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FIELD Computational Sciences
DATE November 10 (Tue), 2020
TIME 14:00-15:00
PLACE 7323
SPEAKER somya mani
HOST Hyeon, Changbong
INSTITUTE IBS-CSLM
TITLE [GS_C_BSM] A stochastic model to study de novo gene birth
ABSTRACT

Whole genome studies have revealed an abundance of genes with no clear homologs. The origins of many of these genes is proposed to be in intergenic sequences that somehow gained expression and adaptive value ? a process termed de novo gene birth. Here, we explore the mechanism of de novo gene birth in a first-principles stochastic evolution model taking into account the effects of mutations on both expression level and the adaptive value. In our model, gene birth appears as an abrupt dynamical phase transition from a mutation-dominated phase to a selection-dominated phase. Rather than a rare mutation incurred by a single lucky individual, we show that de novo gene birth is whole population phenomenon. Through this study, we aim to infer the relationship between the mutational and epigenetic dynamics at intergenic regions, and the probability and timing of gene birth in natural populations.

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