Data derived from male recombination rate analysis in cattle

Description of data derived from male recombination rate analysis in cattle N. Melzer and D. Wittenburg Research Institute for Farm Animal Biology (FBN) Date: 16.11.2025 Version: 1.0 Contact: [email protected] 1. Data sets generated applying the hsrecombi pipeline Data sets were generated for the Clarity App (v.1.0.1) using the hsrecombi pipeline (v1.0.0, GitHub) with the following approaches included: deterministic approach (hsphase; v2.0.2, CRAN) and likelihood-based approach (hsrecombi; v0.3.4, CRAN). Breed-specific data were stored in breed-specific folders. 1.1 geneticMap.Rdata The Rdata file contains a data frame termed “geneticMap” with relevant genetic-map information of all markers and chromosomes derived from the different approaches. Header description: “genetic_map_header.csv” 1.2 genetic_map_summary.Rdata The Rdata file contains a data frame termed “genetic_map_summary” with descriptive statistics and key metrics for every chromosome and over all chromosomes derived from the different approaches. Header description: “genetic_map_summary_header.csv” 1.3 adjacentRecRate.Rdata The Rdata file contains a data frame termed “adjacentRecRate” with information about recombination rate between adjacent markers on all chromosomes derived from the deterministic approach. Header description: “adjacentRecRate_header.csv” 1.4 bestmapfun.Rdata The Rdata contains a matrix termed “out” with information about estimated parameters of genetic-map functions and mean squared errors of curves fitted to recombination rates that were derived from the likelihood-based approach for all chromosomes. Header description: “bestmapfun_header.csv” 1.5 curve-short-<chr>.Rdata The file contains relevant information of four genetic-map functions (Haldane scaled, Rao, Felsenstein, and Liberman & Karlin) fitted to recombination rates that were derived from the likelihood-based approach for each chromosome (for more details see Melzer et al. 2023). Each file contains a list termed “store” with four elements: 1. Matrix (numeric values): genetic distance in Morgan (dist_M) and recombination rate (theta) between markers. Only a reduced number of data points are provided; a data point is a pair of recombination rate and genetic-map coordinate ordered according to a vectorized triangular matrix of SNP identifiers. 2. Matrix (numeric values): x values of applied genetic-map functions (order: Haldane scaled, Rao, Felsenstein, and Liberman & Karlin) 3. Matrix (numeric values): y values of applied genetic-map functions (order: Haldane scaled, Rao, Felsenstein, and Liberman & Karlin) 4. Numeric value: percentage of marker pairs considered in matrix. Note: no specific header files were created. 2. Additional data sets Additional data sets contain information about markers that are putatively misplaced in the underlying reference genome ARS-UCD1.2 as well as information about chromosome regions that were difficult to assemble in general. 2.1 generalProblematicRegions.Rdata The file contains a tibble data frame termed “generalProblematicRegions” with information about problematic chromosome regions that are recommended to be removed from genome-based analysis regardless of the SNP panel used (Qanbari et al. 2022). Header description: “generalProblematicRegions_header.csv” 2.2 misplacedMarkers.Rdata The file contains a tibble data frame termed “misplacedMarkers with information about 65 SNP markers with strong evidence for being misplaced in the bovine reference genome based on the analysis of male recombination rate in German Holstein cattle (Qanbari et al. 2022). Header description: “misplacedMarkers_header.csv” Acknowledgments We gratefully acknowledge the support of the Association for Bioeconomy Research (FBF, Bonn, Germany) as representative of German Holstein cattle breeders for participating in this project and the German Evaluation Center (VIT, Verden, Germany) for composing the Holstein data. We thank ZuchtData (Vienna, Austria) for providing the German/Austrian Fleckvieh data.