Evolution-based screening enables genome-wide prioritization and discovery of DNA repair genes

Abstract

DNA repair is critical for genome stability and is maintained through conserved pathways. Traditional genome-wide mammalian screens are both expensive and laborious. However, computational approaches circumvent these limitations and are a powerful tool to identify new DNA repair factors. By analyzing the evolutionary relationships between genes in the major DNA repair pathways, we uncovered functional relationships between individual genes and identified partners. Here we ranked 17,487 mammalian genes for coevolution with 6 distinct DNA repair pathways. Direct comparison to genetic screens for homologous recombination or Fanconi anemia factors indicates that our evolution-based screen is comparable, if not superior, to traditional screening approaches. Demonstrating the utility of our strategy, we identify a role for the DNA damage-induced apoptosis suppressor (DDIAS) gene in double-strand break repair based on its coevolution with homologous recombination. DDIAS knockdown results in DNA double-strand breaks, indicated by ATM kinase activation and 53BP1 foci induction. Additionally, DDIAS-depleted cells are deficient for homologous recombination. Our results reveal that evolutionary analysis is a powerful tool to uncover novel factors and functional relationships in DNA repair.

MCM8IP activates the MCM8-9 helicase to promote DNA synthesis and homologous recombination upon DNA damage

“…ERC between MCM8IP and major mammalian DNA repair pathways was calculated by taking the mean ERC score between MCM8IP and the genes in each pathway. Statistical significance was determined by permutation test, where the p-value is the computed probability of the observed mean ERC or greater when taking the mean between each gene group and 10,000 random genes, as described 79 .…”

A Drosophila screen identifies NKCC1 as a modifier of NGLY1 deficiency

“…Using estimates of evolutionary rate over the branches of a gene’s phylogenetic tree, the method measures the correlation between genes of these branch-specific rates. Genes within correlated rate variation tend to be functionally related and have been used to discover new genes within pathways and diseases ( Brunette et al, 2019 ; Priedigkeit et al, 2015 ; Raza et al, 2019 ).…”

Evolutionary rate covariation identifies SLC30A9 (ZnT9) as a mitochondrial zinc transporter

“…This evolutionary rate covariation occurs in physically interacting proteins that coevolve as well as functionally related proteins such as gene regulatory elements, membrane traffic adaptors, and transporters. As a result, ERC has been used to identify the functions of uncharacterized genes, including novel DNA damage-induced apoptosis suppressor, sex peptide network components, regulators of cell adhesion, and ion and aminoacid transporters (Brunette et al, 2019; Clark et al, 2012; Findlay et al, 2014; Raza et al, 2019; Talsness et al, 2020; Ziegler et al, 2016). ERC is calculated as correlation between evolutionary rates throughout a phylogeny.…”