Biology subjects

Wilcox, E.

Publications and source records attributed to Wilcox, E..

3 recordsLinked to original sources

bioRxiv2021

Evaluating the impact of in silico predictors on clinical variant classification

BackgroundIn silico evidence is important to consider when interpreting genetic variants. According to the ACMG/AMP, in silico evidence is applied at the supporting strength level using the PP3 and BP4 criteria, for pathogenic and benign evidence, respectively. While PP3 has been determined to be one of the most commonly applied criteria, less is known about the effect of these two criteria on variant classification outcomes. MethodsIn this study, a total of 727 missense variants curated by Clinical Genome Resource (ClinGen) Variant Curation Expert Panels (VCEPs) were analyzed to determine how often PP3 and BP4 were applied and how often they influenced final variant classifications. The current categorical system of variant classification was compared with a point-based system being developed by the ClinGen Sequence Variant Interpretation Working Group. In addition, the performance of four in silico tools (REVEL, VEST, FATHMM, and MPC) was assessed by using a gold set of 237 variants (classified as benign or pathogenic independent of PP3 or BP4) to calculate pathogenicity likelihood ratios. ResultsCollectively, the PP3 and BP4 criteria were applied by ClinGen VCEPs to 55% of missense variants in this data set. Removing in silico criteria from variants where they were originally applied caused variants to change classification from pathogenic to likely pathogenic (14%), likely pathogenic to variant of uncertain significance (VUS) (24%), or likely benign to VUS (64%). The proportion of downgrades with the categorical classification system was similar to that of the point-based system, though the latter resolved borderline classifications. REVEL and VEST performed at a level consistent with moderate strength towards either benign or pathogenic evidence, while FATHMM performed at the supporting level. ConclusionsOverall, this study demonstrates that in silico criteria PP3 and BP4 are commonly applied in variant classification and often affect the final classification. Our results suggest that when sufficient thresholds for in silico predictors are established, PP3 and BP4 may be appropriate to use at a moderate strength. However, further calibration with larger datasets is needed to optimize the performance of current in silico tools given the impact they have on clinical variant classification.

genomics↗

bioRxiv2021

Complex feline disease mapping using a dense genotyping array

The current feline genotyping array of 63k single nucleotide polymorphisms has proven its utility within breeds, and its use has led to the identification of variants associated with Mendelian traits in purebred cats. However, compared to single gene disorders, association studies of complex diseases, especially with the inclusion of random bred cats with relatively low linkage disequilibrium, require a denser genotyping array and an increased sample size to provide statistically significant associations. Here, we undertook a multi-breed study of 1,122 cats, most of which were admitted and phenotyped for nine common complex feline diseases at the Cornell University Hospital for Animals. Using a proprietary 340k single nucleotide polymorphism mapping array, we identified significant genome-wide associations with hyperthyroidism, diabetes mellitus, and eosinophilic keratoconjunctivitis. These results provide genomic locations for variant discovery and candidate gene screening for these important complex feline diseases, which are relevant not only to feline health, but also to the development of disease models for comparative studies.

genetics↗

bioRxiv2017

Cross-Site Comparison of Ribosomal Depletion Kits for Illumina RNAseq Library Construction

Ribosomal RNA (rRNA) comprises at least 90% of total RNA extracted from mammalian tissue or cell line samples. Informative transcriptional profiling using massively parallel sequencing technologies requires either enrichment of mature poly-adenylated transcripts or targeted depletion of the rRNA fraction. The latter method is of particular interest because it is compatible with degraded samples such as those extracted from FFPE and also captures transcripts that are not poly-adenylated such as some non-coding RNAs. Here we provide a cross-site study that evaluates the performance of ribosomal RNA removal kits from Illumina, Takara/Clontech, Kapa Biosystems, Lexogen, New England Biolabs and Qiagen on intact and degraded RNA samples. We find that all of the kits are capable of performing significant ribosomal depletion, though there are differences in their ease of use. All kits were able to remove ribosomal RNA to below 20% with intact RNA and identify [~]14,000 protein coding genes from the Universal Human Reference RNA sample at >1FPKM. Analysis of differentially detected genes between kits suggests that transcript length may be a key factor in library production efficiency. These results provide a roadmap for labs on the strengths of each of these methods and how best to utilize them.

genomics↗