Such regulatory hotspots were enriched for known regulatory functions, such as recombinational DNA repair, telomere replication, and general transcription control. The OCRs associated with these multi-target trans-loci coincided with recombination hotspots, telomeres, and gene-rich regions according to the function of the associated regulators. Our findings provide a global quantitative picture of the genetic architecture of chromatin regulation.Chromatin regulation underlies a variety of DNA metabolism processes, including transcription, recombination, repair, and replication. To perform a quantitative genetic analysis of chromatin accessibility, we obtained open chromatin profiles across 96 genetically different yeast strains by FAIRE  assay followed by sequencing. While 5∼10% of open chromatin region (OCRs) were significantly affected by variations in their underlying DNA sequences, subtelomeric areas as well as gene-rich and gene-poor regions displayed high levels of sequence-independent variation. We performed quantitative trait loci (QTL) mapping using the FAIRE signal for each OCR as a quantitative trait. While individual OCRs were associated with a handful of specific genetic markers, gene expression levels were associated with many regulatory loci. We found multi-target  Quantitative trait loci (QTL) mapping is a genetic approach that allows the identification of genetic factors underlying a phenotype of interest. Genomic technologies such as DNA microarray and next-generation sequencing provide data that can be used for the analysis of multiple molecular phenotypes. For example, the expression levels of thousands of genes can be associated with subject-specific genome-wide genetic information in expression QTL mapping. Similarly, the genetic regulation of transcription factor binding or epigenetic mechanisms such as DNA methylation or chromatin structure has begun to be investigated. In particular, the mechanisms controlling chromatin accessibility have attracted special interest due to their importance in a variety of DNA regulation processes including recombination, repair, replication, and transcription. In this work, we sought to dissect the genetic architecture of chromatin accessibility regulation by harnessing the power of genetic and genomic techniques. By analyzing open (accessible) chromatin maps of multiple yeast individuals in association with their genetic backgrounds, we were able to characterize the regulatory structure of chromatin traits versus that of gene expression. Importantly, we observed that the genetic loci responsible for multiple open chromatin regions were enriched for known regulatory factors. Saccharomyces cerevisiae (BY and RM) were crossed to produce a number of different genetic recombinants, and their expression levels and genotypes were analyzed cis- and trans-components of variation in gene expression et al. cis- and trans-effects on nucleosome positioning. Recently, variations in the binding patterns of transcription factors (TFs) have begun to be studied The genetic basis of gene expression has been studied in various organisms Chromatin structure controls the access of a wide spectrum of DNA binding proteins involved in not only transcription but also DNA repair, recombination, and replication. Therefore, open chromatin areas can indicate DNA regions accessible to such regulators and thus have been used to identify regulatory regions or elements in the genome. In addition to the well-known DNaseI hypersensitivity assay, the FAIRE technique has been used to capture open chromatin sites in the genome with the aid of massively parallel sequencing (FAIRE-seq) cis-associations. Transcription factor binding was shown to be one of the main mechanisms by which DNA polymorphisms affect chromatin structure.As chromatin is a genetically regulated material, a genetic association approach could be used to understand the genetic architecture of chromatin regulation by examining open chromatin in multiple genetically different individuals. A recent study cis- and trans-associations, to better interpret the functional association of trans-acting factors. To this end, we generated open chromatin maps of 100 yeast samples, including the parental strains  and their descendants In this work, we took advantage of the compact size and comprehensive annotation of the yeast genome to dissect the entire genetic architecture of chromatin regulation, including both Open chromatin peaks were first identified for each sample. We then obtained a total of 7,527 OCRs by combining the peak signals of the 96 genetically different yeast strains. For each OCR, the density of the corresponding peak in each strain was calculated and normalized across the strains. The normalized peak density measures showed high reproducibility (R = 0.95∼0.99) between the replicates from different FAIRE batches and sequencing libraries . More thcis) variation and sequence-independent (trans) variation in chromatin accessibility. Cis-variation indicates variation in chromatin accessibility among individuals in which the DNA sequences of the given open-chromatin locus are different, while trans-variation indicates variation in chromatin accessibility among individuals with an identical genotype at the given locus. To measure cis-variation as the magnitude of chromatin variation caused primarily by cis-acting elements residing directly beneath open chromatin, we sought to determine the genotype of each OCR based on the SNP profiles generated from our sequence data. This enabled the classification of OCRs into either BY or RM groups according to each strain's inheritance of the locus (cis-variation of each OCR was defined as the variance of peak density among the strains with the same genotype at that OCR. The two cis-variation measures (each from the BY and RM group) were highly consistent (trans-variation by considering the within-group variance (cis-variation): 11.8% (P<0.05) or 4.8% (P<0.01) of the 1,738 OCRs were called significant (We sought to estimate the direct influence of underlying DNA sequences on chromatin configuration by quantitatively comparing sequence-dependent (he locus . The cisnsistent . Approxinificant .cis-acting loci within 100 kb (12.66% within 1 Mb), whereas the majority of chromatin traits were linked to trans-regulatory loci. The OCRs associated in trans tended to display a higher trans-variation (P<2×10−16), while those associated in cis had a higher cis-variation (P = 1.1×10−4), indicating consistency between sequence-based genotyping and microarray-based genotyping. We employed the gene expression data for the 96 strains QTL mapping was performed by interrogating the 7,527 OCRs against the genetic markers selected and processed based on the previous genotype data cis than other OCRs (P = 4.6×10−7). However, there was no difference with respect to trans-association. This implies that the effect of DNA sequence variation on chromatin structure is often manifested through underlying TF-binding motifs independently of trans-acting regulators.We identified a total of 2,234 OCRs in which there was a TF-binding motif that contained a polymorphism and found that these OCRs were twice as likely to be associated in cis-associations can also be explained by differential nucleosome formation, we searched for cis-QTL SNPs in the well-known poly A/T tract nucleosome depletion signature. We extracted the reference genome sequences surrounding the SNP locations within the OCRs from our FAIRE-seq data and then looked for the presence of a poly A/T tract. Even with a very loose threshold (five consecutive A/Ts), we could only identify five such instances. This is contradictory to the major role of the AT-rich sequences in the divergence of nucleosome positioning between different species To determine whether cis-associations between DNA sequences and chromatin accessibility are likely to be mediated by TF binding, a sequence polymorphism that affects chromatin accessibility in cis should also affect gene expression in the neighborhood. Indeed, a sizeable fraction (45%) of the chromatin-associated SNPs were associated with the expression of nearby genes. By contrast, only 15% of the expression-associated SNPs turned out to influence the accessibility of nearby chromatin, indicating that there are mechanisms by which sequence polymorphisms can affect the expression of nearby genes without affecting chromatin accessibility.Because the cis-markers encompassing 100 kb upstream to 15 kb downstream of the loci. Sequence analysis detected two underlying SNPs that were associated with the peak density of OCR #464  for each OCR and its associated trans-loci. The average R2 of the trans-associated OCRs was 33%. Enrichment of high trans-variation OCRs was observed in the vicinity of telomeres . It is possible that regulatory SNPs affect chromatin accessibility for DNA regulation other than transcription , which in turn leads to secondary gene expression changes, and that regulatory loci affect the expression of downstream regulators in trans, which in turn causes secondary changes in the accessibility of the target chromatin regions.Approximately 50% of chromatin QTLs were gene expression QTLs and vice versa, indicating that the trans-linkages for each OCR. Most OCRs were responsive to a small number of regulatory loci. Only a few (6.8%) had more than five linkages with the average number being three times lower than for gene expression traits (2.1 versus 5.9)  . This imory loci . There wory loci . The horory loci  illustraory loci , as oppoory loci .trans-associated OCRs. We annotated each locus by searching for known DNA or chromatin regulators flanking the marker within 10 kb −4)  . By cont0 kb −4) .DAL82, TEC1, and NRG2. Position weight matrices were available for the DNA-binding motif of Dal82p and Tec1p. Remarkably, 62% of the 71 DAL82-associated OCRs contained the Dal82p-binding motif. However, no Tec1p-binding motif enrichment was observed in the associated OCRs. The influence of Tec1p might be exerted not through direct binding but via interaction with other factors under normal growth conditions. Data for Nrg2p binding sites are not available. SET2 and MED2 are involved in the transcription of many genes in a non-sequence-specific manner. Set2p is a histone methyltransferase that plays a role in general transcription elongation, and Med2p is a subunit of the mediator complex that forms the RNA polymerase II holoenzyme. Their target OCRs were identified in gene-rich regions (Among the master regulators  were thr regions .RDH54 OCRs showed the highest recombination hotness among the master regulators (−25 (CDC13 locus had the largest number of associated OCRs in close proximity to telomeres (seven OCRs within 1 kb from telomeres). The enrichment of CDC13-associated OCRs near telomeres is shown in CDC13 OCRs was very low  during mitosis and meiosis by interacting with Rad51p and Rad54p gulators , with a ors  were associated with chromatin accessibility and gene expression at the same locus simultaneously. However, the identification of many dual QTLs was encouraging itself because it suggests that the detected QTLs are likely to contain functional regulators. We successfully annotated chromatin QTLs, particularly those responsible for a large number of target chromatin traits. The identification of functionally relevant cis-associations. We observed an enrichment of cis-associations for TF-motif-containing OCRs and common QTLs linking chromatin accessibility and nearby gene expression. This is consistent with the finding that human SNPs associated with chromatin in cis are frequently found in TF-binding sites Sequence-specific TF binding appears to be very important in cis-regulation was thoroughly examined, here we took advantage of the compact size and comprehensive annotation of the yeast genome to dissect the architecture of trans-regulatory mechanisms as well. In conclusion, our work provides insight into the genetic basis of chromatin regulation and its relationship with transcription control. Genetic variation in open chromatin in the human genome can underlie disease phenotypes, and thus, the current study has medical implications. For example, previous studies In contrast to the previous study We obtained the BY-RM cross strains from the original authors trans-variation, the standard deviations of the normalized peak density measures within the BY and RM groups was measured. We identified a total of 1,738 OCRs for which at least ten individuals inherited either a BY or RM allele; we then re-grouped the yeast strains according to the genotype of the given OCR. To assess the statistical significance of cis-variation, we used the two-sample t test to measure the difference in the means of the BY and RM groups.SNPs were detected from the FAIRE-seq reads using the Illumina's CASAVA suite. SNP calls with fewer than five reads were discarded. For heterogeneous calls, only the major polymorphism with a certain frequency (>80%) was taken. The genotype of each OCR was determined based on its SNP profile. The OCR in the given strain was considered to have inherited the BY (or RM) allele if its genotype perfectly matched with the genotype of the OCR in the BY (or RM) strain. For genotyping at a less stringent threshold, the OCRs whose SNP profile matched with either the BY or RM profile for >50% of the SNPs were also classified as BY or RM. To compute . The P value was determined by comparing the observed association cis- and trans-associations. We employed the gene expression data for the 96 strains The genetic markers from the original study −3 and <10−5, 91.1% and 81.1% of the identified associations were called significant, respectively. Adjacent genetic markers (<10 kb) associated with a common trait in QTL mapping were combined. Trans-loci were examined to determine whether the corresponding genetic marker covered at least one of the 752 regulators. According to this criterion, all trans-loci were classified into annotated loci or unannotated loci. We defined hotspot chromatin loci as having more than 65 genetic linkages. Adjacent genetic markers covering the same regulator were manually merged.A total of 11,048 marker-trait associations involving 3,522 OCRs were identified at an FDR of 0.01 when the correlation coefficient was used. To evaluate the consistency between the FDR-based non-parametric approach and the parametric method, we obtained a P value for each marker-trait pair based on the linear regression. At parametric P values<10http://derisilab.ucsf.edu/hotspots/. The cy5/cy3 ratios from seven ORF arrays were averaged and log2 transformed. The positions of replication origins were downloaded from http://cerevisiae.oridb.org. For TF motif analysis, we used position weight matrices in vivo binding assays by chromatin immunoprecipitation for 203 yeast TFs in vitro assays of 112 yeast TFs To calculate the density of the genes surrounding each OCR, the number of genes located within 50 kb upstream and 50 kb downstream of the OCR peak boundaries was determined. This number was divided by the size of the peak for normalization. The microarray data for the recombination hotspots of the yeast genome The FAIRE-seq data for the 96 yeast strains are available at the GEO database with accession number GSE33466.http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=zvyznqwickewmto&acc=GSE33466The following link has been created to allow review of the record GSE33466: Figure S1Reproducibility of FAIRE-seq. Beside BY and RM FAIRE-seq run on HiSeq2000, an additional set of FAIRE-seq libraries was independently sequenced on Illumina GA2. Another set of FAIRE samples was separately prepared and sent to another sequencing operator for library preparation and sequencing on Illumina GA2. In total, we sequenced three different batches of FAIRE-seq libraries for each of BY and RM. The normalized peak density of the OCRs from HiSeq2000 sequencing was compared with the two replicates from the completely different batches.(PDF)Click here for additional data file.Figure S2The percentage of OCRs falling on the promoter, ORF, and transcription termination site of protein-coding genes and on replication origins.(PDF)Click here for additional data file.Figure S3The frequency of OCRs (gray shade) found near the transcription start site (left panel) and the transcription termination site (right panel) in comparison with nucleosome occupancy (black curve).(PDF)Click here for additional data file.Figure S4The size of the OCRs identified in either parental strain (BY or RM) and those combined across the 96 strains .(PDF)Click here for additional data file.Figure S5trans-variation. The magnitude of trans-variation for each OCR was plotted along with the chromosomal coordinates of telomeres, centromeres, gene-rich or gene-poor regions, CDC13-associated OCRs, and multi-input OCRs (those with more than five associated QTLs).Chromosome-wide maps of (PDF)Click here for additional data file.Figure S6Gene density surrounding the OCRs of the master regulators as listed in (PDF)Click here for additional data file.Figure S7Recombination hotness of the OCRs of the master regulators as listed in (PDF)Click here for additional data file.


Analysis of a transcriptional regulatory network in a fungal pathogen reveals that four interdependent transcription factors respond to human body temperature to trigger changes in cell shape and virulence gene expression. Histoplasma capsulatum, are soil fungi that undergo dramatic changes in cell shape and virulence gene expression in response to host temperature. How these organisms link changes in temperature to both morphologic development and expression of virulence traits is unknown. Here we elucidate a temperature-responsive transcriptional network in H. capsulatum, which switches from a filamentous form in the environment to a pathogenic yeast form at body temperature. The circuit is driven by three highly conserved factors, Ryp1, Ryp2, and Ryp3, that are required for yeast-phase growth at 37°C. Ryp factors belong to distinct families of proteins that control developmental transitions in fungi: Ryp1 is a member of the WOPR family of transcription factors, and Ryp2 and Ryp3 are both members of the Velvet family of proteins whose molecular function is unknown. Here we provide the first evidence that these WOPR and Velvet proteins interact, and that Velvet proteins associate with DNA to drive gene expression. Using genome-wide chromatin immunoprecipitation studies, we determine that Ryp1, Ryp2, and Ryp3 associate with a large common set of genomic loci that includes known virulence genes, indicating that the Ryp factors directly control genes required for pathogenicity in addition to their role in regulating cell morphology. We further dissect the Ryp regulatory circuit by determining that a fourth transcription factor, which we name Ryp4, is required for yeast-phase growth and gene expression, associates with DNA, and displays interdependent regulation with Ryp1, Ryp2, and Ryp3. Finally, we define cis-acting motifs that recruit the Ryp factors to their interwoven network of temperature-responsive target genes. Taken together, our results reveal a positive feedback circuit that directs a broad transcriptional switch between environmental and pathogenic states in response to temperature.Survival at host temperature is a critical trait for pathogenic microbes of humans. Thermally dimorphic fungal pathogens, including  Histoplasma capsulatum, are a class of soil fungi that upon being inhaled into the human lung, undergo dramatic changes in cell shape and virulence gene expression in response to host temperature. The ability of these pathogens to cause disease is exquisitely coupled to temperature response. Here we elucidate the regulatory network that governs the ability of H. capsulatum to switch from a filamentous form in the soil environment to a pathogenic yeast form at body temperature. The circuit is driven by three transcription regulators  that control yeast-phase growth. We show that these factors, which include two highly conserved proteins of the Velvet family of unknown function, bind to specific regulatory DNA elements and directly regulate expression of virulence genes. We identify and characterize Ryp4, a fourth regulator of this pathway, and define DNA motifs that recruit these transcription factors to their temperature-responsive target genes. Our results provide a molecular understanding of how changes in cell shape are linked to expression of virulence genes in thermally dimorphic fungi.Microbial pathogens of humans display the ability to thrive at host temperature. So-called “thermally dimorphic” fungal pathogens, which include  Coccidioides, Paracoccidioides, Blastomyces, and Histoplasma species. These evolutionarily related fungi are notable among fungal pathogens in that they all cause disease in healthy individuals Cells adapt to their environment by responding to specific environmental stimuli such as light, temperature, and nutrients. For microbial pathogens, mammalian body temperature can signal the induction of pathways required for host colonization and pathogenesis Histoplasma capsulatum, which is endemic to the Ohio and Mississippi River Valleys of the United States, can cause life-threatening respiratory and/or systemic disease (histoplasmosis) H. capsulatum is found almost exclusively in the yeast form within mammalian hosts. Despite the prevalence of H. capsulatum and its threat to human health, we have a limited understanding of the transcriptional regulatory network that governs pathogenic yeast-phase growth. Previously, we identified three regulators, Ryp1, Ryp2, and Ryp3, and showed that they are required for yeast-phase growth ryp1, ryp2, and ryp3 mutants grow constitutively in the filamentous form independent of temperature. In wild-type cells, RYP1, RYP2, and RYP3 transcripts and proteins accumulate preferentially at 37°C and each Ryp protein is required for the wild-type expression levels of the others RYP1 encodes a fungal-specific transcriptional regulator that is required for modifying the transcriptional program of H. capsulatum in response to temperature Candida albicansSaccharomyces cerevisiae, the Ryp1 ortholog, Mit1, is required for a morphologic switch that occurs under nutrient limitation Fusarium oxysporum (Sge1), Fusarium graminerium (Fgp1), and Botrytis cinerae (Reg1) are required for full pathogenicity and conidiation Wor1, Pac2, Ryp1) family of proteins Aspergillus nidulansAspergillus species, Fusarium species, Neurospora crassa, and Acremonium chrysogenum  act together to regulate asexual and sexual development and secondary metabolism In contrast, Ryp2 and Ryp3 belong to the Velvet family of regulatory proteins Saccharomyces and Candida species, lack Velvet family proteins. Since both families of proteins are required for yeast-phase growth in H. capsulatum, we explored if and how these two distinct classes of fungal regulators work together to govern temperature-responsive traits by dissecting the Ryp regulatory network in H. capsulatum. To this end, we performed whole-genome transcriptional profiling and chromatin immunoprecipitation experiments to determine the shared and unique roles of Ryp1, Ryp2, and Ryp3 in regulating yeast-phase growth. We show that 96% of yeast-phase enriched transcripts are dependent on Ryp1, Ryp2, and Ryp3 for their enhanced expression in response to temperature, whereas 66% of filamentous-phase enriched transcripts require Ryp1, Ryp2, and Ryp3 to prevent their inappropriate expression at 37°C. We demonstrate that all three Ryp factors physically interact and associate with the upstream regions of a core set of target genes, including those required for yeast-phase growth and virulence. Additionally, we identify a fourth transcriptional regulator, Ryp4, to be a component of the Ryp regulatory network required for temperature-responsive yeast-phase growth. Finally, the identification of two distinct cis-acting regulatory sequences that are bound and utilized by Ryp proteins provides the first evidence that highly conserved Velvet family proteins can directly bind to DNA and activate gene expression using a unique cis-acting element. Overall, our results provide a molecular understanding of how regulation of cell morphology and virulence gene expression is coordinated in response to temperature in H. capsulatum.As noted above, both WOPR and Velvet family proteins are widely distributed among fungi, although the Hemiascomycetes, including RYP1, RYP2, or RYP3 grow constitutively as filaments independent of temperature ryp1, ryp2, ryp3 mutants and wild-type strains grown at room temperature (RT) and 37°C. We identified 388 genes with significantly increased transcript levels and 376 genes with significantly decreased transcript levels in wild-type yeast cells grown at 37°C compared to wild-type filaments grown at RT  YPS3) SOD3) AMY1) HSP82) CATB), which has been shown to display yeast-specific expression in the H. capsulatum strain used here and encodes a secreted catalase that may help cope with oxidative stress in the host ryp mutants, showing that Ryp factors are important for expression of virulence genes in H. capsulatum in response to temperature (Gene Ontology (GO) analysis showed that YPS genes were enriched in terms such as cell cycle regulation, chromosome segregation, and DNA recombination, all of which are characteristics of metabolically active, budding yeast cells . In contperature .ryp mutant revealed that the ryp mutants had a strongly diminished transcriptional response to temperature. The transcriptome of each ryp mutant grown at 37°C strongly resembled the transcriptome of wild-type cells grown at RT  in ryp mutants compared to the wild-type strain at 37°C. These results showed that Ryp1, Ryp2, and Ryp3 are master regulators required for the appropriate temperature-responsive transcriptional program in H. capsulatum.Global comparison of the gene expression profile of wild-type cells to that of each wn at RT . Additioch other , indicatRYP1, RYP2, and RYP3, and each of the RYPs depended on the other two for its temperature-regulated expression  using antibodies raised against Ryp1, Ryp2, and Ryp3. Experiments were performed in either wild-type yeast cells grown at 37°C, or in the respective ryp mutant control grown at 37°C. We observed 361 ChIP events throughout the genome of wild-type cells  were shared Ryp targets  compared to the whole genome, which is of interest since secreted proteins produced by intracellular pathogens are often involved in virulence.To map the genomic regions defined by ChIP-chip events to specific genes, we used a validated gene set that was defined previously based on gene expression and sequence conservation  of RYP3 . To furt of RYP3 . Targets targets . These r2Cys6 zinc binuclear cluster domain protein . We were able to deplete mRNA levels of HISTO_DM.Contig933.eannot.1650.final_new by 72%–88% (ryp mutants (RYP4 (Required for Yeast-Phase Growth). Although these morphologic studies revealed that ryp4 knockdown strains appeared drastically different from wild-type cells grown at 37°C, they were indistinguishable from wild-type filaments in appearance when grown at RT  protein . As show protein . Moreove protein . We inve 72%–88% . Additio mutants . Loss of mutants , indicatwn at RT .A. nidulans , and phylogenetic analysis  revealed that Ryp4 is an ortholog of FacB , leading us to favor the hypothesis that Ryp4 has been rewired to regulate morphology in H. capsulatum.BLASTP analysis indicated that the closest homolog of Ryp4 is FacB of  of FacB . FacB isryp1, ryp2, ryp3, and ryp4 knockdown strains grown either at RT or at 37°C. In contrast to the gene expression studies performed in ryp1, ryp2, and ryp3 knockdown strains to match the ryp4 knockdown strain (hereafter referred to as “mutant”). Statistical analyses revealed 441 YPS genes and 362 FPS genes in this dataset  and  dataset . Similar dataset . Notably mutants . The trawn at RT . Additioand RYP3 . In contand RYP3 . OverallRYP1, RYP2, and RYP4) and genes required for virulence (CBP1 and SOD3), further emphasizing the role of Ryp4 as a fundamental regulator of yeast-phase growth and an essential component of the temperature-responsive Ryp regulatory network .The ChIP data described above revealed that Ryp1, Ryp2, Ryp3, and Ryp4 share a large number of overlapping targets, suggesting that these proteins may physically interact. To test this hypothesis, we performed co-immunoprecipitation (co-IP) experiments in wild-type cells grown at 37°C using each of the Ryp antibodies. Of all possible co-IP combinations, we were able to reliably and reproducibly detect Ryp1, Ryp2, and Ryp3 in Ryp2 and Ryp3 IPs, indicating that at least these three Ryp proteins physically interact . Ryp4 IPS. cerevisiae strains used for yeast-two-hybrid analysis. As a result, yeast-two-hybrid interactions with Ryp1 could not be assessed. Similarly, a previous study reported difficulty expressing yeast-two-hybrid constructs made with the Ryp1 ortholog from F. oxysporumS. cerevisiae.In addition to these biochemical experiments, we used yeast two-hybrid experiments to assess Ryp1–Ryp2–Ryp3–Ryp4 interactions. We observed a reciprocal interaction between Ryp2 and Ryp3, confirming the co-IP results . Our rescis-acting regulatory sequences (hereafter referred to as DNA motifs). This de novo motif analysis was especially interesting for Ryp2 and Ryp3, since there has been no prior evidence that Velvet family proteins associate with DNA, and thus, no DNA motifs have been identified for Velvet family proteins. Through the analysis of Ryp1, Ryp2, and Ryp3 ChIP events, we identified two distinct DNA motifs, which we named Motif A and Motif B. Specifically, different variants of Motifs A and B were identified through the analysis of Ryp ChIP events (http://jaspar.genereg.net/) and YETFASCO (http://yetfasco.ccbr.utoronto.ca/). ROC plots using all ChIP events from each of the regulators demonstrated that Motif A and B were enriched in the entire ChIP set. Shuffled versions of each motif resulted in loss of specificity  associate with DNA via Motif B. To test whether Ryp1, Ryp2, or Ryp3 can directly bind to Motif A or Motif B, we performed electrophoretic mobility shift assays (EMSAs). The promoter region of the  Motif B , was use Motif B . His-tagEMSA revealed that full-length Ryp1 binds directly to Motif A, whereas control extracts contained no binding activity . In analin vivo transcriptional activation assay CYC1 promoter fused to the lacZ gene. We introduced these reporter plasmids along with constructs expressing the Ryp proteins, either individually or in combination, into S. cerevisiae and monitored β-galactosidase activity. S. cerevisiae provides an ideal heterologous expression system for our experiments, since the reporter strain we used lacks Ryp1 orthologs, and Velvet family proteins are not present in S. cerevisiae.Since Ryp1 is sufficient to bind Motif A and Ryp2–Ryp3 is sufficient to bind Motif B, we next used an In the strains that contained the Motif A reporter construct, β-galactosidase activity was detected only when Ryp1 was heterologously expressed . This acH. capsulatum.Cells have derived complex regulatory networks to reprogram their transcriptional response upon changes in the environment. In thermally dimorphic fungi, regulation of cell morphology and virulence traits is coupled: they respond to host temperature by altering their cell shape and inducing virulence gene expression. This study is the first elucidation of the transcriptional circuitry underlying this dramatic change in any of these organisms. In this article, we have shown that an interlocking network of transcription factors regulate each other and common target genes to trigger a transcriptional program that is required for cell shape changes and virulence gene expression in response to host temperature in RYP1, RYP2, and RYP4 genes—but none of the factors, including Ryp3 itself, associates upstream of the RYP3 gene. Thus we propose that at 37°C, each of the factors acts in a positive-feedback loop to regulate itself and each of the others. The exception is Ryp3, which regulates the other factors but is only indirectly regulated by them and does not directly regulate itself. Perhaps the interlocking nature of the network promotes a robust response by amplifying and stabilizing the signal generated by increased temperature. Additionally, the absolute requirement for activation of all four Ryp factors may provide specificity by requiring a sustained increase in temperature  to trigger the appropriate developmental program. Moreover, the requirement for multiple factors may allow unknown host signals other than temperature to influence the transition from filaments to yeast-form cells. The nature of the molecular signal that induces an initial increase in Ryp expression in response to temperature is unknown, but others have identified a histidine kinase, DRK1, that is required for yeast-phase growth in H. capsulatum and the related thermal dimorph Blastomyces dermatitidisDRK1 and regulation of Ryp factors has not been explored.Each of the Ryp transcription factors described here, including the newly discovered Ryp4, is absolutely required for the normal transcriptional profile of cells grown at 37°C. The structure of the corresponding transcription factor network is diagrammed in Ryp factors are required both to promote transcription of genes with enhanced expression at 37°C and to prevent the inappropriate expression of filament-associated genes at this temperature. Transcriptional profiling of wild-type cells grown either at 37°C (in the yeast form) or at room temperature (in the filamentous form) yielded 764 genes (about 8.5% of the genome) that passed our criteria for differential expression in one of the two growth phases. Remarkably, 96% of YPS genes required each of the four Ryp proteins to achieve differential expression in response to temperature. The majority of this regulon is a consequence of indirect regulation by the Ryp factors, since only a fraction of YPS genes are downstream of Ryp association events. The most significant enrichment for YPS genes was observed for shared targets of multiple Ryp factors: about 21% of shared targets were YPS genes as opposed to 4% of the whole genome. Interestingly, Ryp association events that are unique to an individual Ryp factor, such as the large cohort of ChIP-chip events that associate only with Ryp1 and not the other three Ryp factors, showed no enrichment for YPS genes. Additionally, Ryp targets that were not YPS genes did not depend on Ryp factors for their expression under standard laboratory conditions. It is possible that Ryp factors are poised upstream of these genes to regulate their expression in response to environmental signals other than temperature, such as light intensity, nutrient availability or exposure to reactive radicals in the host.S. cerevisiae, and the biochemical experiments that show that the Ryp1 ortholog Wor1 associates directly with DNA via a motif that is highly similar to Motif A in vitro, requires the presence of Ryp2, it is possible that these orphan events are actually shared with Ryp2 but fall below our level of detection for Ryp2 association. Alternatively, Ryp3 might be recruited to these targets via association with one of the other two Velvet domain proteins in H. capsulatum. Finally, the newly identified yeast-phase regulator Ryp4 seems to play no role in recognition of Motif A or Motif B, at least in vitro, and is incapable of driving gene expression via these motifs in a heterologous transcriptional activation assay. Additionally, we did not observe any physical interactions between Ryp4 and other Ryp factors. Taken together, these observations suggest that a third cis-regulatory element might recruit Ryp4 to its targets.Recruitment of the Ryp transcription factors to their direct targets is driven, at least in part, by DNA sequence motifs that are sufficient to recruit either Ryp1 (Motif A) or the Ryp2–Ryp3 complex (Motif B) . Motif AS. cerevisiae when Ryp2 and Ryp3 are co-expressed. The N-terminus of Ryp2, which contains the Velvet domain, is required for Ryp2–Ryp3 interaction in the yeast two-hybrid assay, whereas the C-terminus of Ryp2 mediates multimerization of Ryp2 . A hallmark of thermally dimorphic fungal pathogens is that temperature regulates cell shape and other factors required for pathogenesis. In the case of H. capsulatum, yeast-phase morphology is thought to be critical for the lifestyle of this fungus in the host, especially since replication of the fungus within host immune cells is likely to be incompatible with filamentous growth. Thus, Ryp factors catalyze both the cell shape change and the increased expression of known virulence factors, resulting in a molecular link between temperature and the expression of traits required to cause disease in a mammalian host. A link between morphology and virulence has been explored for many of the major human fungal pathogens, perhaps most extensively for C. albicans 2Cys6. Expression of each of the Ryp proteins has been wired to be absolutely dependent on all of the others, so strains that lack any of the regulators fail to undergo a developmental program in response to temperature. This network structure is interesting, in part because of the regulatory implications described above, but also because the relationship between orthologs of these transcription factors is not static throughout the fungal kingdom. For example, Hemiascomycetes have retained WOPR family members but lack Velvet family proteins. These phylogenetic differences provide an opportunity to study how regulatory circuits evolve. Finally, the role of the Ryp proteins in the life cycle of other thermally dimorphic fungi has not been examined. Elucidating the nature of this circuit in these related fungal pathogens will provide insight on the evolution of this temperature-responsive circuit.Finally, this work expands the rich history of elucidating fungal transcription circuits to understand regulatory networks in eukaryotic cells. Studies of fungal gene regulation continue to provide examples of novel DNA-binding domains, as was previously the case with the Ryp1 family of proteins H. capsulatum strains G217B (ATCC26032) and G217Bura5 (WU15) were kind gifts from Dr. William Goldman . ryp1, ryp2, ryp3 T-DNA, and knockdown mutants were previously generated ryp4 knockdown mutants and wild-type strains with control RNAi plasmids were generated in this study.Histoplasma macrophage medium (HMM) broth or on HMM agarose plates. G217Bura5 cultures were supplemented with 0.2 mg/ml uracil. Liquid cultures were grown at 37°C with 5% CO2 and shaking at 150 rpm and were passaged in every 2–3 d with 1∶25 dilution into fresh medium. For transcriptional profiling experiments, liquid cultures were grown at 120 rpm to minimize growth condition differences with filamentous-phase cultures. Plates were grown at 37°C with 5% CO2.All cultures were grown in ryp mutants taken from frozen stock were also plated on Sabouraud Dextrose agar and incubated either at 37°C with 5% CO2 or at 25°C. The resulting filamentous cells were inoculated into HMM and grown for 2 wk at 37°C with 5% CO2 or room temperature with shaking at 120 rpm to establish a filamentous-phase culture. Cultures were passaged with 1∶ 5 dilution into fresh medium every 1–3 wk.As previously described Escherichia coli DH5α strain and sequenced to ensure no mutation was introduced during the cloning process.All plasmids and primers used in this study are listed in RYP4 ORF were amplified from G217B gDNA using OAS2235-36 and OAS2237-38. Using Gateway Cloning Technology (Life Technologies-Invitrogen), these two fragments were cloned into pDONR/Zeo vector, generating pSB7 and pSB8 to target two different regions in the RYP4 mRNA. Combining pFANTAi4 with donor vectors generated integrating RNAi plasmids (pSB18 and pSB19). pSB23 is a Gateway-compatible destination plasmid and was derived from pCR186 . Combining pSB23 with donor vectors (pSB7 and pSB8) generated episomal RNAi plasmids (pSB30 and pSB31).Two ∼500 bp fragments of the S. cerevisiae strains EGY48/pSH18-34 and W303A, and plasmids pEG202 and pJSC401 were kind gifts from Dr. Jeffery S. Cox . The RYP3 ORF was amplified from G217B cDNA using OAS3415-3551, digested with EcoRI and XhoI, and ligated into similarly digested bait and prey plasmids pEG202 and pJSC401, respectively. This process generated the RYP3 bait plasmid (pSB74) and the RYP3 prey plasmid (pSB80). pSB74 was transformed into the EGY48/pSH18-34 strain and pSB80 was transformed into W303A using standard protocols RYP2 ORF was cloned directly into S. cerevisiae strains using standard protocols RYP2 full-length, RYP2-N-terminal (1–624 bp), and RYP2-C-terminal (595–1215 bp) fragments were amplified from G217B cDNA using OAS3559-60, OAS3559-96, and OAS3595-60, respectively. These three fragments were re-amplified using OAS3565-66 to increase homologous flanking sites to 50 bp. Extended fragments were cloned into linearized pEG202 generating the RYP2 full-length (pSB73), RYP2-N-terminal (pSB86), and RYP2-C-terminal (pSB87) bait plasmids. To generate prey plasmids, RYP2 full-length, RYP2-N-terminal (1–624 bp), and RYP2-C-terminal (595–1215 bp) fragments were amplified from G217B cDNA using OAS3567-68, OAS3567-4032, and OAS4031-3568, respectively; and these fragments were re-amplified using OAS3573-74. Extended fragments were cloned into linearized pJSC401 generating the RYP2 full-length (pSB79), RYP2-N-terminal (pJW1), and RYP2-C-terminal (pJW2) prey plasmids. Plasmids that were constructed in S. cerevisiae strains were rescued from yeast and transformed into E. coli DH5α strains for further manipulations.RYP genes, RYP1-N-terminus (1–801 bp), RYP1, RYP2, and RYP3 ORFs were amplified from G217B cDNA using OAS4110-11, OAS4114-15, OAS4118-19, and OAS4122-24, respectively. These reactions were cleaned and used as a template for the following amplification reaction. The goal of the second amplification was to introduce the T7 promoter, β-globin, and Kozak sequences to the 5′ end, and sequences encoding the TEV cleavage site, 6XHis-tag, polyA tail, and T7 terminator sequences to the 3′ end of each RYP fragment. To this end, all RYP fragments were amplified for 10 cycles in the presence of low amounts (0.05 µM) of OAS4106-07. Then, 0.5 µM of OAS4102-03 was added to the reactions and an additional 20 cycles of PCR amplifications were done. Resulting fragments were purified using QIAquick PCR purification kit (Qiagen) and cloned into pCR2.1-TOPO vector using the TOPO TA cloning kit (Invitrogen), generating pSB122 , pSB124 (RYP1), pSB128 (RYP2), and pSB130 (RYP3) plasmids.For expression of RYP genes, RYP1, RYP2, RYP3, and RYP4 ORFs, as well as RYP2 N-terminal fragments, were amplified from G217B cDNA using OAS3411-3549, OAS3555-3750, OAS3415-3551, OAS3751-52, and OAS3555-4205, respectively. RYP1, RYP2, RYP3, RYP4, and RYP2 N-terminal fragments were digested with EcoRI-XhoI, BamHI-SalI, EcoRI-XhoI, and SpeI-SalI, and BamHI-SalI, respectively, and ligated into similarly digested p413TEF and p414TEF vectors. Resulting plasmids are listed in RYP2 and RYP3 on the same plasmid, PTEF1-RYP2-tCYC1 fragment was amplified from pSB95 using OAS3783-84. This fragment was digested with SacI and ligated into SacI-digested pSB97, resulting in pSB115. To generate PCYC1ΔUAS-lacZ plasmids with DNA motifs, primer pairs OAS3893-94, OAS3895-96, OAS3901-2, and OAS3103-4 were annealed, digested with XhoI, and ligated into XhoI-digested PCYC1ΔUAS-lacZ plasmid. DNA sequencing was used to identify plasmids with single insertion and correct orientation of motifs. Resulting plasmids are listed in S. cerevisiae Δmit1Δyhr177w strain, which was a kind gift from Dr. Alexander D. Johnson .For expression of H. capsulatum G217Bura5 strain was done as previously described ryp4 knockdown strains with integrated RNAi constructs were used in all experiments, except for the plasmid loss experiments where episomal RNAi plasmids were used.Introduction of integrating and episomal RNAi plasmids into ryp4 mutants generated with two different episomal RNAi plasmids (pSB30 and pSB31) were grown in HMM broth supplemented with uracil (0.2 mg/ml) at 37°C, 120 rpm with 5% CO2. After 4 wk, an inoculating loop was used to transfer cells from each flask onto HMM+uracil agarose plates followed by incubation at 37°C with 5% CO2. Individual yeast-phase colonies were streaked again and tested for uracil auxotrophy on HMM agarose plates. Representative images of the resulting strains are shown in Four independent All images were obtained using a Zeiss Axiovert 200 microscope with 40× Phase objective.H. capsulatum strains was harvested using Trizol (Life Technologies-Invitrogen) following manufacturer's instructions. RNA was treated with RNase-free DNase set (Qiagen) and cleaned using the RNeasy mini kit (Qiagen). 2 µg of total RNA was used in cDNA synthesis using Superscript RT II (Life Technologies-Invitrogen) following manufacturer's instructions. cDNAs were used to amplify RYP1, 2, 3, 4, and GADPH transcripts using OAS1057-58, OAS1942-43, OAS1944-45, OAS3320-31, and OAS1452-53, respectively . cDNA from each ryp mutants and wild-type controls was labeled with Cy5  as described H. capsulatum whole-genome 70-mer oligonucleotide microarray. For the experiments with ryp T-DNA mutants, there were four to six replicates for each strain and condition, and for the experiments with ryp knockdown strains, there were three to 12 replicates for each strain and condition. Raw data for all hybridizations  performed are available through Gene Expression Omnibus  with accession numbers GSE46936, GSE46937, GSE46938, and GSE46939 (GEO superseries accession number GSE 47832).Total RNA from http://nomad2.ucsf.edu/NOMAD/nomad-cgi/login.pl), and MultiExperiment Viewer 4.0 (www.tm4.org/mev.html) p value <0.01 as a cutoff criteria. Results of these analyses are given in Arrays were scanned on a GenePix 4000B scanner (Molecular Devices) to determine the intensity units in the 635- and 523-nm channels  for each spot on the microarray. Data were analyzed by using GENEPIX PRO version 6.0, NOMAD (http://www.geneontology.org/]). GO-to-gene edges were added from the 12/7/2011 versions of the AspGD [http://www.aspgd.org/] http://www.candidagenome.org/] http://www.yeastgenome.org/] A. nidulans (An), A. fumigatus (Af), C. albicans (Ca), Candida glabrata (Cg), and S. cerevisiae (Sc). Gene-to-gene edges were added for An/Af/Ca/Cg/Sc genes to their H. capsulatum G217B (HcG217B) orthologs based on InParanoid mapping of each genome pair (using default parameters with no outgroup). InterPro domains (IPR) from the Pfam, TIGRFAMS, SMART, PANTHER, and Gene3D databases from InterPro version 34 were mapped to HcG217B genes with InterProScan version 4.8 A directed graph was constructed from all “is-a” relationships in the 12/7/2011 version of the Gene Ontology (go_daily-termdb.obo-xml.gz downloaded from the GO Consortium website [2Cys6 binuclear cluster domain (PF00172.13) and the fungal-specific transcription factor domain (PF04082.13). Each HMM was searched against the BROAD predicted gene sets for Coccidioides immitis RS, Trichophyton verrucosum HKI 0517, Paracoccidioides brasiliensis Pb03, Blastomyces dermatitidis er-3, Fusarium graminearum ph-1, Neurospora crassa OR74A, Magnaporthe oryzae 70-15, Botrytis cinerea B05.10, and Stagnospora nodorum SN15; the SGD curated gene set for Saccharomyces cerevisiae S288C; the AspGD curated gene set for Aspergillus nidulans FGSC; and the GSC predicted gene set for Histoplasma capsulatum G217B using hmmscan. Hits were aligned to each HMM using hmmalign, and neighbor-joining trees were generated from the aligned domain sequences using CLUSTALW 2.1. For PF00172.13, Ryp4 was found in a monophyletic clade, sister to Sip4, with orthologs from each target species except for B. cinerea. For PF04082.13, Ryp4 was found in a monophyletic clade identical to the previous one except for the gain of B. cinerea BC1G_13551 and the loss of Sc Cat8. TBLASTN of the Ryp4 protein sequence against the B. cinerea genome yielded a hit to the Zn(II)2Cys6 domain (E = 2e-29) about 170 bp upstream of BC1G_13551, consistent with an incorrectly predicted 5′ for this gene. Based on these results, the union of pezizomycotina hits was annotated as orthologs of Ryp4. The full-length protein sequences of the Ryp4 orthologs, as well as Cat8 and Sip4, were aligned, and a bootstrapped  neighbor-joining tree was generated using CLUSTALW.Initial sets of Ryp4 homologs were identified using HMMer 3.0 and the Pfam hidden Markov models (HMMs) for the fungal Zn(II)ryp1, ryp2, ryp3, and ryp4 mutants and wild-type (G217B) cells were grown at 37°C. Cells were fixed and collected as previously described ryp mutants), lysates from three identical tubes were combined prior to antibody incubation. Each sample was incubated overnight at 4°C with 20 µg of polyclonal antibodies against portion of Ryp1 , Ryp2 , Ryp3 , or Ryp4 . On the next day, 40 µl of Protein-A Sepharose 4B Fast Flow (Sigma-Aldrich) beads were added to the lysate-antibody mixture and further incubated for 2 h. Subsequently, beads were collected by centrifugation and washed nine times. Protein–DNA complexes that are bound to the beads were collected by incubating beads at 65°C with elution buffer . Protein–DNA crosslinks in input and ChIPed samples were reversed overnight at 65°C. Proteins were digested with proteinase K and DNA was purified with phenol∶chloroform extraction as described H. capsulatum genome at a frequency of one probe per 50 bp. Oligos were selected based on a previously published method ryp mutants were used as a negative control in this analysis. Default parameters of Mochiview peak extraction were used with the exception of increasing total random samples to 100,000 and maximum random samples to 100 . Median+Interquartile range (IQR) was used as a threshold to filter extracted peaks. Peaks that were eliminated based on the noisy enrichment values in ryp mutants were included back if there was >2-fold difference between wild-type and ryp mutant enrichment ratios. Additionally, peaks that were greater than a median value for a given Ryp event and had another Ryp event greater than median+IQR were also included in the finalized list of events (Slides were scanned with an Agilent scanner and raw ratios were obtained with the Agilent ChIP_107_Sep09 protocol. Background subtracted probe intensities were transformed to log2 (red/green) ratios (M) and log2 (sqrt(red*green)) geometric mean intensities (A), excluding probes with intensities below background. The M,A values were fit using the LOWESS algorithm f events . ChIP enH. capsulatum G217B strain validated gene set that was defined previously using gene expression and sequence conservation criteria Each ChIP event was mapped to specific genes using an Signal peptide and transmembrane helix prediction algorithm Phobius 1.01 p value reflects only the alignment of the motif instance to the query matrix). For ROC plots, the motif threshold (-mt) was set to 0.01 in order to explore a wide range of possible parameter values. For genome-wide searches, the motif threshold was set to the values determined from the ROC plots using false positive rate of 10% as a cutoff . Motif locations identified in the genome are given in Each set of Ryp ChIP events was randomly split into two sets using Mochiview. Each set was subjected to motif finding algorithms using Mochiview and Bioprospector For expression of the Ryp1-N-terminus, Ryp1, Ryp2, and Ryp3 proteins for EMSA experiments, we subjected pSB122, pSB124, pSB128, and pSB130, respectively, to TNT Coupled Wheat Germ Extract systems (Promega) following the manufacturer's instructions. For purification of Ryp proteins, eight 50-µl reactions were pooled and diluted 10-fold in binding buffer  supplemented with HALT phosphatase and protease inhibitors (Pierce). For each sample, 100 µl of Ni-NTA agarose beads (Qiagen) was washed in binding buffer and incubated with extracts for 1 h at 4°C. Following the incubation, beads were washed once with binding buffer, and once with binding buffer with no detergents. His-tagged proteins were recovered with elution buffer . The presence of His-tagged Ryp proteins was confirmed by SDS-PAGE analysis and Western blotting. Wheat germ extract with no DNA template was subjected to a similar purification process and use as a control in mobility shift assays.2, and 1 mM DTT. Nonlabeled competitor probes were prepared similarly with nonlabeled oligonucleotides , α-Ryp2 , or α-Ryp3  antibodies were used to detect Ryp proteins.Wild-type (G217B) cells grown to late log phase at 37°C were harvested by filtration, and the pellet was frozen in liquid nitrogen. Whole cell extracts were made by cryogrinding the pellet in Retsch Mixer Mill MM 400. Co-immunoprecipitation experiments were performed using the Dynabeads Co-immunoprecipitation kit from Invitrogen following the manufacturer's instructions. Briefly, 100 ug of polyclonal α-Ryp2  or α-Ryp3  antibodies were covalently linked to 5 mg of magnetic beads using Dynabeads Antibody Coupling kit. To prepare cell lysate, 2 g of ground samples were mixed with lysis buffer, vortexed, and spun down. Then, supernatant was incubated with 5 mg of antibody-coupled magnetic beads for 8 h at 4°C. After multiple washes, protein complexes that are bound to antibody-coupled beads were eluted in low pH buffer provided by the manufacturer. IPs with S. cerevisiae strain were grown to late log (for the yeast-two-hybrid assay) or stationary  phase. Each isolate was assayed in quadruplicate, and the results of representative isolates are shown in β-galactosidase assays were performed as previously described Figure S1ryp mutants and wild-type cells grown at room temperature are presented as scatter plots with Pearson correlation coefficients . (B) qRT-PCR was used to quantify relative levels of RYP1, RYP2, and RYP3 transcripts in ryp1, ryp2, and ryp3 mutants and wild-type cells grown at 37°C and room temperature (RT). GAPDH was used as a normalizer gene. Experiments were performed with at least two biological replicates for each strain. Triplicate measurements of representative replicates are graphed as the mean ± standard deviation.Ryp factors are required for each other's expression. (A) Correlation between transcriptional profiles of YPS and FPS genes in (TIF)Click here for additional data file.Figure S2Ryp events occur at longer intergenic regions. (A) Numbers of Ryp1, Ryp2, and Ryp3 ChIP events are shown as a Venn diagram. (B) Intergenic length distributions for the whole genome (black line) and Ryp1, Ryp2, and Ryp3 individual and common ChIP events (red lines) are shown. The differences between length distributions were compared using the Wilcoxon test.(TIF)Click here for additional data file.Figure S3RYP genes. (A) Phase-contrast microscopy images of wild-type cells, or wild-type cells carrying either a vector control or RYP4 RNAi plasmid are shown. RNAi vectors were maintained episomally and strains were grown at 37°C. ryp4 knockdown strains were grown without selection to allow growth of clones that underwent spontaneous plasmid loss. Isolates of these strains that converted to the yeast form were analyzed to confirm that they had lost the RNAi marker. Black bar equals 20 µm.  Ryp4 is an ortholog of FacB. Initial sets of Ryp4 homologs were identified using HMMer 3.0 and the Pfam hidden Markov models (HMMs) for the fungal Zn(II)2Cys6 binuclear cluster domain  and the fungal-specific transcription factor domain . Details of the databases used and searches are given in Materials and Methods. The full-length protein sequences of the Ryp4 orthologs, as well as Cat8 and Sip4, were aligned (C), and a bootstrapped  neighbor-joining tree (B) was generated using CLUSTALW. (D) qRT-PCR was used to quantify relative levels of RYP1, RYP2, and RYP3 transcripts in ryp4 mutants and wild-type controls grown at 37°C and room temperature (RT). GAPDH was used as a normalizer gene. Experiments were performed with at least two biological replicates for each strain. Triplicate measurements of representative replicates are graphed as mean ± standard deviation.Ryp4 is required for yeast-phase growth and the expression of (TIF)Click here for additional data file.Figure S4ryp mutants grown at (A) 37°C and (B) room temperature and wild-type cells grown at room temperature are presented as scatter plots with Pearson correlation coefficients .Ryp knockdown mutants display similar transcriptional profiles to that of wild-type filaments. Correlation between transcriptional profiles of YPS and FPS genes in (TIF)Click here for additional data file.Figure S5p values obtained in this analysis are given. Additionally, Ryp1, Ryp3; Ryp1, Ryp2, Ryp3; and Ryp1, Ryp2, Ryp3, Ryp4 shared targets were enriched for YPS genes  as determined by hypergeometric tests performed in R.Ryp4 associates upstream of Ryp1, Ryp2, and Ryp3 targets. A network view of ChIP targets was generated using Cytoscape software. Each large open circle is composed of individual closed circles that represent individual genes. YPS genes are colored in yellow, and FPS genes are colored in blue. Microarrays used in this study represent 9,289 genes, which were also colored similarly as shown. The distribution of YPS and FPS genes in each type of ChIP event was compared to the whole genome using the Wilcoxon test. The (TIF)Click here for additional data file.Figure S6Ryp events are enriched for specific DNA sequences. Logos of (A) Motif A and (B) Motif B variants are shown.  Motif specificity of (C) Motif A and (D) Motif B were analyzed by ROC plots. True positive rate was defined as motifs found in ChIP events that contained or excluded a given Ryp event. False positive rate was defined as motifs found in unbound intergenic regions. (E) Similarly, motif specificity of Motif A and Motif B was analyzed in Ryp1-only or shared events by ROC plots.(TIF)Click here for additional data file.Figure S7RYP genes were cloned into two different vectors with two different markers. Each of these vectors were transformed into yeast strains with plasmids containing the UAS-less CYC1 promoter fused to the lacZ gene to generate “no motif” controls (A). Additionally, complementary sequences of (B) Motif A, (C) Motif B, and their mutated versions were cloned into a plasmid containing the UAS-less CYC1 promoter fused to the lacZ gene. Point mutations made in the motifs are shown in red. Each of the motif and Ryp plasmids were transformed into yeast strains as labeled. β-galactosidase activities were measured for three independent isolates of each strain. Quadruplicate measurements of representative isolates are graphed as the mean ± standard deviation.Motif A and Motif B are sufficient to drive gene expression in the presence of Ryp factors. (TIF)Click here for additional data file.Table S1ryp T-DNA mutants. Normalized expression ratios were analyzed with BAGEL using default parameters. Relative expression ratios and posterior probabilities for each pairwise comparison are listed for each gene. Phase-specific (YPS and FPS) genes were identified using the criteria of p value <0.01 and >2-fold change in gene expression levels in the WT_37 (wild-type yeast cells) versus WT_RT (wild-type filamentous cells) comparison. These genes are shown also as a heatmap in Whole-genome transcriptional profiling results of (TXT)Click here for additional data file.Table S2ChIP-chip results. ChIP events identified in this study are listed according to their genomic locations. Each ChIP event was mapped to annotated genes with a criterion of an event preceding an open reading frame with 5′-3′ orientation. Target genes, associated ChIP event IDs, gene annotations, and Log2-based expression ratios (WT_37/WT_RT) are listed. This list was used to generate (TXT)Click here for additional data file.Table S3ryp knockdown strains. Normalized expression ratios were analyzed with BAGEL using default parameters. Relative expression ratios and posterior probabilities for each pairwise comparison are listed for each gene. Phase-specific (YPS and FPS) genes were identified using the criteria of p value <0.01 and >2-fold change in gene expression levels in the WT_37 (wild-type yeast cells) versus WT_RT (wild-type filamentous cells) comparison. These genes are shown also as a heatmap in Whole-genome transcriptional profiling results of (TXT)Click here for additional data file.Table S4Motif position weight matrices. Position weight matrices of motifs shown in (TXT)Click here for additional data file.Table S5p values of 2.08e-04 for Motif A and 9.18e-05 for Motif B).Genomic coordinates of Motif A and Motif B hits. All intergenic sequences were searched for occurrences of Motif A and Motif B using MAST. Motif hits were filtered using <10% false positive rate as a cut-off (corresponding to (TXT)Click here for additional data file.Table S6Plasmids used in this study.(PDF)Click here for additional data file.Table S7Primers used in this study.(PDF)Click here for additional data file.


Saccharomyces cerevisiae established that depletion of histone H4 results in the genome-wide transcriptional de-repression of hundreds of genes. To probe the mechanism of this transcriptional de-repression, we depleted nucleosomes in vivo by conditional repression of histone H3 transcription. We then measured the resulting changes in transcription by RNA–seq and in chromatin organization by MNase–seq. This experiment also bears on the degree to which trans-acting factors and DNA–encoded elements affect nucleosome position and occupancy in vivo. We identified ∼60,000 nucleosomes genome wide, and we classified ∼2,000 as having preferentially reduced occupancy following H3 depletion and ∼350 as being preferentially retained. We found that the in vivo influence of DNA sequences that favor or disfavor nucleosome occupancy increases following histone H3 depletion, demonstrating that nucleosome density contributes to moderating the influence of DNA sequence on nucleosome formation in vivo. To identify factors important for influencing nucleosome occupancy and position, we compared our data to 40 existing whole-genome data sets. Factors associated with promoters, such as histone acetylation and H2A.z incorporation, were enriched at sites of nucleosome loss. Nucleosome retention was linked to stabilizing marks such as H3K36me2. Notably, the chromatin remodeler Isw2 was uniquely associated with retained occupancy and altered positioning, consistent with Isw2 stabilizing histone–DNA contacts and centering nucleosomes on available DNA in vivo. RNA–seq revealed a greater number of de-repressed genes  than previous studies, and these genes exhibited reduced nucleosome occupancy in their promoters. In summary, we identify factors likely to influence nucleosome stability under normal growth conditions and the specific genomic locations at which they act. We find that DNA–encoded nucleosome stability and chromatin composition dictate which nucleosomes will be lost under conditions of limiting histone protein and that this, in turn, governs which genes are susceptible to a loss of regulatory fidelity.Previous studies in  Chromatin is formed by wrapping 146 bp of DNA around a disc-shaped complex of proteins called histones. These protein–DNA structures are known as nucleosomes. Nucleosomes help to regulate gene transcription, because nucleosomes compete with transcription factors for access to DNA. The precise positioning and level of nucleosome occupancy are known to be vital for transcriptional regulation, but the mechanisms that regulate the position and occupancy of nucleosomes are not fully understood. Recently, many studies have focused on the role of DNA sequence and chromatin remodeling proteins. Here, we manipulate the concentration of histone proteins in the cell to determine which nucleosomes are most susceptible to changes in occupancy and position. We find that the chromatin-associated proteins Sir2 and Tup1, and the chromatin remodelers Isw2 and Rsc8, are associated with stabilized nucleosomes. Histone acetylation and incorporation of the histone variant H2A.z are the factors most highly associated with destabilized nucleosomes. Certain DNA sequence properties also contribute to stability. The data identify factors likely to influence nucleosome stability and show a direct link between changes in chromatin and changes in transcription upon histone depletion. After histone gene silencing, the yeast cells complete a single round of DNA replication, reducing their histone-DNA ratio by a factor of approximately two, and enter cell-cycle arrest. A number of conditionally expressed genes, including PHO5, GAL1, CYC1, CUP1, and HIS3, were reported to be transcriptionally de-repressed following histone depletion PHO5 promoter during H4 depletion, but at the time these experiments were performed, high-resolution genomic methods were not available to measure the widespread chromatin changes hypothesized to underpin the observed transcriptional changes. We therefore revisited these classic experiments using RNA-seq and MNase digestion coupled with next-generation sequencing (MNase-seq) to monitor RNA and chromatin changes after histone depletion. These experiments also bear on the recent debate regarding the degree to which DNA-encoded elements or other cellular factors control nucleosome position and occupancy Twenty-five years ago, Michael Grunstein's laboratory began a series of experiments in which histones H2B or H4 were depleted S. cerevisiae, HHT1 and HHT2. We obtained a strain in which HHT1 had been deleted and HHT2 had been placed under control of the GAL1 promoter  To assess the overall similarity of our experimental replicates, we compared the overall nucleosome occupancy for each base pair among the replicates and found the experiments to be highly correlated –S2K. As To identify changes in specific nucleosomes, we determined the position and occupancy of individual nucleosomes in each replicate at each time point . We usedChanges in each nucleosome's position between the 0- and 3-hour time points were assessed using the t-test on the distribution of the read centers. The nucleosome position was then classified as being “altered” or “unchanged” based on the resulting p-value. Nucleosomes with borderline p-values were placed in a “no call” category and not used for the downstream analyses . The useChanges in each nucleosome's occupancy were assayed using the binomial distribution test on the number of read centers that fell within a 100-bp window centered on the nucleosome's consensus dyad. We stress that our experimental approach did not allow absolute nucleosome occupancy calculations, so the occupancy at a given location is in effect measured relative to all other nucleosomes in the same experiment. Nucleosomes were classified as “preferentially reduced” (decreased occupancy relative to other nucleosomes), “unchanged” (similar occupancy relative to others), or “preferentially retained” (increased relative occupancy). Nucleosomes with borderline p-values were placed in a separate “no call” category, similar to the position classification .http://sourceforge.net/p/callnucleosomes.Nucleosomes that were classified identically in two or more replicates were selected as being “reliably characterized” . By compPHO5, which had been previously shown to have altered chromatin and increased transcription following H3 depletion IDP2, a gene with increased transcription following H3 depletion  to genome annotations and to previously published ChIP-chip or ChIP-seq experiments, including proteins . Nearly proteins . Therefoproteins . TherefoUpon histone H3 depletion, reduced-occupancy nucleosomes tended to occur in promoter regions, while nucleosomes in the gene bodies were associated with unchanged occupancy . ConsistConsistent with nucleosome destabilization due to histone acetylation, “altered position” or “reduced occupancy” nucleosomes were enriched for 14 of the 16 of the histone acetylation marks we examined (p<0.01) . AcetylaWe compared the H3-depletion responsive nucleosomes to previously published genome-wide data for several transcription factors, including Bdf1, Rap1, Reb1, and Tup1 In contrast, Tup1 is a known transcriptional repressor that can recruit histone deacetylases (HDACs) in vitroIsw2 is an ATP-dependent chromatin remodeler that positions nucleosomes at the 5′ and 3′ ends of genes by binding to both the histone octamer and DNA in vivo  increased both upstream and downstream of Isw2-bound nucleosomes following nucleosome depletion such that the Isw2-bound nucleosomes became centered on the new local DNA substrate. While the ability of Isw2 to slide nucleosomes in vivo has been demonstrated previously in vivo. We note that position-altered nucleosomes not bound by the mutant Isw2K215R as described in Based on its biochemical nucleosome-centering activity in vivo . The shiin vivo . Fully cin vivo may be aided by incorporation of H2A.z and restricted by Tup1 and Rsc8.“Position altered,” Isw2-bound nucleosomes tended to contain the histone variant H2A.z (p<0.01) relative to all Isw2-bound nucleosomes in vitroS. cerevisiae results in a 20–30% decrease in histone levels in vivoNhp6a is an HMG-group protein known to associate with chromatin . After 3 hours in dextrose, the wildtype correlation to the in vitro data decreased (r = 0.59), but the H3 shutoff strain's correlation increased  and dextrose-grown (r = 0.716) yeast  results in a chromatin organization that is much more similar to the in vitro configuration than cells with the normal complement of nucleosomes grown in either dextrose or galactose.The influence of DNA sequence on nucleosome occupancy has been determined directly by 6) yeast . This suWe next used a previously published DNA sequence-based model of nucleosome occupancy in vivo correlated with the degree of change in the DNA sequence-predicted nucleosome affinity  also showed a significant position change following H3 depletion. At these nucleosomes, the average predicted occupancy for the “before” and “after” positions corresponds with the actual observed change in nucleosome occupancy . To see affinity . In a reWe next revisited the hypothesis that gene expression changes in response to histone depletion are rooted in changes in chromatin organization We divided the yeast genes into three groups based on expression changes: increased, normal, and decreased. In the promoters of genes with increased or normal expression following H3 depletion, we found an over-representation of “occupancy reduced” nucleosomes . In contin vivo. (2) Nucleosomes that are preferentially lost tend to be located at promoters, and this, in turn, leads to de-repression of downstream genes. (3) Isw2, an important ATP-dependent chromatin remodeler, is associated with stable nucleosome occupancy but altered position, especially when an adjacent nucleosome is destabilized. Such nucleosomal positioning shifts in the direction of the adjacent loss event are consistent with a nucleosome-centering activity for Isw2 in vivo, which to this point has been observed only in vitro. (4) Following nucleosome loss, the intrinsic DNA sequence preferences of nucleosomes have a greater influence on occupancy profiles, presumably due to reduced steric hindrance from adjacent nucleosomes. (5) Nhp6a is associated with preferentially lost nucleosomes in gene bodies. Deletion of Nhp6a/b causes a 20–30% reduction in histone abundance and altered transcription of approximately 10% of the yeast genome (fold-change >1.5 and p<0.05) The experiments described above support the following main conclusions: (1) Depletion of histone H3 levels causes a defined subset of nucleosomes to alter their position and/or occupancy Our approach used MNase-seq to map nucleosome position and relative occupancy before and after H3 depletion. One concern with using MNase to measure nucleosome position and occupancy is that the enzyme's ability to digest DNA can be influenced by the local histone occupancy, with regions of lower histone occupancy being more susceptible to MNase digestion. Following H3 depletion, we observed increased smearing in the MNase-digested DNA fragments but saw no change in the average fragment length or the number of nucleosomes called by our algorithm. Thus, despite the increased sensitivity to MNase, the mononucleosome properties were equivalent to wildtype cells after adjusting the MNase concentration. The strong correlations to biologically relevant annotations provide additional evidence that the position and occupancy comparisons we make based on the data are informative.We conclude that a combination of DNA-encoded nucleosome preference and chromatin composition regulate nucleosome occupancy and positional stability under conditions of limited histone protein availability. This, in turn, dictates which genes are most susceptible to a loss of regulatory fidelity. Most importantly, our data point to the factors likely to influence nucleosome stability under normal growth conditions, and to the specific genomic locations at which they are likely to act. This information serves as a platform for more detailed investigations into the mechanisms of nucleosome regulation.600 of 0.0375 in 1.25 L of fresh YPGal media  and grown for 16 hours. Cells were collected via suction filtration with a 0.2 µm filter and washed with approximately 100 mL YPD  before being resuspended in 1.25 L of YPD media. After switching the carbon source, 1 L of cells was immediately transferred to a fresh flask containing formaldehyde for our “0 hour” MNase digested time point (next section). We added 750 mL of fresh YPD to the remaining 250 mL, and the cells were grown at 30°C with shaking for 3 hours prior to collection for the final time point.Wildtype (YEF473A) and H3 shutoff (DCB200.1) cells were maintained on agar plates containing 2% galactose After collection, the cells were crosslinked with formaldehyde, the cell wall was digested with lyticase, and the DNA was digested with a titration of MNase. The resulting DNA was electrophoresed on an agarose gel, and the mono-nucleosome band was excised for sequencing. See RNA was isolated using the hot acidic phenol method Samples were prepared for either single-end  or paired-end (two H3 shutoff and two wildtype replicates) sequencing using established protocols . All libReads were aligned to the sacCer1 build of the yeast genome using Bowtie v. 0.12.6 with default settings. Single-end reads were extended to the average fragment size in each experiment, which was calculated based on the distribution of reads on the Watson and Crick strands. Paired-end reads were required to have matching ends within 100–200 bases. Reads aligning to the rDNA locus  were removed. For analysis, all replicates were normalized with regard to sequencing depth by randomly selecting 5 million aligned reads per sample.A read center density map was created for each experiment using the center point of each extended (single-end) or paired (paired-end) read. The read-center density map was Gaussian smoothed with a standard deviation (s.d.) of 10 bp and a window of 3 s.d. The overall dyad density was visualized for Nucleosome positions at 0 and 3 hours in each replicate were required to overlap by 30 bp, and the coverage in each case was required to be greater than 5 reads. The nucleosome center positions at 0 and 3 hours were subjected to a t-test, and a p-value was calculated. The occupancy was compared using the binomial distribution test on the number of read centers in the 100-bp window centered on the nucleosomes' respective centers. In both cases, the resulting p-values were Bonferroni corrected based on the total number of nucleosomes compared in that replicate. Nucleosomes for each replicate were classified as having either unchanged (p>0.2) or altered (p<0.01) position and reduced (p<0.01), unchanged (p>0.2 and <0.8), or retained (p>0.99) occupancy relative to the 0 hour position and occupancy. Nucleosomes with p-values between 0.01 and 0.2 or 0.8 and 0.99 were left unclassified  and were not used in downstream analyses. Nucleosome classification was compared between replicates, and only nucleosomes that were similarly classified in two or more replicates were used for further analyses. In addition, occupancy categories were restricted to nucleosomes that were not oppositely classified in any replicates . Nucleosomes exhibiting behavior that was dependent on histone H3 depletion were identified by comparing the wildtype and H3 shutoff strains and removing any nucleosomes that were similarly classified in the wildtype experiments.www.bioinformatics2.wsu.edu/cgi-bin/ChromatinDB/cgi/downloader_select.pl) as bulk histone occupancy normalized data: H2AK7ac, H2BK11ac, H2BK16ac, H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H4K8ac, H4K12ac and H4K16ac 600∼0.6–0.8). Rpo21, Bdf1, Rap1, Reb1, Vps72, and Srm1 data is from 600∼0.7). Nhp6a data is from 10 of the p-value of the z-score  and TopHat (v. 1.1.0) with a maximum intron size of 1 kb. Samtools (v. 0.1.8.0) was used to determine read pileups at each base in the genome. The total coverage in bases reported as transcribed RNA-seq reads from three biological replicates each of H3 shutoff and wildtype cells were mapped to the 10 p-value of the z-score is reported.The number of nucleosomes in each class that overlapped with each gene and upstream, non-transcribed region was determined. To calculate significance, a number of nucleosomes equal to those in the class were randomly chosen from all classified nucleosomes, and this subset was tested for overlap with the region. This was repeated 100 times, and the −logFigure S1GAL-H3 transcription. (A) Wildtype  and H3 shutoff  strains grow at similar rates in media containing galactose. Values reported are the cell count relative to the 0 hour time point for each strain. (B) Although the H3 shutoff cells (red) undergo DNA synthesis, they arrest in large-budded phase prior to a complete cell division in dextrose-containing media while the wildtype cells (brown) continue to divide. All counts are reported relative to the 0 hour time point for each strain. See HHT2) transcription is nearly silent compared to wildtype cells. Note that the transcription of the other histone proteins  is unaffected. Transcription of G6PDH (ZWF1 in yeast) is not repressed in the H3 shutoff strain following the shift to dextrose. All bars indicate the average reads per thousand mapped tags (RPKM) from three RNA-seq experiments. The error bars indicate the standard error. (D) H3 protein levels were reduced to ∼50% of the original level after 3 hours in dextrose. A representative digital western blot image and the quantification of three blot replicates (bar plot) are shown. G6PDH was uniform over the time course in the H3 shutoff strain . The reported H3 levels following nucleosome depletion are normalized to G6PDH at that time point prior to normalization against the 0 hour H3 level. The average of three replicates is reported along with the standard error.Transition to dextrose silences (TIF)Click here for additional data file.Figure S2600 between 0.8 and 1 in galactose media. (B) Cells were then isolated by filtration, rinsed with dextrose media, and resuspended at the original density in fresh dextrose media. A sample was removed for MNase digestion. (C) Cells were diluted 1∶4 in dextrose media and incubated at 30°C for 3 hours before being digested with MNase.  0 hour MNase digest gels for wildtype and H3 shutoff cells.  MNase digest gels for wildtype and H3 shutoff cells after 3 hours in dextrose. No clear tri-nucleosome band is seen for H3 shutoff cells, and there is increased background smearing  Cultures of either wildtype or H3 shutoff cells were initially grown to an ODsmearing , p<0.05.(TIF)Click here for additional data file.Figure S3Stringent identification of H3-depletion responsive nucleosomes. Nucleosomes were first classified in each replicate in H3 shutoff  and wildtype cells . Nucleosomes that behaved consistently in two or more replicates and met other quality-control measures see  were sel(TIF)Click here for additional data file.Figure S4PHO5 are linked to increased PHO5 expression. (A) Independent MNase-seq experiments PHO5/PBY1 divergent promoter. (B) Nucleosome positions as called in PHO5 promoter was found to be disrupted. (D–G). Normalized nucleosome occupancy for each of our four H3 shutoff replicates in YPGal  and YPD  with the nucleosome position calls made by our algorithm shown below. Our algorithm identified either two (Reps A and C) or three (reps B and D) nucleosomes between DNase hypersensitivity sites 1 and 2 . Numbering nucleosomes backwards from the PHO5 gene, the −1 and −2 nucleosomes that flank HS1 were relatively unaffected by the histone shutoff, but nucleosomes −3 through −5, which were the nucleosomes measured by the probes in Han et al. Nucleosome rearrangements upstream of (TIF)Click here for additional data file.Figure S5IDP2 transcription start site. The IDP2 gene experienced an H3-depletion dependent increase in transcription. We chose this locus as an example to illustrate our classification process. (A) Normalized wildtype nucleosome occupancy profiles generated in YPGal (black) and YPD (pink) from H3 depletion alters chromatin structure around the (TIF)Click here for additional data file.Figure S6Enrichment for factors in H3-depletion effect categories. The average value of previously published genome-wide data sets and genome annotations vs. expected (Z-score) for each of the nucleosome change categories shown in (TIF)Click here for additional data file.Figure S7−8; ** p-value<1×10−15.H3 turnover is associated with nucleosome loss. (A) Comparison of nucleosome's H3-depletion dependent occupancy change vs. the H3 turnover Z-score from (TIF)Click here for additional data file.Figure S8Isw2-bound altered position nucleosomes are centered on available DNA. (A) Schematic representation of the hypothesized nucleosome-centering function of Isw2  following histone (yellow circle) depletion.  Nucleosomes that fell within regions identified as bound by Isw2K215R in (TIF)Click here for additional data file.Figure S9Context-dependent associations of chromatin marks and remodelers. (A) Similar enrichment patterns are seen for transcription-associated factors regardless of if the nucleosome falls in an intergenic or genic region. (B) Chromatin remodelers show altered associations with H3 depletion effects in intergenic and coding regions. (C) Histone protein enrichment levels are similar regardless of whether the nucleosome falls in an intergenic or genic region. (D) The histone modification status affects outcome primarily at nucleosomes that occur in genic regions. For all sections, the number in parentheses indicates the technical resolution of the data set used for comparison.(TIF)Click here for additional data file.Figure S102 ratio of WT to Nhp6a/b deleted cells <−2 are highlighted in orange. (D) As in B with classifications of “decreased” (log2 ratio<−2), “no change” (log2 ratio >−0.5 and <0.5), and “increased” (log2 ratio >2). * p-value <0.01; ** p-value<1×10−5.Nhp6a enrichment is associated with nucleosome loss in H3-depleted cells. We compared changes in nucleosome occupancy as the result of H3 depletion (this study) or deletion of Nhp6a/b (TIF)Click here for additional data file.Figure S11in vitro reconstituted nucleosome occupancy than dextrose-grown cells. (A) In vivo nucleosome occupancy from yeast grown in galactose versus previously published in vitro nucleosome occupancy genome wide 2 values are plotted. (B) Same as (A), but for yeast grown in dextrose.Nucleosome occupancy in galactose-grown cells is more similar to (TIF)Click here for additional data file.Figure S1210 of the p-value. This relationship is shown for promoters, defined as the untranscribed region upstream of a gene, and genes, defined as the transcribed regions from Association of H3-depletion effect categories with the transcriptional response. The relationship between gene expression changes upon histone depletion (rows) and changes in nucleosome occupancy and position (columns) as in (TIF)Click here for additional data file.Table S1Enrichment of histone modifications and chromatin associated proteins by nucleosome class.(XLS)Click here for additional data file.Table S2Enrichment of histone modifications and chromatin associated proteins by nucleosome class split by genomic annotation.(XLS)Click here for additional data file.Table S3Expression changes by gene following H3 depletion.(XLS)Click here for additional data file.Text S1Additional details regarding the western blots, MNase digestions, calculations regarding MNase susceptibility, and details on single-end and paired-end library preparations.(DOCX)Click here for additional data file.