Recommendations for the analysis of gene expression data to identify intrinsic differences between similar tissues.

Identifying genes involved in functional differences between similar tissues from expression profiles is challenging, because the expected differences in expression levels are small. To exemplify this challenge, we studied the expression profiles of two skeletal muscles, deltoid and biceps, in healthy individuals. We provide a series of guides and recommendations for the analysis of this type of studies. These include how to account for batch effects and inter-individual differences to optimize the detection of gene signatures associated with tissue function. We provide guidance on the selection of optimal settings for constructing gene co-expression networks through parameter sweeps of settings and calculation of the overlap with an established knowledge network. Our main recommendation is to use a combination of the data-driven approaches, such as differential gene expression analysis and gene co-expression network analysis, and hypothesis-driven approaches, such as gene set connectivity analysis. Accordingly, we detected differences in metabolic gene expression between deltoid and biceps that were supported by both data- and hypothesis-driven approaches. Finally, we provide a bioinformatic framework that support the biological interpretation of expression profiles from related tissues from this combination of approaches, which is available at github.com/tabbassidaloii/AnalysisFrameworkSimilarTissues.

Sox4 mediates Tbx3 transcriptional regulation of the gap junction protein Cx43.

Tbx3, a T-box transcription factor, regulates key steps in development of the heart and other organ systems. Here, we identify Sox4 as an interacting partner of Tbx3. Pull-down and nuclear retention assays verify this interaction and in situ hybridization reveals Tbx3 and Sox4 to co-localize extensively in the embryo including the atrioventricular and outflow tract cushion mesenchyme and a small area of interventricular myocardium. Tbx3, SOX4, and SOX2 ChIP data, identify a region in intron 1 of Gja1 bound by all tree proteins and subsequent ChIP experiments verify that this sequence is bound, in vivo, in the developing heart. In a luciferase reporter assay, this element displays a synergistic antagonistic response to co-transfection of Tbx3 and Sox4 and in vivo, in zebrafish, drives expression of a reporter in the heart, confirming its function as a cardiac enhancer. Mechanistically, we postulate that Sox4 is a mediator of Tbx3 transcriptional activity.

Cell type-specific changes in transcriptomic profiles of endothelial cells, iPSC-derived neurons and astrocytes cultured on microfluidic chips.

In vitro neuronal models are essential for studying neurological physiology, disease mechanisms and potential treatments. Most in vitro models lack controlled vasculature, despite its necessity in brain physiology and disease. Organ-on-chip models offer microfluidic culture systems with dedicated micro-compartments for neurons and vascular cells. Such multi-cell type organs-on-chips can emulate neurovascular unit (NVU) physiology, however there is a lack of systematic data on how individual cell types are affected by culturing on microfluidic systems versus conventional culture plates. This information can provide perspective on initial findings of studies using organs-on-chip models, and further optimizes these models in terms of cellular maturity and neurovascular physiology. Here, we analysed the transcriptomic profiles of co-cultures of human induced pluripotent stem cell (hiPSC)-derived neurons and rat astrocytes, as well as one-day monocultures of human endothelial cells, cultured on microfluidic chips. For each cell type, large gene expression changes were observed when cultured on microfluidic chips compared to conventional culture plates. Endothelial cells showed decreased cell division, neurons and astrocytes exhibited increased cell adhesion, and neurons showed increased maturity when cultured on a microfluidic chip. Our results demonstrate that culturing NVU cell types on microfluidic chips changes their gene expression profiles, presumably due to distinct surface-to-volume ratios and substrate materials. These findings inform further NVU organ-on-chip model optimization and support their future application in disease studies and drug testing.

Literature-based priors for gene regulatory networks.

MOTIVATION: The use of prior knowledge to improve gene regulatory network modelling has often been proposed. In this article we present the first research on the massive incorporation of prior knowledge from literature for Bayesian network learning of gene networks. As the publication rate of scientific papers grows, updating online databases, which have been proposed as potential prior knowledge in past research, becomes increasingly challenging. The novelty of our approach lies in the use of gene-pair association scores that describe the overlap in the contexts in which the genes are mentioned, generated from a large database of scientific literature, harnessing the information contained in a huge number of documents into a simple, clear format. RESULTS: We present a method to transform such literature-based gene association scores to network prior probabilities, and apply it to learn gene sub-networks for yeast, Escherichia coli and Human organisms. We also investigate the effect of weighting the influence of the prior knowledge. Our findings show that literature-based priors can improve both the number of true regulatory interactions present in the network and the accuracy of expression value prediction on genes, in comparison to a network learnt solely from expression data. Networks learnt with priors also show an improved biological interpretation, with identified subnetworks that coincide with known biological pathways.

Applying the FAIR Data Principles to the Registry of Vascular Anomalies (VASCA).

BACKGROUND: Connecting currently existing, heterogeneous rare disease (RD) registries would greatly facilitate epidemiological and clinical research. To increase their interoperability, the European Union developed a set of Common Data Elements (CDEs) for RD registries. OBJECTIVES: To implement the CDEs and the FAIR data principles in the Registry of Vascular Anomalies (VASCA). METHODS: We created a semantic model for the CDE and transformed this into a Resource Description Framework (RDF) template. The electronic case report forms (eCRF) were mapped to the RDF template and published in a FAIR Data Point (FDP). RESULTS: The FAIR VASCA registry was successfully implemented using Castor EDC (Electronic Data Capture) software. CONCLUSION: FAIR technology allows researchers to query and combine data from different registries in real-time.

Relative power and sample size analysis on gene expression profiling data.

BACKGROUND: With the increasing number of expression profiling technologies, researchers today are confronted with choosing the technology that has sufficient power with minimal sample size, in order to reduce cost and time. These depend on data variability, partly determined by sample type, preparation and processing. Objective measures that help experimental design, given own pilot data, are thus fundamental. RESULTS: Relative power and sample size analysis were performed on two distinct data sets. The first set consisted of Affymetrix array data derived from a nutrigenomics experiment in which weak, intermediate and strong PPARalpha agonists were administered to wild-type and PPARalpha-null mice. Our analysis confirms the hierarchy of PPARalpha-activating compounds previously reported and the general idea that larger effect sizes positively contribute to the average power of the experiment. A simulation experiment was performed that mimicked the effect sizes seen in the first data set. The relative power was predicted but the estimates were slightly conservative. The second, more challenging, data set describes a microarray platform comparison study using hippocampal deltaC-doublecortin-like kinase transgenic mice that were compared to wild-type mice, which was combined with results from Solexa/Illumina deep sequencing runs. As expected, the choice of technology greatly influences the performance of the experiment. Solexa/Illumina deep sequencing has the highest overall power followed by the microarray platforms Agilent and Affymetrix. Interestingly, Solexa/Illumina deep sequencing displays comparable power across all intensity ranges, in contrast with microarray platforms that have decreased power in the low intensity range due to background noise. This means that deep sequencing technology is especially more powerful in detecting differences in the low intensity range, compared to microarray platforms. CONCLUSION: Power and sample size analysis based on pilot data give valuable information on the performance of the experiment and can thereby guide further decisions on experimental design. Solexa/Illumina deep sequencing is the technology of choice if interest lies in genes expressed in the low-intensity range. Researchers can get guidance on experimental design using our approach on their own pilot data implemented as a BioConductor package, SSPA http://bioconductor.org/packages/release/bioc/html/SSPA.html.

Common pathological mechanisms in mouse models for muscular dystrophies.

Duchenne/Becker and limb-girdle muscular dystrophies share clinical symptoms like muscle weakness and wasting but differ in clinical presentation and severity. To get a closer view on the differentiating molecular events responsible for the muscular dystrophies, we have carried out a comparative gene expression profiling of hindlimb muscles of the following mouse models: dystrophin-deficient (mdx, mdx(3cv)), sarcoglycan-deficient (Sgca null, Sgcb null, Sgcg null, Sgcd null), dysferlin-deficient (Dysf null, SJL(Dysf)), sarcospan-deficient (Sspn null), and wild-type (C57Bl/6, C57Bl/10) mice. The expression profiles clearly discriminated between severely affected (dystrophinopathies and sarcoglycanopathies) and mildly or nonaffected models (dysferlinopathies, sarcospan-deficiency, wild-type). Dystrophin-deficient and sarcoglycan-deficient profiles were remarkably similar, sharing inflammatory and structural remodeling processes. These processes were also ongoing in dysferlin-deficient animals, albeit at lower levels, in agreement with the later age of onset of this muscular dystrophy. The inflammatory proteins Spp1 and S100a9 were up-regulated in all models, including sarcospan-deficient mice, which points, for the first time, at a subtle phenotype for Sspn null mice. In conclusion, we identified biomarker genes for which expression correlates with the severity of the disease, which can be used for monitoring disease progression. This comparative study is an integrating step toward the development of an expression profiling-based diagnostic approach for muscular dystrophies in humans.

Muscle regeneration in dystrophin-deficient mdx mice studied by gene expression profiling.

BACKGROUND: Duchenne muscular dystrophy (DMD), caused by mutations in the dystrophin gene, is lethal. In contrast, dystrophin-deficient mdx mice recover due to effective regeneration of affected muscle tissue. To characterize the molecular processes associated with regeneration, we compared gene expression levels in hindlimb muscle tissue of mdx and control mice at 9 timepoints, ranging from 1-20 weeks of age. RESULTS: Out of 7776 genes, 1735 were differentially expressed between mdx and control muscle at at least one timepoint (p < 0.05 after Bonferroni correction). We found that genes coding for components of the dystrophin-associated glycoprotein complex are generally downregulated in the mdx mouse. Based on functional characteristics such as membrane localization, signal transduction, and transcriptional activation, 166 differentially expressed genes with possible functions in regeneration were analyzed in more detail. The majority of these genes peak at the age of 8 weeks, where the regeneration activity is maximal. The following pathways are activated, as shown by upregulation of multiple members per signalling pathway: the Notch-Delta pathway that plays a role in the activation of satellite cells, and the Bmp15 and Neuregulin 3 signalling pathways that may regulate proliferation and differentiation of satellite cells. In DMD patients, only few of the identified regeneration-associated genes were found activated, indicating less efficient regeneration processes in humans. CONCLUSION: Based on the observed expression profiles, we describe a model for muscle regeneration in mdx mice, which may provide new leads for development of DMD therapies based on the improvement of muscle regeneration efficacy.

Despite differential gene expression profiles pediatric MDS derived mesenchymal stromal cells display functionality in vitro.

Pediatric myelodysplastic syndrome (MDS) is a heterogeneous disease covering a spectrum ranging from aplasia (RCC) to myeloproliferation (RAEB(t)). In adult-type MDS there is increasing evidence for abnormal function of the bone-marrow microenvironment. Here, we extensively studied the mesenchymal stromal cells (MSCs) derived from children with MDS. MSCs were expanded from the bone-marrow of 17 MDS patients (RCC: n=10 and advanced MDS: n=7) and pediatric controls (n=10). No differences were observed with respect to phenotype, differentiation capacity, immunomodulatory capacity or hematopoietic support. mRNA expression analysis by Deep-SAGE revealed increased IL-6 expression in RCC- and RAEB(t)-MDS. RCC-MDS MSC expressed increased levels of DKK3, a protein associated with decreased apoptosis. RAEB(t)-MDS revealed increased CRLF1 and decreased DAPK1 expressions. This pattern has been associated with transformation in hematopoietic malignancies. Genes reported to be differentially expressed in adult MDS-MSC did not differ between MSC of pediatric MDS and controls. An altered mRNA expression profile, associated with cell survival and malignant transformation, of MSC derived from children with MDS strengthens the hypothesis that the micro-environment is of importance in this disease. Our data support the understanding that pediatric and adult MDS are two different diseases. Further evaluation of the pathways involved might reveal additional therapy targets.

Serum matrix metalloproteinase-9 (MMP-9) as a biomarker for monitoring disease progression in Duchenne muscular dystrophy (DMD).

To identify serum biomarkers that allow monitoring of disease progression and treatment effects in Duchenne muscular dystrophy (DMD) patients, levels of matrix metalloproteinase-9 (MMP-9), tissue inhibitors of metalloproteinase-1 (TIMP-1) and osteopontin (OPN) were determined in 63 DMD patients on corticosteroid therapy. These proteins were selected for their role in the pathogenesis of muscular dystrophy. Levels of MMP-9 and TIMP-1 were significantly higher in sera of DMD patients compared to healthy controls, whereas the OPN levels showed no significant difference. MMP-9 levels were also observed to be significantly higher in older, nonambulant patients, compared to ambulant patients. Longitudinal data from a smaller cohort of DMD patients followed up for over 4years showed that MMP-9, but not TIMP-1 increased significantly with age. Hence, MMP-9 is a potential DMD biomarker for disease progression. Future studies have to confirm whether serum MMP-9 levels can be used to monitor therapeutic response.