“An Evolutionary Model of Transcription Networks”

Biological functions are facilitated by proteins, which are produced (expressed) from genes. Gene regulation, the processes that cells use to control the time, the place, and the intensity of gene expression, is therefore at the forefront of researches on human development, behavior, and disease. Gene regulation involves coordinated interactions of many proteins and DNA segments, namely transcription networks (TNs). It has been a long-time challenge to accurately identify TNs in vertebrate species, particularly in humans. We brought evolutionary biology ideas to meet this challenge.

In order to build an evolutionary model of TNs, we had to forfeit available models for DNA evolution and to start from modeling the evolution of the interactions between regulatory proteins and target genes. We developed a quantitative evolutionary model of TNs, subjecting the phylogenetic distance and the evolutionary changes of cis-regulatory sequence, gene expression and network structure to one probabilistic framework. Using the genome sequences and gene expression data from multiple species, this model can predict regulatory relationships between a transcription factor (TF) and its target genes in every species, and thus identify TNs, together with TN re-wiring events (evolutionary changes of interactions between TFs and target genes). Applying this model to analyze the pre-implantation development of three mammalian species, we identified the conserved and re-wired components of the TNs downstream to a set of TFs including Oct4, Gata3/4/6, cMyc and nMyc. Evolutionary events on the DNA sequence that led to turnover of TF binding sites were identified, including a birth of an Oct4 binding site by a 2nt deletion. In contrast to recent reports of large interspecies differences of TF binding sites and gene expression patterns, the interspecies difference in TF-target relationship is much smaller. The data indicated increasing conservation levels from genomic sequences to TF-DNA interaction, gene expression, TN, and finally to morphology, suggesting that evolutionary changes are larger at molecular levels and smaller at functional levels. The data also indicated that evolutionary older TFs are more likely to have conserved target genes, whereas younger TFs tend to have larger re-wiring rates.