| Literature DB >> 34785703 |
Albina Nowak1,2, Omer Murik3, Tzvia Mann3, David A Zeevi3, Gheona Altarescu4.
Abstract
More than 900 variants have been described in the GLA gene. Some intronic variants and copy number variants in GLA can cause Fabry disease but will not be detected by classical Sanger sequence. We aimed to design and validate a method for sequencing the GLA gene using long-read Oxford Nanopore sequencing technology. Twelve Fabry patients were blindly analyzed, both by conventional Sanger sequence and by long-read sequencing of a 13 kb PCR amplicon. We used minimap2 to align the long-read data and Nanopolish and Sniffles to call variants. All the variants detected by Sanger (including a deep intronic variant) were also detected by long-read sequencing. One patient had a deletion that was not detected by Sanger sequencing but was detected by the new technology. Our long-read sequencing-based method was able to detect missense variants and an exonic deletion, with the added advantage of intronic analysis. It can be used as an efficient and cost-effective tool for screening and diagnosing Fabry disease.Entities:
Mesh:
Substances:
Year: 2021 PMID: 34785703 PMCID: PMC8595663 DOI: 10.1038/s41598-021-01749-7
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Clinical presentation of the cohort of Fabry patients.
| Sample | Therapy | Acrop | Hypo | Angio | Cornea | Nephro | Cardio | Stroke | Phenotype | Note |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Agalsidase α | + | Classic | |||||||
| 2 | Agalsidase β | + | + | + | + | Classic | ||||
| 3 | Agalsidase β | + | + | + | + | Classic | ||||
| 4 | Agalsidase β | + | + | + | + | Classic | ||||
| 5 | Agalsidase β | + | + | + | + | + | + | Classic | ||
| 6 | No therapy | Benign | ||||||||
| 7 | Agalsidase α | + | + | + | + | + | Classic | Brother of 8 | ||
| 8 | Agalsidase α | + | + | + | + | + | + | + | Classic | Brother of 7 |
| 9 | Agalsidase α | + | + | + | + | + | Classic | |||
| 10 | Agalsidase β | + | Late-onset | |||||||
| 11 | Agalsidase α | + | + | + | + | + | + | Classic | ||
| 12 | Agalsidase α | + | + | + | + | + | + | Classic |
Acrop acroparesthesia, Hypo hypohidriosis, Angio angioceratoma, Cornea cornea verticillata, Nephro nephropathy, Cardio cardiomyopathy, Stroke history of stroke.
Genotyping results based on ONT amplicon sequencing, and predicted consequence of the genetic variant on GLA.
| ONT barcode | GLA protein variant (accession: NP_000160) | Comments (source of variant annotation)† | |
|---|---|---|---|
| 1 | c.547 + 404T>G | N/A-deep intronic | Deep intronic variant; possible branch site; may affect splicing; SpliceAI score 0.55 |
| 2 | c.1147_1149delTTC | p.Phe383del | Pathogenic (Clinvar, VarSome); Phenotype: classic (dbFGP) |
| 3 | c.744_745delTA* | p.Phe248LeufsX7 | Likely-pathogenic (VarSome); same haplotype as barcode05 suggests blood relationship; Phenotype: classic (dbFGP) |
| 4 | c.559_560delAT | p.Met187Valfs*6 | Pathogenic (Clinvar, VarSome) |
| 5 | c.744_745delTA* | p.Phe248LeufsX7 | Likely-pathogenic (VarSome); same haplotype as barcode03 suggests blood relationship; Phenotype: classic (dbFGP) |
| 6 | c.352C>T | p.Arg118Cys | Conflicting_interpretations_of_pathogenicity (ClinVar) ; Phenotype: Benign (dbFGP) |
| 7 | c.370-2A>G* | N/A- splicing | Pathogenic (Clinvar, VarSome); same haplotype as barcode08 suggests blood relationship; Phenotype: classic (dbFGP) |
| 8 | c.370-2A>G* | N/A- splicing | Pathogenic (Clinvar, VarSome); same haplotype as barcode07 suggests blood relationship; Phenotype: classic (dbFGP) |
| 9 | c.704C > A | p.Ser235Tyr | Pathogenic (VarSome); Phenotype: classic (dbFGP) |
| 10 | c.337T>C | p. Phe113Leu | Pathogenic (Clinvar, VarSome); Phenotype: late- onset (dbFGP) |
| 11 | Exon 2 deletion | N/A | pathogenic; 2914 bp deletion removes |
| 12 | c.581C>T | p.Thr194Ile | Likely-pathogenic (VarSome) ; Phenotype: Likely-classic (dbFGP) |
*Two samples from the same family were tested, N/A not applicable.
†Source material is from the following databases: ClinVar[29]; Varsome[30]; dbFGP[35].
Figure 1Downsampling the sequencing data of the 12 samples to 10–10,000 reads per sample. For each downsampled library the rate of variants detected from the full dataset variant list was calculated.