initiate a strategy to enhance the collection of phenotype and genotype data from the clinician/diagnostic laboratory nexus. Thus, the aim is to develop universally applicable forms that people can use when investigating patients for each inherited disease, to assist in satisfying many of the recommendations of the HVP Meeting [Cotton et al., 2007]. We call for comment and collaboration in this article., (Copyright 2007 Wiley-Liss, Inc.)

PhenCode (Phenotypes for ENCODE; http://www.bx.psu.edu/phencode) is a collaborative, exploratory project to help understand phenotypes of human mutations in the context of sequence and functional data from genome projects. Currently, it connects human phenotype and clinical data in various locus-specific databases (LSDBs) with data on genome sequences, evolutionary history, and function from the ENCODE project and other resources in the UCSC Genome Browser. Initially, we focused on a few selected LSDBs covering genes encoding alpha- and beta-globins (HBA, HBB), phenylalanine hydroxylase (PAH), blood group antigens (various genes), androgen receptor (AR), cystic fibrosis transmembrane conductance regulator (CFTR), and Bruton's tyrosine kinase (BTK), but we plan to include additional loci of clinical importance, ultimately genomewide. We have also imported variant data and associated OMIM links from Swiss-Prot. Users can find interesting mutations in the UCSC Genome Browser (in a new Locus Variants track) and follow links back to the LSDBs for more detailed information. Alternatively, they can start with queries on mutations or phenotypes at an LSDB and then display the results at the Genome Browser to view complementary information such as functional data (e.g., chromatin modifications and protein binding from the ENCODE consortium), evolutionary constraint, regulatory potential, and/or any other tracks they choose. We present several examples illustrating the power of these connections for exploring phenotypes associated with functional elements, and for identifying genomic data that could help to explain clinical phenotypes.

Cyclic and congenital neutropenia are caused by mutations in the human neutrophil elastase (HNE) gene (ELA2), leading to an immunodeficiency characterized by decreased or oscillating levels of neutrophils in the blood. The HNE mutations presumably cause loss of enzyme activity, consequently leading to compromised immune system function. To understand the structural basis for the disease, we implemented methods from bioinformatics to analyze all the known HNE missense mutations at both the sequence and structural level. Our results demonstrate that the 32 different mutations have diverse effects on HNE structure and function, affecting structural disorder and aggregation tendencies, stability maintaining contacts, and electrostatic properties. A large proportion of the mutations are located at conserved amino acids, which are usually essential in determining protein structure and function. The majority of the disease-causing HNE missense mutations lead to major structural changes and loss of stability in the protein. A few mutations also affect functional residues, leading into decreased catalytic activity or altered ligand binding. Our analysis reveals the putative effects of all known missense mutations in HNE, thus allowing the structural basis of cyclic and congenital neutropenia to be elucidated. We have employed and analyzed a set of some 30 different methods for predicting the effects of amino acid substitutions. We present results and experience from the analysis of the applicability of these methods in the analysis of numerous genes, proteins, and diseases to reveal protein structure-function relationships and disease genotype-phenotype correlations., ((c) 2006 Wiley-Liss, Inc.)

X-linked agammaglobulinemia (XLA) is a hereditary immunodeficiency caused by mutations in the gene encoding Bruton tyrosine kinase (BTK). XLA patients have a decreased number of mature B cells and a lack of all immunoglobulin isotypes, resulting in susceptibility to severe bacterial infections. XLA-causing mutations are collected in a mutation database (BTKbase), which is available at http://bioinf.uta.fi/BTKbase. For each patient the following information is given (when available): the identification of the entry, a plain English description of the mutation followed by a reference, formal characterization of the mutation, and the various parameters from the patient. BTKbase is implemented with the MUTbase program suite, which provides an easy, interactive, and quality controlled submission of information to mutation databases. BTKbase version 8 lists mutation entries of 1,111 patients from 973 unrelated families showing 602 unique molecular events. The localization of the mutations on the gene and protein for BTK can be analyzed by clicking sequences on the web pages. The distribution of the mutations in the five structural domains is approximately proportional to the length of the domains, except for the Tec homology (TH) domain. The most frequently affected sites are CpG dinucleotides. The majority of the missense mutations are structural-disturbing Bruton tyrosine kinase (Btk) folding or decreasing stability. Many of the mutations affect functionally significant, conserved residues. The structural consequences of the mutations in all the domains have been studied based on crystallographic and nuclear magnetic resonance (NMR) structures as well as computer-aided molecular modeling., ((c) 2006 Wiley-Liss, Inc.)

Primary immunodeficiencies (IDs) are a heterogenic group of inherited disorders of the immune system. Immunodeficiency patients have increased susceptibility to recurrent and persistent, even life-threatening infections. Mutations in a large number of genes can cause defects in different cellular functions and lead to impaired immune response. To date, approximately 150 IDs and more than 100 affected genes have been identified. ID-related genes are distributed throughout the genome, and diseases can be inherited in an X-linked, an autosomal recessive, or an autosomal dominant way. We have collected ID mutation data into locus-specific patient-related mutation databases, IDbases (http://bioinf.uta.fi/IDbases). Mutations are described at DNA, mRNA, and protein levels with links to reference sequences and reference articles. The mutation data has been collated into entries along with some clinical information. IDbases offer an easy way, e.g., to find recently identified mutations, to reveal genotype-phenotype correlations, and to discover a specific mutation or to examine the most common mutations in a single immunodeficiency related gene. At the moment we have databases for 107 ID genes with 4,140 public patient entries. An exhaustive statistical analysis of mutation data from the IDbases was made. Missense and nonsense mutations are the most common mutation types, and the most common single substitution is a nonsense mutation from tryptophan to a stop codon. Arginine is the most mutated as well as the most abundant mutant amino acid., ((c) 2006 Wiley-Liss, Inc.)

A large number of disease-causing mutations have been identified from several protein kinases. KinMutBase is a comprehensive knowledge base for human disease-related mutations in protein kinase domains (http://bioinf.uta.fi/KinMutBase/). The latest version contains 582 different mutations for 1,790 cases in 1,322 families. KinMutBase entries are described on the DNA, mRNA, and protein level. Numbers for affected patients and families are also provided. KinMutBase has extensive amount of links and cross-references to literature, other databases, and information sources. There are numerous interactive pages about sequences, structures, mutation statistics, and diseases. Detailed statistical study was done on frequencies of different types of mutations both on the DNA and protein level in serine/threonine kinase (PSK) and tyrosine kinase (PTK). Three-dimensional structures indicate clustering of disease-related mutations mainly to conserved subdomains, and substrate and coligand binding amino acids, although mutations appear throughout the sequences. CpG containing codons, especially for arginine, constitute the majority of mutational hotspots. There are certain clear differences in mutation patterns and types between PSKs and PTKs.

A defective form of the AIRE protein causes autoimmune destruction of target organs by disturbing the immunological tolerance of patients with a rare monogenic disease, autoimmune polyendocrinopathy (APE)-candidiasis (C)-ectodermal dystrophy (ED), APECED. Recently, experiments on knockout mice revealed that AIRE controls autoimmunity by regulating the transcription of peripheral tissue-restricted antigens in thymic medullary epithelial cells. Thus, AIRE provides a unique model for molecular studies of organ-specific autoimmunity. In order to analyze the molecular and cellular consequences of 16 disease-causing mutations in vitro, we studied the subcellular localization, transactivation capacity, homomultimerization, and complex formation of several mutant AIRE polypeptides. Most of the mutations altered the nucleus-cytoplasm distribution of AIRE and disturbed its association with nuclear dots and cytoplasmic filaments. While the PHD zinc fingers were necessary for the transactivation capacity of AIRE, other regions of AIRE also modulated this function. Consequently, most of the mutations decreased transactivation. The HSR domain was responsible for the homomultimerization activity of AIRE; all the missense mutations of the HSR and the SAND domains decreased this activity, but those in other domains did not. The AIRE protein was present in soluble high-molecular-weight complexes. Mutations in the HSR domain and deletion of PHD zinc fingers disturbed the formation of these complexes. In conclusion, we propose an in vitro model in which AIRE transactivates transcription through heteromeric molecular interactions that are regulated by homomultimerization and conditional localization of AIRE in the nucleus or in the cytoplasm., (Copyright 2004 Wiley-Liss, Inc.)

Protein structure-function relationships can be studied by using linker insertion mutagenesis, which efficiently identifies essential regions in target proteins. Bacteriophage Mu in vitro DNA transposition was used to generate an extensive library of pentapeptide insertion mutants within the alpha-complementing domain 1 of Escherichia coli beta-galactosidase, yielding mutants at 100% efficiency. Each mutant contained an accurate 15-bp insertion that translated to five additional amino acids within the protein, and the insertions were distributed essentially randomly along the target sequence. Individual mutants (alpha-donors) were analyzed for their ability to restore (by alpha-complementation) beta-galactosidase activity of the M15 deletion mutant (alpha-acceptor), and the data were correlated to the structure of the beta-galactosidase tetramer. Most of the insertions were well tolerated, including many of those disrupting secondary structural elements even within the protein's interior. Nevertheless, certain sites were sensitive to mutations, indicating both known and previously unknown regions of functional importance. Inhibitory insertions within the N-terminus and loop regions most likely influenced protein tetramerization via direct local effects on protein-protein interactions. Within the domain 1 core, the insertions probably caused either lateral shifting of the polypeptide chain toward the protein's exterior or produced more pronounced structural distortions. Six percent of the mutant proteins exhibited temperature sensitivity, in general suggesting the method's usefulness for generation of conditional phenotypes. The method should be applicable to any cloned protein-encoding gene., (Copyright 2004 Wiley-Liss, Inc.)

Mutations in the gene encoding Bruton tyrosine kinase (BTK) result in X-linked agammaglobulinemia (XLA), an immunodeficiency of antibody defect. By using base excision sequence scanning method (BESS) followed by direct sequencing we found in seven unrelated families with a classical XLA phenotype various mutations including six novel mutations (g.64512_64513insC, c.108_109insG, c.1700_1701insACTACAG, g.51375_51376GC>TG, g.63991_63992insGGTAGAAAAAA, c.1956_1957insCA) and a previously known silent polymorphism (c.2031C>T). Except for two mutations, the alterations affect the kinase domain. There was exceptionally high proportion of insertions in the cohort. Frameshift insertion was found altogether in five patients, three of which are on introns, one in upstream region, and one in exon 18 leading to frameshift mutation and truncation of the protein. In the intron 4 there is a substitution of two bases. Carrier detection was performed in four families. In one case the mutation was found to be de novo., (Copyright 2002 Wiley-Liss, Inc.)

During the last 10 years, an increasing number of genes have been identified whose abnormalities account for primary immunodeficiencies, with defects in development and/or function of the immune system. Among them is the JAK3-gene, encoding for a tyrosine kinase that is functionally coupled to cytokine receptors which share the common gamma chain. Defects of this gene cause an autosomal recessive form of severe combined immunodeficiency with almost absent T-cells and functionally defective B-cells (T(-)B(+) SCID). Herewith, we present molecular information on the first 27 unique mutations identified in the JAK3 gene, including clinical data on all of the 23 affected patients reported so far. A variety of mutations scattered throughout all seven functional domains of the protein, and with different functional effects, have been identified. Availability of a molecular screening test, based on amplification of genomic DNA, facilitates the diagnostic approach, and has permitted recognition that JAK3 deficiency may also be associated with atypical clinical and immunological features. Development of a structural model of the JAK3 kinase domain has allowed characterization of the functional effects of the various mutations. Most importantly, molecular analysis at the JAK3 locus results in improved genetic counseling, allows early prenatal diagnosis, and prompts appropriate treatment (currently based on hematopoietic stem cell transplantation) in affected families., (Copyright 2001 Wiley-Liss, Inc.)

X-linked agammaglobulinemia (XLA) is an immunodeficiency caused by mutations in the gene coding for Bruton agammaglobulinemia tyrosine kinase (BTK). A database (BTKbase) of BTK mutations lists 544 mutation entries from 471 unrelated families showing 341 unique molecular events. In addition to mutations, a number of variants or polymorphisms have been found. Mutations in all the five domains of BTK cause the disease, the single most common event being missense mutations. Most mutations lead to truncation of the enzyme. The mutations appear almost uniformly throughout the molecule. About one-third of point mutations affect CpG sites, which usually code for arginine residues. The putative structural implications of all the missense mutations are provided in the database. BTKbase is available at http://www.uta.fi/imt/bioinfo.