Conservation and evolvability in regulatory networks: the evolution of ribosomal regulation in yeast

The Rtf1/Prf1-dependent histone modification axis counteracts multi-drug resistance in fission yeast

RNA polymerase II transcription elongation directs an intricate pattern of histone modifications. This pattern includes a regulatory cascade initiated by the elongation factor Rtf1, leading to monoubiquitylation of histone H2B, and subsequent methylation of histone H3 on lysine 4. Previous studies have defined the molecular basis for these regulatory relationships, but it remains unclear how they regulate gene expression. To address this question, we investigated a drug resistance phenotype that characterizes defects in this axis in the model eukaryote Schizosaccharomyces pombe (fission yeast). The mutations caused resistance to the ribonucleotide reductase inhibitor hydroxyurea (HU) that correlated with a reduced effect of HU on dNTP pools, reduced requirement for the S-phase checkpoint, and blunting of the transcriptional response to HU treatment. Mutations in the C-terminal repeat domain of the RNA polymerase II large subunit Rpb1 led to similar phenotypes. Moreover, all the HU-resistant mutants also exhibited resistance to several azole-class antifungal agents. Our results suggest a novel, shared gene regulatory function of the Rtf1-H2Bub1-H3K4me axis and the Rpb1 C-terminal repeat domain in controlling fungal drug tolerance.

Stem cell transcriptional profiles from mouse subspecies reveal cis-regulatory evolution at translation genes

A key goal of evolutionary genomics is to harness molecular data to draw inferences about selective forces that have acted on genomes. The field progresses in large part through the development of advanced molecular-evolution analysis methods. Here we explored the intersection between classical sequence-based tests for selection and an empirical expression-based approach, using stem cells from Mus musculus subspecies as a model. Using a test of directional, cis-regulatory evolution across genes in pathways, we discovered a unique program of induction of translation genes in stem cells of the Southeast Asian mouse M. m. castaneus relative to its sister taxa. As a complement, we used sequence analyses to find population-genomic signatures of selection in M. m. castaneus, at the upstream regions of the translation genes, including at transcription factor binding sites. We interpret our data under a model of changes in lineage-specific pressures across Mus musculus in stem cells with high translational capacity. Together, our findings underscore the rigor of integrating expression and sequence-based methods to generate hypotheses about evolutionary events from long ago.

Species-aware DNA language models capture regulatory elements and their evolution

BACKGROUND

The rise of large-scale multi-species genome sequencing projects promises to shed new light on how genomes encode gene regulatory instructions. To this end, new algorithms are needed that can leverage conservation to capture regulatory elements while accounting for their evolution.

RESULTS

Here, we introduce species-aware DNA language models, which we trained on more than 800 species spanning over 500 million years of evolution. Investigating their ability to predict masked nucleotides from context, we show that DNA language models distinguish transcription factor and RNA-binding protein motifs from background non-coding sequence. Owing to their flexibility, DNA language models capture conserved regulatory elements over much further evolutionary distances than sequence alignment would allow. Remarkably, DNA language models reconstruct motif instances bound in vivo better than unbound ones and account for the evolution of motif sequences and their positional constraints, showing that these models capture functional high-order sequence and evolutionary context. We further show that species-aware training yields improved sequence representations for endogenous and MPRA-based gene expression prediction, as well as motif discovery.

CONCLUSIONS

Collectively, these results demonstrate that species-aware DNA language models are a powerful, flexible, and scalable tool to integrate information from large compendia of highly diverged genomes.

Gene loss and cis-regulatory novelty shaped core histone gene evolution in the apiculate yeast Hanseniaspora uvarum

Core histone genes display a remarkable diversity of cis-regulatory mechanisms despite their protein sequence conservation. However, the dynamics and significance of this regulatory turnover are not well understood. Here, we describe the evolutionary history of core histone gene regulation across 400 million years in budding yeasts. We find that canonical mode of core histone regulation-mediated by the trans-regulator Spt10-is ancient, likely emerging between 320 and 380 million years ago and is fixed in the majority of extant species. Unexpectedly, we uncovered the emergence of a novel core histone regulatory mode in the Hanseniaspora genus, from its fast-evolving lineage, which coincided with the loss of 1 copy of its paralogous core histone genes. We show that the ancestral Spt10 histone regulatory mode was replaced, via cis-regulatory changes in the histone control regions, by a derived Mcm1 histone regulatory mode and that this rewiring event occurred with no changes to the trans-regulator, Mcm1, itself. Finally, we studied the growth dynamics of the cell cycle and histone synthesis in genetically modified Hanseniaspora uvarum. We find that H. uvarum divides rapidly, with most cells completing a cell cycle within 60 minutes. Interestingly, we observed that the regulatory coupling between histone and DNA synthesis was lost in H. uvarum. Our results demonstrate that core histone gene regulation was fixed anciently in budding yeasts, however it has greatly diverged in the Hanseniaspora fast-evolving lineage.

Rapid evolutionary repair by secondary perturbation of a primary disrupted transcriptional network

The discrete steps of transcriptional rewiring have been proposed to occur neutrally to ensure steady gene expression under stabilizing selection. A conflict-free switch of a regulon between regulators may require an immediate compensatory evolution to minimize deleterious effects. Here, we perform an evolutionary repair experiment on the Lachancea kluyveri yeast sef1Δ mutant using a suppressor development strategy. Complete loss of SEF1 forces cells to initiate a compensatory process for the pleiotropic defects arising from misexpression of TCA cycle genes. Using different selective conditions, we identify two adaptive loss-of-function mutations of IRA1 and AZF1. Subsequent analyses show that Azf1 is a weak transcriptional activator regulated by the Ras1-PKA pathway. Azf1 loss-of-function triggers extensive gene expression changes responsible for compensatory, beneficial, and trade-off phenotypes. The trade-offs can be alleviated by higher cell density. Our results not only indicate that secondary transcriptional perturbation provides rapid and adaptive mechanisms potentially stabilizing the initial stage of transcriptional rewiring but also suggest how genetic polymorphisms of pleiotropic mutations could be maintained in the population.

Cis-regulatory variants affect gene expression dynamics in yeast

Evolution of cis-regulatory sequences depends on how they affect gene expression and motivates both the identification and prediction of cis-regulatory variants responsible for expression differences within and between species. While much progress has been made in relating cis-regulatory variants to expression levels, the timing of gene activation and repression may also be important to the evolution of cis-regulatory sequences. We investigated allele-specific expression (ASE) dynamics within and between Saccharomyces species during the diauxic shift and found appreciable cis-acting variation in gene expression dynamics. Within-species ASE is associated with intergenic variants, and ASE dynamics are more strongly associated with insertions and deletions than ASE levels. To refine these associations, we used a high-throughput reporter assay to test promoter regions and individual variants. Within the subset of regions that recapitulated endogenous expression, we identified and characterized cis-regulatory variants that affect expression dynamics. Between species, chimeric promoter regions generate novel patterns and indicate constraints on the evolution of gene expression dynamics. We conclude that changes in cis-regulatory sequences can tune gene expression dynamics and that the interplay between expression dynamics and other aspects of expression is relevant to the evolution of cis-regulatory sequences.

The Path towards Predicting Evolution as Illustrated in Yeast Cell Polarity

A bottom-up route towards predicting evolution relies on a deep understanding of the complex network that proteins form inside cells. In a rapidly expanding panorama of experimental possibilities, the most difficult question is how to conceptually approach the disentangling of such complex networks. These can exhibit varying degrees of hierarchy and modularity, which obfuscate certain protein functions that may prove pivotal for adaptation. Using the well-established polarity network in budding yeast as a case study, we first organize current literature to highlight protein entrenchments inside polarity. Following three examples, we see how alternating between experimental novelties and subsequent emerging design strategies can construct a layered understanding, potent enough to reveal evolutionary targets. We show that if you want to understand a cell’s evolutionary capacity, such as possible future evolutionary paths, seemingly unimportant proteins need to be mapped and studied. Finally, we generalize this research structure to be applicable to other systems of interest.

Evolutionary Repair Experiments as a Window to the Molecular Diversity of Life

Comparative genomics reveals an unexpected diversity in the molecular mechanisms underlying conserved cellular functions, such as DNA replication and cytokinesis. However, the genetic bases and evolutionary processes underlying this 'molecular diversity' remain to be explained. Here, we review a tool to generate alternative mechanisms for conserved cellular functions and test hypotheses concerning the generation of molecular diversity - evolutionary repair experiments, in which laboratory microbial populations adapt in response to a genetic perturbation. We summarize the insights gained from evolutionary repair experiments, the spectrum and dynamics of compensatory mutations, and the alternative molecular mechanisms used to repair perturbed cellular functions. We relate these experiments to the modifications of conserved functions that have occurred outside the laboratory. We end by proposing strategies to improve evolutionary repair experiments as a tool to explore the molecular diversity of life.

A Theoretical Framework for Evolutionary Cell Biology

One of the last uncharted territories in evolutionary biology concerns the link with cell biology. Because all phenotypes ultimately derive from events at the cellular level, this connection is essential to building a mechanism-based theory of evolution. Given the impressive developments in cell biological methodologies at the structural and functional levels, the potential for rapid progress is great. The primary challenge for theory development is the establishment of a quantitative framework that transcends species boundaries. Two approaches to the problem are presented here: establishing the long-term steady-state distribution of mean phenotypes under specific regimes of mutation, selection, and drift and evaluating the energetic costs of cellular structures and functions. Although not meant to be the final word, these theoretical platforms harbor potential for generating insight into a diversity of unsolved problems, ranging from genome structure to cellular architecture to aspects of motility in organisms across the Tree of Life.

A Novel cis Element Achieves the Same Solution as an Ancestral cis Element During Thiamine Starvation in Candida glabrata

Regulatory networks often converge on very similar cis sequences to drive transcriptional programs due to constraints on what transcription factors are present. To determine the role of constraint loss on cis element evolution, we examined the recent appearance of a thiamine starvation regulated promoter in Candida glabrata. This species lacks the ancestral transcription factor Thi2, but still has the transcription factor Pdc2, which regulates thiamine starvation genes, allowing us to determine the effect of constraint change on a new promoter. We identified two different cis elements in C. glabrata - one present in the evolutionarily recent gene called CgPMU3, and the other element present in the other thiamine (THI) regulated genes. Reciprocal swaps of the cis elements and incorporation of the S. cerevisiaeThi2 transcription factor-binding site into these promoters demonstrate that the two elements are functionally different from one another. Thus, this loss of an imposed constraint on promoter function has generated a novel cis sequence, suggesting that loss of trans constraints can generate a non-convergent pathway with the same output.

Introducing Trait Networks to Elucidate the Fluidity of Organismal Evolution Using Palaeontological Data

Explaining the evolution of animals requires ecological, developmental, paleontological, and phylogenetic considerations because organismal traits are affected by complex evolutionary processes. Modeling a plurality of processes, operating at distinct time-scales on potentially interdependent traits, can benefit from approaches that are complementary treatments to phylogenetics. Here, we developed an inclusive network approach, implemented in the command line software ComponentGrapher, and analyzed trait co-occurrence of rhinocerotoid mammals. We identified stable, unstable, and pivotal traits, as well as traits contributing to complexes, that may follow to a common developmental regulation, that point to an early implementation of the postcranial Bauplan among rhinocerotoids. Strikingly, most identified traits are highly dissociable, used repeatedly in distinct combinations and in different taxa, which usually do not form clades. Therefore, the genes encoding these traits are likely recruited into novel gene regulation networks during the course of evolution. Our evo-systemic framework, generalizable to other evolved organizations, supports a pluralistic modeling of organismal evolution, including trees and networks.

Progress in the identification of gene mutations involved in multiple myeloma

Sequencing studies have been used to determine a spectrum of multiple myeloma (MM) mutations. Mutation of certain genes, including KRAS, NRAS, TP53, FAM46C, DIS3 and BRAF, have a high recurrence rate and may play important roles in the pathogenesis, progression and prognosis of MM. Mutations in DIS3, which encodes a highly conserved RNA exonuclease, lead to loss of function. The expression of FAM46C is highly correlated with the expression of ribosomal protein, but the exact function of FAM46C mutation is unclear. There are mutants of IRF4, which is considered an MM survival factor. Mutations in the gene coding for the DNA damage-binding protein (DDB1) may affect interactions with CUL4A, which is part of the cereblon (CRBN) ubiquitin ligase complex. IRF4is part of the complex, which binds to DNA. These findings might explain the resistance to immunomodulatory. TP53 deletion or mutation is often present in B-cell malignancies and is associated with low response rates. Myeloma pathogenic mutations in ATM have been found in adult lymphatic tumors. XBP1 and PSMB5 mutations may be related to bortezomib resistance. Multiple gene mutations (KRAS, NRAS and BRAF) involved in the same pathway were found a single patient. Identification of driver gene mutations has brought great hope to the field of individualized, targeted medicine for MM.

Functional duplication of Rap1 in methylotrophic yeasts

The telomere regulator and transcription factor Rap1 is the only telomere protein conserved in yeasts and mammals. Its functional repertoire in budding yeasts is a particularly interesting field for investigation, given the high evolutionary diversity of this group of unicellular organisms. In the methylotrophic thermotolerant species Hansenula polymorpha DL-1 the RAP1 gene is duplicated (HpRAP1A and HpRAP1B). Here, we report the functional characterization of the two paralogues from H. polymorpha DL-1. We uncover distinct (but overlapping) DNA binding preferences of HpRap1A and HpRap1B proteins. We show that only HpRap1B is able to recognize telomeric DNA directly and to protect it from excessive recombination, whereas HpRap1A is associated with subtelomere regions. Furthermore, we identify specific binding sites for both HpRap1A and HpRap1B within promoters of a large number of ribosomal protein genes (RPGs), implicating Rap1 in the control of the RP regulon in H. polymorpha. Our bioinformatic analysis suggests that RAP1 was duplicated early in the evolution of the “methylotrophs” clade, and the two genes evolved independently. Therefore, our characterization of Rap1 paralogues in H. polymorpha may be relevant to other “methylotrophs”, yielding valuable insights into the evolution of budding yeasts.

Dynamic Targeting in Cancer Treatment

With the advent of personalized medicine, design and development of anti-cancer drugs that are specifically targeted to individual or sets of genes or proteins has been an active research area in both academia and industry. The underlying motivation for this approach is to interfere with several pathological crosstalk pathways in order to inhibit or at the very least control the proliferation of cancer cells. However, after initially conferring beneficial effects, if sub-lethal, these artificial perturbations in cell function pathways can inadvertently activate drug-induced up- and down-regulation of feedback loops, resulting in dynamic changes over time in the molecular network structure and potentially causing drug resistance as seen in clinics. Hence, the targets or their combined signatures should also change in accordance with the evolution of the network (reflected by changes to the structure and/or functional output of the network) over the course of treatment. This suggests the need for a "dynamic targeting" strategy aimed at optimizing tumor control by interfering with different molecular targets, at varying stages. Understanding the dynamic changes of this complex network under various perturbed conditions due to drug treatment is extremely challenging under experimental conditions let alone in clinical settings. However, mathematical modeling can facilitate studying these effects at the network level and beyond, and also accelerate comparison of the impact of different dosage regimens and therapeutic modalities prior to sizeable investment in risky and expensive clinical trials. A dynamic targeting strategy based on the use of mathematical modeling can be a new, exciting research avenue in the discovery and development of therapeutic drugs.

New insights into Phakopsora pachyrhizi infection based on transcriptome analysis in planta

Asian soybean rust (ASR) is one of the most destructive diseases affecting soybeans. The causative agent of ASR, the fungus Phakopsora pachyrhizi, presents characteristics that make it difficult to study in vitro, limiting our knowledge of plant-pathogen dynamics. Therefore, this work used leaf lesion laser microdissection associated with deep sequencing to determine the pathogen transcriptome during compatible and incompatible interactions with soybean. The 36,350 generated unisequences provided an overview of the main genes and biological pathways that were active in the fungus during the infection cycle. We also identified the most expressed transcripts, including sequences similar to other fungal virulence and signaling proteins. Enriched P. pachyrhizi transcripts in the resistant (PI561356) soybean genotype were related to extracellular matrix organization and metabolic signaling pathways and, among infection structures, in amino acid metabolism and intracellular transport. Unisequences were further grouped into gene families along predicted sequences from 15 other fungi and oomycetes, including rust fungi, allowing the identification of conserved multigenic families, as well as being specific to P. pachyrhizi. The results revealed important biological processes observed in P. pachyrhizi, contributing with information related to fungal biology and, consequently, a better understanding of ASR.

Intrinsic cooperativity potentiates parallel cis-regulatory evolution

Convergent evolutionary events in independent lineages provide an opportunity to understand why evolution favors certain outcomes over others. We studied such a case where a large set of genes-those coding for the ribosomal proteins-gained cis-regulatory sequences for a particular transcription regulator (Mcm1) in independent fungal lineages. We present evidence that these gains occurred because Mcm1 shares a mechanism of transcriptional activation with an ancestral regulator of the ribosomal protein genes, Rap1. Specifically, we show that Mcm1 and Rap1 have the inherent ability to cooperatively activate transcription through contacts with the general transcription factor TFIID. Because the two regulatory proteins share a common interaction partner, the presence of one ancestral cis-regulatory sequence can 'channel' random mutations into functional sites for the second regulator. At a genomic scale, this type of intrinsic cooperativity can account for a pattern of parallel evolution involving the fixation of hundreds of substitutions.

Patterns of Conservation and Diversification in the Fungal Polarization Network

The combined actions of proteins in networks underlie all fundamental cellular functions. Deeper insights into the dynamics of network composition across species and their functional consequences are crucial to fully understand protein network evolution. Large-scale comparative studies with high phylogenetic resolution are now feasible through the recent rise in available genomic data sets of both model and nonmodel species. Here, we focus on the polarity network, which is universally essential for cell proliferation and studied in great detail in the model organism, Saccharomyces cerevisiae. We examine 42 proteins, directly related to cell polarization, across 298 fungal strains/species to determine the composition of the network and patterns of conservation and diversification. We observe strong protein conservation for a group of 23 core proteins: >95% of all examined strains/species possess at least 14 of these core proteins, albeit in varying compositions, and non of the individual core proteins is 100% conserved. We find high levels of variation in prevalence and sequence identity in the remaining 19 proteins, resulting in distinct lineage-specific compositions of the network in the majority of strains/species. We show that the observed diversification in network composition correlates with lineage, lifestyle, and genetic distance. Yeast, filamentous and basal unicellular fungi, form distinctive groups based on these analyses, with substantial differences to their polarization network. Our study shows that the fungal polarization network is highly dynamic, even between closely related species, and that functional conservation appears to be achieved by varying the specific components of the fungal polarization repertoire.

Archetypal transcriptional blocks underpin yeast gene regulation in response to changes in growth conditions

The transcriptional responses of yeast cells to diverse stresses typically include gene activation and repression. Specific stress defense, citric acid cycle and oxidative phosphorylation genes are activated, whereas protein synthesis genes are coordinately repressed. This view was achieved from comparative transcriptomic experiments delineating sets of genes whose expression greatly changed with specific stresses. Less attention has been paid to the biological significance of 1) consistent, albeit modest, changes in RNA levels across multiple conditions, and 2) the global gene expression correlations observed when comparing numerous genome-wide studies. To address this, we performed a meta-analysis of 1379 microarray-based experiments in yeast, and identified 1388 blocks of RNAs whose expression changes correlate across multiple and diverse conditions. Many of these blocks represent sets of functionally-related RNAs that act in a coordinated fashion under normal and stress conditions, and map to global cell defense and growth responses. Subsequently, we used the blocks to analyze novel RNA-seq experiments, demonstrating their utility and confirming the conclusions drawn from the meta-analysis. Our results provide a new framework for understanding the biological significance of changes in gene expression: 'archetypal' transcriptional blocks that are regulated in a concerted fashion in response to external stimuli.

Development of a yeast heterologous expression cassette based on the promoter and terminator elements of the Eremothecium cymbalariae translational elongation factor 1α (EcTEF1) gene

A new expression cassette (EC0) consisting of the fused 5′ and 3′ intergenic regions (IGRs) of the Eremothecium cymbalariae translational elongation factor 1α (EcTEF1) gene was evaluated through expression of the bacterial hygromycin B phosphotransferase (hph) resistance gene in the common baker’s yeast Saccharomyces cerevisiae. Progressively shorter versions of the hph-containing EC cassette (hphEC1 though hphEC6) with trimmed 5′ and 3′ EcTEF1 IGRs were tested for their ability to confer resistance to hygromycin B in S. cerevisiae. Hygromycin B resistance was retained in all six generated hphEC variants up to a concentration of 400 mg/L. The hphEC6 cassette was the shortest cassette to be assayed in this study with 366 and 155 bp of the EcTEF1 5′ and 3′ IGRs, respectively. When tested for deletion of the S. cerevisiae proline oxidase gene PUT1, the hphEC6 cassette was shown to successfully act as a selection marker on hygromycin B-containing medium. The hphEC6 cassette could be placed immediately adjacent to a kanMX4 G418 disulfate resistance marker without any discernable effect on the ability of the yeast to grow in the presence of both hygromycin B and G418 disulfate. Co-cultivation experiments under non-selective conditions demonstrated that a PUT1 deletion strain carrying the hphEC6 cassette displayed equivalent fitness to an otherwise isogenic PUT1 deletion strain carrying the kanMX4 cassette.

How transcription circuits explore alternative architectures while maintaining overall circuit output

This review by Dalal and Johnson focuses on the evolutionary rewiring of transcription regulators and the conservation of patterns of gene expression. They describe how preservation of gene expression patterns in the wake of extensive rewiring is a general feature of transcription circuit evolution.

Transcription regulators bind to cis-regulatory sequences and thereby control the expression of target genes. While transcription regulators and the target genes that they regulate are often deeply conserved across species, the connections between the two change extensively over evolutionary timescales. In this review, we discuss case studies where, despite this extensive evolutionary rewiring, the resulting patterns of gene expression are preserved. We also discuss in silico models that reach the same general conclusions and provide additional insights into how this process occurs. Together, these approaches make a strong case that the preservation of gene expression patterns in the wake of extensive rewiring is a general feature of transcription circuit evolution.

A sequence-specific core promoter-binding transcription factor recruits TRF2 to coordinately transcribe ribosomal protein genes

Ribosomal protein (RP) genes must be coordinately expressed for proper assembly of the ribosome yet the mechanisms that control expression of RP genes in metazoans are poorly understood. Recently, TATA-binding protein-related factor 2 (TRF2) rather than the TATA-binding protein (TBP) was found to function in transcription of RP genes in Drosophila. Unlike TBP, TRF2 lacks sequence-specific DNA binding activity, so the mechanism by which TRF2 is recruited to promoters is unclear. We show that the transcription factor M1BP, which associates with the core promoter region, activates transcription of RP genes. Moreover, M1BP directly interacts with TRF2 to recruit it to the RP gene promoter. High resolution ChIP-exo was used to analyze in vivo the association of M1BP, TRF2 and TFIID subunit, TAF1. Despite recent work suggesting that TFIID does not associate with RP genes in Drosophila, we find that TAF1 is present at RP gene promoters and that its interaction might also be directed by M1BP. Although M1BP associates with thousands of genes, its colocalization with TRF2 is largely restricted to RP genes, suggesting that this combination is key to coordinately regulating transcription of the majority of RP genes in Drosophila.

Ribosomal DNA copy number amplification and loss in human cancers is linked to tumor genetic context, nucleolus activity, and proliferation

Ribosomal RNAs (rRNAs) are transcribed from two multicopy DNA arrays: the 5S ribosomal DNA (rDNA) array residing in a single human autosome and the 45S rDNA array residing in five human autosomes. The arrays are among the most variable segments of the genome, exhibit concerted copy number variation (cCNV), encode essential components of the ribosome, and modulate global gene expression. Here we combined whole genome data from >700 tumors and paired normal tissues to provide a portrait of rDNA variation in human tissues and cancers of diverse mutational signatures, including stomach and lung adenocarcinomas, ovarian cancers, and others of the TCGA panel. We show that cancers undergo coupled 5S rDNA array expansion and 45S rDNA loss that is accompanied by increased estimates of proliferation rate and nucleolar activity. These somatic changes in rDNA CN occur in a background of over 10-fold naturally occurring rDNA CN variation across individuals and cCNV of 5S-45S arrays in some but not all tissues. Analysis of genetic context revealed associations between cancer rDNA CN amplification or loss and the presence of specific somatic alterations, including somatic SNPs and copy number gain/losses in protein coding genes across the cancer genome. For instance, somatic inactivation of the tumor suppressor gene TP53 emerged with a strong association with coupled 5S expansion / 45S loss in several cancers. Our results uncover frequent and contrasting changes in the 5S and 45S rDNA along rapidly proliferating cell lineages with high nucleolar activity. We suggest that 5S rDNA amplification facilitates increased proliferation, nucleolar activity, and ribosomal synthesis in cancer, whereas 45S rDNA loss emerges as a byproduct of transcription-replication conflict in rapidly replicating tumor cells. The observations raise the prospects of using the rDNA arrays as re-emerging targets for the design of novel strategies in cancer therapy.

The 45S and 5S ribosomal DNA (rDNA) arrays contain hundreds of rDNA copies, with substantial variability across individuals in human populations. Although physically unlinked, the arrays also exhibit joint variation across individual genotypes. However, whether this co-variation in copy number (CN) is universally observed across all tissues is unknown. It also remains unknown if rDNA CN might vary across tissues and in cancer lineages. Here we showed that most cancers undergo coupled 5S rDNA array amplification and 45S rDNA loss, and concerted 5S-45S CN variation in some but not all tissues. The coupled 5S amplification and 45S loss is associated with the presence of certain somatic genetic alterations, as well as increased estimates of cancerous cell proliferation rate and nucleolar activity. Our research uncovers frequent and contrasting changes in rDNA CN in cancers of diverse tissue origin and associated with diverse mutational contexts of tumor suppressors and oncogenes. The observations raise the prospects of using the rDNA arrays as re-emerging targets in novel strategies for cancer therapy.

Osmolality/salinity-responsive enhancers (OSREs) control induction of osmoprotective genes in euryhaline fish

Fish respond to salinity stress by transcriptional induction of many genes, but the mechanism of their osmotic regulation is unknown. We developed a reporter assay using cells derived from the brain of the tilapia Oreochromis mossambicus (OmB cells) to identify osmolality/salinity-responsive enhancers (OSREs) in the genes of Omossambicus Genomic DNA comprising the regulatory regions of two strongly salinity-induced genes, inositol monophosphatase 1 (IMPA1.1) and myo-inositol phosphate synthase (MIPS), was isolated and analyzed with dual luciferase enhancer trap reporter assays. We identified five sequences (two in IMPA1.1 and three in MIPS) that share a common consensus element (DDKGGAAWWDWWYDNRB), which we named "OSRE1." Additional OSREs that were less effective in conferring salinity-induced trans-activation and do not match the OSRE1 consensus also were identified in both MIPS and IMPA1.1 Although OSRE1 shares homology with the mammalian osmotic-response element/tonicity-responsive enhancer (ORE/TonE) enhancer, the latter is insufficient to confer osmotic induction in fish. Like other enhancers, OSRE1 trans-activates genes independent of orientation. We conclude that OSRE1 is a cis-regulatory element (CRE) that enhances the hyperosmotic induction of osmoregulated genes in fish. Our study also shows that tailored reporter assays developed for OmB cells facilitate the identification of CREs in fish genomes. Knowledge of the OSRE1 motif allows affinity-purification of the corresponding transcription factor and computational approaches for enhancer screening of fish genomes. Moreover, our study enables targeted inactivation of OSRE1 enhancers, a method superior to gene knockout for functional characterization because it confines impairment of gene function to a specific context (salinity stress) and eliminates pitfalls of constitutive gene knockouts (embryonic lethality, developmental compensation).

Gene regulatory network plasticity predates a switch in function of a conserved transcription regulator

The rewiring of gene regulatory networks can generate phenotypic novelty. It remains an open question, however, how the large number of connections needed to form a novel network arise over evolutionary time. Here, we address this question using the network controlled by the fungal transcription regulator Ndt80. This conserved protein has undergone a dramatic switch in function-from an ancestral role regulating sporulation to a derived role regulating biofilm formation. This switch in function corresponded to a large-scale rewiring of the genes regulated by Ndt80. However, we demonstrate that the Ndt80-target gene connections were undergoing extensive rewiring prior to the switch in Ndt80's regulatory function. We propose that extensive drift in the Ndt80 regulon allowed for the exploration of alternative network structures without a loss of ancestral function, thereby facilitating the formation of a network with a new function.

Recurrent rewiring and emergence of RNA regulatory networks

Alterations in regulatory networks contribute to evolutionary change. Transcriptional networks are reconfigured by changes in the binding specificity of transcription factors and their cognate sites. The evolution of RNA-protein regulatory networks is far less understood. The PUF (Pumilio and FBF) family of RNA regulatory proteins controls the translation, stability, and movements of hundreds of mRNAs in a single species. We probe the evolution of PUF-RNA networks by direct identification of the mRNAs bound to PUF proteins in budding and filamentous fungi and by computational analyses of orthologous RNAs from 62 fungal species. Our findings reveal that PUF proteins gain and lose mRNAs with related and emergent biological functions during evolution. We demonstrate at least two independent rewiring events for PUF3 orthologs, independent but convergent evolution of PUF4/5 binding specificity and the rewiring of the PUF4/5 regulons in different fungal lineages. These findings demonstrate plasticity in RNA regulatory networks and suggest ways in which their rewiring occurs.

Fused Regression for Multi-source Gene Regulatory Network Inference

Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species. Most approaches consider the problem of network inference independently in each species, despite evidence that gene regulation can be conserved even in distantly related species. Further, network inference is often confined to single data-types (single platforms) and single cell types. We introduce a method for multi-source network inference that allows simultaneous estimation of gene regulatory networks in multiple species or biological processes through the introduction of priors based on known gene relationships such as orthology incorporated using fused regression. This approach improves network inference performance even when orthology mapping and conservation are incomplete. We refine this method by presenting an algorithm that extracts the true conserved subnetwork from a larger set of potentially conserved interactions and demonstrate the utility of our method in cross species network inference. Last, we demonstrate our method’s utility in learning from data collected on different experimental platforms.

Gene regulatory networks describing related biological processes are thought to share conserved interaction structure. This assumption motivates a great deal of work in model systems–where discovery of gene regulation may be more experimentally tractable–but is difficult to directly evaluate using existing methods. The presence of shared structure in a well studied model system or process should make the problem of network inference in a related process easier, but this information is not often applied to the discovery of global gene regulatory networks. Further, to be able to successfully translate findings between different organisms, it is important to be able to identify where regulatory structure is different. We provide a method based on penalized fused regression for inferring gene regulatory networks given prior knowledge about the similarity of interactions in each network. This method is demonstrated on synthetic data, and applied to the problem of inferring networks in distantly related bacterial organisms. We then introduce an extension of the method to deal with the condition of uncertainty over the degree of regulatory conservation by simultaneously inferring gene conservation and interaction weights.

Natural gene expression variation studies in yeast

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

Evolution of transcriptional networks in yeast: alternative teams of transcriptional factors for different species

Background

The diversity in eukaryotic life reflects a diversity in regulatory pathways. Nocedal and Johnson argue that the rewiring of gene regulatory networks is a major force for the diversity of life, that changes in regulation can create new species.

Results

We have created a method (based on our new “ping-pong algorithm) for detecting more complicated rewirings, where several transcription factors can substitute for one or more transcription factors in the regulation of a family of co-regulated genes. An example is illustrative. A rewiring has been reported by Hogues et al. that RAP1 in Saccharomyces cerevisiae substitutes for TBF1/CBF1 in Candida albicans for ribosomal RP genes. There one transcription factor substitutes for another on some collection of genes. Such a substitution is referred to as a “rewiring”. We agree with this finding of rewiring as far as it goes but the situation is more complicated. Many transcription factors can regulate a gene and our algorithm finds that in this example a “team” (or collection) of three transcription factors including RAP1 substitutes for TBF1 for 19 genes. The switch occurs for a branch of the phylogenetic tree containing 10 species (including Saccharomyces cerevisiae), while the remaining 13 species (Candida albicans) are regulated by TBF1.

Conclusions

To gain insight into more general evolutionary mechanisms, we have created a mathematical algorithm that finds such general switching events and we prove that it converges. Of course any such computational discovery should be validated in the biological tests. For each branch of the phylogenetic tree and each gene module, our algorithm finds a sub-group of co-regulated genes and a team of transcription factors that substitutes for another team of transcription factors. In most cases the signal will be small but in some cases we find a strong signal of switching. We report our findings for 23 Ascomycota fungi species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3102-7) contains supplementary material, which is available to authorized users.

Regulatory RNAs in Bacillus subtilis: a Gram-Positive Perspective on Bacterial RNA-Mediated Regulation of Gene Expression

Bacteria can employ widely diverse RNA molecules to regulate their gene expression. Such molecules include trans-acting small regulatory RNAs, antisense RNAs, and a variety of transcriptional attenuation mechanisms in the 5' untranslated region. Thus far, most regulatory RNA research has focused on Gram-negative bacteria, such as Escherichia coli and Salmonella. Hence, there is uncertainty about whether the resulting insights can be extrapolated directly to other bacteria, such as the Gram-positive soil bacterium Bacillus subtilis. A recent study identified 1,583 putative regulatory RNAs in B. subtilis, whose expression was assessed across 104 conditions. Here, we review the current understanding of RNA-based regulation in B. subtilis, and we categorize the newly identified putative regulatory RNAs on the basis of their conservation in other bacilli and the stability of their predicted secondary structures. Our present evaluation of the publicly available data indicates that RNA-mediated gene regulation in B. subtilis mostly involves elements at the 5' ends of mRNA molecules. These can include 5' secondary structure elements and metabolite-, tRNA-, or protein-binding sites. Importantly, sense-independent segments are identified as the most conserved and structured potential regulatory RNAs in B. subtilis. Altogether, the present survey provides many leads for the identification of new regulatory RNA functions in B. subtilis.

Growth rate controls mRNA turnover in steady and non-steady states

Gene expression has been investigated in relation with growth rate in the yeast Saccharomyces cerevisiae, following different experimental strategies. The expression of some specific gene functional categories increases or decreases with growth rate. Our recently published results have unveiled that these changes in mRNA concentration with growth depend on the relative alteration of mRNA synthesis and decay, and that, in addition to this gene-specific transcriptomic signature of growth, global mRNA turnover increases with growth rate. We discuss here these results in relation with other previous and concurrent publications, and we add new evidence which indicates that growth rate controls mRNA turnover even under non-steady-state conditions.

Evolution of New cis-Regulatory Motifs Required for Cell-Specific Gene Expression in Caenorhabditis

Patterning of C. elegans vulval cell fates relies on inductive signaling. In this induction event, a single cell, the gonadal anchor cell, secretes LIN-3/EGF and induces three out of six competent precursor cells to acquire a vulval fate. We previously showed that this developmental system is robust to a four-fold variation in lin-3/EGF genetic dose. Here using single-molecule FISH, we find that the mean level of expression of lin-3 in the anchor cell is remarkably conserved. No change in lin-3 expression level could be detected among C. elegans wild isolates and only a low level of change—less than 30%—in the Caenorhabditis genus and in Oscheius tipulae. In C. elegans, lin-3 expression in the anchor cell is known to require three transcription factor binding sites, specifically two E-boxes and a nuclear-hormone-receptor (NHR) binding site. Mutation of any of these three elements in C. elegans results in a dramatic decrease in lin-3 expression. Yet only a single E-box is found in the Drosophilae supergroup of Caenorhabditis species, including C. angaria, while the NHR-binding site likely only evolved at the base of the Elegans group. We find that a transgene from C. angaria bearing a single E-box is sufficient for normal expression in C. elegans. Even a short 58 bp cis-regulatory fragment from C. angaria with this single E-box is able to replace the three transcription factor binding sites at the endogenous C. elegans lin-3 locus, resulting in the wild-type expression level. Thus, regulatory evolution occurring in cis within a 58 bp lin-3 fragment, results in a strict requirement for the NHR binding site and a second E-box in C. elegans. This single-cell, single-molecule, quantitative and functional evo-devo study demonstrates that conserved expression levels can hide extensive change in cis-regulatory site requirements and highlights the evolution of new cis-regulatory elements required for cell-specific gene expression.

Diversification of mechanisms regulating gene expression of key developmental factors is a major force in the evolution of development. However, in the past, comparisons of gene expression across different species have often been qualitative (i.e. ‘expression is on versus off’ in a certain cell) without precise quantification. New experimental methods now allow us to quantitatively compare the expression of gene homologs across species, with single cell resolution. Moreover, the development of genome editing tools enables the dissection of regulatory DNA sequences that drive gene expression. We use here a well-established “textbook” example of animal organogenesis in the microscopic nematode, Caenorhabditis elegans, focusing on the expression of lin-3, coding for the main inducer of the vulva, in a single cell called the anchor cell. We find that the lin-3 expression level is remarkably conserved, with 20–25 messenger RNAs per anchor cell, in species that are molecularly as distant as fish and mammals. This conservation occurs despite substantial changes and compensation in the regulatory elements required for cell-specific gene expression.

Noncommutative Biology: Sequential Regulation of Complex Networks

Single-cell variability in gene expression is important for generating distinct cell types, but it is unclear how cells use the same set of regulatory molecules to specifically control similarly regulated genes. While combinatorial binding of transcription factors at promoters has been proposed as a solution for cell-type specific gene expression, we found that such models resulted in substantial information bottlenecks. We sought to understand the consequences of adopting sequential logic wherein the time-ordering of factors informs the final outcome. We showed that with noncommutative control, it is possible to independently control targets that would otherwise be activated simultaneously using combinatorial logic. Consequently, sequential logic overcomes the information bottleneck inherent in complex networks. We derived scaling laws for two noncommutative models of regulation, motivated by phosphorylation/neural networks and chromosome folding, respectively, and showed that they scale super-exponentially in the number of regulators. We also showed that specificity in control is robust to the loss of a regulator. Lastly, we connected these theoretical results to real biological networks that demonstrate specificity in the context of promiscuity. These results show that achieving a desired outcome often necessitates roundabout steps.

DNA is the blueprint of life. Yet the order in which a cell follows these instructions makes it capable of generating thousands of different fates. How this information is extracted from underlying gene regulatory networks is unclear, especially given that biological networks are highly interconnected, and that the number of signaling pathways is relatively small (approximately 5–10). The conventional approach for increasing the information capacity of a limited set of regulators is to use them in combination. Surprisingly, combinatorial logic does not increase the diversity of target configurations or cell fates, but instead causes information bottlenecks. A different approach, called sequential logic, uses noncommutative sequences of a small set of regulators to drive networks to a large number of novel configurations. If certain targets are first protected, then even promiscuous regulators can activate specific subsets of lineage-specific targets. In this paper we show how sequential logic outperforms combinatorial logic, and argue that noncommutative sequences underlie a number of cases of biological regulation, e.g. how a small number of signaling pathways generates a large diversity of cell types in development. In addition to explaining biological networks, sequential logic may be a general experimental design strategy in synthetic and single-cell biology.

Punctuated evolution and transitional hybrid network in an ancestral cell cycle of fungi

Although cell cycle control is an ancient, conserved, and essential process, some core animal and fungal cell cycle regulators share no more sequence identity than non-homologous proteins. Here, we show that evolution along the fungal lineage was punctuated by the early acquisition and entrainment of the SBF transcription factor through horizontal gene transfer. Cell cycle evolution in the fungal ancestor then proceeded through a hybrid network containing both SBF and its ancestral animal counterpart E2F, which is still maintained in many basal fungi. We hypothesize that a virally-derived SBF may have initially hijacked cell cycle control by activating transcription via the cis-regulatory elements targeted by the ancestral cell cycle regulator E2F, much like extant viral oncogenes. Consistent with this hypothesis, we show that SBF can regulate promoters with E2F binding sites in budding yeast.

DOI:http://dx.doi.org/10.7554/eLife.09492.001

Living cells grow and divide with remarkable precision to ensure that their genetic material is faithfully duplicated and distributed equally to the newly formed daughter cells. This precision is achieved through a series of steps known as the cell cycle. The cell cycle is ancient and conserved across all Eukaryotes, including plants, animals and fungi. However, some of the core proteins present in animals and fungi are unrelated. This raises the question as to how a drastic change could have occurred and been tolerated over evolution.

In animals and plants, a protein called E2F controls the expression of genes that are needed to begin the cell cycle. In most fungi, an equivalent protein called SBF performs the same role as E2F, but the two proteins are very different and do not appear to share a common ancestor. This is unexpected given that fungi and animals are more closely related to one another than either is to plants.

Medina et al. searched the genomes of many animals, fungi, plants, algae, and their closest relatives for genes that encoded proteins like E2F and SBF. SBF-like proteins were only found in fungi, yet some fungal groups had cell cycle regulators like those found in animals. Zoosporic fungi, which diverged early from the fungal ancestor, had both SBF- and E2F-like proteins, while many fungi later lost E2F during evolution.

So how did fungi acquire SBF? Medina et al. observed that part of the SBF protein is similar to proteins found in many viruses. The broad distribution of these viral SBF-like proteins suggests that they arose first in viruses, and a fungal ancestor acquired one such protein during a viral infection. As SBF and E2F bind similar DNA sequences, Medina et al. hypothesized that this viral SBF hijacked control of the cell cycle in the fungal ancestor by controlling expression of genes that were originally controlled only by E2F. In support of this idea, experiments showed that many E2F binding sites in modern genes are also SBF binding sites, and that E2F sites can substitute for SBF sites in SBF-controlled genes. Future experiments in zoosporic fungi, which have animal-like and fungal-like features, would provide a glimpse of how a fungal ancestor may have used both SBF and E2F. These experiments may also reveal why most fungi have retained the newer SBF but lost the ancestral and widely conserved E2F protein.

DOI:http://dx.doi.org/10.7554/eLife.09492.002

Making sense of transcription networks

When transcription regulatory networks are compared among distantly related eukaryotes, a number of striking similarities are observed: a larger-than-expected number of genes, extensive overlapping connections, and an apparently high degree of functional redundancy. It is often assumed that the complexity of these networks represents optimized solutions, precisely sculpted by natural selection; their common features are often asserted to be adaptive. Here, we discuss support for an alternative hypothesis: the common structural features of transcription networks arise from evolutionary trajectories of "least resistance"--that is, the relative ease with which certain types of network structures are formed during their evolution.

The Power of Natural Variation for Model Organism Biology

Genetic background effects have long been recognized and, in some cases studied, but they are often viewed as a nuisance by molecular biologists. We suggest that genetic variation currently represents a critical frontier for molecular studies. Human genetics has seen a surge of interest in genetic variation and its contributions to disease, but insights into disease mechanisms are difficult since information about gene function is lacking. By contrast, model organism genetics has excelled at revealing molecular mechanisms of cellular processes, but often de-emphasizes genetic variation and its functional consequences. We argue that model organism biology would benefit from incorporating natural variation, both to capture how well laboratory lines exemplify the species they represent and to inform on molecular processes and their variability. Such a synthesis would also greatly expand the relevance of model systems for studies of complex trait variation, including disease.

Determinants of RNA metabolism in the Schizosaccharomyces pombe genome

To decrypt the regulatory code of the genome, sequence elements must be defined that determine the kinetics of RNA metabolism and thus gene expression. Here, we attempt such decryption in an eukaryotic model organism, the fission yeast S. pombe. We first derive an improved genome annotation that redefines borders of 36% of expressed mRNAs and adds 487 non‐coding RNAs (ncRNAs). We then combine RNA labeling in vivo with mathematical modeling to obtain rates of RNA synthesis and degradation for 5,484 expressed RNAs and splicing rates for 4,958 introns. We identify functional sequence elements in DNA and RNA that control RNA metabolic rates and quantify the contributions of individual nucleotides to RNA synthesis, splicing, and degradation. Our approach reveals distinct kinetics of mRNA and ncRNA metabolism, separates antisense regulation by transcription interference from RNA interference, and provides a general tool for studying the regulatory code of genomes.

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

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

Comparisons of Ribosomal Protein Gene Promoters Indicate Superiority of Heterologous Regulatory Sequences for Expressing Transgenes in Phytophthora infestans

Molecular genetics approaches in Phytophthora research can be hampered by the limited number of known constitutive promoters for expressing transgenes and the instability of transgene activity. We have therefore characterized genes encoding the cytoplasmic ribosomal proteins of Phytophthora and studied their suitability for expressing transgenes in P. infestans. Phytophthora spp. encode a standard complement of 79 cytoplasmic ribosomal proteins. Several genes are duplicated, and two appear to be pseudogenes. Half of the genes are expressed at similar levels during all stages of asexual development, and we discovered that the majority share a novel promoter motif named the PhRiboBox. This sequence is enriched in genes associated with transcription, translation, and DNA replication, including tRNA and rRNA biogenesis. Promoters from the three P. infestans genes encoding ribosomal proteins S9, L10, and L23 and their orthologs from P. capsici were tested for their ability to drive transgenes in stable transformants of P. infestans. Five of the six promoters yielded strong expression of a GUS reporter, but the stability of expression was higher using the P. capsici promoters. With the RPS9 and RPL10 promoters of P. infestans, about half of transformants stopped making GUS over two years of culture, while their P. capsici orthologs conferred stable expression. Since cross-talk between native and transgene loci may trigger gene silencing, we encourage the use of heterologous promoters in transformation studies.

Molecular mechanisms of ribosomal protein gene coregulation

The 137 ribosomal protein genes (RPG) of Saccharomyces provide a model for gene coregulation. Reja et al. examine the positional and functional organization of their regulators (Rap1, Fhl1, Ifh1, Sfp1, and Hmo1), the transcription machinery (TFIIB, TFIID, and RNA polymerase II), and chromatin at near-base-pair resolution using ChIP-exo.

The 137 ribosomal protein genes (RPGs) of Saccharomyces provide a model for gene coregulation. We examined the positional and functional organization of their regulators (Rap1 [repressor activator protein 1], Fhl1, Ifh1, Sfp1, and Hmo1), the transcription machinery (TFIIB, TFIID, and RNA polymerase II), and chromatin at near-base-pair resolution using ChIP-exo, as RPGs are coordinately reprogrammed. Where Hmo1 is enriched, Fhl1, Ifh1, Sfp1, and Hmo1 cross-linked broadly to promoter DNA in an RPG-specific manner and demarcated by general minor groove widening. Importantly, Hmo1 extended 20–50 base pairs (bp) downstream from Fhl1. Upon RPG repression, Fhl1 remained in place. Hmo1 dissociated, which was coupled to an upstream shift of the +1 nucleosome, as reflected by the Hmo1 extension and core promoter region. Fhl1 and Hmo1 may create two regulatable and positionally distinct barriers, against which chromatin remodelers position the +1 nucleosome into either an activating or a repressive state. Consistent with in vitro studies, we found that specific TFIID subunits, in addition to cross-linking at the core promoter, made precise cross-links at Rap1 sites, which we interpret to reflect native Rap1–TFIID interactions. Our findings suggest how sequence-specific DNA binding regulates nucleosome positioning and transcription complex assembly >300 bp away and how coregulation coevolved with coding sequences.

Genome-wide identification and characterization of transcription start sites and promoters in the tunicate Ciona intestinalis

The tunicate Ciona intestinalis, an invertebrate chordate, has recently emerged as a powerful model organism for gene regulation analysis. However, few studies have been conducted to identify and characterize its transcription start sites (TSSs) and promoters at the genome-wide level. Here, using TSS-seq, we identified TSSs at the genome-wide scale and characterized promoters in C. intestinalis. Specifically, we identified TSS clusters (TSCs), high-density regions of TSS-seq tags, each of which appears to originate from an identical promoter. TSCs were found not only at known TSSs but also in other regions, suggesting the existence of many unknown transcription units in the genome. We also identified candidate promoters of 79 ribosomal protein (RP) genes, each of which had the major TSS in a polypyrimidine tract and showed a sharp TSS distribution like human RP gene promoters. Ciona RP gene promoters, however, did not appear to have typical TATA boxes, unlike human RP gene promoters. In Ciona non-RP promoters, two pyrimidine-purine dinucleotides, CA and TA, were frequently used as TSSs. Despite the absence of CpG islands, Ciona TATA-less promoters showed low expression specificity like CpG-associated human TATA-less promoters. By using TSS-seq, we also predicted trans-spliced gene TSSs and found that their downstream regions had higher G+T content than those of non-trans-spliced gene TSSs. Furthermore, we identified many putative alternative promoters, some of which were regulated in a tissue-specific manner. Our results provide valuable information about TSSs and promoter characteristics in C. intestinalis and will be helpful in future analysis of transcriptional regulation in chordates.

How Transcription Networks Evolve and Produce Biological Novelty

The rewiring of gene regulatory networks over evolutionary timescales produces changes in the patterns of gene expression and is a major source of diversity among species. Yet the molecular mechanisms underlying evolutionary rewiring are only beginning to be understood. Here, we discuss recent analyses in ascomycete yeasts that have revealed several general principles of network rewiring. Specifically, we discuss how transcription networks can maintain a functional output despite changes in mechanism, how specific types of constraints alter available evolutionary trajectories, and how regulatory rewiring can ultimately lead to phenotypic novelty. We also argue that the structure and "logic" of extant gene regulatory networks can largely be accounted for by constraints that shape their evolutionary trajectories.

Evolutionary Conservation and Diversification of Puf RNA Binding Proteins and Their mRNA Targets

Reprogramming of a gene’s expression pattern by acquisition and loss of sequences recognized by specific regulatory RNA binding proteins may be a major mechanism in the evolution of biological regulatory programs. We identified that RNA targets of Puf3 orthologs have been conserved over 100–500 million years of evolution in five eukaryotic lineages. Focusing on Puf proteins and their targets across 80 fungi, we constructed a parsimonious model for their evolutionary history. This model entails extensive and coordinated changes in the Puf targets as well as changes in the number of Puf genes and alterations of RNA binding specificity including that: 1) Binding of Puf3 to more than 200 RNAs whose protein products are predominantly involved in the production and organization of mitochondrial complexes predates the origin of budding yeasts and filamentous fungi and was maintained for 500 million years, throughout the evolution of budding yeast. 2) In filamentous fungi, remarkably, more than 150 of the ancestral Puf3 targets were gained by Puf4, with one lineage maintaining both Puf3 and Puf4 as regulators and a sister lineage losing Puf3 as a regulator of these RNAs. The decrease in gene expression of these mRNAs upon deletion of Puf4 in filamentous fungi (N. crassa) in contrast to the increase upon Puf3 deletion in budding yeast (S. cerevisiae) suggests that the output of the RNA regulatory network is different with Puf4 in filamentous fungi than with Puf3 in budding yeast. 3) The coregulated Puf4 target set in filamentous fungi expanded to include mitochondrial genes involved in the tricarboxylic acid (TCA) cycle and other nuclear-encoded RNAs with mitochondrial function not bound by Puf3 in budding yeast, observations that provide additional evidence for substantial rewiring of post-transcriptional regulation. 4) Puf3 also expanded and diversified its targets in filamentous fungi, gaining interactions with the mRNAs encoding the mitochondrial electron transport chain (ETC) complex I as well as hundreds of other mRNAs with nonmitochondrial functions. The many concerted and conserved changes in the RNA targets of Puf proteins strongly support an extensive role of RNA binding proteins in coordinating gene expression, as originally proposed by Keene. Rewiring of Puf-coordinated mRNA targets and transcriptional control of the same genes occurred at different points in evolution, suggesting that there have been distinct adaptations via RNA binding proteins and transcription factors. The changes in Puf targets and in the Puf proteins indicate an integral involvement of RNA binding proteins and their RNA targets in the adaptation, reprogramming, and function of gene expression.

A map of the evolutionary history of Puf proteins and their RNA targets shows that reprogramming of global gene expression programs via adaptive mutations that affect protein-RNA interactions is an important source of biological diversity.

We set out to trace the evolutionary history of an RNA binding protein and how its interactions with targets change over evolution. Identifying this natural history is a step toward understanding the critical differences between organisms and how gene expression programs are rewired during evolution. Using bioinformatics and experimental approaches, we broadly surveyed the evolution of binding targets of a particular family of RNA binding proteins—the Puf proteins, whose protein sequences and target RNA sequences are relatively well-characterized—across 99 eukaryotic species. We found five groups of species in which targets have been conserved for at least 100 million years and then took advantage of genome sequences from a large number of fungal species to deeply investigate the conservation and changes in Puf proteins and their RNA targets. Our analyses identified multiple and extensive reconfigurations during the natural history of fungi and suggest that RNA binding proteins and their RNA targets are profoundly involved in evolutionary reprogramming of gene expression and help define distinct programs unique to each organism. Continuing to uncover the natural history of RNA binding proteins and their interactions will provide a unique window into the gene expression programs of present day species and point to new ways to engineer gene expression programs.

AnGeLi: A Tool for the Analysis of Gene Lists from Fission Yeast

Genome-wide assays and screens typically result in large lists of genes or proteins. Enrichments of functional or other biological properties within such lists can provide valuable insights and testable hypotheses. To systematically detect these enrichments can be challenging and time-consuming, because relevant data to compare against query gene lists are spread over many different sources. We have developed AnGeLi (Analysis of Gene Lists), an intuitive, integrated web-tool for comprehensive and customized interrogation of gene lists from the fission yeast, Schizosaccharomyces pombe. AnGeLi searches for significant enrichments among multiple qualitative and quantitative information sources, including gene and phenotype ontologies, genetic and protein interactions, numerous features of genes, transcripts, translation, and proteins such as copy numbers, chromosomal positions, genetic diversity, RNA polymerase II and ribosome occupancy, localization, conservation, half-lives, domains, and molecular weight among others, as well as diverse sets of genes that are co-regulated or lead to the same phenotypes when mutated. AnGeLi uses robust statistics which can be tailored to specific needs. It also provides the option to upload user-defined gene sets to compare against the query list. Through an integrated data submission form, AnGeLi encourages the community to contribute additional curated gene lists to further increase the usefulness of this resource and to get the most from the ever increasing large-scale experiments. AnGeLi offers a rigorous yet flexible statistical analysis platform for rich insights into functional enrichments and biological context for query gene lists, thus providing a powerful exploratory tool through which S. pombe researchers can uncover fresh perspectives and unexpected connections from genomic data. AnGeLi is freely available at: www.bahlerlab.info/AnGeLi.

Mechanisms of mutational robustness in transcriptional regulation

Robustness is the invariance of a phenotype in the face of environmental or genetic change. The phenotypes produced by transcriptional regulatory circuits are gene expression patterns that are to some extent robust to mutations. Here we review several causes of this robustness. They include robustness of individual transcription factor binding sites, homotypic clusters of such sites, redundant enhancers, transcription factors, redundant transcription factors, and the wiring of transcriptional regulatory circuits. Such robustness can either be an adaptation by itself, a byproduct of other adaptations, or the result of biophysical principles and non-adaptive forces of genome evolution. The potential consequences of such robustness include complex regulatory network topologies that arise through neutral evolution, as well as cryptic variation, i.e., genotypic divergence without phenotypic divergence. On the longest evolutionary timescales, the robustness of transcriptional regulation has helped shape life as we know it, by facilitating evolutionary innovations that helped organisms such as flowering plants and vertebrates diversify.

Comparative Transcriptomics in Yeasts

Comparative functional genomics approaches have already shed an important light on the evolution of gene expression that underlies phenotypic diversity. However, comparison across many species in a phylogeny presents several major challenges. Here, we describe our experimental framework for comparative transcriptomics in a complex phylogeny.

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.

High-Throughput Identification of Cis-Regulatory Rewiring Events in Yeast

A coregulated module of genes ("regulon") can have evolutionarily conserved expression patterns and yet have diverged upstream regulators across species. For instance, the ribosomal genes regulon is regulated by the transcription factor (TF) TBF1 in Candida albicans, while in Saccharomyces cerevisiae it is regulated by RAP1. Only a handful of such rewiring events have been established, and the prevalence or conditions conducive to such events are not well known. Here, we develop a novel probabilistic scoring method to comprehensively screen for regulatory rewiring within regulons across 23 yeast species. Investigation of 1,713 regulons and 176 TFs yielded 5,353 significant rewiring events at 5% false discovery rate (FDR). Besides successfully recapitulating known rewiring events, our analyses also suggest TF candidates for certain processes reported to be under distinct regulatory controls in S. cerevisiae and C. albicans, for which the implied regulators are not known: 1) Oxidative stress response (Sc-MSN2 to Ca-FKH2) and 2) nutrient modulation (Sc-RTG1 to Ca-GCN4/Ca-UME6). Furthermore, a stringent screen to detect TF rewiring at individual genes identified 1,446 events at 10% FDR. Overall, these events are supported by strong coexpression between the predicted regulator and its target gene(s) in a species-specific fashion (>50-fold). Independent functional analyses of rewiring TF pairs revealed greater functional interactions and shared biological processes between them (P = 1 × 10(-3)).Our study represents the first comprehensive assessment of regulatory rewiring; with a novel approach that has generated a unique high-confidence resource of several specific events, suggesting that evolutionary rewiring is relatively frequent and may be a significant mechanism of regulatory innovation.

De novo ChIP-seq analysis

Methods for the analysis of chromatin immunoprecipitation sequencing (ChIP-seq) data start by aligning the short reads to a reference genome. While often successful, they are not appropriate for cases where a reference genome is not available. Here we develop methods for de novo analysis of ChIP-seq data. Our methods combine de novo assembly with statistical tests enabling motif discovery without the use of a reference genome. We validate the performance of our method using human and mouse data. Analysis of fly data indicates that our method outperforms alignment based methods that utilize closely related species.