Comparative analyses of natural and mutated sequences have been used to probe mechanisms of gene expression, but small sample sizes may produce biased outcomes. Here, we applied an unbiased design-of-experiments approach to disentangle factors suspected to affect translation efficiency in Escherichia coli. We precisely designed 244,000 DNA sequences implementing 56 replicates of a full-factorial design to evaluate nucleotide, secondary structure, codon and amino-acid properties in combination. For each sequence, we measured reporter transcript abundance and decay, polysome profiles, protein production and growth rates. Associations between designed sequences properties and these consequent phenotypes are dominated by secondary structures and their interactions in transcripts. We confirm that transcript structure generally limits translation initiation, and demonstrate its physiological cost using an epigenetic assay. Codon composition has a sizable impact on translatability, but only in comparatively rare elongation-limited transcripts. We propose a set of design principles to improve translation efficiency that would benefit from more accurate prediction of secondary structures in vivo. Despite the extensive and systematic nature of our dataset, long and scrupulous manual analyses were necessary to build a consistent view of the underlying mechanisms of gene expression and physiology. Improved learning approaches are needed to fully realize the power of such massive molecular Design of Experiments.