Inferring regulatory mechanisms from patterns of evolutionary divergence

Interspecific hybridization as a driver of fungal evolution and adaptation

Cross-species gene transfer is often associated with bacteria, which have evolved several mechanisms that facilitate horizontal DNA exchange. However, the increased availability of whole-genome sequences has revealed that fungal species also exchange DNA, leading to intertwined lineages, blurred species boundaries or even novel species. In contrast to prokaryotes, fungal DNA exchange originates from interspecific hybridization, where two genomes are merged into a single, often highly unstable, polyploid genome that evolves rapidly into stabler derivatives. The resulting hybrids can display novel combinations of genetic and phenotypic variation that enhance fitness and allow colonization of new niches. Interspecific hybridization led to the emergence of important pathogens of humans and plants (for example, various Candida and 'powdery mildew' species, respectively) and industrially important yeasts, such as Saccharomyces hybrids that are important in the production of cold-fermented lagers or cold-cellared Belgian ales. In this Review, we discuss the genetic processes and evolutionary implications of fungal interspecific hybridization and highlight some of the best-studied examples. In addition, we explain how hybrids can be used to study molecular mechanisms underlying evolution, adaptation and speciation, and serve as a route towards development of new variants for industrial applications.

Frequent Assembly of Chimeric Complexes in the Protein Interaction Network of an Interspecies Yeast Hybrid

Hybrids between species often show extreme phenotypes, including some that take place at the molecular level. In this study, we investigated the phenotypes of an interspecies diploid hybrid in terms of protein–protein interactions inferred from protein correlation profiling. We used two yeast species, Saccharomyces cerevisiae and Saccharomyces uvarum, which are interfertile, but yet have proteins diverged enough to be differentiated using mass spectrometry. Most of the protein–protein interactions are similar between hybrid and parents, and are consistent with the assembly of chimeric complexes, which we validated using an orthogonal approach for the prefoldin complex. We also identified instances of altered protein–protein interactions in the hybrid, for instance, in complexes related to proteostasis and in mitochondrial protein complexes. Overall, this study uncovers the likely frequent occurrence of chimeric protein complexes with few exceptions, which may result from incompatibilities or imbalances between the parental proteomes.

Protein Complexes Form a Basis for Complex Hybrid Incompatibility

Proteins are the workhorses of the cell and execute many of their functions by interacting with other proteins forming protein complexes. Multi-protein complexes are an admixture of subunits, change their interaction partners, and modulate their functions and cellular physiology in response to environmental changes. When two species mate, the hybrid offspring are usually inviable or sterile because of large-scale differences in the genetic makeup between the two parents causing incompatible genetic interactions. Such reciprocal-sign epistasis between inter-specific alleles is not limited to incompatible interactions between just one gene pair; and, usually involves multiple genes. Many of these multi-locus incompatibilities show visible defects, only in the presence of all the interactions, making it hard to characterize. Understanding the dynamics of protein-protein interactions (PPIs) leading to multi-protein complexes is better suited to characterize multi-locus incompatibilities, compared to studying them with traditional approaches of genetics and molecular biology. The advances in omics technologies, which includes genomics, transcriptomics, and proteomics can help achieve this end. This is especially relevant when studying non-model organisms. Here, we discuss the recent progress in the understanding of hybrid genetic incompatibility; omics technologies, and how together they have helped in characterizing protein complexes and in turn multi-locus incompatibilities. We also review advances in bioinformatic techniques suitable for this purpose and propose directions for leveraging the knowledge gained from model-organisms to identify genetic incompatibilities in non-model organisms.

Dissecting the Heterogeneous Population Genetic Structure of Candida albicans: Limitations and Constraints of the Multilocus Sequence Typing Scheme

Candida albicans is a fungal opportunistic pathogen of significant public health importance mainly due to the recent emergence of strains with increased aggressiveness and antifungal resistance. Here, we aimed to describe the epidemiological profiles and approximate the population structure of C. albicans by analyzing the C. albicans multilocus sequence typing (MLST) database (Calb-MLST-DB), which contains the largest publically available dataset for this species. Based on 4,318 database isolates, we confirmed the ubiquitous nature of C. albicans including a group of diploid sequence types (DSTs) obtained from Healthy individuals exclusively (taken as an indicator of lack of association with illnesses in its host), until isolates established from Non-Healthy individuals (potentially associated with pathogenic processes) and other DSTs reported in both types (Healthy and Non-Healthy). The highest number of reported DSTs was related to blood, oral and vaginal swabs (32.4, 20.5, and 13.8%, respectively). High genetic diversity was observed in the seven housekeeping genes included in the MLST scheme, with a diverse population structure (154 clonal complexes, CCs; and a high number of singletons, n = 1,074). Phylogenetic reconstruction on the concatenated alignment of these housekeeping genes for all the reported DSTs (n = 3,483) was partially concordant with the CC assignment, however, an absence of bootstrap threshold supported nodes or p-distance, and the lack of association with the other epidemiological variables, evidenced the limitations of the MLST scheme. Marked genetic admixture signals were identified by STRUCTURE, with the majority being attributable to recombination events according to the RDP program results, although another type of exchange event cannot be ruled out. Our results reaffirm the genetic diversity inherent in the genes used for the MLST scheme, which are associated with the chromosomal remodeling already proposed for C. albicans. This was also corroborated with an internal validation at a micro geographical scale. Despite these results are biased due to the unavailability of considering the broad global spectrum of C. albicans isolates around the world. This suggests that the strategy used to population type this pathogen should be reevaluated to improve epidemiological monitoring of its health impact.

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.

Evolution of gene regulation during transcription and translation

Understanding how gene regulation evolves is a key area in the current evolutionary field. Gene regulation occurs at various levels. Previous work on the evolution of gene regulation has largely focused on gene transcription. In this study, we used a recently developed ribosomal footprint profiling method to investigate how gene regulation evolves at both the transcription (mRNA abundance) and translation (ribosomal density) levels. By constructing a hybrid between Saccharomyces cerevisiae (Scer) and Saccharomyces bayanus (Sbay), which diverged ∼20 Ma, and quantifying transcriptome and translatome in both parental strains and their hybrid, we showed that translation is much more conserved than transcription, mostly due to the buffering effect of translational regulation for the transcriptional divergence. More conservation in translation than transcription is also confirmed by the inheritance mode of transcription and translation between two species. Furthermore, cis and trans effects are widely involved in changes at both transcription and translation levels. Finally, our results showed that genes with certain functions and sequence features might employ specific modes for evolution at these two critical levels of gene regulation. Our results demonstrated that it is essential to investigate the evolution of gene regulation at various levels from different genetic backgrounds to obtain a complete picture of its evolutionary modes in nature.

Tracing the evolution of lineage-specific transcription factor binding sites in a birth-death framework

Changes in cis-regulatory element composition that result in novel patterns of gene expression are thought to be a major contributor to the evolution of lineage-specific traits. Although transcription factor binding events show substantial variation across species, most computational approaches to study regulatory elements focus primarily upon highly conserved sites, and rely heavily upon multiple sequence alignments. However, sequence conservation based approaches have limited ability to detect lineage-specific elements that could contribute to species-specific traits. In this paper, we describe a novel framework that utilizes a birth-death model to trace the evolution of lineage-specific binding sites without relying on detailed base-by-base cross-species alignments. Our model was applied to analyze the evolution of binding sites based on the ChIP-seq data for six transcription factors (GATA1, SOX2, CTCF, MYC, MAX, ETS1) along the lineage toward human after human-mouse common ancestor. We estimate that a substantial fraction of binding sites (∼58–79% for each factor) in humans have origins since the divergence with mouse. Over 15% of all binding sites are unique to hominids. Such elements are often enriched near genes associated with specific pathways, and harbor more common SNPs than older binding sites in the human genome. These results support the ability of our method to identify lineage-specific regulatory elements and help understand their roles in shaping variation in gene regulation across species.

Recent experimental studies showed that the evolution of transcription factor binding sites (TFBS) is highly dynamic, with sites differing a great deal even between closely related mammalian species. Despite the substantial experimental evidence for rapid divergence of regulatory protein-binding events across species, computational methods designed to analyze regulatory elements evolution have focused primarily on phylogenetic footprinting approaches, in which putative functional regulatory elements are identified according to strong sequence conservation. Cross-species comparisons of non-coding sequences are limited in their ability to fully understand the evolution of regulatory sequences, particularly in cases where the elements are selected for novelty or species-specific. We have developed a novel framework to reconstruct the history of lineage-specific TFBS and showed that large amount of TFBS in human were born after human-mouse divergence. These elements also have distinct biological implications as compared to more ancient ones. This method can help understand the roles of lineage-specific TFBS in shaping gene regulation across different species.

Conservation and divergence of gene expression plasticity following c. 140 million years of evolution in lodgepole pine (Pinus contorta) and interior spruce (Picea glauca×Picea engelmannii)

Species respond to environmental stress through a combination of genetic adaptation and phenotypic plasticity, both of which may be important for survival in the face of climatic change. By characterizing the molecular basis of plastic responses and comparing patterns among species, it is possible to identify how such traits evolve. Here, we used de novo transcriptome assembly and RNAseq to explore how patterns of gene expression differ in response to temperature, moisture, and light regime treatments in lodgepole pine (Pinus contorta) and interior spruce (a natural hybrid population of Picea glauca and Picea engelmannii). We found wide evidence for an effect of treatment on expression within each species, with 6413 and 11,658 differentially expressed genes identified in spruce and pine, respectively. Comparing patterns of expression among these species, we found that 74% of all orthologs with differential expression had a pattern that was conserved in both species, despite 140 million yr of evolution. We also found that the specific treatments driving expression patterns differed between genes with conserved versus diverged patterns of expression. We conclude that natural selection has probably played a role in shaping plastic responses to environment in these species.

Pervasive divergence of transcriptional gene regulation in Caenorhabditis nematodes

Because there is considerable variation in gene expression even between closely related species, it is clear that gene regulatory mechanisms evolve relatively rapidly. Because primary sequence conservation is an unreliable proxy for functional conservation of cis-regulatory elements, their assessment must be carried out in vivo. We conducted a survey of cis-regulatory conservation between C. elegans and closely related species C. briggsae, C. remanei, C. brenneri, and C. japonica. We tested enhancers of eight genes from these species by introducing them into C. elegans and analyzing the expression patterns they drove. Our results support several notable conclusions. Most exogenous cis elements direct expression in the same cells as their C. elegans orthologs, confirming gross conservation of regulatory mechanisms. However, the majority of exogenous elements, when placed in C. elegans, also directed expression in cells outside endogenous patterns, suggesting functional divergence. Recurrent ectopic expression of different promoters in the same C. elegans cells may reflect biases in the directions in which expression patterns can evolve due to shared regulatory logic of coexpressed genes. The fact that, despite differences between individual genes, several patterns repeatedly emerged from our survey, encourages us to think that general rules governing regulatory evolution may exist and be discoverable.

Rounding up natural gene expression variation during development

Molecular insights into the genetic control of development have been mainly derived from single gene mutant studies. Francesconi and Lehner (2013) report now in Nature a genome-wide map of natural sequence variants that affect the temporal expression dynamics of thousands of genes during development of the roundworm Caenorhabditis elegans.

Evolution at two levels of gene expression in yeast

Despite the greater functional importance of protein levels, our knowledge of gene expression evolution is based almost entirely on studies of mRNA levels. In contrast, our understanding of how translational regulation evolves has lagged far behind. Here we have applied ribosome profiling—which measures both global mRNA levels and their translation rates—to two species of Saccharomyces yeast and their interspecific hybrid in order to assess the relative contributions of changes in mRNA abundance and translation to regulatory evolution. We report that both cis- and trans-acting regulatory divergence in translation are abundant, affecting at least 35% of genes. The majority of translational divergence acts to buffer changes in mRNA abundance, suggesting a widespread role for stabilizing selection acting across regulatory levels. Nevertheless, we observe evidence of lineage-specific selection acting on several yeast functional modules, including instances of reinforcing selection acting at both levels of regulation. Finally, we also uncover multiple instances of stop-codon readthrough that are conserved between species. Our analysis reveals the underappreciated complexity of post-transcriptional regulatory divergence and indicates that partitioning the search for the locus of selection into the binary categories of “coding” versus “regulatory” may overlook a significant source of selection, acting at multiple regulatory levels along the path from genotype to phenotype.

Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

Background

Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking.

Results

In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes using Arabidopsis NimbleGen ATH6 microarrays. In total 6061 transcripts were significantly cold regulated (p < 0.01) in 10 ecotypes, including 498 transcription factors and 315 transposable elements. The majority of the transcripts (75%) showed ecotype specific expression pattern. By using sequence data available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about regulatory interactions between transcription factors and their target genes in the model plant A. thaliana, we have adopted a powerful systems genetics approach- Network Component Analysis (NCA) to construct an in-silico transcriptional regulatory network model during response to cold stress. The resulting regulatory network contained 1,275 nodes and 7,720 connections, with 178 transcription factors and 1,331 target genes.

Conclusions

A. thaliana ecotypes exhibit considerable variation in transcriptome level responses to non-freezing cold stress treatment. Ecotype specific transcripts and related gene ontology (GO) categories were identified to delineate natural variation of cold stress regulated differential gene expression in the model plant A. thaliana. The predicted regulatory network model was able to identify new ecotype specific transcription factors and their regulatory interactions, which might be crucial for their local geographic adaptation to cold temperature. Additionally, since the approach presented here is general, it could be adapted to study networks regulating biological process in any biological systems.

Genome scale transcriptional response diversity among ten ecotypes of Arabidopsis thaliana during heat stress

In the scenario of global warming and climate change, heat stress is a serious threat to crop production worldwide. Being sessile, plants cannot escape from heat. Plants have developed various adaptive mechanisms to survive heat stress. Several studies have focused on diversity of heat tolerance levels in divergent Arabidopsis thaliana (A. thaliana) ecotypes, but comprehensive genome scale understanding of heat stress response in plants is still lacking. Here we report the genome scale transcript responses to heat stress of 10 A. thaliana ecotypes (Col, Ler, C24, Cvi, Kas1, An1, Sha, Kyo2, Eri, and Kond) originated from different geographical locations. During the experiment, A. thaliana plants were subjected to heat stress (38°C) and transcript responses were monitored using Arabidopsis NimbleGen ATH6 microarrays. The responses of A. thaliana ecotypes exhibited considerable variation in the transcript abundance levels. In total, 3644 transcripts were significantly heat regulated (p < 0.01) in the 10 ecotypes, including 244 transcription factors and 203 transposable elements. By employing a systems genetics approach- Network Component Analysis (NCA), we have constructed an in silico transcript regulatory network model for 35 heat responsive transcription factors during cellular responses to heat stress in A. thaliana. The computed activities of the 35 transcription factors showed ecotype specific responses to the heat treatment.

An allele of an ancestral transcription factor dependent on a horizontally acquired gene product

Changes in gene regulatory circuits often give rise to phenotypic differences among closely related organisms. In bacteria, these changes can result from alterations in the ancestral genome and/or be brought about by genes acquired by horizontal transfer. Here, we identify an allele of the ancestral transcription factor PmrA that requires the horizontally acquired pmrD gene product to promote gene expression. We determined that a single amino acid difference between the PmrA proteins from the human adapted Salmonella enterica serovar Paratyphi B and the broad host range S. enterica serovar Typhimurium rendered transcription of PmrA-activated genes dependent on the PmrD protein in the former but not the latter serovar. Bacteria harboring the serovar Typhimurium allele exhibited polymyxin B resistance under PmrA- or under PmrA- and PmrD-inducing conditions. By contrast, isogenic strains with the serovar Paratyphi B allele displayed PmrA-regulated polymyxin B resistance only when experiencing activating conditions for both PmrA and PmrD. We establish that the two PmrA orthologs display quantitative differences in several biochemical properties. Strains harboring the serovar Paratyphi B allele showed enhanced biofilm formation, a property that might promote serovar Paratyphi B's chronic infection of the gallbladder. Our findings illustrate how subtle differences in ancestral genes can impact the ability of horizontally acquired genes to confer new properties.

Ecological interactions drive evolutionary loss of traits

Loss of traits can dramatically alter the fate of species. Evidence is rapidly accumulating that the prevalence of trait loss is grossly underestimated. New findings demonstrate that traits can be lost without affecting the external phenotype, provided the lost function is compensated for by species interactions. This is important because trait loss can tighten the ecological relationship between partners, affecting the maintenance of species interactions. Here, we develop a new perspective on so-called `compensated trait loss' and how this type of trait loss may affect the evolutionary dynamics between interacting organisms. We argue that: (1) the frequency of compensated trait loss is currently underestimated because it can go unnoticed as long as ecological interactions are maintained; (2) by analysing known cases of trait loss, specific factors promoting compensated trait loss can be identified and (3) genomic sequencing is a key way forwards in detecting compensated trait loss. We present a comprehensive literature survey showing that compensated trait loss is taxonomically widespread, can involve essential traits, and often occurs as replicated evolutionary events. Despite its hidden nature, compensated trait loss is important in directing evolutionary dynamics of ecological relationships and has the potential to change facultative ecological interactions into obligatory ones.

Redundancy and rewiring of genetic networks following genome-wide duplication events

Polyploidy or whole-genome duplication is a frequent phenomenon within the plant kingdom and has been associated with the occurrence of evolutionary novelty and increase in biological complexity. Because genome-wide duplication events duplicate whole molecular networks it is of interest to investigate how these networks evolve subsequent to such events. Although genome duplications are generally followed by massive gene loss, at least part of the network is usually retained in duplicate and can rewire to execute novel functions. Alternatively, the network can remain largely redundant and as such confer robustness against mutations. The increasing availability of high-throughput data makes it possible to study evolution following whole genome duplication events at the network level. Here we discuss how the use of 'omics' data in network analysis can provide novel insights on network redundancy and rewiring and conclude with some directions for future research.

Evolutionary systems biology: historical and philosophical perspectives on an emerging synthesis

Systems biology (SB) is at least a decade old now and maturing rapidly. A more recent field, evolutionary systems biology (ESB), is in the process of further developing system-level approaches through the expansion of their explanatory and potentially predictive scope. This chapter will outline the varieties of ESB existing today by tracing the diverse roots and fusions that make up this integrative project. My approach is philosophical and historical. As well as examining the recent origins of ESB, I will reflect on its central features and the different clusters of research it comprises. In its broadest interpretation, ESB consists of five overlapping approaches: comparative and correlational ESB; network architecture ESB; network property ESB; population genetics ESB; and finally, standard evolutionary questions answered with SB methods. After outlining each approach with examples, I will examine some strong general claims about ESB, particularly that it can be viewed as the next step toward a fuller modern synthesis of evolutionary biology (EB), and that it is also the way forward for evolutionary and systems medicine. I will conclude with a discussion of whether the emerging field of ESB has the capacity to combine an even broader scope of research aims and efforts than it presently does.

Comparative interaction networks: bridging genotype to phenotype

Over the past decade, biomedical research has witnessed an exponential increase in the throughput of the characterization of biological systems. Here we review the recent progress in large-scale methods to determine protein-protein, genetic and chemical-genetic interaction networks. We discuss some of the limitations and advantages of the different methods and give examples of how these networks are being used to study the evolutionary process. Comparative studies have revealed that different types of protein-protein interactions diverge at different rates with high conservation of co-complex membership but rapid divergence of more promiscuous interactions like those that mediate post-translational modifications. These evolutionary trends have consistent genetic consequences with highly conserved epistatic interactions within complex subunits but faster divergence of epistatic interactions across complexes or pathways. Finally, we discuss how these evolutionary observations are being used to interpret cross-species chemical-genetic studies and how they might shape therapeutic strategies. Together, these interaction networks offer us an unprecedented level of detail into how genotypes are translated to phenotypes, and we envision that they will be increasingly useful in the interpretation of genetic and phenotypic variation occurring within populations as well as the rational design of combinatorial therapeutics.