Population Genetics of Melampsora larici-populina

Microsatellite-based workflow for population genetic analysis of Melampsora larici-populina isolates.

This repository contains an R workflow to:

• Load isolate metadata and microsatellite genotypes
• Define multilocus genotypes (MLGs) and multilocus lineages (MLLs)
• Assign isolates to genetic clusters
• Infer sexual versus asexual reproduction
• Calculate population genetic indices
• Build a bootstrapped phylogenetic tree
• Generate spatial maps
• Test the effects of geography and year using regression models

This repository contains a fully reproducible R workflow with Docker for cross-platform.

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Fully Reproducible with Docker

The entire analysis environment is packaged in a Docker image. No R installation, no package management, no dependency conflicts.

Prerequisites

• Docker Desktop (free, works on macOS / Windows / Linux)

Quick start

# 1. Clone the repository (contains the input data)
git clone https://github.com/ammarabdalrahem/poplar_rust.git
cd poplar_rust

# 2. Run the analysis — one command
docker run --rm \
  -v $(pwd):/project \
  ghcr.io/ammarabdalrahem/poplar_rust:1.0

On Windows PowerShell, replace $(pwd) with ${PWD}.

All outputs (figures, tables, CSV files) will appear in your local poplar_rust/ folder after the run completes.

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Associated study

Long-lasting coexistence of multiple asexual lineages alongside their sexual counterparts in a fungal plant pathogen

Authors:
Ammar Abdalrahem, Axelle Andrieux, Ronan Becheler, Sébastien Duplessis, Pascal Frey, Benoit Marcais, Kadiatou Schiffer-Forsyth, Solenn Stoeckel, Fabien Halkett

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Repository contents

File	Description
data_analysis_mlp_new.R	R script version for terminal / Docker execution
Table_data.tsv	Input file with isolate metadata and microsatellite genotypes
Dockerfile	Docker image definition for full reproducibility

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Manual setup (without Docker)

If you prefer to run the analysis manually in R:

Requirements

• R 4.4.1 or later recommended
• RStudio recommended for interactive work

R packages

Install the required CRAN packages:

install.packages(c(
  "lme4","knitr", "ggplot2", "readxl", "tidyverse",
  "genepop", "hierfstat", "mapdata", "mapplots",
  "adegenet", "poppr", "pegas", "ape",
  "cowplot", "ade4", "viridis", "ggrepel", "ggsci",
  "scales", "dplyr", "factoextra", "sf",
  "rnaturalearth", "rnaturalearthdata",
  "svglite", "BiocManager", "devtools", "reshape2",
  "ggpubr", "ggforce"
))

Install required Bioconductor packages (ggtree and ggtreeExtra):

if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")
BiocManager::install(c("ggtree", "ggtreeExtra"), ask = FALSE, update = FALSE)

Install RClone from GitHub:

remotes::install_github("dbailleul/RClone", dependencies = TRUE)

Run the script

Rscript data_analysis_mlp_new.R

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Input format

The input file must be named:

Table_data.tsv

Requirements:

• Microsatellite locus columns must contain Mlp in the column name
• Missing genotype values must be coded as 999

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Main outputs

File	Description
new_genotype_data.csv	Final genotype table with cluster and reproduction labels
filtered_mll_years.csv	MLLs recurring across multiple years
Fig1A_map.svg	Sampling map
Silhouette_kmeans.png	Silhouette plot for cluster evaluation
Dapc_xval.png	Cross-validation plot for DAPC
DAPC_scatter.png	DAPC scatter plot
DAPC_compoplot.png	DAPC composition plot
cluster_assignments.png	Cluster assignment probability plot
tree_plot1.png	Circular phylogenetic tree
tree_plot2.png	Annotated phylogenetic tree
map_all_years.png	Map of sexual versus asexual proportions across all years
map_2009_2011.png	Map for 2009 and 2011 only
effect_of_latitude_filtered.png	GLM-based latitude effect plot
effect_of_latitude_glmm.png	GLMM-based latitude effect plot
MST_data_mlp_pop_as_Reproduction_for_cloneEstimate.txt	Export for downstream clone analysis
asex_mll_Year.png	Asexual lineage abundance across years
asex_mll_Locations.png	Asexual lineage abundance across locations
asex_mll_Year_Locations.png	Combined lineage abundance figure

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Notes

• The .R script is the main reproducible workflow for generating the report
• The Docker image (ghcr.io/ammarabdalrahem/poplar_rust:1.0) contains R 4.4.1 and all required packages pre-installed
• Isolates with uncertain cluster assignment are excluded from downstream analyses
• Most output files are written to the working directory

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Citation

If you use this workflow or the associated Docker image, please cite:

Abdalrahem, A., et al. (2026). Long-lasting coexistence of multiple asexual lineages alongside their sexual counterparts in a fungal plant pathogen.

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License

This project is distributed under the CC BY 4.0 license.