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The link between the experimental laboratory studies and bioinformatic approaches aims to find procedures to connect tools from both branches producing workflows that bring together different techniques that are capable of exploiting data at many levels. Thanks to the open access sources and the numerous tools available, it is possible to create various pipelines capable of solving specific problems. Nevertheless the lack of connectivity between them that interconnect different approaches complicates the exploitation of these workflows. Here, we present a detailed description of a workflow composed of different bioinformatics tools that exploits data from large-scale gene expression experiments, contextualizing them at many biological levels. To illustrate the relevance of our workflow for the vitamin D community we applied it to data from myeloid cell models treated with the hormonally active form of vitamin. From raw files of functional genomic studies it is possible to utilize the whole information to obtain a biological insight. Different software and algorithms are included to analyse at pathway, metabolic, ontology and molecular biology level the effects on gene expression. The usage of different databases to analyse gene expression data allows to perform a complete interpretation of functional genomic studies and the implementation of analysis and visualization software tools gives a better understanding of the biological meaning of the results. This review is an example of how to select and bring together several software modules to create one pipeline that processes and analyses genomic data at many biological levels making it open, reproducible and user friendly. Finally, the application of our bioinformatic pipeline revealed that vitamin D modulates crucial metabolic pathways in different myeloid cells that may play an important role in their immune function., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: A comprehensive assessment of the epigenetic dynamics in cancer cells is the key to understanding the molecular mechanisms underlying cancer and to improving cancer diagnostics, prognostics and treatment. By combining genome-wide ChIP-seq epigenomics and microarray transcriptomics, we studied the effects of oxygen deprivation and subsequent reoxygenation on histone 3 trimethylation of lysine 4 (H3K4me3) and lysine 27 (H3K27me3) in a breast cancer cell line, serving as a model for abnormal oxygenation in solid tumors. A priori, epigenetic markings and gene expression levels not only are expected to vary greatly between hypoxic and normoxic conditions, but also display a large degree of heterogeneity across the cell population. Where traditionally ChIP-seq data are often treated as dichotomous data, the model and experiment here necessitate a quantitative, data-driven analysis of both datasets., Results: We first identified genomic regions with sustained epigenetic markings, which provided a sample-specific reference enabling quantitative ChIP-seq data analysis. Sustained H3K27me3 marking was located around centromeres and intergenic regions, while sustained H3K4me3 marking is associated with genes involved in RNA binding, translation and protein transport and localization. Dynamic marking with both H3K4me3 and H3K27me3 (hypoxia-induced bivalency) was found in CpG-rich regions at loci encoding factors that control developmental processes, congruent with observations in embryonic stem cells., Conclusions: In silico -identified epigenetically sustained and dynamic genomic regions were confirmed through ChIP-PCR in vitro, and obtained results are corroborated by published data and current insights regarding epigenetic regulation.

Study Question: Is gene expression in human preimplantation embryos affected by the medium used for embryo culture in vitro during an IVF treatment?, Summary Answer: Six days of in vitro culture of human preimplantation embryos resulted in medium-dependent differences in expression level of genes involved in apoptosis, protein degradation, metabolism and cell-cycle regulation., What Is Known Already: Several human studies have shown an effect of culture medium on embryo development, pregnancy outcome and birthweight. However, the underlying mechanisms in human embryos are still unknown. In animal models of human development, it has been demonstrated that culture of preimplantation embryos in vitro affects gene expression. In humans, it has been found that culture medium affects gene expression of cryopreserved embryos that, after thawing, were cultured in two different media for 2 more days., Study Design, Size, Duration: In a multicenter trial, women were randomly assigned to two culture medium groups [G5 and human tubal fluid (HTF)]. Data on embryonic development were collected for all embryos. In one center, embryos originating from two pronuclei (2PN) zygotes that were not selected for transfer or cryopreservation on Day 2 or 3 because of lower morphological quality, were cultured until Day 6 and used in this study, if couples consented., Participants/materials, Setting, Methods: Ten blastocysts each from the G5 and HTF study groups, matched for fertilization method, maternal age and blastocyst quality, were selected and their mRNA was isolated and amplified. Embryos were examined individually for genome-wide gene expression using Agilent microarrays and PathVisio was used to identify the pathways that showed a culture medium-dependent activity., Main Results and the Role of Chance: Expression of 951 genes differed significantly (P < 0.01) between the G5 and HTF groups. Eighteen pathways, involved in apoptosis, metabolism, protein processing and cell-cycle regulation, showed a significant overrepresentation of differentially expressed genes. The DNA replication, G1 to S cell-cycle control and oxidative phosphorylation pathways were up-regulated in the G5 group compared with the HTF group. This is in agreement with the morphological assessment of the 1527 embryos (originating from 2PN zygotes), which showed that embryos consisted of more cells on Day 2 (3.73 ± 1.30 versus 3.40 ± 1.35, P < 0.001) and Day 3 (7.00 ± 2.41 versus 5.84 ± 2.36, P < 0.001) in the G5 group when compared with the HTF group. Furthermore, the implantation rate was significantly higher in the G5 group compared with the HTF group (26.7% versus 14.7%, P = 0.002) after transfer on the second or the third day after fertilization., Limitations, Reasons for Caution: Despite careful matching of the embryos, it cannot be excluded that the differences observed between the study groups are caused by factors that we did not investigate. Extrapolation of these results to embryos used for transfer demands caution as in the present study embryos that were not selected for either embryo transfer or cryopreservation have been used for the culture experiment until Day 6., Wider Implications of the Findings: This study shows that gene expression in human preimplantation embryos is altered by the culture medium used during IVF treatment and provides insight into the biological pathways that are affected. Whether these changes in gene expression have any long-term effects on children born after IVF remains unknown. However, it is possible that early adaptations of the preimplantation embryo to its environment persist during fetal and post-natal development., Study Funding/competing Interests: No funding and no competing interests declared., Trial Registration Number: Not applicable., (© The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: Biological pathways are descriptive diagrams of biological processes widely used for functional analysis of differentially expressed genes or proteins. Primary data analysis, such as quality control, normalisation, and statistical analysis, is often performed in scripting languages like R, Perl, and Python. Subsequent pathway analysis is usually performed using dedicated external applications. Workflows involving manual use of multiple environments are time consuming and error prone. Therefore, tools are needed that enable pathway analysis directly within the same scripting languages used for primary data analyses. Existing tools have limited capability in terms of available pathway content, pathway editing and visualisation options, and export file formats. Consequently, making the full-fledged pathway analysis tool PathVisio available from various scripting languages will benefit researchers., Results: We developed PathVisioRPC, an XMLRPC interface for the pathway analysis software PathVisio. PathVisioRPC enables creating and editing biological pathways, visualising data on pathways, performing pathway statistics, and exporting results in several image formats in multiple programming environments. We demonstrate PathVisioRPC functionalities using examples in Python. Subsequently, we analyse a publicly available NCBI GEO gene expression dataset studying tumour bearing mice treated with cyclophosphamide in R. The R scripts demonstrate how calls to existing R packages for data processing and calls to PathVisioRPC can directly work together. To further support R users, we have created RPathVisio simplifying the use of PathVisioRPC in this environment. We have also created a pathway module for the microarray data analysis portal ArrayAnalysis.org that calls the PathVisioRPC interface to perform pathway analysis. This module allows users to use PathVisio functionality online without having to download and install the software and exemplifies how the PathVisioRPC interface can be used by data analysis pipelines for functional analysis of processed genomics data., Conclusions: PathVisioRPC enables data visualisation and pathway analysis directly from within various analytical environments used for preliminary analyses. It supports the use of existing pathways from WikiPathways or pathways created using the RPC itself. It also enables automation of tasks performed using PathVisio, making it useful to PathVisio users performing repeated visualisation and analysis tasks. PathVisioRPC is freely available for academic and commercial use at http://projects.bigcat.unimaas.nl/pathvisiorpc.

Background: Illumina whole-genome expression bead arrays are a widely used platform for transcriptomics. Most of the tools available for the analysis of the resulting data are not easily applicable by less experienced users. ArrayAnalysis.org provides researchers with an easy-to-use and comprehensive interface to the functionality of R and Bioconductor packages for microarray data analysis. As a modular open source project, it allows developers to contribute modules that provide support for additional types of data or extend workflows., Results: To enable data analysis of Illumina bead arrays for a broad user community, we have developed a module for ArrayAnalysis.org that provides a free and user-friendly web interface for quality control and pre-processing for these arrays. This module can be used together with existing modules for statistical and pathway analysis to provide a full workflow for Illumina gene expression data analysis. The module accepts data exported from Illumina's GenomeStudio, and provides the user with quality control plots and normalized data. The outputs are directly linked to the existing statistics module of ArrayAnalysis.org, but can also be downloaded for further downstream analysis in third-party tools., Conclusions: The Illumina bead arrays analysis module is available at http://www.arrayanalysis.org . A user guide, a tutorial demonstrating the analysis of an example dataset, and R scripts are available. The module can be used as a starting point for statistical evaluation and pathway analysis provided on the website or to generate processed input data for a broad range of applications in life sciences research.

Study Question: Is gene expression in placental tissue of IVF/ICSI patients altered when compared with a spontaneously conceived group, and are these alterations due to loss of imprinting (LOI) in the case of imprinted genes?, Summary Answer: An altered imprinted gene expression of H19 and Pleckstrin homology-like domain family A member 2 (PHLDA2), which was not due to LOI, was observed in human placentas after IVF/ICSI and several biological pathways were significantly overrepresented and mostly up-regulated., What Is Known Already: Genomic imprinting plays an important role in placental biology and in placental adaptive responses triggered by external stimuli. Changes in placental development and function can have dramatic effects on the fetus and its ability to cope with the intrauterine environment. An increased frequency of placenta-related problems as well as an adverse perinatal outcome is seen in IVF/ICSI derived pregnancies, but the role of placental epigenetic deregulation is not clear yet., Study Design and Participants: In this prospective cohort study, a total of 115 IVF/ICSI and 138 control couples were included during pregnancy. After applying several exclusion criteria (i.e. preterm birth or stillbirth, no placental samples, pregnancy complications or birth defects), respectively, 81 and 105 placentas from IVF/ICSI and control pregnancies remained for analysis. Saliva samples were collected from both parents., Methods: We quantitatively analysed the mRNA expression of several growth-related imprinted genes [H19, insulin-like growth factor 2 (IGF2), PHLDA2, cyclin-dependent kinase inhibitor 1C (CDKN1C), mesoderm-specific transcript homolog (MEST) isoform α and β by quantitative PCR] after standardization against three housekeeping genes [Succinate dehydrogenase A (SDHA), YWHAZ and TATA-binding protein (TBP)]. A quantitative allele-specific expression analysis of the differentially expressed imprinted genes was performed to investigate LOI, independent of the mechanism of imprinting. Furthermore, a microarray analysis was carried out (n = 10 in each group) to investigate the expression of non-imprinted genes as well., Main Results and the Role of Chance: Both H19 and PHLDA2 showed a significant change, respectively, a 1.3-fold (P = 0.033) and 1.5-fold (P = 0.002) increase in mRNA expression in the IVF/ICSI versus control group. However, we found no indication that there is an increased frequency of LOI in IVF/ICSI placental samples. Genome-wide mRNA expression revealed 13 significantly overrepresented biological pathways involved in metabolism, immune response, transmembrane signalling and cell cycle control, which were mostly up-regulated in the IVF/ICSI placental samples., Limitations, Reasons for Caution: Only a subset of samples was found to be fully informative, which unavoidably led to lower sample numbers for our LOI analysis. Our study cannot distinguish whether the reported differences in the IVF/ICSI group are exclusively attributable to the IVF/ICSI technique itself or to the underlying subfertility of the patients., Wider Implications of the Findings: Whether these placental adaptations observed in pregnancies conceived by IVF/ICSI might be connected to an adverse perinatal outcome after IVF remains unknown. However, it is possible that these differences affect fetal development and long-term patterns of gene expression, as well as maternal gestational physiology., Study Funding/competing Interests: Partly funded by an unrestricted research grant by Organon BV (now MSD BV) and GROW School for Oncology and Developmental Biology without any role in study design, data collection and analysis or preparation of the manuscript. No conflict of interests to declare., Trial Registration Number: Dutch Trial Registry (NTR) number 1298., (© The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The serotonin transporter gene (5-HTT/SLC6A4)-linked polymorphic region has been suggested to have a modulatory role in mediating effects of early-life stress exposure on psychopathology rendering carriers of the low-expression short (s)-variant more vulnerable to environmental adversity in later life. The underlying molecular mechanisms of this gene-by-environment interaction are not well understood, but epigenetic regulation including differential DNA methylation has been postulated to have a critical role. Recently, we used a maternal restraint stress paradigm of prenatal stress (PS) in 5-HTT-deficient mice and showed that the effects on behavior and gene expression were particularly marked in the hippocampus of female 5-Htt+/- offspring. Here, we examined to which extent these effects are mediated by differential methylation of DNA. For this purpose, we performed a genome-wide hippocampal DNA methylation screening using methylated-DNA immunoprecipitation (MeDIP) on Affymetrix GeneChip Mouse Promoter 1.0 R arrays. Using hippocampal DNA from the same mice as assessed before enabled us to correlate gene-specific DNA methylation, mRNA expression and behavior. We found that 5-Htt genotype, PS and their interaction differentially affected the DNA methylation signature of numerous genes, a subset of which showed overlap with the expression profiles of the corresponding transcripts. For example, a differentially methylated region in the gene encoding myelin basic protein (Mbp) was associated with its expression in a 5-Htt-, PS- and 5-Htt × PS-dependent manner. Subsequent fine-mapping of this Mbp locus linked the methylation status of two specific CpG sites to Mbp expression and anxiety-related behavior. In conclusion, hippocampal DNA methylation patterns and expression profiles of female prenatally stressed 5-Htt+/- mice suggest that distinct molecular mechanisms, some of which are promoter methylation-dependent, contribute to the behavioral effects of the 5-Htt genotype, PS exposure and their interaction.

Quality control (QC) is crucial for any scientific method producing data. Applying adequate QC introduces new challenges in the genomics field where large amounts of data are produced with complex technologies. For DNA microarrays, specific algorithms for QC and pre-processing including normalization have been developed by the scientific community, especially for expression chips of the Affymetrix platform. Many of these have been implemented in the statistical scripting language R and are available from the Bioconductor repository. However, application is hampered by lack of integrative tools that can be used by users of any experience level. To fill this gap, we developed a freely available tool for QC and pre-processing of Affymetrix gene expression results, extending, integrating and harmonizing functionality of Bioconductor packages. The tool can be easily accessed through a wizard-like web portal at http://www.arrayanalysis.org or downloaded for local use in R. The portal provides extensive documentation, including user guides, interpretation help with real output illustrations and detailed technical documentation. It assists newcomers to the field in performing state-of-the-art QC and pre-processing while offering data analysts an integral open-source package. Providing the scientific community with this easily accessible tool will allow improving data quality and reuse and adoption of standards.

Initiation of and progression through chondrogenesis is driven by changes in the cellular microenvironment. At the onset of chondrogenesis, resting mesenchymal stem cells are mobilized in vivo and a complex, step-wise chondrogenic differentiation program is initiated. Differentiation requires coordinated transcriptomic reprogramming and increased progenitor proliferation; both processes require chromatin remodeling. The nature of early molecular responses that relay differentiation signals to chromatin is poorly understood. We here show that immediate early genes are rapidly and transiently induced in response to differentiation stimuli in vitro. Functional ablation of the immediate early factor EGR1 severely deregulates expression of key chondrogenic control genes at the onset of differentiation. In addition, differentiating cells accumulate DNA damage, activate a DNA damage response and undergo a cell cycle arrest and prevent differentiation associated hyper-proliferation. Failed differentiation in the absence of EGR1 affects global acetylation and terminates in overall histone hypermethylation. We report novel molecular connections between EGR1 and Polycomb Group function: Polycomb associated histone H3 lysine27 trimethylation (H3K27me3) blocks chromatin access of EGR1. In addition, EGR1 ablation results in abnormal Ezh2 and Bmi1 expression. Consistent with this functional interaction, we identify a number of co-regulated targets genes in a chondrogenic gene network. We here describe an important role for EGR1 in early chondrogenic epigenetic programming to accommodate early gene-environment interactions in chondrogenesis.

Background: The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate., Results: We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures., Conclusion: T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially.

Background: Prostate cancer is currently the most frequently diagnosed malignancy in men and the second leading cause of cancer-related deaths in industrialized countries. Worldwide, an increase in prostate cancer incidence is expected due to an increased life-expectancy, aging of the population and improved diagnosis. Although the specific underlying mechanisms of prostate carcinogenesis remain unknown, prostate cancer is thought to result from a combination of genetic and environmental factors altering key cellular processes. To elucidate these complex interactions and to contribute to the understanding of prostate cancer progression and metastasis, analysis of large scale gene expression studies using bioinformatics approaches is used to decipher regulation of core processes., Methodology/principal Findings: In this study, a standardized quality control procedure and statistical analysis (http://www.arrayanalysis.org/) were applied to multiple prostate cancer datasets retrieved from the ArrayExpress data repository and pathway analysis using PathVisio (http://www.pathvisio.org/) was performed. The results led to the identification of three core biological processes that are strongly affected during prostate carcinogenesis: cholesterol biosynthesis, the process of epithelial-to-mesenchymal transition and an increased metabolic activity., Conclusions: This study illustrates how a standardized bioinformatics evaluation of existing microarray data and subsequent pathway analysis can quickly and cost-effectively provide essential information about important molecular pathways and cellular processes involved in prostate cancer development and disease progression. The presented results may assist in biomarker profiling and the development of novel treatment approaches.

Background: The m.3243A>G mutation in the mitochondrial tRNA(Leu(UUR)) gene is an example of a mutation causing a very heterogeneous phenotype. It is the most frequent cause (80%) of the MELAS syndrome (mitochondrial myopathy, encephalopathy, lactic acidosis and stroke-like episodes), but it can also lead in addition or separately to type 2 diabetes, deafness, renal tubulopathy and/or cardiomyopathy., Methods: To identify pathogenic processes induced by this mutation, we compared global gene expression levels of muscle biopsies from affected and unaffected mutation carriers with controls., Results and Conclusions: Gene expression changes were relatively subtle. In the asymptomatic group 200 transcripts were upregulated and 12 were downregulated, whereas in the symptomatic group 15 transcripts were upregulated and 52 were downregulated. In the asymptomatic group, oxidative phosphorylation (OXPHOS) complex I and IV genes were induced. Protein turnover and apoptosis were elevated, most likely due to the formation of dysfunctional and reactive oxygen species (ROS) damaged proteins. These processes returned to normal in symptomatic patients. Components of the complement system were upregulated in both groups, but the strongest in the symptomatic group, which might indicate muscle regeneration--most likely, protein damage and OXPHOS dysfunction stimulate repair (protein regeneration) and metabolic adaptation (OXPHOS). In asymptomatic individuals these processes suffice to prevent the occurrence of symptoms. However, in affected individuals the repair process terminates, presumably because of excessive damage, and switches to muscle regeneration, as indicated by a stronger complement activation. This switch leaves increasingly damaged tissue in place and muscle pathology becomes manifest. Therefore, the expression of complement components might be a marker for the severity and progression of MELAS clinical course.

To extract functional information on genes and processes from large expression datasets, analysis methods are required that can computationally deal with these amounts of data, are tunable to specific research questions, and construct classifiers that are not overspecific to the dataset at hand. To satisfy these requirements, a stepwise procedure that combines elements from principal component analysis and discriminant analysis, was developed to specifically retrieve genes involved in processes of interest and classify samples based upon those genes. In a global expression dataset of 300 gene knock-outs in Saccharomyces cerevisiae, the procedure successfully classified samples with similar 'cellular component' Gene Ontology annotations of the knock-out gene by expression signatures of limited numbers of genes. The genes discriminating 'mitochondrion' from the other subgroups were evaluated in more detail. The thiamine pathway turned out to be one of the processes involved and was successfully evaluated in a logistic model to predict whether yeast knock-outs were mitochondrial or not. Further, this pathway is biologically related to the mitochondrial system. Hence, this strongly indicates that our approach is effective and efficient in extracting meaningful information from large microarray experiments and assigning functions to yet uncharacterized genes.

Familial hypertrophic cardiomyopathy (FHC) is an autosomal dominant disease characterized by left ventricular hypertrophy (LVH) predominantly affecting the interventricular septum. Cardiac myosin-binding protein C (cMyBP-C) mutations are common causes of FHC. Gene expression profiling was performed in left ventricles of 9-week-old wild-type mice, heterozygous cMyBP-C KO mice displaying asymmetric septal hypertrophy, and homozygous mice developing eccentric LVH. Knocking out one or two cMyBP-C genes leads primarily to gene expression changes indicating an increased energy demand, activation of the JNK and p38 parts of the MAPK pathway and deactivation of the ERK part, and induction of apoptosis. Altered gene expression for processes related to cardiac structure, contractile proteins, and protein turnover was also identified. Many of the changes were more pronounced in the homozygous KO mice. These alterations point to physiological and pathological adaptations in the prehypertrophic heterozygous KO mice and the hypertrophic homozygous mice.

Purpose: Oxidative phosphorylation is under dual genetic control of the nuclear and the mitochondrial DNA (mtDNA). Oxidative phosphorylation disorders are clinically and genetically heterogeneous, which makes it difficult to determine the genetic defect, and symptom-based protocols which link clinical symptoms directly to a specific gene or mtDNA mutation are falling short. Moreover, approximately 25% of the pediatric patients with oxidative phosphorylation disorders is estimated to have mutations in the mtDNA and a standard screening approach for common mutations and deletions will only explain part of these cases. Therefore, we tested a new CHIP-based screening method for the mtDNA., Methods: MitoChip (Affymetrix) resequencing was performed on three test samples and on 28 patient samples., Results: Call rates were 94% on average and heteroplasmy detection levels varied from 5-50%. A genetic diagnosis can be made in almost one-quarter of the patients at a potential output of 8 complete mtDNA sequences every 4 days. Moreover, a number of potentially pathogenic unclassified variants (UV) were detected., Conclusions: The availability of long-range PCR protocols and the predominance of single nucleotide substitutions in the mtDNA make the resequencing CHIP a very fast and reliable method to screen the complete mtDNA for mutations.