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Results for “gene expression”

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At least 343 records · Page 19Linked to original sources

bioRxiv2025

Integrating gene expression, mutation and copy number data to identify driver genes of recurrent chromosome-arm losses

Aneuploidy is a hallmark of cancer, yet the specific genes driving recurrent chromosome-arm losses remain largely unknown. Here, we present a systematic framework integrating gene expression, mutation, and copy number data to identify candidate driver genes of cancer type-specific recurrent chromosome-arm losses across 20 cancer types, using [~]7,500 tumors from The Cancer Genome Atlas. By analyzing focal deletions and point mutations that co-occur with, or are mutually exclusive with, chromosome-arm losses, we pinpoint 311 candidate drivers associated with 160 cancer type-specific recurrent events. Our approach identifies known aneuploidy drivers such as TP53 and PTEN, while revealing multiple novel candidates, including established tumor suppressor genes not previously linked to aneuploidy. Furthermore, we leverage gene expression changes associated with these chromosome-arm losses to propose pathway-level alterations that may drive cancer progression. Integrating these findings highlights key candidate drivers underlying the observed gene expression alterations, thereby reinforcing their biological relevance. This work provides the first comprehensive catalogue of candidate driver genes for recurrently lost chromosome-arms in human cancer.

cancer biology↗

bioRxiv2020

Identification of Differentially Expressed Gene Modules in Heterogeneous Diseases

MotivationIdentification of differentially expressed genes is necessary for unraveling disease pathogenesis. This task is complicated by the fact that many diseases are heterogeneous at the molecular level and samples representing distinct disease subtypes may demonstrate different patterns of dysregulation. Biclustering methods are capable of identifying genes that follow a similar expression pattern only in a subset of samples and hence can consider disease heterogeneity. However, identifying biologically significant and reproducible sets of genes and samples remains challenging for the existing tools. Many recent studies have shown that the integration of gene expression and protein interaction data improves the robustness of prediction and classification and advances biomarker discovery. ResultsHere we present DESMOND, a new method for identification of Differentially ExpreSsed gene MOdules iN Diseases. DESMOND performs network-constrained biclustering on gene expression data and identifies gene modules -- connected sets of genes up- or down-regulated in subsets of samples. We applied DESMOND on expression profiles of samples from two large breast cancer cohorts and have shown that the capability of DESMOND to incorporate protein interactions allows identifying the biologically meaningful gene and sample subsets and improves the reproducibility of the results. Availabilityhttps://github.com/ozolotareva/DESMOND Contactozolotareva@techfak.uni-bielefeld.de Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2024

Efficient fine-tuning of endothelial gene expression by Y to Phe mutation in the VE-cadherin gene

Cancer and inflammation are associated with vascular diseases that affect endothelial cells (ECs) and alter gene expression. We aimed at understanding whether the site Y685 in the cytoplasmic domain of VE-cadherin triggers epigenetic programming in vivo. Using our knock-in mice carrying the Y685F VE-cadherin mutation, RNA sequencing from lung ECs identified 884 differentially expressed genes (DEG) involved in processes such as cell-cell adhesion, vascular development, and angiogenesis. The 30 DEGs include 22 down-regulated genes (genes encoding cell signalling enzymes, anion transport and lipid metabolism) and 8 up-regulated genes, including the endothelial-specific S1PR1. Analysis of the VEGF/VEGFR2 signaling pathway shows a significant decrease in the expression of pY1173VEGFR2 whereas VEGF remains constant, this was consistent with impaired migration, proliferation and protrusive properties of ECs in vitro. Co-immunoprecipitation experiments showed that c-Src and Y685F-VE-cadherin association which was enhanced in KI compared to WT, resulting in increased in Y685F-VE-cadherin phosphorylation at site Y731. As a consequence, its partner {beta}-catenin translocates to the nucleus. CHIPS assay showed that FOXF1 binds to the s1pr1 promoter, leading to increased expression of the S1PR1. In vivo, in the lung vasculature, this process was associated with increased vessel wall thickness and reduced fibrosis. Overall, our findings provide a novel transcriptomic profile triggered by Y685F-VE-cadherin ECs for potential insights into therapeutic targets to envisage normalisation of the tumor vasculature.

cell biology↗

bioRxiv2026

Pretraining Enhances Megabase-Scale Gene Expression Prediction with GeneUnet

Predicting gene expression from DNA sequence across diverse genomic tracks is essential for understanding gene regulation and interpreting non-coding variants. Existing supervised methods are limited to few species and fail to exploit conserved regulatory mechanisms, while DNA foundation models capture cross-species information but remain constrained to kilobase-scale contexts insufficient for this task. Here we introduce GB.GeneUnet, an 837M-parameter transformer-based U-Net pretrained on 6 trillion tokens from multi-species genomes in OpenGenome2, extending genomic context to 1 Mb with up to 100x inference speedup over GeneMoE, a preliminary MoE transformer baseline of similar model size pretrained on the same data. Fine-tuned for gene expression prediction, GB.GeneUnet achieves state-of-the-art performance on the Borzoi benchmark at 524 kb context, and attains performance comparable to AlphaGenome at 1 Mb context while requiring a lighter fine-tuning procedure. Together, these results establish a scalable framework linking multi-species pretraining to ultra-long-context gene expression modeling.

genomics↗

bioRxiv2023

Pan-transcriptome reveals a large accessory genome contribution to gene expression variation in yeast

Gene expression is an essential step in the translation of genotypes into phenotypes. However, little is known about the transcriptome architecture and the underlying genetic effects at a species-level. Here, we generated and analyzed the pan-transcriptome of [~]1,000 yeast natural isolates across 4,977 core and 1,468 accessory genes. We found that the accessory genome is an underappreciated driver of the transcriptome divergence. Global gene expression patterns combined with population structure show that the heritable expression variation mainly lies within subpopulation-specific signatures, for which the accessory genes are overrepresented. Genome-wide association analyses consistently highlight that the accessory genes are associated with proportionally more variants with larger effect sizes, illustrating the critical role of the accessory genome on the transcriptional landscape within and between populations.

genomics↗

bioRxiv2024

Benchmarking macaque gene expression for horizontal and vertical translation

The spatial patterning of gene expression shapes cortical organization and emergent function. Advances in spatial transcriptomics make it possible to comprehensively map cortical gene expression in both humans and model organisms. The macaque is a particularly valuable model organism, due to its evolutionary similarity with the human. The translational potential of macaque gene expression rests on the assumption that it is a good proxy for spatial patterns of corresponding proteins (vertical translation) and for spatial patterns of ortholog human genes (horizontal translation). Here we systematically benchmark the spatial distribution of gene expression in the macaque cortex against (a) cortical receptor density in the macaque and (b) cortical gene expression in the human. We find that there is moderate cortex-wide correspondence between gene expression and protein density in the macaque, which is improved by considering layer-specific gene expression. We find greater correspondence between orthologous gene expression in the macaque and human. Inter-species correspondence of gene expression exhibits systematic regional heterogeneity, with greater correspondence in unimodal than transmodal cortex, mapping onto patterns of evolutionary cortical expansion. We extend these results to additional micro-architectural features using macaque immunohistochemistry and T1w:T2w ratio, and replicate them using macaque RNA-seq and human RNA-seq gene expression. Collectively, the present results showcase both the potential and limitations of macaque spatial transcriptomics as an engine of translational discovery within and across species.

neuroscience↗

bioRxiv2025

Collective Gene Expression Fluctuations Encode the Regulatory State of Cells

Gene expression is inherently stochastic, leading to substantial cell-to-cell variability in mRNA and protein abundances. Variability in the expression of individual genes has been associated both with impaired signal processing and with facilitation of stress responses and differentiation. Here, combining machine learning, theory, and analysis of scRNA-seq data across various organisms and tissues, we show that variability in gene expression can be coordinated cell-wide. We define a statistical score that quantifies this coordination in single-cell data and demonstrate that distinct coordination patterns reflect the regulatory state of cells. We further develop a physics-informed machine-learning framework that identifies and predicts such variability patterns. Coordinated gene-expression variability emerges as a hallmark of stem and progenitor cells and distinguishes intrinsic stochasticity from cell-population heterogeneity. Together, our results establish the structure of gene expression variability as a cellular-scale signature of cell identity and regulatory organization.

biophysics↗

bioRxiv2022

Gene expression profiles of chemosensory genes of termite soldier and worker antennae

Termite caste differentiation and social behavior are appropriately regulated by the chemical signals among individuals in each colony. Signal transduction is well known to be triggered by the reception of odorant molecules by some binding proteins in the antennae, after which, a signal is transmitted to chemosensory receptors. However, there is insufficient information on the role of chemosensory genes involved in signal transduction in termites. Here, we identified the genes involved in chemosensory reception in the rhinotermitid termite Reticulitermes speratus, and performed a genome-wide comparative transcriptome analysis of worker and soldier antennae. First, we identified 31 odorant-binding proteins (OBPs), and three chemosensory protein A (CheA) from the available genome sequence data. Thereafter, we performed RNA sequencing to compare the expression levels of OBPs, CheAs, and previously identified chemosensory receptor genes between workers and soldiers antennae. Of note, there were no receptor genes with significant differences in expression between castes. However, the expression levels of three non-receptor genes (OBP, CheA, and Sensory neuron membrane protein) were significantly different between castes. Quantiative polymerase chain reaction (qPCR) analysis using antennae and other head parts confirmed that these genes were highly expressed in soldier antennae. Finally, independent qPCR analysis showed that the expression patterns of these genes were altered in soldiers from different social contexts. The present results suggest that some non-receptor protein genes are involved in the social behaviors of termites.

evolutionary biology↗

bioRxiv2019

Developmental transcriptomes of the sea star, Patiria miniata, illuminate the relationship between conservation of gene expression and morphological conservation

Evolutionary changes in developmental gene expression lead to alteration in the embryonic body plan and biodiversity. A promising approach for linking changes in developmental gene expression to altered morphogenesis is the comparison of developmental transcriptomes of closely related and further diverged species within the same phylum. Here we generated quantitative transcriptomes of the sea star, Patiria miniata (P. miniata) of the echinoderm phylum, at eight embryonic stages. We then compared developmental gene expression between P. miniata and the sea urchin, Paracentrotus lividus (~500 million year divergence) and between Paracentrotus lividus and the sea urchin, Strongylocentrotus purpuratus (~40 million year divergence). We discovered that the interspecies correlations of gene expression level between morphologically equivalent stages decreases with increasing evolutionary distance, and becomes more similar to the correlations between morphologically distinct stages. This trend is observed for different sub-sets of genes, from various functional classes and embryonic territories, but is least severe for developmental genes sub-sets. The interspecies correlation matrices of developmental genes show a consistent peak at the onset of gastrulation, supporting the hourglass model of phylotypic stage conservation. We propose that at large evolutionary distance the conservation of relative expression levels for most sets of genes is more related to the required quantities of transcripts in a cell than to conserved morphogenesis processes. In these distances, the information about morphological similarity is reflected mostly in the interspecies correlations between the expressions of developmental control genes.\n\nAuthor summaryUnderstanding the relationship between the interspecies conservation of gene expression and morphological similarity is a major challenge in modern evolutionary and developmental biology. The Interspecies correlations of gene expression levels have been used extensively to illuminate these relationships and reveal the developmental stages that show the highest conservation of gene expression, focusing on the diagonal elements of the correlation matrices. Here we generated the developmental transcriptomes of the sea star, Patiria miniata, and used them to study the interspecies correlations between closely related and further diverged species within the echinoderm phylum. Our study reveals that the diagonal elements of the correlation matrices contain only partial information. The off-diagonal elements, that compare gene expression between distinct developmental stages, indicate whether the conservation of gene expression is indeed related to similar morphology or instead, to general cellular constraints that linger throughout development. With increasing evolutionary distances the diagonal elements decrease and become similar to the off-diagonal elements, reflecting the shift from morphological to general cellular constraints. Within this trend, the interspecies correlations of developmental control genes maintain their diagonality even at large evolutionary distance, and peak at the onset of gastrulation, supporting the hourglass model of phylotypic stage conservation.

evolutionary biology↗

bioRxiv2019

Tbx2a modulates switching of opsin gene expression

Differences in sensory tuning are reported to maintain species boundaries and may even lead to speciation. Variation in the tuning of color vision is likely due to differences in the expression of opsin genes. Over 1,000 species of African cichlid fishes provide an excellent model system for studying the genetic basis of opsin gene expression because of the presence of seven distinct genes, yet individual species typically express only a divergent set of three opsins. The evolution of such shifts is expected to arise through either (a) two simultaneous regulatory changes (one for each opsin), or (b) one regulatory change that simultaneously promotes expression of one opsin while repressing another. Here, we used QTL analyses, genome sequencing, and gene expression studies to identify the transcription factor Tbx2a as likely driving a switch between LWS and RH2 opsin expression. Binding sites for Tbx2a in the LWS promoter and the highly conserved Locus Control Region of RH2 act to concurrently promote LWS expression while repressing RH2 expression. Our data support the hypothesis that instant changes in visual tuning can be achieved by switching the expression of multiple genes by a single mutation and do not require independent changes in the regulatory regions of each opsin.

evolutionary biology↗

bioRxiv2026

Design of synthetic activators for programmable gene expression

Transcription factors control gene expression by recruiting transcriptional coactivators through intrinsically disordered transcriptional activation domains (TADs), whose weak and promiscuous interactions make it difficult to establish quantitative relationships between coactivator recruitment and transcriptional output, and to precisely modulate gene expression. To overcome this limitation, we set out to design coactivator-recruiting proteins using AlphaFold3-predicted TAD-coactivator interactions as a guide. We developed a high-throughput functional screening platform in mammalian cells and identified over 300 well folded nanomolar affinity binders to the transcription coactivators Mediator (multiple subunits), BRD4, NCOA, and p300; targeted interface mutations enabled systematic tuning of their binding affinities. Using a panel of p300 binders spanning nanomolar to micromolar affinities, we found an ultrasensitive relationship between coactivator-binding affinity and transcriptional output, with a sharp transcriptional activation threshold at ~500 nM. Incorporating p300 binder designs into CRISPRa yielded compact synthetic effectors that drove stronger activation than VPR across multiple genomic loci with minimal detectable cytotoxicity. Combining p300- and Mediator-specific binders further enhanced transcription, revealing functional synergy between these coactivators. Together, our work establishes a quantitative framework linking coactivator-binding affinity to transcriptional output and provides compact synthetic effectors for programmable gene activation.

synthetic biology↗

bioRxiv2023

Interrogating the function of bicistronic translational control elements to improve consistency of gene expression

Context independent gene expression is required for genetic circuits to maintain consistent and predicable behavior. Previous efforts to develop context independent translation have leveraged the helicase activity of translating ribosomes via bicistronic design translational control elements (BCDs) located within an efficiently translated leader peptide. We have developed a series of bicistronic translational control elements with strengths that span several orders of magnitude, maintain consistent expression levels across diverse sequence contexts, and are agnostic to common ligation sequences used in modular cloning systems. We have used this series of BCDs to investigate several features of this design, including the spacing of the start and stop codons, the nucleotide identity upstream of the start codon, and factors affecting translation of the leader peptide. To demonstrate the flexibility of this architecture and their value as a generic modular expression control cassette for synthetic biology, we have developed a set of robust BCDs for use in several Rhodococcus species.

synthetic biology↗

bioRxiv2026

DEAR-OWL: a fully browser-based hybrid resource for instant or precise differential gene expression analysis

MotivationDifferential gene expression analysis (DEA) via RNA sequencing (RNA-seq) is essential but remains challenging for wet-lab biologists due to command-line complexities. Centralized web platforms democratize this process but suffer from server congestion, long queuing delays, data privacy risks with proprietary datasets, and limited long-term sustainability due to hosting fees. ResultsWe present DEAR-OWL (Differential Expression Analysis Resource on the Web (Lite)), a fully serverless, privacy-preserving web application that performs the DEA locally inside the users web browser. To combine instant exploratory speed with rigorous verification, the application runs two distinct analysis options. The first option is a fast screening tool written in native browser language (JavaScript) that delivers immediate, genome-wide fold-change calculations and statistical screening based on an edgeR-equivalent logic. The second option is a heavy-duty statistical tool that brings the standard R package (DESeq2) directly into the browser using WebR and WebAssembly technology, ensuring publication-grade validation without needing server power. Interactive visual plots (volcano plots, minus-average plots, and heatmaps) are seamlessly generated from the results of either analysis choice. Benchmarking proved its hardware compatibility: the browser-based DESeq2 engine completed the analysis in [~]30 seconds on a 64 GB RAM workstation and in [~]3 minutes on an 8 GB RAM laptop without crashing. DEAR-OWL can utilize the Grass Expression Atlas (GExA) data as built-in and supports secure local file uploads, ensuring total data privacy with neither queuing delays nor cloud infrastructure costs. Availability and implementationDEAR-OWL is freely accessible at https://webpark2116.sakura.ne.jp/deseq2/. The source code is available at https://github.com/kota200/DEAR-OWL.

bioinformatics↗

bioRxiv2024

Gene body methylation buffers noise in gene expression in plants

Non-genetic variability in gene expression is an inevitable consequence of stochastic nature of processes driving transcription and translation. Largely thought to be deleterious to cell fitness, it is not uniform across the transcriptome. This implies the existence of (molecular) determinants affecting the degree of gene expression variability, although this remain poorly understood in multicellular systems. In this study, we found a link between gene body methylation and noise in gene expression in Arabidopsis thaliana. More specifically, genes with high levels of noise show low levels of gene body methylation, while genes with lower level of noise in gene expression show higher level of gene body methylation. Most importantly, loss of CpG methylation in gene bodies lead to a significant number of genes displaying higher noise in gene expression. This could be compensated by low but significant gain of non-CpG methylation at promoters of certain genes. Overall, our results show that gene body methylation has a functional role and specifically controls the noise in gene expression for a large number of genes.

molecular biology↗

bioRxiv2021

Phosphatidylglycerol synthesis facilitates plastid gene expression and light induction of nuclear photosynthetic genes

Phosphatidylglycerol (PG) is the only major phospholipid in the thylakoid membrane of chloroplasts. PG is essential for photosynthesis and loss of PG in Arabidopsis thaliana results in severe defects of growth and chloroplast development with decreased chlorophyll accumulation, impaired thylakoid formation, and downregulation of photosynthesis-associated genes encoded in nuclear and plastid genomes. However, how the absence of PG affects the gene expression and plant growth remains unclear. To elucidate this mechanism, we investigated the growth and transcriptional profiles of a PG-deficient Arabidopsis mutant pgp1-2 under various light conditions. Microarray analysis demonstrated that reactive oxygen species-responsive genes were upregulated in pgp1-2. Decreased growth light did not alleviated the impaired leaf development and the downregulation of photosynthesis-associated genes in pgp1-2, indicating limited impacts of photooxidative stress on the defects of pgp1-2. Illumination to dark-adapted pgp1-2 triggered downregulation of photosynthesis-associated nuclear-encoded genes (PhANGs), while plastid-encoded genes were constantly suppressed. Overexpression of GOLDEN2-LIKE1 (GLK1), a transcription factor regulating chloroplast development, in pgp1-2 upregulated PhANGs but not plastid-encoded genes along with chlorophyll accumulation. Our data suggest a broad impact of PG biosynthesis on nuclear-encoded genes partially via GLK1 and a specific involvement of this lipid in the plastid gene expression and plant development.

plant biology↗

bioRxiv2016

Age-dependent changes in mean and variance of gene expression across tissues in a twin cohort

Gene expression changes with age have consequences for healthy aging and disease development. Here we investigate age-related changes in gene expression measured by RNA-seq in four tissues and the interplay between genotypes and age-related changes in expression. Using concurrently measured methylation array data from fat we also investigate the relationship between methylation, gene expression and age. We identified age-dependent changes in mean levels of gene expression in 5,631 genes and in splicing of 904 genes. Age related changes were widely shared across tissues, with up to 60% of age-related changes in expression and 47% on splicing in multi-exonic genes shared; amongst these we highlight effects on genes involved in diseases such as Alzheimer and cancer. We identified 137 genes with age-related changes in variance and 42 genes with age-dependent discordance between genetically identical individuals; implying the latter are driven by environmental effects. We also give four examples where genetic control of expression is affected by the aging process. Analysis of methylation observed a widespread and stronger effect of age on methylation than expression; however we did not find a strong relationship between age-related changes in both expression and methylation. In summary, we quantified aging affects in splicing, level and variance of gene expression, and show that these processes can be both environmentally and genetically influenced.

Genomics↗

bioRxiv2022

DNA methylation regulates sex-biased gene expression in the house sparrow

Sexual dimorphism is often mediated by tissue-specific, differential gene expression, but the mechanisms that regulate these gene expression patterns are not well understood. Here, we investigate DNA methylation as a potential regulator of sex-biased gene expression in the house sparrow (Passer domesticus). First, we examine whether sex-bias in gene expression or DNA methylation is present in this species, and whether any sex differences are tissue-general or tissue-specific. Second, we assess the correlation between gene expression and DNA methylation at different genomic features in several tissues. Samples clustered by tissue type when looking at both gene expression and DNA methylation, and in gonads samples clustered according to sex. We demonstrate sex-bias in DNA methylation and gene expression on the Z-chromosome as well as on autosomes, but find that most of the sex-biased genes are tissue-specific and that the majority of sex-bias occurs in gonads, although some tissue-general sex differences were observed. This underscores the importance of choosing a tissue relevant to the studied phenotype in DNA methylation or gene expression studies. We find strong negative correlation between DNA methylation and gene expression at the transcription start site (TSS), and that the TSS of highly expressed genes is hypomethylated in comparison to the TSS of genes with low expression. Furthermore, we show that sex-biased DNA methylation can account for 14% of the sex differences in gene expression in gonads. Together these results indicate that DNA methylation differences between the sexes can provide a mechanistic explanation for sex-biased gene expression that likely contributes to trait sexual dimorphism in nature.

evolutionary biology↗

bioRxiv2024

SLAM-seq reveals independent contributions of RNA processing and stability to gene expression in African trypanosomes

Gene expression is a multi-step process that converts DNA-encoded information into proteins, involving RNA transcription, maturation, degradation, and translation. While transcriptional control is a major regulator of protein levels, the role of post-transcriptional processes such as RNA processing and degradation is less well understood due to the challenge of measuring their contributions individually. To address this challenge, we investigated the control of gene expression in Trypanosoma brucei, a unicellular parasite assumed to lack transcriptional control. Instead, mRNA levels in T. brucei are controlled by post-transcriptional processes, which enabled us to disentangle the contribution of both processes to total mRNA levels. In this study, we developed an efficient metabolic RNA labeling approach and combined ultra-short metabolic labeling with transient transcriptome sequencing (TT-seq) to confirm the long-standing assumption that RNA polymerase II transcription is unregulated in T. brucei. In addition, we established thiol (SH)-linked alkylation for metabolic sequencing of RNA (SLAM-seq) to globally quantify RNA processing rates and half-lives. Our data, combined with scRNA-seq data, indicate that RNA processing and stability independently affect total mRNA levels and contribute to the variability seen between individual cells in African trypanosomes.

molecular biology↗