Identity-by-descent filtering as a tool for the identification of disease alleles in exome sequence data from distant relatives

Large-scale, deep resequencing may be the next logical step in the genetic investigation of common complex diseases. Because each individual is likely to carry many thousands of variants, the identification of causal alleles requires an efficient strategy to reduce the number of candidate variants. Under many genetic models, causal alleles can be expected to reside within identity-by-descent (IBD) regions shared by affected relatives. In distant relatives, IBD regions constitute a small portion of the genome and can thus greatly reduce the search space for causal alleles. However, the effectiveness of this strategy is unknown. We test the simulated mini-exome data set in extended pedigrees provided by Genetic Analysis Workshop 17. At the fourth- and fifth-degree level of relatedness, case-case pairs shared between 1% and 9% of the genome identical by descent. As expected, no genes were shared identical by descent by all case subjects, but 43 genes were shared by many case subjects across at least 50 replicates. We filtered variants in these genes based on population frequency, function, informativeness, and evidence of association using the family-based association test. This analysis highlighted five genes previously implicated in triglyceride, lipid, and cholesterol metabolism. Comparison with the list of true risk alleles revealed that strict IBD filtering followed by association testing of the rarest alleles was the most sensitive strategy. IBD filtering may be a useful strategy for narrowing down the list of candidate variants in exome data, but the optimal degree of relatedness of affected pairs will depend on the genetic architecture of the disease under study

Whole-exome re-sequencing in a family quartet identifies POP1 mutations as the cause of a novel skeletal dysplasia

Recent advances in DNA sequencing have enabled mapping of genes for monogenic traits in families with small pedigrees and even in unrelated cases. We report the identification of disease-causing mutations in a rare, severe, skeletal dysplasia, studying a family of two healthy unrelated parents and two affected children using whole-exome sequencing. The two affected daughters have clinical and radiographic features suggestive of anauxetic dysplasia (OMIM 607095), a rare form of dwarfism caused by mutations of RMRP. However, mutations of RMRP were excluded in this family by direct sequencing. Our studies identified two novel compound heterozygous loss-of-function mutations in POP1, which encodes a core component of the RNase mitochondrial RNA processing (RNase MRP) complex that directly interacts with the RMRP RNA domains that are affected in anauxetic dysplasia. We demonstrate that these mutations impair the integrity and activity of this complex and that they impair cell proliferation, providing likely molecular and cellular mechanisms by which POP1 mutations cause this severe skeletal dysplasia

Statistical Guidance for Experimental Design and Data Analysis of Mutation Detection in Rare Monogenic Mendelian Diseases by Exome Sequencing

Recently, whole-genome sequencing, especially exome sequencing, has successfully led to the identification of causal mutations for rare monogenic Mendelian diseases. However, it is unclear whether this approach can be generalized and effectively applied to other Mendelian diseases with high locus heterogeneity. Moreover, the current exome sequencing approach has limitations such as false positive and false negative rates of mutation detection due to sequencing errors and other artifacts, but the impact of these limitations on experimental design has not been systematically analyzed. To address these questions, we present a statistical modeling framework to calculate the power, the probability of identifying truly disease-causing genes, under various inheritance models and experimental conditions, providing guidance for both proper experimental design and data analysis. Based on our model, we found that the exome sequencing approach is well-powered for mutation detection in recessive, but not dominant, Mendelian diseases with high locus heterogeneity. A disease gene responsible for as low as 5% of the disease population can be readily identified by sequencing just 200 unrelated patients. Based on these results, for identifying rare Mendelian disease genes, we propose that a viable approach is to combine, sequence, and analyze patients with the same disease together, leveraging the statistical framework presented in this work

Analysis of exome data for 4293 trios suggests GPI-anchor biogenesis defects are a rare cause of developmental disorders.

Over 150 different proteins attach to the plasma membrane using glycosylphosphatidylinositol (GPI) anchors. Mutations in 18 genes that encode components of GPI-anchor biogenesis result in a phenotypic spectrum that includes learning disability, epilepsy, microcephaly, congenital malformations and mild dysmorphic features. To determine the incidence of GPI-anchor defects, we analysed the exome data from 4293 parent-child trios recruited to the Deciphering Developmental Disorders (DDD) study. All probands recruited had a neurodevelopmental disorder. We searched for variants in 31 genes linked to GPI-anchor biogenesis and detected rare biallelic variants in PGAP3, PIGN, PIGT (n=2), PIGO and PIGL, providing a likely diagnosis for six families. In five families, the variants were in a compound heterozygous configuration while in a consanguineous Afghani kindred, a homozygous c.709G>C; p.(E237Q) variant in PIGT was identified within 10-12 Mb of autozygosity. Validation and segregation analysis was performed using Sanger sequencing. Across the six families, five siblings were available for testing and in all cases variants co-segregated consistent with them being causative. In four families, abnormal alkaline phosphatase results were observed in the direction expected. FACS analysis of knockout HEK293 cells that had been transfected with wild-type or mutant cDNA constructs demonstrated that the variants in PIGN, PIGT and PIGO all led to reduced activity. Splicing assays, performed using leucocyte RNA, showed that a c.336-2A>G variant in PIGL resulted in exon skipping and p.D113fs*2. Our results strengthen recently reported disease associations, suggest that defective GPI-anchor biogenesis may explain ~0.15% of individuals with developmental disorders and highlight the benefits of data sharing

Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease

Pedigree, linkage and association studies are consistent with heritable variation for complex disease due to the segregation of genetic factors in families and in the population. In contrast, de novo mutations make only minor contributions to heritability estimates for complex traits. Nonetheless, some de novo variants are known to be important in disease etiology. The identification of risk-conferring de novo variants will contribute to the discovery of etiologically relevant genes and pathways and may help in genetic counseling. There is considerable interest in the role of such mutations in complex neuropsychiatric disease, largely driven by new genotyping and sequencing technologies. An important role for large de novo copy number variations has been established. Recently, whole-exome sequencing has been used to extend the investigation of de novo variation to point mutations in protein-coding regions. Here, we consider several challenges for the interpretation of such mutations in the context of their role in neuropsychiatric disease

From glycosylation disorders to dolichol biosynthesis defects: a new class of metabolic diseases

Polyisoprenoid alcohols are membrane lipids that are present in every cell, conserved from archaea to higher eukaryotes. The most common form, alpha-saturated polyprenol or dolichol is present in all tissues and most organelle membranes of eukaryotic cells. Dolichol has a well defined role as a lipid carrier for the glycan precursor in the early stages of N-linked protein glycosylation, which is assembled in the endoplasmic reticulum of all eukaryotic cells. Other glycosylation processes including C- and O-mannosylation, GPI-anchor biosynthesis and O-glucosylation also depend on dolichol biosynthesis via the availability of dolichol-P-mannose and dolichol-P-glucose in the ER. The ubiquity of dolichol in cellular compartments that are not involved in glycosylation raises the possibility of additional functions independent of these protein post-translational modifications. The molecular basis of several steps involved in the synthesis and the recycling of dolichol and its derivatives is still unknown, which hampers further research into this direction. In this review, we summarize the current knowledge on structural and functional aspects of dolichol metabolites. We will describe the metabolic disorders with a defect in known steps of dolichol biosynthesis and recycling in human and discuss their pathogenic mechanisms. Exploration of the developmental, cellular and biochemical defects associated with these disorders will provide a better understanding of the functions of this lipid class in human

Targeted high throughput sequencing in clinical cancer Settings: formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity

<p>Abstract</p> <p>Background</p> <p>Massively parallel sequencing technologies have brought an enormous increase in sequencing throughput. However, these technologies need to be further improved with regard to reproducibility and applicability to clinical samples and settings.</p> <p>Methods</p> <p>Using identification of genetic variations in prostate cancer as an example we address three crucial challenges in the field of targeted re-sequencing: Small nucleotide variation (SNV) detection in samples of formalin-fixed paraffin embedded (FFPE) tissue material, minimal amount of input sample and sampling in view of tissue heterogeneity.</p> <p>Results</p> <p>We show that FFPE tissue material can supplement for fresh frozen tissues for the detection of SNVs and that solution-based enrichment experiments can be accomplished with small amounts of DNA with only minimal effects on enrichment uniformity and data variance.</p> <p>Finally, we address the question whether the heterogeneity of a tumor is reflected by different genetic alterations, e.g. different foci of a tumor display different genomic patterns. We show that the tumor heterogeneity plays an important role for the detection of copy number variations.</p> <p>Conclusions</p> <p>The application of high throughput sequencing technologies in cancer genomics opens up a new dimension for the identification of disease mechanisms. In particular the ability to use small amounts of FFPE samples available from surgical tumor resections and histopathological examinations facilitates the collection of precious tissue materials. However, care needs to be taken in regard to the locations of the biopsies, which can have an influence on the prediction of copy number variations. Bearing these technological challenges in mind will significantly improve many large-scale sequencing studies and will - in the long term - result in a more reliable prediction of individual cancer therapies.</p

Whole-Exome Sequencing and Homozygosity Analysis Implicate Depolarization-Regulated Neuronal Genes in Autism

Although autism has a clear genetic component, the high genetic heterogeneity of the disorder has been a challenge for the identification of causative genes. We used homozygosity analysis to identify probands from nonconsanguineous families that showed evidence of distant shared ancestry, suggesting potentially recessive mutations. Whole-exome sequencing of 16 probands revealed validated homozygous, potentially pathogenic recessive mutations that segregated perfectly with disease in 4/16 families. The candidate genes (UBE3B, CLTCL1, NCKAP5L, ZNF18) encode proteins involved in proteolysis, GTPase-mediated signaling, cytoskeletal organization, and other pathways. Furthermore, neuronal depolarization regulated the transcription of these genes, suggesting potential activity-dependent roles in neurons. We present a multidimensional strategy for filtering whole-exome sequence data to find candidate recessive mutations in autism, which may have broader applicability to other complex, heterogeneous disorders

Somatic Mutation Profiles of MSI and MSS Colorectal Cancer Identified by Whole Exome Next Generation Sequencing and Bioinformatics Analysis

BACKGROUND: Colorectal cancer (CRC) is with approximately 1 million cases the third most common cancer worldwide. Extensive research is ongoing to decipher the underlying genetic patterns with the hope to improve early cancer diagnosis and treatment. In this direction, the recent progress in next generation sequencing technologies has revolutionized the field of cancer genomics. However, one caveat of these studies remains the large amount of genetic variations identified and their interpretation. METHODOLOGY/PRINCIPAL FINDINGS: Here we present the first work on whole exome NGS of primary colon cancers. We performed 454 whole exome pyrosequencing of tumor as well as adjacent not affected normal colonic tissue from microsatellite stable (MSS) and microsatellite instable (MSI) colon cancer patients and identified more than 50,000 small nucleotide variations for each tissue. According to predictions based on MSS and MSI pathomechanisms we identified eight times more somatic non-synonymous variations in MSI cancers than in MSS and we were able to reproduce the result in four additional CRCs. Our bioinformatics filtering approach narrowed down the rate of most significant mutations to 359 for MSI and 45 for MSS CRCs with predicted altered protein functions. In both CRCs, MSI and MSS, we found somatic mutations in the intracellular kinase domain of bone morphogenetic protein receptor 1A, BMPR1A, a gene where so far germline mutations are associated with juvenile polyposis syndrome, and show that the mutations functionally impair the protein function. CONCLUSIONS/SIGNIFICANCE: We conclude that with deep sequencing of tumor exomes one may be able to predict the microsatellite status of CRC and in addition identify potentially clinically relevant mutations