ParthenoGenius: A User-Friendly Heuristic for Inferring Presence and Mechanism of Facultative Parthenogenesis from Genetic and Genomic Data Sets

Abstract Facultative parthenogenesis (FP), or asexual reproduction by sexually-reproducing female animals, has been reported across several clades of vertebrates and is increasingly being recognized as a reproductive mechanism with significant implications for the genetic variation of captive and wild populations. The definitive identification of parthenogens requires molecular confirmation, with large genomic data sets necessary to accurately parse the parthenogenetic mechanism (i.e., endoduplication, gametic duplication, terminal fusion automixis, or central fusion automixis). Current methods for inferring FP from large genomic data sets are statistically intensive, require competency in R scripting for their execution, and are not designed for detection of facultative parthenogenesis or screening of large numbers of mother/offspring pairs, whereas small data sets (i.e., microsatellites) that can be evaluated visually lack the power to discriminate among FP mechanisms. Here, we present the user-friendly software program, ParthenoGenius, that uses intuitive logic to infer presence and mechanism of FP from even large genomic data sets comprising many mothers and offspring. ParthenoGenius runs relatively quickly and does not require the researcher to have knowledge of R scripting or statistics. ParthenoGenius was tested on eight empirical data sets, and in each case identified parthenogens (and parthenogenic mechanism when present) consistent with results of previous studies or corroborating evidence. ParthenoGenius will facilitate the rapid screening of large genomic data sets comprising many mothers and offspring for the presence and mechanism of parthenogenesis, improving our understanding of the frequency and phylogenetic distribution of FP across the animal kingdom.