Quantifying the Strength of Natural Selection of a Motif Sequence

Abstract

Quantification of selective pressures on regulatory sequences is a central issue in studying the evolution of gene regulatory networks. Previous methods of detecting natural selection focus primarily on single sites rather than motif sequences. We propose a method of evaluating the strength of natural selection of a motif from a family of aligned sequences. The method is based on a Poisson process model of neutral sequence substitution and derives a system of differential-difference equations of the additions and deletions of motifs. The selection coefficient is treated as a penalty for the motif death rate. We demonstrate that the birth-death model closely approximates statistics generated from simulated data and the Poisson process assumption holds in mammalian promoter sequences. Furthermore, we show that a considerably higher portion of known transcription factor binding motifs possess high selection coefficients compared to random controls. Comparison of SP1 and TP53 binding motifs indicates that a higher portion of the SP1 motifs are conserved between the orthologous promoters of human and other mammals. Preliminary analysis suggests the potential applications of the model to identify regulatory sequences under selection.