Empirical prediction of variant-associated cryptic-donors with 87% sensitivity and 95% specificity

Abstract Predicting which cryptic-donors may be activated by a genetic variant is notoriously difficult. Through analysis of 5,145 cryptic-donors activated by 4,811 variants (versus 86,963 decoy-donors not used; any GT or GC), we define an empirical method predicting cryptic-donor activation with 87% sensitivity and 95% specificity. Strength (according to four algorithms) and proximity to the authentic-donor appear important determinants of cryptic-donor activation. However, other factors such as auxiliary splicing elements, which are difficult to identify, play an important role and are likely responsible for current prediction inaccuracies. We find that the most frequent mis-splicing events at each exon-intron junction, mined from 40,233 RNA-sequencing samples, predict with remarkable accuracy which cryptic-donor will be activated in rare disease. Aggregate RNA-Sequencing splice-junction data provides an accurate, evidence-based method to predict variant-activated cryptic-donors in genetic disorders, assisting pathology consideration of possible consequences of a variant for the encoded protein and RNA diagnostic testing strategies.

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Empirical prediction of variant-associated cryptic-donors with 87% sensitivity and 95% specificity

10.1101/2021.07.18.452855 ◽

2021 ◽

Author(s):

Ruebena Dawes ◽

Himanshu Joshi ◽

Sandra T Cooper

Keyword(s):

Rare Disease ◽

Rna Sequencing ◽

Genetic Variant ◽

Genetic Disorders ◽

Diagnostic Testing ◽

Splice Junction ◽

Empirical Method ◽

Evidence Based ◽

Empirical Prediction ◽

Testing Strategies

Predicting which cryptic-donors may be activated by a genetic variant is notoriously difficult. Through analysis of 5,145 cryptic-donors activated by 4,811 variants (versus 86,963 decoy-donors not used; any GT or GC), we define an empirical method predicting cryptic-donor activation with 87% sensitivity and 95% specificity. Strength (according to four algorithms) and proximity to the authentic-donor appear important determinants of cryptic-donor activation. However, other factors such as auxiliary splicing elements, which are difficult to identify, play an important role and are likely responsible for current prediction inaccuracies. We find that the most frequent mis-splicing events at each exon-intron junction, mined from 40,233 RNA-sequencing samples, predict with remarkable accuracy which cryptic-donor will be activated in rare disease. Aggregate RNA-Sequencing splice-junction data provides an accurate, evidence-based method to predict variant-activated cryptic-donors in genetic disorders, assisting pathology consideration of possible consequences of a variant for the encoded protein and RNA diagnostic testing strategies.

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MRSD: a novel quantitative approach for assessing suitability of RNA-seq in the clinical investigation of mis-splicing in Mendelian disease

10.1101/2021.03.19.21253973 ◽

2021 ◽

Author(s):

Charlie F. Rowlands ◽

Algy Taylor ◽

Gillian Rice ◽

Nicola Whiffin ◽

Hildegard Nikki Hall ◽

...

Keyword(s):

Rna Sequencing ◽

Diagnostic Yield ◽

Clinical Investigation ◽

Genetic Disorders ◽

Splice Junction ◽

Mendelian Disease ◽

Gene Transcript ◽

Relative Expression Level ◽

Gene Panels ◽

The Impact

Background: RNA-sequencing of patient biosamples is a promising approach to delineate the impact of genomic variants on splicing, but variable gene expression between tissues complicates selection of appropriate tissues. Relative expression level is often used as a metric to predict RNA-sequencing utility. Here, we describe a gene- and tissue-specific metric to inform the feasibility of RNA-sequencing, overcoming some issues with using expression values alone. Results: We derive a novel metric, Minimum Required Sequencing Depth (MRSD), for all genes across three human biosamples (whole blood, lymphoblastoid cell lines (LCLs) and skeletal muscle). MRSD estimates the depth of sequencing required from RNA-sequencing to achieve user-specified sequencing coverage of a gene, transcript or group of genes of interest. MRSD predicts levels of splice junction coverage with high precision (90.1-98.2%) and overcomes transcript region-specific sequencing biases. Applying MRSD scoring to established disease gene panels shows that LCLs are the optimum source of RNA, of the three investigated biosamples, for 69.3% of gene panels. Our approach demonstrates that up to 59.4% of variants of uncertain significance in ClinVar predicted to impact splicing could be functionally assayed by RNA-sequencing in at least one of the investigated biosamples. Conclusions: We demonstrate the power of MRSD as a metric to inform choice of appropriate biosamples for the functional assessment of splicing aberrations. We apply MRSD in the context of Mendelian genetic disorders and illustrate its benefits over expression-based approaches. We anticipate that the integration of MRSD into clinical pipelines will improve variant interpretation and, ultimately, diagnostic yield.

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Herd Diagnostic Testing Strategies

Bovine Reproduction ◽

10.1002/9781119602484.ch43 ◽

2021 ◽

pp. 526-531

Author(s):

Robert L. Larson

Keyword(s):

Diagnostic Testing ◽

Testing Strategies

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The cost-effectiveness of diagnostic testing strategies for Helicobacter pylori

The American Journal of Gastroenterology ◽

10.1111/j.1572-0241.2000.02193.x ◽

2000 ◽

Vol 95 (7) ◽

pp. 1691-1698 ◽

Cited By ~ 8

Author(s):

Nimish Vakil ◽

David Rhew ◽

Andrew Soll ◽

Joshua J. Ofman

Keyword(s):

Helicobacter Pylori ◽

Cost Effectiveness ◽

Diagnostic Testing ◽

Testing Strategies ◽

The Cost

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Splicing in the Diagnosis of Rare Disease: Advances and Challenges

Frontiers in Genetics ◽

10.3389/fgene.2021.689892 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jenny Lord ◽

Diana Baralle

Keyword(s):

Rare Disease ◽

Clinical Application ◽

Predictive Modeling ◽

Diagnostic Testing ◽

Rare Disorders ◽

Diagnostic Odyssey ◽

Sequencing Technologies ◽

Splicing Variants ◽

The Way

Mutations which affect splicing are significant contributors to rare disease, but are frequently overlooked by diagnostic sequencing pipelines. Greater ascertainment of pathogenic splicing variants will increase diagnostic yields, ending the diagnostic odyssey for patients and families affected by rare disorders, and improving treatment and care strategies. Advances in sequencing technologies, predictive modeling, and understanding of the mechanisms of splicing in recent years pave the way for improved detection and interpretation of splice affecting variants, yet several limitations still prohibit their routine ascertainment in diagnostic testing. This review explores some of these advances in the context of clinical application and discusses challenges to be overcome before these variants are comprehensively and routinely recognized in diagnostics.

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