Mating-Type Imputation (MTI) provides an efficient tool for the mating-type inference of tetrapolar fungi

Abstract

Mating-type identification is fundamental for the genetic diversity and genetic breeding study 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 their hybridization experiments; however, the process is rather complex, time-consuming and error-prone for large-scale hybridization experiments. In this study, we developed the Mating-Type Imputation (MTI) software for automatic, rapid and accurate monokaryon mating-type inference for tetrapolar fungi using a combinatorial pruning traversal algorithm. Taking the compatibility matrix from 435 hybridization experiments of 30 Flammulina velutipes monokaryons as an example, MTI takes a few minutes to infer the accurate mating-types of all monokaryons, which might take several days for manual inference by experienced investigators. Furthermore, MTI enables us to investigate how false-positives and false-negatives influence mating-type inference results. Using simulated compatibility matrix, we found that MTI could accurately detect potential false-negatives in compatibility and successfully infer the true mating-type combination with limited false-negatives, but the tool could be misled by any false-positives to result in a wrong mating-type combination, indicating that false-positives records in hybridization experiments should be strictly obviated for mating-type inferences. In summary, MTI provides an efficient tool for mating-type inference of tetrapolar fungi, offering technical support for the research paradigm in mating-type studies of edible and medicinal fungi and holding significant theoretical value and broad application prospects in the fields of fungal genetic diversity and breeding studies.