bioRxivGenetics
Meiotic interactors of a mitotic gene TAO3 revealed by functional analysis of its rare variant
Saumya GuptaiD, Aparna Radhakrishnan, Rachana Nitin, Pandu Raharja-Liu, Gen Lin, Lars M Steinmetz, Julien Gagneur, Himanshu SinhaiD
Abstract
Studying the molecular consequences of rare genetic variants has the potential of identifying novel and hereto uncharacterized pathways causally contributing to phenotypic variation. Here we characterize the functional consequences of a rare coding variant of TAO3, previously reported to significantly contribute to sporulation efficiency variation in Saccharomyces cerevisiae. During mitosis TAO3 interacts with CBK1, a conserved NDR kinase and a component of RAM network. The RAM network genes are involved in regulation cell separation and polarization. We demonstrate that the role of the rare allele TAO3(4477C) in meiosis is distinct from its role in mitosis by being independent of ACE2, which is a RAM network target gene. By quantitatively measuring cell morphological dynamics and conditionally expressing TAO3(4477C) allele during sporulation, we show that TAO3 has an early role in meiosis. This early role of TAO3 coincides with entry of cells into meiotic division. Time-resolved transcriptome analyses during early sporulation phase identified regulators of carbon and lipid metabolic pathways as candidate mediators. We experimentally show that during sporulation the TAO3 allele genetically interacts with ERT1 and PIP2, the regulators of tricarboxylic acid cycle and gluconeogenic enzymes, respectively. We thus uncover meiotic functions of TAO3, a mitotic gene and propose ERT1 and PIP2 as novel regulators of sporulation efficiency. Our results demonstrate that study of causal effects of genetic variation on the underlying molecular network has the potential to provide more extensive comprehension of the pathways driving a complex trait. This can help identify prospective personalized targets for intervention in complex diseases.
- organism: yeast
- assay: proteomics
- research focus: gene regulatory network inference
- approach: experimental assay
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