Biology subjects

Zong, W.

Publications and source records attributed to Zong, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Multi-region two-photon calcium imaging in freely moving animals

Complex behaviors emerge from the coordinated activity of neural circuits distributed across widely separated brain regions. Existing optical approaches for monitoring neural activity lack the combined capability to record from anatomically distributed regions with high spatiotemporal resolution in freely moving animals. Here we introduce MINI2P-II, a 1.1-g 2P miniscope that achieves large-scale calcium imaging with high spatial resolution, deep imaging depth and dual-color imaging capability. Together with a dual-scope imaging system and a novel implantable periscope lens assembly, MINI2P-II enables simultaneous 2P imaging in widely separated or anatomically adjacent brain regions. In mice, we demonstrate inter-hemisphere coordination in bilateral motor cortex during climbing, egocentric boundary coding in simultaneous retrosplenial and posterior parietal cortex recordings, and in zebra finches, we showed large-scale behavior-dependent activity in both juvenile and adult individuals. MINI2P-II opens the door to multi-region 2P imaging across species and developmental stages in freely moving animals.

neuroscience↗

bioRxiv2026

Epi-PoreC: a nanopore-based method for simultaneous profiling of chromatin conformation, DNA methylation, and chromatin accessibility

Understanding how the three-dimensional (3D) organization of the genome relates to chromatin and epigenetic landscapes requires methods capable of measuring chromosomal DNA interactions and chromatin modifications in an integrated manner. Current approaches typically use separate assays to assess chromatin conformation and epigenetic state, thus these features are not assessed on the same DNA molecules. Here, we describe Epi-PoreC, an Oxford Nanopore long-read sequencing-based method that combines the chromosome conformation capture method, PoreC with Fiber-seq, a method for detecting accessible chromatin regions based on their ability to be labeled using an exogenous adenosine methyltransferase. The positions of chromosome contacts, 6-methyladenosines, and endogenous 5-methylcytosines are then detected by nanopore sequencing, all on the same DNA molecules. Using Arabidopsis thaliana nuclei, we demonstrate that Epi-PoreC yields genome-wide chromatin contact maps comparable to those obtained by standard PoreC and DNA methylation and accessibility profiles comparable to standard Fiber-seq experiments. Epi-PoreC is thus an efficient means for conducting epigenetic and 3D genome profiling on individual DNA sequences in a single assay.

genomics↗

bioRxiv2026

Gene-specific exponent-corrected normalization for library size in bulk RNA-seq

Correcting for library size is an essential step in bulk RNA-seq analyses, as differences in sequencing depth across samples can obscure biological signal with technical noise. While numerous normalization methods and model-based strategies have been proposed, we demonstrate here that library size-normalized counts and differential expression results obtained from such widely adopted approaches often remain strongly correlated with library size in large-scale RNA-seq experiments. Through a systematic analysis of over 100 publicly available GEO and TCGA RNA-seq datasets with raw count data, we show that library size association is observed for a substantial proportion of genes even after state-of-the-art library size correction approaches recommended by leading normalization tools. To address this issue, we propose gecco, a gene-specific exponent-corrected normalization method for RNA-seq counts that incorporates library size directly into the statistical framework via a gene-specific correction term, rather than applying a uniform adjustment factor across all genes. This formulation generalizes existing normalization approaches and yields normalized counts that are free of residual library size effects. Using both simulation studies and real large-scale RNA-seq datasets, we show that our method mitigates library size bias while preserving biological signal across a range of parameter settings. We further demonstrate that our approach leads to higher detection accuracy and more biologically meaningful pathway enrichment results in downstream differential expression and rhythmicity analyses without compromising false discovery rate control. Our method is implemented in R and is fully compatible with the widely used differential expression analysis methods DESeq2 and edgeR.

bioinformatics↗

bioRxiv2026

A versatile, positive-going voltage indicator that enables accessible two-photon recordings in vivo

Genetically encoded voltage indicators (GEVIs) enable cell-type-specific optical readout of membrane potential, but two-photon (2P) spike detection has been hampered by low signal-to-noise and ultrafast off-kinetics, restricting use to specialized microscopes. We introduce FORCE1s, a green, positive-going GEVI engineered to make robust 2P voltage imaging broadly accessible. FORCE1s brightens from a dark baseline during depolarization, reports spikes with [~]100% {Delta}F/F in awake mice, and displays repolarization kinetics that are tuned for reliable spike detection at sub-kilohertz frame rates. As a result, FORCE1s supports spike-resolved multi-cell recordings on standard resonant-scanning microscopes, and further scales to larger fields of view and neuron counts on advanced modalities. FORCE1s also enables multiplexed voltage-neurotransmitter imaging and extended recordings in freely moving mice using a compact, affordable MEMS-based 2P miniscope. Together, these advances establish FORCE1s as a community-ready tool that democratizes deep-tissue voltage imaging across platforms and experimental contexts.

neuroscience↗

bioRxiv2026

Multi-agent reasoning enables predictive design of living materials

Artificial intelligence is increasingly used to accelerate scientific discovery, but most successful frameworks operate within well-defined molecular, protein or materials spaces. Living materials present a more formidable computational problem because functions emerge from context dependent coupling among cells, matrices, fabrication processes and evaluation conditions. Here we introduce LiveMat, a multi-agent reasoning framework that transforms unstructured literature into a computable design space for living materials. LiveMat standardizes 34,215 living material records, integrating 16,769 microorganism and 17,446 polymer entries into a knowledge graph linking living components, abiotic matrices, functional outputs, evaluation contexts and performance metrics. Benchmarking across five large language models shows that living material reasoning is limited mainly by cross-domain feature integration rather than coarse classification. LiveMat overcomes this limitation through constraint decomposition, provenance-aware extraction, consistency checking and expert-anchored ranking. In a prospective wound-healing task, it prioritizes a four-component design with state-of-the-art in vivo performance, establishing a scalable infrastructure for interpretable, evidence-grounded living material discovery.

biochemistry↗

bioRxiv2025

Joint analysis of expression and variation at single cell resolution by scVar

Tumor heterogeneity represents a critical determinant affecting both cancer diagnosis and therapeutic efficacy. Traditional bulk sequencing approaches are limited in their ability to resolve genomic alterations at the resolution of individual cells. In this study, we present scVar, an integrated analytical framework designed for mutation profiling using single-cell transcriptomic data. scVar enables sensitive and robust detection of single-nucleotide variants, particularly facilitating the identification of low-frequency variants. The framework incorporates customizable filtering parameters including variant allele frequency, and provides comprehensive functional and clinical annotations for identified mutations. Furthermore, scVar includes downstream analytical modules that facilitate the joint investigation of transcriptomic and mutational profiles within single cells. Benchmarking on simulated datasets and matched tumor samples demonstrates that scVar consistently outperforms existing methods, especially in detecting variants of low abundance, and shows strong concordance with whole-exome sequencing data. Application of scVar to non-small cell lung cancer samples effectively characterized ITH across spatially distinct tumor regions and diverse cellular populations. Collectively, scVar offers an integrated platform for concurrent analysis of somatic mutations and transcriptomic data derived from single-cell RNA sequencing, providing a powerful tool for elucidating tumor evolution and the complex interplay between genomic heterogeneity and the tumor microenvironment.

bioinformatics↗

bioRxiv2025

TypeSINE: Genome-Wide Detection of SINE Retrotransposon Polymorphisms Reveals Functional Variants Linked to Body Size Variation in Pigs

The genotyping of Short Interspersed Element (SINE) retrotransposon insertion polymorphisms (RIPs) from large-scale sequencing data remains technically challenging. To overcome this limitation, we developed TypeSINE to genotype SINE-RIPs from short-read sequencing data. Analyzing 362 porcine genomes, we identified 749,835 SINE-RIPs (>85% accuracy), including 65,917 common variants (5-95% frequency). These showed uniform genomic distribution ([~]22/Mb), with 40% in introns. Population analyses based on SINE-RIPs revealed independent domestication of Asian and European pigs from local wild populations, followed by introgression. GWAS detected body size-associated regions using SINE-RIPs. We created pigRIPdb (82,227 curated SINE-RIPs) with browsing and visualization tools. The methods cross-species applicability is supported by conserved SINE evolutionary patterns, enabling polymorphism discovery of SINEs in livestock and humans. TypeSINE represents an efficient, scalable solution for genome-wide SINE-RIP analysis, advancing population genomics research. TeaserAn integrated SINE-RIP genotyping platform with companion database enables large-scale analysis of SINE evolution and population genetics in swine

bioinformatics↗

bioRxiv2025

Prior cocaine use disrupts identification of hidden states by single units and neural ensembles in orbitofrontal cortex

The orbitofrontal cortex (OFC) is critical to identifying task structure and to generalizing appropriately across task states with similar underlying or hidden causes. This capability is at the heart of OFCs proposed role in a network responsible for cognitive mapping, and its loss can explain many deficits associated with OFC damage or inactivation. Substance use disorder is defined by behaviors that share much in common with these deficits, such as an inability to modify learned behaviors in the face of new information about undesired consequences. One explanation for this similarity would be if addictive drugs impacted the ability of OFC to recognize underlying similarities, hidden states, that allow information learned in one setting to be used in another. To explore this possibility, we trained rats to self-administer cocaine and then recorded single unit activity in lateral OFC as these rats performed in an odor sequence task consisting of unique and shared positions. In well-trained controls, we observed chance decoding of sequence at shared positions and near chance decoding even at unique positions, reflecting the irrelevance of distinguishing these positions in the task. By contrast, in cocaine-experienced rats, decoding remained significantly elevated, particularly at the positions that had superficial sensory differences that were collapsed in controls across learning. These neural differences were accompanied by increases in behavioral variability at these positions. A tensor component analysis showed that this effect of reduced generalization after cocaine use also extended across positions in the sequences. These results show that prior cocaine use disrupts the normal identification of hidden states by OFC.

neuroscience↗

bioRxiv2024

Molecular and cellular rhythms in excitatory and inhibitory neurons in the mouse prefrontal cortex

Previous studies have shown that there are rhythms in gene expression in the mouse prefrontal cortex (PFC); however, the contribution of different cell types and potential variation by sex has not yet been determined. Of particular interest are excitatory pyramidal cells and inhibitory parvalbumin (PV) interneurons, as interactions between these cell types are essential for regulating the excitation/inhibition balance and controlling many of the cognitive functions regulated by the PFC. In this study, we identify cell-type specific rhythms in the translatome of PV and pyramidal cells in the mouse PFC and assess diurnal rhythms in PV cell electrophysiological properties. We find that while core molecular clock genes are conserved and synchronized between cell types, pyramidal cells have nearly twice as many rhythmic transcripts as PV cells (35% vs. 18%). Rhythmic transcripts in pyramidal cells also show a high degree of overlap between sexes, both in terms of which transcripts are rhythmic and in the biological processes associated with them. Conversely, in PV cells, rhythmic transcripts from males and females are largely distinct. Moreover, we find sex-specific effects of phase on action potential properties in PV cells that are eliminated by environmental circadian disruption. Together, this study demonstrates that rhythms in gene expression and electrophysiological properties in the mouse PFC vary by both cell type and sex. Moreover, the biological processes associated with these rhythmic transcripts may provide insight into the unique functions of rhythms in these cells, as well as their selective vulnerabilities to circadian disruption. Significance statementThis is the first study to examine translatomic rhythms in the mouse PFC with cell-type specificity. We find that the core molecular clock cycles in phase across cell types, indicating that previously described daily oscillations in the cortical excitation/inhibition balance are not the consequence of a phase offset between PV and pyramidal cells. Nevertheless, rhythmic transcripts and their associated biological processes differ by both sex and cell type, suggesting that molecular rhythms may play a unique role in different cell types and between sexes. Therefore, our results, such as the enrichment of transcripts associated with mitochondrial function in PV cells from males, point towards possible cell and sex-specific mechanisms that could contribute to psychiatric and cognitive diseases upon rhythm disruption.

neuroscience↗

bioRxiv2023

Pathogenic CD8 T cell responses are driven by neutrophil-mediated hypoxia in cutaneous leishmaniasis.

Cutaneous leishmaniasis caused by Leishmania parasites exhibits a wide range of clinical manifestations. Although parasites influence disease severity, cytolytic CD8 T cell responses mediate disease. While these responses originate in the lymph node, we find that expression of the cytolytic effector molecule granzyme B is restricted to lesional CD8 T cells in Leishmania- infected mice, suggesting that local cues within inflamed skin induce cytolytic function. Expression of Blimp-1 (Prdm1), a transcription factor necessary for cytolytic CD8 T cell differentiation, is driven by hypoxia within the inflamed skin. Hypoxia is further enhanced by the recruitment of neutrophils that consume oxygen to produce reactive oxygen species, ultimately increasing granzyme B expression in CD8 T cells. Importantly, lesions from cutaneous leishmaniasis patients exhibit hypoxia transcription signatures that correlate with the presence of neutrophils. Thus, targeting hypoxia-driven signals that support local differentiation of cytolytic CD8 T cells may improve the prognosis for patients with cutaneous leishmaniasis, as well as other inflammatory skin diseases where cytolytic CD8 T cells contribute to pathogenesis.

immunology↗

bioRxiv2023

Schema cell formation in orbitofrontal cortex is suppressed by hippocampal output

Both orbitofrontal cortex (OFC) and hippocampus (HC) are implicated in the formation of cognitive maps and their generalization into schemas. However how these areas interact in supporting this function remains an open question, with some proposals supporting a serial model in which OFC draws upon task representations created by HC to extract key behavioral features and others proposing a parallel model in which both regions construct representations that highlight different types of information. Here we tested between these two models by asking how schema correlates in OFC would be affected by inactivation of HC output, after learning and during transfer across problems. We found the prevalence and content of schema correlates were unaffected by inactivation after learning, while inactivation during learning accelerated their formation. These results contradict a serial model and favor the proposal that OFC and HC operate in parallel to extract different features defining cognitive maps and schemas.

neuroscience↗

bioRxiv2022

The ultradian transcriptome of the human prefrontal cortex and abnormalities in schizophrenia

Twelve-hour (12 h) ultradian rhythms are a well-known phenomenon in coastal marine organisms. While 12 h cycles are observed in human behavior and physiology, no study has measured 12 h rhythms in the human brain. Here we identify 12 h rhythms in transcripts which either peak at sleep/wake transitions (~9 AM/PM) or static times (~3 PM/AM) in the dorsolateral prefrontal cortex, a region involved in cognition. Subjects with schizophrenia lose 12 h rhythms in genes associated with the unfolded protein response and neuronal structural maintenance. Moreover, genes involved in mitochondrial function and protein translation, which normally peak at sleep/wake transitions, peak instead at static times in schizophrenia, suggesting suboptimal timing of these essential processes that may contribute to cognitive deficits commonly found in schizophrenia.

neuroscience↗

bioRxiv2022

Experimental Design and Power Calculation in Omics Circadian Rhythmicity Detection

Circadian clocks are 24-hour endogenous oscillators in physiological and behavioral processes. Though recent transcriptomic studies have been successful in revealing the circadian rhythmicity in gene expression, the power calculation for omics circadian analysis have not been fully explored. In this paper, we develop a statistical method, namely CircaPower, to perform power calculation for circadian pattern detection. Our theoretical framework is determined by three key factors in circadian gene detection: sample size, intrinsic effect size and sampling design. Via simulations, we systematically investigate the impact of these key factors on circadian power calculation. We not only demonstrate that CircaPower is fast and accurate, but also show its underlying cosinor model is robust against variety of violations of model assumptions. In real applications, we demonstrate the performance of CircaPower using mouse pan-tissue data and human post-mortem brain data, and illustrate how to perform circadian power calculation using mouse skeleton muscle RNA-Seq pilot as case study. Our method CircaPower has been implemented in an R package, which is made publicly available on GitHub (https://github.com/circaPower/circaPower).

genomics↗

bioRxiv2021

CAMO: A molecular congruence analysis framework for evaluating model organisms

CAMO provides a rigorous and user-friendly solution for quantification and mechanistic exploration of omics congruence in model organisms and humans. It performs threshold-free differential analysis, quantitative concordance/discordance scoring, pathway-centric investigation, and topological subnetwork detection. Instead of dichotomous claims of "poorly" or "greatly" mimicking humans, CAMO facilitates discovery and visualization of specific molecular mechanisms that are best or least mimicked, providing foundations for hypothesis generation and subsequent translational investigations.

genomics↗

bioRxiv2021

Dysconnectivity between auditory-cognitive network associated with auditory GABA and glutamate levels in presbycusis patients

Accumulating studies suggest an interaction between presbycusis (PC) and cognitive impairment, which may be explained by the cognitive-ear link to a large extent. However, the neurophysiological mechanisms underlying this link are largely unknown. Here, 51 PC patients and 51 well-matched healthy controls were recruited. We combined resting-state functional MRI and edited magnetic resonance spectroscopy to investigate changes of intra- and inter-network functional connectivity and their relationships with auditory gamma-aminobutyric acid (GABA) and glutamate (Glu) levels and cognitive impairment in PC. Our study confirmed the plastic model of cognitive-ear link at the level of the large-scale brain network, including the dysconnectivity within high-order cognitive networks and between the auditory-cognitive network and overactivation between cognitive networks dependent on hearing loss, which was closely related to the cognitive impairment of PC patients. Moreover, GABA and Glu levels in the central auditory processing were abnormal in patients with PC. Importantly, reduction of GABA-mediated inhibition plays a crucial role in a dysconnectivity between the auditory-cognitive network, which may be neurochemical underpinnings of functional remodeling of cognitive-ear link in PC. Modulation of GABA neurotransmission may enable the development of new therapeutic strategies for the cognitive impairment of PC patients.

neuroscience↗

bioRxiv2021

Molecular rhythm alterations in prefrontal cortex and nucleus accumbens associated with opioid use disorder

Severe and persistent disruptions to sleep and circadian rhythms are common features of people with opioid use disorder (OUD). Preclinical findings suggest altered molecular rhythms in the brain are involved in opioid reward and dependence. However, whether molecular rhythms are disrupted in brains of people with OUD remained an open question, critical to understanding the role of circadian rhythms in opioid addiction. We previously used subjects times of death (TOD) as a marker of time of day to investigate transcriptional rhythm alterations in psychiatric disorders. Using TOD and RNA sequencing, we discovered rhythmic transcripts in both the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc), key brain areas involved in opioid addiction, were largely distinct between OUD and unaffected comparison subjects. Further, fewer rhythmic transcripts were identified in DLPFC of OUD subjects compared to unaffected subjects, but nearly double the number of rhythmic transcripts were found in the NAc of OUD subjects. In OUD, rhythmic transcripts in the NAc peaked either in the evening or near sunrise, and were associated with dopamine, opioid, and GABAergic neurotransmission. Co-expression network analysis identified several OUD-specific modules in the NAc, enriched for transcripts involved in the modulation of dopamine and GABA synapses, including glutamatergic signaling and extracellular matrices. Integrative analyses with human GWAS revealed that rhythmic transcripts in DLPFC and NAc were enriched for genomic loci associated with sleep duration and insomnia. Overall, our results connect transcriptional rhythm changes in dopamine, opioid, and GABAergic synaptic signaling in human brain to sleep-related phenotypes and OUD.

neuroscience↗

bioRxiv2021

Large-scale two-photon calcium imaging in freely moving mice

We developed a miniaturized two-photon microscope (MINI2P) for fast, high-resolution, multiplane calcium imaging of over 1,000 neurons at a time in freely moving mice. With a microscope weight below 3g and a highly flexible connection cable, MINI2P allowed imaging to proceed with no impediment of behavior in half-hour free-foraging trials compared to untethered, unimplanted animals. The improved cell yield was achieved through a new optical system design featuring an enlarged field of view (FOV) and a new micro-tunable lens with increased z-scanning range and speed that allowed for fast and stable imaging of multiple, interleaved planes as well as 3D functional imaging. A novel technique for successive imaging across multiple, adjacent FOVs enabled recordings from more than 10,000 neurons in the same animal. Large-scale proof-of-principle data were obtained from cell populations in visual cortex, medial entorhinal cortex, and hippocampus, revealing spatial tuning of cells in all areas, including visual cortex. HighlightsWe developed a lightweight 2-photon miniscope for imaging in freely-foraging mice Activity can be monitored in volumes of over 1,000 visual or entorhinal-cortex cells A new z-scanning module allows fast imaging across multiple interleaved planes Successive imaging from adjacent regions enables imaging from more than 10,000 cells

neuroscience↗

bioRxiv2021

Functional network topography of the medial entorhinal cortex

The medial entorhinal cortex (MEC) creates a map of local space, based on the firing patterns of grid, head direction (HD), border, and object-vector (OV) cells. How these cell types are organized anatomically is debated. In-depth analysis of this question requires collection of precise anatomical and activity data across large populations of neurons during unrestrained behavior, which neither electrophysiological nor previous imaging methods fully afford. Here we examined the topographic arrangement of spatially modulated neurons in MEC and adjacent parasubiculum using miniaturized, portable two-photon microscopes, which allow mice to roam freely in open fields. Grid cells exhibited low levels of co-occurrence with OV cells and clustered anatomically, while border, HD and OV cells tended to intermingle. These data suggest that grid-cell networks might be largely distinct from those of border, HD and OV cells and that grid cells exhibit strong coupling among themselves but weaker links to other cell types. Highlights- Grid and object vector cells show low levels of regional co-occurrence - Grid cells exhibit the strongest tendency to cluster among all spatial cell types - Grid cells stay separate from border, head direction and object vector cells - The territories of grid, head direction and border cells remain stable over weeks

neuroscience↗