Biology subjects

Huo, Y.

Publications and source records attributed to Huo, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Human brain white matter charts in international populations

Brain charts provide normative references for identifying neurodevelopmental milestones and clinically meaningful deviations. Existing white matter (WM) charts are derived predominantly from European and North American populations, limiting generalizability. Here, we established the first set of population-specific WM charts of 198 morphological and microstructural phenotypes for both Chinese (N=19,215) and Western (N=15,584) populations across the human lifespan. Developmental trajectories and spatial organization of WM maturation and degeneration were broadly conserved across the populations, whereas maturational timing varied across pathways and metrics. The Chinese population showed earlier maturation in several projection and sensorimotor pathways, but more protracted maturation in higher-order association and limbic pathways. Chinese population-matched charts more accurately predicted WM phenotypes and detected more extreme disease-related deviations in brain health in the Chinese population than Western-derived models. Individual deviation patterns further discriminated patients from healthy controls and predicted cognitive performance and plasma biomarkers. Our findings reveal population-specific WM maturation and show that reference-population mismatch can reduce the accuracy and clinical sensitivity of normative brain charts.

neuroscience↗

bioRxiv2026

Determining cellular phylogeny and migration at high resolution in spatial genomics

Cellular migration and tumor evolution are central to tissue homeostasis and cancer biology. Rapid advances in spatial genomics have raised the possibility of using somatic mutations to track these processes in situ in human tissues. However, frequent data dropouts in spatial genomics measurements make this challenging to implement. Here, we present StarTrak (SpaTial Analysis for lineage ReconsTRuction with somatic vAriant calling and tracKing), a framework for somatic variant calling and lineage reconstruction at single-pixel spatial resolution. StarTrak employs a neural network framework to integrate mutational evidence (from both nuclear and mitochondrial reads), spatial proximity, histological images, and transcriptomic states to identify spatially informative patterns of mutations. It performs robustly across tissue types and spatial-omics platforms (being particularly successful with spatial ATAC-seq). Applying StarTrak to tumor sections, we infer the migration of mutated tumor cells into adjacent non-malignant tissues and reconstruct distinct lineage trees associated with different spatial regions. Notably, we identify tumor regions with nearly identical transcriptomic states but distinct mutational profiles. Moreover, for skin sections, StarTrak identifies sunlight-associated mutations in non-malignant epidermis and evidence suggesting the migration of these mutant surface cells into deeper skin layers. Overall, by integrating mutation calling with spatial context, StarTrak enables the inference of spatially resolved cellular migration and cellular phylogeny.

bioinformatics↗

bioRxiv2026

Human-specific multicopy gene FRMPD2 promotes synapse formation via recruitment of neuroligin 1

FRMPD2 is a human-specific multi-copy gene with higher mRNA expression in brain tissue, but its role in synapse formation and neurodevelopment remains unknown. We find that FRMPD2 is a neuron-specific protein with a high expression level in human brains compared to rodent brains. FRMPD2 overexpression in rat neurons stimulates synaptogenesis, leading to increased synaptic activities. Importantly, our results show that FRMPD2 via its PDZ domains recruits and enhances neuroligin-1 protein levels at the postsynaptic sites, and via its FERM domain interacts with the F-actin network in the spine. Increased expression of FRMPD2 also promotes spine formation and maturation, a foundational process for synapse formation. In developing embryonic mouse brains expressing higher FRMPD2 protein levels, we observed delayed neuronal migration, presumably promoting a protracted timeline for cortical lamination as a feature in human brain development. Behaviorally, mice with FRMPD2 overexpression in the brain demonstrate enhanced spatial memory retention. These findings indicate an important function for FRMPD2 in neuronal connectivity, brain development, and cognitive function.

neuroscience↗

bioRxiv2026

TRaP: An Open-source, Reproducible Framework for Raman Spectral Preprocessing across Heterogeneous Systems

Raman spectroscopy offers a uniquely rich window into molecular structure and composition, making it a powerful tool across fields ranging from materials science to biology. However, the reproducibility of Raman data analysis remains a fundamental bottleneck. In practice, transforming raw spectra into meaningful results is far from standardized: workflows are often complex, fragmented, and implemented through highly customized, case-specific code. This challenge is compounded by the lack of unified open-source pipelines and the diversity of acquisition systems, each introducing its own file formats, calibration schemes, and correction requirements. Consequently, researchers must frequently rely on manual, ad hoc reconciliation of processing steps. To address this gap, we introduce TRaP (Toolbox for Reproducible Raman Processing), an open-source, GUI-based Python toolkit designed to bring reproducibility, transparency, and portability to Raman spectral analysis. TRaP unifies the entire preprocessing-to-analysis pipeline within a single, coherent framework that operates consistently across heterogeneous instrument platforms (e.g., Clinical Fiber-optic Raman System, Commercial Portable System and Commercial Raman Microscope). Central to its design is the concept of fully shareable, declarative workflows: users can encode complete processing pipelines into a single configuration file (e.g., JSON), enabling others to reproduce results instantly without reimplementing code or reverse-engineering undocumented steps. Beyond convenience, TRaP integrates configuration management, X-axis calibration, spectral response correction, interactive processing, and batch execution into a workflow-driven architecture that enforces deterministic, repeatable operations. Every transformation is explicitly recorded, making the full processing history transparent, inspectable, and reproducible. This eliminates ambiguity in how results are generated and ensures that identical protocols can be applied consistently across datasets and experimental contexts. Through representative use cases, we show that TRaP enables seamless, reproducible preprocessing of Raman spectra acquired from diverse platforms within a unified environment. We hope TRaP can empower Raman data processing as a reproducible, shareable, and systematized scientific practice, aligning it with modern standards for computational research. TRaP is released as an open-source software at https://github.com/hrlblab/TRaP

bioengineering↗

bioRxiv2026

Ubiquitination-mediated mitochondrial protein degradation ensures seedling emergence by regulating ER-mitochondrial interaction and mitophagy

Seedling emergence is a pivotal step of plant survival, requiring rapid hypocotyl elongation for soil penetration. This energy-demanding process necessitates active mitochondrial respiration, which inevitably induces oxidative damage. Therefore, plants evolved a quality control mechanism that selectively removes dysfunctional mitochondria through the mitophagy pathway. Here, we identified SPL2, a mitochondrial E3 ligase which is essential for hypocotyl elongation and seedling emergence through degrading mitochondrial outer membrane proteins, such as TRB1 and FIS1A. Intriguingly, these proteins also interact with an ER protein, VAP27-1, forming a complex at the ER-mitochondria contact sites, which is essential for mitophagy initiation. The spl2 mutant exhibits enhanced ER-mitochondrial tethering and mitophagy activation, whereas its overexpression has the opposite effects. The expression of SPL2 increases after light perception, in agreement with the reduced mitophagy. Collectively, our findings reveal novel mechanistic insights into seedling emergence, which are coordinated through protein ubiquitination, ER-mitochondrial interaction, and mitophagy.

plant biology↗

bioRxiv2026

SpaMOAL: A spatial multi-omics graph contrastive learning method for spatial domains identification

Recent advances in spatial multi-omics technologies have opened new avenues for characterizing tissue architecture and function in situ, by simultaneously providing multimodal and complementary information--such as spatially resolved transcriptomic, epigenomic, and proteomic features. Current computational approaches face substantial challenges such as effective integration of multi-omics molecular information with spatial information and corresponding high-resolution histology images. To address this challenge, we proposed SpaMOAL (Spatially Multi-Omics graph contrAstive Learning), a graph-based contrastive learning approach for spatial domain identification. SpaMOAL learns clustering-friendly representations from spatial multi-omics data by integrating spatial coordinates, histological image features and molecular profiles, enabling accurate delineation of spatial tissue domains. Benchmarking across multiple recent paired spatial multi-omics datasets demonstrated that SpaMOAL consistently outperforms existing methods. By enabling accurate spatial domain delineation, SpaMOAL provides a powerful framework for interpreting tissue organization and cellular microenvironments.

bioinformatics↗

bioRxiv2026

Tumor Cell Clustering Enhances Metastatic Competence by Regulating the H3K36 Histone Demethylase KDM2A

Disseminated tumor cells can form clusters via cell-cell adhesion, which increases their capacity to initiate metastasis. Metastatic clusters are characterized by distinct changes in transcription, suggesting that epigenetic mechanisms underlie their unique phenotypic state. By performing functional epigenomic studies in models of non-small cell lung cancer, we identified the histone H3 lysine 36 (H3K36) demethylase KDM2A as being differentially required for the fitness of metastatic cell clusters. This contextual dependency on KDM2A is predicated by tumor cell-cell aggregation, which specifically induces KDM2A binding to CpG island enriched promoters. At these defined genomic loci, KDM2A maintains H3K36 monomethylation, which preferentially correlates with transcriptional activation. KDM2A directly targets oxidative phosphorylation genes and KDM2A activity is required for optimal mitochondrial respiration and apical cell junction integrity in cell clusters. Consequently, suppressing KDM2A reduces metastatic seeding and colonization in multiple organs, including in the brain. These findings reveal a chromatin regulatory mechanism by which homotypic cell communication instructs the epigenome of disseminated tumor cells to potentiate their metastatic competence.

cancer biology↗

bioRxiv2025

scCotag: Diagonal integration of single-cell multi-omics data via prior-informed co-optimal transport and regularized barycentric mapping

Recent advances in high-throughput single-cell technologies have enabled characterization of cellular states across distinct omics layers, yielding complementary insights into the organization of biological systems. To jointly leverage these disparate modalities, computational methods have been developed to align non-overlapping cell populations profiled in different omics layers, a task known as diagonal integration, thereby facilitating more fine-grained biological interpretations. However, existing integration approaches unrealistically assume that all cells are alignable and treat prior-knowledge-derived feature correspondences as fully reliable, retaining them unrefined throughout the alignment process. In this work, we introduce scCotag, a co-optimal transport (COOT)-based deep learning frame-work for diagonal integration of single-cell multi-omics data, to address these limitations. scCotag first infers cell alignment and feature correspondence with prior-informed COOT in an iterative manner, and then leverages the resulting transport plans to jointly learn cell and feature embeddings via regularized barycentric mapping and graph reweighting. Systematic benchmarking on human brain, bone marrow, and blood single-cell RNA-seq and ATAC-seq datasets demonstrates the overall superior performance of scCotag over state-of-the-art methods in both cell alignment accuracy and embedding accuracy. In particular, scCotag excels in simulated imbalance scenarios where not all cells are alignable. Applying scCotag to data in postmortem brains of Alzheimers disease (AD) and non-AD (NoAD) patients further yields more fine-grained biological interpretation of regulatory mechanisms. Together, these results demonstrate that scCotag provides a robust framework for single-cell diagonal integration and regulatory inference.

bioinformatics↗

bioRxiv2025

Computer Vision Methods for Spatial Transcriptomics: A Survey

Spatial transcriptomics (ST) enables the simultaneous measurement of gene expression and spatial localization within tissue sections, providing unprecedented opportunities to dissect tissue architecture and functional organization. As a relatively new omics technology, bioinformatics has driven much of the innovation in ST. However, within these frameworks, "spatial" information is often reduced to locations and relationships between molecular profiles, without fully leveraging the wealth of submicron morphological detail and histological knowledge available. Advances in computer vision-based artificial intelligence (AI) are opening exciting new avenues beyond conventional bioinformatics approaches by modeling complex histological patterns and linking morphology to molecular states. More excitingly, they bring fresh perspectives to potentially address key limitations of ST, including its high cost, limited clinical applicability, and reliance on twodimensional (2D) analysis of inherently three-dimensional (3D) tissues. For instance, models that predict ST directly from histology images enable "virtual sequencing," drastically reducing costs while integrating morphological insights from pathology with molecular biomarkers, thus accelerating clinical translation. Moreover, computer vision techniques can reconstruct pixel-aligned 3D tissue models, overcoming the technical barriers of 2D acquisition and advancing 3D spatial omics analytics. In this paper, we present the first systematic survey of computer vision AI models for ST analytics, categorizing approaches across architectures, learning paradigms, tasks, and datasets, and tracing their technological evolution. We highlight key challenges and future directions, offering a panoramic perspective on vision-driven ST and its potential to transform both basic research and clinical practice. The curated collection of vision-driven spatial transcriptomics papers is available at https://github.com/hrlblab/computer_vision_spatial_omics.

bioinformatics↗

bioRxiv2025

ASTRO: Automated Spatial Whole-Transcriptome RNA-Expression Workflow

MotivationDespite significant advances in spatial transcriptomics, the analysis of formalin-fixed paraffin-embedded (FFPE) tissues, which constitute most clinically available samples, remains challenging. Additionally, capturing both coding and noncoding RNAs in a spatial context poses significant challenges. We recently introduced Patho-DBiT, a technology designed to address these unmet needs. However, the marked differences between Patho-DBiT and existing spatial transcriptomics protocols necessitate specialized computational tools for comprehensive whole-transcriptome analysis in FFPE samples. ResultsHere, we present ASTRO, an automated pipeline developed to process spatial transcriptomics data. In addition to supporting standard datasets, ASTRO is optimized for whole-transcriptome analyses of FFPE samples, enabling the detection of various RNA species, including non-coding RNAs such as miRNAs. To compensate for the reduced RNA quality in FFPE tissues, ASTRO incorporates a specialized filtering step and optimizes spatial barcode calling, increasing the mapping rate. These optimizations allow ASTRO to spatially quantify coding and non-coding RNA species in the entire transcriptome and achieve robust performance in FFPE samples. AvailabilityCodes are available at GitHub (https://github.com/gersteinlab/ASTRO).

bioinformatics↗

bioRxiv2024

Loss of Neurofibromin Induces Inflammatory Macrophage Phenotypic Switch and Retinal Neovascularization via GLUT1 Activation

Persons with neurofibromatosis type 1 (NF1), a tumor predisposition syndrome, are largely protected from diabetes and exhibit evidence of enhanced glucose metabolism, which is replicated in mice harboring Nf1 mutations. A hallmark of NF1-associated neurofibromas and sarcomas is the high density of inflammatory macrophages and targeting macrophages appears efficacious in models of NF1. Inflammatory macrophages rely on glycolysis to rapidly generate ATP; thus, identifying whether neurofibromin, the protein encoded by the NF1 gene, controls glucose uptake and/or glycolysis in macrophages is therapeutically compelling. Using neurofibromin-deficient macrophages and macrophage-specific Nf1 knockout mice, we demonstrate that neurofibromin complexes with glucose transporter 1 (GLUT1) to restrain its activity and that loss of neurofibromin permits Akt2 to facilitate GLUT1 translocation to the membrane in macrophages. In turn, glucose internalization and glycolysis are highly up regulated and provoke putative reparative (M2) macrophages to undergo inflammatory phenotypic switch. Inflammatory M1 macrophages and inflammatory-like M2 macrophages invest the perivascular stroma of tumors and induce pathologic angiogenesis in mice harboring macrophage-specific Nf1 deletion. These studies identify a clear mechanism for the enhanced glycolysis and low risk for diabetes observed in persons with NF1 and provide a novel therapeutic target for manifestations of NF1.

cell biology↗

bioRxiv2024

Endothelial MICU1 protects against vascular inflammation and atherosclerosis by inhibiting mitochondrial calcium uptake

Atherosclerosis is triggered by endothelial activation and vascular inflammation, which is closely related to mitochondrial dysfunction. Mitochondrial calcium uptake 1 (MICU1), as the gatekeeper of mitochondrial Ca2+ homeostasis, is a critical player in mitochondrial function and implicated in a plethora of pathophysiological conditions. However, the role of MICU1 in the pathogenesis of vascular inflammation and atherosclerosis is unknown. We ask whether endothelial MICU1 can prevent vascular inflammation and atherosclerosis by maintaining mitochondrial homeostasis. We observed that vascular inflammation in response to LPS was aggravated in EC-specific Micu1 knockout mice (Micu1ECKO) and reduced in EC-specific Micu1 transgenic mice (Micu1ECTg). Furthermore, hypercholesterolemic Micu1ECKO mice also showed accelerated formation of atherosclerotic plaques, while Micu1ECTg mice protected against atherosclerosis. Mechanistically, MICU1 regulated mitochondrial Ca2+ influx, thereby reducing the expression of the mitochondrial deacetylase SIRT3 and the ensuing deacetylation of SOD2, leading to the burst of mitochondrial reactive oxygen species (mROS). Of clinical relevance, we identified decreased MICU1 level in endothelial layer of human atherosclerotic plaques, as well as in primary human aortic endothelial cells (HAECs) exposed to serum from patients with coronary artery diseases. Two-sample Wald ratio Mendelian randomization further revealed that increased expression of MICU1 was associated with decreased risk of coronary artery bypass grafting (CABG). Our findings unravel a critical and unrecognized role of MICU1 in preventing vascular inflammation and atherosclerosis by maintaining mitochondrial Ca2+ homeostasis.

molecular biology↗

bioRxiv2024

Modification of regulatory tyrosines biases human Hsp90α for interaction with cochaperones and clients

The highly conserved Hsp90 chaperones control stability and activity of many essential signaling and regulatory proteins including many protein kinases, E3 ligases and transcription factors. Thereby, Hsp90s couple cellular homeostasis of the proteome to cell fate decisions. High-throughput mass spectrometry revealed 178 and 169 posttranslational modifications (PTMs) for human cytosolic Hsp90 and Hsp90{beta}, but for only a few of the modifications the physiological consequences are investigated in some detail. In this study, we explored the suitability of the yeast model system for the identification of key regulatory residues in human Hsp90. Replacement of three tyrosine residues known to be phosphorylated by phosphomimetic glutamate and by non-phosphorylatable phenylalanine individually and in combination influenced yeast growth and the maturation of 7 different Hsp90 clients in distinct ways. Furthermore, wild-type and mutant Hsp90 differed in their ability to stabilize known clients when expressed in HepG2 HSP90AA1-/- cells. The purified mutant proteins differed in their interaction with the cochaperones Aha1, Cdc37, Hop and p23 and in their support of the maturation of glucocorticoid receptor ligand binding domain in vitro. In vivo and in vitro data correspond well to each other confirming that the yeast system is suitable for the identification of key regulatory sites in human Hsp90s. Our findings indicate that even closely related clients are affected differently by the amino acid replacements in the investigated positions, suggesting that PTMs could bias Hsp90s client specificity.

molecular biology↗

bioRxiv2024

Sex, racial, and APOE-ϵ4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer's disease

Structured AbstractO_ST_ABSINTRODUCTIONC_ST_ABSThe effects of sex, race, and Apolipoprotein E (APOE) - Alzheimers disease (AD) risk factors - on white matter integrity are not well characterized. METHODSDiffusion MRI data from nine well-established longitudinal cohorts of aging were free-water (FW)-corrected and harmonized. This dataset included 4,702 participants (age=73.06 {+/-} 9.75) with 9,671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FAFWcorr) were used to assess differences in white matter microstructure by sex, race, and APOE-{varepsilon}4 carrier status. RESULTSSex differences in FAFWcorr in association and projection tracts, racial differences in FAFWcorr in projection tracts, and APOE-{varepsilon}4 differences in FW limbic and occipital transcallosal tracts were most pronounced. DISCUSSIONThere are prominent differences in white matter microstructure by sex, race, and APOE- {varepsilon}4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted. HighlightsO_LISex, race, and APOE-{varepsilon}4 carrier status relate to white matter microstructural integrity C_LIO_LIFemales generally have lower FAFWcorr compared to males C_LIO_LINon-Hispanic Black adults generally have lower FAFWcorr than non-Hispanic White adults C_LIO_LIAPOE-{varepsilon}4 carriers tended to have higher FW than non-carriers C_LI Research in Context Systematic ReviewThe authors used PubMed and Google Scholar to review literature that used conventional and free-water (FW)-corrected microstructural metrics to evaluate sex, race, and APOE-{varepsilon}4 differences in white matter microstructure. While studies have previously explored differences by sex and APOE-{varepsilon}4 status, less is known about racial differences and no large-scale FW-corrected analysis has been performed. InterpretationSex and race were more associated with FAFWcorr while APOE-{varepsilon}4 status was associated with FW metrics. Association, projection, limbic, and occipital transcallosal tracts showed the greatest differences. Future DirectionFuture studies to determine the biological and social pathways that lead to sex, racial, and APOE-{varepsilon}4 differences are warranted. Consent StatementAll participants provided informed consent in their respective cohort studies.

neuroscience↗

bioRxiv2024

The long-chain fatty acid-CoA ligase FadD1 monitors Pseudomonas aeruginosa quorum sensing as a receptor of cis-2-decenoic acid

Diffusible signal factor (DSF)-family quorum sensing (QS) signals are widely utilized by many bacterial pathogens to modulate various biological functions and virulence. Previous studies showed that cis-2-decenoic acid (cis-DA) is involved in modulation of biofilm dispersion in Pseudomonas aeruginosa, but its signaling mechanism remains vague. Here, we report that cis-DA regulates the physiology and virulence of P. aeruginosa through the long-chain fatty acid-CoA ligase FadD1. Cis-DA specifically binds to FadD1 with high affinity and enhances the binding of FadD1 to the promoter DNA region of lasR. Further analysis showed that the FadD1 is a response regulator of cis-DA with a DNA-binding leucine zipper motif to control the transcription of various target genes. Moreover, FadD1 exhibited catalytic activity on cis-2-dodecenoic acid (BDSF) of Burkholderia cenocepacia and enhanced the competitiveness of P. aeruginosa. Together, our work presents a new DSF-type QS signaling system, which is highlighted by its receptor and response regulator evolved from a canonical enzyme of fatty acid metabolism. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/598097v2_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@66b8aaorg.highwire.dtl.DTLVardef@1e5b9b9org.highwire.dtl.DTLVardef@1043525org.highwire.dtl.DTLVardef@13d3ed1_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsThe long-chain fatty acid-CoA ligase FadD1 acts as a global transcriptional regulator in P. aeruginosa. FadD1 is a receptor of QS signal cis-DA and functions at the top of the QS hierarchy in P. aeruginosa. The homolog of FadD1 in P. fluorescens could bind to the target gene promoter by responding to cis-DA. In briefPseudomonas aeruginosa is a human pathogen with antibiotic resistance and a wide range of dynamic defenses makes it an extremely challenging organism to treat in modern-day medicine. It employs cis-2-decenoic acid (cis-DA) quorum sensing to regulate the physiology and pathogenesis. Song et al. demonstrate that the long-chain fatty acid-CoA ligase FadD1 controls the important biological functions and virulence in P. aeruginosa as a novel response regulator of cis-DA signal.

microbiology↗

bioRxiv2024

Desmosomal Cadherin Tension Loss in Pemphigus Vulgaris Mediated by the Inhibition of Active RhoA at Cell-Cell Adhesions

Binding of autoantibodies to keratinocyte surface antigens, primarily desmoglein 3 (Dsg3) of the desmosomal complex, leads to the dissociation of cell-cell adhesion in the blistering disorder pemphigus vulgaris (PV). After the initial disassembly of desmosomes, cell-cell adhesions actively remodel in association with the cytoskeleton and focal adhesions. Growing evidence highlights the role of adhesion mechanics and mechanotransduction at cell-cell adhesions in this remodeling process, as their active participation may direct autoimmune pathogenicity. However, a large part of the biophysical transformations after antibody binding remains underexplored. Specifically, it is unclear how tension in desmosomes and cell-cell adhesions changes in response to antibodies, and how the altered tensional states translate to cellular responses. Here, we showed a tension loss at Dsg3 using fluorescence resonance energy transfer (FRET)-based tension sensors, a tension loss at the entire cell-cell adhesion, and a potentially compensatory increase in junctional traction force at cell-extracellular matrix adhesions after PV antibody binding. Further, our data indicate that this tension loss is mediated by the inhibition of RhoA at cell-cell contacts, and the extent of RhoA inhibition may be crucial in determining the severity of pathogenicity among different PV antibodies. More importantly, this tension loss can be partially restored by altering actomyosin based cell contractility. Collectively, these findings provide previously unattainable details in our understanding of the mechanisms that govern cell-cell interactions under physiological and autoimmune conditions, which may open the window to entirely new therapeutics aimed at restoring physiological balance to tension dynamics that regulates the maintenance of cell-cell adhesion.

biophysics↗

bioRxiv2024

Chlomito: a novel tool for precise elimination of organelle genome contamination in nuclear genome assemblies

Accurate genome assemblies are crucial for understanding biological evolution, mechanisms of disease, and biodiversity. However, contamination from organelle genomes in nuclear genome analyses often leads to inaccuracies and unreliability in results. To address this issue, we developed a tool named Chlomito, which employs innovative algorithms to precisely identify and eliminate organelle genome contamination sequences from nuclear genome assemblies. Compared to conventional approaches, Chlomito can not only detect and eliminate organelle sequences but also effectively distinguish true organelle sequences from those transferred into the nucleus via horizontal gene transfer. To evaluate the accuracy of Chlomito, we conducted tests using sequencing data from Plum and Mango. The results confirmed that Chlomito can accurately detect contigs originating from the organelle genome, and the identified contigs covered most regions of the organelle reference genomes, demonstrating its efficiency and precision in comprehensively recognizing organelle genome sequences. Additionally, for user convenience, we packaged this method into a Docker image, simplifying the data processing workflow. Overall, Chlomito provides a highly efficient and accurate method for identifying and removing contigs derived from organelle genomes in genomic assembly data, thereby contributing to the improvement of genome assembly quality and advancing research in genomics and evolutionary biology.

bioinformatics↗

bioRxiv2023

Integrative multiomics analysis of neointima proliferation in human saphenous vein: implications for bypass graft disease

IntroductionHuman saphenous veins (SV) are widely used as grafts in coronary artery bypass (CABG) surgery but often fail due to neointima proliferation (NP). NP involves complex interplay between vascular smooth muscle cells (VSMC) and fibroblasts. Little is known, however, regarding the transcriptomic and proteomic dynamics of NP. Here, we performed multi-omics analysis in an ex vivo tissue culture model of NP in human SV procured for CABG surgery. Methods and resultsHistological examination demonstrated significant elastin degradation and NP (indicated by increased neointima area and neointima/media ratio) in SV subjected to tissue culture. Analysis of data from 73 patients suggest that the process of SV adaptation and NP may differ according to sex and body mass index. RNA sequencing confirmed upregulation of pro-inflammatory and proliferation-related genes during NP and identified novel processes, including increased cellular stress and DNA damage responses, which may reflect tissue trauma associated with SV harvesting. Proteomic analysis identified upregulated extracellular matrix-related and coagulation/thrombosis proteins and downregulated metabolic proteins. Spatial transcriptomics detected transdifferentiating VSMC in the intima on the day of harvesting and highlighted dynamic alterations in fibroblast and VSMC phenotype and behavior during NP. Specifically, we identified new cell subpopulations contributing to NP, including SPP1+, LGALS3+ VSMC and MMP2+, MMP14+ fibroblasts. ConclusionDynamic alterations of gene and protein expression occur during NP in human SV. Identification of the human-specific molecular and cellular mechanisms may provide novel insight into SV bypass graft disease.

genomics↗