Evolution of gene expression in the Drosophila melanogaster subgroup

The genetic architecture of gene expression levels in wild baboons

Primate evolution has been argued to result, in part, from changes in how genes are regulated. However, we still know little about gene regulation in natural primate populations. We conducted an RNA sequencing (RNA-seq)-based study of baboons from an intensively studied wild population. We performed complementary expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses, discovering substantial evidence for, and surprising power to detect, genetic effects on gene expression levels in the baboons. eQTL were most likely to be identified for lineage-specific, rapidly evolving genes; interestingly, genes with eQTL significantly overlapped between baboons and a comparable human eQTL data set. Our results suggest that genes vary in their tolerance of genetic perturbation, and that this property may be conserved across species. Further, they establish the feasibility of eQTL mapping using RNA-seq data alone, and represent an important step towards understanding the genetic architecture of gene expression in primates.

Evolution of H3K27me3-marked chromatin is linked to gene expression evolution and to patterns of gene duplication and diversification

Histone modifications are critical for the regulation of gene expression, cell type specification, and differentiation. However, evolutionary patterns of key modifications that regulate gene expression in differentiating organisms have not been examined. Here we mapped the genomic locations of the repressive mark histone 3 lysine 27 trimethylation (H3K27me3) in four species of Drosophila, and compared these patterns to those in C. elegans. We found that patterns of H3K27me3 are highly conserved across species, but conservation is substantially weaker among duplicated genes. We further discovered that retropositions are associated with greater evolutionary changes in H3K27me3 and gene expression than tandem duplications, indicating that local chromatin constraints influence duplicated gene evolution. These changes are also associated with concomitant evolution of gene expression. Our findings reveal the strong conservation of genomic architecture governed by an epigenetic mark across distantly related species and the importance of gene duplication in generating novel H3K27me3 profiles.

Genome-wide survey on genomic variation, expression divergence, and evolution in two contrasting rice genotypes under high salinity stress

Expression profiling is one of the most important tools for dissecting biological functions of genes and the upregulation or downregulation of gene expression is sufficient for recreating phenotypic differences. Expression divergence of genes significantly contributes to phenotypic variations. However, little is known on the molecular basis of expression divergence and evolution among rice genotypes with contrasting phenotypes. In this study, we have implemented an integrative approach using bioinformatics and experimental analyses to provide insights into genomic variation, expression divergence, and evolution between salinity-sensitive rice variety Nipponbare and tolerant rice line Pokkali under normal and high salinity stress conditions. We have detected thousands of differentially expressed genes between these two genotypes and thousands of up- or downregulated genes under high salinity stress. Many genes were first detected with expression evidence using custom microarray analysis. Some gene families were preferentially regulated by high salinity stress and might play key roles in stress-responsive biological processes. Genomic variations in promoter regions resulted from single nucleotide polymorphisms, indels (1–10 bp of insertion/deletion), and structural variations significantly contributed to the expression divergence and regulation. Our data also showed that tandem and segmental duplication, CACTA and hAT elements played roles in the evolution of gene expression divergence and regulation between these two contrasting genotypes under normal or high salinity stress conditions.

Functional divergence of the miRNA transcriptome at the onset of Drosophila metamorphosis

MicroRNAs (miRNAs) are endogenous RNA molecules that regulate gene expression posttranscriptionally. To date, the emergence of miRNAs and their patterns of sequence evolution have been analyzed in great detail. However, the extent to which miRNA expression levels have evolved over time, the role different evolutionary forces play in shaping these changes, and whether this variation in miRNA expression can reveal the interplay between miRNAs and mRNAs remain poorly understood. This is especially true for miRNA expressed during key developmental transitions. Here, we assayed miRNA expression levels immediately before (≥18BPF [18 h before puparium formation]) and after (PF) the increase in the hormone ecdysone responsible for triggering metamorphosis. We did so in four strains of Drosophila melanogaster and two closely related species. In contrast to their sequence conservation, approximately 25% of miRNAs analyzed showed significant within-species variation in male expression levels at ≥18BPF and/or PF. Additionally, approximately 33% showed modifications in their pattern of expression bias between developmental timepoints. A separate analysis of the ≥18BPF and PF stages revealed that changes in miRNA abundance accumulate linearly over evolutionary time at PF but not at ≥18BPF. Importantly, ≥18BPF-enriched miRNAs showed the greatest variation in expression levels both within and between species, so are the less likely to evolve under stabilizing selection. Functional attributes, such as expression ubiquity, appeared more tightly associated with lower levels of miRNA expression polymorphism at PF than at ≥18BPF. Furthermore, ≥18BPF- and PF-enriched miRNAs showed opposite patterns of covariation in expression with mRNAs, which denoted the type of regulatory relationship between miRNAs and mRNAs. Collectively, our results show contrasting patterns of functional divergence associated with miRNA expression levels during Drosophila ontogeny.

Expression evolution facilitated the convergent neofunctionalization of a sodium channel gene

Ion channels have played a substantial role in the evolution of novel traits across all of the domains of life. A fascinating example of a novel adaptation is the convergent evolution of electric organs in the Mormyroid and Gymnotiform electric fishes. The regulated currents that flow through ion channels directly generate the electrical signals which have evolved in these fish. Here, we investigated how the expression evolution of two sodium channel paralogs (Scn4aa and Scn4ab) influenced their convergent molecular evolution following the teleost-specific whole-genome duplication. We developed a reliable assay to accurately measure the expression stoichiometry of these genes and used this technique to analyze relative expression of the duplicate genes in a phylogenetic context. We found that before a major shift in expression from skeletal muscle and neofunctionalization in the muscle-derived electric organ, Scn4aa was first downregulated in the ancestors of both electric lineages. This indicates that underlying the convergent evolution of this gene, there was a greater propensity toward neofunctionalization due to its decreased expression relative to its paralog Scn4ab. We investigated another derived muscle tissue, the sonic organ of Porichthys notatus, and show that, as in the electric fishes, Scn4aa again shows a radical shift in expression away from the ancestral muscle cells into the evolutionarily novel muscle-derived tissue. This study presents evidence that expression downregulation facilitates neofunctionalization after gene duplication, a pattern that may often set the stage for novel trait evolution after gene duplication.

Phylogenomic distance method for analyzing transcriptome evolution based on RNA-seq data

Thanks to the microarray technology, our understanding of transcriptome evolution at the genome level has been considerably advanced in the past decade. Yet, further investigation was challenged by several technical limitations of this technology. Recent innovation of next-generation sequencing, particularly the invention of RNA-seq technology, has shed insightful lights on resolving this problem. Though a number of statistical and computational methods have been developed to analyze RNA-seq data, the analytical framework specifically designed for evolutionary genomics remains an open question. In this article we develop a new method for estimating the genome expression distance from the RNA-seq data, which has explicit interpretations under the model of gene expression evolution. Moreover, this distance measure takes the data overdispersion, gene length variation, and sequencing depth variation into account so that it can be applied to multiple genomes from different species. Using mammalian RNA-seq data as example, we demonstrated that this expression distance is useful in phylogenomic analysis.

Ribosome profiling reveals post-transcriptional buffering of divergent gene expression in yeast

Understanding the patterns and causes of phenotypic divergence is a central goal in evolutionary biology. Much work has shown that mRNA abundance is highly variable between closely related species. However, the extent and mechanisms of post-transcriptional gene regulatory evolution are largely unknown. Here we used ribosome profiling to compare transcript abundance and translation efficiency in two closely related yeast species (S. cerevisiae and S. paradoxus). By comparing translation regulatory divergence to interspecies differences in mRNA sequence features, we show that differences in transcript leaders and codon bias substantially contribute to divergent translation. Globally, we find that translation regulatory divergence often buffers species differences in mRNA abundance, such that ribosome occupancy is more conserved than transcript abundance. We used allele-specific ribosome profiling in interspecies hybrids to compare the relative contributions of cis- and trans-regulatory divergence to species differences in mRNA abundance and translation efficiency. The mode of gene regulatory divergence differs for these processes, as trans-regulatory changes play a greater role in divergent mRNA abundance than in divergent translation efficiency. Strikingly, most genes with aberrant transcript abundance in F1 hybrids (either over- or underexpressed compared to both parent species) did not exhibit aberrant ribosome occupancy. Our results show that interspecies differences in translation contribute substantially to the evolution of gene expression. Compensatory differences in transcript abundance and translation efficiency may increase the robustness of gene regulation.

Tempo and mode of regulatory evolution in Drosophila

Genetic changes affecting gene expression contribute to phenotypic divergence; thus, understanding how regulatory networks controlling gene expression change over time is critical for understanding evolution. Prior studies of expression differences within and between species have identified properties of regulatory divergence, but technical and biological differences among these studies make it difficult to assess the generality of these properties or to understand how regulatory changes accumulate with divergence time. Here, we address these issues by comparing gene expression among strains and species of Drosophila with a range of divergence times and use F₁ hybrids to examine inheritance patterns and disentangle cis- and trans-regulatory changes. We find that the fixation of compensatory changes has caused the regulation of gene expression to diverge more rapidly than gene expression itself. Specifically, we observed that the proportion of genes with evidence of cis-regulatory divergence has increased more rapidly with divergence time than the proportion of genes with evidence of expression differences. Surprisingly, the amount of expression divergence explained by cis-regulatory changes did not increase steadily with divergence time, as was previously proposed. Rather, one species (Drosophila sechellia) showed an excess of cis-regulatory divergence that we argue most likely resulted from positive selection in this lineage. Taken together, this work reveals not only the rate at which gene expression evolves, but also the molecular and evolutionary mechanisms responsible for this evolution.

Evolution of splicing regulatory networks in Drosophila

The proteome expanding effects of alternative pre-mRNA splicing have had a profound impact on eukaryotic evolution. The events that create this diversity can be placed into four major classes: exon skipping, intron retention, alternative 5′ splice sites, and alternative 3′ splice sites. Although the regulatory mechanisms and evolutionary pressures among alternative splicing classes clearly differ, how these differences affect the evolution of splicing regulation remains poorly characterized. We used RNA-seq to investigate splicing differences in D. simulans, D. sechellia, and three strains of D. melanogaster. Regulation of exon skipping and tandem alternative 3′ splice sites (NAGNAGs) were more divergent than other splicing classes. Splicing regulation was most divergent in frame-preserving events and events in noncoding regions. We further determined the contributions of cis- and trans-acting changes in splicing regulatory networks by comparing allele-specific splicing in F1 interspecific hybrids, because differences in allele-specific splicing reflect changes in cis-regulatory element activity. We find that species-specific differences in intron retention and alternative splice site usage are primarily attributable to changes in cis-regulatory elements (median ∼80% cis), whereas species-specific exon skipping differences are driven by both cis- and trans-regulatory divergence (median ∼50% cis). These results help define the mechanisms and constraints that influence splicing regulatory evolution and show that networks regulating the four major classes of alternative splicing diverge through different genetic mechanisms. We propose a model in which differences in regulatory network architecture among classes of alternative splicing affect the evolution of splicing regulation.

Modeling gene expression evolution with an extended Ornstein-Uhlenbeck process accounting for within-species variation

Much of the phenotypic variation observed between even closely related species may be driven by differences in gene expression levels. The current availability of reliable techniques like RNA-Seq, which can quantify expression levels across species, has enabled comparative studies. Ornstein-Uhlenbeck (OU) processes have been proposed to model gene expression evolution as they model both random drift and stabilizing selection and can be extended to model changes in selection regimes. The OU models provide a statistical framework that allows comparisons of specific hypotheses of selective regimes, including random drift, constrained drift, and expression level shifts. In this way, inferences may be made about the mode of selection acting on the expression level of a gene. We augment this model to include within-species expression variance, allowing for modeling of nonevolutionary expression variance that could be caused by individual genetic, environmental, or technical variation. Through simulations, we explore the reliability of parameter estimates and the extent to which different selective regimes can be distinguished using phylogenies of varying size using both the typical OU model and our extended model. We find that if individual variation is not accounted for, nonevolutionary expression variation is often mistaken for strong stabilizing selection. The methods presented in this article are increasingly relevant as comparative expression data becomes more available and researchers turn to expression as a primary evolving phenotype.

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.

Genomic and physiological responses to strong selective pressure during late organogenesis: few gene expression changes found despite striking morphological differences

Background

Adaptations to a new environment, such as a polluted one, often involve large modifications of the existing phenotypes. Changes in gene expression and regulation during critical developmental stages may explain these phenotypic changes. Embryos from a population of the teleost fish, Fundulus heteroclitus, inhabiting a clean estuary do not survive when exposed to sediment extract from a site highly contaminated with polycyclic aromatic hydrocarbons (PAHs) while embryos derived from a population inhabiting a PAH polluted estuary are remarkably resistant to the polluted sediment extract. We exposed embryos from these two populations to surrogate model PAHs and analyzed changes in gene expression, morphology, and cardiac physiology in order to better understand sensitivity and adaptive resistance mechanisms mediating PAH exposure during development.

Results

The synergistic effects of two model PAHs, an aryl hydrocarbon receptor (AHR) agonist (β-naphthoflavone) and a cytochrome P4501A (CYP1A) inhibitor (α-naphthoflavone), caused significant developmental delays, impaired cardiac function, severe morphological alterations and failure to hatch, leading to the deaths of reference embryos; resistant embryos were mostly unaffected. Unexpectedly, patterns of gene expression among normal and moderately deformed embryos were similar, and only severely deformed embryos showed a contrasting pattern of gene expression. Given the drastic morphological differences between reference and resistant embryos, a surprisingly low percentage of genes, 2.24% of 6,754 analyzed, show statistically significant differences in transcript levels during late organogenesis between the two embryo populations.

Conclusions

Our study demonstrates important contrasts in responses between reference and resistant natural embryo populations to synergistic effects of surrogate model PAHs that may be important in adaptive mechanisms mediating PAH effects during fish embryo development. These results suggest that statistically significant changes in gene expression of relatively few genes contribute to the phenotypic changes and large morphological differences exhibited by reference and resistant populations upon exposure to PAH pollutants. By correlating cardiac physiology and morphology with changes in gene expression patterns of reference and resistant embryos, we provide additional evidence for acquired resistance among embryos whose parents live at heavily contaminated sites.

Conserved translatome remodeling in nematode species executing a shared developmental transition

Nematodes of the genus Caenorhabditis enter a developmental diapause state after hatching in the absence of food. To better understand the relative contributions of distinct regulatory modalities to gene expression changes associated with this developmental transition, we characterized genome-wide changes in mRNA abundance and translational efficiency associated with L1 diapause exit in four species using ribosome profiling and mRNA-seq. We found a strong tendency for translational regulation and mRNA abundance processes to act synergistically, together effecting a dramatic remodeling of the gene expression program. While gene-specific differences were observed between species, overall translational dynamics were broadly and functionally conserved. A striking, conserved feature of the response was strong translational suppression of ribosomal protein production during L1 diapause, followed by activation upon resumed development. On a global scale, ribosome footprint abundance changes showed greater similarity between species than changes in mRNA abundance, illustrating a substantial and genome-wide contribution of translational regulation to evolutionary maintenance of stable gene expression.

The roles of cis- and trans-regulation in the evolution of regulatory incompatibilities and sexually dimorphic gene expression

Evolutionary changes in gene expression underlie many aspects of phenotypic diversity within and among species. Understanding the genetic basis for evolved changes in gene expression is therefore an important component of a comprehensive understanding of the genetic basis of phenotypic evolution. Using interspecific introgression hybrids, we examined the genetic basis for divergence in genome-wide patterns of gene expression between Drosophila simulans and Drosophila mauritiana. We find that cis-regulatory and trans-regulatory divergences differ significantly in patterns of genetic architecture and evolution. The effects of cis-regulatory divergence are approximately additive in heterozygotes, quantitatively different between males and females, and well predicted by expression differences between the two parental species. In contrast, the effects of trans-regulatory divergence are associated with largely dominant introgressed alleles, have similar effects in the two sexes, and generate expression levels in hybrids outside the range of expression in both parental species. Although the effects of introgressed trans-regulatory alleles are similar in males and females, expression levels of the genes they regulate are sexually dimorphic between the parental D. simulans and D. mauritiana strains, suggesting that pure-species genotypes carry unlinked modifier alleles that increase sexual dimorphism in expression. Our results suggest that independent effects of cis-regulatory substitutions in males and females may favor their role in the evolution of sexually dimorphic phenotypes, and that trans-regulatory divergence is an important source of regulatory incompatibilities.

A comparative analysis of transcription factor expression during metazoan embryonic development

During embryonic development, a complex organism is formed from a single starting cell. These processes of growth and differentiation are driven by large transcriptional changes, which are following the expression and activity of transcription factors (TFs). This study sought to compare TF expression during embryonic development in a diverse group of metazoan animals: representatives of vertebrates (Danio rerio, Xenopus tropicalis), a chordate (Ciona intestinalis) and invertebrate phyla such as insects (Drosophila melanogaster, Anopheles gambiae) and nematodes (Caenorhabditis elegans) were sampled, The different species showed overall very similar TF expression patterns, with TF expression increasing during the initial stages of development. C2H2 zinc finger TFs were over-represented and Homeobox TFs were under-represented in the early stages in all species. We further clustered TFs for each species based on their quantitative temporal expression profiles. This showed very similar TF expression trends in development in vertebrate and insect species. However, analysis of the expression of orthologous pairs between more closely related species showed that expression of most individual TFs is not conserved, following the general model of duplication and diversification. The degree of similarity between TF expression between Xenopus tropicalis and Danio rerio followed the hourglass model, with the greatest similarity occuring during the early tailbud stage in Xenopus tropicalis and the late segmentation stage in Danio rerio. However, for Drosophila melanogaster and Anopheles gambiae there were two periods of high TF transcriptome similarity, one during the Arthropod phylotypic stage at 8-10 hours into Drosophila development and the other later at 16-18 hours into Drosophila development.

Phylogenetic analysis of gene expression

Phylogenetic analyses of gene expression have great potential for addressing a wide range of questions. These analyses will, for example, identify genes that have evolutionary shifts in expression that are correlated with evolutionary changes in morphological, physiological, and developmental characters of interest. This will provide entirely new opportunities to identify genes related to particular phenotypes. There are, however, 3 key challenges that must be addressed for such studies to realize their potential. First, data on gene expression must be measured from multiple species, some of which may be field-collected, and parameterized in such a way that they can be compared across species. Second, it will be necessary to develop comparative phylogenetic methods suitable for large multidimensional datasets. In most phylogenetic comparative studies to date, the number n of independent observations (independent contrasts) has been greater than the number p of variables (characters). The behavior of comparative methods for these classic problems is now well understood under a wide variety of conditions. In studies of gene expression, and in studies based on other high-throughput tools, the number n of samples is dwarfed by the number p of variables. The estimated covariance matrices will be singular, complicating their analysis and interpretation, and prone to spurious results. Third, new approaches are needed to investigate the expression of the many genes whose phylogenies are not congruent with species phylogenies due to gene loss, gene duplication, and incomplete lineage sorting. Here we outline general considerations of project design for phylogenetic analyses of gene expression and suggest solutions to these three categories of challenges. These topics are relevant to high-throughput phenotypic data well beyond gene expression.

Interspecific divergence of transcription networks along lines of genetic variance in Drosophila: dimensionality, evolvability, and constraint

Change in gene expression is a major facilitator of phenotypic evolution. Understanding the evolutionary potential of gene expression requires taking into account complex systems of regulatory networks, the structure of which could potentially bias evolutionary trajectories. We analyzed the evolutionary potential and divergence of multigene expression in three well-characterized signaling pathways in Drosophila, the mitogen-activated protein kinase (MapK), the Toll, and the insulin receptor/Foxo (InR/Foxo or InR/TOR) pathways in a multivariate quantitative genetic framework. Gene expression data from a natural population of D. melanogaster were used to estimate the genetic variance-covariance matrices (G) for each network. Although most genes within each pathway exhibited significant genetic variance, the number of independent dimensions of multivariate genetic variance was fewer than the number of genes analyzed. However, for expression, the reduction in dimensionality was not as large as seen for other trait types such as morphology. We then tested whether gene expression divergence between D. melanogaster and an additional six species of the Drosophila genus was biased along the major axes of standing variation observed in D. melanogaster. In many cases, divergence was restricted to directions of phenotypic space harboring above average levels of genetic variance in D. melanogaster, indicating that genetic covariances between genes within pathways have biased interspecific divergence. We tested whether co-expression of genes in both sexes has also biased the pattern of divergence. Including cross-sex genetic covariances increased the degree to which divergence was biased along major axes of genetic variance, suggesting that the co-expression of genes in males and females can generate further constraints on divergence across the Drosophila phylogeny. In contrast to patterns seen for morphological traits in vertebrates, transcriptional constraints do not appear to break down as divergence time between species increases, instead they persist over tens of millions of years of divergence.

Population genetics of cis-regulatory sequences that operate during embryonic development in the sea urchin Strongylocentrotus purpuratus

Despite the fact that noncoding sequences comprise a substantial fraction of functional sites within all genomes, the evolutionary mechanisms that operate on genetic variation within regulatory elements remain poorly understood. In this study, we examine the population genetics of the core, upstream cis-regulatory regions of eight genes (AN, CyIIa, CyIIIa, Endo16, FoxB, HE, SM30 a, and SM50) that function during the early development of the purple sea urchin, Strongylocentrotus purpuratus. Quantitative and qualitative measures of segregating variation are not conspicuously different between cis-regulatory and closely linked "proxy neutral" noncoding regions containing no known functional sites. Length and compound mutations are common in noncoding sequences; conventional descriptive statistics ignore such mutations, under-representing true genetic variation by approximately 28% for these loci in this population. Patterns of variation in the cis-regulatory regions of six of the genes examined (CyIIa, CyIIIa, Endo16, FoxB, AN, and HE) are consistent with directional selection. Genetic variation within annotated transcription factor binding sites is comparable to, and frequently greater than, that of surrounding sequences. Comparisons of two paralog pairs (CyIIa/CyIIIa and AN/HE) suggest that distinct evolutionary processes have operated on their cis-regulatory regions following gene duplication. Together, these analyses provide a detailed view of the evolutionary mechanisms operating on noncoding sequences within a natural population, and underscore how little is known about how these processes operate on cis-regulatory sequences.

Matching experiments across species using expression values and textual information

Motivation: With the vast increase in the number of gene expression datasets deposited in public databases, novel techniques are required to analyze and mine this wealth of data. Similar to the way BLAST enables cross-species comparison of sequence data, tools that enable cross-species expression comparison will allow us to better utilize these datasets: cross-species expression comparison enables us to address questions in evolution and development, and further allows the identification of disease-related genes and pathways that play similar roles in humans and model organisms. Unlike sequence, which is static, expression data changes over time and under different conditions. Thus, a prerequisite for performing cross-species analysis is the ability to match experiments across species.

Results: To enable better cross-species comparisons, we developed methods for automatically identifying pairs of similar expression datasets across species. Our method uses a co-training algorithm to combine a model of expression similarity with a model of the text which accompanies the expression experiments. The co-training method outperforms previous methods based on expression similarity alone. Using expert analysis, we show that the new matches identified by our method indeed capture biological similarities across species. We then use the matched expression pairs between human and mouse to recover known and novel cycling genes as well as to identify genes with possible involvement in diabetes. By providing the ability to identify novel candidate genes in model organisms, our method opens the door to new models for studying diseases.

Availability: Source code and supplementary information is available at: www.andrew.cmu.edu/user/aaronwis/cotrain12.

Contact:zivbj@cs.cmu.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Comparative gene expression between two yeast species

Background

Comparative genomics brings insight into sequence evolution, but even more may be learned by coupling sequence analyses with experimental tests of gene function and regulation. However, the reliability of such comparisons is often limited by biased sampling of expression conditions and incomplete knowledge of gene functions across species. To address these challenges, we previously systematically generated expression profiles in Saccharomyces bayanus to maximize functional coverage as compared to an existing Saccharomyces cerevisiae data repository.

Results

In this paper, we take advantage of these two data repositories to compare patterns of ortholog expression in a wide variety of conditions. First, we developed a scalable metric for expression divergence that enabled us to detect a significant correlation between sequence and expression conservation on the global level, which previous smaller-scale expression studies failed to detect. Despite this global conservation trend, between-species gene expression neighborhoods were less well-conserved than within-species comparisons across different environmental perturbations, and approximately 4% of orthologs exhibited a significant change in co-expression partners. Furthermore, our analysis of matched perturbations collected in both species (such as diauxic shift and cell cycle synchrony) demonstrated that approximately a quarter of orthologs exhibit condition-specific expression pattern differences.

Conclusions

Taken together, these analyses provide a global view of gene expression patterns between two species, both in terms of the conditions and timing of a gene's expression as well as co-expression partners. Our results provide testable hypotheses that will direct future experiments to determine how these changes may be specified in the genome.

Systematic reviews of animal models: methodology versus epistemology

Systematic reviews are currently favored methods of evaluating research in order to reach conclusions regarding medical practice. The need for such reviews is necessitated by the fact that no research is perfect and experts are prone to bias. By combining many studies that fulfill specific criteria, one hopes that the strengths can be multiplied and thus reliable conclusions attained. Potential flaws in this process include the assumptions that underlie the research under examination. If the assumptions, or axioms, upon which the research studies are based, are untenable either scientifically or logically, then the results must be highly suspect regardless of the otherwise high quality of the studies or the systematic reviews. We outline recent criticisms of animal-based research, namely that animal models are failing to predict human responses. It is this failure that is purportedly being corrected via systematic reviews. We then examine the assumption that animal models can predict human outcomes to perturbations such as disease or drugs, even under the best of circumstances. We examine the use of animal models in light of empirical evidence comparing human outcomes to those from animal models, complexity theory, and evolutionary biology. We conclude that even if legitimate criticisms of animal models were addressed, through standardization of protocols and systematic reviews, the animal model would still fail as a predictive modality for human response to drugs and disease. Therefore, systematic reviews and meta-analyses of animal-based research are poor tools for attempting to reach conclusions regarding human interventions.

Adaptive evolution and the birth of CTCF binding sites in the Drosophila genome

Comparative ChIP-seq data reveal adaptive evolution of insulator protein CTCF binding in multiple Drosophila species.

Changes in the physical interaction between cis-regulatory DNA sequences and proteins drive the evolution of gene expression. However, it has proven difficult to accurately quantify evolutionary rates of such binding change or to estimate the relative effects of selection and drift in shaping the binding evolution. Here we examine the genome-wide binding of CTCF in four species of Drosophila separated by between ∼2.5 and 25 million years. CTCF is a highly conserved protein known to be associated with insulator sequences in the genomes of human and Drosophila. Although the binding preference for CTCF is highly conserved, we find that CTCF binding itself is highly evolutionarily dynamic and has adaptively evolved. Between species, binding divergence increased linearly with evolutionary distance, and CTCF binding profiles are diverging rapidly at the rate of 2.22% per million years (Myr). At least 89 new CTCF binding sites have originated in the Drosophila melanogaster genome since the most recent common ancestor with Drosophila simulans. Comparing these data to genome sequence data from 37 different strains of Drosophila melanogaster, we detected signatures of selection in both newly gained and evolutionarily conserved binding sites. Newly evolved CTCF binding sites show a significantly stronger signature for positive selection than older sites. Comparative gene expression profiling revealed that expression divergence of genes adjacent to CTCF binding site is significantly associated with the gain and loss of CTCF binding. Further, the birth of new genes is associated with the birth of new CTCF binding sites. Our data indicate that binding of Drosophila CTCF protein has evolved under natural selection, and CTCF binding evolution has shaped both the evolution of gene expression and genome evolution during the birth of new genes.

A large proportion of the diversity of living organisms results from differential regulation of gene transcription. Transcriptional regulation is thought to differ between species because of evolutionary changes in the physical interactions between regulatory DNA elements and DNA-binding proteins; these can generate variation in the spatial and temporal patterns of gene expression. The mechanisms by which these protein–DNA interactions evolve is therefore an important question in evolutionary biology. Does adaptive evolution play a role, or is the process dominated by neutral genetic drift? Insulator proteins are a special group of DNA-binding proteins—instead of directly serving to activate or repress genes, they can function to coordinate the interactions between other regulatory elements (such as enhancers and promoters). Additionally, insulator proteins can limit the spreading of chromatin condensation and help to demarcate the boundaries of regulatory domains in the genome. In spite of their critical role in genome regulation, little is known about the evolution of interactions between insulator proteins and DNA. Here, we use ChIP-seq to examine the distribution of binding sites for CTCF, a highly conserved insulator protein, in four closely related Drosophila species. We find that genome-wide binding profiles of CTCF are highly dynamic across evolutionary time, with frequent births of new CTCF-DNA interactions, and we demonstrate that this evolutionary process is driven by natural selection. By comparing these with RNA-seq data, we find that gain or loss of CTCF binding impacts the expression levels of nearby genes and correlates with structural evolution of the genome. Together these results suggest a potential mechanism of regulatory re-wiring through adaptive evolution of CTCF binding.

Faster-X evolution of gene expression in Drosophila

DNA sequences on X chromosomes often have a faster rate of evolution when compared to similar loci on the autosomes, and well articulated models provide reasons why the X-linked mode of inheritance may be responsible for the faster evolution of X-linked genes. We analyzed microarray and RNA-seq data collected from females and males of six Drosophila species and found that the expression levels of X-linked genes also diverge faster than autosomal gene expression, similar to the "faster-X" effect often observed in DNA sequence evolution. Faster-X evolution of gene expression was recently described in mammals, but it was limited to the evolutionary lineages shortly following the creation of the therian X chromosome. In contrast, we detect a faster-X effect along both deep lineages and those on the tips of the Drosophila phylogeny. In Drosophila males, the dosage compensation complex (DCC) binds the X chromosome, creating a unique chromatin environment that promotes the hyper-expression of X-linked genes. We find that DCC binding, chromatin environment, and breadth of expression are all predictive of the rate of gene expression evolution. In addition, estimates of the intraspecific genetic polymorphism underlying gene expression variation suggest that X-linked expression levels are not under relaxed selective constraints. We therefore hypothesize that the faster-X evolution of gene expression is the result of the adaptive fixation of beneficial mutations at X-linked loci that change expression level in cis. This adaptive faster-X evolution of gene expression is limited to genes that are narrowly expressed in a single tissue, suggesting that relaxed pleiotropic constraints permit a faster response to selection. Finally, we present a conceptional framework to explain faster-X expression evolution, and we use this framework to examine differences in the faster-X effect between Drosophila and mammals.

Combinatorial control of temporal gene expression in the Drosophila wing by enhancers and core promoters

Background

The transformation of a developing epithelium into an adult structure is a complex process, which often involves coordinated changes in cell proliferation, metabolism, adhesion, and shape. To identify genetic mechanisms that control epithelial differentiation, we analyzed the temporal patterns of gene expression during metamorphosis of the Drosophila wing.

Results

We found that a striking number of genes, approximately 50% of the Drosophila transcriptome, exhibited changes in expression during a time course of wing development. While cis-acting enhancer sequences clearly correlated with these changes, a stronger correlation was discovered between core-promoter types and the dynamic patterns of gene expression within this differentiating tissue. In support of the hypothesis that core-promoter type influences the dynamics of expression, expression levels of several TATA-box binding protein associated factors (TAFs) and other core promoter-associated components changed during this developmental time course, and a testes-specific TAF (tTAF) played a critical role in timing cellular differentiation within the wing.

Conclusions

Our results suggest that the combinatorial control of gene expression via cis-acting enhancer sequences and core-promoter types, determine the complex changes in gene expression that drive morphogenesis and terminal differentiation of the Drosophila wing epithelium.

Animal models and conserved processes

BACKGROUND

The concept of conserved processes presents unique opportunities for using nonhuman animal models in biomedical research. However, the concept must be examined in the context that humans and nonhuman animals are evolved, complex, adaptive systems. Given that nonhuman animals are examples of living systems that are differently complex from humans, what does the existence of a conserved gene or process imply for inter-species extrapolation?

METHODS

We surveyed the literature including philosophy of science, biological complexity, conserved processes, evolutionary biology, comparative medicine, anti-neoplastic agents, inhalational anesthetics, and drug development journals in order to determine the value of nonhuman animal models when studying conserved processes.

RESULTS

Evolution through natural selection has employed components and processes both to produce the same outcomes among species but also to generate different functions and traits. Many genes and processes are conserved, but new combinations of these processes or different regulation of the genes involved in these processes have resulted in unique organisms. Further, there is a hierarchy of organization in complex living systems. At some levels, the components are simple systems that can be analyzed by mathematics or the physical sciences, while at other levels the system cannot be fully analyzed by reducing it to a physical system. The study of complex living systems must alternate between focusing on the parts and examining the intact whole organism while taking into account the connections between the two. Systems biology aims for this holism. We examined the actions of inhalational anesthetic agents and anti-neoplastic agents in order to address what the characteristics of complex living systems imply for inter-species extrapolation of traits and responses related to conserved processes.

CONCLUSION

We conclude that even the presence of conserved processes is insufficient for inter-species extrapolation when the trait or response being studied is located at higher levels of organization, is in a different module, or is influenced by other modules. However, when the examination of the conserved process occurs at the same level of organization or in the same module, and hence is subject to study solely by reductionism, then extrapolation is possible.

Effects of cis and trans regulatory variations on the expression divergence of heat shock response genes between yeast strains

Phenotypic variation among individuals in a population can be due to DNA sequence variation in protein coding regions or in regulatory elements. Recently, many studies have indicated that mutations in regulatory elements may be the major cause of phenotypic evolution. However, the mechanisms for evolutionary changes in gene expression are still not well understood. Here, we studied the relative roles of cis and trans regulatory changes in Saccharomyces cerevisiae cells to cope with heat stress. It has been found that the expression level of ~300 genes was induced at least two fold and that of ~500 genes was repressed at least two fold in response to heat shock. From the former set of genes, we randomly selected 65 genes that showed polymorphism(s) between the BY and RM strains for pyrosequencing analysis to explore the relative contributions of cis and trans regulatory variations to the expression divergence between BY and RM. Our data indicated that the expression divergence between BY and RM was mainly due to trans regulatory variations under either the normal condition or the heat stress condition. However, the relative contribution of trans regulatory variation was decreased from 76.9% to 61.5% after the heat shock stress. These results indicated that the cis regulatory variation may play an important role in the adaption to heat stress. In our data, 43.1% (28 genes) of the 65 genes showed the same trend of cis or trans variation effect after the heat shock stress, 35.4% (23 genes) showed an increased cis variation effect and 21.5% (14 genes) showed an increased trans variation effect after the heat shock stress. Thus, our data give insights into the relative roles of cis and trans variations in response to heat shock in yeast.

Comparative studies of gene expression and the evolution of gene regulation

The hypothesis that differences in gene regulation have an important role in speciation and adaptation is more than 40 years old. With the advent of new sequencing technologies, we are able to characterize and study gene expression levels and associated regulatory mechanisms in a large number of individuals and species at an unprecedented resolution and scale. We have thus gained new insights into the evolutionary pressures that shape gene expression levels and have developed an appreciation for the relative importance of evolutionary changes in different regulatory genetic and epigenetic mechanisms. The current challenge is to link gene regulatory changes to adaptive evolution of complex phenotypes. Here we mainly focus on comparative studies in primates and how they are complemented by studies in model organisms.

A genomic bias for genotype-environment interactions in C. elegans

The phenotype of an organism is determined by its genotype and environment. An interaction between these two arises from the differential effect of the environment on gene expression in distinct genotypes; however, the genomic properties identifying these are not well understood. Here we analyze the transcriptomes of five C. elegans strains (genotype) cultivated in five growth conditions (environment), and find that highly regulated genes, as distinguished by intergenic lengths, motif concentration, and expression levels, are particularly biased toward genotype-environment interactions. Sequencing these strains, we find that genes with expression variation across genotypes are enriched for promoter single-nucleotide polymorphisms (SNPs), as expected. However, genes with genotype-environment interactions do not significantly differ from background in terms of their promoter SNPs. Collectively, these results indicate that the highly regulated nature of particular genes predispose them for exhibiting genotype-environment interaction as a consequence of changes to upstream regulators. This observation may provide a deeper understanding into the origin of the extraordinary gene expression diversity present in even closely related species.

Population transcriptomics of cactus host shifts in Drosophila mojavensis

In the presence of environmental change, natural selection can shape the transcriptome. Under a scenario of environmental change, genotypes that are better able to modulate gene expression to maximize fitness will tend to be favoured. Therefore, it is important to examine gene expression at the population level to distinguish random or neutral gene expression variation from the pattern produced by natural selection. This study investigates the natural variation in transcriptional response to a cactus host shift utilizing the mainland Sonora population of Drosophila mojavensis. Drosophila mojavensis is a cactophilic species composed of four cactus host populations endemic to the deserts of North America. Overall, the change in cactus host was associated with a significant reduction in larval viability as well as the differential expression of 21% of the genome (3109 genes). Among the genes identified were a set of genes previously known to be involved in xenobiotic metabolism, as well as genes involved in cellular energy production, oxidoreductase/carbohydrate metabolism, structural components and mRNA binding. Interestingly, of the 3109 genes whose expression was affected by host use, there was a significant overrepresentation of genes that lacked an orthologous call to the D. melanogaster genome, suggesting the possibility of an accelerated rate of evolution in these genes. Of the genes with a significant cactus effect, the majority, 2264 genes, did not exhibit a significant cactus-by-line interaction. This population-level approach facilitated the identification of genes involved in past cactus host shifts.

A selection index for gene expression evolution and its application to the divergence between humans and chimpanzees

The importance of gene regulation in animal evolution is a matter of long-standing interest, but measuring the impact of selection on gene expression has proven a challenge. Here, we propose a selection index of gene expression as a straightforward method for assessing the mode and strength of selection operating on gene expression levels. The index is based on the widely used McDonald-Kreitman test and requires the estimation of four quantities: the within-species and between-species expression variances as well as the sequence heterozygosity and divergence of neutrally evolving sequences. We apply the method to data from human and chimpanzee lymphoblastoid cell lines and show that gene expression is in general under strong stabilizing selection. We also demonstrate how the same framework can be used to estimate the proportion of adaptive gene expression evolution.

Promoter nucleosome organization shapes the evolution of gene expression

Understanding why genes evolve at different rates is fundamental to evolutionary thinking. In species of the budding yeast, the rate at which genes diverge in expression correlates with the organization of their promoter nucleosomes: genes lacking a nucleosome-free region (denoted OPN for “Occupied Proximal Nucleosomes”) vary widely between the species, while the expression of those containing NFR (denoted DPN for “Depleted Proximal Nucleosomes”) remains largely conserved. To examine if early evolutionary dynamics contributes to this difference in divergence, we artificially selected for high expression of GFP–fused proteins. Surprisingly, selection was equally successful for OPN and DPN genes, with ∼80% of genes in each group stably increasing in expression by a similar amount. Notably, the two groups adapted by distinct mechanisms: DPN–selected strains duplicated large genomic regions, while OPN–selected strains favored trans mutations not involving duplications. When selection was removed, DPN (but not OPN) genes reverted rapidly to wild-type expression levels, consistent with their lower diversity between species. Our results suggest that promoter organization constrains the early evolutionary dynamics and in this way biases the path of long-term evolution.

Species diverge by mutations that change protein structure or protein regulation. While the evolution of protein sequence was studied extensively, much less is known about the divergence of gene expression. To better understand the process of gene expression evolution, we characterized the early genomic response of yeast cells to selection for high gene expression. Notably, the response to selection was strongly dependent on the organization of the gene promoter: genes whose promoters had a pronounced nucleosome-free region (NFR) primarily duplicated the chromosome containing the gene of interest, while genes whose promoters lacked a pronounced NFR adapted by trans mutations not involving duplications. Further, when selection was removed, the former (but not the later) evolved strains reverted rapidly to wild-type expression levels, consistent with their lower diversity between species. Together, our study provides strong support to the idea that physiological regulation impacts the evolutionary path and suggests that, by regulating promoter nucleosomes, cells can regulate the response to selection and control the long-term stability of the selected changes.

Tempo and mode in evolution of transcriptional regulation

Perennial questions of evolutionary biology can be applied to gene regulatory systems using the abundance of experimental data addressing gene regulation in a comparative context. What is the tempo (frequency, rate) and mode (way, mechanism) of transcriptional regulatory evolution? Here we synthesize the results of 230 experiments performed on insects and nematodes in which regulatory DNA from one species was used to drive gene expression in another species. General principles of regulatory evolution emerge. Gene regulatory evolution is widespread and accumulates with genetic divergence in both insects and nematodes. Divergence in cis is more common than divergence in trans. Coevolution between cis and trans shows a particular increase over greater evolutionary timespans, especially in sex-specific gene regulation. Despite these generalities, the evolution of gene regulation is gene- and taxon-specific. The congruence of these conclusions with evidence from other types of experiments suggests that general principles are discoverable, and a unified view of the tempo and mode of regulatory evolution may be achievable.

A genome-wide analysis of promoter-mediated phenotypic noise in Escherichia coli

Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alone.

Many biological processes in a cell involve small numbers of molecules and therefore fluctuate over time. As a consequence, genetically identical cells that live in the same environment differ from each other in many phenotypic traits, including the expression level of different genes. Our aim was to identify types of genes with particularly low or high levels of variation (“noise”) and to understand molecular and evolutionary factors that determine noise level. Working with the bacterium E. coli, we analyzed the expression—at the single cell level—of more than 1,500 different genes. We found particularly low levels of noise in genes that E. coli needs to live and genes that this bacterium shares with many related taxa. This suggests that cellular functions that are particularly important for this organism evolved towards low levels of variation. In contrast to previous results with yeast, we find that genes that change their expression levels in response to environmental signals do not have high levels of noise. This suggests that there may be fundamental differences in how noise is controlled in bacteria and eukaryotes.

Allelic imbalance in Drosophila hybrid heads: exons, isoforms, and evolution

Unraveling how regulatory divergence contributes to species differences and adaptation requires identifying functional variants from among millions of genetic differences. Analysis of allelic imbalance (AI) reveals functional genetic differences in cis regulation and has demonstrated differences in cis regulation within and between species. Regulatory mechanisms are often highly conserved, yet differences between species in gene expression are extensive. What evolutionary forces explain widespread divergence in cis regulation? AI was assessed in Drosophila melanogaster-Drosophila simulans hybrid female heads using RNA-seq technology. Mapping bias was virtually eliminated by using genotype-specific references. Allele representation in DNA sequencing was used as a prior in a novel Bayesian model for the estimation of AI in RNA. Cis regulatory divergence was common in the organs and tissues of the head with 41% of genes analyzed showing significant AI. Using existing population genomic data, the relationship between AI and patterns of sequence evolution was examined. Evidence of positive selection was found in 30% of cis regulatory divergent genes. Genes involved in defense, RNAi/RISC complex genes, and those that are sex regulated are enriched among adaptively evolving cis regulatory divergent genes. For genes in these groups, adaptive evolution may play a role in regulatory divergence between species. However, there is no evidence that adaptive evolution drives most of the cis regulatory divergence that is observed. The majority of genes showed patterns consistent with stabilizing selection and neutral evolutionary processes.

Animal models in an age of personalized medicine

Personalized medicine is based on intraspecies differences. It is axiomatic that small differences in genetic make-up can result in dramatic differences in response to drugs or disease. To express this in more general terms: in any given complex system, small changes in initial conditions can result in dramatically different outcomes. Despite human variability and intraspecies variation in other species, nonhuman species are still the primary model for ascertaining data for humans. We call this practice into question and conclude that human-based research should be the primary means for obtaining data about human diseases and responses to drugs.

Using genomic tools to study regulatory evolution

Differences in gene regulation are thought to play an important role in speciation and adaptation. Comparative genomic studies of gene expression levels have identified a large number of differentially expressed genes among species, and, in a number of cases, also pointed to connections between interspecies differences in gene regulation and differences in ultimate physiological or morphological phenotypes. The mechanisms underlying changes in gene regulation are also being actively studied using comparative genomic approaches. However, the relative importance of different regulatory mechanisms to interspecies differences in gene expression levels is not yet well understood. In particular, it is often difficult to infer causality between apparent differences in regulatory mechanisms and changes in gene expression levels, a challenge that is compounded by the fact that the link between sequence variation and gene regulation is not clear. Indeed, in certain cases, gene regulation can be conserved even when sequences at associated regulatory elements have changed. In this chapter, I examine different genomic approaches to the study of regulatory evolution and the underlying genetic and epigenetic regulatory mechanisms. I try to distinguish between hypothesis-driven and exploratory studies, and argue that the latter class of studies provides valuable information in its own right as well as necessary context for the former. I discuss issues related to study designs and statistical analyses of genomic studies, and review the evidence for natural selection on gene expression levels and associated regulatory mechanisms. Most of the issues that are discussed pertain to the general nature of multivariate genomic data, and thus are often relevant regardless of the technology that is used to collect high-throughput genomic data (for example, microarrays or massively parallel sequencing).

The evolution of gene expression and the transcriptome-phenotype relationship

Changes in gene expression underlie the adaptive evolution in many complex phenotypes, and the recent increase in the availability of multi-species comparative transcriptome data has made it possible to scan whole transcriptomes for loci that have experienced adaptive changes in expression. However, despite the increase in data availability, current models of gene expression evolution often do not account for the complexities and inherent noise associated with transcriptome data. Additionally, in contrast to current models of gene sequence evolution, models of transcriptome evolution often lack the sophistication to effectively determine whether transcriptional differences between species or within a clade are the result of neutral or adaptive processes. In this review, we discuss the tools, methods and models that define our current understanding of the relationship between gene expression and complex phenotype evolution. Our goal is to summarize what we know about the evolution of global gene expression patterns underlying complex traits, as well to identify some of the questions that remain to be answered.

Partitioning transcript variation in Drosophila: abundance, isoforms, and alleles

Multilevel analysis of transcription is facilitated by a new array design that includes modules for assessment of differential expression, isoform usage, and allelic imbalance in Drosophila. The ∼2.5 million feature chip incorporates a large number of controls, and it contains 18,769 3' expression probe sets and 61,919 exon probe sets with probe sequences from Drosophila melanogaster and 60,118 SNP probe sets focused on Drosophila simulans. An experiment in D. simulans identified genes differentially expressed between males and females (34% in the 3' expression module; 32% in the exon module). These proportions are consistent with previous reports, and there was good agreement (κ = 0.63) between the modules. Alternative isoform usage between the sexes was identified for 164 genes. The SNP module was verified with resequencing data. Concordance between resequencing and the chip design was greater than 99%. The design also proved apt in separating alleles based upon hybridization intensity. Concordance between the highest hybridization signals and the expected alleles in the genotype was greater than 96%. Intriguingly, allelic imbalance was detected for 37% of 6579 probe sets examined that contained heterozygous SNP loci. The large number of probes and multiple probe sets per gene in the 3' expression and exon modules allows the array to be used in D. melanogaster and in closely related species. The SNP module can be used for allele specific expression and genotyping of D. simulans.

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.

Meta Analysis of Gene Expression Data within and Across Species

Since the second half of the 1990s, a large number of genome-wide analyses have been described that study gene expression at the transcript level. To this end, two major strategies have been adopted, a first one relying on hybridization techniques such as microarrays, and a second one based on sequencing techniques such as serial analysis of gene expression (SAGE), cDNA-AFLP, and analysis based on expressed sequence tags (ESTs). Despite both types of profiling experiments becoming routine techniques in many research groups, their application remains costly and laborious. As a result, the number of conditions profiled in individual studies is still relatively small and usually varies from only two to few hundreds of samples for the largest experiments. More and more, scientific journals require the deposit of these high throughput experiments in public databases upon publication. Mining the information present in these databases offers molecular biologists the possibility to view their own small-scale analysis in the light of what is already available. However, so far, the richness of the public information remains largely unexploited. Several obstacles such as the correct association between ESTs and microarray probes with the corresponding gene transcript, the incompleteness and inconsistency in the annotation of experimental conditions, and the lack of standardized experimental protocols to generate gene expression data, all impede the successful mining of these data. Here, we review the potential and difficulties of combining publicly available expression data from respectively EST analyses and microarray experiments. With examples from literature, we show how meta-analysis of expression profiling experiments can be used to study expression behavior in a single organism or between organisms, across a wide range of experimental conditions. We also provide an overview of the methods and tools that can aid molecular biologists in exploiting these public data.

Linking fold, function and phylogeny: a comparative genomics view on protein (domain) evolution

Domains are the building blocks of all globular proteins and present one of the most useful levels at which protein function can be understood. Through recombination and duplication of a limited set of domains, proteomes evolved and the collection of protein superfamilies in an organism formed. As such, the presence of a shared domain can be regarded as an indicator of similar function and evolutionary history, but it does not necessarily imply it since convergent evolution may give rise to similar gene functions as well as architectures.Through the wealth of sequences and annotation data brought about by genomics, evolutionary links can be sought for via homology relationships and comparative genomics, structural modeling and phylogenetics. The goal hereby is not only to predict the function of newly discovered proteins, but also to spell out their pathway of evolution and, possibly, identify their most likely origin. This can ultimately help to understand protein function and functional relationships of protein families. Additionally, through comparison with transcriptional data, evolutionary data can be linked to gene (and genome) activity and thus allow for the identification of common principles behind fast evolving proteins and relatively stable ones.In this review, we describe the basic principles of studying protein (domain) evolution and illustrate recent developments in molecular evolution and give valuable new insights in the field of comparative genomics. As an example, we include here molecular models of the multiple PDZ domain protein MUPP-1 and present a simple comparative genomic view on its structural course of evolution.

A comparison of the low temperature transcriptomes and CBF regulons of three plant species that differ in freezing tolerance: Solanum commersonii, Solanum tuberosum, and Arabidopsis thaliana

Solanum commersonii and Solanum tuberosum are closely related plant species that differ in their abilities to cold acclimate; whereas S. commersonii increases in freezing tolerance in response to low temperature, S. tuberosum does not. In Arabidopsis thaliana, cold-regulated genes have been shown to contribute to freezing tolerance, including those that comprise the CBF regulon, genes that are controlled by the CBF transcription factors. The low temperature transcriptomes and CBF regulons of S. commersonii and S. tuberosum were therefore compared to determine whether there might be differences that contribute to their differences in ability to cold acclimate. The results indicated that both plants alter gene expression in response to low temperature to similar degrees with similar kinetics and that both plants have CBF regulons composed of hundreds of genes. However, there were considerable differences in the sets of genes that comprised the low temperature transcriptomes and CBF regulons of the two species. Thus differences in cold regulatory programmes may contribute to the differences in freezing tolerance of these two species. However, 53 groups of putative orthologous genes that are cold-regulated in S. commersonii, S. tuberosum, and A. thaliana were identified. Given that the evolutionary distance between the two Solanum species and A. thaliana is 112-156 million years, it seems likely that these conserved cold-regulated genes-many of which encode transcription factors and proteins of unknown function-have fundamental roles in plant growth and development at low temperature.

Evolutionary origin of a novel gene expression pattern through co-option of the latent activities of existing regulatory sequences

Spatiotemporal changes in gene expression underlie many evolutionary novelties in nature. However, the evolutionary origins of novel expression patterns, and the transcriptional control elements ("enhancers") that govern them, remain unclear. Here, we sought to explore the molecular genetic mechanisms by which new enhancers arise. We undertook a survey of closely related Drosophila species to identify recently evolved novel gene expression patterns and traced their evolutionary history. Analyses of gene expression in a variety of developing tissues of the Drosophila melanogaster species subgroup revealed high rates of expression pattern divergence, including numerous evolutionary losses, heterochronic shifts, and expansions or contractions of expression domains. However, gains of novel expression patterns were much less frequent. One gain was observed for the Neprilysin-1 (Nep1) gene, which has evolved a unique expression pattern in optic lobe neuroblasts of Drosophila santomea. Dissection of the Nep1 cis-regulatory region localized a newly derived optic lobe enhancer activity to a region of an intron that has accumulated a small number of mutations. The Nep1 optic lobe enhancer overlaps with other enhancer activities, from which the novel activity was co-opted. We suggest that the novel optic lobe enhancer evolved by exploiting the cryptic activity of extant regulatory sequences, and this may reflect a general mechanism whereby new enhancers evolve.

Mapping gene expression in two Xenopus species: evolutionary constraints and developmental flexibility

Changes in gene expression are thought to be important for morphological evolution, though little is known about the nature or magnitude of the differences. Here, we examine Xenopus laevis and Xenopus tropicalis, two amphibians with very similar development, and ask how their transcriptomes compare. Despite separation for ~30-90 million years, there is strong conservation in gene expression in the vast majority of the expressed orthologs. Significant changes occur in the level of gene expression but changes in the timing of expression (heterochrony) were much less common. Differences in level were concentrated in the earliest embryonic stages. Changes in timing were prominently found in pathways that respond to selective features of the environment. We propose that different evolutionary rates across developmental stages may be explained by the stabilization of cell fate determination in the later stages.

Divergent transcriptional response to thermal stress by Anopheles gambiae larvae carrying alternative arrangements of inversion 2La

The African malaria mosquito Anopheles gambiae is polymorphic for chromosomal inversion 2La, whose frequency strongly correlates with degree of aridity across environmental gradients. Recent physiological studies have associated 2La with resistance to desiccation in adults and thermal stress in larvae, consistent with its proposed role in aridity tolerance. However, the genetic basis of these traits remains unknown. To identify genes that could be involved in the differential response to thermal stress, we compared global gene expression profiles of heat-hardened 2La or 2L+(a) larvae at three time points, for up to eight hours following exposure to the heat stress. Treatment and control time series, replicated four times, revealed a common and massive induction of a core set of heat-shock genes regardless of 2La orientation. However, clear differences between the 2La and 2L+(a) arrangements emerged at the earliest (0.25 h) time point, in the intensity and nature of the stress response. Overall, 2La was associated with the more aggressive response: larger numbers of genes were heat responsive and up-regulated. Transcriptionally induced genes were enriched for functions related to ubiquitin-proteasomal degradation, chaperoning and energy metabolism. The more muted transcriptional response of 2L+(a) was largely repressive, including genes involved in proteolysis and energy metabolism. These results may help explain the maintenance of the 2La inversion polymorphism in An. gambiae, as the survival benefits offered by high thermal sensitivity in harsh climates could be offset by the metabolic costs of such a drastic response in more equable climates.