DOI: 10.5061/dryad.k6djh9wg3
title: Drosophila serrata mutation accumulation lines: Phenotypic data on survival following infection with Drosophila C virus and reproduction

description: The impact of selection on host immune function genes has been widely
 documented. However, it remains essentially unknown how mutation
 influences the quantitative immune traits that selection acts on. Applying
 a classical mutation accumulation (MA) experimental design in Drosophila
 serrata, we found the mutational variation in susceptibility (median time
 of death, LT50) to Drosophila C virus (DCV) was of similar magnitude to
 that reported for intrinsic survival traits. Mean LT50 did not change as
 mutations accumulated, suggesting no directional bias in mutational
 effects. Maintenance of genetic variance in immune function is
 hypothesised to be influenced by pleiotropic effects on immunity and other
 traits that contribute to fitness. To investigate this, we assayed female
 reproductive output for a subset of MA lines with relatively long or short
 survival times under DCV infection. Longer survival time tended to be
 associated with lower reproductive output, suggesting that mutations
 affecting susceptibility to DCV had pleiotropic effects on investment in
 reproductive fitness. Further studies are needed to uncover the general
 patterns of mutational effect on immune responses and other fitness
 traits, and to determine how selection might typically act on new
 mutations via their direct and pleiotropic effects.
description: This project first determined that <em>D.
 serrata</em> is a susceptible host of the Drosophila C virus.
 Second, survival time following DCV infection was measured for a panel of
 65 inbred lines that differed from one another by fixation of spontaneous
 mutations over 30 generations , and that data used to determine how
 mutations affected DCV susceptibility. Finally, for a subset of lines with
 extreme differences in survival time, we also measured female offspring
 production to determine whether mutations affecting immune function also
 affected productivity.
description: # Drosophila serrata Mutation Accumulation lines: Phenotypic data on
 survival following infection with Drosophila C virus and reproduction
 [https://doi.org/10.5061/dryad.k6djh9wg3](https://doi.org/10.5061/dryad.k6djh9wg3) ## Description of the data and file structure List of files and their use. 1\. `DCV vs PBS and Sex.csv`: file contains data from first (prelim) experiment determining susceptibility of D. serrata to DCV infection. Data is day of death for each fly in each vial; further details in the `DCV vs PBS and Sex README.txt`. This data is analysed using `DCV PBS Sex Survival Curve Analyses.R` file to generate both main text and supplementary results. 2\. `Expt 2 MA LT50 input data.csv`: the data from experiment in which 4 (12) replicates vials of 7 females from each of 65 MA lines (their Ancestor) were injected with DCV, and survival recored. Data formatted as the number of flies alive and number dead on each day post injection. Full data description in 'Expt 2 MA LT50 input data README.txt'. LT50 per vial estimated using `Expt 2 Estimate LT50 per vial.R`. There are no reported results arising directly from these files. 3\. `LT50.csv`: Output of `Expt 2 Estimate LT50 per vial.R`, with further information on variables included in `LT50 README.txt`. This data was input to SAS for estimating among-line variance (model 3 main text) and effect of mutation on population mean LT50 (model 4 main text). The code for those analyses is 'LT50 SAS code for VM and delta M.sas' (can be opened with a text edit app). 4\. `post SAS LT50.....` are R code and data (including README files for details) for taking output from analyses implemented in SAS to generate Figure 2 and Table 1. R code contains file names for data files for Figure 2; for table 1, SAS parameters were typed into the code file. 5\. `Productivity input data.csv` is the raw counts of offspring emerging from vials set up each day, and the count of females alive to contribute those offspring (see `Productivity input data README.txt`). This data is processed via `Productivity_Expt 3 data handling and analyses.R`, which also contains code for analyses and display items (Figures 3 & 4)Sharing/Access information Files are available via The University of Queensland's eSpace * [https://doi.org/10.48610/48d7c29](https://doi.org/10.48610/48d7c29 "https://doi.org/10.48610/48d7c29") Data was generated *de novo* following protocols detailed in the associated manuscript ## Code/Software Data were analysed using SAS and R (RStudio). Code files are included as detailed above.