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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2021

Differential gene expression by RNA-Seq in Sigma-2 Receptor/TMEM97 knockout cells reveals its role in complement activation and SARS-CoV-2 viral uptake

Our lab has recently shown that the Sigma-2 Receptor/Transmembrane Protein 97 (sigma-2R/TMEM97) interacts with the low-density lipoprotein receptor (LDLR) and facilitates the enhanced uptake of various ligands including lipoproteins and intrinsically disordered proteins. TMEM97 has been recently been shown to interact with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral proteins, highlighting its potential involvement with viral entry into the cell. We hypothesized that sigma-2R/TMEM97 may play a role in facilitating viral uptake, and with the regulation of inflammatory and thrombotic pathways that are involved with viral infection. In this study, we identified the top differentially expressed genes upon the knockout of sigma-2R/TMEM97, and analyzed the genes involved with the inflammatory and thrombotic cascades, effects that are observed in patients infected with SARS-CoV-2. We found that the ablation of sigma-2R/TMEM97 resulted in an increase in Complement Component 4 Binding Protein (C4BP) proteins, at both the translational and transcriptional levels. We also showed that sigma-2R/TMEM97 interacts with the cellular receptor for SARS-CoV-2, the human angiotensin-converting enzyme 2 (ACE2) receptor, forming a protein complex, and that disruption of this complex results in the inhibition of viral uptake. The results of this study suggest that sigma-2R/TMEM97 may be a novel therapeutic target to inhibit SARS-CoV-2 viral uptake, as well as to decrease inflammatory and thrombotic effects through the modulation of the complement cascade.

cell biology↗

bioRxiv2022

Single Cell RNA-Sequence Analyses Reveal Uniquely Expressed Genes and Heterogeneous Immune Cell Involvement in the Rat Model of Intervertebral Disc Degeneration

Intervertebral disc (IVD) degeneration is characterized by a loss of cellularity, and changes in cell-mediated activity that drives anatomic changes to IVD structure. In this study, we use single cell RNA-sequencing analysis of cells extracted from the degenerating tissues of the rat IVD following lumbar disc puncture. Two control, uninjured IVDs (L2-3, L3-4) and two degenerated, injured IVDs (L4-5, L5-6) from each animal were examined either at two- and eight-week post-operative time points. The cells from these IVDs were extracted and transcriptionally profiled at a single-cell resolution. Unsupervised cluster analysis revealed the presence of 4 known cell types in both non-degenerative and degenerated IVDs based on previously established gene markers: IVD cells, endothelial cells, myeloid cells, and lymphoid cells. As a majority of cells were associated with the IVD cell cluster, sub-clustering was used to further identify the cell populations of the nucleus pulposus, inner and outer annulus fibrosus. The most notable difference between control and degenerated IVDs was the increase of myeloid and lymphoid cells in degenerated samples at 2- and 8- weeks post-surgery. Differential gene expression analysis revealed multiple distinct cell types from the myeloid and lymphoid lineages, most notably macrophages and B lymphocytes and demonstrated a high degree of immune specificity during degeneration. In addition to the heterogenous infiltrating immune cell populations in the degenerating IVD, the increased number of cells in the AF sub-cluster expressing Ngf and Ngfr, encoding for p75NTR, suggest that NGF signaling may be one of the key mediators of the IVD crosstalk between immune and neuronal cell populations. These findings provide the basis for future work to understand the involvement of select subsets of non-resident cells in IVD degeneration.

cell biology↗

bioRxiv2023

Why do cell-level test methods for detecting differentially expressed genes fail in single-cell RNA-seq data?

Large-scale multi-subject single-cell data have become very common. For differential gene expression (DGE) analysis of these datasets, a common practice is to choose any of the two: pseudobulk methods or cell-wise methods. However, multi-subject single-cell studies have highly heterogeneous study designs. Some studies have case/control samples to be compared and tested, and some make within-sample perturbations. In this work, we report that to prevent severely inflated errors, we must treat the two categories of study designs differently in the DGE analysis. In studies with case/control labels, pseudobulk methods work the best, and cell-wise methods produce severe inflation of type II errors. Cell-wise methods work best in studies with within-sample perturbations, and pseudobulk methods produce severe inflation of type I errors. We provide mathematical proofs to support this argument. Surprisingly, many existing studies, even published ones, often choose an inappropriate DGE method. The most common temptation is to use cell-wise methods for case/control studies, which will only make p-values falsely look significant. Our analyses and proofs warn that choosing an appropriate DGE method is not an option but a requirement.

genomics↗

bioRxiv2023

Chromatin and gene expression changes during female Drosophila germline stem cell development illuminate the biology of highly potent stem cells

Highly potent animal stem cells either self renew or launch complex differentiation programs, using mechanisms that are only partly understood. Drosophila female germline stem cells (GSC) perpetuate without change over evolutionary time and generate cystoblast daughters that develop into nurse cells and oocytes. Cystoblasts initiate differentiation by generating a transient syncytial state, the germline cyst, and by increasing pericentromeric H3K9me3 modification, actions likely to suppress transposable element activity. Relatively open GSC chromatin is further restricted by Polycomb repression of testis or somatic cell-expressed genes briefly active in early female germ cells. Subsequently, Neijre/CBP and Myc help upregulate growth and reprogram GSC metabolism by altering mitochondrial transmembrane transport, gluconeogenesis and other processes. In all these respects GSC differentiation resembles development of the totipotent zygote. We propose that the totipotent stem cell state was shaped by the need to resist transposon activity over evolutionary time scales.

developmental biology↗

bioRxiv2024

Spleen gene expression is associated with mercury content in three-spined stickleback populations

Mercury can be very toxic at low environmental concentrations by impairing immunological, neurological, and other vital pathways in humans and animals. Aquatic ecosystems are heavily impacted by mercury pollution, with evidence of biomagnification through the food web. We examined the effect of mercury toxicity on the spleen, one of the primary immune organs in fish, in natural populations of the three-spined stickleback (Gasterosteus aculeatus Linnaeus, 1758). Our aim was to better understand adaptation to high mercury environments by investigating transcriptomic changes in the spleen. Three stickleback populations with mean Hg muscle concentrations above and three populations with mean Hg muscle concentrations below the European Biota Quality Standard of 20 ng/g wet weight were selected from the Scheldt and Meuse basin in Belgium. We then conducted RNA sequencing of the spleen tissue of 22 females from these populations. We identified 136 differentially expressed genes between individuals from populations with high and low mean mercury content. The 129 genes that were upregulated were related to the neurological system, immunological activity, hormonal regulation, and inorganic cation transporter activity. Seven genes were downregulated and were all involved in pre-mRNA splicing. The results are indicative of our ability to detect molecular alterations in natural populations that exceed an important environmental quality standard. This allows us to assess the biological relevance of such standards, offering an opportunity to better describe and manage mercury-associated environmental health risks in aquatic populations.

ecology↗

bioRxiv2024

Silicone Wire Embolization-induced Acute Retinal Artery Ischemia and Reperfusion Model in Mouse: Gene Expression Provide Insight into Pathological Processes

Acute retinal ischemia and ischemia-reperfusion injury are the primary causes of retinal neural cell death and vision loss in retinal artery occlusion (RAO). The absence of an accurate mouse model for simulating the retinal ischemic process has hindered progress in developing neuroprotective agents for RAO. We developed a unilateral pterygopalatine ophthalmic artery occlusion (UPOAO) mouse model using silicone wire embolization combined with carotid artery ligation. The survival of retinal ganglion cells and visual function were evaluated to determine the duration of ischemia. Immunofluorescence staining, optical coherence tomography, and haematoxylin and eosin staining were utilized to assess changes in major neural cell classes and retinal structure degeneration at two reperfusion durations. Transcriptomics was employed to investigate alterations in the pathological process of UPOAO following ischemia and reperfusion, highlighting transcriptomic differences between UPOAO and other retinal ischemia-reperfusion models. The UPOAO model successfully replicated the acute interruption of retinal blood supply observed in RAO. 60-minutes of Ischemia led to significant loss of major retinal neural cells and visual function impairment. Notable thinning of the inner retinal layer, especially the ganglion cell layer, was evident post-UPOAO. Temporal transcriptome analysis revealed various pathophysiological processes related to immune cell migration, oxidative stress, and immune inflammation during the non-reperfusion and reperfusion periods. A pronounced increase in microglia within the retina and peripheral leukocytes accessing the retina was observed during reperfusion periods. Comparison of differentially expressed genes (DEGs) between the UPOAO and high intraocular pressure models revealed specific enrichments in lipid and steroid metabolism-related genes in the UPOAO model. The UPOAO model emerges as a novel tool for screening pathogenic genes and promoting further therapeutic research in RAO.

neuroscience↗

bioRxiv2026

Host gene expression changes induced by an HIV-1 mutant associated with delayed AIDS progression reveal potential mechanisms

HIV-1 viral protein R (Vpr) is a multifunctional protein central to HIV-1 pathogenesis and progression to AIDS. Polymorphisms in vpr have been linked to varying rates of HIV-1 progression. Of note is the HIV-1 Vpr R77Q mutant, associated with delayed progression to AIDS (also as the long-term non-progressor phenotype, or LTNP). We previously demonstrated that the R77Q mutant promotes a non-inflammatory, apoptotic phenotype in CD4+ T cells. To investigate the mechanism underlying the R77Q-induced apoptotic phenotype, we performed RNA sequencing on a CD4+ T cell line, HUT78, infected with either a replication-competent wild-type strain (NL4-3) or the R77Q mutant. Our results show that at 72 hours post-infection, transcriptomes were heterogeneous, and differential expression analysis identified 289 differentially expressed genes (DEGs) in the R77Q vs. WT comparison. Functional enrichment analysis revealed enriched pathways associated with apoptosis. Gene ontology (GO) terms and GO connections also revealed an apoptotic signature. Although both viral strains upregulated pro-apoptotic genes, the R77Q mutant failed to upregulate some key anti-apoptotic genes such as bcl-2, while WT-infected cells displayed upregulation of those anti-apoptotic genes. Predicted protein-protein interaction within the Bcl-2 family local network also suggests that interactions within this network were substantially affected. Taken together, these findings provide a transcriptomic basis for our previous observations of enhanced apoptosis in R77Q-infected cells and highlight distinct host cell responses that may underlie delayed HIV-1 progression. These results may be useful in identifying new targets to delay AIDS progression. ImportanceThe R77Q mutant has been a long-standing variant of interest because of its association with long-term non-progressors (LTNPs), yet the mechanisms behind this phenotype remain poorly defined. We previously showed that the R77Q mutant is less cytotoxic, killing fewer cells than WT via a non-inflammatory apoptotic pathway while suppressing inflammatory cytokine release, possibly contributing to the LTNP phenotype. Here, we provide a transcriptomic basis for this phenotype and identify a potential novel loss-of-function mechanism in which R77Q-induced apoptosis arises from a failure to upregulate key anti-apoptotic genes. Defining host responses in the context of delayed HIV-1 progression offers novel insights into cellular networks that could inform future therapeutic strategies beyond the current antiviral approaches.

microbiology↗

bioRxiv2025

Distilling Direct Effects via Conditional Differential Gene Expression Analysis

Differential gene expression (DGE) analysis is foundational for interpreting RNA sequencing data, but it conflates direct biological effects with correlations propagated through gene co-expression. Across three RNA sequencing datasets (including a genome-scale perturb-seq experiment), we find that only a small fraction of differentially expressed genes have direct effects on the trait of interest, while the majority are undirected or passengers whose associations are mediated through other genes. To distinguish direct effect genes, we introduce conditional differential gene expression (CDGE) analysis, a framework that tests for conditional rather than marginal association between each gene and the trait of interest. Implemented via the GhostKnockoff procedure with lasso regression, CDGE delivers false discovery rate control, operates on summary statistics from existing DGE pipelines, and accommodates batch effects. The genes identified by CDGE mediate the effects of most other differentially expressed genes and show stronger enrichment for known protein-protein interactions and biological pathways than DGE-identified genes. These results suggest that the field has been systematically over-interpreting DGE outputs, and that distinguishing direct from mediated effects is essential for prioritizing genes for functional follow-up and therapeutic development.

bioinformatics↗

bioRxiv2018

Large-scale analysis of the global transcriptional regulation of bacterial gene expression

Bacterial gene expression depends on the allocation of limited transcriptional resources provided a particular growth rate and growth condition. Early studies in a few genes suggested this global regulation to generate a unifying hyperbolic expression pattern. Here, we developed a large-scale method that generalizes these experiments to quantify the response to growth of over 700 genes that a priori do not exhibit any specific control. We distinguish a core subset following a promoter-specific hyperbolic response. Within this group, we sort genes with regard to their responsiveness to the global regulatory program to show that those with a particularly sensitive linear response are located near the origin of replication. We then find evidence that this genomic architecture is biologically significant by examining position conservation of E. coli genes in 100 bacteria. The response to the transcriptional resources of the cell results consequently in an additional feature contributing to bacterial genome organization.

systems biology↗

bioRxiv2020

Comparison of sparse biclustering algorithms for gene expression datasets

Gene clustering and sample clustering are commonly used to find patterns in gene expression datasets. However, in heterogeneous samples (e.g. different tissues or disease states), genes may cluster differently. Biclustering algorithms aim to solve this issue by performing sample clustering and gene clustering simultaneously. Existing reviews of biclustering algorithms have yet to include a number of more recent algorithms and have based comparisons on simplistic simulated datasets without specific evaluation of biclusters in real datasets, using less robust metrics. In this study we compared four classes of sparse biclustering algorithms on a range of simulated and real datasets. In particular we use a knockout mouse RNA-seq dataset to evaluate each algorithms ability to simultaneously cluster genes and cluster samples across multiple tissues. We found that Bayesian algorithms with strict sparsity constraints had high accuracy on the simulated datasets and didnt require any post-processing, but were considerably slower than other algorithm classes. We assessed whether non-negative matrix factorisation algorithms can be repurposed for biclustering and found that, although the raw output was poor, after using a sparsity-inducing post-processing procedure we introduce, one such algorithm was one of the most highly ranked on real datasets. We also exhibit the limitations of biclustering algorithms by varying the complexity of simulated datasets. The algorithms generally struggled on simulated datasets with a large number of implanted factors, or with a large number of genes. In real datasets, the algorithms rarely returned clusters containing samples from multiple tissues, which highlights the need for further thought in the design and analysis of multi-tissue studies to avoid differences between tissues dominating the analysis. Code to run the analysis is available at https://github.com/nichollskc/biclust_comp, including wrappers for each algorithm, implementations of evaluation metrics, and code to simulate datasets and perform pre- and post-processing. The full tables of results are available at https://doi.org/10.5281/zenodo.4317556

genomics↗

bioRxiv2018

Evaluation of endothelial nitric oxide synthase gene expression in mice genetically heterozygous in Cx43 (Cx43 + / - mice)

Gap junctions are proteins made of connexins which are involved in the regulation of vascular function. Deletion of connexins 43 (Cx43) modifies expression of genes known to be involved in the regulation of the vasculature, differentiation and function of vascular cells. Interestingly, mutant mice lacking endothelial nitric oxide synthase (eNOS) gene have been shown to be hypertensive, suggesting that nitric oxide (NO) plays a role in the physiological control of blood pressure. It was therefore hypothesised that the endothelial deletion of Cx43 in the pulmonary vasculature induces endothelial dysfunction and causes eNOS impairment thereby reducing NO biosynthesis, thus leading to vasoconstriction and vascular remodelling which subsequently leads to the development of pulmonary arterial hypertension (PAH). This project was aimed at evaluating eNOS gene expression in mice genetically heterozygous (HET) in Cx43 (Cx43 +/- mice). This was achieved by using lung tissues from four groups of wild type (W/T) and Cx43 +/- (male and female) mice. Ribonucleic acid (RNA) was isolated from the lung tissues using RNA II isolation system and was reverse transcribed to complementary deoxyribonucleic acid (cDNA). End - point polymerase chain reaction (PCR) and real time PCR were used to measure the expression of eNOS gene. eNOS gene expression levels were found to be the same in all four groups of mice tested, with no significant difference. The result therefore suggests that eNOS gene is expressed in mice genetically heterozygous in Cx43 (Cx43 + / -).

cell biology↗

bioRxiv2023

Visualisation of gene expression within the context of tissues: an X-ray computed tomography-based multimodal approach

The development of an organism is orchestrated by the spatial and temporal expression of genes. Accurate visualisation of gene expression patterns in the context of the surrounding tissues offers a glimpse into the mechanisms that drive morphogenesis. We developed correlative light-sheet fluorescence microscopy and X-ray computed tomography approach to map gene expression patterns to the whole organisms 3D anatomy at cellular resolution. We show that this multimodal approach is applicable to gene expression visualised by protein-specific antibodies and fluorescence RNA in situ hybridisation, offering a detailed understanding of individual phenotypic variations in model organisms. Furthermore, the approach provides a unique possibility to identify tissues together with their 3D cellular and molecular composition in anatomically less-defined in vitro models, such as organoids. We anticipate that the visual and quantitative insights into the 3D distribution of gene expression within tissue architecture, by the multimodal approach developed here, will be equally valuable for reference atlases of model organisms development, as well as for comprehensive screens and morphogenesis studies of in vitro models.

developmental biology↗

bioRxiv2022

Nonmodular oscillator and switch based on RNA decay drive regeneration of multimodal gene expression

Periodic gene expression dynamics are key to cell and organism physiology. Studies of oscillatory expression have focused on networks with intuitive regulatory negative feedback loops, leaving unknown whether other common biochemical reactions can produce oscillations. Oscillation and noise have been proposed to support mammalian progenitor cells capacity to restore heterogenous, multimodal expression from extreme subpopulations, but underlying networks and specific roles of noise remained elusive. We use mass-action-based models to show that regulated RNA degradation involving as few as two RNA species--applicable to nearly half of human protein-coding genes--can generate sustained oscillations without imposed feedback. Diverging oscillation periods synergize with noise to robustly restore cell populations bimodal expression. The global bifurcation organizing this divergence relies on an oscillator and bistable switch which cannot be decomposed into two structural modules. Our work reveals surprisingly rich dynamics of post-transcriptional reactions and a potentially widespread mechanism useful for development and regeneration.

systems biology↗

bioRxiv2025

Uncovering Host-Parasite Dynamics: Gene Expression Shifts in Hematodinium-infected Chionoecetes bairdi in Response to Temperature ChangeChanges in gene expression under differing temperature regimes of infected Chionoecetes bairdi and the parasitic dinoflagellate Hematodinium sp.

Parasites can have profound effects on their hosts, and those effects can be altered by changing environmental conditions. The dinoflagellate Hematodinium sp. is a common and deadly parasite of the crab Chionoecetes bairdi, a species vulnerable to rising ocean temperatures. To examine the impact of parasitism under various temperature conditions, infected crabs (n = 9) were held under three temperature regimes (4{degrees}C, 7.5{degrees}C, and 10{degrees}C) for 17 days. RNAseq was performed on samples from three timepoints, and the relationships of temperature and time to gene expression were examined. Transcriptomes for C. bairdi and Alveolata symbiotes were created, and genes linked to immune function were identified within both host and parasite. Within the host, 1721 contigs were differentially expressed in response to a temperature increase, with 86% of these increased in expression. In total, 3013 contigs linked to temperature response were identified. Additionally, numerous changes in biological processes were observed in Hematodinium over the course of the experiment, including development and microtubule-based processes and ribosomal assembly. Through understanding the impact of changes in temperature on gene expression within both Hematodinium and infected C. bairdi, we provide a more complete picture of the response of these species to rising ocean temperatures.

molecular biology↗

bioRxiv2021

The early embryonic transcriptome of a Hawaiian Drosophila picture-wing fly shows evidence of altered gene expression and novel gene evolution

A massive adaptive radiation on the Hawaiian archipelago has produced approximately one quarter of the fly species in the family Drosophilidae. The Hawaiian Drosophila clade has long been recognized as a model system for the study of both the ecology of island endemics and the evolution of developmental mechanisms, but relatively few genomic and transcriptomic datasets are available for this group. We present here a differential expression analysis of the transcriptional profiles of two highly conserved embryonic stages in the Hawaiian picture-wing fly Drosophila grimshawi. When we compared our results to previously published datasets across the family Drosophilidae, we identified cases of both gains and losses of gene representation in D. grimshawi, including an apparent delay in Hox gene activation. We also found high expression of unannotated genes. Most transcripts of unannotated genes with open reading frames do not have homologs in non-Hawaiian Drosophila species, although the vast majority have sequence matches in other genomes of the Hawaiian picture-wing flies. Some of these genes may have arisen from non-coding sequence in the ancestor of Hawaiian flies or during the evolution of the clade. Our results suggests that both the modified use of ancestral genes and the evolution of new ones may occur in rapid radiations. RESEARCH HIGHLIGHTSThe early embryonic transcriptome of the Hawaiian fly Drosophila grimshawi shows a loss of expression of conserved Stage 5 genes, including the Hox genes The de novo evolution of embryonically expressed genes may be occurring in the Hawaiian Drosophila lineage AUTHORS STATEMENTThis paper is not being considered for publication elsewhere. This study formed part of Madeline Cheneverts M.S. thesis.

developmental biology↗

bioRxiv2019

Differential gene expression analysis reveals novel genes and pathways in pediatric septic shock patients

Septic shock is a severe health condition caused by uncontrolled sepsis. Advancements in the high-throughput sequencing techniques have risen the number of potential genetic biomarkers under review. Multiple genetic markers and functional pathways play a part in the development and progression of pediatric septic shock. Fifty-four differentially expressed pediatric septic shock gene biomarkers were identified using gene expression data from 181 pediatric intensive care unit (PICU) patients within the first 24 hours of admission. The gene expression signatures discovered showed discriminatory power between pediatric septic shock survivors and nonsurvivors types. Using functional enrichment analysis of differentially expressed genes (DEGs), the known genes and pathways in septic shock were validated, and unexplored septic shock-related genes and functional groups were identified. Septic shock survivors were distinguished from septic shock non-survivors by differential expression of genes involved in the immune response, chemokine-mediated signaling, neutrophil chemotaxis, and chemokine activity. The identification of the septic shock gene biomarkers may facilitate in septic shock diagnosis, treatment, and prognosis.

bioinformatics↗

bioRxiv2016

Translational contributions to tissue-specificity in rhythmic and constitutive gene expression.

BACKGROUNDThe daily gene expression oscillations that underlie mammalian circadian rhythms show striking tissue differences and involve post-transcriptional regulation. Both aspects remain poorly understood. We have used ribosome profiling to explore the contribution of translation efficiency to temporal gene expression in kidney, and contrasted our findings with liver data available from the same mice.\n\nRESULTSRhythmic translation of constantly abundant mRNAs affected largely non-overlapping transcript sets with distinct phase clustering in the two organs. Moreover, tissue differences in translation efficiency modulated the timing and amount of protein biosynthesis from rhythmic mRNAs, consistent with organ-specificity in clock output gene repertoires and rhythmicity parameters. Our comprehensive datasets provided insights into translational control beyond temporal regulation. Between tissues, many transcripts showed differences in translation efficiency, which were, however, of markedly smaller scale than mRNA abundance differences. Tissue-specific changes in translation efficiency were associated with specific transcript features and, intriguingly, globally counteracted and compensated transcript abundance variations, leading to higher similarity at the level of protein biosynthesis between both tissues.\n\nCONCLUSIONSWe show that tissue-specificity in rhythmic gene expression extends to the translatome and contributes to define the identities, the phases and the expression levels of rhythmic protein biosynthesis. Moreover, translational compensation of transcript abundance divergence leads to overall higher similarity at the level of protein production across organs. The unique resources provided through our study will serve to address fundamental questions of post-transcriptional control and differential gene expression in vivo.

Genomics↗

bioRxiv2020

Characterizing microRNA-mediated modulation of gene expression noise and its effect on synthetic gene circuits

Gene expression noise plays an important role in many biological processes, such as cell differentiation and reprogramming. It can also dramatically influence the behavior of synthetic gene circuits. MicroRNAs (miRNAs) have been shown to reduce the noise of lowly expressed genes and increase the noise of highly expressed genes, but less is known about how miRNAs with different properties may regulate gene expression noise differently. Here, by quantifying gene expression noise using mathematical modeling and experimental measurements, we showed that competing RNAs and the composition of miRNA response elements (MREs) play important roles in modulating gene expression noise. We found that genes targeted by miRNAs with weak competing RNAs show lower noise than those targeted by miRNAs with strong competing RNAs. In addition, in comparison with a single MRE, repetitive MREs targeted by the same miRNA suppress the noise of lowly expressed genes but increase the noise of highly expressed genes. Additionally, MREs composed of different miRNA targets could cause similar repression levels but lower noise compared with repetitive MREs. We further observed the influence of miRNA-mediated noise modulation in synthetic gene circuits which could be applied to classify cell types using miRNAs as sensors. We found that miRNA sensors that introduce higher noise could lead to better classification performance. Our results provide a systematic and quantitative understanding of the function of miRNAs in controlling gene expression noise and how we can utilize miRNAs to modulate the behavior of synthetic gene circuits.

systems biology↗