A microbial population-species interface: nested cladistic and coalescent inference with multilocus data.

Area of Science:

• Mycology
• Evolutionary Biology
• Population Genetics

Background:

• Sclerotinia is a haploid, plant parasitic fungus with significant ecological and agricultural impact.
• Understanding the evolutionary history and divergence of Sclerotinia populations and species is crucial for disease management and evolutionary studies.

Purpose of the Study:

• To distinguish divergence times between populations and species of the fungus Sclerotinia.
• To reconstruct the evolutionary history of haplotypes at both population and species scales.
• To investigate phylogeographic processes and define the boundary between divergent populations and species.

Main Methods:

• Utilized sequence data from seven nuclear loci across 385 Sclerotinia isolates.
• Reconstructed haplotype evolutionary history using parsimony, maximum likelihood, and coalescent methods.
• Analyzed recombination blocks and inferred alternative networks to reduce uncertainty.

Main Results:

• Successfully distinguished divergence times for Sclerotinia populations and species.
• Identified consistent phylogeographic processes using modified cladistic and coalescent approaches.
• Defined the population-species boundary as a temporal interval between coalescence events.

Conclusions:

• The study provides a robust framework for understanding fungal evolutionary history and divergence.
• Recombination analysis effectively reduced uncertainty in evolutionary network inference.
• The findings offer insights into the speciation process in plant parasitic fungi.