henhaobio
Sign in

Human Molecular GeneticsGeneticsPeer-reviewed journal article

A combined RNA-seq and whole genome sequencing approach for identification of non-coding pathogenic variants in single families.

Revital BronsteiniD, Elizabeth E. CapowskiiD, Sudeep MehrotraiD, Alex D. Jansen, Daniel Navarro-Gomez, Mathew Maher, Emily PlaceiD, Riccardo SangermanoiD, Kinga M. BujakowskaiD, David M. GammiD, Eric A. PierceiD

PDFDOIPreprint

Abstract

Inherited retinal degenerations (IRDs) are at the focus of current genetic therapeutic advancements. For a genetic treatment such as gene therapy to be successful an accurate genetic diagnostic is required. Genetic diagnostics relies on the assessment of the probability that a given DNA variant is pathogenic. Non-coding variants present a unique challenge for such assessments as compared to coding variants. For one, non-coding variants are present at much higher number in the genome than coding variants. In addition, our understanding of the rules that govern the non-coding regions of the genome is less complete than our understanding of the coding regions. Methods that allow for both the identification of candidate non-coding pathogenic variants and their functional validation may help overcome these caveats allowing for a greater number of patients to benefit from advancements in genetic therapeutics. We present here an unbiased approach combining whole genome sequencing (WGS) with patient induced pluripotent stem cell (iPSC) derived retinal organoids (ROs) transcriptome analysis. With this approach we identified and functionally validated a novel pathogenic non-coding variant in a small family with a previously unresolved genetic diagnosis.

Citations
26
FWCI
0.97
Field percentile
top 29%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISJamshidi '18Zampaglione '20Wen '23Rodenburg '26Rey '24Fabian-Mora '25
69% semantic matchGenomics
Farzad Jamshidi, Emily Place, Sudeep Mehrotra+9 more·Genetics in Medicine·Aug 1, 2018· 29 citations