Biology subjects

Jiang, Z.

Publications and source records attributed to Jiang, Z..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Fully functional AAV viral vectors with highly altered structural cores and subunit interfaces using ProteinMPNN

Adeno-associated viruses (AAV) have emerged as a viable vector for gene therapy, with several clinical approvals and a growing pipeline in clinical trials. These vectors have several challenges that need to be addressed to widen their use, including improving tropisms, reducing manufacturing costs, increasing storage stability, minimising their immunogenicity, or evasion of existing AAV immunity in which neutralising antibodies lead to loss of potency. Vector engineering, particularly capsid protein engineering, offers a potential route to generating new capsids that can selectively target desired cell types or evade pre-existing immunity, while also ensuring that they are manufacturable at higher titres, more stable, and have reduced immunogenicity. Extensive protein redesign is emerging as a viable option, through generative AI approaches, for engineering many types of protein. Here we explored the potential of ProteinMPNN, to extensively redesign AAV2 and yet still form stable and functional capsids. We targeted 52% of AAV2 residues for redesign by ProteinMPNN, such that only the buried protein core and subunit interfaces would be varied, leaving the capsid external and internal surface features unchanged. The aim was to significantly modify the structure responsible for assembly and capsid integrity, while maximising the probability of maintaining the wild-type DNA packaging and transduction capabilities. The final designs were between 14% and 30% mutated overall, and yet were capable of forming functional and intact capsids, with the transduction efficiency of wild type retained for some variants. The designs generally led to lower titres from cell culture, yet some designs had either improved capsid packaging efficiency or transduction efficiency. In particular, our "Pentamer" design had the best transduction efficiency, while our "Chimera" design had a packaging efficiency that was 2.5x higher than for the WT AAV2. These results demonstrate the potential to use generative AI tools in vector capsid redesign for novel core assembly features, and now pave the way for expanding this approach into selectively re-engineering their surface properties to influence tropism, immunogenicity and transduction efficiency.

bioengineering↗

bioRxiv2025

SVPG: A pangenome-based structural variant detection approach and rapid augmentation of pangenome graphs with new samples

Breakthrough advances in long-read sequencing technologies have opened unprecedented opportunities to study genetic variations through comprehensive pangenome analysis. However, the availability of structural variant (SV) calling tools that can effectively leverage pangenome information is limited. In addition, efficient construction of pangenome graphs becomes increasingly challenging with acquisition of larger number of samples. In this study, we present SVPG, an approach that leverages haplotype-resolved pangenome reference for accurate SV detection and rapid pangenome graph augmentation from long-read sequencing data. Compared to state-of-the-art SV callers, SVPG maintained superior overall performance across different sequencing technologies and coverages. SVPG also achieved notable improvements in calling rare and individual-specific SVs on both simulated and real somatic datasets. Furthermore, in a benchmark involving 20 samples, SVPG accelerated pangenome graph augmentation by nearly 10-fold compared to traditional augmentation strategies. We believe that this novel SVPG method, has the potential to revolutionize SV detection and serve as an effective and essential tool, offering new possibilities for advancing pangenomic research.

bioinformatics↗

bioRxiv2025

DrugLM: A Unified Framework to Enhance Drug-Target Interaction Predictions by Incorporating Textual Embeddings via Language Models

MotivationAccurate prediction of drug-target interactions (DTIs) is central to computational drug discovery, offering the potential to reduce experimental costs and accelerate development timelines. While existing deep learning approaches such as Graph Neural Networks and Transformers have shown promise, they often overlook the rich semantic information embedded in textual descriptions of drugs and targets. These descriptions encode critical biomedical knowledge, including mechanisms of action, biological pathways involved, and therapeutic effects of drugs, which can enhance DTI prediction performance. ResultsWe introduce DrugLM, a unified framework that integrates embeddings derived from large language models (LLMs) into DTI-specific model architectures. DrugLM leverages textual descriptions of drugs and targets to generate semantic embeddings using a range of pretrained LLMs. These embeddings can be seamlessly incorporated into existing DTI models. We systematically evaluate multiple LLMs on benchmark DTI datasets and demonstrate strong performance even without fine-tuning. Moreover, supervised parameter-efficient fine-tuning of the LLMs further improves embedding quality, leading to enhanced prediction accuracy. Notably, a simple multilayer perceptron (MLP) using only LLM-derived embeddings surpasses several established DTI methods, underscoring the power of semantic features. Our findings highlight the practical value of integrating LLMs into DTI pipelines and offer a straightforward recipe for improved drug discovery: LLM embeddings of drugs and targets are both effective and easy to use. AvailabilityOur code and dataset are available at https://github.com/ShPhoebus/DrugLM

bioinformatics↗

bioRxiv2025

Single-nucleotide Resolution Epitranscriptomic Profiling Uncovers Dynamic m6A Regulation in Bovine Preimplantation Development

RNA N6-methyladenosine (m6A) plays a crucial role in regulating gene expression during early embryonic development. However, the m6A dynamics at single-nucleotide resolution in preimplantation development remain uncharacterized, and the functional significance of site specific m6A modifications in key developmental regulators is largely unknown. Here, using SAC-seq, a single-base resolution, antibody-independent m6A profiling method, we generate the first comprehensive m6A landscape in bovine oocytes and preimplantation embryos. We identify a previously uncharacterized m6A site in RPL12 transcript that is essential for embryonic development. Loss of m6A at this site leads to reduced protein synthesis, disrupted expression of translation-related genes, and impaired zygotic genome activation and blastocyst formation. Notably, supplementation with wild-type RPL12 mRNA fails to rescue the developmental arrest, indicating that m6A regulation extends beyond transcript abundance. Our findings provide a valuable resource of m6A at single-nucleotide resolution in mammalian embryogenesis and uncover a critical mechanism by which precise, site-specific m6A regulates translation and developmental competence in early embryos.

developmental biology↗

bioRxiv2025

The pathogenic E139D mutation stabilizes a non-canonical active state of the multi-domain phosphatase SHP2

Dysregulation of the phosphatase SHP2 is implicated in various diseases, including congenital disorders and cancer. SHP2 contains two phosphotyrosine-recognition domains (N-SH2 and C-SH2) and a protein tyrosine phosphatase (PTP) domain. The N-SH2 domain is critical for SHP2 regulation. In the auto-inhibited state, it binds to the PTP domain and blocks the active site, but phosphoprotein engagement destabilizes the N-SH2/PTP domain interaction, thereby exposing the active site. Many disease mutations in SHP2 are at the N-SH2/PTP interface, and they hyperactivate SHP2 by disrupting auto-inhibitory interactions. The activating E139D mutation represents an exception to this mechanism, as it resides in the C-SH2 domain and makes minimal interactions in auto-inhibited and active state crystal structures. In this study, using AlphaFold2 modeling and molecular dynamics simulations, we identify an alternative active conformation of SHP2, in which Glu139 interacts with Arg4 and Arg5 on the N-SH2 domain to stabilize a novel N-SH2/C-SH2 interface. Using double mutant cycles, we show that this active state is further stabilized by the E139D mutation. Finally, we demonstrate that the E139D mutation enforces an active conformation with distinct phosphoprotein binding preferences from canonical hyperactive mutants. Thus, our study reveals a novel mechanism for SHP2 dysregulation.

biochemistry↗

bioRxiv2025

Multiplexed single-cell transcriptomics reveals diverse phenotypic outcomes for pathogenic SHP2 variants

The protein tyrosine phosphatase SHP2, encoded by PTPN11, is an important regulator of Ras/MAPK signaling that acts downstream of receptor tyrosine kinases and other transmembrane receptors. Germline PTPN11 mutations cause developmental disorders such as Noonan Syndrome, whereas somatic mutations drive various cancers. While many pathogenic mutations enhance SHP2 catalytic activity, others are inactivating or affect protein interactions, confounding our understanding of SHP2-driven disease. Here, we combine single-cell transcriptional profiling of cells expressing clinically diverse SHP2 variants with protein biochemistry, structural analysis, and cell biology to explain how pathogenic mutations dysregulate signaling. Our analyses reveal that loss of catalytic activity does not phenocopy SHP2 knock-out at the gene expression level, that some mechanistically distinct mutations have convergent phenotypic effects, and that different mutations at the same hotspot residue can yield divergent cell states. These findings provide a framework for understanding the connection between SHP2 structural perturbations, cellular outcomes, and human diseases.

molecular biology↗

bioRxiv2025

The bifunctional dynamin-like GTPase switch DynAB modulates both vegetative and sporulation cell division in Streptomyces.

As part of their complex developmental lifecycle, the multicellular filamentous bacteria Streptomyces have evolved two modes of cell division distinct from binary fission. In vegetative cell division, irregularly spaced cross-walls form within vegetative hyphae, whereas in sporogenic hyphae, regularly spaced sporulation septa form synchronously, leading to spore formation. However, the mechanisms controlling these processes largely remain unknown. The bacterial dynamin-like protein pair DynAB was previously reported to be a component of sporulation septa. Here, we reveal that DynA and DynB have critical roles in both cell division modes, regulating the formation of sporulation septa and cross-walls, with the Streptomyces cell division protein SsgB modulating their activities. dynAB deletion and overexpression, respectively, increased and abrogated cross-wall formation in vegetative hyphae, and Streptomyces DynAB also inhibited cell division in Escherichia coli, resulting in formation of unicellular filamentous cells and suggesting an ancient and conserved function for these proteins. Notably, SsgB could relieve the inhibition of cell division by DynAB in both Streptomyces and E. coli. In contrast to DynAB, SsgB overexpression generated spore-like compartments in vegetative hyphae, a phenomenon that required disruption of the DynAB complex. Fluorescent tags revealed dynamic localization of DynAB during development, and further analyses indicated that, in sporogenic hyphae, the timing of DynAB expression, their GTP-binding activity, and interaction with SsgB were associated with the synchronous initiation of sporulation septation. Our findings establish DynAB as an integrator of spatiotemporal cues in bacterial multicellularity and provide insights into the evolution of complex cell cycle regulation in prokaryotes. SignificanceThe evolution of multicellularity in bacteria involved the development of complex mechanisms to spatially and temporally coordinate cell division. Streptomyces, renowned for their production of bioactive secondary metabolites, exemplify bacterial complexity. This study reveals how Streptomyces employ the dynamin-like proteins DynAB as a bifunctional molecular switch, enabling transition between vegetative and reproductive growth through integrated interactions with developmentally regulated proteins and the availability of the energy supplier GTP. Importantly, DynAB could repress cell division in both Streptomyces and Escherichia coli, suggesting an evolutionary origin of these proteins prior to bacterial multicellularity. Our work reveals the dual function and switch mechanism of DynAB in Streptomyces, providing insights into the emergence of dynamic cell cycle control in prokaryotes.

microbiology↗

bioRxiv2025

Transient Dietary Changes Modulate Inflammatory Disease Trajectory in the Lean State

Obesity potently alters immune responses across various inflammatory contexts1-7. However, it is unclear whether a transient high-fat diet (HFD) can affect immune function despite minimal effects on body weight. Here, we demonstrate that a short-term HFD regimen significantly exacerbates disease severity in a model of experimental psoriasis, comparable to what is observed in obese mice on long-term HFD. We find that a critical 4-day window of HFD coinciding with disease onset is sufficient to overactivate the immune response, leading to worsened disease outcomes. Mechanistically, we identify the CD4+ T cell compartment as an essential mediator of HFD-induced disease severity. Within the compartment, we functionally validate that disease exacerbation is driven by increased differentiation of a pathogenic population of T helper 17 (TH17) cells8 expressing IL1R1 (interleukin-1 receptor, type I)9, which is triggered by localized activation of the NLRP3 (NOD-, LRR-, and pyrin domain-containing protein 3) inflammasome10. This brief window of HFD at disease onset leads to immune-dependent sensitization, as disease severity is increased upon a subsequent flare, despite complete recovery and under a low-fat diet (LFD) regimen. Our data indicate that transient dietary changes during the initial stages of an inflammatory event can rewire the immune milieu, profoundly influencing disease progression and inflammatory memory11. This phenomenon may have broad implications for conditions where obesity, and not diet itself, is considered the primary risk factor.

immunology↗

bioRxiv2025

CNVPipe: An enhanced pipeline for accurate analysis of copy number variation from whole-genome sequencing

Copy number variations (CNVs) are critical contributors to the genetic architecture of complex diseases, yet many existing pipelines for whole-genome sequencing (WGS) data exhibit persistently high false discovery rates (FDR). Here, we introduce CNVPipe, an enhanced workflow that integrates widely used CNV-calling tools with a novel machine-learning framework to achieve lower FDR and higher sensitivity. CNVPipe also provides a specialised module for single-cell CNV analysis, featuring a new model that accurately estimates the ploidy of single cells to get integer copy number profile. Benchmark evaluations demonstrate that CNVPipe outperforms current pipelines in various genomic contexts. In addition to detecting recurrent CNVs in paediatric developmental disorders, CNVPipe enables large-scale functional genomics applications involving stem cell technologies. Moreover, its application to sparse single-cell DNA sequencing data provides a new aspect of research in cancer evolution. Collectively, these findings underscore the versatility and reliability of CNVPipe as a comprehensive solution for CNV detection in WGS-based research.

systems biology↗

bioRxiv2025

A Universal 6iL/E4 Culture System for Deriving and Maintaining Embryonic Stem Cells Across Mammalian Species

The derivation of authentic embryonic stem cells (ESCs) from diverse mammalian species offers valuable opportunities for advancing regenerative medicine, studying developmental biology, and enabling species conservation. Here, we report the development of a robust, serum-free culture system, termed 6iL/E4 that enables the derivation and long-term self-renewal of ESCs from multiple mammalian species, including mouse, rat, bovine, rabbit, and human. Using systematic signaling pathway analysis, we identified key regulators--including GSK3, STAT3, PDGFR, BRAF, and LATS--critical for ESC maintenance across species. Additionally, inducible expression of KLF2 and NANOG enhances the naive pluripotency and chimeric potential of bovine ESCs. The E4 medium also supports stable ESC growth while minimizing lineage bias. These findings reveal conserved principles underlying ESC self-renewal across divergent mammalian species and provide a universal platform for cross-species stem cell research, disease modeling, and biotechnology applications. In BriefWang et al. developed 6iL/E4, a serum-free system sustaining ESCs from mouse, rat, bovine, rabbit, and human. These findings reveal conserved fundamental mechanisms governing ESC self-renewal across diverse mammalian species. HighlightsO_LIDeveloped 6iL/E4 system for ESC derivation across five mammalian species. C_LIO_LIPDGFR signaling inhibition as critical for ESC derivation across species. C_LIO_LIE4 medium improves ESC maintenance and avoids neural bias of traditional N2B27. C_LIO_LIInducible KLF2/NANOG enhances naive pluripotency and chimera formation in bovine. C_LI

cell biology↗

bioRxiv2025

Enhancing Neural Synchrony with Endogenous-like 1/f Noise Stimulation

Aperiodic components of neural activity, characterized by endogenous 1/f noise dynamics, are hypothesized to support the emergence of large-scale cortical order and cognitive flexibility. Here, we combine computational modeling and human brain stimulation to elucidate the role of 1/f noise in modulating neural synchrony. Using a coupled oscillator model, we demonstrate that ubiquitous 1/f noise does more effectively enhances phase synchrony than spectrally flat (white) noise. Crucially, we identify a competitive synergy between noise intensity and the 1/f spectral exponent: starting from optimal white noise-induced synchrony, increasing the 1/f exponent while decreasing noise intensity leads to a further enhancement of synchrony, which peaks at a specific parameter regime before diminishing. To experimentally validate these findings, we developed a transcranial 1/f noise stimulation (tFNS) system and applied it to human subjects. Compared to spectrally white noise stimulation, the tFNS more robustly enhanced corticospinal synchrony, consistent with model predictions. These results uncover a functional advantage of scale-free brain noise in driving coordinated neural dynamics, offering a new framework for optimizing non-invasive brain stimulation. More broadly, our findings suggest that the brain may harness stochastic facilitation through adaptive modulation of its aperiodic activity to support ordered macro-dynamics.

biophysics↗

bioRxiv2025

Reference-guided genome assembly at scale using ultra-low-coverage high-fidelity long-reads with HiFiCCL

Population genomics using short-read resequencing captures single nucleotide polymorphisms and small insertions and deletions but struggles with structural variants (SVs), leading to a loss of heritability in genome-wide association studies. In recent years, long-read sequencing has improved pangenome construction for key eukaryotic species, addressing this issue to some extent. Sufficient-coverage high-fidelity (HiFi) data for population genomics is often prohibitively expensive, limiting its use in large-scale populations and broader eukaryotic species and creating an urgent need for robust ultra-low coverage assemblies. However, current assemblers underperform in such conditions. To address this, we propose HiFiCCL, the first assembly framework specifically designed for ultra-low-coverage high-fidelity reads, using a reference-guided, chromosome-by-chromosome assembly approach. We demonstrate that HiFiCCL improves ultra-low-coverage assembly performance of existing assemblers and outperforms the state-of-the-art assemblers on human and plant datasets. Tested on 45 human datasets ([~]5x coverage), HiFiCCL combined with hifiasm reduces the length of misassembled contigs relative to hifiasm by an average of 21.19% and up to 38.58%. These improved assemblies enhance germline structural variant detection, reduce chromosome-level mis-scaffolding, enable more accurate pangenome graph construction, and improve the detection of rare and somatic structural variants based on the pangenome graph under ultra-low-coverage conditions.

bioinformatics↗

bioRxiv2025

Cooperation Between Genotoxic Bacteria Accelerates Tumorigenesis in a Mouse Model of Colon Carcinogenesis

To identify causal links between gut microbes and tumorigenesis, we colonized groups of germ-free colon tumor-susceptible mice (ApcMin/+;Il10-/-) with 15 cultured human fecal microbiotas from healthy individuals, as well as patients with inflammatory bowel disease and colorectal cancer. The number of colonic tumors in ApcMin/+;Il10-/- mice varied by donor microbiota but not by the health status of the donor. In vitro screens of host cell proliferation, genotoxicity, and inflammation in bacteria-mammalian cell cocultures revealed that genotoxicity best predicted tumorigenic microbes in vivo with genotoxic microbes present in all tested individuals. The genotoxic subset of strains from each donor induced more tumors than the complete community - even when the complete community was not tumorigenic. Combining genotoxic microbes from multiple sources increased tumor number and decreased the time to tumor onset. Together these results suggest that most individuals harbor genotoxic bacterial strains and the balance of genotoxic to protective strains determines the timing and severity of tumorigenesis in vivo.

microbiology↗

bioRxiv2025

Molecular insights into early malignant transition of hepatocellular carcinoma

The molecular continuum of premalignant-to-malignant transition remains elusive in carcinogenesis, primarily due to the difficulty in sampling transitional lesions. Here, we present comprehensive genomic and immunological profiling of 21 very early hepatocellular carcinomas (veHCCs) arising within 17 cancer-prone DNs. Surprisingly, 82% of cancer-prone DNs harbored TERT alterations, suggesting a predisposing rather than causative role in malignancy transition. A substantial increase in CNA burden, rather than SNV, was noted, indicating a role of chromosome instability in malignancy transition. Additionally, veHCC-originating DNs showed immune inactivity, not falling into the prevailing paradigm that HCCs develop in a context of chronic inflammation. 43% of veHCCs showed an inflamed phenotype with relatively mild CNA burden but already exhibited immune evasion features. Two major evolutionary scenarios were thus proposed: 1) CNA-dominant progression and 2) early immune evasion of those with mild CNA burden. Collectively, our findings illustrate previously unexplored molecular paradigms in HCC initiation, highlighting the therapeutic potential of immunotherapy for early intervention.

cancer biology↗

bioRxiv2025

Energy predicts global mountain endemic plant richness better than environmental heterogeneity

The drivers of biodiversity in mountain ecosystems have long been a central focus in ecologists. Increasing evidence suggests that energy is a key determinant of mountain species diversity; however, whether this pattern holds universally across different mountain ecosystems remains unclear, especially as there may be differences between different plant taxa. To address this knowledge gap, we selected mountain endemic plant genera from global biodiversity hotspots to explore the main drivers of diversity of different taxa in the mountains. Our results indicate that energy is the key driver of endemic plant richness in mountain regions worldwide, particularly for endemic tree and shrub taxa, while endemic herb richness is shaped by both energy and environmental heterogeneity. Regional studies have shown that energy availability drives total endemic plant groups in 70% of mountain regions. Specifically, energy is the dominant driver for 86% of endemic tree groups and 67% of endemic shrub groups, whereas endemic herb groups are the least influenced by energy, with only 50% of mountain regions showing energy as the primary driver. Our findings indicate that energy availability is the predominant factor shaping the diversity of endemic plant groups in mountain ecosystems worldwide. Therefore, mountain ecological conservation efforts should focus extensively on energy input aspects. HighlightsO_LIClimate energy is the main driver of the richness of montane endemic plant taxa, especially for tree and shrub, whereas herb richness is determined by a combination of energy and environmental heterogeneity. C_LIO_LIEnvironmental heterogeneity predominantly drives endemic taxa richness in the Cape of Good Hope, whereas both climatic energy and environmental heterogeneity jointly influence endemic taxa richness in the Andes and Japan. In all other mountain ranges, climatic energy is the primary determinant. C_LIO_LIEndemic tree taxa have the highest number of mountains dominated by climatic energy, followed by endemic shrub taxa, and endemic herb taxa are more affected by environmental heterogeneity. C_LI

ecology↗

bioRxiv2025

Revealing a coherent cell state landscape across single cell datasets with CONCORD

Revealing the underlying cell-state landscape from single-cell data requires overcoming the critical obstacles of batch integration, denoising, and dimensionality reduction. Here, we present CONCORD, a unified framework that simultaneously addresses these challenges within a single self-supervised model. At its core, CONCORD implements a unified probabilistic sampling strategy that corrects batch effects via dataset-aware sampling and enhances biological resolution through hard-negative sampling. Remarkably, using only a minimalist neural network with a single hidden layer and contrastive learning, CONCORD surpasses state-of-the-art performance without relying on deep architectures, auxiliary losses, or external supervision. It seamlessly integrates data across batches, technologies, and even species to generate high-resolution cell atlases. The resulting latent representations are denoised and biologically meaningful--capturing gene co-expression programs, revealing detailed lineage trajectories, and preserving both local geometric relationships and global topological structures. We demonstrate CONCORDs broad applicability across diverse datasets, establishing it as a general-purpose framework for learning unified, high-fidelity representations of cellular identity and dynamics.

bioinformatics↗

bioRxiv2025

Proximity-labeling proteomics reveals remodeled interactomes and altered localization of pathogenic SHP2 variants

Missense mutations in PTPN11, which encodes the protein tyrosine phosphatase SHP2, are common in several developmental disorders and cancers. While many mutations disrupt auto-inhibition and hyperactivate SHP2, several do not enhance catalytic activity. Both activating and non-activating mutations could potentially drive pathogenic signaling by altering SHP2 interactions or localization. We employed proximity-labeling proteomics to map the interaction networks of wild-type SHP2, ten clinically-relevant mutants, and SHP2 bound to an inhibitor that stabilizes its auto-inhibited state. Our analyses revealed mutation- and inhibitor-dependent alterations in the SHP2 interactome, with several mutations also changing localization. Some mutants had increased mitochondrial localization and impacted mitochondrial function. This study provides a resource for exploring SHP2 signaling and offers new insights into the molecular basis of SHP2-driven diseases. Furthermore, this work highlights the capacity for proximity-labeling proteomics to detect missense-mutation-dependent changes in protein interactions and localization.

molecular biology↗

bioRxiv2025

Spatio-temporal distribution patterns and ecological correlates of new mammal records in China

AbstractSpecies geographic distributions are central to research in biogeography, macroecology, and conservation biology. However, incomplete or inaccurate knowledge about their spatiotemporal ranges--known as the Wallacean shortfall--hampers our understanding of biodiversity patterns and processes. In this study, we systematically reviewed 192 papers that reported new distribution records of Chinas mammals from 2001 to 2023, covering 150 species in 26 families across 7 orders. We examined the taxonomic, spatiotemporal, and biogeographic characteristics of these newly recorded species. We used Bayesian Phylogenetic Generalized Linear Mixed Models (BPGLMM) to assess how intrinsic traits and extrinsic factors influenced the likelihood of discoveries and partial Poisson regressions to evaluate how species-level attributes, environmental and socio-economic factors shaped the number of new occurrence records across provinces. Our results showed that Chiroptera (n=69), Eulipotyphla (n=26) and Rodentia (n=23) had the highest number of new records. Among provinces, Yunnan (n=31), Guangdong (n=22), and Xizang (n=18) yielded the most newly recorded species. The amount of annual discoveries varied and peaked between 2017 and 2021. The Western Mountain and Plateau (n=39) and the East Hilly Plain (n=33) zoogeographic subregions had the greatest number of newly recorded species, including two new records extending into historically unrecognized zoogeographic realms. Notably, 61 (40.7%) species were found to extend towards the north or northeast of their known ranges, and 32 (21.3%) eastward, mainly due to the sampling bias. Smaller-bodied species and those with broader habitat ranges are more likely to yield new records, and the total number of new records was positively correlated with regional species richness and current survey efforts (r > 0.5, p < 0.05). These findings expand the known distributions of Chinas mammals and provide essential data for mitigating the Wallacean shortfall. They underscore the urgent need for intensified surveys in biodiversity-rich, underexplored regions--especially targeting small-bodied, data-deficient taxa--and for timely updates and data-sharing to better inform conservation strategies.

ecology↗