<scp>RNA</scp>
            seq analysis for the diagnosis of muscular dystrophy

Gonorazky, Hernan; Liang, Minggao; Cummings, Beryl B.; Lek, Monkol; Micallef, Johann; Hawkins, Cynthia; Basran, Raveen K.; Cohn, Ronald D.; Wilson, Michael D.; MacArthur, Daniel G.; Marshall, Christian R.; Ray, Peter N.; Dowling, James J.

doi:10.1002/acn3.267

Cited by 79 publications

(67 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Only small regions (20 bp) of introns adjacent to the exons were detected. A patient who receives a definite diagnosis by means of muscle biopsy and immunopathology, but no causative mutation can be detected using the present strategy should further undergo WGS or RNA sequence‐based transcriptome analyses …”

Section: Discussionmentioning

confidence: 99%

Genetic analysis of the dystrophin gene in children with Duchenne and Becker muscular dystrophies

Zhong

Chen

et al. 2017

Muscle and Nerve

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 99%

Genetic analysis of the dystrophin gene in children with Duchenne and Becker muscular dystrophies

Zhong

Chen

et al. 2017

Muscle and Nerve

View full text Add to dashboard Cite

show abstract

“…Furthermore, novel rare variant burden tests have demonstrated the dramatic enrichment of rare variants in the promoters of genes with outlier gene expression [75]. By using these outlier methods to identify rare regulatory variants and the growing number of reference transcriptomes being made available, it is increasingly possible to identify rare non-coding variants that cause rare Mendelian diseases [76,77]. …”

Section: From Exome To Genome Interpretationmentioning

confidence: 99%

Non-Coding Loss-of-Function Variation in Human Genomes

Zappala¹,

Montgomery²

2016

Hum Hered

View full text Add to dashboard Cite

Whole-genome and exome sequencing in human populations has revealed the tolerance of each gene for loss-of-function variation. By understanding this tolerance, it has become increasingly possible to identify genes that would make safe therapeutic targets and to identify rare genetic risk factors and phenotypes at the scale of individual genomes. To date, the vast majority of surveyed loss-of-function variants are in protein-coding regions of the genome mainly due to the focus on these regions by exome-based sequencing projects and their relative ease of interpretability. As whole-genome sequencing becomes more prevalent, new strategies will be required to uncover impactful variation in non-coding regions of the genome where the architecture of genome function is more complex. In this review, we investigate recent studies of loss-of-function variation and emerging approaches for interpreting whole-genome sequencing data to identify rare and impactful non-coding loss-of-function variants.

show abstract

“…Analysis of the complementary DNA (cDNA) of single genes has proven useful on a case-by-case basis to provide diagnoses to patients with Mendelian disorders (10–13), and RNA-seq has previously been used to observe the effect of pathogenic variants, which were identified through DNA sequencing (14, 15). However, the use of transcriptome sequencing has not yet been assessed for the discovery of pathogenic variants in a cohort of Mendelian disease patients.…”

Section: Introductionmentioning

confidence: 99%

Improving genetic diagnosis in Mendelian disease with transcriptome sequencing

et al. 2017

Self Cite

View full text Add to dashboard Cite

Exome and whole-genome sequencing are becoming increasingly routine approaches in Mendelian disease diagnosis. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25 to 50%. We explore the utility of transcriptome sequencing [RNA sequencing (RNA-seq)] as a complementary diagnostic tool in a cohort of 50 patients with genetically undiagnosed rare muscle disorders. We describe an integrated approach to analyze patient muscle RNA-seq, leveraging an analysis framework focused on the detection of transcript-level changes that are unique to the patient compared to more than 180 control skeletal muscle samples. We demonstrate the power of RNA-seq to validate candidate splice-disrupting mutations and to identify splice-altering variants in both exonic and deep intronic regions, yielding an overall diagnosis rate of 35%. We also report the discovery of a highly recurrent de novo intronic mutation in COL6A1 that results in a dominantly acting splice-gain event, disrupting the critical glycine repeat motif of the triple helical domain. We identify this pathogenic variant in a total of 27 genetically unsolved patients in an external collagen VI–like dystrophy cohort, thus explaining approximately 25% of patients clinically suggestive of having collagen VI dystrophy in whom prior genetic analysis is negative. Overall, this study represents a large systematic application of transcriptome sequencing to rare disease diagnosis and highlights its utility for the detection and interpretation of variants missed by current standard diagnostic approaches.

show abstract

RNA seq analysis for the diagnosis of muscular dystrophy

Cited by 79 publications

References 21 publications

Genetic analysis of the dystrophin gene in children with Duchenne and Becker muscular dystrophies

Genetic analysis of the dystrophin gene in children with Duchenne and Becker muscular dystrophies

Non-Coding Loss-of-Function Variation in Human Genomes

Improving genetic diagnosis in Mendelian disease with transcriptome sequencing

Contact Info

Product

Resources

About