The Hyphal Tip: Fungal Genomes and Comparative Genomics

A link to the story about Matteo Garbelotto's work on Phytophthora ramorum and showing that the source in California is likely from ornamentals from a nursery. The work is to appear soon in Molecular Ecology but alas is not available yet.

A recent paper on updated Phytophthora phylogeny from Jamie Blair and co-authors is also out in FGB.

Estimating divergence times is notorious difficult and the field can be downright rancorous with some being accused of reading tea leaves and chicken entrails - interesting reading for personalities as much as the different scientific approaches. There are several different approaches to trying to estimate a divergence time among species, using calibration points usually anchored by fossil data. Molecular clock methods have problems sometimes producing extremely old dates that are quite hotly debated. In fungi we have a very few fossils (and their placement on the phylogeny is debated).

There are quite a few available methods for reconstructing divergence times including r8s and multidivtime which start with various types of trees and use calibration time points that are typically informed by fossil dates. The simplest approaches assume a molecular clock (rates are same across the tree) and then one only needs to calibrate the number of substitutions (or rate really) to time to determine how phylogenetic tree branch lengths map to time. The BEAST package also does phylogenetic inference and divergence time estimation (and provided the necessary analysis for exoneration of the Tripoli Six) across a sample of trees. BEAST (and MrBayes) use MCMC to sample the space of parameters and tree space to identify phylogenies and evolutionary parameters that explain the data (an alignment of sequences).

A paper from Akerborg and colleagues introduces a new approach that uses MCMC but apply a few twists, using a birth-death model that doesn't assume a molecular clock and employing a hill-climbing algorithm instead of MCMC to find parameter optima. They use a Maximum a posterior (MAP) framework which is more computational efficient than MCMC. They couple the MAP approach with a dynamic-programming approach that separates the estimation of rates (branch length) from the estimation of times (which often require assumption of a molecular clock). While I can't speak with much authority on the MAP approach or yet how well this compares on different datasets, it suggests a different method to tackle these problems. They authors point out one drawback with their approach is it only allows for derivation of point-estimates so statistical confidences like bootstrap support are not easily calculated through this approach. Their software, called PRIME is available here and I will be curious to see how it performs in other peoples' hands.

Akerborg, O., Sennblad, B., Lagergren, J. (2008). Birth-death prior on phylogeny and speed dating. BMC Evolutionary Biology, 8(1), 77. DOI: 10.1186/1471-2148-8-77

A review in Plant Cell from Darren Soanes and colleagues summarizes some of the major findings about evolution of phytopathogenic fungi gleaned from genome sequencing highlighting 12 fungi and 2 oomycetes. By mapping evolution of genes identified as virulence factors as well as genes that appear to have similar patterns of diversification, we can hope to derive some principals about how phytopathogenic fungi have evolved from saprophyte ancestors.

Fungi, like most organisms, take an active role in finding food for survival. When thinking about hostile takeovers by fungi, one probably thinks about mycelia growing towards nutrients, rotting plant matter, the ability to extract nutrients from a living host, or perhaps producing toxins or secondary metabolites that can affect the host. However, some fungi can take an even more active role and trap their animal hosts (when that animal isn't much bigger than you). A paper from earlier this year on "Evolution of nematode-trapping cells of predatory fungi of the Orbiliaceae based on evidence from rRNA-encoding DNA and multiprotein sequences" describes the evolutionary history of a group of fungi able to trap and eat nematodes. Nematode trapping fungi have been investigated experimentally since at least the 30s (Drechsler, Mycologia. 1937, Drechsler, J Wash Acad Sci. 1933), and some more recent studies of the relationship of the groups (Rubner, Studies in Mycology. 1996). In the recent PNAS paper, the authors used multi-locus sequencing to reconstruct a phylogeny and history of large group of carnivorous fungi and reconstruct the ancestral history the prey trapping mechanism of either through constricting rings or adhesive traps. They were able to reconstruct the likely order of the evolutionary steps needed to make the stalk and trapping cells. They found that the most common type of trap, an Adhesive Network, was the earliest evolved trap. Some movies also demonstrate how these fungi make their living.

Back from ISMB/ECCB and a mountain of things left undone that somehow still need doing ... including a quick entry about what was interesting at the conference.

Perhaps not a surprise to anyone that has dabbled in evolutionary analysis of proteins, Kawahara and Imanishi (BMC Evolutionary Biology 2007) confirm that not every protein evolves via a molecular clock in Saccharomyces sensu scricto. Using everyone's favorite evolutionary tool, PAML, the authors identify protein lineages via a whole genome scan that evolve relatively slow or

The Candida clade of Hemiascomycete fungi have received much attention from funding bodies so that many genomic and experimental resources are available address questions of pathogenecity and industrial applications of these species.

The Candida genus

Traditionally, species of yeasts that were thought to be asexual were given the genus name Candida. This has lead to Candida being a sort of taxonomic rubbish bin.