Biology subjects

Aslanzadeh, V.

Publications and source records attributed to Aslanzadeh, V..

5 recordsLinked to original sources

bioRxiv2026

Mechanism-selective deep mutational scanning distinguishes ERCC2 disease phenotypes

Pathogenic ERCC2 variants cause xeroderma pigmentosum (XP), trichothiodystrophy (TTD) or both, yet variant effect scores are usually interpreted only as measures of pathogenicity rather than of which disease mechanism is disrupted. XPD, the ERCC2-encoded TFIIH subunit, functions in both nucleotide excision repair and transcription. Using yeast complementation deep mutational scanning, we measured the effects of nearly all XPD amino acid substitutions. The assay was mechanism-selective: it preferentially reported transcription-associated function, with pronounced intolerance at the p44 interface, whereas many substitutions affecting DNA binding and helicase activity retained near-wild-type fitness. Accordingly, TTD variants had much lower fitness than XP variants. Computational predictors discriminated pathogenic from benign variants similarly across phenotypes, but the DMS distinguished XP from TTD variants better than all 73 predictors tested. Phenotype-specific ACMG/AMP calibration provided evidence in both directions for TTD but mainly pathogenic evidence for XP. Thus, the selectivity of functional assays, often viewed as a limitation, can reveal disease mechanisms and support phenotype-aware variant interpretation.

genetics↗

bioRxiv2026

A Functional Genetic Atlas of Parkin Resolves Variants of Uncertain Significance and Predicts Parkinson's Disease Age at Onset

Autosomal recessive mutations in the Parkin gene (PRKN) cause early-onset Parkinsons disease (PD). Parkin functions as a ubiquitin E3 ligase acting downstream of the PINK1 kinase to promote phosphorylated ubiquitin at sites of mitochondrial damage. Yet the functional effects of most PRKN gene variants remain unknown. Here we use a pooled cellular assay measuring phosphorylated ubiquitin accumulation to quantify the activity of [~]9,200 PRKN missense and nonsense variants. Our screen identifies thousands of loss- and gain-of-function variants, including activating variants mainly residing at autoinhibitory interfaces. Functional scores accurately distinguish known PD pathogenic and benign variants, and enable reclassification of 173/184 variants of uncertain significance (VUS). When combined into biallelic genotype scores, these data predict the age at disease onset in patients, revealing a quantitative link between Parkin activity and clinical manifestation. Our results provide a comprehensive functional genetic map of Parkin and demonstrate the power of multiplexed assays of variant effects (MAVEs) for variant interpretation and precision medicine in PD.

genetics↗

bioRxiv2025

Mechanistic Modelling of Recessive Disease through Allelic Integration of Variant Effects

Interpreting the effects of genetic variants remains a major challenge in recessive diseases, where clinical outcomes often depend on interactions between alleles. Multiplex assays of variant effects (MAVEs) measure variant function at scale, but nonlinear relationships with biochemical activity complicate the interpretation of MAVE scores. Here, we describe a broadly applicable approach to estimate enzymatic activities for thousands of genetic variants using a pair of fitness assays conducted at different expression levels, by modelling the nonlinear relationship between activity and fitness. Activity scores from two alleles are then combined into a single pathogenicity metric that captures their joint effect. We applied this approach to adenylosuccinate lyase (ADSL), a purine biosynthesis enzyme mutated in the autosomal recessive disorder ADSL deficiency. Using a yeast-based MAVE, we quantified the functional impact of over 8,000 coding variants. Our framework distinguished pathogenic from benign alleles based on estimated activity, and the integrated pathogenicity score correlated strongly with biochemical measurements from patient-derived cells, outperforming existing computational predictors. This dual innovation--the mechanistic transformation of MAVE data and allelic integration--offers a generalizable strategy for probing enzyme function and interpreting genetic variation in recessive disorders.

genetics↗

bioRxiv2024

Deep mutational scanning of the human insulin receptor ectodomain to inform precision therapy for insulin resistance

The insulin receptor (INSR) entrains tissue growth and metabolism to nutritional conditions. Complete loss of function in humans leads to extreme insulin resistance and infantile mortality, while loss of 80-90% function permits longevity of decades. Even low-level activation of severely compromised receptors, for example by anti-receptor monoclonal antibodies, thus offers the potential for decisive clinical benefit. A barrier to genetic diagnosis and translational research is the increasing identification of INSR variants of uncertain significance. We employed saturation mutagenesis coupled to multidimensional flow-based assays to stratify approximately 14,000 INSR extracellular domain missense variants by cell surface expression, insulin binding, and insulin- or monoclonal antibody-stimulated signaling. The resulting function scores correlate strongly with clinical syndromes, offer insights into dynamics of insulin binding, and reveal novel potential gain-of-function variants. This INSR sequence-function map has high biochemical, diagnostic and translational utility, aiding rapid identification of variants amenable to activation by non-canonical INSR agonists.

genetics↗

bioRxiv2018

Revisiting the window of opportunity for co-transcriptional splicing efficiency and fidelity

Recently, we reported that changes in transcription elongation rate affect the efficiency and fidelity of precursor mRNA (pre-mRNA) splicing, especially of ribosomal protein (RP) transcripts. Here, we analyse these results in more detail, finding that the majority of RP transcripts with non-consensus 5 splice sites have reduced splicing efficiency with faster transcription elongation, and improved efficiency with slower elongation, as might be predicted by the \"window of opportunity\" model for co-transcriptional splicing. In contrast, both faster and slower elongation reduce splicing fidelity, often for the same splicing events, and both faster and slower transcription increase fidelity with a different set of splicing events. We propose that certain non-consensus 5 splice sites in ribosomal protein transcripts confer a stronger effect of transcription elongation rate on splicing efficiency, possibly by causing a rate-limiting step that delays activation of spliceosomes. The effects of different rates of transcription elongation on splicing fidelity are more difficult to explain by a simple window of opportunity model. We discuss these new findings in the context of current models of co-transcriptional splicing and splicing fidelity.

molecular biology↗