Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Systematic characterization of indel variants using a yeast-based protein folding sensor

ABSTRACT: Gene variants resulting in insertions or deletions of amino acid residues (indels) have important consequences for evolution and are often linked to disease, yet compared to missense variants the effects of indels are poorly understood and ineptly predicted. To approach this issue, we developed a sensitive protein folding sensor based on complementation of uracil auxotrophy in yeast by circular permutated orotate phosphoribosyltransferase (CPOP). The sensor accurately reports on the folding of disease-linked missense variants and artificially designed proteins. Applying the folding sensor to a saturated library of single amino acid indel variants in human DHFR revealed that most regions which tolerate indels are confined to internal loops and the N- and C-termini. Surprisingly, indels are also allowed at a central α-helix. Several indels are temperature-sensitive and the folding of most indels is rescued upon binding to the competitive DHFR inhibitor methotrexate. Predictions using Rosetta and AlphaFold2 correlate with the observed effects, suggesting that most indels operate by destabilizing the native fold and that these computational tools may be useful for classification of indels observed in population sequencing.

ORGANISM(S): synthetic construct

PROVIDER: GSE270811 | GEO | 2024/07/25

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Deep indel mutagenesis reveals the impact of insertions and deletions on protein stability and function

Project description:Amino acid insertions and deletions (indels) are an abundant class of genetic variants. However, compared to substitutions, the effects of indels are not well understood and poorly predicted. Here we address this shortcoming by performing deep indel mutagenesis (DIM) of structurally diverse proteins. Indel tolerance is strikingly different to substitution tolerance and varies extensively both between different proteins and within different regions of the same protein. Although state of the art variant effect predictors perform poorly on indels, we show that both experimentally-measured and computationally-predicted substitution scores can be repurposed as good indel variant effect predictors by incorporating information on protein secondary structures. Quantifying the effects of indels on protein-protein interactions reveals that insertions can be an important class of gain-of-function variants. Our results provide an overview of the impact of indels on proteins and a method to predict their effects genome-wide.

2023-09-28 | GSE244096 | GEO

Systematic characterization of indel variants using a yeast-based protein folding sensor

Project description:Systematic characterization of indel variants using a yeast-based protein folding sensor

| PRJNA1128549 | ENA

Peptide mass fingerprinting to investigate if histidine was incorporated as residue 136 in DHFR variants

Project description:SDS-PAGE gel bands of DHFR variants (produced using modified versions of the PURE express in vitro protein synthesis system) were analyzed via peptide mass fingerprinting (PMF). The goal was to detect which amino acids were incorporated at position 136 in DHFR.

2024-10-29 | PXD051338 | Pride

CAO indel evolution

Project description:Evolution of indels in a MTBC lineage 2 MDR-outbreak

| PRJEB36040 | ENA

On/Off targets INDEL analysis by Next Generation Sequencing

Project description:SpCas9 INDEL frequency was evaluated at both the on- and off-target sites of guideRNA targeting either the murine Rhodopsin or Albumin by Next Generation Sequencing. Minimal INDELs were found at the off target sites evaluted, while SpCas9 activity was predominantly on-target.

2021-11-11 | GSE180117 | GEO

Genome-wide binding of wild-type and missense mutant p53 in isogenic human acute myeloid leukemia (AML) cell lines

Project description:TP53, encoding for the tumor suppressor p53, is the most frequently mutated gene in human cancer. The selective pressures shaping its mutational spectrum, dominated by missense mutations, have remained enigmatic, and neomorphic gain-of-function (GOF) activities have been implicated. We generated isogenic human leukemia cell lines of the most common TP53 missense mutations using CRISPR/Cas9. Functional, DNA binding, and transcriptional analyses revealed loss-of-function (LOF) without GOF effects of missense mutations. Comprehensive mutational scanning of p53 single amino acid variants demonstrated that DNA-binding domain missense variants exert dominant-negative effects (DNE). In mice, DNE of p53 missense variants confer a selective advantage on hematopoietic cells upon DNA damage in vivo. Clinical outcomes in acute myeloid leukemia patients showed no evidence of GOF for TP53 missense mutations. These findings establish dominant-negativity as the primary unit of selection for TP53 missense mutations in myeloid malignancies.

2019-08-30 | GSE131484 | GEO

Transcriptional consequences of wild-type and missense mutant p53 in isogenic human acute myeloid leukemia (AML) cell lines

2019-08-30 | GSE131592 | GEO

Assessment of Variant Abundance by Massively Parallel Sequencing for PTEN and TPMT

Project description:Determining the pathogenicity of human genetic variants is a critical challenge, and functional assessment is often the only option. Experimentally characterizing millions of possible missense variants in thousands of clinically important genes will likely require generalizable, scalable assays. Here we describe Variant Abundance by Massively Parallel Sequencing (VAMP-seq), which measures the effects of thousands of missense variants of a protein on intracellular abundance in a single experiment. We applied VAMP-seq to quantify the abundance of many thousands of single amino acid variants of two proteins, PTEN and TPMT, in which functional variants are clinically actionable.

2018-03-13 | GSE108727 | GEO

DNA Repair Function Scores for 2172 Variants in the BRCA1 Amino-Terminus

Project description:Single nucleotide variants are the most frequent type of sequence changes detected in the genome and these are frequently variants of uncertain significance (VUS). VUS are changes in DNA for which disease risk association is unknown. Thus, methods that classify the functional impact of a VUS can be used as evidence for variant interpretation. In the case of the breast and ovarian cancer specific tumor suppressor protein, BRCA1, pathogenic missense variants frequently score as loss of function in an assay for homology-directed repair (HDR) of DNA double-strand breaks. We previously published functional results using a multiplexed assay for 1056 amino acid substitutions residues 2-192 in the amino terminus of BRCA1. In this study, we have re-assessed the data from this multiplexed assay using an improved analysis pipeline. These new analysis methods yield functional scores for more variants in the first 192 amino acids of BRCA1, plus we report new results for BRCA1 amino acid residues 193-302. We now present the functional classification of 2172 BRCA1 variants in BRCA1 residues 2-302 using the multiplexed HDR assay. Comparison of the functional determinations of the missense variants with clinically known benign or pathogenic variants indicated 93% sensitivity and 100% specificity for this assay. The results from BRCA1 variants tested in this assay are a resource for clinical geneticists for evidence to evaluate VUS in BRCA1.

2023-06-12 | GSE234482 | GEO

Site saturation mutagenesis of 500 human protein domains

Project description:Missense variants that change the amino acid sequences of proteins cause one third of human genetic diseases. Tens of millions of missense variants exist in the current human population, with the vast majority having unknown functional consequences. Here we present the first large-scale experimental analysis of human missense variants. Using DNA synthesis and cellular selection experiments we quantify the impact of >500,000 variants on the abundance of >500 human protein domains. This dataset, Domainome 1.0, reveals that >60% of disease-causing variants destabilize proteins. The contribution of stability to protein fitness varies across proteins and diseases, and is particularly important in recessive disorders. Combining experimental stability measurements with large language models we annotate functionally important sites across domains. Fitting energy models to the data demonstrates the conservation of mutation effects in homologous domains and allows stability to be accurately predicted for entire domain families. Domainome 1.0 demonstrates the feasibility of assaying human protein variant effects at scale and provides a large consistent reference dataset for clinical variant interpretation and the training and benchmarking of computational methods.

2024-04-27 | GSE265942 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data