Related Experiment Video
Updated: Jan 1, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Identification of pathogenic variant enriched regions across genes and gene families
Eduardo Pérez-Palma1,2, Patrick May3, Sumaiya Iqbal4,5
1Cologne Center for Genomics, University of Cologne, Cologne, 50931 NRW, Germany.
Abstract:
Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene-family members, and genetic variants within these regions are potentially more likely to confer risk to disease. Here, we generated 2871 gene-family protein sequence alignments involving 9990 genes and performed missense variant burden analyses to identify novel essential protein regions. We mapped 2,219,811 variants from the general population into these alignments and compared their distribution with 76,153 missense variants from patients. With this gene-family approach, we identified 465 regions enriched for patient variants spanning 41,463 amino acids in 1252 genes. As a comparison, by testing the same genes individually, we identified fewer patient variant enriched regions, involving only 2639 amino acids and 215 genes. Next, we selected de novo variants from 6753 patients with neurodevelopmental disorders and 1911 unaffected siblings and observed an 8.33-fold enrichment of patient variants in our identified regions (95% C.I. = 3.90-Inf, P-value = 2.72 × 10-11). By using the complete ClinVar variant set, we found that missense variants inside the identified regions are 106-fold more likely to be classified as pathogenic in comparison to benign classification (OR = 106.15, 95% C.I = 70.66-Inf, P-value < 2.2 × 10-16). All pathogenic variant enriched regions (PERs) identified are available online through "PER viewer," a user-friendly online platform for interactive data mining, visualization, and download. In summary, our gene-family burden analysis approach identified novel PERs in protein sequences. This annotation can empower variant interpretation.
More Related Videos
11:35Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
Published on: August 21, 2016
06:41In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
Published on: August 20, 2019
Related Concept Videos
Evolutionary Relationships through Genome Comparisons
Genome-wide Association Studies-GWAS
GWAS does not require the identification of the target gene involved in...
Comparing Copy Number Variations and SNPs
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Gene Evolution - Fast or Slow?
In contrast, regions which code...
Gene Families
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
Gene Families