Purpose: We investigated the value of transcriptome sequencing (RNAseq) in ascertaining the consequence of DNA variants on RNA transcripts to improve the diagnostic rate from exome or genome sequencing for undiagnosed Mendelian diseases spanning a wide spectrum of clinical indications.Methods: From 234 subjects referred to the Undiagnosed Diseases Network, University of California-Los Angeles clinical site between July 2014 and August 2018, 113 were enrolled for high likelihood of having rare undiagnosed, suspected genetic conditions despite thorough prior clinical evaluation. Exome or genome sequencing and RNAseq were performed, and RNAseq data was integrated with genome sequencing data for DNA variant interpretation genome-wide. Results:The molecular diagnostic rate by exome or genome sequencing was 31%. Integration of RNAseq with genome sequencing resulted in an additional seven cases with clear diagnosis of a known genetic disease. Thus, the overall molecular diagnostic rate was 38%, and 18% of all genetic diagnoses returned required RNAseq to determine variant causality. Conclusion:In this rare disease cohort with a wide spectrum of undiagnosed, suspected genetic conditions, RNAseq analysis increased the molecular diagnostic rate above that possible with genome sequencing analysis alone even without availability of the most appropriate tissue type to assess.
(8,12). During continued culture over many generations in FR light, we observed increases in growth rate and in the Chl/PC ratio, usually occurring in a concomitant and stepwise fashion. From such cultures, we were able to establish clones which differed from the parent in pigment composition. We have described six clones, which are presumed to be spontaneous mutants selected under the photosynthetically restrictive condition of FR illumination (13). As compared to the parent, all mutants showed better performance (growth) under FR light for which Chl is the principal absorber but poorer perform-
Antisense oligonucleotide (AON)‐mediated exon skipping is an emerging therapeutic for individuals with Duchenne muscular dystrophy (DMD). Skipping of exons adjacent to common exon deletions in DMD using AONs can produce in‐frame transcripts and functional protein. Targeted skipping of DMD exons 8, 44, 45, 50, 51, 52, 53, and 55 is predicted to benefit 47% of affected individuals. We observed a correlation between mutation subgroups and age at loss of ambulation in the Duchenne Registry, a large database of phenotypic and genetic data for DMD (N = 765). Males amenable to exon 44 (N = 74) and exon 8 skipping (N = 18) showed prolonged ambulation compared to other exon skip groups and nonsense mutations (P = 0.035 and P < 0.01, respectively). In particular, exon 45 deletions were associated with prolonged age at loss of ambulation relative to the rest of the exon 44 skip amenable cohort and other DMD mutations. Exon 3–7 deletions also showed prolonged ambulation relative to all other exon 8 skippable mutations. Cultured myotubes from DMD patients with deletions of exons 3–7 or exon 45 showed higher endogenous skipping than other mutations, providing a potential biological rationale for our observations. These results highlight the utility of aggregating phenotypic and genotypic data for rare pediatric diseases to reveal progression differences, identify potentially confounding factors, and probe molecular mechanisms that may affect disease severity.
BackgroundMassively parallel DNA sequencing, such as exome sequencing, has become a routine clinical procedure to identify pathogenic variants responsible for a patient’s phenotype. Exome sequencing has the capability of reliably identifying inherited and de novo single-nucleotide variants, small insertions, and deletions. However, due to the use of 100–300-bp fragment reads, this platform is not well powered to sensitively identify moderate to large structural variants (SV), such as insertions, deletions, inversions, and translocations.MethodsTo overcome these limitations, we used next-generation mapping (NGM) to image high molecular weight double-stranded DNA molecules (megabase size) with fluorescent tags in nanochannel arrays for de novo genome assembly. We investigated the capacity of this NGM platform to identify pathogenic SV in a series of patients diagnosed with Duchenne muscular dystrophy (DMD), due to large deletions, insertion, and inversion involving the DMD gene.ResultsWe identified deletion, duplication, and inversion breakpoints within DMD. The sizes of deletions were in the range of 45–250 Kbp, whereas the one identified insertion was approximately 13 Kbp in size. This method refined the location of the break points within introns for cases with deletions compared to current polymerase chain reaction (PCR)-based clinical techniques. Heterozygous SV were detected in the known carrier mothers of the DMD patients, demonstrating the ability of the method to ascertain carrier status for large SV. The method was also able to identify a 5.1-Mbp inversion involving the DMD gene, previously identified by RNA sequencing.ConclusionsWe showed the ability of NGM technology to detect pathogenic structural variants otherwise missed by PCR-based techniques or chromosomal microarrays. NGM is poised to become a new tool in the clinical genetic diagnostic strategy and research due to its ability to sensitively identify large genomic variations.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-017-0479-0) contains supplementary material, which is available to authorized users.
Using radiation hybrid genotyping data, 99% of all possible gene pairs across the mammalian genome were tested for interactions based on co-retention frequencies higher (attraction) or lower (repulsion) than chance. Gene interaction networks constructed from six independent data sets overlapped strongly. Combining the data sets resulted in a network of more than seven million interactions, almost all attractive. This network overlapped with protein-protein interaction networks on multiple measures and also confirmed the relationship between essentiality and centrality. In contrast to other biological networks, the radiation hybrid network did not show a scale-free distribution of connectivity but was Gaussian-like, suggesting a closer approach to saturation. The radiation hybrid (RH) network constitutes a platform for understanding the systems biology of the mammalian cell.
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