title: Comprehensive detection of genes causing a phenotype using phenotype sequencing and pathway analysis.
abstract: Discovering all the genetic causes of a phenotype is an important goal in functional genomics. We combine an experimental design for detecting independent genetic causes of a phenotype with a high-throughput sequencing analysis that maximizes sensitivity for comprehensively identifying them. Testing this approach on a set of 24 mutant strains generated for a metabolic phenotype with many known genetic causes, we show that this pathway-based phenotype sequencing analysis greatly improves sensitivity of detection compared with previous methods, and reveals a wide range of pathways that can cause this phenotype. We demonstrate our approach on a metabolic re-engineering phenotype, the PEP/OAA metabolic node in E. coli, which is crucial to a substantial number of metabolic pathways and under renewed interest for biofuel research. Out of 2157 mutations in these strains, pathway-phenoseq discriminated just five gene groups (12 genes) as statistically significant causes of the phenotype. Experimentally, these five gene groups, and the next two high-scoring pathway-phenoseq groups, either have a clear connection to the PEP metabolite level or offer an alternative path of producing oxaloacetate (OAA), and thus clearly explain the phenotype. These high-scoring gene groups also show strong evidence of positive selection pressure, compared with strictly neutral selection in the rest of the genome.
authors.affiliation: Institute for Genomics and Proteomics, University of California Los Angeles, Los Angeles, California, United States of America.
authors.forename: Marc
authors.initials: M
authors.lastname: Harper
authors.affiliation: Department of Chemical and Biomolecular Engineering, University of California Los Angeles, Los Angeles, California, United States of America.
authors.forename: Luisa
authors.initials: L
authors.lastname: Gronenberg
authors.affiliation: Institute for Genomics and Proteomics, University of California Los Angeles, Los Angeles, California, United States of America ; Department of Chemical and Biomolecular Engineering, University of California Los Angeles, Los Angeles, California, United States of America.
authors.forename: James
authors.initials: J
authors.lastname: Liao
authors.affiliation: Institute for Genomics and Proteomics, University of California Los Angeles, Los Angeles, California, United States of America ; Dept. of Chemistry & Biochemistry, University of California Los Angeles, Los Angeles, California, United States of America ; Dept. of Computer Science, University of California Los Angeles, Los Angeles, California, United States of America ; Molecular Biology Institute, University of California Los Angeles, Los Angeles, California, United States of America.
authors.forename: Christopher
authors.initials: C
authors.lastname: Lee
mesh_terms: D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D005798:Genes, Bacterial; D010641:Phenotype
chemical_list: D001426:Bacterial Proteins