Fungal regulatory evolution: cis and trans in the balance

Polyphasic Characterization of the Biocontrol Potential of a Novel Strain of Trichoderma atroviride Isolated from Central Mexico

This work describes the characterization of Trichoderma atroviride strain CMU-08, isolated from Michoacán, Mexico. CMU-08 demonstrated robust growth and conidiation across a temperature range from 16 to 32 °C and a pH range from 4 to 9 on potato dextrose agar (PDA) and malt extract agar (MEA) media. The strain is an efficient antagonist of six species of phytopathogenic fungi and oomycetes in PDA, MEA, and Vogel minimal medium (VMM). Antagonist mechanisms of CMU-08 included direct mycoparasitism observed in dual-culture assays, as well as antibiosis attributed to growth inhibition via both volatile and non-volatile metabolites, with the effectiveness varying depending on the test phytopathogen and culture medium. Extracellular filtrates (ECFs) recovered from liquid cultures of CMU-08 under basal and induced conditions using Botrytis cinerea cell walls significantly inhibited their growth at a concentration of 750 µg/mL. Moreover, in detached tomato leaf assays, these ECFs reduced foliar damage caused by B. cinerea by 24-34%. The volatile organic compounds (VOCs) produced by CMU-08 also exhibited substantial efficacy, reducing foliar damage by up to 50% in similar tests. Despite showing no basal extracellular chitinase enzymatic activity, CMU-08 demonstrated significant induction of this activity in cultures supplemented with B. cinerea and Fusarium sp. cell walls. Four genes encoding extracellular chitinases (chit33, chit36, ech42, and locus 217415) showed different dynamics of transcriptional regulation during the dual-culture confrontation of strain CMU-08 with B. cinerea and Fusarium sp., varying according to the phytopathogen and the interaction stage. The CMU-08 strain shows physiological versatility and employs a variety of antagonist mechanisms toward different species of phytopathogenic microorganisms, making it a good candidate for developing a biocontrol product for field application.

Data integration for inferring context-specific gene regulatory networks

Transcriptional regulatory networks control context-specific gene expression patterns and play important roles in normal and disease processes. Advances in genomics are rapidly increasing our ability to measure different components of the regulation machinery at the single-cell and bulk population level. An important challenge is to combine different types of regulatory genomic measurements to construct a more complete picture of gene regulatory networks across different disease, environmental, and developmental contexts. In this review, we focus on recent computational methods that integrate regulatory genomic data sets to infer context specificity and dynamics in regulatory networks.

Integrative Omics Analysis Reveals a Limited Transcriptional Shock After Yeast Interspecies Hybridization

The formation of interspecific hybrids results in the coexistence of two diverged genomes within the same nucleus. It has been hypothesized that negative epistatic interactions and regulatory interferences between the two sub-genomes may elicit a so-called genomic shock involving, among other alterations, broad transcriptional changes. To assess the magnitude of this shock in hybrid yeasts, we investigated the transcriptomic differences between a newly formed Saccharomyces cerevisiae × Saccharomyces uvarum diploid hybrid and its diploid parentals, which diverged ∼20 mya. RNA sequencing (RNA-Seq) based allele-specific expression (ASE) analysis indicated that gene expression changes in the hybrid genome are limited, with only ∼1-2% of genes significantly altering their expression with respect to a non-hybrid context. In comparison, a thermal shock altered six times more genes. Furthermore, differences in the expression between orthologous genes in the two parental species tended to be diminished for the corresponding homeologous genes in the hybrid. Finally, and consistent with the RNA-Seq results, we show a limited impact of hybridization on chromatin accessibility patterns, as assessed with assay for transposase-accessible chromatin using sequencing (ATAC-Seq). Overall, our results suggest a limited genomic shock in a newly formed yeast hybrid, which may explain the high frequency of successful hybridization in these organisms.

Evolution of reduced co-activator dependence led to target expansion of a starvation response pathway

Although combinatorial regulation is a common feature in gene regulatory networks, how it evolves and affects network structure and function is not well understood. In S. cerevisiae, the phosphate starvation (PHO) responsive transcription factors Pho4 and Pho2 are required for gene induction and survival during phosphate starvation. In the related human commensal C. glabrata, Pho4 is required but Pho2 is dispensable for survival in phosphate starvation and is only partially required for inducing PHO genes. Phylogenetic survey suggests that reduced dependence on Pho2 evolved in C. glabrata and closely related species. In S. cerevisiae, less Pho2-dependent Pho4 orthologs induce more genes. In C. glabrata, its Pho4 binds to more locations and induces three times as many genes as Pho4 in S. cerevisiae does. Our work shows how evolution of combinatorial regulation allows for rapid expansion of a gene regulatory network’s targets, possibly extending its physiological functions.

The diversity of life on Earth has intrigued generations of scientists and nature lovers alike. Research over recent decades has revealed that much of the diversity we can see did not require the invention of new genes. Instead, living forms diversified mostly by using old genes in new ways – for example, by changing when or where an existing gene became active. This kind of change is referred to as “regulatory evolution”.

A class of proteins called transcription factors are hot spots in regulatory evolution. These proteins recognize specific sequences of DNA to control the activity of other genes, and so represent the “readers” of the genetic information. Small changes to how a transcription factor is regulated, or the genes it targets, can lead to dramatic changes in an organism. Before we can understand how life on Earth evolved to be so diverse, scientists must first answer how transcription factors evolve and what consequences this has on their target genes.

So far, most studies of regulatory evolution have focused on networks of transcription factors and genes that control how an organism develops. He et al. have now studied a regulatory network that is behind a different process, namely how an organism responds to stress or starvation. These two types of regulatory networks are structured differently and work in different ways. These differences made He et al. wonder if the networks evolved differently too.

The chemical phosphate is an essential nutrient for all living things, and He et al. compared how two different species of yeast responded to a lack of phosphate. The key difference was how much a major transcription factor known as Pho4 depended on a so-called co-activator protein named Pho2 to carry out its role. Baker’s yeast (Saccharomyces cerevisiae), which is commonly used in laboratory experiments, requires both Pho4 and Pho2 to activate about 20 genes when inorganic phosphate is not available in its environment. However, in a related yeast species called Candida glabrata, Pho4 has evolved to depend less on Pho2. He et al. went on to show that, as well as being less dependent on Pho2, Pho4 in C. glabrata activates more than three times as many genes as Pho4 in S. cerevisiae does in the absence of phosphate. These additional gene targets for Pho4 in C. glabrata are predicted to extend the network’s activities, and allow it to regulate new process including the yeast’s responses to other types of stress and the building of the yeast’s cell wall.

Together these findings show a new way that regulatory networks can evolve, that is, by reducing its dependence on the co-activator, a transcription factor can expand the number of genes it targets. This has not been seen for regulatory networks related to development, suggesting that different networks can indeed evolve in different ways. Lastly, because disease-causing microbes are often stressed inside their hosts and C. glabrata sometimes infects humans, understanding how this yeast’s response to stress has evolved may lead to new ways to prevent and treat this infection.

Natural gene expression variation studies in yeast

The rise of sequence information across different yeast species and strains is driving an increasing number of studies in the emerging field of genomics to associate polymorphic variants, mRNA abundance and phenotypic differences between individuals. Here, we gathered evidence from recent studies covering several layers that define the genotype-phenotype gap, such as mRNA abundance, allele-specific expression and translation efficiency to demonstrate how genetic variants co-evolve and define an individual's genome. Moreover, we exposed several antecedents where inter- and intra-specific studies led to opposite conclusions, probably owing to genetic divergence. Future studies in this area will benefit from the access to a massive array of well-annotated genomes and new sequencing technologies, which will allow the fine breakdown of the complex layers that delineate the genotype-phenotype map. Copyright © 2016 John Wiley & Sons, Ltd.

Reconstruction and Analysis of the Evolution of Modular Transcriptional Regulatory Programs Using Arboretum

Comparative functional genomics aims to measure and compare genome-wide functional data such as transcriptomes, proteomes, and epigenomes across multiple species to study the conservation and divergence patterns of such quantitative measurements. However, computational methods to systematically compare these quantitative genomic profiles across multiple species are in their infancy. We developed Arboretum, a novel algorithm to identify modules of co-expressed genes and trace their evolutionary history across multiple species from a complex phylogeny. To interpret the results from Arboretum we developed several measures to examine the extent of conservation and divergence in modules and their relationship to species lifestyle, cis-regulatory elements, and gene duplication. We applied Arboretum to study the evolution of modular transcriptional regulatory programs controlling transcriptional response to different environmental stresses in the yeast Ascomycota phylogeny. We found that modules of similar patterns of expression captured the transcriptional responses to different stresses across species; however, the genes exhibiting these patterns were not the same. Divergence in module membership was associated with changes in lifestyle and specific clades and that gene duplication was a major factor contributing to the divergence of module membership.

Evolution of regulatory networks in Candida glabrata: learning to live with the human host

The opportunistic human fungal pathogen Candida glabrata is second only to C. albicans as the cause of Candida infections and yet is more closely related to Saccharomyces cerevisiae. Recent advances in functional genomics technologies and computational approaches to decipher regulatory networks, and the comparison of these networks among these and other Ascomycete species, have revealed both unique and shared strategies in adaptation to a human commensal/opportunistic pathogen lifestyle and antifungal drug resistance in C. glabrata. Recently, several C. glabrata sister species in the Nakeseomyces clade representing both human associated (commensal) and environmental isolates have had their genomes sequenced and analyzed. This has paved the way for comparative functional genomics studies to characterize the regulatory networks in these species to identify informative patterns of conservation and divergence linked to phenotypic evolution in the Nakaseomyces lineage.

Comparative analysis of gene regulatory networks: from network reconstruction to evolution

Regulation of gene expression is central to many biological processes. Although reconstruction of regulatory circuits from genomic data alone is therefore desirable, this remains a major computational challenge. Comparative approaches that examine the conservation and divergence of circuits and their components across strains and species can help reconstruct circuits as well as provide insights into the evolution of gene regulatory processes and their adaptive contribution. In recent years, advances in genomic and computational tools have led to a wealth of methods for such analysis at the sequence, expression, pathway, module, and entire network level. Here, we review computational methods developed to study transcriptional regulatory networks using comparative genomics, from sequence to functional data. We highlight how these methods use evolutionary conservation and divergence to reliably detect regulatory components as well as estimate the extent and rate of divergence. Finally, we discuss the promise and open challenges in linking regulatory divergence to phenotypic divergence and adaptation.

Divergence and selectivity of expression-coupled histone modifications in budding yeasts

Various histone modifications are widely associated with gene expression, but their functional selectivity at individual genes remains to be characterized. Here, we identify widespread differences between genome-wide patterns of two prominent marks, H3K9ac and H3K4me3, in budding yeasts. As well as characteristic gene profiles, relative modification levels vary significantly amongst genes, irrespective of expression. Interestingly, we show that these differences couple to contrasting features: higher methylation to essential, periodically expressed, 'DPN' (Depleted Proximal Nucleosome) genes, and higher acetylation to non-essential, responsive, 'OPN' (Occupied Proximal Nucleosome) genes. Thus, H3K4me3 may generally associate with expression stability, and H3K9ac, with variability. To evaluate this notion, we examine their association with expression divergence between the closely related species, S. cerevisiae and S. paradoxus. Although individually well conserved at orthologous genes, changes between modifications are mostly uncorrelated, indicating largely non-overlapping regulatory mechanisms. Notably, we find that inter-species differences in methylation, but not acetylation, are well correlated with expression changes, thereby proposing H3K4me3 as a candidate regulator of expression divergence. Taken together, our results suggest distinct evolutionary roles for expression-linked modifications, wherein H3K4me3 may contribute to stabilize average expression, whilst H3K9ac associates with more indirect aspects such as responsiveness.

Evolutionary principles of modular gene regulation in yeasts

Divergence in gene regulation can play a major role in evolution. Here, we used a phylogenetic framework to measure mRNA profiles in 15 yeast species from the phylum Ascomycota and reconstruct the evolution of their modular regulatory programs along a time course of growth on glucose over 300 million years [corrected]. We found that modules have diverged proportionally to phylogenetic distance, with prominent changes in gene regulation accompanying changes in lifestyle and ploidy, especially in carbon metabolism. Paralogs have significantly contributed to regulatory divergence, typically within a very short window from their duplication. Paralogs from a whole genome duplication (WGD) event have a uniquely substantial contribution that extends over a longer span. Similar patterns occur when considering the evolution of the heat shock regulatory program measured in eight of the species, suggesting that these are general evolutionary principles. DOI:http://dx.doi.org/10.7554/eLife.00603.001.

Arboretum: reconstruction and analysis of the evolutionary history of condition-specific transcriptional modules

Comparative functional genomics studies the evolution of biological processes by analyzing functional data, such as gene expression profiles, across species. A major challenge is to compare profiles collected in a complex phylogeny. Here, we present Arboretum, a novel scalable computational algorithm that integrates expression data from multiple species with species and gene phylogenies to infer modules of coexpressed genes in extant species and their evolutionary histories. We also develop new, generally applicable measures of conservation and divergence in gene regulatory modules to assess the impact of changes in gene content and expression on module evolution. We used Arboretum to study the evolution of the transcriptional response to heat shock in eight species of Ascomycota fungi and to reconstruct modules of the ancestral environmental stress response (ESR). We found substantial conservation in the stress response across species and in the reconstructed components of the ancestral ESR modules. The greatest divergence was in the most induced stress, primarily through module expansion. The divergence of the heat stress response exceeds that observed in the response to glucose depletion in the same species. Arboretum and its associated analyses provide a comprehensive framework to systematically study regulatory evolution of condition-specific responses.

Population genomics and transcriptional consequences of regulatory motif variation in globally diverse Saccharomyces cerevisiae strains

Noncoding genetic variation is known to significantly influence gene expression levels in a growing number of specific cases; however, the patterns of genome-wide noncoding variation present within populations, the evolutionary forces acting on noncoding variants, and the relative effects of regulatory polymorphisms on transcript abundance are not well characterized. Here, we address these questions by analyzing patterns of regulatory variation in motifs for 177 DNA binding proteins in 37 strains of Saccharomyces cerevisiae. Between S. cerevisiae strains, we found considerable polymorphism in regulatory motifs across strains (mean π = 0.005) as well as diversity in regulatory motifs (mean 0.91 motifs differences per regulatory region). Population genetics analyses reveal that motifs are under purifying selection, and there is considerable heterogeneity in the magnitude of selection across different motifs. Finally, we obtained RNA-Seq data in 22 strains and identified 49 polymorphic DNA sequence motifs in 30 distinct genes that are significantly associated with transcriptional differences between strains. In 22 of these genes, there was a single polymorphic motif associated with expression in the upstream region. Our results provide comprehensive insights into the evolutionary trajectory of regulatory variation in yeast and the characteristics of a compendium of regulatory alleles.

Multiple genomic changes associated with reorganization of gene regulation and adaptation in yeast

Frequently during evolution, new phenotypes evolved due to novelty in gene regulation, such as that caused by genome rewiring. This has been demonstrated by comparing common regulatory sequences among species and by identifying single regulatory mutations that are associated with new phenotypes. However, while a single mutation changes a single element, gene regulation is accomplished by a regulatory network involving multiple interactive elements. Therefore, to better understand regulatory evolution, we have studied how mutations contributed to the adaptation of cells to a regulatory challenge. We created a synthetic genome rewiring in yeast cells, challenged their gene regulation, and studied their adaptation. HIS3, an essential enzyme for histidine biosynthesis, was placed exclusively under a GAL promoter, which is induced by galactose and strongly repressed in glucose. Such rewired cells were faced with significant regulatory challenges in a repressive glucose medium. We identified several independent mutations in elements of the GAL system associated with the rapid adaptation of cells, such as the repressor GAL80 and the binding sites of the activator GAL4. Consistent with the extraordinarily high rate of cell adaptation, new regulation emerged during adaptation via multiple trajectories, including those involving mutations in elements of the GAL system. The new regulation of HIS3 tuned its expression according to histidine requirements with or without these significant mutations, indicating that additional factors participated in this regulation and that the regulatory network could reorganize in multiple ways to accommodate different mutations. This study, therefore, stresses network plasticity as an important property for regulatory adaptation and evolution.

Gene expression in fungi

This contribution is based on the four presentations made at the Special Interest Group (SIG) meeting titled Gene Expression in Fungi held during IMC9 in Edinburgh. This overview is independent from other articles published or that will be published by each speaker. In the SIG meeting, basic principles of in vivo animal models for virulence studies were discussed. Infection associated genes of Candida albicans and fungal adaptation to the host was summarized. Azole susceptibility was evaluated as a combined result of several changes in expression of pertinent genes. Gene transfer in fungi, resulting in fungal evolution and gene adaptation to environmental factors, was reported.

Extensive divergence of yeast stress responses through transitions between induced and constitutive activation

Closely related species show a high degree of differences in gene expression, but the functional significance of these differences remains unclear. Similarly, stress responses in yeast typically involve differential expression of numerous genes, and it is unclear how many of these are functionally significant. To address these issues, we compared the expression programs of four yeast species under different growth conditions, and found that the response of these species to stress has diverged extensively. On an individual gene basis, most transcriptional responses are not conserved in any pair of species, and there are very limited common responses among all four species. We present evidence that many evolutionary changes in stress responses are compensated either (i) by the response of related genes or (ii) by changes in the basal expression levels of the genes whose responses have diverged. Thus, stress-related genes are often induced upon stress in some species but maintain high levels even in the absence of stress at other species, indicating a transition between induced and constitutive activation. In addition, ~15% of the stress responses are specific to only one of the four species, with no evidence for compensating effects or stress-related annotations, and these may reflect fortuitous regulation that is unimportant for the stress response (i.e., biological noise). Frequent compensatory changes and biological noise may explain how diverged expression responses support similar physiological responses.

Inferring regulatory mechanisms from patterns of evolutionary divergence

The number of sequenced species is increasing at a staggering rate, calling for new approaches for incorporating evolutionary information in the study of biological mechanisms. Evolutionary conservation is widely used for assigning a function to new proteins and for predicting functional coding or non-coding sequences. Here, we argue for a complementary approach that focuses on the divergence of regulatory programs. Regulatory mechanisms can be learned from patterns of evolutionary divergence in regulatory properties such as gene expression, transcription factor binding or nucleosome positioning. We review examples of this concept using yeast as a model system, and highlight a hybrid-based approach that is highly instrumental in this analysis.

Evidence of association between nucleosome occupancy and the evolution of transcription factor binding sites in yeast

Background

Divergence of transcription factor binding sites is considered to be an important source of regulatory evolution. The associations between transcription factor binding sites and phenotypic diversity have been investigated in many model organisms. However, the understanding of other factors that contribute to it is still limited. Recent studies have elucidated the effect of chromatin structure on molecular evolution of genomic DNA. Though the profound impact of nucleosome positions on gene regulation has been reported, their influence on transcriptional evolution is still less explored. With the availability of genome-wide nucleosome map in yeast species, it is thus desirable to investigate their impact on transcription factor binding site evolution. Here, we present a comprehensive analysis of the role of nucleosome positioning in the evolution of transcription factor binding sites.

Results

We compared the transcription factor binding site frequency in nucleosome occupied regions and nucleosome depleted regions in promoters of old (orthologs among Saccharomycetaceae) and young (Saccharomyces specific) genes; and in duplicate gene pairs. We demonstrated that nucleosome occupied regions accommodate greater binding site variations than nucleosome depleted regions in young genes and in duplicate genes. This finding was confirmed by measuring the difference in evolutionary rates of binding sites in sensu stricto yeasts at nucleosome occupied regions and nucleosome depleted regions. The binding sites at nucleosome occupied regions exhibited a consistently higher evolution rate than those at nucleosome depleted regions, corroborating the difference in the selection constraints at the two regions. Finally, through site-directed mutagenesis experiment, we found that binding site gain or loss events at nucleosome depleted regions may cause more expression differences than those in nucleosome occupied regions.

Conclusions

Our study indicates the existence of different selection constraint on binding sites at nucleosome occupied regions than at the nucleosome depleted regions. We found that the binding sites have a different rate of evolution at nucleosome occupied and depleted regions. Finally, using transcription factor binding site-directed mutagenesis experiment, we confirmed the difference in the impact of binding site changes on expression at these regions. Thus, our work demonstrates the importance of composite analysis of chromatin and transcriptional evolution.

Pyrenophora bromi, causal agent of brownspot of bromegrass, expresses a gene encoding a protein with homology and similar activity to Ptr ToxB, a host-selective toxin of wheat

Ptr ToxB, encoded by ToxB, is one of multiple host-selective toxins (HST) produced by the wheat pathogen Pyrenophora tritici-repentis. Homologs of ToxB are found in several ascomycetes, including sister species Pyrenophora bromi, causal agent of brownspot of bromegrass. Due to the close evolutionary relatedness of P. tritici-repentis and P. bromi and that of their grass hosts, we hypothesized that homologs of ToxB in P. bromi may act as HST in the disease interaction between P. bromi and bromegrass. A representative set of transcriptionally active P. bromi ToxB genes were heterologously expressed in Pichia pastoris and the resultant proteins tested for their ability to act as HST on bromegrass. The tested Pyrenophora bromi ToxB (Pb ToxB) proteins were not toxic to bromegrass; thus, Pb ToxB does not appear to function as an HST in the P. bromi-bromegrass interaction. Instead, we revealed that the Pb ToxB proteins can be toxic to Ptr ToxB-sensitive wheat, at levels similar to Ptr ToxB, and the corresponding P. bromi ToxB genes are expressed in P. bromi-inoculated wheat. Our data suggest that P. bromi possesses the potential to become a wheat pathogen and highlights the importance of investigating the interaction between P. bromi and wheat.

The role of nucleosome positioning in the evolution of gene regulation

Chromatin organization plays a major role in gene regulation and can affect the function and evolution of new transcriptional programs. However, it can be difficult to decipher the basis of changes in chromatin organization and their functional effect on gene expression. Here, we present a large-scale comparative genomic analysis of the relationship between chromatin organization and gene expression, by measuring mRNA abundance and nucleosome positions genome-wide in 12 Hemiascomycota yeast species. We found substantial conservation of global and functional chromatin organization in all species, including prominent nucleosome-free regions (NFRs) at gene promoters, and distinct chromatin architecture in growth and stress genes. Chromatin organization has also substantially diverged in both global quantitative features, such as spacing between adjacent nucleosomes, and in functional groups of genes. Expression levels, intrinsic anti-nucleosomal sequences, and trans-acting chromatin modifiers all play important, complementary, and evolvable roles in determining NFRs. We identify five mechanisms that couple chromatin organization to evolution of gene regulation and have contributed to the evolution of respiro-fermentation and other key systems, including (1) compensatory evolution of alternative modifiers associated with conserved chromatin organization, (2) a gradual transition from constitutive to trans-regulated NFRs, (3) a loss of intrinsic anti-nucleosomal sequences accompanying changes in chromatin organization and gene expression, (4) re-positioning of motifs from NFRs to nucleosome-occluded regions, and (5) the expanded use of NFRs by paralogous activator-repressor pairs. Our study sheds light on the molecular basis of chromatin organization, and on the role of chromatin organization in the evolution of gene regulation.

A unifying view of 21st century systems biology

The idea that multi-scale dynamic complex systems formed by interacting macromolecules and metabolites, cells, organs and organisms underlie some of the most fundamental aspects of life was proposed by a few visionaries half a century ago. We are witnessing a powerful resurgence of this idea made possible by the availability of nearly complete genome sequences, ever improving gene annotations and interactome network maps, the development of sophisticated informatic and imaging tools, and importantly, the use of engineering and physics concepts such as control and graph theory. Alongside four other fundamental "great ideas" as suggested by Sir Paul Nurse, namely, the gene, the cell, the role of chemistry in biological processes, and evolution by natural selection, systems-level understanding of "What is Life" may materialize as one of the major ideas of biology.