ParthenoGenius: A user-friendly heuristic for inferring presence and mechanism of facultative parthenogenesis from genetic and genomic datasets.

The article focuses on the development and validation of ParthenoGenius, a user-friendly Python software designed to detect facultative parthenogenesis (FP)—asexual reproduction by sexually reproducing female vertebrates—and to infer its underlying cytological mechanisms from large genetic or genomic parentage datasets. ParthenoGenius uses heuristic logic to analyze maternal and offspring genotypes, distinguishing parthenogenetic offspring from sexually produced ones and identifying mechanisms such as gametic duplication, terminal fusion automixis, central fusion automixis, or endoduplication. Tested on simulated and multiple published and novel datasets across diverse vertebrate taxa, ParthenoGenius produced results consistent with previous studies, demonstrating rapid run times and ease of use without requiring advanced statistical or scripting skills. While effective for large SNP datasets, the program’s accuracy depends on appropriate error rate settings and may have limited power with small microsatellite datasets; it is intended as a screening tool to facilitate further detailed analyses and improve understanding of FP’s frequency and evolutionary significance in wild and captive populations.