Synonymous mutations reveal genome-wide levels of positive selection in healthy tissues | Nature Genetics
Genetic alterations under positive selection in healthy tissues have implications for cancer risk. However, total levels of positive selection across the genome remain unknown. Passenger mutations are influenced by all driver mutations, regardless of type or location in the genome. Therefore, the total number of passengers can be used to estimate the total number of drivers—including unidentified drivers outside of cancer genes that are traditionally missed. Here researchers analyze the variant allele frequency spectrum of synonymous mutations from healthy blood and esophagus to quantify levels of missing positive selection.
spatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data | Bioinformatics
Multiplex immunofluorescence (mIF) staining combined with quantitative digital image analysis is a novel and increasingly used technique that allows for the characterization of the tumor immune microenvironment (TIME). Researchers developed an R package spatialTIME that enables spatial analysis of mIF data, as well as the iTIME web application that provides a robust but simplified user interface for describing both abundance and spatial architecture of the TIME.
Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus | Nature Genetics
The severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) disease (COVID-19) pandemic has caused millions of deaths worldwide. Genome-wide association studies identified the 3p21.31 region as conferring a twofold increased risk of respiratory failure. Here, using a combined multiomics and machine learning approach, researchers identify the gain-of-function risk A allele of an SNP, rs17713054G>A, as a probable causative variant.