Publications by authors named "Anjali D Zimmer"

The relevance of large copy number variants (CNVs) to hereditary disorders has been long recognized, and population sequencing efforts have chronicled many common structural variants (SVs). However, limited data are available on the clinical contribution of rare germline SVs. Here, a detailed characterization of SVs identified using targeted next-generation sequencing was performed.

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Publicly available genetic databases promote data sharing and fuel scientific discoveries for the prevention, treatment and management of disease. In 2018, we built Color Data, a user-friendly, open access database containing genotypic and self-reported phenotypic information from 50 000 individuals who were sequenced for 30 genes associated with hereditary cancer. In a continued effort to promote access to these types of data, we launched Color Data v2, an updated version of the Color Data database.

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Advances in genome sequencing have led to a tremendous increase in the discovery of novel missense variants, but evidence for determining clinical significance can be limited or conflicting. Here, we present Learning from Evidence to Assess Pathogenicity (LEAP), a machine learning model that utilizes a variety of feature categories to classify variants, and achieves high performance in multiple genes and different health conditions. Feature categories include functional predictions, splice predictions, population frequencies, conservation scores, protein domain data, and clinical observation data such as personal and family history and covariant information.

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Recent advancements in next-generation sequencing have greatly expanded the use of multi-gene panel testing for hereditary cancer risk. Although genetic testing helps guide clinical diagnosis and management, testing recommendations are based on personal and family history of cancer and ethnicity, and many carriers are being missed. Herein, we report the results from 23,179 individuals who were referred for 30-gene next-generation sequencing panel testing for hereditary cancer risk, independent of current testing guidelines-38.

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Next generation sequencing multi-gene panels have greatly improved the diagnostic yield and cost effectiveness of genetic testing and are rapidly being integrated into the clinic for hereditary cancer risk. With this technology comes a dramatic increase in the volume, type and complexity of data. This invaluable data though is too often buried or inaccessible to researchers, especially to those without strong analytical or programming skills.

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In cascade testing, genetic testing for an identified familial pathogenic variant extends to disease-free relatives to allow genetically targeted disease prevention. We evaluated the results of an online initiative in which carriers of 1 of 30 cancer-associated genes, or their first-degree relatives, could offer low-cost testing to at-risk first-degree relatives. In the first year, 1101 applicants invited 2280 first-degree relatives to undergo genetic testing.

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Background: Next generation sequencing (NGS) has become a common technology for clinical genetic tests. The quality of NGS calls varies widely and is influenced by features like reference sequence characteristics, read depth, and mapping accuracy. With recent advances in NGS technology and software tools, the majority of variants called using NGS alone are in fact accurate and reliable.

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DNA:RNA hybrids can lead to DNA damage and genome instability. This damage can be prevented by degradation of the RNA in the hybrid by two evolutionarily conserved enzymes, RNase H1 and H2. Indeed, RNase H-deficient cells have increased chromosomal rearrangements.

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In Saccharomyces cerevisiae, transcription of the MET regulon, which encodes the proteins involved in the synthesis of the sulfur-containing amino acids methionine and cysteine, is repressed by the presence of either methionine or cysteine in the environment. This repression is accomplished by ubiquitination of the transcription factor Met4, which is carried out by the SCF(Met30) E3 ubiquitin ligase. Mutants defective in MET regulon repression reveal that loss of Cho2, which is required for the methylation of phosphatidylethanolamine to produce phosphatidylcholine, leads to induction of the MET regulon.

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