From elements to modules: regulatory evolution in Ascomycota fungi

available in PMC 2010 April 12.Regulatory divergence is likely a major driving force in evolution. Comparative transcriptomics provides a new glimpse into the evolution of gene regulation. Ascomycota fungi are uniquely suited among eukaryotes for studies of regulatory evolution, because of broad phylogenetic scope, many sequenced genomes, and facility of genomic analysis. Here we review the substantial divergence in gene expression in Ascomycota and how this is reconciled with the modular organization of transcriptional networks. We show that flexibility and redundancy in both cis-regulation and trans-regulation can lead to changes from altered expression of single genes to wholesale rewiring of regulatory modules. Redundancy thus emerges as a major driving force facilitating expression divergence while preserving the coherent functional organization of a transcriptional response.National Library of Medicine (U.S.) (NLM training grant 5T15LM007359)Burroughs Wellcome Fund (Career Award at the Scientific Interface)National Institute of General Medical Sciences (U.S.) (NIGMS R01GM083989-01)National Science Foundation (U.S.) (CAREER award (#0447887))Human Frontier Science Program (Strasbourg, France) (Research grant)Alfred P. Sloan FoundationNational Institutes of Health (U.S.) (PIONEER award

Comparative genomics of xylose-fermenting fungi for enhanced biofuel production

Cellulosic biomass is an abundant and underused substrate for biofuel production. The inability of many microbes to metabolize the pentose sugars abundant within hemicellulose creates specific challenges for microbial biofuel production from cellulosic material. Although engineered strains of Saccharomyces cerevisiae can use the pentose xylose, the fermentative capacity pales in comparison with glucose, limiting the economic feasibility of industrial fermentations. To better understand xylose utilization for subsequent microbial engineering, we sequenced the genomes of two xylose-fermenting, beetle-associated fungi, Spathaspora passalidarum and Candida tenuis. To identify genes involved in xylose metabolism, we applied a comparative genomic approach across 14 Ascomycete genomes, mapping phenotypes and genotypes onto the fungal phylogeny, and measured genomic expression across five Hemiascomycete species with different xylose-consumption phenotypes. This approachimplicated many genes and processes involved in xylose assimilation. Several of these genes significantly improved xylose utilization when engineered into S. cerevisiae, demonstrating the power of comparative methods in rapidly identifying genes for biomass conversion while reflecting on fungal ecology

Comparative genomics of xylose-fermenting fungi for enhanced biofuel production

Cellulosic biomass is an abundant and underused substrate for biofuel production. The inability of many microbes to metabolize the pentose sugars abundant within hemicellulose creates specific challenges for microbial biofuel production from cellulosic material. Although engineered strains of Saccharomyces cerevisiae can use the pentose xylose, the fermentative capacity pales in comparison with glucose, limiting the economic feasibility of industrial fermentations. To better understand xylose utilization for subsequent microbial engineering, we sequenced the genomes of two xylose-fermenting, beetle-associated fungi, Spathaspora passalidarum and Candida tenuis. To identify genes involved in xylose metabolism, we applied a comparative genomic approach across 14 Ascomycete genomes, mapping phenotypes and genotypes onto the fungal phylogeny, and measured genomic expression across five Hemiascomycete species with different xylose-consumption phenotypes. This approachimplicated many genes and processes involved in xylose assimilation. Several of these genes significantly improved xylose utilization when engineered into S. cerevisiae, demonstrating the power of comparative methods in rapidly identifying genes for biomass conversion while reflecting on fungal ecology

Analysis of the Arabidopsis Histidine Kinase ATHK1 Reveals a Connection between Vegetative Osmotic Stress Sensing and Seed Maturation[W][OA]

To cope with water stress, plants must be able to effectively sense, respond to, and adapt to changes in water availability. The Arabidopsis thaliana plasma membrane His kinase ATHK1 has been suggested to act as an osmosensor that detects water stress and initiates downstream responses. Here, we provide direct genetic evidence that ATHK1 not only is involved in the water stress response during early vegetative stages of plant growth but also plays a unique role in the regulation of desiccation processes during seed formation. To more comprehensively identify genes involved in the downstream pathways affected by the ATHK1-mediated response to water stress, we created a large-scale summary of expression data, termed the AtMegaCluster. In the AtMegaCluster, hierarchical clustering techniques were used to compare whole-genome expression levels in athk1 mutants with the expression levels reported in publicly available data sets of Arabidopsis tissues grown under a wide variety of conditions. These experiments revealed that ATHK1 is cotranscriptionally regulated with several Arabidopsis response regulators, together with two proteins containing novel sequences. Since overexpression of ATHK1 results in increased water stress tolerance, our observations suggest a new top-down route to increasing drought resistance via receptor-mediated increases in sensing water status, rather than through genetically engineered changes in downstream transcription factors or specific osmolytes

Genome-wide association across <i>Saccharomyces cerevisiae</i> strains reveals substantial variation in underlying gene requirements for toxin tolerance

<div><p>Cellulosic plant biomass is a promising sustainable resource for generating alternative biofuels and biochemicals with microbial factories. But a remaining bottleneck is engineering microbes that are tolerant of toxins generated during biomass processing, because mechanisms of toxin defense are only beginning to emerge. Here, we exploited natural diversity in 165 <i>Saccharomyces cerevisiae</i> strains isolated from diverse geographical and ecological niches, to identify mechanisms of hydrolysate-toxin tolerance. We performed genome-wide association (GWA) analysis to identify genetic variants underlying toxin tolerance, and gene knockouts and allele-swap experiments to validate the involvement of implicated genes. In the process of this work, we uncovered a surprising difference in genetic architecture depending on strain background: in all but one case, knockout of implicated genes had a significant effect on toxin tolerance in one strain, but no significant effect in another strain. In fact, whether or not the gene was involved in tolerance in each strain background had a bigger contribution to strain-specific variation than allelic differences. Our results suggest a major difference in the underlying network of causal genes in different strains, suggesting that mechanisms of hydrolysate tolerance are very dependent on the genetic background. These results could have significant implications for interpreting GWA results and raise important considerations for engineering strategies for industrial strain improvement.</p></div

<i>LEU3</i> is important for SynH tolerance.

<p>(A) Wild-type YPS128 and a YPS128 <i>leu3Δ</i> mutant were grown in Synthetic Complete medium (SC), SynH without toxins (SynH -HT), or SynH with toxins, and final OD₆₀₀ was measured after 24 hours. (B) Final OD₆₀₀ was also measured in strains grown in media with 10X SC concentration of branched amino acids (leucine, isoleucine, and valine) in SynH -HT and SynH. Data represent average of 3 replicates with standard deviation. Significance was determined by paired t-test.</p

SNPs associated with SynH tolerance.

<p>SNPs associated with SynH tolerance.</p

Genetic diversity found in the 165-strain collection.

<p>The entire collection of high quality SNPs (486,302) was used as input for principal component analysis (PCA) (A) and to generate a neighbor-joining (NJ) tree (B). Populations assigned in circles were defined manually using published population structure data. Strains are color-coded according to genetic similarity, with matching colors between the PCA and NJ tree (generated by Adegenet [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007217#pgen.1007217.ref110" target="_blank">110</a>]). The population and/or niche is represented by the key, with the number of strains in each group indicated in parentheses.</p

Strain-specific difference for SynH and HT tolerance.

<p>Tolerance to lignocellulosic hydrolysate across strains (left) and across each population (right) measured as glucose consumption in SynH (A) and HT tolerance based on glucose consumption (B), calculated as described in Methods for 165 strains. Individual strains in B were ordered based on the quantitative scores in A. Population distributions shown in the boxplots are indicated for named populations from <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007217#pgen.1007217.g001" target="_blank">Fig 1</a>.</p