Our objective was to harness the power of interactive visualizations by utilizing open-source tools to develop an efficient strategy for visualizing Single Nucleotide Polymorphism data within a livestock population, focusing on tracking the transmission of haplotypes. To achieve this, we simulated a realistic beef cattle population in order to obtain phased haplotypes and generate the necessary inputs for creating our visualizations. The visualization tool was built using Python and the Plotly library, which enables interactivity. We set out to explore three scenarios: trio comparison, visualization of grandparents, and half-sibling evaluation. These scenarios enabled us to trace the inheritance of genetic segments, identify crossover events, and uncover common regions within related and unrelated animals. The potential applications of this approach are significant, particularly for improving genomic selection in smaller breeding programs and farms, and it provides valuable insights for guiding more in-depth genomic region analysis. Beyond its practical applications, we believe this strategy can be a valuable educational tool, helping educators clarify complex concepts like Mendelian sampling and haplotypic diversity. Furthermore, we hope it will encourage livestock producers to adopt advanced technologies like genotyping and genomic selection, thereby contributing to the advancement of livestock genetics.
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