Biology subjects

Li, R.

Publications and source records attributed to Li, R..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

MissenseHMM: state-based annotations for missense variants through joint modeling of pathogenicity scores

Many computational predictors of missense variant pathogenicity are available. To capture information across various predictors, we propose MissenseHMM, which learns states corresponding to combinatorial patterns of variant prioritizations. We applied MissenseHMM to 43 predictors, annotating over 70 million missense variants with 20 states that showed distinct predictor scores patterns, amino acid substitutions and other genomic annotation enrichments. MissenseHMM state annotations enhanced individual predictors associations with clinical pathogenic variants and deep mutational scanning data, and also provided insight into the performances of various protein language models. Overall, MissenseHMM complements pathogenicity predictors and is an annotation resource for missense variant interpretation.

genomics↗

bioRxiv2026

Ultra-flexible PINE arrays for month-long, continuous intracellular ion flux monitoring in plants with nanomolar accuracy

High-precision in vivo monitoring of ion fluxes is essential yet challenging studying plant electrophysiology such as growth regulation, signal transduction and stress responses. Existing methods for probing ion dynamics are limited by low sensitivity, high invasiveness that interferes physiological processes, and the inability to accurately resolve ion homeostasis with required spatial and temporal resolution. Here, we introduce ultraflexible, plant implantable nanoelectrode (PINE) arrays manufactured on 1.2-m-thick polymer substrates, which enable ultrasensitive and selective measurement of ionic current for month-long via scalable nanofabrication techniques. The fabricated PINE arrays have a smaller dimension than typical plant cells as well as less stiffness, facilitating minimally invasive integration with living plant cells. This subcellular-scale plant-electronic interface allows for reliable, selective detection of K+ flux with a detection limit of [~]10- M, and thus allows continuous, stable monitoring of tomato stem cells over six weeks, capturing dynamic potassium fluctuations during all key growth stages. More importantly, the method permits long-term, real-time tracking of ion-specific dynamics without disrupting plant cellular structure or altering endogenous ion concentrations. Therefore, PINE provides unprecedented access to ion homeostasis and signaling networks, making it an excellent platform for precision agriculture and a foundational tool for future digital plant engineering.

plant biology↗

bioRxiv2026

A Single-Cell and Spatial 3D Multi-omic Atlas of Developing Human Basal Ganglia and Inhibitory Neurons

The human basal ganglia (BG), subcortical nuclei fundamental to motor regulation and cognitive modulation, is constructed from neurons produced during gestation in the adjacent ganglionic eminences (GEs). GEs are transient structures in the ventral prenatal brain that also generate GABAergic inhibitory neurons which migrate to destinations in the BG, cortex and other destinations. This study aims to elucidate the epigenomic and 3D-genomic dynamics involved in the specification and maturation of GEs and GE-derived neurons, using single-nucleus methyl-3C sequencing (snm3C-seq), highly-multiplexed spatial transcriptomics, and chromatin+RNA single-molecule imaging. Our multi-modal data support a heterogeneous temporal progression across GE subregions, with the lateral GE (LGE) showing declining neurogenic activity in mid-gestation and caudal GE (CGE) exhibiting ongoing developmental progression through infancy. We identified regulatory programs that specify subtypes of BG principal cells, medium spiny neurons (MSN), via synchronized maturation of the 3D-epigenome. In infant brains, we found a transient short-range enriched (SE) chromatin conformation during the transition between oligodendrocyte progenitors (OPCs) and oligodendrocytes (ODCs), and a temporary shift toward Long-range Enriched (LE) chromatin conformation in projection neurons, extending previous works showing the differentiation of neurons and glial cells is associated with permanent SE and LE conformation, respectively. Lastly, we found that gene regulatory regions active in MSNs were enriched in loci associated with genetic risk for neuropsychiatric disease. Our study delineates the highly complex, lineage-specific 3D genomic dynamics in ventral progenitors and basal ganglia populations of the perinatal human brain. HighlightsO_LIJoint 3D genome and DNA methylome analysis of ventral brain progenitor zones C_LIO_LIHeterogeneous developmental progressions of the ganglionic eminences C_LIO_LIDistinct development dynamics and regulatory landscape of MSNs and interneurons C_LIO_LITransient remodeling of the 3D-genome in neurons and oligodendrocyte progenitors C_LI

genomics↗

bioRxiv2026

Organoid-Based Transcriptomics Indicate IFIT-Associated Immune Modulation during Cryptotanshinone Treatment in Bladder Cancer

Bladder cancer (BC), particularly muscle-invasive and metastatic disease, remains a major clinical challenge despite recent advances in immunotherapy. In this study, we aimed to identify a promising antitumor compound from five candidate small molecules and to explore its potential roles in BC progression. Through antiproliferative screening, cryptotanshinone (CTS) was identified as the promising candidate. Using both two-dimensional BC cell lines and three-dimensional bladder tumor organoid models, we comprehensively evaluated the effects of CTS on cell proliferation, migration, apoptosis, and organoid growth. To further explore the underlying mechanisms, transcriptomic sequencing based on bladder cancer organoid models, protein-protein interaction network analysis, and public databases (TCGA-BLCA, TIMER, and TISIDB) were integrated to examine immune-related pathways and potential molecular targets associated with CTS. GeneMANIA network prediction and molecular docking analyses were subsequently performed to investigate upstream regulatory networks and the potential interactions between CTS and key components of the cGAS-STING-IFN-I-JAK-STAT signaling pathway. Integrative analyses suggested that IFIT1, IFIT2, and IFIT3 may function as immune-associated genes potentially linked to BC progression, patient prognosis, immune cell infiltration, and PD-1/PD-L1 expression. Molecular docking results suggested that CTS may interact with core regulatory proteins within the cGAS-STING-IFN-I-JAK-STAT pathway, potentially influencing IFIT transcriptional regulation. Collectively, these findings indicate that CTS exhibits measurable antitumor and immunomodulatory effects, which may be associated with modulation of the cGAS-STING-IFN-I-JAK-STAT-IFIT signaling axis, supporting its potential as a small-molecule candidate for bladder cancer.

cancer biology↗

bioRxiv2026

EXOSC3 G191 Variants Trigger System-Wide Recalibration of RNA Processing Machinery

Pathogenic variants in EXOSC3, a noncatalytic subunit of the RNA exosome, cause pontocerebellar hypoplasia type 1B (PCH1B), yet substantial variability in disease severity is observed among individuals carrying different EXOSC3 alleles. The molecular mechanisms of RNA exosome dysfunction in individuals carrying EXOSC3 p.G191 variants remains unresolved. To address this, we generated CRISPR/Cas9-engineered human cell models harboring EXOSC3 p.G191 variants and performed integrated transcriptomic, proteomic, and computational structural analyses. EXOSC3 p.G191 variants produced extensive, allele- and dosage-dependent alterations in gene expression and splicing, with heterozygous variants causing broad but attenuated disruption relative to homozygous EXOSC3 G191D/G191D cells. All EXOSC3 G191 variants promoted increased skipping of exon 3 in EXOSC3 transcripts, generating a short isoform predicted to encode an unstable proteoform. Molecular dynamics and {lambda}-dynamics simulations predicted substantial thermodynamic destabilization of all EXOSC3 G191 variant proteoforms, consistent with reduced protein abundance and thermal stability measured by global proteomics and PISA. At the protein complex level, EXOSC3 p.G191 variants were associated with coordinated decreases in all RNA exosome core subunits and the exonuclease EXOSC10, consistent with destabilization of RNA exosome assembly and orphan protein decay. In contrast, the catalytic exonuclease DIS3 and multiple independent RNA processing pathways were upregulated, indicating compensatory recalibration of RNA metabolism. Together, these findings link variant-induced alternative splicing, RNA exosome complex destabilization, and adaptive network responses to phenotypic variability in EXOSC3 p.G191-associated disease.

systems biology↗

bioRxiv2026

OSTM1 is a ubiquitin E3 ligase that suppresses B-cell malignancy by activating the cAMP/PKA/CREB pathway

Osteoclastogenesis-associated transmembrane protein 1 (OSTM1) is a glycosylated, membrane-integral protein that regulates lysosomal homeostasis, with loss-of-function mutations causing autosomal recessive osteopetrosis. Through a whole-genome CRISPR/Cas9 screen, we identified OSTM1 as a previously unrecognized tumor suppressor in B-cell malignancies. Consistent with this role, OSTM1 is frequently deleted or downregulated across a broad spectrum of human B-cell cancers. In mice, B-cell-specific monoallelic or biallelic ablation of Ostm1 cooperates with Cdkn2a loss to drive lymphomagenesis with near-complete penetrance. Mechanistically, we uncover a cytosolic, non-glycosylated fraction of OSTM1 that functions as a ubiquitin E3 ligase to promote proteasomal degradation of phosphodiesterase 3B (PDE3B). As PDE3B hydrolyzes cAMP and suppresses the tumor-protective PKA/CREB/CREBBP signaling axis, loss of OSTM1 leads to PDE3B stabilization, attenuation of cAMP signaling, and enhanced oncogenic transformation. Together, our findings establish OSTM1 as a critical suppressor of B-cell lymphomagenesis through regulation of the cAMP/PKA/CREB pathway.

cancer biology↗

bioRxiv2026

TLR7 inhibition limits cardiac ischemic injury by disrupting ITGAM-dependent immune-endothelial interaction

Percutaneous coronary intervention (PCI) limits ischemic myocardial infarction but also triggers ischemia-reperfusion (I/R) injury in part driven by innate immune activation. Here, we identify Toll-like receptor 7 (TLR7), an endosomal sensor of single-stranded RNA, as a mediator of post-ischemic inflammation and myocardial damage. Pharmacological inhibition of TLR7 with enpatoran reduced myocardial inflammation and infarct size and improved cardiac function in a mouse model of I/R injury when administered before, during, or shortly after ischemia. Single-nucleus RNA sequencing revealed coordinated post-I/R expansion of myeloid cells and distinct inflammatory endothelial subsets enriched for leukocyte-interaction programs, with marked upregulation of Itgam in cardiac leukocytes and endothelial cells and in circulating monocytes. Circulating ITGAM+ monocytes were similarly increased in patients with ST-segment elevation myocardial infarction 24 hours after coronary stenting. Mechanistically, TLR7 activation induced Itgam expression in endothelial cells and leukocytes and promoted their adhesion via ITGAM-ICAM1 interaction under physiological shear stress, whereas ITGAM neutralization disrupted this interaction, reduced immune cell infiltration, and limited ischemic injury. These findings define a TLR7-ITGAM signaling axis as a key driver of endothelial-leukocyte crosstalk in myocardial I/R injury and support TLR7 inhibition as a promising therapeutic strategy to mitigate acute myocardial infarction.

immunology↗

bioRxiv2026

LONP-1 deficiency causes dysregulated protein synthesis within mitochondria that is restored by mitoribosomal mutations

Mitochondrial homeostasis is maintained by multiple molecular chaperones and proteases located within the organelle. The mitochondrial matrix-localized protease LONP-1 degrades oxidatively damaged or misfolded proteins. Importantly, LONP-1 also regulates mitochondrial DNA replication. Here, we show that mutations in C. elegans that impair LONP-1 function cause dysregulation of mitochondrial DNA replication, mitochondrial RNA transcription and protein synthesis within the mitochondrial matrix. LONP-1 deficient worms had reduced levels of oxidative phosphorylation proteins despite increased mtDNA-encoded protein synthesis. Via a forward genetic screen, we identified three mutations that restored mitochondrial function and the rate of development in lonp-1 mutants to levels comparable to those in wildtype worms. Interestingly, all three suppressor mutations were found in genes encoding mitochondrial ribosome proteins. A point mutation in the mitochondrial ribosome protein MRPS-38 restored oxidative phosphorylation in lonp-1 mutant worms. Combined, our results suggest that LONP-1 regulates mitochondrial protein synthesis and that the suppressor mutations within MRPS-38 or MRPS-15 enhance oxidative phosphorylation complex assembly by slowing translation.

cell biology↗

bioRxiv2026

When CycloneSEQ meets Oxford Nanopore Technologies: a performance comparison of contemporary nanopore DNA sequencing platforms

Nanopore sequencing enables direct analysis of native DNA modifications, but these modifications can also introduce systematic basecalling errors. Here, we investigated how bacterial DNA methylation contributes to nanopore substitution errors using matched native whole-genome sequencing (WGS) and methylation-depleted whole-genome amplification (WGA) datasets from six bacterial species across CycloneSEQ (CS) and Oxford Nanopore Technologies platforms (ONT). Adenine-to-guanine (A2G) and guanine-to-adenine (G2A) substitutions were consistently enriched across species, nanopore platforms, sequencing configurations, and basecalling models, indicating a shared nanopore-associated substitution bias. This enrichment remained detectable in WGA reads, whereas native WGS reads showed a further increase. Using independent PacBio methylation profiling, we found that the WGS-associated substitution excess was strongly concentrated around bacterial methylation motifs and was minimal in non-motif regions. The magnitude and substitution pattern of these errors varied among motifs and sequencing platforms. At a subset of motif-associated positions, alternative-base fractions exceeded 50%, producing SNP-like signals. In ONT data, 28 WGS-specific calls survived the applied SNP-calling filters, all within PacBio-supported methylation contexts, and most showed significant strand imbalance. Together, these results identify a shared A2G/G2A substitution bias in all nanopore datasets and support a methylation-associated increase in these errors near bacterial methylation motifs, with some loci producing SNP-like artifacts.

bioinformatics↗

bioRxiv2026

Multiomics reveals epigenetic control of fibroblast activity after myocardial infarction and a key role for RUNX transcription factors

BackgroundAfter myocardial infarction (MI), cardiac fibroblasts proliferate and undergo a sequential differentiation process. They first transition into cardiac myofibroblasts, a transient and highly contractile state, and ultimately into matrifibrocytes, a more stable state that partially resembles chondrocytes. These dynamic transitions are essential for infarct healing and scar formation. While insufficient fibroblast activation can compromise infarct integrity, excessive activation promotes pathological fibrosis that impairs cardiac function. Despite its clinical importance, the transcriptional and epigenetic regulation of these transitions remain poorly understood. Elucidating underlying mechanisms is critical for developing strategies to fine-tune fibroblast activity during cardiac repair. MethodsWe performed bulk RNAseq, ATACseq, CUT&Tag, CUT&RUN, EMseq, and Hi-C on cardiac fibroblasts from uninjured and post-MI mouse hearts. In parallel, we conducted single-nucleus multiomic (snRNAseq and snATACseq) profiling across multiple time points after MI. Subsequent integrated analysis explored epigenetic mechanisms regulating cardiac fibroblast gene expression and activity. Using an improved computational strategy, we constructed gene regulatory networks to identify key transcription factors and biological processes regulated by these transcription factors. To assess the role of Runx1 specifically, we used tamoxifen-inducible, fibroblast-specific Runx1 knockout mice to evaluate transcriptional, epigenetic, and functional outcomes with the same genomic tools and additional complementary assays. ResultsCardiac fibroblasts undergo extensive chromatin remodeling after MI, which is highly correlated with changes in transcriptomic profiles. In contrast, the role of DNA methylation is relatively minor. Gene regulatory network analysis identified Runx1 as a central regulator of cardiac fibroblast proliferation and matrifibrocyte differentiation. In vitro and in vivo validation confirmed Runx1 as a key modulator of transcriptional and epigenetic changes in cardiac fibroblasts. Runx1 KO reduced cardiac fibroblast proliferation, disrupted the myofibroblast-to-matrifibrocyte transition, and affected macrophage cytokine expression through altered cardiac fibroblast-macrophage communication. Fibroblast-specific Runx1 knockout mice showed improved post-MI survival and reduced cardiac dilatation, especially in males. Simultaneous Runx2 deletion further enhanced the effects of Runx1 knockout. ConclusionsCardiac fibroblast activation and differentiation after MI are regulated by dynamic epigenetic changes. Runx1 plays a pivotal role in modulating cardiac fibroblast activities, and its deletion improves cardiac repair by mitigating maladaptive fibroblast responses. By illuminating the centrality of Runx1 in post-MI repair, this study identifies an actionable pathway for therapeutically steering fibroblast responses.

genomics↗

bioRxiv2026

MR-μScope: a multi-scale and simultaneous MRI-miniaturized microscopy system for elucidating neurovascular coupling

Blood Oxygen Level Dependent functional MRI (BOLD-fMRI) revolutionized non-invasive brain mapping, yet the physiological origins of its signal, linking microscopic neurovascular activity to macroscopic hemodynamics, remain elusive. To bridge this gap, we developed MR-Scope: a simultaneous and multimodal platform that integrates preclinic high-field MRI (9.4T) and miniaturized fluorescence microscopy (Miniscope). Our system contains an MR-compatible Miniscope with electromagnetic shielding, a customized radiofrequency coil with a central optical window, and an adjustable animal cradle, enabling artifact-free acquisition of whole-brain fMRI alongside microscopic vascular dynamics. Phantom validation confirmed negligible cross-modal interference (fMRI SNR [≥] 15 dB; optical SNR [≥] 26 dB). MR-Scope captured stimulus-evoked microvascular dilation and blood flow velocity changes in the somatosensory cortex concurrent with BOLD signals, revealing vessel-size-dependent neurovascular coupling. MR-Scope provides an effective solution for deciphering multi-scale neurovascular interactions and offers unique potential for advancing research into brain function and disease mechanisms involving vascular pathology.

bioengineering↗

bioRxiv2026

NORAD orchestrates KLC1-mediated SFPQ transport via liquid-liquid phase separation

Neuronal function requires precise long-distance axonal transport mediated by molecular motors and RNA-binding proteins like SFPQ, though regulatory mechanisms remain poorly defined. We identify long non-coding RNA NORAD as a master regulator of this process through liquid-liquid phase separation (LLPS). While SFPQ and kinesin-1 mediate cargo delivery, the specific RNA coordinating their interaction was unknown. We demonstrate NORAD directly binds kinesin light chain 1 (KLC1) and promotes SFPQ condensation into dynamic LLPS droplets, enabling efficient transport. CRISPR-assisted mapping and functional assays show NORAD depletion disrupts granule dynamics, impairs neuroprotective mRNA localization, and induces axonal degeneration. In vitro reconstitution confirms NORAD-KLC1 synergy enhances SFPQ phase separation, and neuron-specific knockout mice exhibit motor deficits with reduced neuronal density. These findings establish the first evidence of lncRNA NORAD-mediated LLPS in axonal transport, revealing a new paradigm for RNA-guided neuronal maintenance.

molecular biology↗

bioRxiv2026

Large-scale Visuomotor Reaction Time Self-Testing Reveals Subtle Motor Changes in Older Adults with Subjective Cognitive Impairment

IntroductionAffordable tools for early Alzheimers disease (AD) detection could support drug development and early intervention. Subtle motor changes may indicate preclinical AD, but hand response selection and initiation speeds are understudied. This study assessed whether unsupervised, online visuomotor reaction time (RT) tests relate to subjective cognitive impairment (SCI), a validated high risk state for future conversion to AD MethodsA total of 910 participants (age 66.3{+/-}7.5, 70.8% female) completed assessments of simple and choice visuomotor RT tests at home as part of the online TAS Test protocol; they also completed the Cambridge Neuropsychological Test Automated Battery (CANTAB) episodic memory and executive function tests. Among them, 142 participants reported SCI. ResultsOn the TAS Test visuomotor tests, SCI was associated with 8.4% [1.4%, 15.4%] longer RT ( (p = .008; adjusted for task complexity), greater odds of time-out failure (OR = 1.35 [1.01, 1.81]; p = .037), and greater variance in RT (log-variance (SCI - comparison) = .094 [.028, .159]; p < .001). There were no significant differences between the SCI and comparison groups on any of the CANTAB tests. After adjusting for SCI status, none of the CANTAB tests were significantly associated with RT. DiscussionSCI was associated with longer and more variable visuomotor RT, and greater odds of time-out failure, while not being associated with tests of memory and executive function. Cognitive test scores did not explain a significant amount of variance in visuomotor RT. Taken together, these results support a hypothesis that people with SCI may be experiencing earlier visuomotor deficits that are distinct from (or precede) decline in episodic memory and executive function. Visuomotor tasks that record RT may be more sensitive to preclinical manifestations of cognitive decline than more traditional tests of cognitive function.

bioinformatics↗

bioRxiv2026

EssTFNet: Integration of Adaptive Time - Frequency and DNA Language Models for Interpretable Human Essential Gene Prediction

Essential genes are defined as those that are indispensable for an organisms survival. The loss of function of these genes results in cell death or an inability to complete the normal life cycle. Research on essential genes is pivotal in elucidating the origin and evolution of life, as well as in identifying potential therapeutic targets. Therefore, accurately predicting essential genes is of great scientific importance and has many applications in basic research and the biomedical field. In this study, we propose EssTFNet, a novel and interpretable deep learning framework that combines adaptive time-frequency analysis with a DNA language model to achieve accurate prediction of human essential genes while enabling mechanistic biological interpretation. Specifically, EssTFNet leverages the architecture of ATFNet, which innovatively maps DNA and protein sequences into equivalent time-series signals to extract periodic and non-stationary features, thereby enhancing the models capacity to capture complex sequence patterns. Through effective feature selection and architectural optimization, EssTFNet strikes a favorable balance among prediction accuracy, model interpretability, and cross-tissues generalization capability, significantly outperforming current mainstream sequence-based deep learning methods with an AUC of 0.8336 and an AUPR of 0.8212. Additionally, the DeepLIFT attribution method was employed to identify functional motifs closely associated with gene essentiality, offering valuable insights for experimental validation. For the convenience of researchers, we have developed an easy-to-use web server and made it along with the source code in a GitHub repository: https://github.com/QIANJINYDX/EssTFNet. Overall, this study presents a potentially useful methodological framework for human essential genes prediction, which could provide valuable insights for future research and applications in this field.

bioinformatics↗

bioRxiv2025

Identification of molecular and clinical ALS subgroups based on TDP-43 loss of function molecular markers from population-based patient-derived iPS motor neurons

BackgroundAmyotrophic lateral sclerosis (ALS) is a uniformly fatal neurodegenerative disease characterized by progressive cortical and spinal motor neuron loss, with most patients surviving only 2-5 years post-diagnosis. While approximately 10% of cases are familial (fALS), the remaining 90% are sporadic (sALS) with unknown genetic drivers. Importantly, clinical presentations are heterogeneous in both sporadic and familial ALS, underscoring the complexity of the disease. A pathological hallmark of ALS is the mislocalization of RNA-binding protein TDP-43 from the nucleus to the cytoplasm. This mislocalization produces both loss of function consequences, such as widespread RNA processing and splicing defects, as well as potential toxic gain of function effects associated with cytoplasmic aggregation. ResultsIn this study, we used RT-PCR data from induced pluripotent stem cell-derived motor neurons derived from 180 sALS and C9orf72 fALS patients from the Answer ALS collection to identify biological subgroups based on TDP-43 loss-of-function signatures. Spectral embedding revealed four distinct molecular clusters, including one subgroup genetically similar to controls and another with the most dysregulated mRNA expression, suggesting differing disease severity. Linear mixed models were then used to assess the longitudinal trajectory of over 90 clinical measures, and the between-cluster interaction effects were evaluated. Conclusions36 clinical outcomes showed significant differences across clusters, supporting the presence of biologically and clinically distinct ALS subtypes based on the TDP-43 associated pathogenic cascade. These findings demonstrate a critical role of RNA profiling in uncovering biologically meaningful subtypes of ALS, potentially allowing for more precise prognostic tools and the development of future personalized therapeutic approaches.

neuroscience↗

bioRxiv2025

TMC5 promotes lung adenocarcinoma cell proliferation, migration and invasion by regulating epithelial-mesenchymal transition

Background/purposeIn recent years, evidence has indicated that transmembrane channel-like 5 (TMC5) plays an important role in various cancers. Previously, one study showed that TMC5 was highly expressed in lung adenocarcinoma (LUAD), but its mechanism in LUAD remained unclear. In this study, we aimed to investigate the effects of TMC5 and its underlying mechanisms in LUAD progression. MethodsThe expression level of TMC5 in LUAD tissues was detected by real-time quantitative PCR. TMC5 was knocked down in A549 and H1437 cell lines using lentiviral transfection. The oncogenic effect of TMC5 on LUAD cell proliferation was evaluated by CCK-8 assay and colony formation assay. Transwell assay was employed to assess migration and invasion. ResultsTMC5 was overexpressed in LUAD tissues compared with normal tissues. Suppression of TMC5 expression reduced proliferation, migration, and invasion, while also decreasing the expression of mesenchymal markers and increasing epithelial markers in A549 and H1437 cells. Conversely, higher TMC5 expression significantly increased the expression of mesenchymal markers and decreased epithelial markers. ConclusionTMC5 facilitates the malignant behaviors of LUAD cells by regulating epithelial-mesenchymal transition, suggesting its potential as a promising diagnostic and therapeutic target.

molecular biology↗

bioRxiv2025

The plant circadian clock exerts stronger control over the diel proteome than the transcriptome

AbstractThe plant circadian clock is a genetic circuit composed of multiple mutually-regulating transcription factors that together synchronize internal biological rhythms to the [~]24-hour period of planetary rotation. While it has been known for over a decade that nearly 40% of the transcriptome in the model plant Arabidopsis oscillates with a circadian rhythm, it is yet unclear to what extent this translates to the proteome. Here, through parallel quantitative proteome and transcriptome time-course profiling of Arabidopsis wild-type plants and a panel of clock deficient plant lines, we show that specific clock genes exercise extensive control over diel proteome rhythmicity, and to a much greater extent than they do the transcriptome. This control results in a clock-dependent synchronization of rhythmic proteins along a bimodal phase distribution that is lost in circadian clock deficient plants. This suggests pervasive post-translational control of gene expression by specific elements of the circadian system, notably the morning expressed LHY/CCA1 module. Our findings imply that the circadian clock exercises much greater control of gene expression through proteostasis mechanisms than previously recognised, necessitating a recalibration of our current understanding of clock proteins as primarily transcriptional regulators.

plant biology↗

bioRxiv2025

Enigma: An Efficient Model for Deciphering Regulatory Genomics

Genomic sequence-to-function models have emerged as powerful tools for deciphering cis-regulatory grammar to advance our understanding of disease biology and guide therapeutic development. Recent advances have been driven by multi-task training of large transformer-based models on thousands of genome tracks. However, these performance gains have come at significant computational cost for both training and inference, hindering large-scale applications and slowing future model development. Here, rather than continuing to scale model size and add more training tracks, we focus on architectural efficiency and train on a substantially smaller, curated set of genome tracks. Our model Enigma achieves competitive performance with current state-of-the-art models at single-base resolution while substantially reducing computational cost. On zero-shot variant effect prediction benchmarks, Enigma outperforms the leading open-source model, the Borzoi ensemble, while using 10.9% of its compute and improving resolution from 32 bases to a single base. Compared to AlphaGenome, Enigma achieves 90.4 - 97.3% of its performance using 7.5% of its estimated compute. These improvements in efficiency can facilitate further development of models for regulatory genomics. We demonstrate this by fine-tuning Enigma on predicting three new molecular phenotypes -- ChIP-seq, RNA half-life, and translation efficiency -- achieving or exceeding the performance of state-of-the-art task-specific models. We are providing Enigma for non-commercial use to benefit the broader research field. [Formula]Code: https://github.com/deepgenomics/enigma

genomics↗