ArticleBMC medical genomics2025
Long read whole genome sequencing-based discovery of structural variants and their role in aetiology of non-syndromic autism spectrum disorder in India.
Article in BMC medical genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Long-Read sequencing in psychiatric omics: a systematic review of current evidence.Molecular psychiatry · 2026Pooled it
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Authors and funding
13 authors.
Funding
Abstract
backgroundDespite having heritability estimates of 80%, ~ 50% cases of autism spectrum disorders (ASD) remain without a genetic diagnosis. Structural variants (SVs) detected using long-read whole genome sequencing (lrWGS) are a relatively new class of variants implicated in neurodevelopmental disorders. Short read sequencing (SRS) and chromosomal microarray (CMA) are unable to resolve these SVs due to their inherent technological limitations. This study was aimed to detect and delineate the role of SVs in children with non-syndromic ASDs using lrWGS in whom prior traditional genetic tests did not yield a definitive genetic diagnosis.
methodsA total of 23 patients with no prior genetic diagnosis from karyotyping, Fragile-X analysis, CMA and short read whole exome sequencing (srWES) were selected for lrWGS using Oxford Nanopore based sequencing platform. Samples were sequenced at an average coverage of ~ 7x. Contigs generated from high accuracy base calling were aligned against GRCh38/hg38 human reference genome build. SVs were called using five variant callers- Sniffles2, cuteSV, NanoVar, SVIM, and npInv, and annotated using AnnotSV. Calls from cuteSV were used as benchmark to identify concordant calls across at least three variant callers.
resultsAn average whole genome coverage of ~ 7x and N50 read length of 6.65 ± 3.3 kb was obtained across 46 runs (two runs/ sample). On average, a total of approximately 235,163 calls were made across all callers for each sample. The average number of deletions, duplications, insertions, inversions and translocations were 54,787, 3,335, 62,459, 1,286, and 113,296, respectively, were detected across all callers per sample. Of 23 cases, a candidate SV, an inversion of approximately 2.7 Mb in size encompassing SNAP25-AS1 gene was observed. This gene is likely to be involved in the synaptic pathway and has previously been associated with autism.
conclusionThis is the first study from India to assess the role of SVs in the aetiology of non-syndromic ASDs. Despite the small sample size, low-pass genome coverage, and modest N50 read length, the study indicates a modest contribution of SVs in the aetiology of non-syndromic ASD. Dearth of data supporting the role of SVs in non-syndromic ASDs in other cohorts from around the world further supports our conclusion.
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