Curated collection of yeast transcription factor DNA binding specificity data reveals novel structural and gene regulatory insights

Activity of the pleiotropic drug resistance transcription factors Pdr1p and Pdr3p is modulated by binding site flanking sequences

The transcription factors Pdr1p and Pdr3p regulate pleiotropic drug resistance (PDR) in Saccharomyces cerevisiae via the PDR responsive elements (PDREs) to modulate gene expression. However, the exact mechanisms underlying the differences in their regulons remain unclear. Employing genomic occupancy profiling (CUT&RUN), binding assays, and transcription studies, we characterized the differences in sequence specificity between transcription factors. Findings reveal distinct preferences for core PDRE sequences and the flanking sequences for both proteins. While flanking sequences moderately alter DNA binding affinity, they significantly impact Pdr1/3p transcriptional activity. Notably, both proteins demonstrated the ability to bind half sites, showing potential enhancement of transcription from adjacent PDREs. This insight sheds light on ways Pdr1/3p can differentially regulate PDR.

Characterizing Different Modes of Interplay Between Rap1 and H3 Using Inducible H3-depletion Yeast

Histones and transcription factors (TFs) are two important DNA-binding proteins that interact, compete, and together regulate transcriptional processes in response to diverse internal and external stimuli. Condition-specific depletion of histones in Saccharomyces cerevisiae using a galactose-inducible H3 promoter provides a suitable framework for examining transcriptional alteration resulting from reduced nucleosome content. However, the effect on DNA binding activities of TFs is yet to be fully explored. In this work, we combine ChIP-seq of H3 with RNA-seq to elucidate the genome-scale relationships between H3 occupancy patterns and transcriptional dynamics before and after global H3 depletion. ChIP-seq of Rap1 is also conducted in the H3-depletion and control treatments, to investigate the interplay between this master regulator TF and nucleosomal H3, and to explore the impact on diverse transcriptional responses of different groups of target genes and functions. Ultimately, we propose a working model and testable hypotheses regarding the impact of global and local H3 depletion on transcriptional changes. We also demonstrate different potential modes of interaction between Rap1 and H3, which sheds light on the potential multifunctional regulatory capabilities of Rap1 and potentially other pioneer factors.

Overexpression of the Transcription Factor Azf1 Reveals Novel Regulatory Functions and Impacts β-Glucosidase Production in Trichoderma reesei

The fungus Trichoderma reesei is an essential producer of enzymes that degrade lignocellulosic biomass to produce value-added bioproducts. The cellulolytic system of T. reesei is controlled by several transcription factors (TFs) that efficiently regulate the production of these enzymes. Recently, a new TF named Azf1 was identified as a positive regulator of cellulase expression. Here, we investigated novel regulatory functions of Azf1 by its overexpression. In the mutant strain OEazf1, overexpression of azf1 was achieved under both repression and induction conditions. Although azf1 was more abundant in transcript and protein, overexpression of this TF did not activate transcription of the cellulase gene in the presence of the repressor glucose, suggesting that Azf1 may be subject to posttranslational regulation. In cellulose, the expression of swo, encoding the accessory protein swollenin, and the β-glucosidases cel1a, cel1b, cel3b, and cel3g increases in the early stages of cultivation. The increased production of these β-glucosidases increases the hydrolysis rate of cellobiose and sophorose, which activates carbon catabolite repression (CCR) and causes repression of cellulase genes and the regulator Xyr1 in the later stages of cultivation. Moreover, overexpression of azf1 led to increased cellulase activity in T. reesei during long-term cultivation in cellulose and sugarcane bagasse. Our results provide new insights into the mechanisms regulating Azf1 and novel genes that are important targets of this TF. This work contributes to a better understanding of the complex mechanisms regulating cellulase expression in T. reesei. It will contribute to the development of strains with higher production of these essential enzymes.

Deciphering the Role of the Ser-Phosphorylation Pattern on the DNA-Binding Activity of Max Transcription Factor Using Chemical Protein Synthesis

The chemical synthesis of site-specifically modified transcription factors (TFs) is a powerful method to investigate how post-translational modifications (PTMs) influence TF-DNA interactions and impact gene expression. Among these TFs, Max plays a pivotal role in controlling the expression of 15 % of the genome. The activity of Max is regulated by PTMs; Ser-phosphorylation at the N-terminus is considered one of the key regulatory mechanisms. In this study, we developed a practical synthetic strategy to prepare homogeneous full-length Max for the first time, to explore the impact of Max phosphorylation. We prepared a focused library of eight Max variants, with distinct modification patterns, including mono-phosphorylated, and doubly phosphorylated analogues at Ser2/Ser11 as well as fluorescently labeled variants through native chemical ligation. Through comprehensive DNA binding analyses, we discovered that the phosphorylation position plays a crucial role in the DNA-binding activity of Max. Furthermore, in vitro high-throughput analysis using DNA microarrays revealed that the N-terminus phosphorylation pattern does not interfere with the DNA sequence specificity of Max. Our work provides insights into the regulatory role of Max's phosphorylation on the DNA interactions and sequence specificity, shedding light on how PTMs influence TF function.

Amoeba predation of Cryptococcus: A quantitative and population genomic evaluation of the accidental pathogen hypothesis

The "Amoeboid Predator-Fungal Animal Virulence Hypothesis" posits that interactions with environmental phagocytes shape the evolution of virulence traits in fungal pathogens. In this hypothesis, selection to avoid predation by amoeba inadvertently selects for traits that contribute to fungal escape from phagocytic immune cells. Here, we investigate this hypothesis in the human fungal pathogens Cryptococcus neoformans and Cryptococcus deneoformans. Applying quantitative trait locus (QTL) mapping and comparative genomics, we discovered a cross-species QTL region that is responsible for variation in resistance to amoeba predation. In C. neoformans, this same QTL was found to have pleiotropic effects on melanization, an established virulence factor. Through fine mapping and population genomic comparisons, we identified the gene encoding the transcription factor Bzp4 that underlies this pleiotropic QTL and we show that decreased expression of this gene reduces melanization and increases susceptibility to amoeba predation. Despite the joint effects of BZP4 on amoeba resistance and melanin production, we find no relationship between BZP4 genotype and escape from macrophages or virulence in murine models of disease. Our findings provide new perspectives on how microbial ecology shapes the genetic architecture of fungal virulence, and suggests the need for more nuanced models for the evolution of pathogenesis that account for the complexities of both microbe-microbe and microbe-host interactions.

Yeast transcription factor Msn2 binds to G4 DNA

Sequences capable of forming quadruplex or G4 DNA are prevalent in the promoter regions. The transformation from canonical to non-canonical secondary structure apparently regulates transcription of a number of human genes. In the budding yeast Saccharomyces cerevisiae, we identified 37 genes with a G4 motif in the promoters including 20 genes that contain stress response element (STRE) overlapping a G4 motif. STRE is the binding site of stress response regulators Msn2 and Msn4, transcription factors belonging to the C2H2 zinc-finger protein family. We show here that Msn2 binds directly to the G4 DNA structure through its zinc-finger domain with a dissociation constant similar to that of STRE-binding and that, in a stress condition, Msn2 is enriched at G4 DNA-forming loci in the yeast genome. For a large fraction of genes with G4/STRE-containing promoters, treating with G4-ligands led to significant elevations in transcription levels. Such transcriptional elevation was greatly diminished in a msn2Δ msn4Δ background and was partly muted when the G4 motif was disrupted. Taken together, our data suggest that G4 DNA could be an alternative binding site of Msn2 in addition to STRE, and that G4 DNA formation could be an important element of transcriptional regulation in yeast.

Molecular background of HAC1-driven improvement in the secretion of recombinant protein in Yarrowia lipolytica based on comparative transcriptomics

While the unfolded protein response (UPR) and its major regulator - transcription factor Hac1 are well-conserved across Eukarya, species-specific variations are repeatedly reported. Here we investigated molecular mechanisms by which co-over-expression of HAC1 improves secretion of a recombinant protein (r-Prot) in Yarrowia lipolytica, using comparative transcriptomics. Co-over-expression of HAC1 caused an >2-fold increase in secreted r-Prot, but its intracellular levels were decreased. The unconventional splicing rate of the HAC1 mRNA was counted through transcript sequencing. Multiple biological processes were affected in the HAC1-and-r-Prot co-over-expressing strain, including ribosome biogenesis, nuclear and mitochondrial events, cell cycle arrest, attenuation of gene expression by RNA polymerase III and II, as well as modulation of proteolysis and RNA metabolism; but whether the HAC1 co-over-expression/induction was the actual causative agent for these changes, was not always clear. We settled that the expression of the "conventional" HAC1 targets (KAR2 and PDI1) is not affected by its over-expression.

Double DAP-seq uncovered synergistic DNA binding of interacting bZIP transcription factors

Many eukaryotic transcription factors (TF) form homodimer or heterodimer complexes to regulate gene expression. Dimerization of BASIC LEUCINE ZIPPER (bZIP) TFs are critical for their functions, but the molecular mechanism underlying the DNA binding and functional specificity of homo- versus heterodimers remains elusive. To address this gap, we present the double DNA Affinity Purification-sequencing (dDAP-seq) technique that maps heterodimer binding sites on endogenous genomic DNA. Using dDAP-seq we profile twenty pairs of C/S1 bZIP heterodimers and S1 homodimers in Arabidopsis and show that heterodimerization significantly expands the DNA binding preferences of these TFs. Analysis of dDAP-seq binding sites reveals the function of bZIP9 in abscisic acid response and the role of bZIP53 heterodimer-specific binding in seed maturation. The C/S1 heterodimers show distinct preferences for the ACGT elements recognized by plant bZIPs and motifs resembling the yeast GCN4 cis-elements. This study demonstrates the potential of dDAP-seq in deciphering the DNA binding specificities of interacting TFs that are key for combinatorial gene regulation.

Comprehensive transcriptome analysis of different potato cultivars provides insight into early blight disease caused by Alternaria solani

BACKGROUND

Early blight, caused by the necrotrophic fungal pathogen Alternaria solani, is an economically important disease affecting the tuber yield worldwide. The disease is mainly controlled by chemical plant protection agents. However, over-using these chemicals can lead to the evolution of resistant A. solani strains and is environmentally hazardous. Identifying genetic disease resistance factors is crucial for the sustainable management of early blight but little effort has been diverted in this direction. Therefore, we carried out transcriptome sequencing of the A. solani interaction with different potato cultivars with varying levels of early blight resistance to identify key host genes and pathways in a cultivar-specific manner.

RESULTS

In this study, we have captured transcriptomes from three different potato cultivars with varying susceptibility to A. solani,  namely Magnum Bonum, Désirée, and Kuras, at 18 and 36 h post-infection. We identified many differentially expressed genes (DEGs) between these cultivars, and the number of DEGs increased with susceptibility and infection time. There were 649 transcripts commonly expressed between the potato cultivars and time points, of which 627 and 22 were up- and down-regulated, respectively. Interestingly, overall the up-regulated DEGs were twice in number as compared to down-regulated ones in all the potato cultivars and time points, except Kuras at 36 h post-inoculation. In general, transcription factor families WRKY, ERF, bHLH, MYB, and C2H2 were highly enriched DEGs, of which a significant number were up-regulated. The majority of the key transcripts involved in the jasmonic acid and ethylene biosynthesis pathways were highly up-regulated. Many transcripts involved in the mevalonate (MVA) pathway, isoprenyl-PP, and terpene biosynthesis were also up-regulated across the potato cultivars and time points. Compared to Magnum Bonum and Désirée, multiple components of the photosynthesis machinery, starch biosynthesis and degradation pathway were down-regulated in the most susceptible potato cultivar, Kuras.

CONCLUSIONS

Transcriptome sequencing identified many differentially expressed genes and pathways, thereby contributing to the improved understanding of the interaction between the potato host and A. solani. The transcription factors identified are attractive targets for genetic modification to improve potato resistance against early blight. The results provide important insights into the molecular events at the early stages of disease development, help to shorten the knowledge gap, and support potato breeding programs for improved early blight disease resistance.

Transcriptomic changes in single yeast cells under various stress conditions

BACKGROUND

The stress response of Saccharomyces cerevisiae has been extensively studied in the past decade. However, with the advent of recent technology in single-cell transcriptome profiling, there is a new opportunity to expand and further understanding of the yeast stress response with greater resolution on a system level. To understand transcriptomic changes in baker's yeast S. cerevisiae cells under stress conditions, we sequenced 117 yeast cells under three stress treatments (hypotonic condition, glucose starvation and amino acid starvation) using a full-length single-cell RNA-Seq method.

RESULTS

We found that though single cells from the same treatment showed varying degrees of uniformity, technical noise and batch effects can confound results significantly. However, upon careful selection of samples to reduce technical artifacts and account for batch-effects, we were able to capture distinct transcriptomic signatures for different stress conditions as well as putative regulatory relationships between transcription factors and target genes.

CONCLUSION

Our results show that a full-length single-cell based transcriptomic analysis of the yeast may help paint a clearer picture of how the model organism responds to stress than do bulk cell population-based methods.

NetREX-CF integrates incomplete transcription factor data with gene expression to reconstruct gene regulatory networks

The inference of Gene Regulatory Networks (GRNs) is one of the key challenges in systems biology. Leading algorithms utilize, in addition to gene expression, prior knowledge such as Transcription Factor (TF) DNA binding motifs or results of TF binding experiments. However, such prior knowledge is typically incomplete, therefore, integrating it with gene expression to infer GRNs remains difficult. To address this challenge, we introduce NetREX-CF-Regulatory Network Reconstruction using EXpression and Collaborative Filtering-a GRN reconstruction approach that brings together Collaborative Filtering to address the incompleteness of the prior knowledge and a biologically justified model of gene expression (sparse Network Component Analysis based model). We validated the NetREX-CF using Yeast data and then used it to construct the GRN for Drosophila Schneider 2 (S2) cells. To corroborate the GRN, we performed a large-scale RNA-Seq analysis followed by a high-throughput RNAi treatment against all 465 expressed TFs in the cell line. Our knockdown result has not only extensively validated the GRN we built, but also provides a benchmark that our community can use for evaluating GRNs. Finally, we demonstrate that NetREX-CF can infer GRNs using single-cell RNA-Seq, and outperforms other methods, by using previously published human data.

Transcriptional regulation of ergosterol biosynthesis genes in response to iron deficiency

Iron participates as an essential cofactor in the biosynthesis of critical cellular components, including DNA, proteins and lipids. The ergosterol biosynthetic pathway, which is an important target of antifungal treatments, depends on iron in four enzymatic steps. Our results in the model yeast Saccharomyces cerevisiae show that the expression of ergosterol biosynthesis (ERG) genes is tightly modulated by iron availability probably through the iron-dependent variation of sterol and heme levels. Whereas the transcription factors Upc2 and Ecm22 are responsible for the activation of ERG genes upon iron deficiency, the heme-dependent factor Hap1 triggers their Tup1-mediated transcriptional repression. The combined regulation by both activating and repressing regulatory factors allows for the fine-tuning of ERG transcript levels along the progress of iron deficiency, avoiding the accumulation of toxic sterol intermediates and enabling efficient adaptation to rapidly changing conditions. The lack of these regulatory factors leads to changes in the yeast sterol profile upon iron-deficient conditions. Both environmental iron availability and specific regulatory factors should be considered in ergosterol antifungal treatments.

Context-dependent CpG methylation directs cell-specific binding of transcription factor ZBTB38

DNA methylation on CpGs regulates transcription in mammals, both by decreasing the binding of methylation-repelled factors and by increasing the binding of methylation-attracted factors. Among the latter, zinc finger proteins have the potential to bind methylated CpGs in a sequence-specific context. The protein ZBTB38 is unique in that it has two independent sets of zinc fingers, which recognize two different methylated consensus sequences in vitro. Here, we identify the binding sites of ZBTB38 in a human cell line, and show that they contain the two methylated consensus sequences identified in vitro. In addition, we show that the distribution of ZBTB38 sites is highly unusual: while 10% of the ZBTB38 sites are also bound by CTCF, the other 90% of sites reside in closed chromatin and are not bound by any of the other factors mapped in our model cell line. Finally, a third of ZBTB38 sites are found upstream of long and active CpG islands. Our work therefore validates ZBTB38 as a methyl-DNA binder in vivo and identifies its unique distribution in the genome.

Prediction and Experimental Validation of a New Salinity-Responsive Cis-Regulatory Element (CRE) in a Tilapia Cell Line

Transcriptional regulation is a major mechanism by which organisms integrate gene x environment interactions. It can be achieved by coordinated interplay between cis-regulatory elements (CREs) and transcription factors (TFs). Euryhaline tilapia (Oreochromis mossambicus) tolerate a wide range of salinity and thus are an appropriate model to examine transcriptional regulatory mechanisms during salinity stress in fish. Quantitative proteomics in combination with the transcription inhibitor actinomycin D revealed 19 proteins that are transcriptionally upregulated by hyperosmolality in tilapia brain (OmB) cells. We searched the extended proximal promoter up to intron1 of each corresponding gene for common motifs using motif discovery tools. The top-ranked motif identified (STREME1) represents a binding site for the Forkhead box TF L1 (FoxL1). STREME1 function during hyperosmolality was experimentally validated by choosing two of the 19 genes, chloride intracellular channel 2 (clic2) and uridine phosphorylase 1 (upp1), that are enriched in STREME1 in their extended promoters. Transcriptional induction of these genes during hyperosmolality requires STREME1, as evidenced by motif mutagenesis. We conclude that STREME1 represents a new functional CRE that contributes to gene x environment interactions during salinity stress in tilapia. Moreover, our results indicate that FoxL1 family TFs are contribute to hyperosmotic induction of genes in euryhaline fish.

Transcriptional Profiling of Resistant and Susceptible Cultivars of Grapevine (Vitis L.) Reveals Hypersensitive Responses to Plasmopara viticola

Grapevine downy mildew is the most serious disease of grapevine cultivars that affects the rate of resistance/susceptibility to Plasmopara viticola. In this study, we used the susceptible cultivar "Zitian Seedless" and the resistant cultivar "Kober 5BB" as materials to determine the transcriptome differences and phenotypes of the leaves after inoculation with downy mildew. The differences in microstructures and molecular levels were compared and analyzed. Fluorescence staining and microscopic observations confirmed that hypersensitive cell death occurred around the stomata in "Kober 5BB" infected by downy mildew zoospores. Meanwhile, transcriptomic profiling indicated that there were 11,713 and 6,997 gene expression differences between the resistant and susceptible cultivars at 72 h after inoculation when compared to control (0 h), respectively. The differentially expressed genes of the two cultivars are significantly enriched in different pathways, including response to plant-pathogen interaction, mitogen-activated protein kinase (MAPK) signaling pathway, plant hormone signal transduction, phenylpropanoid, and flavonoid biosynthesis. Furthermore, the results of functional enrichment analysis showed that H₂O₂ metabolism, cell death, reactive oxygen response, and carbohydrate metabolism are also involved in the defense response of "Kober 5BB," wherein a total of 322 key genes have been identified. The protein interaction network showed that metacaspases (MCAs), vacuolar processing enzymes (VPEs), and Papain-like cysteine proteases (PLCPs) play an important role in the execution of hypersensitive responses (HR). In conclusion, we demonstrated that HR cell death is the key strategy in the process of grape defense against downy mildew, which may be mediated or activated by Caspase-like proteases.

Structural insights into cooperative DNA recognition by the CCAAT-binding complex and its bZIP transcription factor HapX

The heterotrimeric CCAAT-binding complex (CBC) is a fundamental eukaryotic transcription factor recognizing the CCAAT box. In certain fungi, like Aspergilli, the CBC cooperates with the basic leucine zipper HapX to control iron metabolism. HapX functionally depends on the CBC, and the stable interaction of both requires DNA. To study this cooperative effect, X-ray structures of the CBC-HapX-DNA complex were determined. Downstream of the CCAAT box, occupied by the CBC, a HapX dimer binds to the major groove. The leash-like N terminus of the distal HapX subunit contacts the CBC, and via a flexible polyproline type II helix mediates minor groove interactions that stimulate sequence promiscuity. In vitro and in vivo mutagenesis suggest that the structural and functional plasticity of HapX results from local asymmetry and its ability to target major and minor grooves simultaneously. The latter feature may also apply to related transcription factors such as yeast Hap4 and distinct Yap family members.

Pathogen-driven coevolution across the CBP60 plant immune regulator subfamilies confers resilience on the regulator module

Components of the plant immune signaling network need mechanisms that confer resilience against fast-evolving pathogen effectors that target them. Among eight Arabidopsis CaM-Binding Protein (CBP) 60 family members, AtCBP60g and AtSARD1 are partially functionally redundant, major positive immune regulators, and AtCBP60a is a negative immune regulator. We investigated possible resilience-conferring evolutionary mechanisms among the CBP60a, CBP60g and SARD1 immune regulatory subfamilies. Phylogenetic analysis was used to investigate the times of CBP60 subfamily neofunctionalization. Then, using the pairwise distance rank based on the newly developed analytical platform Protein Evolution Analysis in a Euclidean Space (PEAES), hypotheses of specific coevolutionary mechanisms that could confer resilience on the regulator module were tested. The immune regulator subfamilies diversified around the time of angiosperm divergence and have been evolving very quickly. We detected significant coevolutionary interactions across the immune regulator subfamilies in all of 12 diverse core eudicot species lineages tested. The coevolutionary interactions were consistent with the hypothesized coevolution mechanisms. Despite their unusually fast evolution, members across the CBP60 immune regulator subfamilies have influenced the evolution of each other long after their diversification in a way that could confer resilience on the immune regulator module against fast-evolving pathogen effectors.

RoboCOP: jointly computing chromatin occupancy profiles for numerous factors from chromatin accessibility data

Chromatin is a tightly packaged structure of DNA and protein within the nucleus of a cell. The arrangement of different protein complexes along the DNA modulates and is modulated by gene expression. Measuring the binding locations and occupancy levels of different transcription factors (TFs) and nucleosomes is therefore crucial to understanding gene regulation. Antibody-based methods for assaying chromatin occupancy are capable of identifying the binding sites of specific DNA binding factors, but only one factor at a time. In contrast, epigenomic accessibility data like MNase-seq, DNase-seq, and ATAC-seq provide insight into the chromatin landscape of all factors bound along the genome, but with little insight into the identities of those factors. Here, we present RoboCOP, a multivariate state space model that integrates chromatin accessibility data with nucleotide sequence to jointly compute genome-wide probabilistic scores of nucleosome and TF occupancy, for hundreds of different factors. We apply RoboCOP to MNase-seq and ATAC-seq data to elucidate the protein-binding landscape of nucleosomes and 150 TFs across the yeast genome, and show that our model makes better predictions than existing methods. We also compute a chromatin occupancy profile of the yeast genome under cadmium stress, revealing chromatin dynamics associated with transcriptional regulation.

Competition for DNA binding between paralogous transcription factors determines their genomic occupancy and regulatory functions

Most eukaryotic transcription factors (TFs) are part of large protein families, with members of the same family (i.e., paralogous TFs) recognizing similar DNA-binding motifs but performing different regulatory functions. Many TF paralogs are coexpressed in the cell and thus can compete for target sites across the genome. However, this competition is rarely taken into account when studying the in vivo binding patterns of eukaryotic TFs. Here, we show that direct competition for DNA binding between TF paralogs is a major determinant of their genomic binding patterns. Using yeast proteins Cbf1 and Pho4 as our model system, we designed a high-throughput quantitative assay to capture the genomic binding profiles of competing TFs in a cell-free system. Our data show that Cbf1 and Pho4 greatly influence each other's occupancy by competing for their common putative genomic binding sites. The competition is different at different genomic sites, as dictated by the TFs' expression levels and their divergence in DNA-binding specificity and affinity. Analyses of ChIP-seq data show that the biophysical rules that dictate the competitive TF binding patterns in vitro are also followed in vivo, in the complex cellular environment. Furthermore, the Cbf1-Pho4 competition for genomic sites, as characterized in vitro using our new assay, plays a critical role in the specific activation of their target genes in the cell. Overall, our study highlights the importance of direct TF-TF competition for genomic binding and gene regulation by TF paralogs, and proposes an approach for studying this competition in a quantitative and high-throughput manner.

Machine learning predicts nucleosome binding modes of transcription factors

Background

Most transcription factors (TFs) compete with nucleosomes to gain access to their cognate binding sites. Recent studies have identified several TF-nucleosome interaction modes including end binding (EB), oriented binding, periodic binding, dyad binding, groove binding, and gyre spanning. However, there are substantial experimental challenges in measuring nucleosome binding modes for thousands of TFs in different species.

Results

We present a computational prediction of the binding modes based on TF protein sequences. With a nested cross-validation procedure, our model outperforms several fine-tuned off-the-shelf machine learning (ML) methods in the multi-label classification task. Our binary classifier for the EB mode performs better than these ML methods with the area under precision-recall curve achieving 75%. The end preference of most TFs is consistent with low nucleosome occupancy around their binding site in GM12878 cells. The nucleosome occupancy data is used as an alternative dataset to confirm the superiority of our EB classifier.

Conclusions

We develop the first ML-based approach for efficient and comprehensive analysis of nucleosome binding modes of TFs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04093-9.

The fungal CCAAT-binding complex and HapX display highly variable but evolutionary conserved synergetic promoter-specific DNA recognition

To sustain iron homeostasis, microorganisms have evolved fine-tuned mechanisms for uptake, storage and detoxification of the essential metal iron. In the human pathogen Aspergillus fumigatus, the fungal-specific bZIP-type transcription factor HapX coordinates adaption to both iron starvation and iron excess and is thereby crucial for virulence. Previous studies indicated that a HapX homodimer interacts with the CCAAT-binding complex (CBC) to cooperatively bind bipartite DNA motifs; however, the mode of HapX-DNA recognition had not been resolved. Here, combination of in vivo (genetics and ChIP-seq), in vitro (surface plasmon resonance) and phylogenetic analyses identified an astonishing plasticity of CBC:HapX:DNA interaction. DNA motifs recognized by the CBC:HapX protein complex comprise a bipartite DNA binding site 5′-CSAATN₁₂RWT-3′ and an additional 5′-TKAN-3′ motif positioned 11–23 bp downstream of the CCAAT motif, i.e. occasionally overlapping the 3′-end of the bipartite binding site. Phylogenetic comparison taking advantage of 20 resolved Aspergillus species genomes revealed that DNA recognition by the CBC:HapX complex shows promoter-specific cross-species conservation rather than regulon-specific conservation. Moreover, we show that CBC:HapX interaction is absolutely required for all known functions of HapX. The plasticity of the CBC:HapX:DNA interaction permits fine tuning of CBC:HapX binding specificities that could support adaptation of pathogens to their host niches.

A Comprehensive Drosophila melanogaster Transcription Factor Interactome

Combinatorial interactions among transcription factors (TFs) play essential roles in generating gene expression specificity and diversity in metazoans. Using yeast 2-hybrid (Y2H) assays on nearly all sequence-specific Drosophila TFs, we identified 1,983 protein-protein interactions (PPIs), more than doubling the number of currently known PPIs among Drosophila TFs. For quality assessment, we validated a subset of our interactions using MITOMI and bimolecular fluorescence complementation assays. We combined our interactome with prior PPI data to generate an integrated Drosophila TF-TF binary interaction network. Our analysis of ChIP-seq data, integrating PPI and gene expression information, uncovered different modes by which interacting TFs are recruited to DNA. We further demonstrate the utility of our Drosophila interactome in shedding light on human TF-TF interactions. This study reveals how TFs interact to bind regulatory elements in vivo and serves as a resource of Drosophila TF-TF binary PPIs for understanding tissue-specific gene regulation.

Combinatorial regulation by transcription factors (TFs) is one mechanism for achieving condition and tissue-specific gene regulation. Shokri et al. mapped TF-TF interactions between most Drosophila TFs, reporting a comprehensive TF-TF network integrated with previously known interactions. They used this network to discern distinct TF-DNA binding modes.

RoboCOP: Multivariate State Space Model Integrating Epigenomic Accessibility Data to Elucidate Genome-Wide Chromatin Occupancy

Chromatin is the tightly packaged structure of DNA and protein within the nucleus of a cell. The arrangement of different protein complexes along the DNA modulates and is modulated by gene expression. Measuring the binding locations and level of occupancy of different transcription factors (TFs) and nucleosomes is therefore crucial to understanding gene regulation. Antibody-based methods for assaying chromatin occupancy are capable of identifying the binding sites of specific DNA binding factors, but only one factor at a time. On the other hand, epigenomic accessibility data like ATAC-seq, DNase-seq, and MNase-seq provide insight into the chromatin landscape of all factors bound along the genome, but with minimal insight into the identities of those factors. Here, we present RoboCOP, a multivariate state space model that integrates chromatin information from epigenomic accessibility data with nucleotide sequence to compute genome-wide probabilistic scores of nucleosome and TF occupancy, for hundreds of different factors at once. RoboCOP can be applied to any epigenomic dataset that provides quantitative insight into chromatin accessibility in any organism, but here we apply it to MNase-seq data to elucidate the protein-binding landscape of nucleosomes and 150 TFs across the yeast genome. Using available protein-binding datasets from the literature, we show that our model more accurately predicts the binding of these factors genome-wide.

Bispecific Forkhead Transcription Factor FoxN3 Recognizes Two Distinct Motifs with Different DNA Shapes

Transcription factors (TFs) control gene expression by binding DNA recognition sites in genomic regulatory regions. Although most forkhead TFs recognize a canonical forkhead (FKH) motif, RYAAAYA, some forkheads recognize a completely different (FHL) motif, GACGC. Bispecific forkhead proteins recognize both motifs, but the molecular basis for bispecific DNA recognition is not understood. We present co-crystal structures of the FoxN3 DNA binding domain bound to the FKH and FHL sites, respectively. FoxN3 adopts a similar conformation to recognize both motifs, making contacts with different DNA bases using the same amino acids. However, the DNA structure is different in the two complexes. These structures reveal how a single TF binds two unrelated DNA sequences and the importance of DNA shape in the mechanism of bispecific recognition.

Sumoylation of DNA-bound transcription factor Sko1 prevents its association with nontarget promoters

Sequence-specific transcription factors (TFs) represent one of the largest groups of proteins that is targeted for SUMO post-translational modification, in both yeast and humans. SUMO modification can have diverse effects, but recent studies showed that sumoylation reduces the interaction of multiple TFs with DNA in living cells. Whether this relates to a general role for sumoylation in TF binding site selection, however, has not been fully explored because few genome-wide studies aimed at studying such a role have been reported. To address this, we used genome-wide analysis to examine how sumoylation regulates Sko1, a yeast bZIP TF with hundreds of known binding sites. We find that Sko1 is sumoylated at Lys 567 and, although many of its targets are osmoresponse genes, the level of Sko1 sumoylation is not stress-regulated and the modification does not depend or impinge on its phosphorylation by the osmostress kinase Hog1. We show that Sko1 mutants that cannot bind DNA are not sumoylated, but attaching a heterologous DNA binding domain restores the modification, implicating DNA binding as a major determinant for Sko1 sumoylation. Genome-wide chromatin immunoprecipitation (ChIP-seq) analysis shows that a sumoylation-deficient Sko1 mutant displays increased occupancy levels at its numerous binding sites, which inhibits the recruitment of the Hog1 kinase to some induced osmostress genes. This strongly supports a general role for sumoylation in reducing the association of TFs with chromatin. Extending this result, remarkably, sumoylation-deficient Sko1 binds numerous additional promoters that are not normally regulated by Sko1 but contain sequences that resemble the Sko1 binding motif. Our study points to an important role for sumoylation in modulating the interaction of a DNA-bound TF with chromatin to increase the specificity of TF-DNA interactions.

Systems and Synthetic Biology Approaches to Engineer Fungi for Fine Chemical Production

Since the advent of systems and synthetic biology, many studies have sought to harness microbes as cell factories through genetic and metabolic engineering approaches. Yeast and filamentous fungi have been successfully harnessed to produce fine and high value-added chemical products. In this review, we present some of the most promising advances from recent years in the use of fungi for this purpose, focusing on the manipulation of fungal strains using systems and synthetic biology tools to improve metabolic flow and the flow of secondary metabolites by pathway redesign. We also review the roles of bioinformatics analysis and predictions in synthetic circuits, highlighting in silico systemic approaches to improve the efficiency of synthetic modules.

A prior-based integrative framework for functional transcriptional regulatory network inference

Transcriptional regulatory networks specify regulatory proteins controlling the context-specific expression levels of genes. Inference of genome-wide regulatory networks is central to understanding gene regulation, but remains an open challenge. Expression-based network inference is among the most popular methods to infer regulatory networks, however, networks inferred from such methods have low overlap with experimentally derived (e.g. ChIP-chip and transcription factor (TF) knockouts) networks. Currently we have a limited understanding of this discrepancy. To address this gap, we first develop a regulatory network inference algorithm, based on probabilistic graphical models, to integrate expression with auxiliary datasets supporting a regulatory edge. Second, we comprehensively analyze our and other state-of-the-art methods on different expression perturbation datasets. Networks inferred by integrating sequence-specific motifs with expression have substantially greater agreement with experimentally derived networks, while remaining more predictive of expression than motif-based networks. Our analysis suggests natural genetic variation as the most informative perturbation for network inference, and, identifies core TFs whose targets are predictable from expression. Multiple reasons make the identification of targets of other TFs difficult, including network architecture and insufficient variation of TF mRNA level. Finally, we demonstrate the utility of our inference algorithm to infer stress-specific regulatory networks and for regulator prioritization.

Diversification of transcription factor-DNA interactions and the evolution of gene regulatory networks

Sequence-specific transcription factors (TFs) bind short DNA sequences in the genome to regulate the expression of target genes. In the last decade, numerous technical advances have enabled the determination of the DNA-binding specificities of many of these factors. Large-scale screens of many TFs enabled the creation of databases of TF DNA-binding specificities, typically represented as position weight matrices (PWMs). Although great progress has been made in determining and predicting binding specificities systematically, there are still many surprises to be found when studying a particular TF's interactions with DNA in detail. Paralogous TFs' binding specificities can differ in subtle ways, in a manner that is not immediately apparent from looking at their PWMs. These differences affect gene regulatory outputs and enable TFs to rewire transcriptional networks over evolutionary time. This review discusses recent observations made in the study of TF-DNA interactions that highlight the importance of continued in-depth analysis of TF-DNA interactions and their inherent complexity. This article is categorized under: Biological Mechanisms > Regulatory Biology.

Preferences in a trait decision determined by transcription factor variants

Few mechanisms are known that explain how transcription factors can adjust phenotypic outputs to accommodate differing environments. In Saccharomyces cerevisiae, the decision to mate or invade relies on environmental cues that converge on a shared transcription factor, Ste12. Specificity toward invasion occurs via Ste12 binding cooperatively with the cofactor Tec1. Here, we determine the range of phenotypic outputs (mating vs. invasion) of thousands of DNA-binding domain variants in Ste12 to understand how preference for invasion may arise. We find that single amino acid changes in the DNA-binding domain can shift the preference of yeast toward either mating or invasion. These mutations define two distinct regions of this domain, suggesting alternative modes of DNA binding for each trait. We characterize the DNA-binding specificity of wild-type Ste12 to identify a strong preference for spacing and orientation of both homodimeric and heterodimeric sites. Ste12 mutants that promote hyperinvasion in a Tec1-independent manner fail to bind cooperative sites with Tec1 and bind to unusual dimeric Ste12 sites composed of one near-perfect and one highly degenerate site. We propose a model in which Ste12 alone may have evolved to activate invasion genes, which could explain how preference for invasion arose in the many fungal pathogens that lack Tec1.

Reconstruction of a Global Transcriptional Regulatory Network for Control of Lipid Metabolism in Yeast by Using Chromatin Immunoprecipitation with Lambda Exonuclease Digestion

To build transcription regulatory networks, transcription factor binding must be analyzed in cells grown under different conditions because their responses and targets differ depending on environmental conditions. We performed whole-genome analysis of the DNA binding of five Saccharomyces cerevisiae transcription factors involved in lipid metabolism, Ino2, Ino4, Hap1, Oaf1, and Pip2, in response to four different environmental conditions in chemostat cultures, which allowed us to keep the specific growth rate constant. Chromatin immunoprecipitation with lambda exonuclease digestion (ChIP-exo) enabled the detection of binding events at a high resolution. We discovered a large number of unidentified targets and thus expanded functions for each transcription factor (e.g., glutamate biosynthesis as a target of Oaf1 and Pip2). Moreover, condition-dependent binding of transcription factors in response to cell metabolic state (e.g., differential binding of Ino2 between fermentative and respiratory metabolic conditions) was clearly suggested. Combining the new binding data with previously published data from transcription factor deletion studies revealed the high complexity of the transcriptional regulatory network for lipid metabolism in yeast, which involves the combinatorial and complementary regulation by multiple transcription factors. We anticipate that our work will provide insights into transcription factor binding dynamics that will prove useful for the understanding of transcription regulatory networks. IMPORTANCE Transcription factors play a crucial role in the regulation of gene expression and adaptation to different environments. To better understand the underlying roles of these adaptations, we performed experiments that give us high-resolution binding of transcription factors to their targets. We investigated five transcription factors involved in lipid metabolism in yeast, and we discovered multiple novel targets and condition-specific responses that allow us to draw a better regulatory map of the lipid metabolism.

BEESEM: estimation of binding energy models using HT-SELEX data

Motivation

Characterizing the binding specificities of transcription factors (TFs) is crucial to the study of gene expression regulation. Recently developed high-throughput experimental methods, including protein binding microarrays (PBM) and high-throughput SELEX (HT-SELEX), have enabled rapid measurements of the specificities for hundreds of TFs. However, few studies have developed efficient algorithms for estimating binding motifs based on HT-SELEX data. Also the simple method of constructing a position weight matrix (PWM) by comparing the frequency of the preferred sequence with single-nucleotide variants has the risk of generating motifs with higher information content than the true binding specificity.

Results

We developed an algorithm called BEESEM that builds on a comprehensive biophysical model of protein-DNA interactions, which is trained using the expectation maximization method. BEESEM is capable of selecting the optimal motif length and calculating the confidence intervals of estimated parameters. By comparing BEESEM with the published motifs estimated using the same HT-SELEX data, we demonstrate that BEESEM provides significant improvements. We also evaluate several motif discovery algorithms on independent PBM and ChIP-seq data. BEESEM provides significantly better fits to in vitro data, but its performance is similar to some other methods on in vivo data under the criterion of the area under the receiver operating characteristic curve (AUROC). This highlights the limitations of the purely rank-based AUROC criterion. Using quantitative binding data to assess models, however, demonstrates that BEESEM improves on prior models.

Availability and Implementation

Freely available on the web at http://stormo.wustl.edu/resources.html .

Contact

stormo@wustl.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genome-wide determinants of sequence-specific DNA binding of general regulatory factors

General regulatory factors (GRFs), such as Reb1, Abf1, Rap1, Mcm1, and Cbf1, positionally organize yeast chromatin through interactions with a core consensus DNA sequence. It is assumed that sequence recognition via direct base readout suffices for specificity and that spurious nonfunctional sites are rendered inaccessible by chromatin. We tested these assumptions through genome-wide mapping of GRFs in vivo and in purified biochemical systems at near–base pair (bp) resolution using several ChIP-exo–based assays. We find that computationally predicted DNA shape features (e.g., minor groove width, helix twist, base roll, and propeller twist) that are not defined by a unique consensus sequence are embedded in the nonunique portions of GRF motifs and contribute critically to sequence-specific binding. This dual source specificity occurs at GRF sites in promoter regions where chromatin organization starts. Outside of promoter regions, strong consensus sites lack the shape component and consequently lack an intrinsic ability to bind cognate GRFs, without regard to influences from chromatin. However, sites having a weak consensus and low intrinsic affinity do exist in these regions but are rendered inaccessible in a chromatin environment. Thus, GRF site-specificity is achieved through integration of favorable DNA sequence and shape readouts in promoter regions and by chromatin-based exclusion from fortuitous weak sites within gene bodies. This study further revealed a severe G/C nucleotide cross-linking selectivity inherent in all formaldehyde-based ChIP assays, which includes ChIP-seq. However, for most tested proteins, G/C selectivity did not appreciably affect binding site detection, although it does place limits on the quantitativeness of occupancy levels.

Identification of Human Lineage-Specific Transcriptional Coregulators Enabled by a Glossary of Binding Modules and Tunable Genomic Backgrounds

Transcription factors (TFs) control cellular processes by binding specific DNA motifs to modulate gene expression. Motif enrichment analysis of regulatory regions can identify direct and indirect TF binding sites. Here, we created a glossary of 108 non-redundant TF-8mer "modules" of shared specificity for 671 metazoan TFs from publicly available and new universal protein binding microarray data. Analysis of 239 ENCODE TF chromatin immunoprecipitation sequencing datasets and associated RNA sequencing profiles suggest the 8mer modules are more precise than position weight matrices in identifying indirect binding motifs and their associated tethering TFs. We also developed GENRE (genomically equivalent negative regions), a tunable tool for construction of matched genomic background sequences for analysis of regulatory regions. GENRE outperformed four state-of-the-art approaches to background sequence construction. We used our TF-8mer glossary and GENRE in the analysis of the indirect binding motifs for the co-occurrence of tethering factors, suggesting novel TF-TF interactions. We anticipate that these tools will aid in elucidating tissue-specific gene-regulatory programs.

Genome urbanization: clusters of topologically co-regulated genes delineate functional compartments in the genome of Saccharomyces cerevisiae

The eukaryotic genome evolves under the dual constraint of maintaining coordinated gene transcription and performing effective DNA replication and cell division, the coupling of which brings about inevitable DNA topological tension. DNA supercoiling is resolved and, in some cases, even harnessed by the genome through the function of DNA topoisomerases, as has been shown in the concurrent transcriptional activation and suppression of genes upon transient deactivation of topoisomerase II (topoII). By analyzing a genome-wide transcription run-on experiment upon thermal inactivation of topoII in Saccharomyces cerevisiae we were able to define 116 gene clusters of consistent response (either positive or negative) to topological stress. A comprehensive analysis of these topologically co-regulated gene clusters reveals pronounced preferences regarding their functional, regulatory and structural attributes. Genes that negatively respond to topological stress, are positioned in gene-dense pericentromeric regions, are more conserved and associated to essential functions, while upregulated gene clusters are preferentially located in the gene-sparse nuclear periphery, associated with secondary functions and under complex regulatory control. We propose that genome architecture evolves with a core of essential genes occupying a compact genomic ‘old town’, whereas more recently acquired, condition-specific genes tend to be located in a more spacious ‘suburban’ genomic periphery.

NetProphet 2.0: mapping transcription factor networks by exploiting scalable data resources

Motivation

Cells process information, in part, through transcription factor (TF) networks, which control the rates at which individual genes produce their products. A TF network map is a graph that indicates which TFs bind and directly regulate each gene. Previous work has described network mapping algorithms that rely exclusively on gene expression data and ‘integrative’ algorithms that exploit a wide range of data sources including chromatin immunoprecipitation sequencing (ChIP-seq) of many TFs, genome-wide chromatin marks, and binding specificities for many TFs determined in vitro. However, such resources are available only for a few major model systems and cannot be easily replicated for new organisms or cell types.

Results

We present NetProphet 2.0, a ‘data light’ algorithm for TF network mapping, and show that it is more accurate at identifying direct targets of TFs than other, similarly data light algorithms. In particular, it improves on the accuracy of NetProphet 1.0, which used only gene expression data, by exploiting three principles. First, combining multiple approaches to network mapping from expression data can improve accuracy relative to the constituent approaches. Second, TFs with similar DNA binding domains bind similar sets of target genes. Third, even a noisy, preliminary network map can be used to infer DNA binding specificities from promoter sequences and these inferred specificities can be used to further improve the accuracy of the network map.

Availability and implementation

Source code and comprehensive documentation are freely available at https://github.com/yiming-kang/NetProphet_2.0.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Gcn4 transcription factor reduces protein synthesis capacity and extends yeast lifespan

In Saccharomyces cerevisiae, deletion of large ribosomal subunit protein-encoding genes increases the replicative lifespan in a Gcn4-dependent manner. However, how Gcn4, a key transcriptional activator of amino acid biosynthesis genes, increases lifespan, is unknown. Here we show that Gcn4 acts as a repressor of protein synthesis. By analyzing the messenger RNA and protein abundance, ribosome occupancy and protein synthesis rate in various yeast strains, we demonstrate that Gcn4 is sufficient to reduce protein synthesis and increase yeast lifespan. Chromatin immunoprecipitation reveals Gcn4 binding not only at genes that are activated, but also at genes, some encoding ribosomal proteins, that are repressed upon Gcn4 overexpression. The promoters of repressed genes contain Rap1 binding motifs. Our data suggest that Gcn4 is a central regulator of protein synthesis under multiple perturbations, including ribosomal protein gene deletions, calorie restriction, and rapamycin treatment, and provide an explanation for its role in longevity and stress response.

The transcription factor Gcn4 is known to regulate yeast amino acid synthesis. Here, the authors show that Gcn4 also acts as a repressor of protein biosynthesis in a range of conditions that enhance yeast lifespan, such as ribosomal protein knockout, calorie restriction or mTOR inhibition.

Invisible cities: segregated domains in the yeast genome with distinct structural and functional attributes

Recent advances in our understanding of the three-dimensional organization of the eukaryotic nucleus have rendered the spatial distribution of genes increasingly relevant. In a recent work (Tsochatzidou et al., Nucleic Acids Res 45:5818-5828, 2017), we proposed the existence of a functional compartmentalization of the yeast genome according to which, genes occupying the chromosomal regions at the nuclear periphery have distinct structural, functional and evolutionary characteristics compared to their centromeric-proximal counterparts. Around the same time, it was also shown that the genome of Saccharomyces cerevisiae is organized in topologically associated domains (TADs), which are largely associated with the replication timing. In this work, we proceed to investigate whether such units of three-dimensional genomic organization can be linked to transcriptional activity as a driving force for the shaping of genomic architecture. Through the application of a simple boundary-calling criterion in genome-wide 3C data, we define ~100 TAD-like domains which can be clustered in six different classes with radically different nucleosomal organizations, significant variations in transcription factor binding and uneven chromosomal distribution. Approximately ~20% of the genome is found to be confined in regions with "closed" chromatin structure around gene promoters. Most interestingly, we find both "open" and "closed" regions to be segregated, in the sense that they tend to avoid inter-chromosomal interactions. Our data further enforce the notion of a marked compartmentalization of the yeast genome in isolated territories, with implications in its function and evolution.

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analyzed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined 4 CCA clusters-fluke-positive CCAs (clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations; conversely, fluke-negative CCAs (clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3' untranslated region deletion as a mechanism of FGFR2 upregulation. Integration of noncoding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores-mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics, and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer.Significance: Integrated whole-genome and epigenomic analysis of CCA on an international scale identifies new CCA driver genes, noncoding promoter mutations, and structural variants. CCA molecular landscapes differ radically by etiology, underscoring how distinct cancer subtypes in the same organ may arise through different extrinsic and intrinsic carcinogenic processes. Cancer Discov; 7(10); 1116-35. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 1047.

Transcription factor-DNA binding: beyond binding site motifs

Sequence-specific transcription factors (TFs) regulate gene expression by binding to cis-regulatory elements in promoter and enhancer DNA. While studies of TF-DNA binding have focused on TFs' intrinsic preferences for primary nucleotide sequence motifs, recent studies have elucidated additional layers of complexity that modulate TF-DNA binding. In this review, we discuss technological developments for identifying TF binding preferences and highlight recent discoveries that elaborate how TF interactions, local DNA structure, and genomic features influence TF-DNA binding. We highlight novel approaches for characterizing functional binding site motifs that promise to inform our understanding of how TF binding controls gene expression and ultimately contributes to phenotype.

Transcription Factor-DNA Binding Motifs in Saccharomyces cerevisiae: Tools and Resources

The DNA binding specificity of transcription factors (TFs) is typically represented in the form of a position weight matrix (PWM), also known as a DNA motif. A PWM is a matrix that specifies, for each position in the DNA binding site of a TF, the "weight" or contribution of each possible nucleotide. DNA motifs can be derived from various types of TF-DNA binding data, from small collections of known TF binding sites to large data sets generated using high-throughput technologies. One drawback of this simple model of DNA binding specificity is that it makes the implicit assumption that individual base pairs within a TF binding site contribute independently to the TF-DNA binding affinity. Although this assumption does not always hold, PWM models have been shown to provide reasonable approximations to the DNA binding specificity, and they are still widely used in practice. DNA motifs are currently available for more than 150 Saccharomyces cerevisiae TFs. Here, we briefly describe how these models are built, we provide information on databases containing DNA motifs for S. cerevisiae TFs, and we introduce guidelines on how to interpret the motifs and use them in practice to generate hypotheses about transcriptional regulatory regions.

Dry and wet approaches for genome-wide functional annotation of conventional and unconventional transcriptional activators

Transcription factors (TFs) are master gene products that regulate gene expression in response to a variety of stimuli. They interact with DNA in a sequence-specific manner using a variety of DNA-binding domain (DBD) modules. This allows to properly position their second domain, called "effector domain", to directly or indirectly recruit positively or negatively acting co-regulators including chromatin modifiers, thus modulating preinitiation complex formation as well as transcription elongation. At variance with the DBDs, which are comprised of well-defined and easily recognizable DNA binding motifs, effector domains are usually much less conserved and thus considerably more difficult to predict. Also not so easy to identify are the DNA-binding sites of TFs, especially on a genome-wide basis and in the case of overlapping binding regions. Another emerging issue, with many potential regulatory implications, is that of so-called "moonlighting" transcription factors, i.e., proteins with an annotated function unrelated to transcription and lacking any recognizable DBD or effector domain, that play a role in gene regulation as their second job. Starting from bioinformatic and experimental high-throughput tools for an unbiased, genome-wide identification and functional characterization of TFs (especially transcriptional activators), we describe both established (and usually well affordable) as well as newly developed platforms for DNA-binding site identification. Selected combinations of these search tools, some of which rely on next-generation sequencing approaches, allow delineating the entire repertoire of TFs and unconventional regulators encoded by the any sequenced genome.

The Role of Transcription Factors at Antisense-Expressing Gene Pairs in Yeast

Genes encoded close to one another on the chromosome are often coexpressed, by a mechanism and regulatory logic that remain poorly understood. We surveyed the yeast genome for tandem gene pairs oriented tail-to-head at which expression antisense to the upstream gene was conserved across species. The intergenic region at most such tandem pairs is a bidirectional promoter, shared by the downstream gene mRNA and the upstream antisense transcript. Genomic analyses of these intergenic loci revealed distinctive patterns of transcription factor regulation. Mutation of a given transcription factor verified its role as a regulator in trans of tandem gene pair loci, including the proximally initiating upstream antisense transcript and downstream mRNA and the distally initiating upstream mRNA. To investigate cis-regulatory activity at such a locus, we focused on the stress-induced NAD(P)H dehydratase YKL151C and its downstream neighbor, the metabolic enzyme GPM1. Previous work has implicated the region between these genes in regulation of GPM1 expression; our mutation experiments established its function in rich medium as a repressor in cis of the distally initiating YKL151C sense RNA, and an activator of the proximally initiating YKL151C antisense RNA. Wild-type expression of all three transcripts required the transcription factor Gcr2. Thus, at this locus, the intergenic region serves as a focal point of regulatory input, driving antisense expression and mediating the coordinated regulation of YKL151C and GPM1. Together, our findings implicate transcription factors in the joint control of neighboring genes specialized to opposing conditions and the antisense transcripts expressed between them.

Statistical analysis of structural determinants for protein-DNA-binding specificity

DNA-binding proteins play critical roles in biological processes including gene expression, DNA packaging and DNA repair. They bind to DNA target sequences with different degrees of binding specificity, ranging from highly specific (HS) to nonspecific (NS). Alterations of DNA-binding specificity, due to either genetic variation or somatic mutations, can lead to various diseases. In this study, a comparative analysis of protein-DNA complex structures was carried out to investigate the structural features that contribute to binding specificity. Protein-DNA complexes were grouped into three general classes based on degrees of binding specificity: HS, multispecific (MS), and NS. Our results show a clear trend of structural features among the three classes, including amino acid binding propensities, simple and complex hydrogen bonds, major/minor groove and base contacts, and DNA shape. We found that aspartate is enriched in HS DNA binding proteins and predominately binds to a cytosine through a single hydrogen bond or two consecutive cytosines through bidentate hydrogen bonds. Aromatic residues, histidine and tyrosine, are highly enriched in the HS and MS groups and may contribute to specific binding through different mechanisms. To further investigate the role of protein flexibility in specific protein-DNA recognition, we analyzed the conformational changes between the bound and unbound states of DNA-binding proteins and structural variations. The results indicate that HS and MS DNA-binding domains have larger conformational changes upon DNA-binding and larger degree of flexibility in both bound and unbound states. Proteins 2016; 84:1147-1161. © 2016 Wiley Periodicals, Inc.

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

A Network of Paralogous Stress Response Transcription Factors in the Human Pathogen Candida glabrata

The yeast Candida glabrata has become the second cause of systemic candidemia in humans. However, relatively few genome-wide studies have been conducted in this organism and our knowledge of its transcriptional regulatory network is quite limited. In the present work, we combined genome-wide chromatin immunoprecipitation (ChIP-seq), transcriptome analyses, and DNA binding motif predictions to describe the regulatory interactions of the seven Yap (Yeast AP1) transcription factors of C. glabrata. We described a transcriptional network containing 255 regulatory interactions and 309 potential target genes. We predicted with high confidence the preferred DNA binding sites for 5 of the 7 CgYaps and showed a strong conservation of the Yap DNA binding properties between S. cerevisiae and C. glabrata. We provided reliable functional annotation for 3 of the 7 Yaps and identified for Yap1 and Yap5 a core regulon which is conserved in S. cerevisiae, C. glabrata, and C. albicans. We uncovered new roles for CgYap7 in the regulation of iron-sulfur cluster biogenesis, for CgYap1 in the regulation of heme biosynthesis and for CgYap5 in the repression of GRX4 in response to iron starvation. These transcription factors define an interconnected transcriptional network at the cross-roads between redox homeostasis, oxygen consumption, and iron metabolism.

Sequence-targeted nucleosome sliding in vivo by a hybrid Chd1 chromatin remodeler

ATP-dependent chromatin remodelers regulate chromatin dynamics by modifying nucleosome positions and occupancy. DNA-dependent processes such as replication and transcription rely on chromatin to faithfully regulate DNA accessibility, yet how chromatin remodelers achieve well-defined nucleosome positioning in vivo is poorly understood. Here, we report a simple method for site-specifically altering nucleosome positions in live cells. By fusing the Chd1 remodeler to the DNA binding domain of the Saccharomyces cerevisiae Ume6 repressor, we have engineered a fusion remodeler that selectively positions nucleosomes on top of adjacent Ume6 binding motifs in a highly predictable and reproducible manner. Positioning of nucleosomes by the fusion remodeler recapitulates closed chromatin structure at Ume6-sensitive genes analogous to the endogenous Isw2 remodeler. Strikingly, highly precise positioning of single founder nucleosomes by either chimeric Chd1-Ume6 or endogenous Isw2 shifts phased chromatin arrays in cooperation with endogenous chromatin remodelers. Our results demonstrate feasibility of engineering precise nucleosome rearrangements through sequence-targeted chromatin remodeling and provide insight into targeted action and cooperation of endogenous chromatin remodelers in vivo.

Quantitative characterization of conformational-specific protein-DNA binding using a dual-spectral interferometric imaging biosensor

DNA-binding proteins play crucial roles in the maintenance and functions of the genome and yet, their specific binding mechanisms are not fully understood. Recently, it was discovered that DNA-binding proteins recognize specific binding sites to carry out their functions through an indirect readout mechanism by recognizing and capturing DNA conformational flexibility and deformation. High-throughput DNA microarray-based methods that provide large-scale protein-DNA binding information have shown effective and comprehensive analysis of protein-DNA binding affinities, but do not provide information of DNA conformational changes in specific protein-DNA complexes. Building on the high-throughput capability of DNA microarrays, we demonstrate a quantitative approach that simultaneously measures the amount of protein binding to DNA and nanometer-scale DNA conformational change induced by protein binding in a microarray format. Both measurements rely on spectral interferometry on a layered substrate using a single optical instrument in two distinct modalities. In the first modality, we quantitate the amount of binding of protein to surface-immobilized DNA in each DNA spot using a label-free spectral reflectivity technique that accurately measures the surface densities of protein and DNA accumulated on the substrate. In the second modality, for each DNA spot, we simultaneously measure DNA conformational change using a fluorescence vertical sectioning technique that determines average axial height of fluorophores tagged to specific nucleotides of the surface-immobilized DNA. The approach presented in this paper, when combined with current high-throughput DNA microarray-based technologies, has the potential to serve as a rapid and simple method for quantitative and large-scale characterization of conformational specific protein-DNA interactions.

Small Genetic Circuits and MicroRNAs: Big Players in Polymerase II Transcriptional Control in Plants

RNA Polymerase II (Pol II) regulatory cascades involving transcription factors (TFs) and their targets orchestrate the genetic circuitry of every eukaryotic organism. In order to understand how these cascades function, they can be dissected into small genetic networks, each containing just a few Pol II transcribed genes, that generate specific signal-processing outcomes. Small RNA regulatory circuits involve direct regulation of a small RNA by a TF and/or direct regulation of a TF by a small RNA and have been shown to play unique roles in many organisms. Here, we will focus on small RNA regulatory circuits containing Pol II transcribed microRNAs (miRNAs). While the role of miRNA-containing regulatory circuits as modular building blocks for the function of complex networks has long been on the forefront of studies in the animal kingdom, plant studies are poised to take a lead role in this area because of their advantages in probing transcriptional and posttranscriptional control of Pol II genes. The relative simplicity of tissue- and cell-type organization, miRNA targeting, and genomic structure make the Arabidopsis thaliana plant model uniquely amenable for small RNA regulatory circuit studies in a multicellular organism. In this Review, we cover analysis, tools, and validation methods for probing the component interactions in miRNA-containing regulatory circuits. We then review the important roles that plant miRNAs are playing in these circuits and summarize methods for the identification of small genetic circuits that strongly influence plant function. We conclude by noting areas of opportunity where new plant studies are imminently needed.