Insights into genetics, human biology and disease gleaned from family based genomic studies.

Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of >75% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in novel "disease gene" discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.

The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities.

Discovering the genetic basis of a Mendelian phenotype establishes a causal link between genotype and phenotype, making possible carrier and population screening and direct diagnosis. Such discoveries also contribute to our knowledge of gene function, gene regulation, development, and biological mechanisms that can be used for developing new therapeutics. As of February 2015, 2,937 genes underlying 4,163 Mendelian phenotypes have been discovered, but the genes underlying ∼50% (i.e., 3,152) of all known Mendelian phenotypes are still unknown, and many more Mendelian conditions have yet to be recognized. This is a formidable gap in biomedical knowledge. Accordingly, in December 2011, the NIH established the Centers for Mendelian Genomics (CMGs) to provide the collaborative framework and infrastructure necessary for undertaking large-scale whole-exome sequencing and discovery of the genetic variants responsible for Mendelian phenotypes. In partnership with 529 investigators from 261 institutions in 36 countries, the CMGs assessed 18,863 samples from 8,838 families representing 579 known and 470 novel Mendelian phenotypes as of January 2015. This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype. These results provide insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelian phenotypes. Discovering the gene underlying every Mendelian phenotype will require tackling challenges such as worldwide ascertainment and phenotypic characterization of families affected by Mendelian conditions, improvement in sequencing and analytical techniques, and pervasive sharing of phenotypic and genomic data among researchers, clinicians, and families.

New tools for Mendelian disease gene identification: PhenoDB variant analysis module; and GeneMatcher, a web-based tool for linking investigators with an interest in the same gene.

Identifying the causative variant from among the thousands identified by whole-exome sequencing or whole-genome sequencing is a formidable challenge. To make this process as efficient and flexible as possible, we have developed a Variant Analysis Module coupled to our previously described Web-based phenotype intake tool, PhenoDB (http://researchphenodb.net and http://phenodb.org). When a small number of candidate-causative variants have been identified in a study of a particular patient or family, a second, more difficult challenge becomes proof of causality for any given variant. One approach to this problem is to find other cases with a similar phenotype and mutations in the same candidate gene. Alternatively, it may be possible to develop biological evidence for causality, an approach that is assisted by making connections to basic scientists studying the gene of interest, often in the setting of a model organism. Both of these strategies benefit from an open access, online site where individual clinicians and investigators could post genes of interest. To this end, we developed GeneMatcher (http://genematcher.org), a freely accessible Website that enables connections between clinicians and researchers across the world who share an interest in the same gene(s).

PhenoDB: a new web-based tool for the collection, storage, and analysis of phenotypic features.

To interpret whole exome/genome sequence data for clinical and research purposes, comprehensive phenotypic information, knowledge of pedigree structure, and results of previous clinical testing are essential. With these requirements in mind and to meet the needs of the Centers for Mendelian Genomics project, we have developed PhenoDB (http://phenodb.net), a secure, Web-based portal for entry, storage, and analysis of phenotypic and other clinical information. The phenotypic features are organized hierarchically according to the major headings and subheadings of the Online Mendelian Inheritance in Man (OMIM®) clinical synopses, with further subdivisions according to structure and function. Every string allows for a free-text entry. All of the approximately 2,900 features use the preferred term from Elements of Morphology and are fully searchable and mapped to the Human Phenotype Ontology and Elements of Morphology. The PhenoDB allows for ascertainment of relevant information from a case in a family or cohort, which is then searchable by family, OMIM number, phenotypic feature, mode of inheritance, genes screened, and so on. The database can also be used to format phenotypic data for submission to dbGaP for appropriately consented individuals. PhenoDB was built using Django, an open source Web development tool, and is freely available through the Johns Hopkins McKusick-Nathans Institute of Genetic Medicine (http://phenodb.net).

Genome-wide allelotypes of familial pancreatic adenocarcinomas and familial and sporadic intraductal papillary mucinous neoplasms.

PURPOSE: Most familial cancer susceptibility genes are tumor suppressor genes that are biallelically inactivated in familial neoplasms through somatic deletion of the wild-type allele. Identifying the genomic losses that occur in pancreatic neoplasms, particularly those that occur in familial and precursor neoplasms, may help localize the genes responsible for pancreatic cancer susceptibility. EXPERIMENTAL DESIGN: Normal and neoplastic tissue DNA was isolated from fresh-frozen surgically resected tissues from 20 patients with primary familial pancreatic adenocarcinoma (defined as having at least one first-degree relative with pancreatic cancer), 31 with sporadic intraductal papillary mucinous neoplasms (IPMN), and 7 with familial IPMNs using laser capture microdissection. Microdissected DNA was whole genome amplified using multiple strand displacement. Genome-wide allelotypes were determined using 391 microsatellite markers. The accuracy of microdissection and fidelity of the whole genome amplification were determined by comparing the genotypes of microdissected primary pancreatic cancers to the genotypes of xenografts derived from these cancers and by comparing the results of amplified to nonamplified specimens. RESULTS: The concordance of genotypes between LCM whole genome amplified primary pancreatic cancers and their corresponding pancreatic cancer xenograft DNAs was 98%. Among the 20 primary familial pancreatic adenocarcinomas, we found a high prevalence of loss of heterozygosity (LOH) with an average fractional allelic loss (FAL) of 49.9% of an aggregate of 2,378 informative markers. The level of FAL in the IPMNs (10%) was significantly lower than in the pancreatic adenocarcinomas. The most common locus of LOH in the IPMNs was at 19p (LOH at 24% of markers). The regions of frequent allelic loss observed in the familial pancreatic cancers were similar to those found in sporadic pancreatic cancers. CONCLUSIONS: The allelic loss patterns of familial and sporadic pancreatic cancers and IPMNs provide clues as to the genomic locations of tumor suppressor genes inactivated in these neoplasms.

Mutations in RARS cause a hypomyelination disorder akin to Pelizaeus-Merzbacher disease.

Pelizaeus-Merzbacher disease (PMD) is a rare Mendelian disorder characterised by central nervous system hypomyelination. PMD typically manifests in infancy or early childhood and is caused by mutations in proteolipid protein-1 (PLP1). However, variants in several other genes including gap junction protein gamma 2 (GJC2) can also cause a similar phenotype and are referred to PMD-like disease (PMLD). Whole-exome sequencing in two siblings presenting with clinical symptoms of PMD revealed a homozygous variant in the arginyl-tRNA synthetase (RARS) gene: NM_002887.3: c.[5A>G] p.(Asp2Gly). Subsequent screening of a PMD cohort without a genetic diagnosis identified an unrelated individual with novel compound heterozygous variants including a missense variant c.[1367C>T] p.(Ser456Leu) and a de novo deletion c.[1846_1847delTA] p.(Tyr616Leufs*6). Protein levels of RARS and the multi-tRNA synthetase complex into which it assembles were found to be significantly reduced by 80 and 90% by western blotting and Blue native-PAGE respectively using patient fibroblast extracts. As RARS is involved in protein synthesis whereby it attaches arginine to its cognate tRNA, patient cells were studied to determine their ability to proliferate with limiting amounts of this essential amino acid. Patient fibroblasts cultured in medium with limited arginine at 30 °C and 40 °C, showed a significant decrease in fibroblast proliferation (P<0.001) compared to control cells, suggestive of inefficiency of protein synthesis in the patient cells. Our functional studies provide further evidence that RARS is a PMD-causing gene.

Whole-exome sequencing identifies novel variants in PNPT1 causing oxidative phosphorylation defects and severe multisystem disease.

Recent advances in next-generation sequencing strategies have led to the discovery of many novel disease genes. We describe here a non-consanguineous family with two affected boys presenting with early onset of severe axonal neuropathy, optic atrophy, intellectual disability, auditory neuropathy and chronic respiratory and gut disturbances. Whole-exome sequencing (WES) was performed on all family members and we identified compound heterozygous variants (c.[760C>A];[1528G>C];p.[(Gln254Lys);(Ala510Pro)] in the polyribonucleotide nucleotidyltransferase 1 (PNPT1) gene in both affected individuals. PNPT1 encodes the polynucleotide phosphorylase (PNPase) protein, which is involved in the transport of small RNAs into the mitochondria. These RNAs are involved in the mitochondrial translation machinery, responsible for the synthesis of mitochondrially encoded subunits of the oxidative phosphorylation (OXPHOS) complexes. Both PNPT1 variants are within highly conserved regions and predicted to be damaging. These variants resulted in quaternary defects in the PNPase protein and a clear reduction in protein and mRNA expression of PNPT1 in patient fibroblasts compared with control cells. Protein analysis of the OXPHOS complexes showed a significant reduction in complex I (CI), complex III (CIII) and complex IV (CIV). Enzyme activity of CI and CIV was clearly reduced in patient fibroblasts compared with controls along with a 33% reduction in total mitochondrial protein synthesis. In vitro rescue experiments, using exogenous expression of wild-type PNPT1 in patient fibroblasts, ameliorated the deficiencies in the OXPHOS complex protein expression, supporting the likely pathogenicity of these variants and the importance of WES in efficiently identifying rare genetic disease genes.

Clinical consequences of an increasing trend of preferential use of cultured villi for molecular diagnosis by CVS.

OBJECTIVE: To compare the use of uncultured versus cultured villus cells for DNA-based prenatal diagnosis. METHODS: A retrospective review of molecular testing of chorionic villus sampling (CVS) cases from 1988-2007. Method of analysis, gestational age (GA) at CVS and at diagnosis, time from procedure to results, results of maternal contamination studies, and the laboratory employed were abstracted from patient charts. Trends in laboratory practices over time were analyzed. RESULTS: Time from CVS to diagnosis was longer when cultured cells were used. Average GA at diagnosis was 14-6/7 weeks with cultured cells vs 13-0/7 weeks with uncultured villi (p < 0.001). Recently, laboratories are more frequently requiring cultured cells, resulting in significantly greater delays in time to diagnosis and GA at results. CONCLUSIONS: 'Direct' DNA extraction saves 2 weeks from CVS to results. More women are afforded the option of an earlier, safer pregnancy termination if uncultured villi are used for molecular diagnosis. Implementation of standardized DNA extraction protocols and sample-size requirements can optimize the use of uncultured villi for molecular prenatal diagnosis. Increased awareness of the importance of rapid results and the advantages of 'direct' DNA extraction from uncultured villi can lead to improvements that are of clinical significance for patients undergoing early prenatal diagnosis.

The development of a highly informative mouse Simple Sequence Length Polymorphism (SSLP) marker set and construction of a mouse family tree using parsimony analysis.

To identify highly informative markers for a large number of commonly employed murine crosses, we selected a subset of the extant mouse simple sequence length polymorphism (SSLP) marker set for further development. Primer pairs for 314 SSLP markers were designed and typed against 54 inbred mouse strains. We designed new PCR primer sequences for the markers selected for multiplexing using the fluorescent dyes FAM, VIC, NED, and ROX. The number of informative markers for C57BL/6J x DBA/2J is 217, with an average spacing of 6.8 centiMorgans (cM). For all other pairs of strains, the mean number of informative markers per cross is 197.0 (SD 37.8) with a mean distance between markers of 6.8 cM (SD 1.1). To confirm map positions of the 224 markers in our set that are polymorphic between Mus musculus and Mus spretus, we used The Jackson Laboratory (TJL) interspecific backcross mapping panel (TJL BSS); 168 (75%) of these markers had not been previously mapped in this cross by other investigators, adding new information to this community map resource. With this large data set, we sought to reconstruct a phylogenetic history of the laboratory mouse using Wagner parsimony analysis. Our results are largely congruent with the known history of inbred mouse strains.