The fungal kingdom is too large to be discovered exclusively by classical genetics. The access to omics data opens a new opportunity to study the diversity within the fungal kingdom and how adaptation to new environments shapes fungal metabolism. Genomes are the foundation of modern science but their quality is crucial when analysing omics data. In this study, we demonstrate how one gold-standard genome can improve functional prediction across closely related species to be able to identify key enzymes, reactions and pathways with the focus on primary carbon metabolism.

Based on this approach we identified alternative genes encoding various steps of the different sugar catabolic pathways, and as such provided leads for functional studies into this topic. We also revealed significant diversity with respect to genome content, although this did not always correlate to the ability of the species to use the corresponding sugar as a carbon source.

真菌王国太大了，无法通过经典遗传学专门发现。组学数据的访问为研究真菌界内的多样性以及适应新环境如何影响真菌代谢提供了新的机会。基因组是现代科学的基础，但是在分析组学数据时，基因组的质量至关重要。在这项研究中，我们证明了一个金标准基因组如何能够改善紧密相关物种的功能预测，从而能够识别主要的碳代谢的关键酶，反应和途径。

基于此方法，我们确定了编码不同糖代谢途径各个步骤的替代基因，因此为该主题的功能研究提供了线索。我们还揭示了基因组含量方面的显着多样性，尽管这并不总是与物种使用相应糖作为碳源的能力相关。