Global regulatory architecture of human, mouse and rat tissue transcriptomes

Integrated view and comparative analysis of baseline protein expression in mouse and rat tissues

The increasingly large amount of proteomics data in the public domain enables, among other applications, the combined analyses of datasets to create comparative protein expression maps covering different organisms and different biological conditions. Here we have reanalysed public proteomics datasets from mouse and rat tissues (14 and 9 datasets, respectively), to assess baseline protein abundance. Overall, the aggregated dataset contained 23 individual datasets, including a total of 211 samples coming from 34 different tissues across 14 organs, comprising 9 mouse and 3 rat strains, respectively. In all cases, we studied the distribution of canonical proteins between the different organs. The number of canonical proteins per dataset ranged from 273 (tendon) and 9,715 (liver) in mouse, and from 101 (tendon) and 6,130 (kidney) in rat. Then, we studied how protein abundances compared across different datasets and organs for both species. As a key point we carried out a comparative analysis of protein expression between mouse, rat and human tissues. We observed a high level of correlation of protein expression among orthologs between all three species in brain, kidney, heart and liver samples, whereas the correlation of protein expression was generally slightly lower between organs within the same species. Protein expression results have been integrated into the resource Expression Atlas for widespread dissemination.

lncRNA Kcnq1ot1 promotes bone formation by inhibiting miR‑98‑5p/Tbx5 axis in MC3T3‑E1 cells

Long non-coding (lnc)RNA KCNQ1 opposite strand/antisense transcript 1 (Kcnq1ot1) has been shown to regulate multiple biological processes. However, the functional role of Kcnq1ot1 in osteoporosis and the underlying mechanism are still unclear. The present study aimed to investigate the function of lncRNA Kcnq1ot1 in osteogenic differentiation. Alkaline phosphatase (ALP) activity was measured using an ALP assay kit. Western blotting was performed to assess the expression levels of osteogenic differentiation-associated proteins. Reverse transcription-quantitative PCR was performed to detect Kcnq1ot1, microRNA (miR)-98-5p and T-box transcription factor 5 (Tbx5) expression levels. The binding of Kcnq1ot1 with miR-98-5p and that of miR-98-5p with Tbx5 were predicted by starBase and TargetScan databases, respectively, and verified using dual luciferase reporter assays. The mineralization of MC3T3-E1 cells was observed using an Alizarin red S staining assay. The results revealed that expression of Kcnq1ot1 was increased and that of miR-98-5p was decreased during osteogenic differentiation. Additionally, Kcnq1ot1 was shown to target miR-98-5p and inhibit its expression. Inhibiting miR-98-5p reversed the inhibitory effect of Kcnq1ot1 knockdown on osteogenic differentiation and mineralization of MC3T3-E1 cells. Furthermore, Kcnq1ot1 regulated Tbx5 expression via miR-98-5p. Overexpressing miR-98-5p or downregulating Tbx5 expression reversed the promotive effect of Kcnq1ot1 overexpression on osteogenic differentiation and mineralization of MC3T3-E1 cells. In conclusion, these findings suggested that Kcnq1ot1 may promote bone formation by inhibiting miR-98-5p and upregulating Tbx5. Kcnq1ot1, miR-98-5p and Tbx5 may therefore serve as promising targets for the treatment of osteoporosis.

Contextualization of causal regulatory networks from toxicogenomics data applied to drug-induced liver injury

In recent years, network-based methods have become an attractive analytical approach for toxicogenomics studies. They can capture not only the global changes of regulatory gene networks but also the relationships between their components. Among them, a causal reasoning approach depicts the mechanisms of regulation that connect upstream regulators in signaling networks to their downstream gene targets. In this work, we applied CARNIVAL, a causal network contextualisation tool, to infer upstream signaling networks deregulated in drug-induced liver injury (DILI) from gene expression microarray data from the TG-GATEs database. We focussed on six compounds that induce observable histopathologies linked to DILI from repeated dosing experiments in rats. We compared responses in vitro and in vivo to identify potential cross-platform concordances in rats as well as network preservations between rat and human. Our results showed similarities of enriched pathways and network motifs between compounds. These pathways and motifs induced the same pathology in rats but not in humans. In particular, the causal interactions "LCK activates SOCS3, which in turn inhibits TFDP1" was commonly identified as a regulatory path among the fibrosis-inducing compounds. This potential pathology-inducing regulation illustrates the value of our approach to generate hypotheses that can be further validated experimentally.

Co-expression clustering across flower development identifies modules for diverse floral forms in Achimenes (Gesneriaceae)

BACKGROUND

Genetic pathways involved with flower color and shape are thought to play an important role in the development of flowers associated with different pollination syndromes, such as those associated with bee, butterfly, or hummingbird pollination. Because pollination syndromes are complex traits that are orchestrated by multiple genes and pathways, the gene regulatory networks have not been explored. Gene co-expression networks provide a systems level approach to identify important contributors to floral diversification.

METHODS

RNA-sequencing was used to assay gene expression across two stages of flower development (an early bud and an intermediate stage) in 10 species of Achimenes (Gesneriaceae). Two stage-specific co-expression networks were created from 9,503 orthologs and analyzed to identify module hubs and the network periphery. Module association with bee, butterfly, and hummingbird pollination syndromes was tested using phylogenetic mixed models. The relationship between network connectivity and evolutionary rates (d N/d S) was tested using linear models.

RESULTS

Networks contained 65 and 62 modules that were largely preserved between developmental stages and contained few stage-specific modules. Over a third of the modules in both networks were associated with flower color, shape, and pollination syndrome. Within these modules, several hub nodes were identified that related to the production of anthocyanin and carotenoid pigments and the development of flower shape. Evolutionary rates were decreased in highly connected genes and elevated in peripheral genes.

DISCUSSION

This study aids in the understanding of the genetic architecture and network properties underlying the development of floral form and provides valuable candidate modules and genes for future studies.

Differential subnetwork of chemokines/cytokines in human, mouse, and rat brain cells after oxygen-glucose deprivation

Mice and rats are the most commonly used animals for preclinical stroke studies, but it is unclear whether targets and mechanisms are always the same across different species. Here, we mapped the baseline expression of a chemokine/cytokine subnetwork and compared responses after oxygen-glucose deprivation in primary neurons, astrocytes, and microglia from mouse, rat, and human. Baseline profiles of chemokines (CX3CL1, CXCL12, CCL2, CCL3, and CXCL10) and cytokines (IL-1α, IL-1β, IL-6, IL-10, and TNFα) showed significant differences between human and rodents. The response of chemokines/cytokines to oxygen-glucose deprivation was also significantly different between species. After 4 h oxygen-glucose deprivation and 4 h reoxygenation, human and rat neurons showed similar changes with a downregulation in many chemokines, whereas mouse neurons showed a mixed response with up- and down-regulated genes. For astrocytes, subnetwork response patterns were more similar in rats and mice compared to humans. For microglia, rat cells showed an upregulation in all chemokines/cytokines, mouse cells had many down-regulated genes, and human cells showed a mixed response with up- and down-regulated genes. This study provides proof-of-concept that species differences exist in chemokine/cytokine subnetworks in brain cells that may be relevant to stroke pathophysiology. Further investigation of differential gene pathways across species is warranted.

A systems biology approach to defining regulatory mechanisms for cartilage and tendon cell phenotypes

Phenotypic plasticity of adult somatic cells has provided emerging avenues for the development of regenerative therapeutics. In musculoskeletal biology the mechanistic regulatory networks of genes governing the phenotypic plasticity of cartilage and tendon cells has not been considered systematically. Additionally, a lack of strategies to effectively reproduce in vitro functional models of cartilage and tendon is retarding progress in this field. De- and redifferentiation represent phenotypic transitions that may contribute to loss of function in ageing musculoskeletal tissues. Applying a systems biology network analysis approach to global gene expression profiles derived from common in vitro culture systems (monolayer and three-dimensional cultures) this study demonstrates common regulatory mechanisms governing de- and redifferentiation transitions in cartilage and tendon cells. Furthermore, evidence of convergence of gene expression profiles during monolayer expansion of cartilage and tendon cells, and the expression of key developmental markers, challenges the physiological relevance of this culture system. The study also suggests that oxidative stress and PI3K signalling pathways are key modulators of in vitro phenotypes for cells of musculoskeletal origin.

A risk assessment-driven quantitative comparison of gene expression profiles in PBMCs and white adipose tissue of humans and rats after isoflavone supplementation

Quantitative insight into species differences in risk assessment is expected to reduce uncertainty and variability related to extrapolation from animals to humans. This paper explores quantification and comparison of gene expression data between tissues and species from intervention studies with isoflavones. Gene expression data from peripheral blood mononuclear cells (PBMCs) and white adipose tissue (WAT) after 8wk isoflavone interventions in postmenopausal women and ovariectomized F344 rats were used. A multivariate model was applied to quantify gene expression effects, which showed 3-5-fold larger effect sizes in rats compared to humans. For estrogen responsive genes, a 5-fold greater effect size was found in rats than in humans. For these genes, intertissue correlations (r = 0.23 in humans, r = 0.22 in rats) and interspecies correlation in WAT (r = 0.31) were statistically significant. Effect sizes, intertissue and interspecies correlations for some groups of genes within energy metabolism, inflammation and cell cycle processes were significant, but weak. Quantification of gene expression data reveals differences between rats and women in effect magnitude after isoflavone supplementation. For risk assessment, quantification of gene expression data and subsequent calculation of intertissue and interspecies correlations within biological pathways will further strengthen knowledge on comparability between tissues and species.

Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

Transcriptome data sets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by a lack of metadata or differences in annotation styles of different labs. In this study, we carefully selected and integrated 6057 Arabidopsis microarray expression samples from 304 experiments deposited to the Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI). Metadata such as tissue type, growth conditions and developmental stage were manually curated for each sample. We then studied the global expression landscape of the integrated data set and found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome, compared with aerial tissues, but the transcriptome of cultured root is more similar to the transcriptome of aerial tissues, as the cultured root samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating the re-use of plant transcriptome data. As a proof of principle, we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified the accuracy of our predictions with sample metadata provided by the authors.

Differences in Akt signaling and metabolism gene expression in the right heart, intraventricular septum and left heart of rodents

The right heart is functionally and structurally different from the left heart; however, potential differences in Akt signaling and the expression of metabolic genes between the right heart and left heart in different rodents are still unknown. Using Western blotting and real time quantification polymerase chain reaction, we measured the levels of total Akt, phosphorylated Akt and its downstream targets as well as metabolism genes including glucose transporter 1, glucose transporter 4 (GLUT4), peroxisome proliferator-activated receptor α, peroxisome proliferator-activated receptor γ, peroxisome proliferator-activated receptor δ, peroxisome proliferator-activated receptor gamma coactivator 1α (PGC-1α), and pyruvate dehydrogenase lipoamide kinase isozyme 4. We found that phosphorylated Akt and proline-rich Akt substrate 40 levels were significantly increased in the RV compared with the LV in rats but only had an increased trend in mice. Correspondingly, GLUT4 was significantly increased in the RV compared with the LV both in mice and rats. PGC-1α was significantly increased in the RV compared with the LV in mice but only had an increased trend in rats. Moreover, Akt signaling activity and metabolism genes' expression in the IVS were similar to the RV in mice but to the LV in rats. There were some differences in the activity of Akt signaling and in the levels of metabolism genes among the right ventricle, interventricular septum and left ventricle. Also, the diversity of activity of Akt and metabolism genes between the right ventricle and left ventricle are different between rats and mice. In conclusion, the activity of Akt signaling and the levels of metabolism genes are different among the right ventricle, interventricular septum and left ventricle providing some potential clues for exploring the roles of Akt signaling and cardiac metabolisms in different parts of the heart. Additionally, the differences in Akt activity and metabolism genes' levels between the right and left ventricles are different between mice and rats, to which we should pay attention when using different animal model in heart study.

Modular organization of the white spruce (Picea glauca) transcriptome reveals functional organization and evolutionary signatures

Transcript profiling has shown the molecular bases of several biological processes in plants but few studies have developed an understanding of overall transcriptome variation. We investigated transcriptome structure in white spruce (Picea glauca), aiming to delineate its modular organization and associated functional and evolutionary attributes. Microarray analyses were used to: identify and functionally characterize groups of co-expressed genes; investigate expressional and functional diversity of vascular tissue preferential genes which were conserved among Picea species, and identify expression networks underlying wood formation. We classified 22 857 genes as variable (79%; 22 coexpression groups) or invariant (21%) by profiling across several vegetative tissues. Modular organization and complex transcriptome restructuring among vascular tissue preferential genes was revealed by their assignment to coexpression groups with partially overlapping profiles and partially distinct functions. Integrated analyses of tissue-based and temporally variable profiles identified secondary xylem gene networks, showed their remodelling over a growing season and identified PgNAC-7 (no apical meristerm (NAM), Arabidopsis transcription activation factor (ATAF) and cup-shaped cotyledon (CUC) transcription factor 007 in Picea glauca) as a major hub gene specific to earlywood formation. Reference profiling identified comprehensive, statistically robust coexpressed groups, revealing that modular organization underpins the evolutionary conservation of the transcriptome structure.

Molecular and neuronal homology between the olfactory systems of zebrafish and mouse

Studies of the two major olfactory organs of rodents, the olfactory mucosa (OM) and the vomeronasal organ (VNO), unraveled the molecular basis of smell in vertebrates. However, some vertebrates lack a VNO. Here we generated and analyzed the olfactory transcriptome of the zebrafish and compared it to the olfactory transcriptomes of mouse to investigate the evolutionary and molecular relationship between single and dual olfactory systems. Our analyses revealed a high degree of molecular conservation, with orthologs of mouse olfactory cell-specific markers and all but one of their chemosensory receptor classes expressed in the single zebrafish olfactory organ. Zebrafish chemosensory receptor genes are expressed across a large dynamic range and their RNA abundance correlates positively with the number of neurons expressing that RNA. Thus we estimate the relative proportions of neuronal sub-types expressing different chemosensory receptors. Receptor repertoire size drives the absolute abundance of different classes of neurons, but we find similar underlying patterns in both species. Finally, we identified novel marker genes that characterize rare neuronal populations in both mouse and zebrafish. In sum, we find that the molecular and cellular mechanisms underpinning olfaction in teleosts and mammals are similar despite 430 million years of evolutionary divergence.

ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions

Reference datasets are often used to compare, interpret or validate experimental data and analytical methods. In the field of gene expression, several reference datasets have been published. Typically, they consist of individual baseline or spike-in experiments carried out in a single laboratory and representing a particular set of conditions. Here, we describe a new type of standardized datasets representative for the spatial and temporal dimensions of gene expression. They result from integrating expression data from a large number of globally normalized and quality controlled public experiments. Expression data is aggregated by anatomical part or stage of development to yield a representative transcriptome for each category. For example, we created a genome-wide expression dataset representing the FDA tissue panel across 35 tissue types. The proposed datasets were created for human and several model organisms and are publicly available at http://www.expressiondata.org.

FANSe2: a robust and cost-efficient alignment tool for quantitative next-generation sequencing applications

Correct and bias-free interpretation of the deep sequencing data is inevitably dependent on the complete mapping of all mappable reads to the reference sequence, especially for quantitative RNA-seq applications. Seed-based algorithms are generally slow but robust, while Burrows-Wheeler Transform (BWT) based algorithms are fast but less robust. To have both advantages, we developed an algorithm FANSe2 with iterative mapping strategy based on the statistics of real-world sequencing error distribution to substantially accelerate the mapping without compromising the accuracy. Its sensitivity and accuracy are higher than the BWT-based algorithms in the tests using both prokaryotic and eukaryotic sequencing datasets. The gene identification results of FANSe2 is experimentally validated, while the previous algorithms have false positives and false negatives. FANSe2 showed remarkably better consistency to the microarray than most other algorithms in terms of gene expression quantifications. We implemented a scalable and almost maintenance-free parallelization method that can utilize the computational power of multiple office computers, a novel feature not present in any other mainstream algorithm. With three normal office computers, we demonstrated that FANSe2 mapped an RNA-seq dataset generated from an entire Illunima HiSeq 2000 flowcell (8 lanes, 608 M reads) to masked human genome within 4.1 hours with higher sensitivity than Bowtie/Bowtie2. FANSe2 thus provides robust accuracy, full indel sensitivity, fast speed, versatile compatibility and economical computational utilization, making it a useful and practical tool for deep sequencing applications. FANSe2 is freely available at http://bioinformatics.jnu.edu.cn/software/fanse2/.