Biology subjects

Jin, Y.

Publications and source records attributed to Jin, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

STIMscope: centimeter-scale all-optical imaging and patterned optogenetic manipulation at single-cell resolution

Linking observation to intervention at cellular resolution makes it possible to move from measuring network activity to testing the contribution of defined neurons or ensembles within the same preparation. All-optical probing provides this capability by combining fluorescence-based readout with targeted optogenetic manipulation. Yet the platforms that deliver this capability remain complex, expensive, and difficult to maintain, requiring specialized expertise that has confined them to a small number of laboratories. They also typically provide fields of view too limited for studies of large, distributed neuronal populations. We address these constraints with the Spatiotemporal Illumination Microscope (STIMscope), a one-photon benchtop platform that integrates large-aperture tandem optics with a small-pixel back-illuminated CMOS sensor, a digital micromirror device for patterned illumination, and a GPU-based processing unit coordinated by a microcontroller for hardware-level synchronization. Ray-tracing simulations and point-spread-function measurements confirm cellular-scale resolution, with imaging lateral FWHM of 5.6 {micro}m at the field center and 5.8 {micro}m at the edge, and excitation lateral FWHM of 5.8 {micro}m at the center and 6.2 {micro}m at the edge, supporting fields of view as large as 14 mm x 11 mm in the demagnified configuration. The accompanying Closed-loop ready Real-time Imaging and Stimulation Pipeline (CRISPI) provides GPU-accelerated calibrated mask projection (26.3 ms latency), online ROI trace extraction, and modular ZeroMQ-based control, with a measured imaging-to-stimulation loop benchmark of 91.6 ms. We validate STIMscope in fixed mouse brain tissue, live iPSC-derived human neuronal cultures, and ex vivo organotypic slices of mouse auditory cortex. In organotypic slices, we show that both static and spatiotemporal stimulus identity can be decoded from population activity, revealing reservoir-like population dynamics, and that this decodability remains stable in the same neuronal population over hours. We further show that post-stimulus activity retains information about recent stimuli for several seconds, consistent with short-term memory dynamics. With a bill of materials under $5,000 USD and all mechanical designs, firmware, and software released open-source, STIMscope makes all-optical neuroscience experiments a routine capability accessible to laboratories without specialized optical engineering expertise.

bioengineering↗

bioRxiv2026

Particle Biology: A Perspective on a First-Principles Theory of Life

This Perspective formally proposes Particle Biology as a unifying theoretical framework to address the critical bottleneck in current life science research. Current life science research has reached a critical bottleneck. While the field has advanced to the study of 3D genomic spatial configurations and chromosomal organization, it remains largely descriptive and confined to the macromolecular level. This approach lacks a first-principles understanding of the underlying physical forces that drive biological processes. This Perspective formally proposes Particle Biology as a unifying theoretical framework. We establish an axiomatic system positing that life phenomena are fundamentally emergent spatiotemporal patterns of electromagnetic forces among atoms, electrons, and nuclei operating far from thermodynamic equilibrium. By defining biological states through the Biological Hamiltonian and mapping biochemical pathways to multidimensional Potential Energy Surfaces (PES), we bridge the gap between descriptive biology and predictive physics. We categorize core research technologies into three modalities--seeing, computing, and controlling particles--facilitated by advancements in Cryo-EM, AlphaFold 3, and Boron Neutron Capture Therapy (BNCT). Ultimately, the trajectory of molecular biology has evolved from cells to DNA and onto the 3D spatial genome, yet it cannot go deeper within current paradigms. The next logical evolution is to move beyond the macromolecular bottleneck to focus on the electromagnetic interactions between atoms and ions--the true Particle Biology level--to redefine disease and intervention.

biophysics↗

bioRxiv2026

TxConformal: Controlling False Discoveries in AI-Driven Therapeutic Discovery

Artificial Intelligence (AI) is transforming therapeutic discovery by scoring a large set of promising candidates and prioritizing a shortlist for further investigation. Quantifying the reliability of AI scores and preventing false positives among selected candidates is key to the efficiency of the discovery process. Conformal prediction (CP) has emerged as a popular tool for guiding such prioritization, especially via the conformal selection framework to control false discovery rates (FDR) in selecting top-ranked candidates under distributional shift1, 2. However, deploying these advances in real-world therapeutic discovery remains challenging: distribution shifts are difficult to quantify and correct in high-dimensional biomedical data, and practical workflows often require flexible error metrics. Here, we present TO_SCPLOWXC_SCPLOWCO_SCPLOWONFORMALC_SCPLOW, a general framework for trustworthy decision making when building shortlists using AI scores. TO_SCPLOWXC_SCPLOWCO_SCPLOWONFORMALC_SCPLOW adjusts for distribution shift by balancing the hidden representations in AI models and then provides confidence measures for true discoveries of target biological properties. These confidence measures, interpretable as p-values, can be used in conjunction with statistical multiple testing procedures to derive selection decisions with limited false positives or to estimate the errors in given selection decisions. TO_SCPLOWXC_SCPLOWCO_SCPLOWONFORMALC_SCPLOW controls the false positive rate in six real-world tasks spanning various therapeutic discovery stages, modalities, and AI models with realistic data splits. When selecting promising combinatorial genetic perturbations, TO_SCPLOWXC_SCPLOWCO_SCPLOWONFORMALC_SCPLOW nearly halves false-positive selections compared to baseline methods, substantially reducing unnecessary experimental costs by tens of thousands of dollars. When selecting stable protein structures under mutant shifts, TO_SCPLOWXC_SCPLOWCO_SCPLOWONFORMALC_SCPLOW identifies about 10 times more proteins than baseline methods at stringent thresholds when running at a target FDR level of 10%, recovering over 90% of valuable candidates that baseline methods miss due to unaccounted distribution shifts. Furthermore, we demonstrate that TO_SCPLOWXC_SCPLOWCO_SCPLOWONFORMALC_SCPLOW robustly supports various alternative error metrics suitable for resource-constrained settings. Finally, in a prospective fixed-budget virtual screening campaign for novel antibiotic discovery, TO_SCPLOWXC_SCPLOWCO_SCPLOWONFORMALC_SCPLOW predicted false positives in close agreement with experimental outcomes, with substantial improvements over simple baselines.

bioinformatics↗

bioRxiv2026

Chromosomal rearrangements 1 and sequence similarity drivepreferential allosyndetic introgression from a wild relative into wheat

Recombination in polyploid genomes is generally constrained to homologous or homoeologous chromosomes; however, how chromosomal rearrangements influence recombination between chromosomes remains unclear. Here, we demonstrate that large-scale chromosomal rearrangements in the wild relatives of wheat are associated with recombination involving non-homoeologous chromosomes or arms during alien gene introgression under conditions that permit homoeologous recombination mediated by ph1b. Using a wheat chromosome 6A monosomic-induced 6AS*6CL Robertsonian translocation combined with ph1b-mediated recombination, we generated 17 independent recombinants carrying a new stem rust resistance gene, Sr69, from Aegilops caudata chromosome arm 6CL. Unexpectedly, 94.1% (16 of 17) of recombinants resulted from exchanges with wheat group-7 chromosomes rather than with the homoeologous group-6 chromosome. Comparative sequence- and marker-based analyses identified a 67-Mb rearranged interval on Ae. caudata 6CL that corresponds to telomeric regions of the long arms of wheat group-7 chromosomes. Sequence similarity within this interval was quantitatively associated with recombination frequency, with higher similarity corresponding to more frequent translocations. Physical and optical mapping showed that recombination within the rearranged interval generated compensating 7A/6C, 7B/6C, and 7D/6C translocations, whereas recombination outside this region produced non-compensating 6A/6C exchanges. An independent case involving the powdery mildew resistance gene Pm7C showed a similar correspondence between a rearranged 7CL region and preferential introgression into wheat 7DS. Together, these results indicate that ph1b-mediated recombination involving structurally altered chromosomes is driven by local chromosomal structure and sequence similarity rather than strict homoeologous group identity. This provides a mechanistic basis for harnessing untapped beneficial genes from structurally rearranged alien genomes. Significance StatementAlien gene introgression is a powerful strategy for wheat improvement, typically relying on ph1b-mediated recombination between homoeologous chromosomes. The genomic basis and outcomes of introgression from structurally rearranged alien chromosomes remain unclear. Here, we show that ph1b-induced recombination can efficiently target wheat-allosyntenic blocks in rearranged alien genomes, preferentially transferring genes from structurally altered alien segments into their syntenic regions on wheat chromosomes of different homoeologous groups. Crossover formation is governed by extended sequence similarity within corresponding intervals rather than strict collinearity across entire homoeologous chromosomes. As many wild species exhibit extensive genome rearrangement, these findings and methodologies expand access to underexploited genetic diversity embedded within highly rearranged wild genomes for wheat improvement.

genetics↗

bioRxiv2026

Signal, noise, and bias in phylogenetic inference:potential and limits to the resolution of phylogenetic trees in the phylogenomic era

Phylogenomic datasets assembled to resolve the Tree of Life now routinely span thousands of loci comprising millions of characters. Yet the persistence of incongruent topologies across such datasets reveals a fundamental truth of phylogenetics: not all data are equally informative. Here we derive analytical approaches that predict the relative impacts of phylogenetic signal, stochastic noise, and systematic bias on phylogenetic inference. We show that these three components exhibit divergent scaling properties with character sampling: signal and bias accumulate linearly, while noise accumulates nonlinearly with a concave trajectory. For some phylogenetic problems, substantial amounts of phylogenetic noise may eventually be overwhelmed by signal. For other phylogenetic problems--especially those involving deep divergences, short internodes, or constrained character-state space--the slope of signal accumulation can be so shallow that even signal from genome-scale data may never practically exceed noise. Moreover, linear accumulation of phylogenetic bias can in principle continuously overwhelm accumulation of signal at a lower slope with additional characters, regardless of dataset size. Applying our theory to empirical datasets, we show that anchored hybrid enrichment and ultraconserved element loci, like any loci, can exhibit signal that is overwhelmed by noise, and that character acquisition biases in some loci can further confound inference. Given the pervasive nature of incongruence in the phylogenomic era, our work provides a theoretical foundation for understanding the limits of inference, improving experimental design, and guiding efficient and accurate resolution of the Tree of Life.

evolutionary biology↗

bioRxiv2026

A graph-based learning approach to predict the effects of gene perturbations on molecular phenotypes

MotivationLarge-scale gene knockdown/knockout screens have been used to gain insight into a wide array of phenotypes and biological processes. However, conducting such experiments is expensive and labor-intensive. In this work, we present a general graph-based machine-learning approach that can predict the effects of gene perturbations on molecular phenotypes of interest given some measured phenotypic effects of other gene perturbations. The motivation for learning models that can predict the effects of gene perturbations is fourfold. Such models can (1) predict effects for unmeasured genes in cases in which cost or technical barriers preclude perturbing every gene, (2) prioritize unmeasured genes or sets of genes for subsequent perturbation experiments, (3) hypothesize mechanisms that underlie the relationships between the perturbed genes and their effects, and (4) generalize to other unmeasured phenotypes of interest. ResultsWe evaluate our approach by applying it, in conjunction with four different learning methods, to learn models for four varied phenotypes. Our empirical evaluation demonstrates that the learned models (1) show relatively high levels of predictive accuracy across the four phenotypes, (2) have better predictive accuracy than several standard baselines, (3) can often learn accurate models with small training sets, (4) benefit from having multiple sources of evidence in the input representation, (5) can, in many cases, transfer their predictive value to other phenotypes. Data availabilityThe assembled data sets and source code for this work are available at: https://github.com/Craven-Biostat-Lab/graph-molecular-phenotype-prediction Author summaryOne general approach for gaining insight into the genes involved in a specific biological process is to conduct an experiment in which individual genes are perturbed and the effect on the process is measured for each perturbation. Large-scale experiments of this type have provided important biological insights, but they are often expensive and labor-intensive to perform. As a result, it is not always feasible to measure the effects of perturbing every gene. In this article, we present a machine-learning approach to predicting the effects of gene perturbations using available experimental data and biological network information. Our method can estimate the effects of genes that have not yet been experimentally measured, helping researchers identify promising genes to study next. In addition, the models can suggest hypotheses about the molecular interactions that link genes to the biological process of interest. Approaches like this may help guide experimental studies and accelerate the discovery of gene-phenotype relationships.

systems biology↗

bioRxiv2026

lncRNA-ISM1 Promotes Hepatocellular Carcinoma Progression through RBM10-Mediated Alternative Splicing of ISM1 and Akt-S6-Dependent Glucose Metabolic Reprogramming

A low-glucose microenvironment can induce metabolic abnormalities in tumour cells, including hepatocellular carcinoma (HCC) cells, and enhance cancer cell stemness. Isthmin-1 (ISM1) is a recently identified adipokine that promotes glucose uptake and enhances cellular metabolism. While the activity of the ISM1 protein is regulated by glycosylases, its transcriptional and posttranscriptional regulation remain poorly understood. A novel alternatively spliced variant of ISM1 (ISM1-AS) was recently identified. Unlike canonical ISM1, ISM1-AS lacks an AMOP domain, a key structural element required for ISM1 function, suggesting the loss of its metabolic regulatory activity. In this study, we found that ISM1 expression was significantly reduced in HCC tissues and correlated with poor prognosis. Functional assays revealed that ISM1 overexpression markedly suppressed HCC cell proliferation and invasion, whereas ISM1-AS overexpression had the opposite effect. Importantly, ISM1 co-overexpression attenuated the oncogenic effects of ISM1-AS. Knockdown of the antisense transcript lncRNA-ISM1 reduced ISM1-AS expression while increasing ISM1 expression, thereby suppressing HCC proliferation and migration. Mechanistically, lncRNA-ISM1 regulated ISM1 alternative splicing by interacting with RBM10, thereby altering the balance between ISM1-AS and ISM1. This shift activated the Akt-S6 signalling pathway, promoting glycolysis and HCC progression. In vivo experiments further confirmed that the lncRNA-ISM1/ISM1-AS/ISM1 axis drives tumour growth via Akt-S6 activation. Our findings demonstrate that lncRNA-ISM1 promotes HCC progression through the RBM10-mediated alternative splicing of ISM1 and activation of the Akt-S6 signalling pathway, highlighting its potential as a therapeutic target for HCC.

molecular biology↗

bioRxiv2026

The long non-coding RNA ACHLYS modulates biomolecular condensates to regulate alternative splicing in root development

Alternative splicing (AS) enables eukaryotes to dynamically adjust RNA and protein isoforms encoded in one gene. Long non-coding RNAs (lncRNA) have emerged as novel regulators of AS through multiple modes of action, including interactions with splicing factor (SF) proteins. Here, we used Arabidopsis thaliana lateral root development to dissect the specificity of lncRNAs in AS regulation. Data mining and a transient expression screen allowed us to identify novel lncRNAs interacting in vivo with the well-characterized SFs Nuclear speckle RNA binding protein A (NSRa) and glycine-rich RNA-binding protein 7 (GRP7), that are differentially expressed during lateral root organogenesis. We identified 4 lncRNAs affecting more than 250 AS events in plant cells, whereby most AS events are unique for each lncRNA. Notably, 19% of the AS events linked to two NSRa-recognized lncRNAs are identical and positively correlated. One lncRNA was named ACHLYS and is highly conserved in several Brassicaceae whereas another was the recently characterized FLAIL lncRNA. ACHLYS knockdown (KD-ACHLYS) and overexpressing lines (OE-ACHLYS) modulate AS regulation in plants and affect root architecture. In parallel, we performed NSRa-iCLIP to determine in vivo genome-wide NSRa binding sites. Interestingly, NSRa binding sites are locally enriched in ACHLYS-dependent AS introns and ACHLYS itself. A specific ACHLYS-induced AS event requires NSRa function showing that ACHLYS defines AS targets through NSRa interaction on specific transcripts. In vitro assays indicate that direct interaction of NSRa with ACHLYS promotes NSRa phase separation. Furthermore, overexpression of ACHLYS in NSRa-GFP plants results in increased accumulation of NSRa in Nuclear speckles. Our data revealed that ACHLYS can modulate NSRa condensates in vivo and binds to NSRa for modifying AS patterns, suggesting a new mechanism where lncRNAs can fine tune SFs regulation and the transcriptome output in eukaryotic organogenesis.

molecular biology↗

bioRxiv2026

Cooperative and competitive interactions among transcription regulatory elements modulate transcription output

Transcription is modulated by interactions among transcription regulatory elements (TREs), including promoters and enhancers, but their underlying interaction specificities remain opaque. Here, we develop a Chromatin-Integrated, landing-pad-based Enhancer Reporter Assay, CIERA-seq, that interrogates regulatory interactions between target promoters and distal TREs in a controlled genomic and chromatin context. We find both promoter- and enhancer-TREs exhibit enhancer activities on target promoters with a specificity that depends on factors that TREs recruit. Promoters are generally enriched for factors involved in the core transcription process, whereas enhancers are enriched for pioneer factors and chromatin remodelers. Our CIERA-seq assays support a model where TREs activate target promoters constrained at different rate limiting steps in transcription by supplying complementary components of the transcription regulatory machinery. An orthogonal analysis using CRISPRi datasets shows that both promoters and enhancers can positively regulate expression of neighboring genes at their native loci. However, promoters are also more prone than enhancers to exhibit negative regulatory effects, a difference that may arise from competition for limiting transcriptional machinery. Together, these findings support a framework in which promoters and enhancers act as cooperative, or competitive, regulatory elements within local transcription hubs to modulate transcription outputs.

molecular biology↗

bioRxiv2026

The genome of an aneuploid cultivar facilitates elucidating the genetic bases of trait polymorphisms in Phalaenopsis orchids

As an important ornamental crop, Phalaenopsis orchids exhibit extraordinary trait diversity with unclear genetic bases. Here, we present a haplotype-resolved, chromosome-level genome for an aneuploid cultivar Santiago. We reveal pervasive variation in the number and sequence among homoeologous genes. When serving as a reference, this genome facilitates the genetic understanding of trait variation in a hybrid population that is highly representative in trait polymorphisms. Specifically, nucleotide polymorphisms in a potential long-distance enhancer and the consequential expression variation of PsAGL6-2, presence/absence of PsMYB12 and b-type homoeologous gene of PsMYB2 determine lip morphology variation, presence/absence of venation-associated stripes and background pink color, respectively. Diverse functions of PsMYBx1 in repressing anthocyanin accumulation across different cultivars further enhances the color patterning diversity in Phalaenopsis. Our study provides a practical framework for using a highly heterogeneous, haplotype-resolved genome to decode phenotypic diversity and has the potential to promote marker-assisted breeding in Phalaenopsis.

genomics↗

bioRxiv2026

Formation of homolog pairing-induced domains in early Drosophila embryo genome

Somatic homolog pairing is a defining feature of the diploid genome organization in Drosophila and underlies its transvection-based gene regulation. Here, to understand the physical effect of homolog pairing on the resulting three-dimensional (3D) organization, we employ the heterogeneous loop model and reconstruct 3D structures of the Drosophila embryo genome based on its haplotype-resolved Hi-C data. The resulting structures reveal robust end-to-end juxtaposition between homologous chromosomes amid substantial cell-to-cell variability. On sub-megabase scales, tight pairing between homologous loci at domain boundaries give rise to significant coincidence between cis and trans-homolog domain boundaries in the Hi-C map, while interior regions remain loosely associated. To uncover the physical origin of this organization, we compare the contact maps resulting from the polymer models implementing specific and non-specific button-mediated pairing mechanisms with Hi-C, finding that the intra-chromosomal contacts constrained by specifically paired inter-chromosomal buttons give rise to pairing-induced domains (PIDs). Our study suggests specific adhesive interactions as a central organizing principle of the diploid genome in Drosophila embryos. SignificanceSomatic homolog pairing distinguishes Drosophila from most eukaryotes; yet how the homolog pairing organizes Drosophila genome has remained elusive due to the lack of explicit model. By analyzing 3D structures reconstructed from haplotype-resolved Hi-C data, we clarify that specific homolog-recognizing buttons should generate pairing-induced domains that simultaneously organize cis and trans-homolog contacts. Our study provides a physical explanation on how a single molecular mechanism can simultaneously coordinate homolog pairing and architecture of chromatin domain in the diploid genome.

biophysics↗

bioRxiv2026

Site-specific integration of transposon via engineered piggyBac transposase

The precise integration of large DNA fragments into the human genome holds significant therapeutic potential. Here, we demonstrate that combining engineered piggyBac (PB) transposase with CRISPR/Cas9 enables targeted integration of PB transposons into specified genomic loci. Our engineered PB transposase (PBase) retains high excision activity while substantially reducing endogenous integration activity. In the developed Cas9-PBase fusion system, PBase excises the transposon to generate linear DNA fragments, while Cas9 introduces site-specific double-strand breaks (DSBs), facilitating insertion of the excised fragment at the target locus. The optimized tool achieves 6.1-7.3 kb transposon integration at multiple genomic sites with 10-15% efficiency, demonstrating 60-80% targeted integration specificity. As a proof of concept, we inserted a 7.1 kb transposon encoding three genes into the {beta}2M locus of human induced pluripotent stem cells (iPSCs), conferring protection against allogeneic natural killer (NK) cell-mediated cytotoxicity in derived iNK cells. These results establish Cas9-PBase as a precise and programmable platform for large DNA sequence insertion with potential clinical applications.

genetics↗

bioRxiv2026

EOLA1, a novel mitochondria-localized protein critical for heart functions via regulating mitochondrial translation

Mitochondria possess their own mRNA translation system, mediated by specialized mitoribosomes. Dysregulation of mitochondrial translation disrupts metabolic homeostasis and is linked to various pathologies, including metabolic syndromes, neurological disorders, and cardiac diseases. Using CRISPR/Cas9 screening, we identified EOLA1 (endothelial-overexpressed lipopolysaccharide-associated factor 1) as a novel mitochondrial matrix protein essential for metabolic homeostasis. Knockout of Eola1 severely affects mitochondrial translation and consequently the oxidative phosphorylation in mammalian cells. Mechanistically, EOLA1 physically interacts with mitochondrial 12S ribosomal RNA (12S mt-rRNA) and the mitochondrial Tu translation elongation factor (TUFM), facilitating efficient translation elongation of mitochondrial-encoded mRNAs. Furthermore, genetic ablation of Eola1 in mice induced severe cardiac dysfunction, demonstrating its indispensable role in maintaining heart function through mitochondrial translation control. Together, our findings establish EOLA1 as a key regulator of mitochondrial translation via its interactions with 12S mt-rRNA and TUFM, highlighting its importance in cellular metabolism and a potential role in cardiac disease pathogenesis.

molecular biology↗

bioRxiv2026

Spatiotemporal Mapping of Tertiary Lymphoid Structure Heterogeneity Shapes Immune Niches and Clinical Outcomes in Intrahepatic Cholangiocarcinoma

Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy with limited therapeutic options. The spatial architecture and functional diversity of tertiary lymphoid structures (TLSs) in iCCA remain unclear. Here, we present a multimodal spatial atlas of TLSs and identified Intra-tumoral TLSs (iTLSs) as independent prognostic markers. Bulk proteomic profiling of 214 discovery and 155 validation cases identified a four-tier TLS-based TME classification system and supported development of a TLS-predictive random forest classifier. Imaging mass cytometry revealed that iTLS tumors harbor structured immune architectures, where M1-like tissue-resident macrophages (RTMs), dendritic cells, and CXCL13 CD4 T cells co-localize to form antigen-presenting neighborhoods (apc-CNs) spatially coupled to TLS core regions (TLScore-CNs). Single-cell spatial transcriptomics further resolved 61 TLSs into 14 spatial niches and defined a pseudo-temporal maturation continuum: aggregated, activated, and post-activated. Intra-niche communication, primarily mediated by ifnCAFs, iCAFs, and CXCL12 macrophages, evolved dynamically with maturation. Single-nucleus RNA-sequencing combined with Tangram-based spatial mapping revealed CXCL12 macrophages and iCAFs forming a peripheral band in aggregated TLSs, while ifnCAFs infiltrated TLS interiors during activation. These findings define TLS heterogeneity and provide insights for stroma-directed immunotherapy. TeaserAn atlas of tertiary lymphoid structures reveals immune-stroma interactions in Intrahepatic cholangiocarcinoma.

immunology↗

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

Genome assembly and population genomic analysis of Aegilops caudata uncover a rich source for disease and insect pest resistance for wheat improvement

Aegilops caudata L. is a rich source of resistance genes to major wheat pathogens and pests, yet its complex genome structure and lack of a reference sequence have hindered genetic analysis, gene discovery, and introgression. Here, we report a high-quality genome sequence assembly of Ae. caudata accession S740-69, integrated with optical mapping to precisely delineate introgressed segments from structurally altered genomic regions in wheat-Ae. caudata translocation lines carrying a novel stem rust resistance gene. Resequencing and phenotyping of 95 diverse accessions, coupled with k-mer-based association mapping, enabled population-level identification of several novel loci for resistance to wheat pests and diseases, such as greenbug and stem rust. Virus-induced gene silencing confirmed Aecau6C01G127270 (SrAect1) as the first functionally characterized stem rust resistance gene from Ae. caudata. This new genomic framework provides a foundation for systematic mining of resistance genes in this species and their efficient introgression into wheat.

genomics↗

bioRxiv2025

Regulation of murine follicle-stimulating hormone β subunit transcription by newly identified enhancers

Activin-class ligands of the transforming growth factor {beta} family induce follicle-stimulating hormone (FSH) production by pituitary gonadotrope cells in mice via the actions of the transcription factors SMAD3, SMAD4, and FOXL2, which bind to cis-elements in the FSH{beta} subunit (Fshb) promoter. An enhancer region for murine Fshb transcription was identified in vitro. However, deletion of the region using CRISPR-Cas9 did not affect FSH synthesis or secretion in mice. Using single-nucleus ATAC-seq of whole murine pituitaries, we identified three additional open chromatin regions upstream of Fshb exclusively in gonadotropes. These regions, as well as the Fshb gene, were fully or partially closed in gonadotropes of FSH-deficient mice with genetically or pharmacologically inactivated activin type II receptors. The initially characterized enhancer region did not significantly alter basal or activin-stimulated murine Fshb promoter-reporter activity in homologous L{beta}T2 cells. In contrast, the other three open chromatin regions enhanced basal and activin A-stimulated Fshb promoter-reporter activity in L{beta}T2 cells, with the two most distal showing the greatest effects. These two regions were open, exhibited enrichment of the enhancer mark H3K27ac, and were bound by SMAD2/3 and FOXL2 in response to activin A in L{beta}T2 cells. The most distal enhancer exhibited strong FOXL2 and weak SMAD4 binding in gel shift assays. SMAD4, but not FOXL2, directly bound the other distal enhancer. Mutation of defined FOXL2 and SMAD4 cis-elements diminished enhancer activity in reporter assays in L{beta}T2 cells. Collectively, the data indicate that there may be as many as four activin-sensitive enhancers upstream of murine Fshb.

molecular biology↗

bioRxiv2025

Carbohydrate adaptation drives liver-brain axis maturation

Mammalian postnatal life requires adaptation to a carbohydrate-rich diet, yet how metabolic programs are coordinated within and across organs is unclear. Using time-resolved transcriptomic and metabolomic analyses from the neonatal period through adulthood, we show that mouse liver rapidly acquires oxidative and detoxification capacity after weaning. This transition enables the brain to establish energy-sufficient, low-toxicity metabolic environment for neuronal development. This maturation process is marked by progressive activation of the hepatic electron transport chain (ETC), with the mitochondrial RNA endoribonuclease LACTB2 acting as a key regulator. LACTB2 prevents the accumulation of mitochondrial RNAs and sustains expression of mtDNA-encoded ETC subunits, thereby preserving mitochondrial competence for oxidative metabolism. LACTB2 is postnatally induced in hepatocytes, and its loss causes defective glucose utilization, systemic metabolic toxicity, and impaired brain metabolism and myelination, leading to prepubertal lethality, particularly in males. Restoring ETC function through liver-targeted expression of yeast NADH dehydrogenase NDI1, inhibiting the integrated stress response or ammonia scavenging improved survival. Our findings identify LACTB2-dependent hepatic mitochondrial maturation as a central mechanism that aligns carbohydrate adaptation with the liver-brain metabolic coordination to support early-life development.

developmental biology↗