Compendium of proteins containing segments that exhibit zero‐tolerance to amino acid variation in humans. (18th August 2022)

• Record Type: Journal Article
• Authors: Sanders, Adam L.; Hermanson, Jake N.; Samuels, David C.; Plate, Lars; Sanders, Charles R.
• Is Part Of: Protein science. Volume 31:Number 9(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-18
• Subjects: database -- gene -- genetic -- genome -- intolerance -- intolerant -- missense tolerance ratio -- protein -- proteome; Proteins -- Periodicals; 572.6
• DOI: 10.1002/pro.4408
• Languages: English
• ISSNs: 0961-8368

Abstract

Abstract: Genetic missense tolerance ratio (MTR) analysis systematically evaluates all possible segments in a given protein‐encoding transcript found in the human population. This method scores each segment for the number of observed missense variants versus the number of silent mutations in that same segment. An MTR score of 0 indicates that no missense mutations are observed within a given segment. This is indicative of evolutionary purifying selection, which excludes mutations in that segment from the general human population. Here, we conducted MTR analysis on each of the roughly 20, 000 protein‐encoding human genes. It was seen that there are 257 genes with at least one 31‐residue encoding segment with MTR = 0 (1.3% of all human genes). The proteins encoded by these 257 genes were tabulated along with information regarding the sequence location of each intolerant segment, the likely function of the protein, and so forth. The most functionally‐enriched family among these proteins is a collection of several dozen proteins that are directly involved in RNA splicing. Some of the other proteins with zero‐tolerance segments have thus far escaped significant characterization. Indeed, while a number of these proteins have previously been genetically linked to human disorders, many have not. We hypothesize that this compendium of human proteins with zero‐tolerance segments can be used to complement disease mutation data as a pointer to genes and proteins that are associated with interesting and underexplored human biology.