UC Berkeley

The work presented in this dissertation involves the interpretation of patterns of DNA and gene expression variation to infer ways in which evolutionary events and processes have shaped the life histories of species of filamentous fungi within the genus Neurospora.

The first chapter involves a comparison between genome sequences from both mating types of the self-fertile fungus Neurospora tetrasperma. Self-fertility in this species is associated with a large, sex-linked region of suppressed recombination. The structural rearrangements involved in the suppression of recombination are identified here for the first time and a model for the evolution of this non-recombining chromosomal region is developed. Additionally, evidence is presented that suggests the mat a-linked region of suppressed recombination is accumulating deleterious alleles at a faster rate than the mat A-linked region and thus may be in the early stages of degeneration.

Discovering the genetic basis behind adaptive phenotypes has long been considered the holy grail of evolutionary genetics, yet most instances where adaptive alleles have been identified involved targeting candidate genes based on their having a function related to an obvious phenotype such as pigmentation. This forward-ecology approach is difficult for most fungi because they lack obvious phenotypes. In the second chapter of this dissertation, a reverse-ecology approach is utilized to identify candidate genes involved in local adaptation to cold temperature in two recently diverged populations of Neurospora crassa. High-resolution genome scans between populations were performed to identify genomic islands of extreme divergence. Two such islands were identified and found to contain genes whose functions, pattern of nucleotide polymorphism, and null phenotype are consistent with local adaptation.

The third chapter extends the DNA-based analyses presented in the second chapter to explore natural variation in gene expression within and between these same N. crassa populations. Intrapopulation variation in gene expression is harnessed to identify regulatory modules and to provide a tool for inferring functional information for unannotated genes. Divergence in regulatory networks between populations is assessed, providing insight into potential functional differences between these populations.