Mating-Type Imputation (MTI) Provides an Efficient Tool for the Mating-Type Inference of Tetrapolar Fungi

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.