Benchmarking integration of single-cell differential expression.

Integration of single-cell RNA sequencing data between different samples has been a major challenge for analyzing cell populations. However, strategies to integrate differential expression analysis of single-cell data remain underinvestigated. Here, we benchmark 46 workflows for differential expression analysis of single-cell data with multiple batches. We show that batch effects, sequencing depth and data sparsity substantially impact their performances. Notably, we find that the use of batch-corrected data rarely improves the analysis for sparse data, whereas batch covariate modeling improves the analysis for substantial batch effects. We show that for low depth data, single-cell techniques based on zero-inflation model deteriorate the performance, whereas the analysis of uncorrected data using limmatrend, Wilcoxon test and fixed effects model performs well. We suggest several high-performance methods under different conditions based on various simulation and real data analyses. Additionally, we demonstrate that differential expression analysis for a specific cell type outperforms that of large-scale bulk sample data in prioritizing disease-related genes.

MicroRNA-29 Ameliorates Fibro-Inflammation and Insulin Resistance in HIF1α-Deficient Obese Adipose Tissue by Inhibiting Endotrophin Generation.

Dysregulation of extracellular matrix proteins in obese adipose tissue (AT) induces systemic insulin resistance. The metabolic roles of type VI collagen and its cleavage peptide endotrophin in obese AT are well established. However, the mechanisms regulating endotrophin generation remain elusive. Herein, we identified that several endotrophin-containing peptides (pre-endotrophins) were generated from the COL6A3 chain in a stepwise manner for the efficient production of mature endotrophin, partly through the action of hypoxia-induced matrix metalloproteinases (MMPs), including MMP2, MMP9, and MMP16. Hypoxia is an upstream regulator of COL6A3 expression and the proteolytic processing that regulates endotrophin generation. Hypoxia-inducible factor 1α (HIF1α) and the hypoxia-associated suppression of microRNA-29 (miR-29) cooperatively control the levels of COL6A3 and MMPs, which are responsible for endotrophin generation in hypoxic ATs. Adipocyte-specific Hif1α knock-out (APN-HIF1αKO) mice fed a chronic high-fat diet exhibited the significant amelioration of both local fibro-inflammation in AT and systemic insulin resistance compared with their control littermates, partly through the inhibition of endotrophin generation. Strikingly, adenovirus-mediated miR-29 overexpression in the ATs of APN-HIF1αKO mice in obesity significantly decreased endotrophin levels, suggesting that miR-29, combined with HIF1α inhibition in AT, could be a promising therapeutic strategy for treating obesity and related metabolic diseases.

Hepatic MIR20B promotes nonalcoholic fatty liver disease by suppressing PPARA.

Background: Non-alcoholic fatty liver disease (NAFLD) is characterized by excessive lipid accumulation and imbalances in lipid metabolism in the liver. Although nuclear receptors (NRs) play a crucial role in hepatic lipid metabolism, the underlying mechanisms of NR regulation in NAFLD remain largely unclear. Methods: Using network analysis and RNA-seq to determine the correlation between NRs and microRNA in human NAFLD patients, we revealed that MIR20B specifically targets PPARA. MIR20B mimic and anti-MIR20B were administered to human HepG2 and Huh-7 cells and mouse primary hepatocytes as well as high-fat diet (HFD)- or methionine-deficient diet (MCD)-fed mice to verify the specific function of MIR20B in NAFLD. We tested the inhibition of the therapeutic effect of a PPARα agonist, fenofibrate, by Mir20b and the synergic effect of combination of fenofibrate with anti-Mir20b in NAFLD mouse model. Results: We revealed that MIR20B specifically targets PPARA through miRNA regulatory network analysis of nuclear receptor genes in NAFLD. The expression of MIR20B was upregulated in free fatty acid (FA)-treated hepatocytes and the livers of both obesity-induced mice and NAFLD patients. Overexpression of MIR20B significantly increased hepatic lipid accumulation and triglyceride levels. Furthermore, MIR20B significantly reduced FA oxidation and mitochondrial biogenesis by targeting PPARA. In Mir20b-introduced mice, the effect of fenofibrate to ameliorate hepatic steatosis was significantly suppressed. Finally, inhibition of Mir20b significantly increased FA oxidation and uptake, resulting in improved insulin sensitivity and a decrease in NAFLD progression. Moreover, combination of fenofibrate and anti-Mir20b exhibited the synergic effect on improvement of NAFLD in MCD-fed mice. Conclusions: Taken together, our results demonstrate that the novel MIR20B targets PPARA, plays a significant role in hepatic lipid metabolism, and present an opportunity for the development of novel therapeutics for NAFLD. Funding: This research was funded by Korea Mouse Phenotyping Project (2016M3A9D5A01952411), the National Research Foundation of Korea (NRF) grant funded by the Korea government (2020R1F1A1061267, 2018R1A5A1024340, NRF-2021R1I1A2041463, 2020R1I1A1A01074940, 2016M3C9A394589324), and the Future-leading Project Research Fund (1.210034.01) of UNIST.

Powerful p-value combination methods to detect incomplete association.

Meta-analyses increase statistical power by combining statistics from multiple studies. Meta-analysis methods have mostly been evaluated under the condition that all the data in each study have an association with the given phenotype. However, specific experimental conditions in each study or genetic heterogeneity can result in "unassociated statistics" that are derived from the null distribution. Here, we show that power of conventional meta-analysis methods rapidly decreases as an increasing number of unassociated statistics are included, whereas the classical Fisher's method and its weighted variant (wFisher) exhibit relatively high power that is robust to addition of unassociated statistics. We also propose another robust method based on joint distribution of ordered p-values (ordmeta). Simulation analyses for t-test, RNA-seq, and microarray data demonstrated that wFisher and ordmeta, when only a small number of studies have an association, outperformed existing meta-analysis methods. We performed meta-analyses of nine microarray datasets (prostate cancer) and four association summary datasets (body mass index), where our methods exhibited high biological relevance and were able to detect genes that the-state-of-the-art methods missed. The metapro R package that implements the proposed methods is available from both CRAN and GitHub ( http://github.com/unistbig/metapro ).

Diffusible Signaling Factor, a Quorum-Sensing Molecule, Interferes with and Is Toxic Towards Bdellovibrio bacteriovorus 109J.

Bdellovibrio bacteriovorus 109J is a predatory bacterium which lives by predating on other Gram-negative bacteria to obtain the nutrients it needs for replication and survival. Here, we evaluated the effects two classes of bacterial signaling molecules (acyl homoserine lactones (AHLs) and diffusible signaling factor (DSF)) have on B. bacteriovorus 109J behavior and viability. While AHLs had a non-significant impact on predation rates, DSF considerably delayed predation and bdelloplast lysis. Subsequent experiments showed that 50 µM DSF also reduced the motility of attack-phase B. bacteriovorus 109J cells by 50% (38.2 ± 14.9 vs. 17 ± 8.9 µm/s). Transcriptomic analyses found that DSF caused genome-wide changes in B. bacteriovorus 109J gene expression patterns during both the attack and intraperiplasmic phases, including the significant downregulation of the flagellum assembly genes and numerous serine protease genes. While the former accounts for the reduced speeds observed, the latter was confirmed experimentally with 50 µM DSF completely blocking protease secretion from attack-phase cells. Additional experiments found that 30% of the total cellular ATP was released into the supernatant when B. bacteriovorus 109J was exposed to 200 µM DSF, implying that this QS molecule negatively impacts membrane integrity.

Benchmarking RNA-seq differential expression analysis methods using spike-in and simulation data.

Benchmarking RNA-seq differential expression analysis methods using spike-in and simulated RNA-seq data has often yielded inconsistent results. The spike-in data, which were generated from the same bulk RNA sample, only represent technical variability, making the test results less reliable. We compared the performance of 12 differential expression analysis methods for RNA-seq data, including recent variants in widely used software packages, using both RNA spike-in and simulation data for negative binomial (NB) model. Performance of edgeR, DESeq2, and ROTS was particularly different between the two benchmark tests. Then, each method was tested under most extensive simulation conditions especially demonstrating the large impacts of proportion, dispersion, and balance of differentially expressed (DE) genes. DESeq2, a robust version of edgeR (edgeR.rb), voom with TMM normalization (voom.tmm) and sample weights (voom.sw) showed an overall good performance regardless of presence of outliers and proportion of DE genes. The performance of RNA-seq DE gene analysis methods substantially depended on the benchmark used. Based on the simulation results, suitable methods were suggested under various test conditions.

The voltage-gated potassium channel Shaker promotes sleep via thermosensitive GABA transmission.

Genes and neural circuits coordinately regulate animal sleep. However, it remains elusive how these endogenous factors shape sleep upon environmental changes. Here, we demonstrate that Shaker (Sh)-expressing GABAergic neurons projecting onto dorsal fan-shaped body (dFSB) regulate temperature-adaptive sleep behaviors in Drosophila. Loss of Sh function suppressed sleep at low temperature whereas light and high temperature cooperatively gated Sh effects on sleep. Sh depletion in GABAergic neurons partially phenocopied Sh mutants. Furthermore, the ionotropic GABA receptor, Resistant to dieldrin (Rdl), in dFSB neurons acted downstream of Sh and antagonized its sleep-promoting effects. In fact, Rdl inhibited the intracellular cAMP signaling of constitutively active dopaminergic synapses onto dFSB at low temperature. High temperature silenced GABAergic synapses onto dFSB, thereby potentiating the wake-promoting dopamine transmission. We propose that temperature-dependent switching between these two synaptic transmission modalities may adaptively tune the neural property of dFSB neurons to temperature shifts and reorganize sleep architecture for animal fitness.

Bioinformatics services for analyzing massive genomic datasets.

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.

netGO: R-Shiny package for network-integrated pathway enrichment analysis.

SUMMARY: We present an R-Shiny package, netGO, for novel network-integrated pathway enrichment analysis. The conventional Fisher's exact test (FET) considers the extent of overlap between target genes and pathway gene-sets, while recent network-based analysis tools consider only network interactions between the two. netGO implements an intuitive framework to integrate both the overlap and networks into a single score, and adaptively resamples genes based on network degrees to assess the pathway enrichment. In benchmark tests for gene expression and genome-wide association study (GWAS) data, netGO captured the relevant gene-sets better than existing tools, especially when analyzing a small number of genes. Specifically, netGO provides user-interactive visualization of the target genes, enriched gene-set and their network interactions for both netGO and FET results for further analysis. For this visualization, we also developed a standalone R-Shiny package shinyCyJS to connect R-shiny and the JavaScript version of cytoscape. AVAILABILITY AND IMPLEMENTATION: netGO R-Shiny package is freely available from github, https://github.com/unistbig/netGO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PPM1A Controls Diabetic Gene Programming through Directly Dephosphorylating PPARγ at Ser273.

Peroxisome proliferator-activated receptor γ (PPARγ) is a master regulator of adipose tissue biology. In obesity, phosphorylation of PPARγ at Ser273 (pSer273) by cyclin-dependent kinase 5 (CDK5)/extracellular signal-regulated kinase (ERK) orchestrates diabetic gene reprogramming via dysregulation of specific gene expression. Although many recent studies have focused on the development of non-classical agonist drugs that inhibit the phosphorylation of PPARγ at Ser273, the molecular mechanism of PPARγ dephosphorylation at Ser273 is not well characterized. Here, we report that protein phosphatase Mg2+/Mn2+-dependent 1A (PPM1A) is a novel PPARγ phosphatase that directly dephosphorylates Ser273 and restores diabetic gene expression which is dysregulated by pSer273. The expression of PPM1A significantly decreases in two models of insulin resistance: diet-induced obese (DIO) mice and db/db mice, in which it negatively correlates with pSer273. Transcriptomic analysis using microarray and genotype-tissue expression (GTEx) data in humans shows positive correlations between PPM1A and most of the genes that are dysregulated by pSer273. These findings suggest that PPM1A dephosphorylates PPARγ at Ser273 and represents a potential target for the treatment of obesity-linked metabolic disorders.

Unleashing the full potential of Hsp90 inhibitors as cancer therapeutics through simultaneous inactivation of Hsp90, Grp94, and TRAP1.

The Hsp90 family proteins Hsp90, Grp94, and TRAP1 are present in the cell cytoplasm, endoplasmic reticulum, and mitochondria, respectively; all play important roles in tumorigenesis by regulating protein homeostasis in response to stress. Thus, simultaneous inhibition of all Hsp90 paralogs is a reasonable strategy for cancer therapy. However, since the existing pan-Hsp90 inhibitor does not accumulate in mitochondria, the potential anticancer activity of pan-Hsp90 inhibition has not yet been fully examined in vivo. Analysis of The Cancer Genome Atlas database revealed that all Hsp90 paralogs were upregulated in prostate cancer. Inactivation of all Hsp90 paralogs induced mitochondrial dysfunction, increased cytosolic calcium, and activated calcineurin. Active calcineurin blocked prosurvival heat shock responses upon Hsp90 inhibition by preventing nuclear translocation of HSF1. The purine scaffold derivative DN401 inhibited all Hsp90 paralogs simultaneously and showed stronger anticancer activity than other Hsp90 inhibitors. Pan-Hsp90 inhibition increased cytotoxicity and suppressed mechanisms that protect cancer cells, suggesting that it is a feasible strategy for the development of potent anticancer drugs. The mitochondria-permeable drug DN401 is a newly identified in vivo pan-Hsp90 inhibitor with potent anticancer activity.

Glucosylceramide synthase regulates adipo-osteogenic differentiation through synergistic activation of PPARγ with GlcCer.

Dysregulation of the adipo-osteogenic differentiation balance of mesenchymal stem cells (MSCs), which are common progenitor cells of adipocytes and osteoblasts, has been associated with many pathophysiologic diseases, such as obesity, osteopenia, and osteoporosis. Growing evidence suggests that lipid metabolism is crucial for maintaining stem cell homeostasis and cell differentiation; however, the detailed underlying mechanisms are largely unknown. Here, we demonstrate that glucosylceramide (GlcCer) and its synthase, glucosylceramide synthase (GCS), are key determinants of MSC differentiation into adipocytes or osteoblasts. GCS expression was increased during adipogenesis and decreased during osteogenesis. Targeting GCS using RNA interference or a chemical inhibitor enhanced osteogenesis and inhibited adipogenesis by controlling the transcriptional activity of peroxisome proliferator-activated receptor γ (PPARγ). Treatment with GlcCer sufficiently rescued adipogenesis and inhibited osteogenesis in GCS knockdown MSCs. Mechanistically, GlcCer interacted directly with PPARγ through A/B domain and synergistically enhanced rosiglitazone-induced PPARγ activation without changing PPARγ expression, thereby treatment with exogenous GlcCer increased adipogenesis and inhibited osteogenesis. Animal studies demonstrated that inhibiting GCS reduced adipocyte formation in white adipose tissues under normal chow diet and high-fat diet feeding and accelerated bone repair in a calvarial defect model. Taken together, our findings identify a novel lipid metabolic regulator for the control of MSC differentiation and may have important therapeutic implications.

Androgen-induced expression of DRP1 regulates mitochondrial metabolic reprogramming in prostate cancer.

Androgen receptor (AR) signaling plays a central role in metabolic reprogramming for prostate cancer (PCa) growth and progression. Mitochondria are metabolic powerhouses of the cell and support several hallmarks of cancer. However, the molecular links between AR signaling and the mitochondria that support the metabolic demands of PCa cells are poorly understood. Here, we demonstrate increased levels of dynamin-related protein 1 (DRP1), a mitochondrial fission mediator, in androgen-sensitive and castration-resistant AR-driven PCa. AR signaling upregulates DRP1 to form the VDAC-MPC2 complex, increases pyruvate transport into mitochondria, and supports mitochondrial metabolism, including oxidative phosphorylation and lipogenesis. DRP1 inhibition activates the cellular metabolic stress response, which involves AMPK phosphorylation, induction of autophagy, and the ER unfolded protein response, and attenuates androgen-induced proliferation. Additionally, DRP1 expression facilitates PCa cell survival under diverse metabolic stress conditions, including hypoxia and oxidative stress. Moreover, we found that increased DRP1 expression was indicative of poor prognosis in patients with castration-resistant PCa. Collectively, our findings link androgen signaling-mediated mitochondrial dynamics to metabolic reprogramming; moreover, they have important implications for understanding PCa progression.

Transcriptional Regulator TonEBP Mediates Oxidative Damages in Ischemic Kidney Injury.

TonEBP (tonicity-responsive enhancer binding protein) is a transcriptional regulator whose expression is elevated in response to various forms of stress including hyperglycemia, inflammation, and hypoxia. Here we investigated the role of TonEBP in acute kidney injury (AKI) using a line of TonEBP haplo-deficient mice subjected to bilateral renal ischemia followed by reperfusion (I/R). In the TonEBP haplo-deficient animals, induction of TonEBP, oxidative stress, inflammation, cell death, and functional injury in the kidney in response to I/R were all reduced. Analyses of renal transcriptome revealed that genes in several cellular pathways including peroxisome and mitochondrial inner membrane were suppressed in response to I/R, and the suppression was relieved in the TonEBP deficiency. Production of reactive oxygen species (ROS) and the cellular injury was reproduced in a renal epithelial cell line in response to hypoxia, ATP depletion, or hydrogen peroxide. The knockdown of TonEBP reduced ROS production and cellular injury in correlation with increased expression of the suppressed genes. The cellular injury was also blocked by inhibitors of necrosis. These results demonstrate that ischemic insult suppresses many genes involved in cellular metabolism leading to local oxidative stress by way of TonEBP induction. Thus, TonEBP is a promising target to prevent AKI.

GScluster: network-weighted gene-set clustering analysis.

BACKGROUND: Gene-set analysis (GSA) has been commonly used to identify significantly altered pathways or functions from omics data. However, GSA often yields a long list of gene-sets, necessitating efficient post-processing for improved interpretation. Existing methods cluster the gene-sets based on the extent of their overlap to summarize the GSA results without considering interactions between gene-sets. RESULTS: Here, we presented a novel network-weighted gene-set clustering that incorporates both the gene-set overlap and protein-protein interaction (PPI) networks. Three examples were demonstrated for microarray gene expression, GWAS summary, and RNA-sequencing data to which different GSA methods were applied. These examples as well as a global analysis show that the proposed method increases PPI densities and functional relevance of the resulting clusters. Additionally, distinct properties of gene-set distance measures were compared. The methods are implemented as an R/Shiny package GScluster that provides gene-set clustering and diverse functions for visualization of gene-sets and PPI networks. CONCLUSIONS: Network-weighted gene-set clustering provides functionally more relevant gene-set clusters and related network analysis.

Biclustering analysis of transcriptome big data identifies condition-specific microRNA targets.

We present a novel approach to identify human microRNA (miRNA) regulatory modules (mRNA targets and relevant cell conditions) by biclustering a large collection of mRNA fold-change data for sequence-specific targets. Bicluster targets were assessed using validated messenger RNA (mRNA) targets and exhibited on an average 17.0% (median 19.4%) improved gain in certainty (sensitivity + specificity). The net gain was further increased up to 32.0% (median 33.4%) by incorporating functional networks of targets. We analyzed cancer-specific biclusters and found that the PI3K/Akt signaling pathway is strongly enriched with targets of a few miRNAs in breast cancer and diffuse large B-cell lymphoma. Indeed, five independent prognostic miRNAs were identified, and repression of bicluster targets and pathway activity by miR-29 was experimentally validated. In total, 29 898 biclusters for 459 human miRNAs were collected in the BiMIR database where biclusters are searchable for miRNAs, tissues, diseases, keywords and target genes.

The E3 ubiquitin ligase TRIM25 regulates adipocyte differentiation via proteasome-mediated degradation of PPARγ.

Peroxisome proliferator-activated receptor gamma (PPARγ) is a ligand-dependent transcription factor that regulates adipocyte differentiation and glucose homeostasis. The transcriptional activity of PPARγ is regulated not only by ligands but also by post-translational modifications (PTMs). In this study, we demonstrate that a novel E3 ligase of PPARγ, tripartite motif-containing 25 (TRIM25), directly induced the ubiquitination of PPARγ, leading to its proteasome-dependent degradation. During adipocyte differentiation, both TRIM25 mRNA and protein expression significantly decreased and negatively correlated with the expression of PPARγ. The stable expression of TRIM25 reduced PPARγ protein levels and suppressed adipocyte differentiation in 3T3-L1 cells. In contrast, the specific knockdown of TRIM25 increased PPARγ protein levels and stimulated adipocyte differentiation. Furthermore, TRIM25-knockout mouse embryonic fibroblasts (MEFs) exhibited an increased adipocyte differentiation capability compared with wild-type MEFs. Taken together, these data indicate that TRIM25 is a novel E3 ubiquitin ligase of PPARγ and that TRIM25 is a novel target for PPARγ-associated metabolic diseases.

Efficient pathway enrichment and network analysis of GWAS summary data using GSA-SNP2.

Pathway-based analysis in genome-wide association study (GWAS) is being widely used to uncover novel multi-genic functional associations. Many of these pathway-based methods have been used to test the enrichment of the associated genes in the pathways, but exhibited low powers and were highly affected by free parameters. We present the novel method and software GSA-SNP2 for pathway enrichment analysis of GWAS P-value data. GSA-SNP2 provides high power, decent type I error control and fast computation by incorporating the random set model and SNP-count adjusted gene score. In a comparative study using simulated and real GWAS data, GSA-SNP2 exhibited high power and best prioritized gold standard positive pathways compared with six existing enrichment-based methods and two self-contained methods (alternative pathway analysis approach). Based on these results, the difference between pathway analysis approaches was investigated and the effects of the gene correlation structures on the pathway enrichment analysis were also discussed. In addition, GSA-SNP2 is able to visualize protein interaction networks within and across the significant pathways so that the user can prioritize the core subnetworks for further studies. GSA-SNP2 is freely available at https://sourceforge.net/projects/gsasnp2.

Gene dispersion is the key determinant of the read count bias in differential expression analysis of RNA-seq data.

BACKGROUND: In differential expression analysis of RNA-sequencing (RNA-seq) read count data for two sample groups, it is known that highly expressed genes (or longer genes) are more likely to be differentially expressed which is called read count bias (or gene length bias). This bias had great effect on the downstream Gene Ontology over-representation analysis. However, such a bias has not been systematically analyzed for different replicate types of RNA-seq data. RESULTS: We show that the dispersion coefficient of a gene in the negative binomial modeling of read counts is the critical determinant of the read count bias (and gene length bias) by mathematical inference and tests for a number of simulated and real RNA-seq datasets. We demonstrate that the read count bias is mostly confined to data with small gene dispersions (e.g., technical replicates and some of genetically identical replicates such as cell lines or inbred animals), and many biological replicate data from unrelated samples do not suffer from such a bias except for genes with some small counts. It is also shown that the sample-permuting GSEA method yields a considerable number of false positives caused by the read count bias, while the preranked method does not. CONCLUSION: We showed the small gene variance (similarly, dispersion) is the main cause of read count bias (and gene length bias) for the first time and analyzed the read count bias for different replicate types of RNA-seq data and its effect on gene-set enrichment analysis.

Memory and synaptic plasticity are impaired by dysregulated hippocampal O-GlcNAcylation.

O-GlcNAcylated proteins are abundant in the brain and are associated with neuronal functions and neurodegenerative diseases. Although several studies have reported the effects of aberrant regulation of O-GlcNAcylation on brain function, the roles of O-GlcNAcylation in synaptic function remain unclear. To understand the effect of aberrant O-GlcNAcylation on the brain, we used Oga+/- mice which have an increased level of O-GlcNAcylation, and found that Oga+/- mice exhibited impaired spatial learning and memory. Consistent with this result, Oga+/- mice showed a defect in hippocampal synaptic plasticity. Oga heterozygosity causes impairment of both long-term potentiation and long-term depression due to dysregulation of AMPA receptor phosphorylation. These results demonstrate a role for hyper-O-GlcNAcylation in learning and memory.