A genetic method to infer ploidy and aberrant inheritance in triploid organisms
Data files
Jul 17, 2024 version files 1.99 MB
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README.md
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Supplementary_data_files.zip
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Abstract
Polyploidy occurs naturally across eukaryotic lineages and has been harnessed in the domestication of many crops and vertebrates. In aquaculture, triploidy can be induced as a biocontainment strategy, as it creates a reproductive barrier preventing farm-to-wild introgression, which is currently a major conservation issue for the industry. However, recent work suggests that triploidization protocols may, on occasion, produce ‘failed triploids’ displaying diploidy, aneuploidy, and aberrant inheritance. The potentially negative consequences for conservation and animal welfare motivate the need for methods to evaluate the success of ploidy-manipulation protocols early in the production process. We developed a semi-automated version of the MAC-PR (microsatellite DNA allele counting – peak ratios) method to resolve the allelic configuration of large numbers of individuals across a panel of microsatellite markers, that can be used to infer ploidy, pedigree, and inheritance aberrations. We demonstrate an application of the approach using material from a series of Atlantic salmon (Salmo salar) breeding experiments where ploidy was manipulated using a hydrostatic pressure treatment. We validated the approach to infer ploidy against blood smears, finding a >99% agreement between these methods, and demonstrate its potential utility to infer ploidy as early as the embryonic stage. Furthermore, we present tools to assign diploid and triploid progeny to families and to detect aberrant inheritance, which may be useful for breeding programmes that utilize ploidy manipulation techniques. The approach adds to the ploidy verification toolbox. The increased precision in detecting ploidy and inheritance aberrations will facilitate the ability of triploidization programmes to prevent farm-to-wild introgression.
Title: A genetic method to infer ploidy and aberrant inheritance in triploid organisms
Authors: Aurélien Delaval, Kevin A. Glover, Monica F. Solberg, John B. Taggart, François Besnier, Anne Grete Eide Sørvik, Johanne Øyro, Sofie Nordaune Garnes-Gutvik, Per Gunnar Fjelldal, Tom Hansen, Alison Harvey
Upload date: 8 July 2024
1. MAC-PR folder:
- MAC-PR_analysis.R: Main script used to perform MAC-PR and estimate ploidy.
- Scripts folder: Contains an additional script sourced by the main script.
- Genotypes folder: Contains raw data for MAC-PR, and curated data for ploidy assessment.
- Reference_dips_trips.csv: A curated GeneMapper dataset containing reference diploids and triploids.
- egg_genotypes_raw.csv: Raw GeneMapper data of salmon eggs, as an example of raw genotyping data to run MAC-PR analysis.
- eggs_MAC-PR_genotypes.csv: Resolved egg genotypes after MAC-PR, in full allele format for downstream pedigree and inheritance analysis.
- eggs_MAC-PR_genotype_categories.csv: Resolved egg genotypes after MAC-PR, in a genotypic category format for downstream ploidy analysis.
- parr_MAC-PR_genotypes.csv: Resolved parr genotypes after MAC-PR, in full allele format for downstream pedigree and inheritance analysis.
- parr_MAC-PR_genotype_categories.csv: Resolved parr genotypes after MAC-PR, in a genotypic category format for downstream ploidy analysis.
- parr_bloodsmears.csv: raw parr bloodsmear data used to validate the MAC-PR ploidy assessment.
2. tripFAP folder:
- tripFAP v1.92.xlsm: Family Analysis Program, with information on how to run the program, tabulated with Atlantic salmon parr genotypes.
3. Mismatch script folder:
- script_check.R: Main script used to identify types of inheritance aberrations (i.e. mismatches between parent and offspring genotypes)
- Scripts folder: Contains additional scripts sourced by the main script.
- offspring_genotypes.csv: genotypes of offspring determined by MAC-PR, with family assignment information (determined by tripFAP)
- parents_genotypes.csv: genotypes of the parents. Three dams (M1-M3) and one sire (M13).
- genotypes_comments_baseshift.csv: Output file generated by script_check.R
Note: R scripts were written in version 4.2.2 (R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.)
