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Davis, J. R.

Publications and source records attributed to Davis, J. R..

3 recordsLinked to original sources

Identification of rare-disease genes in diverse undiagnosed cases using whole blood transcriptome sequencing and large control cohorts

RNA sequencing (RNA-seq) is a complementary approach for Mendelian disease diagnosis for patients in whom exome-sequencing is not informative. For both rare neuromuscular and mitochondrial disorders, its application has improved diagnostic rates. However, the generalizability of this approach to diverse Mendelian diseases has yet to be evaluated. We sequenced whole blood RNA from 56 cases with undiagnosed rare diseases spanning 11 diverse disease categories to evaluate the general application of RNA-seq to Mendelian disease diagnosis. We developed a robust approach to compare rare disease cases to existing large sets of RNA-seq controls (N=1,594 external and N=31 family-based controls) and demonstrated the substantial impacts of gene and variant filtering strategies on disease gene identification when combined with RNA-seq. Across our cohort, we observed that RNA-seq yields a 8.5% diagnostic rate. These diagnoses included diseases where blood would not intuitively reflect evidence of disease. We identified RARS2 as an under-expression outlier containing compound heterozygous pathogenic variants for an individual exhibiting profound global developmental delay, seizures, microcephaly, hypotonia, and progressive scoliosis. We also identified a new splicing junction in KCTD7 for an individual with global developmental delay, loss of milestones, tremors and seizures. Our study provides a broad evaluation of blood RNA-seq for the diagnosis of rare disease.

genomics

Automated Structural Variant Verification In Human Genomes Using Single-Molecule Electronic DNA Mapping

The importance of structural variation in human disease and the difficulty of detecting structural variants larger than 50 base pairs has led to the development of several long-read sequencing technologies and optical mapping platforms. Frequently, multiple technologies and ad hoc methods are required to obtain a consensus regarding the location, size and nature of a structural variant, with no approach able to reliably bridge the gap of variant sizes between the domain of short-read approaches and the largest rearrangements observed with optical mapping.\n\nTo address this unmet need, we have developed a new software package, SV-Verify, which utilizes data collected with the Nabsys High Definition Mapping (HD-Mapping) system, to perform hypothesis-based verification of putative deletions. We demonstrate that whole genome maps, constructed from electronic detection of tagged DNA, hundreds of kilobases in length, can be used effectively to facilitate calling of structural variants ranging in size from 300 base pairs to hundreds of kilobase pairs. SV-Verify implements hypothesis-based verification of putative structural variants using a set of support vector machines and is capable of concurrently testing several thousand independent hypotheses. We describe support vector machine training, utilizing a well-characterized human genome, and application of the resulting classifiers to another human genome, demonstrating high sensitivity and specificity for deletions [≥]300 base pairs.

genomics

High-Definition Electronic Genome Maps From Single Molecule Data

With the advent of routine short-read genome sequencing has come a growing recognition of the importance of long-range, structural information in applications ranging from sequence assembly to the detection of structural variation. Here we describe the Nabsys solid-state detector capable of detecting tags on single molecules of DNA 100s of kilobases in length as they translocate through the detector at a velocity greater than 1 megabase pair per second. Sequence-specific tags are detected with a high signal-to-noise ratio. The physical distance between tags is determined after accounting for viscous drag-induced intramolecular velocity fluctuations. The accurate measurement of the physical distance between tags on each molecule and the ability of the detector to resolve distances between tags of less than 300 base-pairs enables the construction of high-density genome maps.

genomics