Search bioRxiv⌕ Search

SEARCH · Search bioRxiv

Results for “gene expression”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4Linked to original sources
bioRxiv2022

Robustness of organ morphology is associated with modules of co-expressed genes related to plant cell wall

Control of organ morphology is a fundamental feature of living organisms. There is, however, observable variation in organ size and shape within a given genotype. Taking the sepal of Arabidopsis as a model, we investigated whether we can use variability of gene expression alongside variability of organ morphology to identify gene regulatory networks potentially involved in organ size and shape determination. We produced a dataset composed of morphological parameters and genome-wide transcriptome obtained from 27 individual sepals from wild-type plants with nearly identical genetic backgrounds, environment, and developmental stage. Sepals exhibited appreciable variability in both morphology and transcriptome, with response to stimulus genes and cell-wall related genes displaying high variability in expression. We additionally identified five modules of co-expressed genes which correlated significantly with morphology, revealing biologically relevant gene regulatory networks. Interestingly, cell-wall related genes were overrepresented in two of the top three modules. Overall, our work highlights the benefit of using coupled variation in gene expression and phenotype in wild-type plants to shed light on the mechanisms underlying organ size and shape determination. Although causality between gene expression and sepal morphology has not been established, our approach opens the way to informed analysis for mutant characterization and functional studies.

plant biology↗
bioRxiv2019

Identification of differentially expressed genes in hepatocellular carcinoma by integrated bioinformatic analysis

Hepatocellular carcinoma is one of the most common tumors in the world and has a high mortality rate. This study elucidates the mechanism of hepatocellular carcinoma- (HCC) related development. The HCC gene expression profile (GSE54238, GSE84004) was downloaded from Gene Expression Omnibus for comprehensive analysis. A total of 359 genes were identified, of which 195 were upregulated and 164 were downregulated. Analysis of the condensed results showed that \"extracellular allotrope\" is a substantially enriched term. \"Cell cycle\", \"metabolic pathway\" and \"DNA replication\" are three significantly enriched Kyoto Encyclopedia of Genes and Genomespathways. Subsequently, a protein-protein interaction network was constructed. The most important module in the protein-protein interaction network was selected for path enrichment analysis. The results showed that CCNA2, PLK1, CDC20, UBE2C and AURKA were identified as central genes, and the expression of these five hub genes in liver cancer was significantly increased in The Cancer Genome Atlas. Univariate regression analysis was also performed to show that the overall survival and disease-free survival of patients in the high expression group were longer than in the expression group. In addition, genes in important modules are mainly involved in \"cell cycle\", \"DNA replication\" and \"oocyte meiosis\" signaling pathways. Finally, through upstream miRNA analysis, mir-300 and mir-381-3p were found to coregulate CCNA2, AURKA and UBE2C. These results provide a set of targets that can help researchers to further elucidate the underlying mechanism of liver cancer.

genetics↗
bioRxiv2024

SPRITE: improving spatial gene expression imputation with gene and cell networks

Spatially resolved single-cell transcriptomics have provided unprecedented insights into gene expression in situ, particularly in the context of cell interactions or organization of tissues. However, current technologies for profiling spatial gene expression at single-cell resolution are generally limited to the measurement of a small number of genes. To address this limitation, several algorithms have been developed to impute or predict the expression of additional genes that were not present in the measured gene panel. Current algorithms do not leverage the rich spatial and gene relational information in spatial transcriptomics. To improve spatial gene expression predictions, we introduce SPRITE (Spatial Propagation and Reinforcement of Imputed Transcript Expression) as a meta-algorithm that processes predictions obtained from existing methods by propagating information across gene correlation networks and spatial neighborhood graphs. SPRITE improves spatial gene expression predictions across multiple spatial transcriptomics datasets. Furthermore, SPRITE predicted spatial gene expression leads to improved clustering, visualization, and classification of cells. SPRITE is available as a software package and can be used in spatial transcriptomics data analysis to improve inferences based on predicted gene expression.

bioinformatics↗
bioRxiv2023

maGENEgerZ: An Efficient AI-Based Framework Can Extract More Expressed Genes and Biological Insights Underlying Breast Cancer Drug Response Mechanism

Understanding breast cancer drug response mechanism can play a crucial role in improving the treatment outcomes and survival rates. Existing bioinformatics-based approaches are far from perfect and do not adopt computational methods based on advanced artificial intelligence concepts. Therefore, we introduce a novel computational framework based on an efficient support vector machines (esvm) working as follows. First, we downloaded and processed three gene expression datasets related to breast cancer responding and non-responding to the treatments from the gene expression omnibus (GEO) according to the following GEO accession numbers: GSE130787, GSE140494, and GSE196093. Our method esvm is formulated as a constrained optimization problem in the dual form as a function of {lambda}. We recover the importance of each gene as a function of {lambda}, y, and x. Then, we select p genes out of n, provided as input to enrichment analysis tools, Enrichr and Metascape. Compared to existing baseline methods including deep learning, results demonstrate superiority and efficiency of esvm achieving high performance results and having more expressed genes in well-established breast cancer cell lines including MD-MB231, MCF7, and HS578T. Moreover, esvm is able to identify (1) various drugs including clinically approved ones (e.g., tamoxifen and erlotinib); (2) seventy-four unique genes (including tumor suppression genes such as TP53 and BRCA1); and (3) thirty-six unique TFs (including SP1 and RELA). These results have been reported to be linked to breast cancer drug response mechanism, progression, and metastasizing. Our method is available publicly in the maGENEgerZ web server at https://aibio.shinyapps.io/maGENEgerZ/.

bioinformatics↗
bioRxiv2024

The Condensin II Complex Regulates the Expression of Essential Gene Expression Programs During Erythropoiesis

Erythropoiesis is characterized by dramatic changes in gene expression in the context of a cell that is rapidly proliferating while simultaneously condensing its nucleus in anticipation of enucleation. The mechanisms that maintain high level expression of erythroid genes and promote nuclear condensation remain poorly understood. Condensin II is a ring-like complex that promotes mitotic chromatin condensation and has roles in regulating interphase chromatin architecture and gene expression. We interrogated the role of Condensin II in erythropoiesis using an erythroid-specific deletion of the Condensin II subunit, Ncaph2. Ncaph2 loss resulted in severe embryonic anemia with lethality at embryonic day 13.5. Ncaph2 mutant erythroid cells had dysregulated maturation and disrupted cell cycle progression, but surprisingly Ncaph2 was dispensable for nuclear condensation. Genomic studies revealed that Ncaph2 occupied the promoter of key erythroid and cell cycle genes that were downregulated following Ncaph2 loss. Together, our results demonstrate an essential role for Ncaph2 in the gene expression programs that regulate cell cycle progression and erythroid differentiation, and identify a key role for the Condensin II complex in the regulation of a lineage-specific differentiation program. Summary StatementThe Condensin II complex regulates cell cycle progression and erythroid differentiation, but is dispensable for nuclear condensation during terminal erythroid maturation.

genomics↗
bioRxiv2022

Patterns of gene expression and allele-specific expression vary among macular tissues and clinical stages of Age-related Macular Degeneration

Age-related macular degeneration (AMD) is a complex neurodegenerative disease and is the leading cause of blindness in the aging population. Early AMD is characterized by drusen in the macula and causes minimal changes in visual function. The later stages are responsible for the majority of visual impairment and blindness and can be either manifest as geographic atrophy (dry) or neovascular disease (wet). Available medicines are directed against the wet form and do not cure vision loss. Therefore, it is imperative to identify preventive and therapeutic targets. As the mechanism for AMD is unclear, we aim to interrogate the disease-affected tissue - the macular neural retina and macular retina pigment epithelium (RPE)/choroid. We investigated differentially expressed genes expression (DEG) across the clinical stages of AMD in meticulously dissected and phenotyped eyes using a standardized published protocol (Owen et al., 2019). Donor eyes (n=27) were obtained from Caucasian individuals with an age range of 60-94 and 63% were male, and tissue from the macula RPE/choroid and macula neural retina were taken from the same eye. Donor eyes were recovered within 6 hours post mortem interval time to ensure maximal preservation of RNA quality and accuracy of diagnosis. Eyes were then phenotyped by retina experts using multi modal imaging (fundus photos and SD-OCT). Utilizing DESeq2, followed PCA, Benjamini Hochberg adjustment to control for the false discovery rate, and Bonferonni correction for the number of paired comparisons: a total of 26,650 genes were expressed in the macula RPE/choroid and/or macula retina among which significant differential expression was found for 1,204 genes between neovascular AMD and normal eyes, 40 genes between intermediate AMD and normal eyes, and 1,194 genes between intermediate AMD and neovascular AMD. A comparison of intermediate AMD versus normal eyes included TCN2, PON1, IFI6, GPR123, and TIMD4 as being some of the most significant DEGs in the macula RPE/choroid. A comparison of neovascular AMD versus normal eyes included SLC1A2, SLC24A1, SCAMP5, PTPRN, and SEMA7A as being some of the most significant DEGs in the macula RPE/choroid. Top pathways of DEGs in the macular RPE/choroid identified through Ingenuity Pathway Analysis (IPA) for the comparison of intermediate AMD with normal eyes were interferon signaling and Th1 and Th2 activation, while those for the comparison of neovascular AMD with normal eyes were the phototransduction and SNARE signaling pathways. Allele-specific expression (ASE) in coding regions of previously reported AMD risk loci identified by GWAS (Fritsche et al, 2016) revealed significant ASEs for C3 rs2230199 and CFH rs1061170 in the macula RPE/choroid for normal eyes and intermediate AMD, and for CFH rs1061147 in the macula RPE/choroid for normal eyes and intermediate and neovascular AMD. An investigation of the 34 established AMD risk loci revealed that 75% of them were significantly differentially expressed between normal macular RPE/choroid and macular neural retina, with 75% of these loci showing higher expression in the RPE. Similarly, disease state differences for the GWAS loci were only found to be statistically differentially expressed in the macular RPE/choroid. Moreover, the known coding variants in the previously identified GWAS loci including, CFH, C3, CFB, demonstrated ASE across AMD clinical stages in the macular RPE/choroid and not in the neural retina. These data at the bulk level underscore the importance of the RPE/choroid to AMD pathophysiology. While many bulk RNASeq data sets are publicly available, to the best of our knowledge this is one of the first publicly available datasets with both maculae RPE/choroid and macula neural retina from the same well phenotyped donor eye(s) where the macula is separated from the periphery. Our findings also underscore the importance of studying both macular tissue types to gain a full understanding of mechanisms leading to AMD. Our results provide insights into underlying biological mechanisms that may differentiate the disease subtypes and into the tissues affected by the disease.

genomics↗
bioRxiv2021

Patient derived models of bladder cancer amplify tumor specific gene expression compared to surgical specimen while maintaining gene expression of molecular subtype and epithelial mesenchymal transition markers

Patient derived models (PDMs) are a powerful tool to study preclinical responses. However, the benefits of each model have not been compared head-to-head when models are derived from the same surgical specimen. PDMs derived from surgical specimens were established as xenografts (PDX), organoids (PDO), and spheroids (PDS). PDMs were molecularly characterized by RNA sequencing. Differential gene expression was determined between the PDMs and surgical specimens. Surgical specimens had the most differentially expressed genes reflecting loss of immune and stromal compartments in PDMs. PDMs and surgical specimens were clustered using the Euclidian distance analysis to test model fidelity. PDMs upregulated a clear, patient-specific bladder cancer signal. Overall, the molecular profiles of PDXs were the most similar to the matching patient surgical specimen than the PDO and PDS from that patient. The epithelial mesenchymal transition (EMT) gene expression profile is maintained in the PDMs showing the persistence of EMT in both in vivo and in vitro model setting. The consensus molecular subtype was determined in order to compare PDMs to each other and their matching surgical specimen, and only surgical specimens with Basal/Squamous or Luminal Papillary molecular subtype established PDMs. Patient derived models reduce tumor heterogeneity and allow analysis of specific tumor compartments while maintaining the gene expression profile representative of the original tumor.

cancer biology↗
bioRxiv2021

The N-terminal and central domains of CoV-2 nsp1 play key functional roles in suppression of cellular gene expression and preservation of viral gene expression

Nonstructural protein 1 (nsp1) is the first viral protein synthesized during coronavirus (CoV) infection and is a key virulence factor that dampens the innate immune response. It restricts cellular gene expression through a combination of inhibiting translation by blocking the mRNA entry channel of the 40S ribosomal subunit and by promoting mRNA degradation. We performed a detailed structure-guided mutational analysis of CoV-2 nsp1 coupled with in vitro and cell-based functional assays, revealing insight into how it coordinates these activities against host but not viral mRNA. We found that residues in the N-terminal and central regions of nsp1 not involved in docking into the 40S mRNA entry channel nonetheless stabilize its association with the ribosome and mRNA, thereby enhancing its restriction of host gene expression. These residues are also critical for the ability of mRNA containing the CoV-2 leader sequence to escape translational repression. Notably, we identify CoV-2 nsp1 mutants that gain the ability to repress translation of viral leader-containing transcripts. These data support a model in which viral mRNA binding functionally alters the association of nsp1 with the ribosome, which has implications for drug targeting and understanding how engineered or emerging mutations in CoV-2 nsp1 could attenuate the virus.

molecular biology↗
bioRxiv2017

GeoDiver: Differential Gene Expression Analysis & Gene-Set Analysis For GEO Datasets

SummaryGeoDiver is an online web application for performing Differential Gene Expression Analysis (DGEA) and Generally Applicable Gene-set Enrichment Analysis (GAGE) on gene expression datasets from the publicly available Gene Expression Omnibus (GEO). The output produced includes numerous high quality interactive graphics, allowing users to easily explore and examine complex datasets instantly. Furthermore, the results produced can be reviewed at a later date and shared with collaborators.\n\nAvailabilityGeoDiver is freely available online at http://www.geodiver.co.uk. The source code is available on Github: https://github.com/GeoDiver/GeoDiver and a docker image is available for easy installation.

bioinformatics↗
bioRxiv2026

The rabies virus interferon antagonist P protein selectively modulates interferon signalling to inhibit antiviral gene expression while supporting proviral gene expression

Type-I IFNs mediate the principle antiviral response of cells by controlling the expression of hundreds of IFN-regulated genes (IRGs), many of which have antiviral functions. The best understood mediators of IFN signalling are STAT1 and STAT2, and STAT1/2-dependent gene induction is conventionally viewed as the primary outcome of type-I IFN signalling. To overcome the IFN response, viruses express proteins called IFN-antagonists, which target IFN signalling pathways (e.g. rabies virus P-protein (RABV-P) binds and inhibits IFN-activated STAT1/2) and so are typically considered to mediate shutdown of the IFN response. However, IFN signalling is not exclusively antiviral, with many IRGs reported to be required for or to facilitate infection by certain viruses. How viruses coordinate the apparent need to suppress certain antiviral IRGs, while presumably permitting the expression of others, including proviral IRGs is poorly defined. However, it has been shown that type-I IFN can activate multiple pathways other than classical STAT1/2, so discriminatory targeting of specific pathways by IFN-antagonists may enable highly selective regulation of distinct IRGs, dependent on the requirements of the specific virus. Here, we analyse the global effects of RABV-P protein on the IFN-regulated transcriptome. We confirm that IFN not only stimulates (IFN-stimulated genes, ISGs) but also represses (IFN-repressed genes, IRepGs) a large number of IRGs. Notably, our data indicate that RABV-P protein can antagonize both the IFN-dependent stimulation and repression of certain ISGs and IRepGs, without significantly impacting the expression of large proportion of IRGs. Antagonized ISGs included classical antiviral genes, while non-antagonized ISGs include genes with pro-viral effects on RABV. Transcription factor analysis indicated that RABV-P antagonizes STAT1/2-regulated IRGs, but not IRGs regulated by other pathways including MAP-kinase pathways, which are important to process such as cell survival and inflammatory response. These data indicate that selective modulation rather than global inhibition of IFN-signalling has beneficial outcomes for replication. The data also support the significance of IRepGs, and their modulation by IFN antagonists in viral infection. Significance StatementThe ability of viruses to evade immunity is critical to disease and so presents targets for the development of interventions. The principle antiviral response of cells is mediated by interferons (IFNs), which activate STAT proteins to induce hundreds of genes including antiviral genes. Viruses counter this by expressing IFN-antagonist proteins, many of which directly inhibit STATs. IFN-antagonists are typically considered to shut down IFN responses, but many IRGs have pro-viral functions. How viruses coordinate the apparent need to antagonise some IRGs but not others are poorly understood. Using a well-characterised viral IFN-antagonist, we find that by selectively targeting certain IFN-activated pathways, IFN-antagonists can inhibit effects of IFN on specific subsets of IRGs (including antiviral genes) without affecting others (including proviral genes); thus, IFN-antagonists may be redefined as selective IFN-modulators.

systems biology↗
bioRxiv2019

Transcription factor motifs in anterior insula gene-expression in mood disorder

BackgroundMood disorders represent a major cause of morbidity and mortality worldwide but the brain-related molecular pathophysiology in mood disorders remains largely undefined. MethodsBecause the anterior insula is reduced in volume in patients with mood disorders, RNA was extracted from postmortem mood disorder samples and compared with unaffected control samples for RNA-sequencing identification of differentially expressed genes (DEGs) in a) bipolar disorder (BD; n=37) versus (vs.) controls (n=33), and b) major depressive disorder (MDD n=30) vs controls, and c) low vs. high Axis-I comorbidity (a measure of cumulative psychiatric disease burden). Given the regulatory role of transcription factors (TFs) in gene expression via specific-DNA-binding domains (motifs), we used JASPAR TF binding database to identify TF-motifs. ResultsWe found that DEGs in BD vs. controls, MDD vs. controls, and high vs. low Axis-I comorbidity were associated with TF-motifs that are known to regulate expression of toll-like receptor genes, cellular homeostatic-control genes, and genes involved in embryonic, cellular/organ and brain development. DiscussionRobust imaging-guided transcriptomics (i.e., using meta-analytic imaging results to guide independent post-mortem dissection for RNA-sequencing) was applied by targeting the gray matter volume reduction in the anterior insula in mood disorders, to guide independent postmortem identification of TF motifs regulating DEG. TF motifs were identified for immune, cellular, embryonic and neurodevelopmental processes. ConclusionOur findings of TF-motifs that regulate the expression of immune, cellular homeostatic-control, and developmental genes provides novel information about the hierarchical relationship between gene regulatory networks, the TFs that control them, and proximate underlying neuroanatomical phenotypes in mood disorders.

genomics↗
bioRxiv2023

Sex-Specific Developmental Gene Expression Atlas Unveils Dimorphic Gene Networks in C. elegans

Sex-specific traits and behaviors emerge during development by the acquisition of unique properties in the nervous system of each sex. However, the genetic events responsible for introducing these sex-specific features remain poorly understood. In this study, we created a comprehensive gene expression atlas for both sexes of the nematode Caenorhabditis elegans across development. By comparing the transcriptome of pure populations of hermaphrodites and males from early larval stages to adulthood, we discovered numerous differentially expressed genes, including neuronal gene families like transcription factors, neuropeptides, and GPCRs. We identified INS-39, an insulin-like peptide, as a prominent male-biased gene expressed specifically in ciliated sensory neurons. We show that INS-39 serves as an early-stage male marker, facilitating the effective isolation of males in high-throughput experiments. Through complex and sex-specific regulation, ins-39 plays pleiotropic sexually-dimorphic roles in temperature sensation, survival in cold temperatures, resilience against high hydrogen peroxide levels, and dauer entry, while also playing a shared, dimorphic role in early life stress. This study offers a comparative sexual and developmental gene expression database for C. elegans, which will facilitate research into the genetic regulation of the sexual development of other organisms. Furthermore, it highlights conserved candidate genes that may underlie the sexually-dimorphic manifestation of different human diseases.

neuroscience↗
bioRxiv2021

KDM6A knockout in human iPSCs alters the genome-wide histone methylation profile at active and poised enhancers, activating expression of ectoderm gene expression pathways.

KDM6A is a histone demethylase, known to remove methyl moieties at the lysine residues of histone 3-labeled (H3K27me3) poised enhancers and bivalent promoters, which regulates gene expression during the differentiation of embryonic stem cells and tissue-specific development. However, while tissue- and disease-specific analyses have been performed, little is known about the location and consequences on gene expression of these regulatory regions in human pluripotent cells. Poised enhancers and bivalent promoters function in a coordinated fashion during development, which requires timely and efficient histone modifications. Identification of KDM6A-specific gene-regulatory domains is important for understanding the developmental mechanisms controlled by these histone modifications in pluripotency. In this study, we compared genome-wide histone modification and gene expression differences in isogenic wild type and cas9-mediated KDM6A knockout human induced pluripotent stem cells (hiPSC) lines. Here, we report that the absence of KDM6A does not alter the pluripotent phenotype but does substantially alter the histone modification profile at poised and active enhancers, resulting in decreased expression of associated COMPASS complex genes KMT2C and KMT2D and subsequently increasing the expression of gene pathways involved in ectoderm differentiation.

genomics↗
bioRxiv2026

GRNPred: A Multimodal Graph Transformer with Masked Gene Expression Pretraining for Gene Regulatory Network Inference

Gene regulatory network (GRN) inference is a fundamental problem in systems biology, aiming to identify transcription factor (TF)-target gene interactions from high-dimensional gene expression data. Accurate GRN reconstruction remains challenging due to limited labeled regulatory data, severe class imbalance, and the complex, nonlinear nature of transcriptional regulation. Here, we introduce GRNPred, a multimodal graph transformer framework for robust GRN inference that integrates gene expression, functional annotations, semantic gene descriptions, regulatory binding motif priors, and gene co-expression network topology. GRNPred follows a two-stage training strategy. In the first self-supervised pretraining phase, a graph transformer encoder is trained on TF-centered gene co-expression subgraphs using masked gene-expression reconstruction, enabling the model to learn transcriptional context from unlabeled data. In the second supervised fine-tuning stage, the pretrained encoder is finetuned for supervised TF-target edge prediction using available regulatory annotations. Transformer-based attention allows GRNPred to capture long-range and context-dependent regulatory interactions that are difficult to model with conventional graph neural networks. Extensive evaluation across 7 benchmark datasets and 3 regulatory network constructions demonstrates that GRNPred consistently outperforms state-of-the-art GRN inference methods, achieving AUROC scores of up to 0.94 and AUPRC scores of up to 0.93, while maintaining strong robustness across diverse biological contexts.

bioinformatics↗
bioRxiv2025

Mapping gene expression across the microbiome-gut-brain axis of germ- and specific pathogen-free mice

Perturbation of the gut microbiota has been implicated in neurological diseases via communication across the microbiome-gut-brain axis. As a result, the discovery of mechanisms underlying interaction across this axis are becoming increasingly important. The germ-free (GF) mouse model has enabled an improved understanding of the influence of the gut microbiota on brain development and function. By utilising an advanced spatial profiling approach, we determined transcriptional changes in the brain, improving our understanding of how brain cells function and interact within their microenvironment in the absence of microbiome influence. Targeted regions of interest were selected based on brain regions implicated in neurological disease or reported structural differences between GF mouse brains and those of colonized mice. In the hippocampus 276 differentially expressed genes (DEGs) were identified, 345 DEGs in the thalamus, and 21 DEGs in pons. Contrastingly we identified only 2 DEGs in the midbrain and 4 in the medulla oblongata, with no DEGs in the cerebellum or corpus callosum. This data provides an overview of gut microbiota influence on gene expression in the brain, highlighting multiple genes of interest for further investigation in the context of microbiome influence on brain function and their potential relevance to neurological disease.

microbiology↗
bioRxiv2024

GAGER: gene regulatory network assisted gene expression restoration

Gene regulatory networks are crucial for cellular function, and disruptions in transcription factor (TF) regulation often lead to diseases. However, identifying TFs to transition a source cell state to a desired target state remains challenging. We present a method to identify key TFs whose perturbation can restore gene expressions in a source state to target levels. Its effectiveness is demonstrated on datasets from yeast TF knockouts, cardiomyocytes from hypoplastic left heart syndrome patients, and mouse models of neurodegeneration. The method accurately identifies knocked-out TFs in the yeast dataset. In the cardiomyocyte dataset, it pinpoints TFs that, though not differentially expressed in many cases, exert significant regulatory influence on downstream differentially expressed genes. Finally, in the mouse model dataset, it identifies disease stage-specific TFs, improving similarity between healthy and diseased states at various time points. Unlike traditional approaches relying on differential expression analysis, our method uses network-based prioritization for more targeted and biologically relevant TF selection. These findings highlight its potential as a therapeutic tool for precise TF targeting to normalize gene expressions in diseased states.

bioinformatics↗
bioRxiv2025

Direct single cell-type gene expression analysis in Whole blood: Novel ratio-based gene expression biomarkers using 2 novel monocyte reference genes (PSAP and CTSS) for monitoring bacterial infection

BackgroundTo determine single cell-type specific gene expression in peripheral blood (PB) requires either prior labour-intense cell sorting or expensive single-cell RNA sequencing. We developed and validated a novel ratio-based biomarker (RBB) called Direct Leukocyte Subpopulation-Transcript Abundance (DIRECT LS-TA) assay that allows quantification of monocyte-specific gene expression directly from peripheral blood samples without cell sorting. MethodsThe DIRECT LS-TA method leverages known cell-type proportions and differential gene expression profiles among leukocyte subpopulations (e.g. monocytes, lymphocytes and granulocytes) to identify monocyte-informative genes. We shortlisted genes that had 2.5-fold higher expression in isolated monocytes compared to PB samples, indicating >50% transcript of genes in PB are contributed by monocytes alone. Public gene expression datasets were used to generate a list of monocyte informative genes with which DIRECT LS-TA assay is applicable in PB samples. PSAP and CTSS were identified as the monocyte informative reference genes, based on low biological variation (CV <12%) and high monocyte specificity. They were used as the denominator and together with another monocyte informative target gene as the numerator, the value of this new DIRECT LS-TA can be determined which is a kind of ratio-based biomarker (RBB). The clinical utility was the differentiation of patients with bacterial infection from control subjects in a discovery dataset and 4 other replication datasets. Methods to convert DIRECT LS-TA results to multiple of control median (MoM) provided approximations to delta-delta CT values of relative quantification commonly used in qPCR or digital PCR assays. ResultsOver 50 monocyte-informative genes were identified, including key immune response genes like IFI44L, IL1B, VNN1 and NFKBIZ. DIRECT LS-TA results showed excellent correlation with the gold standard results, gene expression in isolated monocyte expression (R2=0.55-0.97). Then, DIRECT LS-TA of these 50 target genes were evaluated to identify the best RBB to detect the host response to bacterial infection. Monocyte DIRECT LS-TA VNN1 RBB showed consistent upregulation across five independent datasets (median fold change 2.7-fold, p<10-8) with strong diagnostic performance (AUC=0.84-0.99). The expected corresponding delta-delta CT value is more than 1.4 cycle which can be reliably measured by qPCR. Additional monocyte-informative genes including NLRC4, CYP1B1, PFKFB3, LILRA5, NFKBIA, and NFKBIZ also demonstrated significant diagnostic ability (AUC>0.8). ConclusionsThe DIRECT LS-TA method (as a simple RBB) provides reliable quantification of monocyte-specific gene expression directly from whole blood samples without cell separation. The robust performance in bacterial infection diagnosis demonstrates its potential clinical utility for rapid infection differentiation and informed antibiotic stewardship. DIRECT LS-TA will emerge as a new kind of in vitro diagnostics (IVD) which can convey single cell-type gene expression information from PB samples. The new kind of IVD and uniqueness of the information, together with the ease of implementation will make it very useful in clinics

immunology↗
bioRxiv2023

Transcriptional profiling of populations in the clam Ruditapes decussatus suggests genetically determined differentiation in gene-expression along parallel temperature gradients and between races of the Atlantic Ocean and West Mediterranean sea

Ongoing ocean warming due to climate change poses new challenges for marine life and its exploitation. We have used transcriptomics to find genetically-based responses to increased temperature in natural populations of the marine clam Ruditapes decussatus living along parallel thermal gradients in southern Europe. Clams of the Atlantic and West Mediterranean races were collected in a northern (cool) and a southern (warm) localities. The animals were kept in running seawater in the warm, Atlantic southern locality for a 15-week period, during which water temperature raised to typical southern European summer values. After this period, the expression profile was obtained for a total of 34 clams and 11,025 probes by means of an oligonucleotide microarray. We found distinct transcriptional patterns for each population based on a total of 553 differentially expressed genes (DEG), indicating innate differences which probably have a genetic basis. Race and latitude contributed significantly to gene expression differences, with very different sets of DEG. A gene ontology analysis showed that races differed mainly at genes involved in ribosomal function and protein biosynthesis, while genes related to glutathione metabolism and ATP synthesis in the mitochondria were the most outstanding as to north/south transcriptional differences.

genomics↗