Mating-type identification is fundamental to studies of genetic diversity and genetic breeding in fungi, especially for tetrapolar basidiomycetes, whose mating types are determined by two multiallelic loci, A and B. Traditional mating-type identification of monokaryons relies on manual inference based on hybridization experiments; however, this process is highly complex, time-consuming, and error-prone when applied to large-scale studies. In this study, we isolated 30 monokaryons from protoplasts derived from 15 dikaryons of Flammulina velutipes and developed a software tool, Mating-Type Imputation (MTI), to automatically, rapidly, and accurately infer monokaryon mating types in tetrapolar fungi using a combinatorial pruning traversal algorithm. Using a compatibility matrix derived from 435 hybridization experiments involving these 30 monokaryons, MTI required only a few minutes to accurately infer the mating types of all monokaryons-a task that typically takes several days for manual inference by experienced investigators. Furthermore, MTI enabled us to investigate how false-positive and false-negative interactions influence mating-type inference results. Using a simulated compatibility matrix, we found that MTI could accurately detect potential false negatives in compatibility and successfully infer the true mating-type combinations even in the presence of limited false negatives; conversely, the tool was easily misled by any false positives, resulting in incorrect mating-type combinations. This indicates that false-positive records in hybridization experiments must be strictly eliminated during mating-type inference. In summary, MTI provides an efficient tool for inferring the mating types of tetrapolar fungi, offering technical support for mating-type studies of edible and medicinal fungi, and holds significant theoretical value and broad application potential in the fields of fungal genetic diversity and breeding research.
Yu et al. (Fri,) studied this question.