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bioRxiv · 10.1101/2020.05.24.113217

Mapping the architecture of regulatory variation provides insights into the evolution of complex traits

Abstract

BackgroundOrganisms evolve complex traits by recruiting existing programs to new contexts, referred as co-option. Within a species, single upstream regulators can trigger full differentiation programs. Distinguishing whether co-option of differentiation programs results from variation in single regulator, or in multiple genes, is key for understanding how complex traits evolve. As an experimentally accessible model for studying this question we turned to budding yeast, where a differentiation program (filamentous) is activated in S. cerevisiae only upon starvation, but used by the related species S. paradoxus also in rich conditions. ResultsTo define expression variations associated with species-specific activation of the filamentous program, we profiled the transcriptome of S. cerevisiae, S. paradoxus and their hybrid along two cell cycles at 5-minutes resolution. As expected in cases of co-option, expression of oscillating genes varies between the species in synchrony with their growth phenotypes and was dominated by upstream trans-variations. Focusing on regulators of filamentous growth, we identified gene-linked variations (cis) in multiple genes across regulatory layers, which propagated to affect expression of target genes, as well as binding specificities of downstream transcription factor. Unexpectedly, variations in regulators essential for S. cerevisiae filamentation were individually too weak to explain activation of this program in S. paradoxus. ConclusionsOur study reveals the complex architecture of regulatory variation associated with species-specific use of a differentiation program. Based on these results, we suggest a new model in which evolutionary co-option of complex traits is stabilized in a distributed manner through multiple weak-effect variations accumulating throughout the regulatory network.

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Lupo, O., Krieger, G., Jonas, F., Barkai, N.. 2020-05-27. Mapping the architecture of regulatory variation provides insights into the evolution of complex traits. https://doi.org/10.1101/2020.05.24.113217

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