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Discovering all the genetic causes of a phenotype is an important goal infunctional genomics. In this paper we combine an experimental design formultiple independent detections of the genetic causes of a phenotype, with ahigh-throughput sequencing analysis that maximizes sensitivity forcomprehensively identifying them. Testing this approach on a set of 24 mutantstrains generated for a metabolic phenotype with many known genetic causes, weshow that this pathway-based phenotype sequencing analysis greatly improvessensitivity of detection compared with previous methods, and reveals a widerange of pathways that can cause this phenotype. We demonstrate our approach ona metabolic re-engineering phenotype, the PEP/OAA metabolic node in E. coli,which is crucial to a substantial number of metabolic pathways and underrenewed interest for biofuel research. Out of 2157 mutations in these strains,pathway-phenoseq discriminated just five gene groups (12 genes) asstatistically significant causes of the phenotype. Experimentally, these fivegene groups, and the next two high-scoring pathway-phenoseq groups, either havea clear connection to the PEP metabolite level or offer an alternative path ofproducing oxaloacetate (OAA), and thus clearly explain the phenotype. Thesehigh-scoring gene groups also show strong evidence of positive selectionpressure, compared with strictly neutral selection in the rest of the genome.

Comprehensive Detection of Genes Causing a Phenotype using Phenotype Sequencing and Pathway Analysis