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

Area of Science:

• Mycology
• Genetics
• Bioinformatics

Background:

• Mating-type identification is crucial for fungal genetic diversity and breeding.
• Tetrapolar basidiomycetes have complex mating systems controlled by two loci (A and B).
• Traditional manual mating-type inference is laborious and prone to errors in large-scale studies.

Purpose of the Study:

• To develop an automated software tool for accurate mating-type inference in tetrapolar fungi.
• To compare the efficiency of the automated tool against traditional manual methods.
• To investigate the impact of experimental errors on mating-type inference.

Main Methods:

• Isolated 30 monokaryons from *Flammulina velutipes*.
• Developed the Mating-Type Imputation (MTI) software using a combinatorial pruning traversal algorithm.
• Utilized a compatibility matrix from 435 hybridization experiments for validation.

Main Results:

• MTI accurately inferred mating types of 30 monokaryons in minutes, significantly faster than manual methods.
• The tool successfully identified false negatives in compatibility data.
• False positives in experimental data led to incorrect mating-type assignments, highlighting the need for data accuracy.

Conclusions:

• MTI offers an efficient, rapid, and accurate solution for mating-type identification in tetrapolar fungi.
• The software provides essential technical support for fungal genetic diversity and breeding research.
• MTI has broad application potential for edible and medicinal fungi studies.