Data and code from: Spatially structured host genetic diversity leads to the evolution of local specialization
Data files
Feb 10, 2026 version files 105.55 KB
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README.md
3.85 KB
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SpacexDiversity_2025Sub.R
35.60 KB
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SpacexDiversity_DataFull.xlsx
66.10 KB
Abstract
Host heterogeneity and spatial population structure each influence parasite evolution and may interact when space structures contacts between host types. Here, we experimentally evolve granulosis virus in microcosms of its natural Plodia interpunctella (Indian meal moth) host that differ in both spatial structure and host genetic diversity. We control spatial structure by manipulating the viscosity of the food that the larvae live within and host genetic diversity by adding larvae from either one or two non-evolving inbred lines to opposite microcosm ends. We preserve spatial structure across passages and assay virus from different positions within the microcosm on both host genotypes. We find that the lower contact rates between host genotypes resulting from spatial structure can lead to the evolution of locally specialized virus, even when the host population is genetically diverse overall. We also find that spatial structure changes how viruses specialize: viruses evolved in well-mixed environments had lower exploitation rates (proportion infected x virions) on the host they evolved with, while those in spatially structured environments exhibited higher exploitation of familiar hosts. These results demonstrate that spatial structure and host heterogeneity interact to shape pathogen specialization and that the evolutionary consequences of host diversity depend on population structure.
Dataset DOI: 10.5061/dryad.pnvx0k72n
Description of the data and file structure
READ ME : This file contains all the data associated with the Space x Diversity manuscript. Each tab has a different dataset that can be loaded into the R script as a .csv. Note: blanks or NA cells mean missing data or inapplicable.
PassageEcology.csv : Contains the count of infected cavaders found in each grid square during serial passage. Therefore, it represents the spatial ecology of infections. Columns: Replicate = replicate of the treatment. Lines = Host lines used in the treatment. Note that 17and9 and 9and17 are different and represent the two different 'sides' of the host types. Food = Food type used in the treatment. S is sticky, L is loose. Position = Position within the microcosm. There are 15 positions labelled with letters from left to right and then down the grid. A is the top left, C is the top right, H is the center, M is bottom left, O is bottom right. Pass\_ = Columns that contain the counts at the different passage numbers (column name).
Movement.csv : Contains the count data from the movement experiment. Line = Host line used (IL-17). Food = Food type used, sticky or loose. Position = position in the microcosm, same as above. Infected = count of infected individuals. Noninfected = count of not infected individuals. Added? = Whether larvae were added to that half of the microcosm (1) or not (0). 0.5 means it was the border row where half of it had larvae added. Distance = Distance (in grid squares) from where larvae were added. 0 means larvae were added to that square. Row and Column = Position in the microcosm translated into rows and columns.
AssayData.csv : Contains the results of infectivity and productivity assays. ID = anonymizing ID used to prevent experimental bias. Plate = plate number for the count. 2 plates were made for each assay. Infected = number of infected individuals in the plate. Uninfected =number of uninfected individuals in the plate. Set-up = set up date of the batch. VirusLine = numbered ID for the virus population used in the assay. Number before the decimal corresponds the the microcosm number. After the decimal is the position within the microcosm. Lines = Host lines used to set up the microcosm (as above note that 17and9 and 9and17 are separate). Food = Food type for the evolution (as above). Position = position of origin within the micocosm for the virus population. Each row is pooled so this is different than previous. t is top, tm is top middle, m is middle, mb is middle bottom, b is bottom. AssayLine = Host line that the virus line is being assayed on. Replicate = Replicate of the evolution. AveCount = Count of virus particles per cadaver (counted all infecteds in a pool and then divided by number of infecteds). * and Note : notes of when data has been deleted / maniplated because of experimental errors.
HostLines.csv : Infectivity and Productivity of ancestral virus on the two host lines. Line = Host Line. Infecticity = proportion of larvae infected. Productivity = average count of virus per infected individual. Exploitation = composite score of infectivity x productivity. Assay Line = Host Line (used for graphing)
TimetoKill : Data from a test of how long it takes the ancestral virus to kill 3rd instar larvae. Time to Kill (days): number of days after exposure that infected larvae died. Average Virus Count : Number of virus in the cadaver (averaged over multiple counts)
Files and variables
File: SpacexDiversity_DataFull.xlsx
Description: Data
File: SpacexDiversity_2025Sub.R
Description: Code for analysis
Code/software
Excel and R