A machine learning enhanced EMS mutagenesis probability map for efficient identification of causal mutations in Caenorhabditis elegans

• Published in: PLoS genetics Vol. 20; no. 8; p. e1011377
• Main Authors: Guo, Zhengyang, Wang, Shimin, Wang, Yang, Wang, Zi, Ou, Guangshuo
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 26.08.2024; Public Library of Science (PLoS)
• Subjects: Caenorhabditis elegans; Chemical mutagenesis; Chromatin; Chromosome mapping; DNA sequencing; Gene mutations; Genetic aspects; Genetic research; Genetic screening; Genomes; Genomics; Machine learning; Methane; Methods; Nucleotide sequencing; Organosulfur compounds; China

Chemical mutagenesis-driven forward genetic screens are pivotal in unveiling gene functions, yet identifying causal mutations behind phenotypes remains laborious, hindering their high-throughput application. Here, we reveal a non-uniform mutation rate caused by Ethyl Methane Sulfonate (EMS) mutagene...