Biology subjects

Zhang, D.

Publications and source records attributed to Zhang, D..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

A comprehensive functional landscape of α-tubulin TUBA1A variants illuminates microtubule biology and refines clinical classification

Missense variant interpretation in highly conserved, paralog-rich gene families remains a critical bottleneck for precision medicine. Here, we developed an integrated experimental-computational platform to systematically assess the functional impact of all possible missense mutations in the -tubulin TUBA1A. Combining high-throughput comprehensive mutagenesis, high-content imaging, convolutional neural network- driven phenotyping, and machine learning-guided prediction, we quantified microtubule assembly phenotypes for every coding variant. This approach outperforms conservation-based predictors and enables functional reinterpretation of disease-associated variants. Structural mapping of the TUBA1A mutational landscape reveals distinct domains critical for GTP binding, chaperone-assisted folding or protofilament interaction, illuminating diverse mechanisms of tubulin-related diseases. Integration with ACMG-AMP guidelines demonstrates this mutational landscape improves clinical variant classification in redundant gene families. This framework is broadly applicable to other structurally conserved proteins, linking variant effect prediction to mechanistic insight and clinical translation.

genetics↗

bioRxiv2025

From Correlation to Causation: Cell-Type-Specific Gene Regulatory Networks in Alzheimer's Disease

INTRODUCTIONAlzheimers disease (AD) involves complex regulatory disruptions across multiple brain cell types, yet a comprehensive understanding of the intracellular causal mechanisms remains unclear. METHODSWe presented an integrative analysis framework using single-nucleus transcriptomic with matched subject-level genotype data from 272 human AD in the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP) study, and constructed causality-based, cell-type-specific gene regulatory networks (GRNs). RESULTSOur method identifies regulatory genes from both transcription factors (TFs) and non-TFs, thereby capturing a complete and accurate causal regulatory map across different brain cell types. This work revealed both established and novel regulations, pathways, and cell-type-unique hub genes in AD. Beyond constructing transcriptome-wide GRNs, we quantitatively assessed hub genes and distinguished those with regulatory or responsive roles. DISCUSSIONOur study provides a comprehensive mapping of cell-type-specific causal GRNs in AD, providing a powerful resource for dynamic pathway exploration, hypothesis generation, and functional interpretation.

neuroscience↗

bioRxiv2025

Dual effects of nicotinamide on aging-related arrhythmia: protective at low dose, proarrhythmic at high doses

BackgroundCardiac arrhythmia and dysfunction progressively increase with age, both of which are closely associated with a decline in NAD+. Supplementation with nicotinamide (NAM), a critical NAD+ precursor, has shown protection in experimental models of aging-related cardiac diseases, including atrial fibrillation (AF) and heart failure, especially heart failure with preserved ejection fraction. With the potential rise of NAM in treatment of various cardiometabolic diseases, its dose-dependent cardiac-specific adverse effects and underlying mechanisms warrant investigation. MethodsThe effects of NAM on aging-related arrhythmia and cardiac dysfunction were assessed using ex vivo Langendorff mouse hearts and adult Drosophila heart preparations. Different doses of NAM (10-100 mM) were tested for their impact on the contractility of HL-1 cardiomyocytes, lifespan and cardiac function of Drosophila, as well as arrhythmia susceptibility of ex vivo mouse hearts. Acetylation of sarcoplasmic/endoplasmic reticulum Ca{superscript 2} ATPase 2a (SERCA2a) was measured by immunoprecipitation followed by Western blotting. ResultsAcute perfusion with 10 mM NAM had limited influence on aging-related AF susceptibility in ex vivo mouse hearts. Short-term dietary intervention with 10 mM NAM in late-life protected against aging-induced cardiac arrhythmia and contractile dysfunction exclusively in male Drosophila. In contrast, life-long exposure or NAM concentrations above 20 mM led to dose-dependent adverse cardiac effects, including impaired contractility in HL-1 cardiomyocyte and shortened lifespan in Drosophila, with increased arrhythmia observed in both models. In ex vivo mouse hearts, 100 mM NAM increased SERCA2a acetylation, suggesting inhibition of sirtuin1 and impaired calcium handling, which likely underlies the observed effects of high-dose NAM on arrhythmia and cardiac dysfunction. ConclusionsNAM exhibits a narrow therapeutic window in aging-related cardiac dysfunction and arrhythmia, with its efficacy highly dependent on dose, duration, and biological context. While a moderate dose in late-life may be protective, chronic or excessive intake of NAM can induce arrythmia and impair cardiac function, likely through disruption of the SERCA2a activity. These findings underscore the importance of cautious and context-specific application of NAM in clinical settings.

physiology↗

bioRxiv2025

Soybean aphids exploit abscisic acid signaling to suppress jasmonate defense responses

SummaryO_LISoybean aphids (Aphis glycines) can induce susceptibility on soybean (Glycine max) during colonization. However, the mechanism for this process is not known. Based on previous transcriptome analyses, we hypothesized that aphids block effective jasmonate (JA) defenses by inducing an antagonistic abscisic acid (ABA) signal. C_LIO_LITo test this hypothesis, we used a combination of gene expression analyses, measurements of hormone levels, and aphid bioassays on plants with reduced expression of ABA-related genes. C_LIO_LIAphid feeding attenuated JA responses in soybean plants and facilitated the growth of a chewing herbivore. Aphid-treated plants had increased levels of cis-JA but not biologically active JA-isoleucine, and aphid feeding induced expression of genes associated with JA-Ile catabolism. In parallel, aphid-feeding induced higher levels of ABA. ABA treatment and knockdown lines impaired in ABA biosynthesis (aba2-RNAi) or signaling (scof-1-RNAi), showed that ABA suppressed wound-induced JA responses. Aphid populations were significantly reduced on ABA-deficient plants and aphid-regulated attenuation of JA signaling was abolished in these lines. Remarkably, plants defective in ABA signaling had increased JA signaling in the absence of stressors. C_LIO_LIOur results indicate that, in soybean, the ABA pathway is necessary to control basal levels of JA and soybean aphids exploit this ABA-JA antagonism to suppress plant defenses. C_LI

plant biology↗

bioRxiv2025

Gene flow from the European wild apple and selection shaped the domesticated apple (Malus domestica Borkh.) genome

How selection and demography shape genomes of long-lived crops remains largely unresolved. Using apple (Malus domestica) as a model, we integrate 218 whole genomes (68 cultivated dessert/cider; 150 wild: M. sieversii, M. orientalis, M. sylvestris), RNA-seq, and a flowering-time GWAS to resolve how these forces forged the cultivated apple genome. Despite weak neutral differentiation and widespread admixture, dessert and cider apples form distinct gene pools that derive primarily from M. sieversii-M. orientalis rather than European M. sylvestris. We find no evidence of a strong domestication bottleneck, as expected in perennials. Demography-aware selection scans reveal largely non-overlapping targets: dessert shows more hard sweeps at genes linked to fruit quality, disease resistance, and flowering, whereas cider shows proportionally more soft sweeps and balancing selection; RNA-seq differential expression supports these candidates. Wild-to-crop introgression from M. sylvestris is extensive but heterogeneous by context: some introgressed tracts concentrate in hard-sweep regions and approach fixation (consistent with rapid, targeted uptake), whereas others persist at intermediate frequencies with soft-sweep signatures (consistent with diffuse, recurrent introgression of adaptive alleles). Extending to the phenotype, the lead chromosome 9 flowering-time association lies within an introgressed segment near a transposable element and is separated from sweep peaks, consistent with regulatory/polygenic control. Cultivated apples carry a lower predicted deleterious load than wild relatives. Together, these results provide one of the most comprehensive population genomic portraits of a perennial fruit tree domestication, clarifying how selection and adaptive introgression jointly shaped the cultivated apple genome architecture and yielding actionable targets for breeding and conservation. Significance statementPerennial crops are underexplored compared to annuals, leaving open the question of how selection, gene flow, and demography shape their genomes. Using the apple tree (Malus domestica), we analyzed 218 genomes, along with expression and trait data. Despite weak genome-wide differences, dessert and cider apples form distinct gene pools. Widespread gene flow from the European wild apple supplied adaptive alleles, with contrasting dynamics: in cider, a few introgressed DNA segments rose rapidly; in dessert, many variants shifted gradually. Cultivated apples also carry a lower predicted burden of harmful mutations than wild relatives. Together, these results redefine perennial domestication and pinpoint genomic targets to accelerate breeding and conservation.

genetics↗

bioRxiv2025

Unfolding Suppression: statistical learning drives suppression through dynamic attentional states modulated by threat

How does statistical learning drive distractor suppression? A central debate in current research concerns whether the underlying mechanism operates proactively or reactively. Here, we propose a Temporal Dynamics of Attentional Suppression (TDAS) hypothesis, successfully reconciling these seemingly contradictory views. Across four visual search experiments, participants faced a probabilistic electric shock when a neutral distractor (Experiments 1a, 1b) or a threat-associated distractor (Experiments 2a, 2b) appeared at a threat-related high-probability location. Trial-averaged results showed faster responses and reduced fixations on distractors, but slower responses and fewer fixations on targets at these locations, consistent with learned distractor suppression. SMART analyses for eye-tracking data further revealed that learned suppression emerged from temporal state transitions: from distractor dominance via attentional limbo states to proactive suppression. Critically, spatial probability gates suppression pathways. At low-probability locations, suppression transitions to limbo states, while at high-probability locations, suppression either unfolds through the full three-state sequence or shifts directly from attentional limbo states to proactive suppression. Furthermore, threat signals accelerated these transitions compared to neutral contexts. Overall, these findings contribute to resolving the ongoing debate about the mechanisms of learned distractor suppression. They also offer a new theoretical perspective by establishing spatiotemporally distributed suppression as a core principle of attentional selection, thereby providing a unifying framework for understanding the dynamic nature of attentional control.

neuroscience↗

bioRxiv2025

The two-component nuclease-active KELShedu system confers broad antiphage activity via abortive infection

Bacteriophages and bacteria engage in a continuous evolutionary arms race, driving the development of intricate bacterial defense systems such as CRISPR-Cas, BREX, Gabija, and Shedu. Here, we characterize a two-component KELShedu system in Escherichia coli that confers resistance to phages via abortive infection. The KELShedu system comprises KELA, a dsDNA-binding protein, and KELB, a metal ion-dependent nuclease harboring the DUF4263 domain. In addition, we find that physiological levels of NTP inhibit the DNA cleavage activity of the KELShedu system, suggesting that KELShedus activation depends on reduced intracellular NTP levels during phage invasion. Our research demonstrates that the KELShedu system responds to nucleotide depletion triggered by phage replication, leading to non-specific degradation of cellular DNA and ultimately inducing abortive infection. These insights into the KELShedu system expand the repertoire of bacterial anti-phage mechanisms and lay the groundwork for novel applications in microbial engineering and therapeutic development. TeaserThe KELShedu system exerts anti-phage function by aborting infection in response to physiological changes following phage infection

microbiology↗

bioRxiv2025

Genome assembly and annotations of a Cyprinidae fish, Sinibrama wui

Sinibrama wui is a freshwater fish belonging to the Cyprinidae family, primarily found in the middle and upper Yangtze River of China. However, no reference genome sequence for S. wui has yet to be established. The present study presents a high-quality, chromosome-level genome assembly of S. wui through PacBio Biosciences sequencing and Hi-C technologies. The genome size was 1028.95 Mb, with a contig N50 length of 37.21 Mb and scaffold N50 of 40.74 Mb. We assembled 124 contigs, within which 68 were organized into 24 chromosomes. In total, 25,967 protein-coding genes were predicted, with 99.10% functionally annotated. We further analyzed the evolutionary relationships, gene families expansion, and positive selection of S. wui. Our data showed that S. wui diverged from Megalobrama amblycephala approximately 10.1 million years ago, and the expanded gene families had enriched in the lipid metabolism and nervous system. These datasets offer valuable genomic resources for future investigations studies on the genetic conservation, selective breeding, and evolution of S. wui.

genomics↗

bioRxiv2025

QuantaMind MD enables protein modeling with ab initio accuracy

Accurate biomolecular simulations are essential for understanding chemical processes and advancing applications such as protein engineering and drug design. While quantum mechanical (QM) methods can provide chemical accuracy, their computational cost limits their scalability. Machine learning force fields (MLFFs) offer a promising alternative by achieving similar accuracy with vastly improved efficiency, but their effectiveness is often constrained by limited conformational and chemical diversity in training. We introduce QuantaMind, a robust MLFF workflow designed to extend chemical and conformational coverage, particularly in transition-state regions. QuantaMind enables quantum-accurate molecular dynamics simulations, successfully capturing complex phenomena such as proton diffusion, water dissociation, and acid-base neutralization. We show that QuantaMind can be applied to large biomolecular systems, enabling accurate protein structure optimization and improving the prediction of residue contacts and hydrogen bonds. A pocket-centric simulation strategy further allows QuantaMind to efficiently model protein-ligand interactions with high structural accuracy. These results establish QuantaMind as a versatile and scalable tool for atomistic simulations at ab initio accuracy.

biochemistry↗

bioRxiv2025

MCL1 may not mediate chemoresistance

The anti-apoptotic BCL2 family member MCL1 is overexpressed in many cancers and has been linked to chemoresistance. Unlike other BCL2 family members, MCL1 displays both well-defined mitochondrial anti-apoptotic activities and also emerging nuclear functions. Prior reports suggest that MCL1 enters the nucleus during chemotherapy and promotes chemoresistance by influencing cell cycle progression and DNA repair. These nuclear roles of MCL1, however, remain poorly characterized. Using a newly validated monoclonal antibody across several cell lines and treatments, we find no evidence that MCL1 enhances chemoresistance or preferentially accumulates in the nucleus after drug exposure. Proximity biotinylation identified novel nuclear MCL1 interactors but did not recover previously reported DNA repair or cell cycle partners. Thus, while MCL1 does reach the nucleus and interact with nuclear proteins, our data do not support a role for MCL1 in chemoresistance. Further work is needed to clarify the functional significance of nuclear MCL1. SIGNFIGANCEPrevious studies have implicated MCL1 in promoting chemoresistance via interactions with DNA repair machinery in the nucleus. Using a validated, monoclonal anti-MCL1 antibody, we were unable to replicate these data. We report that MCL1 neither confers chemoresistance, translocates to the nucleus during chemotherapy treatment, nor interacts with DNA repair proteins in live cancer cells.

cell biology↗

bioRxiv2025

A non-catalytic role for RFC in PCNA-mediated processive DNA synthesis

The ring-shaped sliding clamp PCNA enables DNA polymerases to perform processive DNA synthesis during replication and repair. The loading of PCNA onto DNA is catalyzed by the ATPase clamp loader RFC. Using a single-molecule platform to visualize the dynamic interplay between PCNA and RFC on DNA, we unexpectedly discovered that RFC continues to associate with PCNA after loading, contrary to the conventional view. Functionally, this clamp-loader/clamp complex is required for processive DNA synthesis by polymerase {delta} (Pol{delta}), as the PCNA-Pol{delta} assembly is inherently unstable. This architectural role of RFC is dependent on the BRCT domain of Rfc1, and mutation of its DNA-binding residues causes sensitivity to DNA damage in vivo. We further showed the FEN1 flap endonuclease can also stabilize the PCNA-Pol{delta} interaction and mediate robust synthesis. Overall, our work revealed that, beyond their canonical enzymatic functions, PCNA-binding proteins harbor non-catalytic functions essential for DNA replication and genome maintenance.

biophysics↗

bioRxiv2025

Protein Function Prediction via Contig-Aware Multi-Level Feature Integration

Proteins play a central role in biological processes, and accurately predicting their functions is crucial for biomedical research. While computational methods have advanced significantly, most approaches rely solely on sequence or structure, neglecting critical inter-protein relationships, such as the topological arrangement of coding sequences (CDSs) within contigs. To address this gap, we propose CAML, a novel deep learning model that integrates intra-protein features including sequence and predicted structure with inter-protein features capturing functional linkages among CDSs in contigs. Specifically, CAML employs a Graph Isomorphism Network (GIN) to extract structural features from predicted protein contact graphs and ESM-2 for sequence embeddings. Additionally, it leverages kmer frequencies and a Bidirectional Long Short-Term Memory (BiLSTM) network to model functional relationships among colocalized CDSs within contigs, capturing operon-like associations. Extensive experiments demonstrate that CAML outperforms the state-of-the-art methods in accuracy, precision, recall and F1-score, achieving improvements of 11.24%, 12.43%, 13.59%, and 13.30%, respectively over the second-best model. Ablation studies further confirm the critical contribution of CAMLs multi-level biological feature integration in enhancing functional annotation accuracy. Our study demonstrates the importance of integrating structural, sequential, and CDSs topological features for accurate protein function prediction, providing a robust computational framework for genomics research.

bioinformatics↗

bioRxiv2025

Uranium mining fuels evolution in deep groundwater microbiomes

Deep-biosphere microbes have been underpinning global biogeochemical cycles throughout Earth history, yet their evolutionary responses to long-term anthropogenic disturbance remain poorly understood. Neutral-pH in-situ leaching (ISL), the dominant uranium-mining strategy, imposes persistent radiochemical and redox stress offering rare natural experiments across decades for observing subsurface microbial evolution. Here, by exploiting metagenomics and metatranscriptomics in examining microbial responses through various mining stages, we show that neutral U ISL causes substantial changes in microbial communities spanning 2,294 strains accompanied by diversification and selection of active microbial species. These changes occurred during elevated dissolved uranium and radiological activity which correlated with a substantial transcriptional change in energy metabolism, and with an overexpression of specific genes for oxidative-stress defence and DNA-repair pathways. Increased nucleotide diversity in 101 out of 392 species clusters and nonsynonymous/synonymous polymorphism ratios greater than one in 139 species clusters were predominantly observed in metatranscriptomes with elevated radiation, highlighting positive selection of transcriptionally active populations. These findings demonstrate that neutral U ISL drives functional and genetic diversification of subsurface microbiomes, revealing a dynamic and evolutionarily responsive deep biosphere.

genomics↗

bioRxiv2025

Postnatal Abrogation of VEGFR2 Blocks Terminal Cap2 Differentiation by Preventing the Developmental Progression from a Capillary Intermediate Cell State

After birth, the alveolar capillary network expands to increase gas exchange surface area and endothelial-derived signals promote alveolarization. Lung capillaries are comprised of two distinct subsets, one with proliferative potential to facilitate growth and repair (Cap1), and the other serving a specialized role in gas exchange (Cap2). However, the molecular mechanisms directing capillary speciation, developmental plasticity, and fate transitions during development and repair are not well understood. Here, we show that Cap2 are absent in late embryonic life but rapidly appear and expand immediately after birth. We show that Cap1 progenitors first transition to a novel, intermediate cell state (CapINT), characterized by co-expression of Cap1 and Cap2 markers, and heightened proliferation. CapINT are present in both the developing mouse and human lung. Hyperoxia, an experimental model of bronchopulmonary dysplasia (BPD), a chronic lung disease marked by impaired alveolarization, increases CapINT abundance and persistence and expands Cap2 EC. CapINT EC are also increased in human infants dying with active BPD. Using genetic lineage tracing, single cell transcriptomics, ATAC-sequencing and a mouse model that permits inducible deletion of VEGFR2 in CapINT and Cap2 EC, we show that postnatal abrogation of VEGFR2 markedly increases CapINT EC abundance, blocks Cap2 terminal differentiation, impairs alveolarization, and activates alveolar fibroblasts. Finally, we identify ERG as a putative VEGFR2-downstream mechanism that promotes CapINT to Cap2 differentiation. Taken together, our data show that Cap1-Cap2 differentiation is a two-step process that only requires VEGFR2 for the second step. Elucidation of the physiologic and molecular pathways that control the initial transition of Cap1 to CapINT EC has the potential to reveal new therapeutic targets for lung diseases that disrupt the alveolar capillary formation and integrity.

developmental biology↗

bioRxiv2025

CAT-APP: Contamination Analysis and Tempering--An Automated Online Platform for Plasma Proteomics with Data Rescuing Capabilities

Plasma and serum proteome profiling have become central to biomarker discovery for medical research. The advent of high-throughput plasma proteomics pipelines has enabled the generation of massive datasets. However, biomarker discovery is frequently compromised by sample contamination, primarily from erythrocytes, platelets, and coagulation factors. Such contamination can lead to the false identification of contaminants as biomarkers in over 50% of studies or obscure genuine biomarkers due to contamination-induced variability. Currently, no tools are available to salvage such compromised data, and the default approach is often to discard the affected samples. To address this gap, we introduce CAT-APP (Contamination Analysis and Tempering-An Automated Online Platform for Plasma Proteomics). CAT-APP tackles contamination through three key modules: multi-dimensional contamination assessment and adaptive contamination indexing, mathematical model-based contamination tempering, and data recovery evaluation with visualization. We applied CAT-APP to 28 independent plasma proteomics datasets and found that 82% exhibited contamination issues. CAT-APP markedly improved data quality by removing false-positive biomarkers introduced by contamination and restoring true biological signals that were previously obscured in representative datasets. To promote widespread adoption, we provide CAT-APP as an freely accessible, user-friendly, and robust web platform at https://www.bloodecosystem.com/tools/CAT-APP/.

bioinformatics↗

bioRxiv2025

Mitochondrial Genome-Based Phylogeny of Turbellarians and Evidence for Accelerated Mitochondrial Evolution in Symbiotic Species

BackgroundFlatworms are a highly diverse phylum with over 26,500 predominantly parasitic species. A minor portion of this diversity comprise predominantly free-living "turbellarians" Phylogenetic relationships within turbellarian orders remain debated, with recent mitochondrial genome studies also questioning the monophyly of the "Neoophora clade". Some unique mitochondrial gene features have also been observed in this group. Within Turbellaria, the order Rhabdocoela includes significant symbiotic lineages, such as the endosymbiotic Umagillidae, Pterastericolidae, and Graffillidae, and the ectosymbiotic Temnocephalidae, which notably exhibits characteristics akin to a parasitic lifestyle. Given evidence linking parasitic lifestyles to accelerated mitogenomic evolution, we hypothesize that similar patterns: symbiotic turbellarians have mitochondrial genomes that accelerate evolution compared to free-living turbellarians. This study presents the first complete mitochondrial genome of the ectosymbiont Craspedella pedum, provides mitogenomic insights into turbellarian phylogeny, and addressing our hypothesis. ResultsThe mitochondrial genome of Craspedella pedum is a circular DNA molecule of 18,456 base pairs, containing the standard 36 flatworm mitochondrial genes, a duplicated trnT, two cox1 pseudogene fragments, a putative atp8 gene, and several distinctive NCRs. Phylogenetic analyses based on 47 mitochondrial genomes, including the newly sequenced C. pedum and two assembled species from SRA database, using CAT-GTR model and BI and ML algorithms further confirmed that the paraphyly of the Neoophora clade and the basal position of Catenulida and Macrostomida. Different from previous study, Rhabdocoela forms a distinct clade within the turbellarians diverged immediately after Macrostomida before Polycladida and Tricladida. Within Rhabdocoela, C. pedum formed a direct sister clade with Typhloplanidae, suggesting a close phylogenetic relationship between the two. We also identified the paraphyletic of the Planoceridae of Polycladida and the unstable position of Planariidae within Tricladidain. Furthermore, we found a trend that the nad4L-nad4 gene box in turbellarians may have evolved from an overlapping state, to the insertion of a non-coding region (NCR), and subsequently to a separated configuration, correlating with species divergence. The selection pressure analysis showcased selective relaxation from free-living species of Rhabdocoela to symbiotic species of Rhabdocoela. Furthermore, we also detected a relaxation from certain tubellarian lineages to Rhabdocoela. Along with higher GORR and longer Brl, Rhabdocoela and its symbiotic group possesses a more rapidly evolving mitochondrial genome. ConclusionsThe mitochondrial genome of Craspedella pedum displays uncommon characteristics, combined extended branch lengths and elevated GORR, suggesting rapid evolution and extensive rearrangements. Our phylogenetic analysis, integrating additional mitogenome data, further corroborates the paraphyly of the Neoophora clade and offers novel insights into turbellarian phylogeny. For the first time, we confirmed the accelerated evolution of mitochondrial genomes in symbiotic tubellarians compared to free-living ones, as evidenced by a longer average Brl, a higher average GORR, and relaxed selection pressure. Additionally, with the same evidences, we found that Rhabdocoela also exhibited accelerated mitochondrial genome evolution in planarians.

genomics↗

bioRxiv2025

Cross-talk between RNA secondary and three-dimensional structure prediction: a comprehensive study

In recent years, various computational methods have been developed to predict the three-dimensional (3D) structures of RNAs. Due to its hierarchical folding property, RNA secondary (2D) structure is usually used as input for 3D structure prediction to improve accuracy and efficiency. However, the extent to which the accuracy of input 2D structure affects the performance of 3D structure prediction remains to be further investigated. Additionally, whether and how the input base-pairing interactions are modified during the 3D structure modeling process is another question worth exploring. To address these issues, here we comprehensively benchmark five representative 3D structure prediction models on extensive datasets, using 2D structures of varied accuracies as input. Our results indicate that there is a pervasive cross-talk between RNA 2D and 3D structure predictions, where the performance dependence of 3D structure prediction on the accuracy of input 2D structure is closely associated with the 3D models ability to modify the input base-pairing interactions during structure modeling. Furthermore, we also observed that RNA 3D structure prediction performance is more sensitive to the occurrence of false positive base pairs in the input 2D structure than to true positive base pairs, suggesting a worthy direction to further improve the model performance. Author summaryThree-dimensional (3D) structural modeling of RNAs with large sizes and complex topologies remains challenging despite the availability of (predicted) 2D structures as constraints. Exploring the potential cross-talk between 2D and 3D structure predictions is a worthy direction to improve the performance of RNA structure modeling. In this study, we found that all tested popular RNA 3D structure prediction models were able to modify the original base pairing interactions contained in the input 2D structure during the 3D modeling process. Especially, all of these models presented increased F1-score for the optimal combination of RNA 2D and 3D structure prediction models. The results suggest that a worthwhile direction to further improve the performance of RNA 3D structure prediction is to minimize the incidence of incorrectly predicted base pairing interactions during modeling process without compromising or even improving the presence of correct interactions in the input 2D structure.

biophysics↗

bioRxiv2025

The uncertainty partitioning of the terrestrial C cycling over CONUS NEON sites using model-data fusion

Accurate inventories of terrestrial carbon pools and fluxes are crucial for understanding ecosystem processes, tracking climate change impacts, and meeting the monitoring, reporting, and verification (MRV) requirements in international treaties and voluntary carbon markets. In meeting this need, the fusion of process-based modeling, field data, and remote sensing observations has the potential to provide more accurate and precise estimates than each alone. However, as the number of data constraints on a system increases, different sources of information can interact with each other in complex ways across space, time, and processes. In this study, we undertake a value-of-information analysis to assess the contribution of different observations to reducing carbon cycle uncertainties across pools, fluxes, and spatial domains within the PEcAn carbon cycle data assimilation system. We used a novel block-based Tobit Gamma Ensemble Filter to assimilate four synergistic data constraints, MODIS leaf area index, Landtrendr aboveground biomass, SMAP soil moisture, and SoilGrids soil organic C, into a process-based ecosystem model (SIPNET) at 39 National Ecological Observatory Network sites across the contiguous U.S. from 2012 to 2021. Results showed that not only did we greatly reduce uncertainty among the directly constrained pools but many observations were able to share information across variables and space. These indirect constraints helped identify synergies and conflicts among data streams and across space, which provides insights for further constraining carbon inventories. Overall, soil carbon remains the largest source of uncertainty in the overall carbon budget due to both its large size and limited observational constraints.

ecology↗