Dataset Information

Characterizing glucokinase variant mechanisms using a multiplexed abundance assay.

ABSTRACT: Amino acid substitutions can perturb protein activity in multiple ways. Understanding their mechanistic basis may pinpoint how residues contribute to protein function. Here, we characterize the mechanisms of human glucokinase (GCK) variants, building on our previous comprehensive study on GCK variant activity. We assayed the abundance of 95% of GCK missense and nonsense variants, and found that 43% of hypoactive variants have a decreased cellular abundance. By combining our abundance scores with predictions of protein thermodynamic stability, we identify residues important for GCK metabolic stability and conformational dynamics. These residues could be targeted to modulate GCK activity, and thereby affect glucose homeostasis.

SUBMITTER: Gersing S

PROVIDER: S-EPMC10245906 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characterizing glucokinase variant mechanisms using a multiplexed abundance assay.

Gersing Sarah S Schulze Thea K TK Cagiada Matteo M Stein Amelie A Roth Frederick P FP Lindorff-Larsen Kresten K Hartmann-Petersen Rasmus R

bioRxiv : the preprint server for biology 20230524

Amino acid substitutions can perturb protein activity in multiple ways. Understanding their mechanistic basis may pinpoint how residues contribute to protein function. Here, we characterize the mechanisms of human glucokinase (GCK) variants, building on our previous comprehensive study on GCK variant activity. We assayed the abundance of 95% of GCK missense and nonsense variants, and found that 43% of hypoactive variants have a decreased cellular abundance. By combining our abundance scores with ...[more]

PMID: 37292969

Similar Datasets

Project description:Although genetic studies have identified many hundreds of loci associated with human traits and diseases, pinpointing the causal alleles remains difficult, particularly for non-coding variants. To address this challenge, we have enhanced the sensitivity and reproducibility of the massively parallel reporter assay (MPRA), adapting it to identify variants that directly modulate gene expression. We then applied it to over 29,000 single nucleotide and insertion/deletion polymorphisms from 3,965 cis-expression quantitative trait loci (eQTL). We demonstrate strong correlation between our MPRA approach and existing measures of regulatory function, and determine an approximate sensitivity of ~20% with a positive predictive value of 60-65% to detect an eQTL causal allele. We identify 842 variants showing differential expression between alleles, including 53 well-annotated variants associated with diseases and traits. Thus, we have created a resource of concrete leads for understanding the genetic basis of specific phenotypes and illustrate the promise of this kind of approach for comprehensively interrogating how non-coding polymorphism shapes human biology. The study consists of two separate MPRA experiments, a 78,958 oligo (79k study) and a 7,500 oligo library (7.5k). For each library we processed independent transfections into two lymphoblastoid cell lines; in total we completed 5 replicates of NA12878 and 3 replicates of NA19239. For the 79k library we also performed 5 replicate transfections into the hepatocarcinoma cell line HepG2. Raw data is provided as Illumina reads of the 20 bp barcode from the RNA extracted 24 hours post transfection as well as from the plasmid library used for transfection. We also provide oligo/barcode combinations from the âgfp vector in the form of a tab delimited file containing the raw sequence reads of the barcode (column 1) and genomic sequence (column 2). Processed count files are unnormalized counts for each oligo acquired by summing all barcode matches together for each replicate.

Dataset Information

Characterizing glucokinase variant mechanisms using a multiplexed abundance assay.

Publications

Characterizing glucokinase variant mechanisms using a multiplexed abundance assay.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets