An information content principle explains regulatory patterns of gene expression across human tissues

Abstract

Abstract Gene expression ranges from broadly expressed to tissue-specific patterns, with many genes displaying intermediate specificity. Understanding how regulatory architecture scales with tissue specificity can reveal fundamental principles of genome regulation. By analyzing cis -regulatory element counts across human genes with varying tissue specificity, we identify a non-monotonic pattern: genes with intermediate specificity harbor the most regulatory elements, suggesting distinct regulatory strategies across the expression spectrum. We apply the Minimum Description Length principle from information theory, and maximum parsimony from phylogenetics, to quantify regulatory demand underlying expression patterns. This measure scales consistently with cis -regulatory element counts, transcription factors, microRNAs, and gene structure, and distinguishes switch-like regulation in selectively expressed genes from fine-tuning regulation in broadly expressed genes. Regulatory element abundance peaks in genes of intermediate evolutionary age. Regulatory architecture appears to scale with informational costs, suggesting that the genome operates as a decompression device, where regulation is dictated by minimally required complexity.