Gain and loss of phosphorylation sites in human cancer

MOTIVATION: Coding-region mutations in human genes are responsible for a diverse spectrum of diseases and phenotypes. Among lesions that have been studied extensively, there are insights into several of the biochemical functions disrupted by disease-causing mutations. Currently, there are more than 60 000 coding-region mutations associated with inherited disease catalogued in the Human Gene Mutation Database (HGMD, August 2007) and more than 70 000 polymorphic amino acid substitutions recorded in dbSNP (dbSNP, build 127). Understanding the mechanism and contribution these variants make to a clinical phenotype is a formidable problem. RESULTS: In this study, we investigate the role of phosphorylation in somatic cancer mutations and inherited diseases. Somatic cancer mutation datasets were shown to have a significant enrichment for mutations that cause gain or loss of phosphorylation when compared to our control datasets (putatively neutral nsSNPs and random amino acid substitutions). Of the somatic cancer mutations, those in kinase genes represent the most enriched set of mutations that disrupt phosphorylation sites, suggesting phosphorylation target site mutation is an active cause of phosphorylation deregulation. Overall, this evidence suggests both gain and loss of a phosphorylation site in a target protein may be important features for predicting cancer-causing mutations and may represent a molecular cause of disease for a number of inherited and somatic mutations.     

Keio Mutation Database (KMDB) for human disease gene mutations

A database of mutations in human disease-causing genes has been constructed and named as Keio Mutation Database (KMDB). This KMDB utilizes a database software called MutationView which was designed to compile various mutation data and to provide graphical presentation of data analysis. Currently, the KMDB accommodates mutation data of 38 different genes for 35 different diseases which are involved in eye, heart, ear and brain. These KMDBs are accessible through http://mutview.dmb.med.keio.ac.jp with advanced internet browsers.     

The Histone Database: a comprehensive resource for histones and histone fold-containing proteins

The Histone Database is a curated and searchable collection of full-length sequences and structures of histones and nonhistone proteins containing histone-like folds, compiled from major public databases. Several new histone fold-containing proteins have been identified, including the huntingtin-interacting protein HYPM. Additionally, based on the recent crystal structure of the Son of Sevenless protein, an interpretation of the sequence analysis of the histone fold domain is presented. The database contains an updated collection of multiple sequence alignments for the four core histones (H2A, H2B, H3, and H4) and the linker histones (H1/H5) from a total of 975 organisms. The database also contains information on the human histone gene complement and provides links to three-dimensional structures of histone and histone fold-containing proteins. The Histone Database is a comprehensive bioinformatics resource for the study of structure and function of histones and histone fold-containing proteins. The database is available at http://research.nhgri.nih.gov/histones/.     

An Excess of G over C Nucleotides in Mutagenesis of Human Genetic Diseases

Strand asymmetries in DNA evolution, including indel and single nucleotide substitutions, were reported in prokaryotes. Recently, an excess of G>A over C>T substitutions in hemophilia B patients was recognized in our molecular diagnostic practices. Further analysis demonstrated biased point mutations between sense and antisense strands when unique changes in factor IX were counted. Similar mutation spectra of factor IX and the HGMD prompted us to speculate that the excess of G>A over C>T may be present in genes other than factor IX. Data from nine genes (each has ≥100 missense mutations) retrieved from HGMD, international factor IX database, and Dr. Sommer’s lab database in the City of Hope National Medical Center, Duarte, CA, USA were analyzed for their point mutation spectra. Similar to factor IX, all genes selected in this study have biased G>A over C>T unique mutations when nonsense mutations were excluded. The biased missense point mutations were recently convincingly documented by the statistic data of categorized missense mutation in HGMD. The consistence of the genetic observation and the genomic data from HGMD strongly indicate that biased point mutations, possibly a phenotypic selection, are more widespread than previously thought. The biased mutations have immediate clinical impact in molecular diagnostics.     

Localization of retina/pineal-expressed sequences: identification of novel candidate genes for inherited retinal disorders.

More than 100 genes causing inherited retinal diseases have been mapped to chromosomal locations, but less than half of these genes have been cloned. Mutations in many retina/pineal-specific genes are known to cause inherited retinal diseases. Examples include mutations in arrestin, rhodopsin kinase, and the cone-rod homeobox gene, CRX. To identify additional candidate genes for inherited retinal disorders, novel retina/pineal-expressed EST clusters were identified from the TIGR Human Gene Index database and mapped to specific chromosomal sites. After known human gene sequences were excluded, and repeat sequences were masked, 26 novel retina and pineal gland cDNA clusters were identified. The retinal expression of each novel EST cluster was confirmed by PCR assay of a retinal cDNA library, and each cluster was localized in the genome using the GeneBridge 4.0 radiation hybrid panel. In silico expression data from the TIGR database suggest that these EST clusters are retina/pineal-specific or predominantly expressed in these tissues. This combination of database analysis and laboratory investigation has localized several EST clusters that are potential candidates for genes causing inherited retinopathy.     

Cystic fibrosis testing in a referral laboratory: results and lessons from a six-year period

Background

The recent introduction of high throughput sequencing technologies into clinical genetics has made it practical to simultaneously sequence many genes. In contrast, previous technologies limited sequencing based tests to only a handful of genes. While the ability to more accurately diagnose inherited diseases is a great benefit it introduces specific challenges. Interpretation of missense mutations continues to be challenging and the number of variants of uncertain significance continues to grow.

Results

We leveraged the data available at ARUP Laboratories, a major reference laboratory, for the CFTR gene to explore specific challenges related to variant interpretation, including a focus on understanding ethnic-specific variants and an evaluation of existing databases for clinical interpretation of variants. In this study we analyzed 555 patients representing eight different ethnic groups. We observed 184 different variants, most of which were ethnic group specific. Eighty-five percent of these variants were present in the Cystic Fibrosis Mutation Database, whereas the Human Mutation Database and dbSNP/1000 Genomes had far fewer of the observed variants. Finally, 21 of the variants were novel and we report these variants and their clinical classifications.

Conclusions

Based on our analyses of data from six years of CFTR testing at ARUP Laboratories a more comprehensive, clinical grade database is needed for the accurate interpretation of observed variants. Furthermore, there is a particular need for more and better information regarding variants from individuals of non-Caucasian ethnicity.     

Actionable,Pathogenic Incidental Findings in 1,000 Participants’ Exomes

The incorporation of genomics into medicine is stimulating interest on the return of incidental findings (IFs) from exome and genome sequencing. However, no large-scale study has yet estimated the number of expected actionable findings per individual; therefore, we classified actionable pathogenic single-nucleotide variants in 500 European- and 500 African-descent participants randomly selected from the National Heart, Lung, and Blood Institute Exome Sequencing Project. The 1,000 individuals were screened for variants in 114 genes selected by an expert panel for their association with medically actionable genetic conditions possibly undiagnosed in adults. Among the 1,000 participants, 585 instances of 239 unique variants were identified as disease causing in the Human Gene Mutation Database (HGMD). The primary literature supporting the variants’ pathogenicity was reviewed. Of the identified IFs, only 16 unique autosomal-dominant variants in 17 individuals were assessed to be pathogenic or likely pathogenic, and one participant had two pathogenic variants for an autosomal-recessive disease. Furthermore, one pathogenic and four likely pathogenic variants not listed as disease causing in HGMD were identified. These data can provide an estimate of the frequency (∼3.4% for European descent and ∼1.2% for African descent) of the high-penetrance actionable pathogenic or likely pathogenic variants in adults. The 23 participants with pathogenic or likely pathogenic variants were disproportionately of European (17) versus African (6) descent. The process of classifying these variants underscores the need for a more comprehensive and diverse centralized resource to provide curated information on pathogenicity for clinical use to minimize health disparities in genomic medicine.     

Genome-wide analysis of human disease alleles reveals that their locations are correlated in paralogous proteins

The millions of mutations and polymorphisms that occur in human populations are potential predictors of disease, of our reactions to drugs, of predisposition to microbial infections, and of age-related conditions such as impaired brain and cardiovascular functions. However, predicting the phenotypic consequences and eventual clinical significance of a sequence variant is not an easy task. Computational approaches have found perturbation of conserved amino acids to be a useful criterion for identifying variants likely to have phenotypic consequences. To our knowledge, however, no study to date has explored the potential of variants that occur at homologous positions within paralogous human proteins as a means of identifying polymorphisms with likely phenotypic consequences. In order to investigate the potential of this approach, we have assembled a unique collection of known disease-causing variants from OMIM and the Human Genome Mutation Database (HGMD) and used them to identify and characterize pairs of sequence variants that occur at homologous positions within paralogous human proteins. Our analyses demonstrate that the locations of variants are correlated in paralogous proteins. Moreover, if one member of a variant-pair is disease-causing, its partner is likely to be disease-causing as well. Thus, information about variant-pairs can be used to identify potentially disease-causing variants, extend existing procedures for polymorphism prioritization, and provide a suite of candidates for further diagnostic and therapeutic purposes.     

Deleterious- and Disease-Allele Prevalence in Healthy Individuals: Insights from Current Predictions,Mutation Databases,and Population-Scale Resequencing

We have assessed the numbers of potentially deleterious variants in the genomes of apparently healthy humans by using (1) low-coverage whole-genome sequence data from 179 individuals in the 1000 Genomes Pilot Project and (2) current predictions and databases of deleterious variants. Each individual carried 281–515 missense substitutions, 40–85 of which were homozygous, predicted to be highly damaging. They also carried 40–110 variants classified by the Human Gene Mutation Database (HGMD) as disease-causing mutations (DMs), 3–24 variants in the homozygous state, and many polymorphisms putatively associated with disease. Whereas many of these DMs are likely to represent disease-allele-annotation errors, between 0 and 8 DMs (0–1 homozygous) per individual are predicted to be highly damaging, and some of them provide information of medical relevance. These analyses emphasize the need for improved annotation of disease alleles both in mutation databases and in the primary literature; some HGMD mutation data have been recategorized on the basis of the present findings, an iterative process that is both necessary and ongoing. Our estimates of deleterious-allele numbers are likely to be subject to both overcounting and undercounting. However, our current best mean estimates of ∼400 damaging variants and ∼2 bona fide disease mutations per individual are likely to increase rather than decrease as sequencing studies ascertain rare variants more effectively and as additional disease alleles are discovered.     

The Human PAX6 Mutation Database.

The Human PAX6 Mutation Database contains details of 94 mutations of the PAX6 gene. A Microsoft Access program is used by the Curator to store, update and search the database entries. Mutations can be entered directly by the Curator, or imported from submissions made via the World Wide Web. The PAX6 Mutation Database web page at URL http://www.hgu.mrc.ac.uk/Softdata/PAX6/ provides information about PAX6, as well as a fill-in form through which new mutations can be submitted to the Curator. A search facility allows remote users to query the database. A plain text format file of the data can be downloaded via the World Wide Web. The Curation program contains prior knowledge of the genetic code and of the PAX6 gene including cDNA sequence, location of intron/exon boundaries, and protein domains, so that the minimum of information need be provided by the submitter or Curator.     

IARC Database of p53 gene mutations in human tumors and cell lines: updated compilation, revised formats and new visualisation tools.

Since 1989, about 570 different p53 mutations have been identified in more than 8000 human cancers. A database of these mutations was initiated by M. Hollstein and C. C. Harris in 1990. This database originally consisted of a list of somatic point mutations in the p 53 gene of human tumors and cell lines, compiled from the published literature and made available in a standard electronic form. The database is maintained at the International Agency for Research on Cancer (IARC) and updated versions are released twice a year (January and July). The current version (July 1997) contains records on 6800 published mutations and will surpass the 8000 mark in the January 1998 release. The database now contains information on somatic and germline mutations in a new format to facilitate data retrieval. In addition, new tools are constructed to improve data analysis, such as a Mutation Viewer Java applet developed at the European Bioinformatics Institute (EBI) to visualise the location and impact of mutations on p53 protein structure. The database is available in different electronic formats at IARC (http://www.iarc. fr/p53/homepage.htm ) or from the EBI server (http://www.ebi.ac.uk ). The IARC p53 website also provides reports on database analysis and links with other p53 sites as well as with related databases. In this report, we describe the criteria for inclusion of data, the revised format and the new visualisation tools. We also briefly discuss the relevance of p 53 mutations to clinical and biological questions.     

Automated validation of genetic variants from large databases: ensuring that variant references refer to the same genomic locations

SUMMARY: Accurate annotations of genomic variants are necessary to achieve full-genome clinical interpretations that are scientifically sound and medically relevant. Many disease associations, especially those reported before the completion of the HGP, are limited in applicability because of potential inconsistencies with our current standards for genomic coordinates, nomenclature and gene structure. In an effort to validate and link variants from the medical genetics literature to an unambiguous reference for each variant, we developed a software pipeline and reviewed 68 641 single amino acid mutations from Online Mendelian Inheritance in Man (OMIM), Human Gene Mutation Database (HGMD) and dbSNP. The frequency of unresolved mutation annotations varied widely among the databases, ranging from 4 to 23%. A taxonomy of primary causes for unresolved mutations was produced. AVAILABILITY: This program is freely available from the web site (http://safegene.hms.harvard.edu/aa2nt/).     

The GENETPIG database: a tool for comparative mapping in pig (Sus scrofa)

The GENETPIG database has been established for storing and disseminating the results of the European project: 'GENETPIG: identification of genes controlling economic traits in pig'. The partners of this project have mapped about 630 porcine and human ESTs onto the pig genome. The database collects the mapping results and links them to other sources of mapping data; this includes pig maps as well as available comparative mapping information. Functional annotation of the mapped ESTs is also given when a significant similarity to cognate genes was established. The database is accessible for consultation via the Internet at http://www.infobiogen.fr/services/Genetpig/.     

Cataloging coding sequence variations in human genome databases

Background

With the recent growth of information on sequence variations in the human genome, predictions regarding the functional effects and relevance to disease phenotypes of coding sequence variations are becoming increasingly important. The aims of this study were to catalog protein-coding sequence variations (CVs) occurring in genetic variation databases and to use bioinformatic programs to analyze CVs. In addition, we aim to provide insight into the functionality of the reference databases.

Methodology and Findings

To catalog CVs on a genome-wide scale with regard to protein function and disease, we investigated three representative databases; the Human Gene Mutation Database (HGMD), the Single Nucleotide Polymorphisms database (dbSNP), and the Haplotype Map (HapMap). Using these three databases, we analyzed CVs at the protein function level with bioinformatic programs. We proposed a combinatorial approach using the Support Vector Machine (SVM) to increase the performance of the prediction programs. By cataloging the coding sequence variations using these databases, we found that 4.36% of CVs from HGMD are concurrently registered in dbSNP (8.11% of CVs from dbSNP are concurrent in HGMD). The pattern of substitutions and functional consequences predicted by three bioinformatic programs was significantly different among concurrent CVs, and CVs occurring solely in HGMD or in dbSNP. The experimental results showed that the proposed SVM combination noticeably outperformed the individual prediction programs.

Conclusions

This is the first study to compare human sequence variations in HGMD, dbSNP and HapMap at the genome-wide level. We found that a significant proportion of CVs in HGMD and dbSNP overlap, and we emphasize the need to use caution when interpreting the phenotypic relevance of these concurrent CVs. Combining bioinformatic programs can be helpful in predicting the functional consequences of CVs because it improved the performance of functional predictions.     

遗传性胆红素代谢障碍与胆汁淤积NGS方法的建立及应用

为快速准确、低成本、高通量地检测我国人群常见的遗传性胆红素代谢障碍及胆汁淤积综合征,选择了10个易感基因的全部外显子及内含子剪切区的SNP/CNV,建立了基于二代测序技术(next generation sequencing, NGS)的靶向捕获测序方法。通过6例已知突变位点的样本对该方法的准确性进行验证,准确率为100%。收集首都医科大学附属北京友谊医院遗传性胆红素代谢障碍及胆汁淤积综合征患者39例进行检测,共检测到58种突变。检测结果与HGMD、Clin Var、OMIM突变数据库比较,未报道的突变通过千人基因组数据集对比并按照哈温平衡检验(HWE＿P>0.05)和χ²检验确定新突变19种。检测到的不同突变类型有效地揭示了该类疾病的遗传多样性。NGS方法的建立及应用为临床诊断提供了新的技术手段。     

A C. elegans homolog of the Cockayne syndrome complementation group A gene

Cockayne syndrome (CS) is a debilitating and complex disorder that results from inherited mutations in the CS complementation genes A and B, CSA and CSB. The links between the molecular functions of the CS genes and the complex pathophysiology of CS are as of yet poorly understood and are the subject of intense debate. While mouse models reflect the complexity of CS, studies on simpler genetic models might shed new light on the consequences of CS mutations. Here we describe a functional homolog of the human CSA gene in Caenorhabditis elegans. Similar to its human counterpart, mutations in the nematode csa-1 gene lead to developmental growth defects as a consequence of DNA lesions.