ChIP-seq Analysis in R (CSAR): An R package for the statistical detection of protein-bound genomic regions

<p>Abstract</p> <p>Background</p> <p><it>In vivo </it>detection of protein-bound genomic regions can be achieved by combining chromatin-immunoprecipitation with next-generation sequencing technology (ChIP-seq). The large amount of sequence data produced by this method needs to be analyzed in a statistically proper and computationally efficient manner. The generation of high copy numbers of DNA fragments as an artifact of the PCR step in ChIP-seq is an important source of bias of this methodology.</p> <p>Results</p> <p>We present here an R package for the statistical analysis of ChIP-seq experiments. Taking the average size of DNA fragments subjected to sequencing into account, the software calculates single-nucleotide read-enrichment values. After normalization, sample and control are compared using a test based on the ratio test or the Poisson distribution. Test statistic thresholds to control the false discovery rate are obtained through random permutations. Computational efficiency is achieved by implementing the most time-consuming functions in C++ and integrating these in the R package. An analysis of simulated and experimental ChIP-seq data is presented to demonstrate the robustness of our method against PCR-artefacts and its adequate control of the error rate.</p> <p>Conclusions</p> <p>The software <it>ChIP-seq Analysis in R </it>(CSAR) enables fast and accurate detection of protein-bound genomic regions through the analysis of ChIP-seq experiments. Compared to existing methods, we found that our package shows greater robustness against PCR-artefacts and better control of the error rate.</p

PRI-CAT: a web-tool for the analysis, storage and visualization of plant ChIP-seq experiments

Although several tools for the analysis of ChIP-seq data have been published recently, there is a growing demand, in particular in the plant research community, for computational resources with which such data can be processed, analyzed, stored, visualized and integrated within a single, user-friendly environment. To accommodate this demand, we have developed PRI-CAT (Plant Research International ChIP-seq analysis tool), a web-based workflow tool for the management and analysis of ChIP-seq experiments. PRI-CAT is currently focused on Arabidopsis, but will be extended with other plant species in the near future. Users can directly submit their sequencing data to PRI-CAT for automated analysis. A QuickLoad server compatible with genome browsers is implemented for the storage and visualization of DNA-binding maps. Submitted datasets and results can be made publicly available through PRI-CAT, a feature that will enable community-based integrative analysis and visualization of ChIP-seq experiments. Secondary analysis of data can be performed with the aid of GALAXY, an external framework for tool and data integration. PRI-CAT is freely available at http://www.ab.wur.nl/pricat. No login is required

Orchestration of Floral Initiation by APETALA1

The MADS-domain transcription factor APETALA1 (AP1) is a key regulator of Arabidopsis flower development. To understand the molecular mechanisms underlying AP1 function, we identified its target genes during floral initiation using a combination of gene expression profiling and genome-wide binding studies. Many of its targets encode transcriptional regulators, including known floral repressors. The latter genes are down-regulated by AP1, suggesting that it initiates floral development by abrogating the inhibitory effects of these genes. Although AP1 acts predominantly as a transcriptional repressor during the earliest stages of flower development, at more advanced stages it also activates regulatory genes required for floral organ formation, indicating a dynamic mode of action. Our results further imply that AP1 orchestrates floral initiation by integrating growth, patterning, and hormonal pathways

Balancing of Histone H3K4 Methylation States by the Kdm5c/SMCX Histone Demethylase Modulates Promoter and Enhancer Function

SummaryThe functional organization of eukaryotic genomes correlates with specific patterns of histone methylations. Regulatory regions in genomes such as enhancers and promoters differ in their extent of methylation of histone H3 at lysine-4 (H3K4), but it is largely unknown how the different methylation states are specified and controlled. Here, we show that the Kdm5c/Jarid1c/SMCX member of the Kdm5 family of H3K4 demethylases can be recruited to both enhancer and promoter elements in mouse embryonic stem cells and in neuronal progenitor cells. Knockdown of Kdm5c deregulates transcription via local increases in H3K4me3. Our data indicate that by restricting H3K4me3 modification at core promoters, Kdm5c dampens transcription, but at enhancers Kdm5c stimulates their activity. Remarkably, an impaired enhancer function activates the intrinsic promoter activity of Kdm5c-bound distal elements. Our results demonstrate that the Kdm5c demethylase plays a crucial and dynamic role in the functional discrimination between enhancers and core promoters

Dynamics of chromatin accessibility and gene regulation by MADS-domain transcription factors in flower development.

BACKGROUND: Development of eukaryotic organisms is controlled by transcription factors that trigger specific and global changes in gene expression programs. In plants, MADS-domain transcription factors act as master regulators of developmental switches and organ specification. However, the mechanisms by which these factors dynamically regulate the expression of their target genes at different developmental stages are still poorly understood. RESULTS: We characterized the relationship of chromatin accessibility, gene expression, and DNA binding of two MADS-domain proteins at different stages of Arabidopsis flower development. Dynamic changes in APETALA1 and SEPALLATA3 DNA binding correlated with changes in gene expression, and many of the target genes could be associated with the developmental stage in which they are transcriptionally controlled. We also observe dynamic changes in chromatin accessibility during flower development. Remarkably, DNA binding of APETALA1 and SEPALLATA3 is largely independent of the accessibility status of their binding regions and it can precede increases in DNA accessibility. These results suggest that APETALA1 and SEPALLATA3 may modulate chromatin accessibility, thereby facilitating access of other transcriptional regulators to their target genes. CONCLUSIONS: Our findings indicate that different homeotic factors regulate partly overlapping, yet also distinctive sets of target genes in a partly stage-specific fashion. By combining the information from DNA-binding and gene expression data, we are able to propose models of stage-specific regulatory interactions, thereby addressing dynamics of regulatory networks throughout flower development. Furthermore, MADS-domain TFs may regulate gene expression by alternative strategies, one of which is modulation of chromatin accessibility

FRUITFULL controls SAUR10 expression and regulates Arabidopsis growth and architecture

[EN] MADS-domain transcription factors are well known for their roles in plant development and regulate sets of downstream genes that have been uncovered by high-throughput analyses. A considerable number of these targets are predicted to function in hormone responses or responses to environmental stimuli, suggesting that there is a close link between developmental and environmental regulators of plant growth and development. Here, we show that the Arabidopsis MADS-domain factor FRUITFULL (FUL) executes several functions in addition to its noted role in fruit development. Among the direct targets of FUL, we identified SMALL AUXIN UPREGULATED RNA 10 (SAUR10), a growth regulator that is highly induced by a combination of auxin and brassinosteroids and in response to reduced R:FR light. Interestingly, we discovered that SAUR10 is repressed by FUL in stems and inflorescence branches. SAUR10 is specifically expressed at the abaxial side of these branches and this localized activity is influenced by hormones, light conditions and by FUL, which has an effect on branch angle. Furthermore, we identified a number of other genes involved in hormone pathways and light signalling as direct targets of FUL in the stem, demonstrating a connection between developmentally and environmentally regulated growth programs.We thank Arjo Meijering for assistance with the light measurements, Niek Stortenbeker for contributions to the manuscript, and Ueli Grossniklaus (University of Zurich) for financial and technical support. MB was supported by the Dutch Organization for Scientific research (NWO) in the framework of the ERA-NET on Plant Genomics (ERA-PG) program project CISCODE and by an NWO Veni-grant. In part, this work was performed in Ueli Grossniklaus' laboratory at the University of Zurich with support through an EMBO LT Fellowship to MB and a grant from the Swiss National Science Foundation to Ueli Grossniklaus. HM was supported by an NWO Vidi-grant, granted to KK.Bemer, M.; Van Mourik, H.; Muiño, JM.; Ferrandiz Maestre, C.; Kaufmann, K.; Angenent, G. (2017). FRUITFULL controls SAUR10 expression and regulates Arabidopsis growth and architecture. Journal of Experimental Botany. 68(13):3391-3403. https://doi.org/10.1093/jxb/erx184S33913403681

A Multitrait Genetic Study of Hemostatic Factors and Hemorrhagic Transformation after Stroke Treatment

BACKGROUND: Thrombolytic recombinant tissue plasminogen activator (r-tPA) treatment is the only pharmacologic intervention available in the ischemic stroke acute phase. This treatment is associated with an increased risk of intracerebral hemorrhages, known as hemorrhagic transformations (HTs), which worsen the patient\u27s prognosis. OBJECTIVES: to investigate the association between genetically determined natural hemostatic factors\u27 levels and increased risk of HT after r-tPA treatment. METHODS: Using data from genome-wide association studies on the risk of HT after r-tPA treatment and data on 7 hemostatic factors (factor [F]VII, FVIII, von Willebrand factor [VWF], FXI, fibrinogen, plasminogen activator inhibitor-1, and tissue plasminogen activator), we performed local and global genetic correlation estimation multitrait analyses and colocalization and 2-sample Mendelian randomization analyses between hemostatic factors and HT. RESULTS: Local correlations identified a genomic region on chromosome 16 with shared covariance: fibrinogen-HT, P = 2.45 × 10 CONCLUSION: We identified 4 shared loci between hemostatic factors and HT after r-tPA treatment, suggesting common regulatory mechanisms between fibrinogen and VWF levels and HT. Further research to determine a possible mediating effect of fibrinogen on HT risk is needed

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease