Simulating genetic mixing in strongly structured populations of the threatened southern brown bandicoot (Isoodon obesulus)
Data files
Jun 03, 2025 version files 19.68 GB
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demultiplexed_data.tar.gz
19.68 GB
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README.md
3.67 KB
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SBB_barcodes.txt
4.45 KB
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SBB_metadata.csv
8.85 KB
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SBB_popmap.txt
3.15 KB
Abstract
Genetic mixing aims to increase the genetic diversity of small or isolated populations, by mitigating genetic drift and inbreeding depression, either by maximally increasing genetic diversity, or minimising the prevalence of recessive, deleterious alleles. However, few studies investigate this beyond a single generation of mixing. Here, we model the mixing using captive, low diversity recipient population of the threatened Southern brown bandicoot (Isoodon obesulus) over fifty generations, and compare wild populations across south-eastern Australia as candidate source populations. We first assess genetic differentiation between twelve populations, including the first genomic assessment of three mainland Australian and three Tasmanian populations. We assess genetic diversity in the twelve populations using a novel autosomal heterozygosity pipeline, using these results to identify a candidate recipient population for genetic mixing simulations. We found that populations fell into four major groups of genetic similarity: Adelaide Hills, western Victoria, eastern Victoria, and Tasmania, but populations within these groups were also distinct, and additional substructure was observed in some populations. Our autosomal heterozygosity pipeline indicated significant variability in mean heterozygosity between populations, identifying one extremely genetically degraded population on Inner Sister Island, Tasmania. Genetic mixing simulations of a low heterozygosity captive population in Victoria suggested the greatest increase in heterozygosity would be reached by using highly differentiated populations as mixing sources. However, when removing outlying populations with extreme differentiation, neither metrics of differentiation nor heterozygosity were strongly correlated with modelled heterozygosity increase, indicating the value of simulation-based approaches when selecting source populations for population mixing.
https://doi.org/10.5061/dryad.34tmpg4v3
Description of the data and file structure
Genotypic data and metadata for 185 Isoodon obesulus, sampled from wild and captive sites across south-eastern between 2008-2023.
Samples provided as demultiplexed raw reads in .fq.gz format, with barcode, metadata, and pop-map files.
Metadata contains coordinate data approximated to two (2) decimal places to protect a sensitive species, as per The Global Biodiversity Information Facility (Category 3 sensitive species). Where exact coordinate data was unavailable, approximate data was inferred from the recorded locality. Two samples had broad location metadata, but no recorded coordinates or locality; coordinates for these samples are recorded as "n/a". Metadata also contains incomplete sex data; where sex was unknown, "n/a" has been used to indicate this.
Three replicate samples are included, indicated by A or B as the final character: WP01A/B, CRBG_02A/B, MR23A/B.
Figure 1 in the paper has been generated from publicly available, 1990-2023 observation data for I. obesuslus stored in ALA. This data is not CC-0 and thus cannot be uploaded directly to Dryad, but is readily accessible.
Description of the data and file structure
Processing details for the raw reads and pseudo-genome are in the associated manuscript.
All programs used to process data, including version, are also indicated in the manuscript.
All software used is open source.
Code/Software
This manuscript uses an autosomal heterozygosity pipeline available at https://github.com/jblack222/AutoHet
This manuscript uses population mixing simulations, available at https://github.com/jblack222/SimIntro
Files and variables
File: README.txt
Description: This file is a brief description of other files in the repository.
File: SBB_barcodes.txt
Description: This file is two columns, tab-seperated, containing sample ID and associated barcode for demultiplexing.
Variables
- ID
- Barcode
File: SBB_popmap.txt
Description: This file is two columns, tab-seperated, containing sample ID and associated population for downstream analysis.
Variables
- ID
- Location
File: demultiplexed_data.tar.gz
Description: This is a tar-ball directory containing 185 demultiplexed raw genomic data files for samples, in .fastq.gz format.
File: SBB_metadata.csv
Description: This file contains all relevant metadata for replication of this study.
Variables
- ID:
- Location:
- Region:
- Lat:
- Long:
- Sex:
Code/software
All software used in the manuscript are open source, freely accessible, and clearly described in the text, except those specified below which were developed for the manuscript.
Individual Autosomal Heterozygosity analysis:
This code, as described in the manuscript, is for a novel calculation of heterozygosity.
Code for generating individual estimates for heterozygosity is available at https://github.com/jblack222/AutoHet
Simulated Introductions analysis
This code, as described in the manuscript, is for calculation of heterozygosity change after mixing of populations.
Code for generating individual estimates for heterozygosity is available athttps://github.com/jblack222/SimIntro
Access information
Data used for Figure 1B was derived from the Atlas of Living Australia, https://www.ala.org.au/