Detecting morphological convergence in true fungi, using 18S rRNA gene sequence data.

Area of Science:

• Mycology
• Molecular Biology
• Evolutionary Biology

Background:

• Fungal classification traditionally relies on morphology, but reduced or simplified traits can lead to ambiguous phylogenetic relationships.
• The 18S ribosomal DNA (rDNA) gene is a widely used marker for inferring evolutionary history due to its conserved and variable regions.

Purpose of the Study:

• To evaluate the congruence between phylogenetic relationships inferred from 18S ribosomal DNA (rDNA) sequence data and traditional morphological classifications in true fungi.
• To investigate instances where morphological data conflicts with molecular phylogenies and to explore potential causes, such as varying evolutionary rates.

Main Methods:

• Phylogenetic analyses were conducted using 18S ribosomal DNA sequence data from various fungal lineages.
• Morphological characteristics and biochemical data were compared with the molecular phylogenetic results.
• Statistical support for clades and evolutionary rates across lineages were assessed.

Main Results:

• 18S rDNA sequence data generally agree with morphology for fungi with distinct diagnostic characters, provided statistically supported clades and comparable evolutionary rates.
• Molecular data support the traditional fungal subdivisions Ascomycotina and Basidiomycotina.
• Discrepancies were observed, with some zygomycetes grouping with chytrid water molds, potentially due to unequal rates of nucleotide substitution. Molecular data resolved taxonomic ambiguities in Ascomycetes, revealing yeasts as polyphyletic and identifying convergent evolution of spore discharge.

Conclusions:

• 18S rDNA sequence data offer a robust framework for fungal phylogeny, often corroborating morphological classifications.
• Molecular phylogenetics provides crucial insights into fungal evolution, particularly for groups with simplified morphology, resolving long-standing taxonomic uncertainties.
• The study highlights the importance of integrating molecular and morphological data for accurate fungal classification and understanding evolutionary processes.