Long-Read Sequencing Improves the Detection of Structural Variations Impacting Complex Non-Coding Elements of the Genome

Abstract

The advent of long-read sequencing offers a new assessment method of detecting genomic structural variation (SV) in numerous rare genetic diseases. For autism spectrum disorders (ASD) cases where pathogenic variants fail to be found in the protein-coding genic regions along chromosomes, we proposed a scalable workflow to characterize the risk factor of SVs impacting non-coding elements of the genome. We applied whole-genome sequencing on an Emirati family having three children with ASD using long and short-read sequencing technology. A series of analytical pipelines were established to identify a set of SVs with high sensitivity and specificity. At 15-fold coverage, we observed that long-read sequencing technology (987 variants) detected a significantly higher number of SVs when compared to variants detected using short-read technology (509 variants) (p-value < 1.1020 × 10−57). Further comparison showed 97.9% of long-read sequencing variants were spanning within the 1–100 kb size range (p-value < 9.080 × 10−67) and impacting over 5000 genes. Moreover, long-read variants detected 604 non-coding RNAs (p-value < 9.02 × 10−9), comprising 58% microRNA, 31.9% lncRNA, and 9.1% snoRNA. Even at low coverage, long-read sequencing has shown to be a reliable technology in detecting SVs impacting complex elements of the genome.

Application and Challenge of 3rd Generation Sequencing for Clinical Bacterial Studies

“…Long-read technology also has other advantages. It improves the identification of transcription isoforms [24], the detection of structural variants [25], enables the direct detection of haplotypes and even whole chromosome phasing [26,27]. Finally, it makes it possible to sequence single molecules in real-time, avoiding DNA amplification which could be a bias inherent to second generation sequencing [28].…”

Population-based whole-genome sequencing with constrained gene analysis identifies predisposing germline variants in children with central nervous system tumors

“…Restricting inclusion of children with optic pathway gliomas to patients who received active treatment may have negatively affected the cohort prevalence of NF1 variants. SV analyses included only deletions detectable on WGS, which, while generally superior to panel or WES, identifies fewer SVs than third generation sequencing 36 .…”

Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing – Review

“…Amongst the many examples available are the fight against complex diseases such as cancer [13,30] and neuromuscular disorders (NMD), involving more than 600 genes, affecting one in every thousand persons worldwide [31], and structural variations (SV), as shown for conditions such as autism. Interestingly, some of them are related to non-coding sequences [32].…”

“…On the other hand, genome-editing technologies such as CRISPR can be combined with scRNA-seq applied to animal models and human organoids, to shed light on poorly understood diseases like autism [123]. Interestingly, non-coding sequences may be linked to some diseases [32]. As with structural genomics, organelle transcriptomics and mitochondrial disorders are also related to non-coding RNA [37].…”