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- Johansson, Josefin, et al.
(författare)
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A novel quantitative targeted analysis of X-chromosome Inactivation (XCI) using Nanopore sequencing
- 2023
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- X-chromosome inactivation (XCI) analyses often assist in diagnostics of X-linked traits, however accurate assessment remains challenging with current methods. We developed a novel strategy using amplification-free Cas9 enrichment and Oxford nanopore technologies sequencing called XCI-ONT, to investigate and rigorously quantify XCI in human androgen receptor gene (AR) and human X-linked retinitis pigmentosa 2 gene (RP2). XCI-ONT measures methylation over 116 CpGs in AR and 58 CpGs in RP2, and separate parental X-chromosomes without PCR bias. We show the usefulness of the XCI-ONT strategy over the PCR-based golden standard XCI technique that only investigates one or two CpGs per gene. The results highlight the limitations of using the golden standard technique when the XCI pattern is partially skewed and the advantages of XCI-ONT to rigorously quantify XCI. This study provides a universal XCI-method on DNA, which is highly valuable in clinical and research framework of X-linked traits.
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| 2. |
- Singer-Berk, Moriel, et al.
(författare)
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Advanced variant classification framework reduces the false positive rate of predicted loss-of-function variants in population sequencing data
- 2023
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 110:9, s. 1496-1508
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Tidskriftsartikel (refereegranskat)abstract
- Predicted loss of function (pLoF) variants are often highly deleterious and play an important role in disease biology, but many pLoF variants may not result in loss of function (LoF). Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines’ PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 genes associated with autosomal-recessive disease from the Genome Aggregation Database (gnomAD v.2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in a low proportion expressed across transcripts (pext) scored region, or the presence of cryptic in-frame splice rescues. Variants predicted to evade LoF or to be potential artifacts were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of pLoF variants predicted as likely not LoF/not LoF, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.
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