Biology subjects

Sheng, Y.

Publications and source records attributed to Sheng, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Depth-resolved analysis reveals target-dependent cryo-FIB damage profiles

Cryogenic focused ion beam (cryo-FIB) milling enables cellular cryo-electron tomography but can compromise high-resolution structural information near milled surfaces. Here we establish recombinant human apoferritin (apoF) as a reporter of depth-dependent structural preservation in cellular lamellae. ApoF yielded a 2.05 [A] in situ reconstruction. Apparent FIB damage was most pronounced within the first 15 nm for xenon, 30 nm for gallium, 45 nm for argon and remained detectable at least 75 nm from oxygen-milled surfaces under the workflows tested. Endogenous 70S ribosomes in the same xenon-milled tomograms showed a broader 30-45 nm profile, whereas {beta}-galactosidase showed a similar narrow xenon-associated profile in a different specimen. Xenon-milled lamellae 125-150 nm thick yielded the highest resolution among the thickness groups examined, with lower resolution in the thinner and thickest groups. These findings show structural preservation is constrained by both surface-associated damage and lamella thickness, with the apparent extent of damage varying by molecular reporter. Previous ribosome-based surface-exclusion estimates may therefore be overly conservative for some molecular targets.

molecular biology↗

bioRxiv2026

The HES1-SOD1 Antagonism Shapes Senescence Heterogeneity and Impacts Metastatic Relapse of Circulating Tumor Cells

Circulating tumor cells (CTCs) encounter multiple challenges within the blood microenvironment, including oxidative stress, flow shear forces, and immune surveillance, often leading to anoikis. Recently, a transitional state of CTC senescence has been identified, contributing to metastatic inefficiency. However, the molecular mechanisms linking senescent CTCs to disease relapse remain to be defined. By integrating a genetic model of cortactin knockdown-induced CTC senescence with single-cell multi-omic analyses, we revealed two distinct senescent CTC subpopulations marked by HES1 expression levels. These HES1low and HES1high subpopulations exhibited differential evolutionary trajectory dynamics and unique molecular and metabolic signatures, which were significantly correlated with adverse clinical outcome across several patient cohorts. HES1low senescent CTCs displayed enhanced mitochondrial fitness, oxidative phosphorylation, and ROS-detoxifying capabilities, resulting in more efficient tumor regrowth with a pro-inflammatory and thrombotic phenotype when compared to the HES1high group. Mechanistically, HES1 directly bound to the Sod1 promoter and repressed its expression, leading to redox imbalance and mitochondrial dysfunction that were linked to weakened tumor regrowth capacity. Both senescent CTC subpopulations were broadly resistant to cytotoxic and targeted therapies, yet they showed elevated dependency on anti-apoptosis programs that make them susceptible to dual blockade by SOD1 inhibitor and the anti-senolytic drug ABT737 in vivo. Finally, in a prospective cohort of on-treatment melanoma patients, HES1 senescent CTCs were highly enriched in patients with progressive disease. Thus, the HES1-SOD1 antagonism shapes CTC senescence heterogeneity and contributes to differential tumor relapse, which can be therapeutically explored for eliminating residual metastatic disease.

cancer biology↗

bioRxiv2026

Structural basis for alternative 3' splice site selection in the human spliceosome active center

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/741260v1_ufig1.gif" ALT="Figure 1"> View larger version (97K): org.highwire.dtl.DTLVardef@279388org.highwire.dtl.DTLVardef@46d636org.highwire.dtl.DTLVardef@997672org.highwire.dtl.DTLVardef@12f40ee_HPS_FORMAT_FIGEXP M_FIG C_FIG Key findingsO_LICryo-EM reveals SDE2 as a novel factor stabilizing the spliceosome active center C_LIO_LISDE2 {Delta}N structures visualize a stalled C* state with impaired docking-factor engagement. C_LIO_LISDE2, Prp18, and FAM32A read a cis-code to stabilize weaker proximal 3'-ss. C_LIO_LISDE2 {Delta}N destabilizes 3'-ss docking and rescues BRCA1 and CFTR mis-splicing in vivo. C_LI Accurate alternative splicing requires discrimination between adjacent 3' splice sites (3'-ss) during catalysis and is disrupted by pathogenic AG-gain mutations that create competing 3'-ss. Here, we present cryo-EM structures of human spliceosomes assembled on native-sequence pre-mRNAs, revealing how the catalytic core controls alternative 3'-ss selection. SDE2 is a previously unrecognized active-center component that promotes a docking-competent spliceosome conformation. Machine learning, in vivo transcriptomics, and in vitro biochemistry show how SDE2 cooperates with FAM32A and Prp18 to act as readers of a cis-regulatory code that governs 3'-ss selection during catalysis. These factors promote weaker, proximal site use by counteracting an intrinsic distal bias generated by active-site interactions with the distal-site -4 nucleotide. Structural or genetic perturbation of these exon-ligation factors destabilizes proximal 3'-ss docking and restores canonical splicing in disease-relevant CFTR and BRCA1 AG-gain alleles. Our work establishes the spliceosome active center as a tunable regulatory hub for alternative splicing.

molecular biology↗

bioRxiv2026

Transposon end recognition and pairing by I-F3 CRISPR-associated transposase

To develop gene therapy tools based on CRISPR-associated transposons (CASTs), it is essential to define how transposon ends are recognized and paired during transposition. Tn7-like transposons typically contain asymmetric left- and right-end sequences that flank and define DNA cargo. However, how the transposase recognizes these different sequences and assembles them into a paired end complex for cut-and-paste transposition remains unknown. Here we present the cryo-EM structure of type I-F3 (VchCAST) CAST transposase TnsB in complex with transposon DNA ends and host factor IHF, along with biochemistry, molecular dynamics, and in vivo analyses. Our structure reveals the stoichiometry and architecture of the assembly, as well as the DNA distortions required to accommodate transposon end asymmetry. Molecular dynamics suggests that these distortions are required for the coordinated assembly of the complex. Physical pairing of asymmetric left and right ends results in a novel protein-protein interface that is required for transposition efficiency. Our findings explain how transposases regulate the pairing of transposon end sequences for high-fidelity recognition, reveal a model of transposon end synapsis, and suggest future avenues to engineer DNA cargo for genome-editing applications.

biochemistry↗

bioRxiv2026

A glycoRNA switch for malignancy: SNORA73B activates TIAR-dependent oncogenic signaling in lung adenocarcinoma

Although glycosylated small non-coding RNAs are emerging players in cancer, their functions in lung adenocarcinoma (LUAD) are largely unknown. We identify SNORA73B as a glycosylated small nucleolar RNA (glycol-snoRNA) that carries sialic acid-capped O-glycans in both normal lung epithelial and LUAD cells. SNORA73B is markedly elevated in LUAD, and its plasma levels distinguish early-stage LUAD from healthy controls with an area under the curve (AUC) of 0.7903. Subcellular fractionation reveals predominant nuclear localization. Functional assays demonstrate that SNORA73B depletion curbs LUAD cell proliferation, migration, and invasion, whereas its overexpression fosters these malignant phenotypes and accelerates tumor growth. Mechanistically, SNORA73B directly binds the T-cell-restricted intracellular antigen-related protein (TIAR), thereby enhancing TIAR protein abundance without affecting its mRNA levels. TIAR then recognizes the 3-untranslated region (3-UTR) of MYC mRNA to upregulate c-Myc, which subsequently augments AKT phosphorylation. Importantly, c-Myc knockdown largely rescues the oncogenic phenotypes and tumorigenesis induced by SNORA73B overexpression. Collectively, our data unveil a glycoRNA-dependent oncogenic axis SNORA73B-TIAR-c-Myc-AKT that drives LUAD progression. These findings position SNORA73B as a promising early diagnostic biomarker and a candidate therapeutic target in LUAD.

Cancer Biology↗

bioRxiv2026

Tex11 Mutant Mouse Models of Human Azoospermia

Non-obstructive azoospermia (NOA) is the absence of sperm in the ejaculate due to spermatogenic failure. Fifty percent of NOA cases are unexplained but may arise from unidentified genetic mutations. Variants in TEX11 have been identified in men with NOA; and Tex11 knockout in mice causes NOA. Here we attempt to validate three TEX11 variants discovered in NOA patients by knocking them into the orthologous region of the mouse genome using CRISPR/Cas9 gene editing. Compared to wild type (144.2 {+/-} 9.87 mg; 1.7 {+/-} 0.5 million sperm/cauda epididymis 4.8 {+/-} 1.3 pups/breeding), Tex11D mice (frameshift mutation) had reduced testis weight (28.33 {+/-} 1.16 mg); no sperm in the epididymis; and were infertile with a maturation arrest testicular phenotype. We did not observe any spermatogenesis or fertility defects Tex11A mice (missense mutation). Tex11L mice had reduced testis weight (87.5 {+/-} 14.79 mg) and epididymal sperm counts (0.33{+/-}0.13 million/cauda epididymis) but an incompletely penetrant infertility phenotype (5.4 {+/-} 1.13 pups/breeding) with one third of mice being infertile. Infertile Tex11L mice also had a distinct epididymal phenotype with reduced sperm density in the caput and no sperm in the cauda, which was filled with amorphous material.

genetics↗

bioRxiv2025

A stress-dependent TRIM28-ALKBH2 feedback loop modulates chemotherapy response

Chemoresistance to DNA-damaging agents, including platinum and alkylating compounds, limits treatment efficacy in non-small cell lung cancer (NSCLC) and is frequently associated with elevated DNA repair activity. Here, we identify a stress-responsive feedback loop between the E3 ligase TRIM28 and the demethylase ALKBH2. TRIM28 binds ALKBH2 and promotes its K48-linked polyubiquitination and proteasomal degradation, whereas ALKBH2 enhances TRIM28 transcription and protein levels, forming a feedback loop. Notably, alkylation stress induces a biphasic response: acute MMS exposure enhances TRIM28-ALKBH2 association and accelerates ALKBH2 degradation, whereas prolonged exposure promotes TRIM28 degradation, leading to ALKBH2 stabilization and transcriptional upregulation. Clinically, ALKBH2 is frequently elevated in lung adenocarcinoma and is associated with worse survival, whereas TRIM28 exhibits prognostic value specifically in chemotherapy-treated patients. Functionally, MMS-cisplatin co-treatment increased DNA damage and reduced clonogenic survival by counteracting ALKBH2-dependent alkylation tolerance, linking the TRIM28-ALKBH2 loop to chemoresistance in NSCLC.

biochemistry↗

bioRxiv2025

A hidden protamine PTM code in sperm generates heterogeneous chromatin states and finetunes reproductive fitness

Traditionally, the sperm genome is thought to be packaged by protamines into a uniformly compact and inert chromatin structure. Here, we challenge this long-standing view by demonstrating that protamine post-translational modifications (PTMs) present on distinct protamine molecules create discrete protamine-DNA chromatin states, ranging from weak to tightly associated chromatin configurations. Loss of these modifications alters protamine-DNA interactions in vitro and in vivo, compromising sperm chromatin integrity and impairing fertility. Therefore, these findings demonstrate that protamines do not merely serve as inert packaging proteins; rather protamine PTMs establish functional heterogeneity within sperm chromatin, creating compartment-like domains analogous to those in somatic cells. Thus, PTMs allow protamines to do more than simply compact the paternal genome--they likely encode a molecular blueprint that orchestrates the timely unpacking and reorganization of the paternal genome after fertilization.

molecular biology↗

bioRxiv2025

R-loops orchestrate the maternal-to-zygotic transition by harnessing RNA polymerase II pause release

R-loops, ubiquitous three-stranded nucleic acid structures abundant in the mammalian genome, play pivotal roles in diverse biological processes1-3. However, the dynamics and functions of R-loops during mammalian preimplantation embryonic development remain poorly understood. Here we optimized an innovative, ultra-sensitive RIAN-seq method capable of mapping genome-wide R-loop landscape using ultra-low cell numbers to investigate R-loop dynamics in mouse gametes and early embryos. Our findings reveal the widespread presence of AT-rich R-loops during early mouse embryonic development and highlight their critical roles in orchestrating transcription machinery during zygotic genome activation (ZGA). We demonstrate that the stability and inheritance of R-loops through developmental stages are governed by their sequence composition, with GC-rich R-loops exhibiting greater stability. Notably, R-loops, particularly AT-rich R-loops, inhibit DDX21 helicase activity on the 7SK/HEXIM1 snRNP complex, thereby reducing CDK9 release. This, in turn, modulates the phosphorylation of Ser2 at C-terminal domain (CTD) of RNA polymerase II (RNAPIIS2p) at the promoters of major ZGA and maternal genes. Furthermore, R-loops promote RNAPII accumulation at major ZGA gene promoters, preventing RNAPII from premature release and ensuring timely activation of major ZGA genes. Conversely, R-loops enhance the retention of stalled RNAPII at maternal gene promoters, effectively repressing their expression and facilitating the maternal-to-zygotic transition. In summary, our study unveils a key role for R-loops in regulating the maternal-to-zygotic transcription transition and early embryonic development in mice.

developmental biology↗

bioRxiv2025

Looking Across Protein Domains to Identify Driver Mutations in Cancer

Cancer can develop through the accumulation of somatic mutations that drive uncontrolled cell proliferation. A central objective in cancer research is to identify mutations that provide a selective growth advantage to tumor cells, so called driver mutations. Many computational methods infer driver missense mutations in proteins by assessing their recurrence. However, such approach suffers from the limited capacity to detect those driver mutations that occur infrequently across tumor samples. One strategy to overcome this limitation is to aggregate mutations from proteins sharing the same protein domain. Here we constructed a benchmark of cancer driver and passenger mutations, based on the known experimental and clinical studies, and systematically evaluated the applicability of methods that aggregate mutations across different mutation types and protein domains. We found that accounting for evidence mutations from different types of amino acid substitutions occurring in the same protein position enhances the classification performance. Furthermore, accounting for evidence mutations from paralogous proteins in the domain family increased the precision but compromised the overall classification accuracy. In addition, the performance of domain-based approaches was shown to crucially depend on the similarity between the target and evidence proteins.

cancer biology↗

bioRxiv2025

NTM-DB: A Comprehensive Non-Tuberculosis Mycobacteria Genomic Database

Non-tuberculous mycobacteria (NTM) are a major group of environmental bacteria, with approximately one-third of them causing serious human infections, particularly respiratory diseases. The global rise in the prevalence and severity of NTM infections has posed a major public health challenge. While high-throughput sequencing has generated vast genomic data on NTM, there remains a lack of comprehensive resources for cross-species genomic analysis. To address these limitations, we have developed a specialized database called NTM-DB (https://ngdc.cncb.ac.cn/ntmdb) tailored for NTM researchers and clinicians. NTM-DB offers the most comprehensive collection of NTM genomic and bioinformatic resources, including 16,469 genome assemblies (13,134 newly assembled genomes), 189 type/standard strain genomes representing 177 species and 12 subspecies, 705 MLST types, 33,240 resistance genes, and 74,315 virulence genes. A user-friendly interactive website has been constructed to enable efficient browsing, MLST profiling, searching, online analysis, and downloading of the aforementioned data. Notably, with online analysis tools, users can perform customized genotyping, cross-species phylogeny, pan-genome, and virulence and drug resistance gene annotation analyses using our data and/or their uploaded data. Overall, with its comprehensive data, intuitive interface, and powerful analysis tools, NTM-DB serves as an important resource and reference for NTM researchers and clinicians, improving diagnosis and treatment for various NTM-related diseases, and supporting both scientific discovery and clinical practice.

microbiology↗

bioRxiv2025

GAME: Genomic API for Model Evaluation

The rapid expansion of genomics datasets and the application of machine learning has produced sequence-to-activity genomics models with ever-expanding capabilities. However, benchmarking these models on practical applications has been challenging because individual projects evaluate their models in ad hoc ways, and there is substantial heterogeneity of both model architectures and benchmarking tasks. To address this challenge, we have created GAME, a system for large-scale, community-led standardized model benchmarking on user-defined evaluation tasks. We borrow concepts from the Application Programming Interface (API) paradigm to allow for seamless communication between pre-trained models and benchmarking tasks, ensuring consistent evaluation protocols. Because all models and benchmarks are inherently compatible in this framework, the continual addition of new models and new benchmarks is easy. We also developed a Matcher module powered by a large language model (LLM) to automate ambiguous task alignment between benchmarks and models. Containerization of these modules enhances reproducibility and facilitates the deployment of models and benchmarks across computing platforms. By focusing on predicting underlying biochemical phenomena (e.g. gene expression, open chromatin, DNA binding), we ensure that tasks remain technology-independent. We provide examples of benchmarks and models implementing this framework, and anticipate that the community will contribute their own, leading to an ever-expanding and evolving set of models and evaluation tasks. This resource will accelerate genomics research by illuminating the best models for a given task, motivating novel functional genomic benchmarks, and providing a more nuanced understanding of model abilities.

bioinformatics↗

bioRxiv2025

Modeling Post-Gastrula Development via Bidirectional Pluripotent Stem Cells

The absence of stem cells capable of efficiently generating both trophoblast and epiblast lineages has hindered precise recapitulation of embryonic development. Through high-content chemical screening, we established an AL medium to generate mouse and human bidirectional pluripotent stem cells (BPSCs) characterized by concurrent OCT4/CDX2 expression. Mouse BPSCs demonstrated high plastic differentiation into trophoblast, epiblast and primitive endoderm lineages in vitro within 48 hours without exogenous induction factors and efficiently contributed to the embryo and extraembryonic tissues in vivo. Mechanistically, hyperactivation of the Wnt signaling pathway breaks the early lineage differentiation barrier by initiating a Lef1-dependent bypass. Remarkably, BPSCs can efficiently generated E8.5 embryoids that completed gastrulation and displayed advanced features such as brain development, a closed neural tube, a beating heart, somite formation, and primordial germ cells. These findings highlight BPSCs as a powerful tool for investigating early lineage specification and post-gastrulation embryonic development, with potential applications across multiple species.

developmental biology↗

bioRxiv2025

OLIVE Provides Rapid Visualization and Analysis of Chromatin Tracing Experiments

Optical chromatin tracing experiments directly capture the three-dimensional folding of thousands of individual alleles, highlighting the need for a tool that enables fast, interactive, and analytical browsing of such data. Here, we introduce Optical Looping Interactive Viewing Engine (OLIVE), a web-based tool designed for high-throughput chromatin tracing data that functions similarly to genome browsers. OLIVE allows users, regardless of computational expertise, to input their own data for automated reconstruction of chromatin fibers at individual alleles or to browse annotated publicly available datasets. Using OLIVEs functionalities, users can interact with three-dimensional presentation of traced alleles and query them based on spatial features, including pairwise distances and perimeters between their segments. Finally, OLIVE calculates and presents several polymer physics metrics of each allele, providing quantitative summaries for hypothesis-driven studies. OLIVE is an open-source project accessible at https://faryabilab.github.io/chromatin-traces-vis/.

bioinformatics↗

bioRxiv2025

PCAGP, a parallel convolutional attention network-based method for crop genomic prediction

Genomic selection (GS) has emerged as a transformative breeding paradigm, leveraging genome-wide marker data to predict phenotypic outcomes and accelerate crop improvement cycles. Traditional statistical models face fundamental limitations in modeling the higher-order, non-linear genotype-phenotype relationships inherent in complex agronomic traits. Deep learning architectures have recently shown remarkable predictive performance in GS applications. Current deep learning approaches in GS predominantly employ a serial structure convolution kernel, this may lead to gradient vanishing and computational efficiency challenges. In this study, we propose a method based on a parallel convolutional attention network for crop genomic prediction (PCAGP), a novel deep learning framework for crop genomic prediction. The architecture uses a convolution kernel to transmit information through a parallel structure, combined with a coordinate attention mechanism that effectively integrates inter-channel relationships and spatial genomic information. This approach significantly improves the accuracy of phenotypic prediction. We compared PCAGP with six widely used GS methods on four benchmark datasets, including statistical method (GBLUP), machine learning approaches (SVR, RF), and deep learning models (DeepGS, DNNGP, and SoyDNGP). The experimental results demonstrate that PCAGP outperforms all baseline methods, and the average prediction accuracy is improved (0.4%-53.1%).

bioinformatics↗

bioRxiv2025

FASN Inactivation-induced Progranulin (GRN) Expression Promotes Lysosome-dependent Cell Death to Suppress Leukemogenesis

Cancer cells rely on lipogenesis in addition to exogenous lipid uptake, and fatty acid synthase (FASN) is aberrantly overexpressed in myeloid leukemia. However, the precise role of FASN in leukemogenesis in vivo remains elusive. Here, we demonstrated that FASN is essential for leukemogenesis. Ablation of FASN impeded leukemic cell growth, survival, clonogenicity in vitro, and the leukemic burden in vivo. Conditional knockout of FASN barely affected hematopoiesis but significantly attenuated the leukemic progression of MLL-AF9 transplants. By screening a library of platensimycin derivatives, we identified compound MS-C19 as a potent FASN inhibitor. Pharmacological targeting of FASN by MS-C19 suppressed leukemic cell growth and clonogenicity in clinical AML blasts. Mechanistically, both MS-C19 treatment and FASN deficiency triggered the activation of lysosomal and inflammatory gene expression. Loss of FASN led to lysosomal membrane permeabilization and subsequent lysosome-associated cell death, but not lysosome biogenesis. We further identified that GRN, a lysosomal and neuroinflammatory gene, was potently transcribed by TFEB upon FASN loss. Depletion of GRN significantly reversed the inhibitory effects caused by FASN knockdown. Our work demonstrates that FASN is a therapeutic target for myeloid leukemia, and inactivation of FASN by the lead compound MS-C19 provides an alternative approach for leukemic intervention. Key PointsO_LIGenetic ablation of FASN induces apoptosis, impedes leukemia cell growth, and improves the survival of leukemic xenografts. C_LIO_LITargeting FASN by the compound MS-C19, a derivative of the natural microbe antibiotic platensimycin, reduces the cell survival of leukemic cell lines, the clinical leukemic blasts, and MLL-AF9 transformed murine leukemic cells. C_LIO_LIFASN inhibition induces lysosome-dependent cell death that relies on Progranulin (GRN) expression. C_LI

cancer biology↗

bioRxiv2025

Aicardi-Goutieres Syndrome Associated ADAR G1007R mutation dominantly induces neuroinflammation in mouse brain

The ADARG1007Rmutation is one of the most frequent mutations found in type six Aicardi-Goutieres Syndrome (AGS), a severe inflammatory encephalopathy in pediatric patients. We report here a mouse model bearing an human equivalent ADARG1007R mutation, and the heterozygous mice recapitulated some pathologic features of ADARG1007R AGS patients, including early-onset brain inflammation in heterozygous individuals and interferon-stimulated gene (ISG) expression within deep brain areas. Furthermore, we demonstrated that brain inflammation could be reversed by deletion of the cellular RNA receptor MDA5, which blocks the cellular RNA sensing signaling pathway. This model provides a unique tool for studying the molecular mechanisms underlying the heterozygous ADARWT/G1007R mutation in AGS brain pathogenesis. It may also be a valuable platform for developing personalized therapies for patients with this specific mutation.

neuroscience↗

bioRxiv2025

Investigating Data Size, Sequence Diversity, and Model Complexity in MPRA-based Sequence-to-Function Prediction

We created the MPRA Dataset Collection (MDC), a curated resource of MPRA data from 12 studies comprising over 150 million labeled DNA subsequences. These datasets include both random and natural genomic sequences paired with diverse functional outputs such as gene expression and splicing efficiency. Using this collection, we build sequence-to-function (S2F) predictive models of regulatory elements and analyze these models to uncover insights into the relationship between training data requirements, experimental design, and model generalizability. By offering a high-quality, machine learning-ready repository, MDC accelerates the development of robust computational tools for deciphering the mechanisms of gene regulation.

bioinformatics↗