Work Description

Title: Dataset for "Empirical measures of mutational effects define neutral models of regulatory evolution in Saccharomyces cerevisiae" Open Access Deposited

Ingest Append Scripts

There are no ingest append scripts associated with this work.
h
Attribute Value
Methodology
  • The data are flow cytometry measurements of the level of expression of a YFP reporter gene driven by one of 10 different promoters for a collection of budding yeast genotypes in which point mutations have been induced by random mutagenesis.
Description
  • Understanding how phenotypes evolve requires disentangling the effects of mutation generating new variation from the effects of selection filtering it. Tests for selection frequently assume that mutation introduces phenotypic variation symmetrically around the population mean, yet few studies have tested this assumption by deeply sampling the distributions of mutational effects for particular traits. Here, we examine distributions of mutational effects for gene expression in the budding yeast Saccharomyces cerevisiae by measuring the effects of thousands of point mutations introduced randomly throughout the genome. We find that the distributions of mutational effects differ for the ten genes surveyed and are inconsistent with normality. For example, all ten distributions of mutational effects included more mutations with large effects than expected for normally distributed phenotypes. In addition, some genes also showed asymmetries in their distribution of mutational effects, with new mutations more likely to increase than decrease the gene’s expression or vice versa. Neutral models of regulatory evolution that take these empirically determined distributions into account suggest that neutral processes may explain more expression variation within natural populations than currently appreciated.
Creator
Depositor
  • andreahd@umich.edu
Contact information
Discipline
Funding agency
  • National Institutes of Health (NIH)
ORSP grant number
  • 15-PAF00017
Keyword
Citations to related material
  • Hodgins-Davis, A., Duveau, F., Walker, E. A., & Wittkopp, P. J. (2019). Empirical measures of mutational effects define neutral models of regulatory evolution in Saccharomyces cerevisiae. BioRxiv, 551804. https://doi.org/10.1101/551804
Resource type
Last modified
  • 11/18/2022
Published
  • 09/20/2019
Language
DOI
  • https://doi.org/10.7302/0dvr-k169
License
To Cite this Work:
Hodgins-Davis, A., Duveau, F., Walker, E., Wittkopp, P. J. (2019). Dataset for "Empirical measures of mutational effects define neutral models of regulatory evolution in Saccharomyces cerevisiae" [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/0dvr-k169

Relationships

This work is not a member of any user collections.

Files (Count: 3; Size: 2.41 MB)

Thumbnaildsfsdfsdf Title Original Upload Last Modified File Size Access Actions
Deep_Blue_ReadME.docx 2019-08-27 2019-09-20 15.5 KB Open Access
for_deep_blue_Supplementary_File_3.zip 2019-08-27 2019-09-20 1.2 MB Open Access
for_deep_blue_Supplementary_Files_6.zip 2019-08-27 2019-08-27 1.2 MB Open Access

Download All Files (To download individual files, select them in the “Files” panel above)

Best for data sets < 3 GB. Downloads all files plus metadata into a zip file.



Best for data sets > 3 GB. Globus is the platform Deep Blue Data uses to make large data sets available.   More about Globus