Rare variant phasing using paired tumor:normal sequence data.

BACKGROUND: In standard high throughput sequencing analysis, genetic variants are not assigned to a homologous chromosome of origin. This process, called haplotype phasing, can reveal information important for understanding the relationship between genetic variants and biological phenotypes. For example, in genes that carry multiple heterozygous missense variants, phasing resolves whether one or both gene copies are altered. Here, we present a novel approach to phasing variants that takes advantage of unique properties of paired tumor:normal sequencing data from cancer studies. RESULTS: VAF phasing uses changes in variant allele frequency (VAF) between tumor and normal samples in regions of somatic chromosomal gain or loss to phase germline variants. We apply VAF phasing to 6180 samples from the Cancer Genome Atlas (TCGA) and demonstrate that our method is highly concordant with other standard phasing methods, and can phase an average of 33% more variants than other read-backed phasing methods. Using variant annotation tools designed to score gene haplotypes, we find a suggestive association between carrying multiple missense variants in a single copy of a cancer predisposition gene and earlier age of cancer diagnosis. CONCLUSIONS: VAF phasing exploits unique properties of tumor genomes to increase the number of germline variants that can be phased over standard read-backed methods in paired tumor:normal samples. Our phase-informed association testing results call attention to the need to develop more tools for assessing the joint effect of multiple genetic variants.

Independent Neuronal Origin of Seizures and Behavioral Comorbidities in an Animal Model of a Severe Childhood Genetic Epileptic Encephalopathy.

The childhood epileptic encephalopathies (EE's) are seizure disorders that broadly impact development including cognitive, sensory and motor progress with severe consequences and comorbidities. Recently, mutations in DNM1 (dynamin 1) have been implicated in two EE syndromes, Lennox-Gastaut Syndrome and Infantile Spasms. Dnm1 encodes dynamin 1, a large multimeric GTPase necessary for activity-dependent membrane recycling in neurons, including synaptic vesicle endocytosis. Dnm1Ftfl or "fitful" mice carry a spontaneous mutation in the mouse ortholog of DNM1 and recapitulate many of the disease features associated with human DNM1 patients, providing a relevant disease model of human EE's. In order to examine the cellular etiology of seizures and behavioral and neurological comorbidities, we engineered a conditional Dnm1Ftfl mouse model of DNM1 EE. Observations of Dnm1Ftfl/flox mice in combination with various neuronal subpopulation specific cre strains demonstrate unique seizure phenotypes and clear separation of major neurobehavioral comorbidities from severe seizures associated with the germline model. This demonstration of pleiotropy suggests that treating seizures per se may not prevent severe comorbidity observed in EE associated with dynamin-1 mutations, and is likely to have implications for other genetic forms of EE.

Pan-cancer analysis reveals technical artifacts in TCGA germline variant calls.

BACKGROUND: Cancer research to date has largely focused on somatically acquired genetic aberrations. In contrast, the degree to which germline, or inherited, variation contributes to tumorigenesis remains unclear, possibly due to a lack of accessible germline variant data. Here we called germline variants on 9618 cases from The Cancer Genome Atlas (TCGA) database representing 31 cancer types. RESULTS: We identified batch effects affecting loss of function (LOF) variant calls that can be traced back to differences in the way the sequence data were generated both within and across cancer types. Overall, LOF indel calls were more sensitive to technical artifacts than LOF Single Nucleotide Variant (SNV) calls. In particular, whole genome amplification of DNA prior to sequencing led to an artificially increased burden of LOF indel calls, which confounded association analyses relating germline variants to tumor type despite stringent indel filtering strategies. The samples affected by these technical artifacts include all acute myeloid leukemia and practically all ovarian cancer samples. CONCLUSIONS: We demonstrate how technical artifacts induced by whole genome amplification of DNA can lead to false positive germline-tumor type associations and suggest TCGA whole genome amplified samples be used with caution. This study draws attention to the need to be sensitive to problems associated with a lack of uniformity in data generation in TCGA data.

Exome-wide analysis of bi-allelic alterations identifies a Lynch phenotype in The Cancer Genome Atlas.

BACKGROUND: Cancer susceptibility germline variants generally require somatic alteration of the remaining allele to drive oncogenesis and, in some cases, tumor mutational profiles. Whether combined germline and somatic bi-allelic alterations are universally required for germline variation to influence tumor mutational profile is unclear. Here, we performed an exome-wide analysis of the frequency and functional effect of bi-allelic alterations in The Cancer Genome Atlas (TCGA). METHODS: We integrated germline variant, somatic mutation, somatic methylation, and somatic copy number loss data from 7790 individuals from TCGA to identify germline and somatic bi-allelic alterations in all coding genes. We used linear models to test for association between mono- and bi-allelic alterations and somatic microsatellite instability (MSI) and somatic mutational signatures. RESULTS: We discovered significant enrichment of bi-allelic alterations in mismatch repair (MMR) genes and identified six bi-allelic carriers with elevated MSI, consistent with Lynch syndrome. In contrast, we find little evidence of an effect of mono-allelic germline variation on MSI. Using MSI burden and bi-allelic alteration status, we reclassify two variants of unknown significance in MSH6 as potentially pathogenic for Lynch syndrome. Extending our analysis of MSI to a set of 127 DNA damage repair (DDR) genes, we identified a novel association between methylation of SHPRH and MSI burden. CONCLUSIONS: We find that bi-allelic alterations are infrequent in TCGA but most frequently occur in BRCA1/2 and MMR genes. Our results support the idea that bi-allelic alteration is required for germline variation to influence tumor mutational profile. Overall, we demonstrate that integrating germline, somatic, and epigenetic alterations provides new understanding of somatic mutational profiles.