DOI: 10.5061/dryad.djh9w0w1p
title: Data and code for: Changes to the mtDNA copy number during yeast culture growth

description: We show that the mtDNA copy number in growing cultures of the yeast
 Saccharomyces cerevisiae increases by a factor of up to 4, being lowest
 (~10 per haploid genome) and stable during rapid fermentative growth, and
 highest at the end of the respiratory phase. When yeast are grown on
 glucose, the onset of the mtDNA copy number increase coincides with the
 early stages of the diauxic shift, and the increase continues through
 respiration. A lesser yet still substantial copy number increase occurs
 when yeast are grown on a nonfermentable carbon source, i.e. when there is
 no diauxic shift. The mtDNA copy number increase during and for some time
 after the diauxic shift is not driven by an increase in cell size. The
 copy number increase occurs in both haploid and diploid strains, but is
 markedly attenuated in a diploid wild isolate that is a ready sporulator.
 Strain-to-strain differences in mtDNA copy number are least apparent in
 fermentation and most apparent in late respiration or stationary phase.
 While changes in mitochondrial morphology and function were previously
 known to accompany changes in physiological state, it had not been
 previously shown that the mtDNA copy number changes substantially over
 time in a clonal growing culture. The mtDNA copy number in yeast is
 therefore a highly dynamic phenotype.
description: # Data from: Changes to the mtDNA copy number during yeast culture growth
 Royal Society Open Science, 2022
 ([https://doi.org/10.1098/rsos.211842](https://doi.org/10.1098/rsos.211842)) ============================================================================ ## Author/Principal Investigator Information Name: Ben Galeota-Sprung ORCID: 0000-0003-0085-0948 Institution: University of Pennsylvania Address: Email: [bsprung@gmail.com](mailto:bsprung@gmail.com) # SHARING/ACCESS INFORMATION * Licenses/restrictions placed on the data: None * Links to publications that cite or use the data: [https://doi.org/10.1098/rsos.211842](https://doi.org/10.1098/rsos.211842) * Recommended citation for this dataset: [https://doi.org/10.1098/rsos.211842](https://doi.org/10.1098/rsos.211842) # DATA & FILE OVERVIEW ## File List ### The following files are the *raw* data for the image-based assessment of cell size over time presented in Fig. S7 C,D,E * `images.zip`: this archive unpacks to several PNG images named similarly to `56.83_B-FL-A.png`. The first portion of the file name (e.g. the 56.83) is the time in hours after transfer. Clusters of cells that were not automatically processed correctly by CellProfile were removed; when this happened the altered image was saved with the suffix `_edited.` ### The following archive and files are the *raw* data for the flow cytometry This is the underlying data for the FSC (forward scatter) and SSC (side scatter) plots shown in Figure 2a and Supplemental Figure 7. The data represents 16 samples taken at between 12.25 and 85.58 hours after culture inoculation. Internally, the 16 timepoints are labelled A,B..P. * The file `timepoints.tsv` maps these internal labels A,B,..P to their specific timepoints, e.g. A is 12.25 hours and P is 85.6 hours. This file is provided as context for the raw flow cytometry data. The column specification for `timepoints.tsv` is as follows: * `sample`: the sample name A..P * `clock_time`: the datetime of the sample * `hour`: the time in units of hours, of the sampling, relative to culture inoculation * `fc_vol`: the volume of sample, in units of microliters, removed for flow cytometry * `dna_vol`: the volume of sample, in units of microliters, removed for DNA extraction * `flow_cytometry_data.zip`: Unpacks to include `2021-12-22_at_01-50-58pm.fcs`, which is 16 wells of data, with each well being a one of the 16 timepoints shown in Figure 2a. This data was generated by a Guava EasyCyte is in FCS format. It may be viewed with standalone software such as FlowJo, or the open-source R package [flowCore](https://www.bioconductor.org/packages//2.10/bioc/html/flowCore.html) which is part of Bioconductor. As an alternative means of access, all the data for each of these wells has also been explored to 16 csv files named `2021-12-22_at_01-50-58pm.A01.CSV` through `2021-12-22_at_01-50-58pm.B08.CSV`. The column spec for these CSV files is as follows. (Note that only FSC, SSC, and gating columns are relevant as these cells are not fluorescent and also note that values for the FSC, SSC, and the fluorescence channels are in arbitrary units.) * `FSC-HLin`: The FSC height for this observation on a linear scale * `SSC-HLin`: The SSC height for this observation on a linear scale * `GRN-B-HLin:` The green fluorescence channel height for this observation on a linear scale * `YEL-B-HLin:` The green fluorescence channel height for this observation on a linear scale * `RED-B-HLin:` The green fluorescence channel height for this observation on a linear scale * `FSC-W`: The FSC width for this observation on a linear scale * `FSC-HLog`: The FSC height for this observation on a log scale * `SSC-HLog`: The SSC height for this observation on a log scale * `GRN-B-HLog:` The green fluorescence channel height for this observation on a log scale * `YEL-B-HLog:` The green fluorescence channel height for this observation on a log scale * `RED-B-HLog:` The green fluorescence channel height for this observation on a log scale * `FSC-ALog`: The FSC area for this observation on a linear scale * `FSC-WLog`: The FSC width for this observation on a log scale * `TIME`: The time of the observation in units of microseconds.  * `P01.Cells`: A boolean value for a gate that was not used.  * `P01.Yeasties`: A boolean value for a gate used to define observations as yeast cells.  * `P01.Yeasties.NotDoublets`: A boolean value for a gate used to define observations as yeast cells that were not doublets, as described in the Methods of the associated paper.  In the FCS and csv files, samples A-H are in wells A01..A08 and samples J..P are in wells B01..B08, respectively. The Guava-generated metadata file `2021-12-22_at_01-50-58pm.xml` also records this mapping, though note that both columns and rows are represented numerically and 0-indexed.  
 
 ### The following archives are the *raw* short- and long-read sequencing
 data used in this paper * `sequences_TableS5.zip`: This unpacks to
 includeall sequence data used for Table S5, the correspondence between
 relative read depth derived from Illumina vs Nanopore reads: | File(s) |
 Platform | Info | |
 :------------------------------------------------------- | :------- |
 :----------------------------------------------------- | |
 `BGS3_nanopore.fastq.gz` | Nanopore | after 3rd transfer, during
 fermentation | | `BGS4_nanopore.fastq.gz` | Nanopore | after 3rd transfer,
 during respiration | | `BGS5_S162_R1_001.fastq.gz`,
 `BGS5_S162_R1_001.fastq.gz` | Illumina | after 3rd transfer, during
 fermentation | | `BGS6_S163_R1_001.fastq.gz`, `BGS6_S163_R2_001.fastq.gz`
 | Illumina | Illumina reads, after 3rd transfer, during respiration | *
 `sequences_main.zip`: This unpacks to include all sequence data used for
 Fig. 1E (W303 haploid relative copy number over time): | Files | Platform
 | Time after inoculation (h) | |
 :-------------------------------------------------------- | :------- |
 :------------------------- | | `BGS7_S90_R1_001.fastq.gz`,
 `BGS7_S90_R2_001.fastq.gz` | Illumina | 11.58 | |
 `BGS9_S92_R1_001.fastq.gz`, `BGS9_S92_R2_001.fastq.gz` | Illumina | 17 | |
 `BGS10_S93_R1_001.fastq.gz`, `BGS10_S93_R1_001.fastq.gz` | Illumina | 23.5
 | | `BGS11_S94_R1_001.fastq.gz`,  `BGS11_S94_R2_001.fastq.gz` | Illumina |
 35.5 | | `BGS12_S95_R1_001.fastq.gz`,  `BGS12_S95_R2_001.fastq.gz` |
 Illumina | 65.5  | ### The following files describe the full sequencing
 pipeline used to process the reads * `sequencing_pipeline.txt`