ChIP Enrichment Research Articles

Activation of estrogen-related receptor γ by calcium and cadmium

ObjectiveEstrogen-related receptor γ (ERRγ) is a metabolic regulator with no identified physiological ligands. This study investigates whether calcium is an ERRγ ligand that mediates the effects of glucagon and whether cadmium, which mimics the effects of calcium, disrupts metabolism through ERRγ.MethodHepG2, MCF-7, and HEK293T transfected with ERRγ were treated with glucagon, calcium, cadmium, ERRγ agonist, or ERRγ inhibitor. Cells were then collected for in vitro assays including real-time qPCR, Western blot, ChIP, immunofluorescence, mutational analysis, or gene set enrichment analysis. Molecular dynamics simulations were performed to study mutation sites.ResultsIn HepG2 cells, treatment with glucagon, calcium, or cadmium re-localized ERRγ to the cell nucleus, recruited ERRγ to estrogen-related response elements, induced the expression of ERRγ-regulated genes, and increased extracellular glucose that was blocked by an ERRγ antagonist. In MCF-7 cells and HEK293T cells transfected with ERRγ, similar treatments induced the expression of metabolic genes. Mutational analysis identified S303, T429, and E452 in the ligand-binding domain as potential interaction sites. Molecular dynamics simulations showed that calcium induced changes in ERRγ similar to ERRγ agonist.ConclusionThe results suggest that calcium is a potential ligand of ERRγ that mediates the effects of glucagon and cadmium disrupts metabolism through ERRγ.

Systematic transcriptome profiling of hPSC-derived osteoblasts unveils CORIN's mastery in governing osteogenesis through CEBPD modulation

The commitment of stem cells to differentiate into osteoblasts is a highly regulated and complex process that involves the coordination of extrinsic signals and intrinsic transcriptional machinery. While rodent osteoblastic differentiation has been extensively studied, research on human osteogenesis has been limited by cell sources and existing models. Here, we systematically dissect hPSC-derived osteoblasts to identify functional membrane proteins and their downstream transcriptional networks involved in human osteogenesis. Our results reveal an enrichment of type II transmembrane serine protease CORIN in humans but not rodent osteoblasts. Functional analyses demonstrated that CORIN depletion significantly impairs osteogenesis. Genome-wide ChIP enrichment and mechanistic studies show that p38 MAPK-mediated CEBPD upregulation is required for CORIN-modulated osteogenesis. Contrastingly, the type I transmembrane heparan sulfate proteoglycan SDC1 enriched in MSCs exerts a negative regulatory effect on osteogenesis through a similar mechanism. ChIP-seq, bulk and single-cell transcriptomes, and functional validations indicated that CEBPD plays a critical role in controlling osteogenesis. In summary, our findings uncover previously unrecognized CORIN-mediated CEBPD transcriptomic networks in driving human osteoblast lineage commitment.

Advanced stage, high-grade primary tumor ovarian cancer: a multi-omics dissection and biomarker prediction process

Ovarian cancer (OC) incidence and mortality rates continue to escalate globally. Early detection of OC is challenging due to extensive metastases and the ambiguity of biomarkers in advanced High-Grade Primary Tumors (HGPTs). In the present study, we conducted an in-depth in silico analysis in OC cell lines using the Gene Expression Omnibus (GEO) microarray dataset with 53 HGPT and 10 normal samples. Differentially-Expressed Genes (DEGs) were also identified by GEO2r. A variety of analyses, including gene set enrichment analysis (GSEA), ChIP enrichment analysis (ChEA), eXpression2Kinases (X2K) and Human Protein Atlas (HPA), elucidated signaling pathways, transcription factors (TFs), kinases, and proteome, respectively. Protein–Protein Interaction (PPI) networks were generated using STRING and Cytoscape, in which co-expression and hub genes were pinpointed by the cytoHubba plug-in. Validity of DEG analysis was achieved via Gene Expression Profiling Interactive Analysis (GEPIA). Of note, KIAA0101, RAD51AP1, FAM83D, CEP55, PRC1, CKS2, CDCA5, NUSAP1, ECT2, and TRIP13 were found as top 10 hub genes; SIN3A, VDR, TCF7L2, NFYA, and FOXM1 were detected as predominant TFs in HGPTs; CEP55, PRC1, CKS2, CDCA5, and NUSAP1 were identified as potential biomarkers from hub gene clustering. Further analysis indicated hsa-miR-215-5p, hsa-miR-193b-3p, and hsa-miR-192-5p as key miRNAs targeting HGPT genes. Collectively, our findings spotlighted HGPT-associated genes, TFs, miRNAs, and pathways as prospective biomarkers, offering new avenues for OC diagnostic and therapeutic approaches.

Study on three-dimensional dielectrophoresis microfluidic chip for separation and enrichment of circulating tumor cells

BackgroundCirculating tumor cells (CTCs) which means tumor cells shed into the peripheral blood of humans, are one of the important indicators in the early and accurate detection of malignancy. ObjectiveThis paper is based on the principle of dielectrophoresis, the design and performance research of microfluidic microarray separating and enriching CTCs was carried out, and the separation and enriching of CTCs was realized by ultilizing the difference in dielectrophoretic force and the movement trajectories between CTCs and leukocytes. ResultsChip structure design and optimization based on the COMSOL software simulation tool, through the separation experiment of human breast cancer cell MCF-7 and white blood cells, 60 kHz was selected as the frequency of cell separation experiment. Taking human liver cancer cell SMMC-7721 and human leukocyte mixture as the research object, the chip separation and enrichment experiment of CTCs was conducted. At 5 V voltage and 60 kHz frequency, the maximum separation flux of three-dimensional dielectrophores is microfluidic chip for human liver cancer cell SMMC-7721 reached 1.1 mL/h, and the separation efficiency was about 94%. ConclusionThe results of this research have important implications for separating, sorting and detecting CTCs.

Epigenetic Repression of RUNX2 and OSX Promoters Controls the Nonmineralized State of the Periodontal Ligament.

The nonmineralized state of the mammalian periodontal ligament is one of the hallmarks of vertebrate evolution as it provides resilient and nontraumatic tooth anchorage for effective predation. Here we sought to determine how the chromatin state of key mineralization gene promoters contributes to the nonmineralized periodontal ligament in the midst of fully mineralized alveolar bone and cementum anchor tissues. In developing mouse periodontal tissues, RUNX2 was localized to alveolar bone-lining cells, while OSX was localized throughout the periodontal ligament's soft tissue. Matching RT-PCR amplification data and western blot comparisons demonstrated that the expression of RUNX2 and OSX bone mineralization transcription factors was at least 2.5-fold elevated in alveolar bone osteoblasts versus periodontal ligament fibroblasts. ChIP enrichment data along the RUNX2 and OSX promoters revealed increased H3K4me3 marks in alveolar bone osteoblasts, while H3K9me3 and H3K27me3 marks were elevated in periodontal ligament fibroblasts. In support of an epigenetic mechanism responsible for the inhibition of mineralization gene expression in periodontal progenitors, histone methylation inhibitors DZNep and Chaetocin reactivated RUNX2 and OSX expression in periodontal progenitors and increased alkaline phosphatase and Alizarin Red, while the in vivo application of DZNep in rat maxillae resulted in aberrant mineralization in the periodontal ligament and a narrowing of the nonmineralized periodontal space. Together, these studies demonstrate that the nonmineralized state of the mammalian periodontal ligament is controlled by an epigenetic regulation of the RUNX2 and OSX key mineralization gene promoters.

A Rapid Detection Method for Tomato Gray Mold Spores in Greenhouse Based on Microfluidic Chip Enrichment and Lens-Less Diffraction Image Processing.

It is of great significance to find tomato gray mold in time and take corresponding control measures to ensure the production of tomato crops. This study proposed a rapid detection method for spores of Botrytis cinerea in green-house based on microfluidic chip enrichment and lens-free diffraction image processing. Microfluidic chip with a regular triangular inner rib structure was designed to achieve the enrichment of Botrytis cinerea spores. In order to obtain the diffraction image of the diseased spores, a lens-less diffraction imaging system was built. Furthermore, the collected spore diffraction images were processed and counted. The simulation results showed that the collection efficiency of 16 μm particles was 79%, 100%, and 89% at the inlet flow rate of 12, 14 and 16 mL/min, respectively. The experimental verification results were observed under a microscope. The results showed that when the flow rate of the microfluidic chip was 12, 14 and 16 mL/min, the collection efficiency of Botrytis cinerea spores was 70.65%, 87.52% and 77.96%, respectively. The Botrytis cinerea spores collected in the experiment were placed under a microscope for manual counting and compared with the automatic counting results based on diffraction image processing. A total of 10 sets of experiments were carried out, with an error range of the experiment was 5.13~8.57%, and the average error of the experiment was 6.42%. The Bland–Altman method was used to analyze two methods based on diffraction image processing and manual counting under a microscope. All points are within the 95% consistency interval. Therefore, this study can provide a basis for the research on the real-time monitoring technology of tomato gray mold spores in the greenhouse.

MED1 mediator subunit is a key regulator of hepatic autophagy and lipid metabolism

ABSTRACT Hepatic macroautophagy/autophagy and fatty acid metabolism are transcriptionally regulated by nuclear receptors (NRs); however, it is not known whether their transcriptional co-activators are involved in autophagy. We thus examined MED1 (mediator complex subunit 1), a key component of the Mediator Complex that directly interacts with NRs, on these processes. We found that MED1 knockdown (KD) in cultured hepatic cells decreased autophagy and mitochondrial activity that was accompanied by decreased transcription of genes involved in these processes. Lipophagy and fatty acid β-oxidation also were impaired. These effects also occurred after thyroid hormone stimulation, nutrient-replete or -deplete conditions, and in liver-specific Med1 KD (Med1 LKD) mice under fed and fasting conditions. Together, these findings showed that Med1 played a key role in hepatic autophagy, mitochondria function, and lipid metabolism under these conditions. Additionally, we identified downregulated hepatic genes in Med1 LKD mice, and subjected them to ChIP Enrichment Analysis. Our findings showed that the transcriptional activity of several NRs and transcription factors (TFs), including PPARA and FOXO1, likely were affected by Med1 LKD. Finally, Med1 expression and autophagy also were decreased in two mouse models of nonalcoholic fatty liver disease (NAFLD) suggesting that decreased Med1 may contribute to hepatosteatosis. In summary, MED1 plays an essential role in regulating hepatic autophagy and lipid oxidation during different hormonal and nutrient conditions. Thus, MED1 may serve as an integrator of multiple transcriptional pathways involved in these metabolic processes. Abbreviations: BAF: bafilomycin A1; db/db mice; Lepr db/db mice; ECAR: extracellular acidification rate; KD: knockdown; MED1: mediator complex subunit 1; NAFLD: nonalcoholic fatty liver disease; OCR: oxygen consumption rate; PPARA/PPARα: peroxisomal proliferator activated receptor alpha; TF: transcription factor; TFEB: transcription factor EB; tf-LC3: tandem fluorescence RFP-GFP-LC3; TG: triglyceride; TH: Thyroid hormone; TR: thyroid hormone receptors; V-ATPase: vacuolar-type H+-ATPase; WDF: Western diet with 15% fructose in drinking water

Abstract 767: Comparison of different methods for the detection of clusters of circulating tumor cells

Abstract BACKGROUND: In the last few years, there has been an increase in research interest and number of studies investigating clusters of circulating tumor cells (CTC clusters) due to their putative higher metastatic potential compared to individual CTCs. Although the majority of studies suggest a link between CTC clusters and worse clinical outcome, their clinical significance and biological role is still not fully demonstrated. A hurdle to this aim is the heterogeneity of the data produced using various technologies and detection strategies. Here, we compare three of the most used approaches to detect CTC clusters in clinical samples. METHODS: Blood samples (30 ml) were collected from patients with metastatic breast cancer, divided in 3 aliquots and processed in parallel with 3 approaches for CTC cluster enrichment and detection: 1. PAR: Microfluidic chip enrichment (Parsortix®), staining for CD45 and CK (CellSearch CTC kit), detection by fluorescent microscope analysis 2. FIL: Enrichment by filtration (CellSieve™), staining for CD45, CK and CD31, detection by fluorescent microscope 3. CS: CellSearch™ platform for enrichment (EPCAM expression), staining (CD45 and CK) and enumeration. RESULTS: Blood samples (n=6) were collected from 6 patients with metastatic breast cancer. CTC clusters were defined as groups of ≥2 cells expressing CK and lacking CD45, accompanied or not by leukocytes (CD45+/CK-). The counts of CTC clusters for each sample/approach were compared. By FIL, CTC clusters were detected in all samples, with some clusters formed by >20 CTCs (not observed using PAR and CS). PAR and CS had similar recovery rates for CK+ clusters, but in all the samples processed with PAR, clusters formed by CK-/CD45- cells (possibly mesenchymal CTC clusters) were observed. This type of cluster, being CK-, is not detectable by CS identification criteria. FIL also detected CK- clusters, but it was difficult to distinguish between real clusters and artifacts, due to the high number of contaminating cells and to the fluorescent background given by the filtration membrane. By using PAR, instead, contaminating cells were less and it was possible to better evaluate the cell morphology. Moreover, PAR is a more flexible methodology, allowing downstream applications not feasible with FIL and CS (RNA analysis and cell culture). CONCLUSIONS: By FIL it is possible to detect CK+ CTC clusters also in samples that would be otherwise considered negative by CS and PAR analysis. Moreover, we could detect clusters formed by CK-/CD45- cells that were undetectable with CS based on the lack of epithelial markers expression. The significance of these clusters is not clear yet and should be further studied. Therefore, in order to completely understand the role of CTC clusters in disease progression, it is instrumental to use technologies able to detect all types of clusters, whose analysis will potentially reveal new features of cluster-mediated dissemination. Citation Format: Carolina Reduzzi, Youbin Zhang, Maria Grazia Daidone, Vera Cappelletti, Massimo Cristofanilli. Comparison of different methods for the detection of clusters of circulating tumor cells [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 767.

ASY1 acts as a dosage-dependent antagonist of telomere-led recombination and mediates crossover interference in Arabidopsis

During meiosis, interhomolog recombination produces crossovers and noncrossovers to create genetic diversity. Meiotic recombination frequency varies at multiple scales, with high subtelomeric recombination and suppressed centromeric recombination typical in many eukaryotes. During recombination, sister chromatids are tethered as loops to a polymerized chromosome axis, which, in plants, includes the ASY1 HORMA domain protein and REC8-cohesin complexes. Using chromatin immunoprecipitation, we show an ascending telomere-to-centromere gradient of ASY1 enrichment, which correlates strongly with REC8-cohesin ChIP-seq data. We mapped crossovers genome-wide in the absence of ASY1 and observe that telomere-led recombination becomes dominant. Surprisingly, asy1/+ heterozygotes also remodel crossovers toward subtelomeric regions at the expense of the pericentromeres. Telomeric recombination increases in asy1/+ occur in distal regions where ASY1 and REC8 ChIP enrichment are lowest in wild type. In wild type, the majority of crossovers show interference, meaning that they are more widely spaced along the chromosomes than expected by chance. To measure interference, we analyzed double crossover distances, MLH1 foci, and fluorescent pollen tetrads. Interestingly, while crossover interference is normal in asy1/+, it is undetectable in asy1 mutants, indicating that ASY1 is required to mediate crossover interference. Together, this is consistent with ASY1 antagonizing telomere-led recombination and promoting spaced crossover formation along the chromosomes via interference. These findings provide insight into the role of the meiotic axis in patterning recombination frequency within plant genomes.

Celecoxib Inhibits Hepatocellular Carcinoma Cell Growth and Migration by Targeting PNO1.

BackgroundCelecoxib has shown anti-tumor activities against several types of cancer. Although the majority of research focuses on its mechanism via cyclooxygenase-2 (COX-2) enzyme inhibition, we identified a distinct mechanism behind celecoxib anti-cancer abilities.Material/MethodsWe treated hepatocellular carcinoma (HCC) Huh-7 cells and tumor xenograft mice models with celecoxib to test its effects on the tumor. Using gene chip method to identify the differential expressed genes after celecoxib treatment and using pathway enrichment analysis to predict the potential pathways for further study. We transfected cells with lentiviral shRNA to detect the effect of RNA binding gene partner of NOB1 (PNO1) on tumor growth in vitro and in vivo. Further we performed western blot to detect the effect of PNO1 on the protein kinase B (AKT) pathway.ResultsCelecoxib inhibited HCC cell growth in vitro and in vivo, and gene chip and pathway enrichment analysis revealed that PNO1 may be the potential target of celecoxib in HCC cells. Celecoxib significantly reduced levels of PNO1 in tumor tissue. Knockdown of PNO1 remarkably suppressed tumor growth and metastasis in vitro and in vivo. Disruption of PNO1 expression significantly reduced protein kinase B (AKT)/rapamycin (mTOR) signaling, indicating that this pathway may be involved in PNO1-mediated tumorigenic activity.ConclusionsCelecoxib may exert its anti-tumor activity by inhibiting PNO1, and that AKT/mTOR signaling helps mediate the oncogenic effects of PNO1. This work offers the first evidence for a role of PNO1 as an HCC oncogene, which may open new avenues for prevention and treatment of HCC.

MiR-146a relieves kidney injury in mice with systemic lupus erythematosus through regulating NF-κB pathway.

To explore the effect of micro ribonucleic acid (miRNA)-146a on kidney injury in mice with systemic lupus erythematosus (SLE), and to investigate its possible mechanism. A total of 45 female MRL/lpr mice were randomly divided into control group, miR-146a mimic group and miR-146a inhibitor group. Urine protein level was measured every 2 weeks. Meanwhile, the levels of serum anti-dsdeoxyribonucleic acid (anti-dsDNA), anti-ssDNA, antinuclear antibody (ANA) and anti-chromatin were measured using enzyme-linked immunosorbent assay (ELISA). At 2 weeks after drug treatment, the effects of miR-146a mimic and inhibitor on kidney tissues of MRL/lpr mice were detected and analyzed by gene chip and gene set enrichment analysis, respectively. The mice were executed at the age of 24 weeks, and the blood samples were collected. Subsequently, the level of blood urea nitrogen (BUN) was measured using the BUN analyzer. After that, kidney tissues were taken, and the effect of drug treatment on the morphology of kidney tissues was detected via hematoxylin-eosin (HE) staining. Moreover, the effects of drug treatment on the mRNA levels of inflammatory factors and the nuclear factor-κB (NF-κB) signaling pathway in kidney tissues were detected via quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting, respectively. MiR-146a mimic significantly reduced urine protein in a time-dependent manner, which also significantly reduced BUN level at 24 weeks. The results of HE staining showed that both glomerular injury and renal vascular injury in miR-146a mimic group were significantly alleviated. In miR-146a mimic group, serum autoantibodies of anti-dsDNA, anti-ssDNA, anti-chromatin and ANA decreased significantly. However, the survival time of mice was significantly prolonged. High-throughput gene expression chip technique elucidated that in miR-146a mimic group, the expression of positive regulatory gene of NF-κB showed a decreasing trend. However, the expression of negative regulatory gene of NF-κB showed an increasing trend. MiR-146a mimic remarkably down-regulated the expression levels of RELA, IRAK1, interleukin-1B (IL1B) and IL-10 in kidney tissues. Furthermore, the results of Western blotting showed that miR-146a mimic inhibited both the classical and non-classical NF-κB signaling pathways. MiR-146a reduces SLE-induced kidney injury in MRL/lpr mice through regulating classical and non-classical NF-κB signaling pathways.

Portable Rice Disease Spores Capture and Detection Method Using Diffraction Fingerprints on Microfluidic Chip.

Crop diseases cause great harm to food security, 90% of these are caused by fungal spores. This paper proposes a crop diseases spore detection method, based on the lensfree diffraction fingerprint and microfluidic chip. The spore diffraction images are obtained by a designed large field of view lensless diffraction detection platform which contains the spore enrichment microfluidic chip and lensless imaging module. By using the microfluidic chip to enrich and isolate spores in advance, the required particles can be captured in the chip enrichment area, and other impurities can be filtered to reduce the interference of impurities on spore detection. The light source emits partially coherent light and irradiates the target to generate diffraction fingerprints, which can be used to distinguish spores and impurities. According to the theoretical analysis, two parameters, Peak to Center ratio (PCR) and Peak to Valley ratio (PVR), are found to quantify these spores. The correlation coefficient between the detection results of rice blast spores by the constructed device and the results of microscopic artificial identification was up to 0.99, and the average error rate of the proposed device was only 5.91%. The size of the device is only 4 cm × 4 cm × 5 cm, and the cost is less than $150, which is one thousandth of the existing equipment. Therefore, it may be widely used as an early detection method for crop disease caused by spores.

Identifying hub genes and potential mechanisms associated with senescence in human annulus cells by gene expression profiling and bioinformatics analysis.

The aim of the present study was to reveal the potential hub genes and regulatory mechanisms associated with senescence in human annulus cells by analyzing microarray data using bioinformatics. The gene expression dataset GSE17077, of senescent and non-senescent annulus cells obtained from patients with disc degenerative diseases (DDD), was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified. Functional and pathway annotations were performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes terms, respectively. Web-based Gene Set Analysis Toolkit and Chip Enrichment Analysis were used to identify key transcription factors (TFs). A protein-protein interaction (PPI) network was constructed to analyze the hub genes associated with senescence in DDD. A total of 667 DEGs were screened, including 368 up- and 299 down-regulated genes. These DEGs were enriched in phosphorylation, regulation of apoptosis and regulation of programmed cell death. In addition, DEGs were involved in axon guidance, natural killer cell-mediated cytotoxicity, purine metabolism and the mitogen-activated protein kinase (MAPK) signaling pathway. The TFs activator protein 1 (AP1), specificity protein 1 and aryl hydrocarbon receptor may serve regulatory roles in gene expression in senescent cells. Certain key target genes of TFs, including heat shock protein 90 (HSP90) and C-X-C motif chemokine 5 (CXCL5), within the DEGs were revealed to have a high connectivity degree by PPI analysis. The results of the present study indicated that the MAPK-regulated AP1 pathway may contribute to senescence-associated disc degeneration. The DEGs, including HSP90 and CXCL5, with a high degree of connectivity may be potential targets for future investigations into molecular biomarkers.

Denoising genome-wide histone ChIP-seq with convolutional neural networks.

MotivationChromatin immune-precipitation sequencing (ChIP-seq) experiments are commonly used to obtain genome-wide profiles of histone modifications associated with different types of functional genomic elements. However, the quality of histone ChIP-seq data is affected by many experimental parameters such as the amount of input DNA, antibody specificity, ChIP enrichment and sequencing depth. Making accurate inferences from chromatin profiling experiments that involve diverse experimental parameters is challenging.ResultsWe introduce a convolutional denoising algorithm, Coda, that uses convolutional neural networks to learn a mapping from suboptimal to high-quality histone ChIP-seq data. This overcomes various sources of noise and variability, substantially enhancing and recovering signal when applied to low-quality chromatin profiling datasets across individuals, cell types and species. Our method has the potential to improve data quality at reduced costs. More broadly, this approach—using a high-dimensional discriminative model to encode a generative noise process—is generally applicable to other biological domains where it is easy to generate noisy data but difficult to analytically characterize the noise or underlying data distribution.Availability and implementation https://github.com/kundajelab/coda.

In silico analysis of the molecular mechanism of postmenopausal osteoporosis.

Postmenopausal osteoporosis (PO) is a common disease in females >50 years of age worldwide and is becoming an increasing burden to society. The present study aimed to assess the molecular mechanism of PO using bioinformatic methods. The gene expression data from patients with PO and normal controls were downloaded from the ArrayExpress database provided by European Bioinformatics Institute. Following the screening of the differentially expressed genes (DEGs) using the Limma package in R language, Kyoto Encyclopedia of Genes and Genomes pathways enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery online tools. Sequentially, modulators of the DEGs, including transcription factors (TFs) and microRNAs, were predicted by the ChIP Enrichment Analysis databases and WEB-based GEne SeT AnaLysis Toolkit system, respectively. In addition, the protein-protein interaction network of DEGs was constructed via the search tool for the retrieval of interacting genes and then the functional modules were further analyzed via the cluster-Maker package and The Biological Networks Gene Ontology package within the Cytoscape software. A total of 482 DEGs, including 279 upregulated and 203 downregulated DEGs, were screened out. DEGs were predominantly enriched in the pathways of fatty acid metabolism, cardiac muscle contraction and DNA replication. TFs, including SMAD4, in addition to microRNAs, including the microRNA-125 (miR-125) family, miR-331 and miR-24, may be the modulators of the DEGs in PO. In addition, the five largest modules were identified with TTN, L1G1, ACADM, UQCRC2 and TRIM63 as the hub proteins, and they were associated with the biological processes of muscle contraction, DNA replication initiation, lipid modification, generation of precursor metabolites and energy, and regulation of acetyl-CoA biosynthetic process, respectively. SMAD4, CACNG1 and TRIM63 are suggested to be important factors in the molecular mechanisms of PO, and miR-331 may be novel potential biomarker for PO.

An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding

Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPS's multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with pre-existing genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.

Model-Free Inference for ChIP-Seq Data

Due to its higher resolution mapping and stronger ChIP enrichment signals, ChIP-seq tends to replace ChIP-chip technology in studying genome-wide protein-DNA interactions, while the massive digital ChIP-seq data present new challenges to statisticians. To date, most methods proposed in the literature for ChIP-seq data analysis are model based, however, finding a single model workable for all datasets is impossible, given the complexity of biological systems and variations generated in the sequencing process. In this paper, we present a model-free approach, the so-called MICS (Model-free Inference for ChIP-Seq), for ChIP-seq data analysis. MICS has a few advantages over the existing methods: Firstly, MICS avoids assumptions for the data distribution, and thus it maintains high power even when model assumptions for the data are violated. Secondly, MICS employs a simulation-based method in estimating the false discovery rate. Since the simulation-based method works independently of ChIP samples, MICS can perform robustly to variety of ChIP samples; it can produce accurate identification of peak regions, even for those where the enrichment is weak. Thirdly, MICS is very efficient in computation, which takes only a few seconds on a personal computer for a reasonably large dataset. In this paper, we also present a simple semi-empirical method for simulating ChIP-seq data, which allows a better assessment of performance of different approaches for ChIP-seq data analysis. MICS is compared with several existing methods, including MACS, CCAT, PICS, BayesPeak and QuEST, based on real and simulated datasets. The numerical results indicate that MICS can outperform others. Availability: An R package called MICS is available at http://www.stat.tamu.edu/~mqwu.

Highly expressed loci are vulnerable to misleading ChIP localization of multiple unrelated proteins

Chromatin immunoprecipitation (ChIP) is the gold-standard technique for localizing nuclear proteins in the genome. We used ChIP, in combination with deep sequencing (Seq), to study the genome-wide distribution of the Silent information regulator (Sir) complex in Saccharomyces cerevisiae. We analyzed ChIP-Seq peaks of the Sir2, Sir3, and Sir4 silencing proteins and discovered 238 unexpected euchromatic loci that exhibited enrichment of all three. Surprisingly, published ChIP-Seq datasets for the Ste12 transcription factor and the centromeric Cse4 protein indicated that these proteins were also enriched in the same euchromatic regions with the high Sir protein levels. The 238 loci, termed "hyper-ChIPable", were in highly expressed regions with strong polymerase II and polymerase III enrichment signals, and the correlation between transcription level and ChIP enrichment was not limited to these 238 loci but extended genome-wide. The apparent enrichment of various proteins at hyper-ChIPable loci was not a consequence of artifacts associated with deep sequencing methods, as confirmed by ChIP-quantitative PCR. The localization of unrelated proteins, including the entire silencing complex, to the most highly transcribed genes was highly suggestive of a technical issue with the immunoprecipitations. ChIP-Seq on chromatin immunoprecipitated with a nuclear-localized GFP reproduced the above enrichment in an expression-dependent manner: induction of the GAL genes resulted in an increased ChIP signal of the GFP protein at these loci, with presumably no biological relevance. Whereas ChIP is a broadly valuable technique, some published conclusions based upon ChIP procedures may merit reevaluation in light of these findings.

DiffReps: Detecting Differential Chromatin Modification Sites from ChIP-seq Data with Biological Replicates

ChIP-seq is increasingly being used for genome-wide profiling of histone modification marks. It is of particular importance to compare ChIP-seq data of two different conditions, such as disease vs. control, and identify regions that show differences in ChIP enrichment. We have developed a powerful and easy to use program, called diffReps, to detect those differential sites from ChIP-seq data, with or without biological replicates. In addition, we have developed two useful tools for ChIP-seq analysis in the diffReps package: one for the annotation of the differential sites and the other for finding chromatin modification “hotspots”. diffReps is developed in PERL programming language and runs on all platforms as a command line script. We tested diffReps on two different datasets. One is the comparison of H3K4me3 between two human cell lines from the ENCODE project. The other is the comparison of H3K9me3 in a discrete region of mouse brain between cocaine- and saline-treated conditions. The results indicated that diffReps is a highly sensitive program in detecting differential sites from ChIP-seq data.

A statistical framework for power calculations in ChIP-seq experiments.

ChIP-seq technology enables investigators to study genome-wide binding of transcription factors and mapping of epigenomic marks. Although the availability of basic analysis tools for ChIP-seq data is rapidly increasing, there has not been much progress on the related design issues. A challenging question for designing a ChIP-seq experiment is how deeply should the ChIP and the control samples be sequenced? The answer depends on multiple factors some of which can be set by the experimenter based on pilot/preliminary data. The sequencing depth of a ChIP-seq experiment is one of the key factors that determine whether all the underlying targets (e.g. binding locations or epigenomic profiles) can be identified with a targeted power. We developed a statistical framework named CSSP (ChIP-seq Statistical Power) for power calculations in ChIP-seq experiments by considering a local Poisson model, which is commonly adopted by many peak callers. Evaluations with simulations and data-driven computational experiments demonstrate that this framework can reliably estimate the power of a ChIP-seq experiment at different sequencing depths based on pilot data. Furthermore, it provides an analytical approach for calculating the required depth for a targeted power while controlling the false discovery rate at a user-specified level. Hence, our results enable researchers to use their own or publicly available data for determining required sequencing depths of their ChIP-seq experiments and potentially make better use of the multiplexing functionality of the sequencers. Evaluation of power for multiple public ChIP-seq datasets indicate that, currently, typical ChIP-seq studies are powered well for detecting large fold changes of ChIP enrichment over the control sample, but they have considerably less power for detecting smaller fold changes. Available at www.stat.wisc.edu/~zuo/CSSP. keles@stat.wisc.edu Supplementary data are available at Bioinformatics online.