Biology subjects

Zhou, M.

Publications and source records attributed to Zhou, M..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

A Full Window Data Independent Acquisition Method for DeeperTop-down Proteomics

Top-down proteomics (TDP) is emerging as a vital tool for the comprehensive characterization of proteoforms. However, as its core technology, top-down mass spectrometry (TDMS) still faces significant analytical challenges. While data-independent acquisition (DIA) has revolutionized bottom-up proteomics and metabolomics, they are rarely employed in TDP. The unique feature of protein ions in an electrospray mass spectrum, as well as the data complexity require the development of new DIA strategies. This study introduces a machine learning assisted Full Window DIA (FW-DIA) method that eliminates precursor ion isolation, making it compatible with a wide range of commercial mass spectrometers. Moreover, FW-DIA leverages all precursor protein ions to generate high-quality tandem mass spectra, enhancing signal intensities by [~]50-fold and protein sequence coverage by threefold in a modular protein analysis. The method was successfully applied to the analysis of a five-protein mixture under native conditions and Escherichia coli ribosomal proteoform characterization.

bioinformatics↗

bioRxiv2024

Single-Cell Antigen Receptor Sequencing in Pigs with Influenza

Understanding the pulmonary adaptive immune system of pigs is important as respiratory pathogens present a major challenge for swine producers and pigs are increasingly used to model human pulmonary diseases. Single-cell RNA sequencing (scRNAseq) has accelerated the characterization of cellular phenotypes in the pig respiratory tract under both healthy and diseased conditions. However, combining scRNAseq with recovery of paired T cell receptor (TCR) and {beta} chains as well as B cell receptor (BCR) heavy and light chains to interrogate their repertoires has not to our knowledge been demonstrated for pigs. Here, we developed primers to enrich porcine TCR and {beta} chains along with BCR {kappa} and {lambda} light chains and IgM, IgA, and IgG heavy chains that are compatible with the 10x Genomics VDJ sequencing protocol. Using these pig-specific assays, we sequenced the T and B cell receptors of cryopreserved lung cells from CD1D-expressing and -deficient pigs after one or two infections with influenza A virus (IAV) to examine whether natural killer T (NKT) cells alter pulmonary TCR and BCR repertoire selection. We also performed paired single-cell RNA and receptor sequencing of FACS-sorted T cells longitudinally sampled from the lungs of IAV-vaccinated and -infected pigs to track clonal expansion in response to IAV exposure. All pigs presented highly diverse repertoires. Pigs re-exposed to influenza antigens from either vaccination or infection exhibited higher numbers of expanded CD4 and CD8 T cell clonotypes with activated phenotypes, suggesting potential IAV reactive T cell populations. Our results demonstrate the utility of high throughput single-cell TCR and BCR sequencing in pigs.

immunology↗

bioRxiv2024

PRC2 facilitates the transition from heterotrophy to photoautotrophy during seedling emergence

Seed-to-seedling transition represents a key developmental and metabolic switch in plants. Catabolism of seed storage reserves fuels germination and early seedling emergence until photosynthesis is established. The developmental transition is controlled by Polycomb repressive complex 2 (PRC2). However, the coordination of PRC2 activity and its contribution to transcriptional reprogramming during seedling establishment is unknown. By analysing the re-distribution of H3K27me3 and changes in gene transcription in shoot and root tissues of heterotrophic and photoautotrophic seedlings, we reveal two phases of PRC2-mediated gene repression. The first phase is independent of light and photosynthesis and results in irreversible repression of the embryo maturation programme, marked by heterotrophy and biosynthesis of reserve storage molecules. The second phase is associated with the repression of metabolic pathways related to germination and early seedling emergence, and H3K27me3 deposition in this phase is sensitive to photosynthesis inhibition. We show that preventing transcription of the PRC2-repressed glyoxylate cycle gene ISOCITRATE LYASE is sufficient to drive the vegetative phase transition in PRC2-depleted plants. This underscores a key role of PRC2 repression in the coordinated metabolic and developmental switches during seedling emergence and emphasizes the close connection between metabolic and developmental identities.

plant biology↗

bioRxiv2024

Inconsistencies in the published rabbit ribosomal rRNAs: a proposal for uniformity in sequence and site numbering

Examination of all publicly available Oryctolagus cuniculus (rabbit) ribosome cryo-EM structures reveals numerous confusing inconsistencies. First, there are a plethora of single nucleotide differences among the various rabbit 28S and 18S rRNA structures. Second, two nucleotides are absent from the NCBI Reference Sequence for the 18S rRNA gene. Moving forward, we propose using the Broad Institutes rabbit whole genome shotgun sequence and numbering to reduce modeling ambiguity and improve consistency between ribosome models.

biophysics↗

bioRxiv2024

An optimized pipeline for high-throughput bulk RNA-Seq deconvolution illustrates the impact of obesity and weight loss on cell composition of human adipose tissue

Cellular heterogeneity of human adipose tissue, is linked to the pathophysiology of obesity and may impact the response to energy restriction and changes in fat mass. Here, we provide an optimized pipeline to estimate cellular composition in human abdominal subcutaneous adipose tissue (ASAT) from publicly available bulk RNA-Seq using signature profiles from our previously published full-length single nuclei (sn)RNA-Seq of the same depot. Individuals with obesity had greater proportions of macrophages and lower proportions of adipocyte sub-populations and vascular cells compared with lean individuals. Two months of diet-induced weight loss (DIWL) increased the estimated proportions of macrophages; however, two years of DIWL reduced the estimated proportions of macrophages, thereby suggesting a bi-phasic nature of cellular remodeling of ASAT during weight loss. Our optimized high-throughput pipeline facilitates the assessment of composition changes of highly characterized cell types in large numbers of ASAT samples using low-cost bulk RNA-Seq. Our data reveal novel changes in cellular heterogeneity and its association with cardiometabolic health in humans with obesity and following weight loss. Lead contactKatie Whytock (Katie.Whytock@adventhealth.com)

physiology↗

bioRxiv2024

Phosphorylation-induced SUMOylation promotes Ulk4 condensation at ciliary tip to transduce Hedgehog signal

Hedgehog (Hh) signaling controls embryonic development and adult tissue homeostasis through the Gli family of transcription factors. In vertebrates, Hh signal transduction depends on the primary cilium where Gli is thought to be activated at the ciliary tip, but the underlying mechanism has remained poorly understood. Here we provide evidence that two Unc-51-like kinase (Ulk) family members Stk36 and Ulk4 regulate Gli2 ciliary tip localization and activation through phosphorylation and SUMOylation-mediated condensation in response to Shh. We find that Stk36-mediated phosphorylation of Ulk4 promotes its SUMOylation in response to Shh, and the subsequent interaction between SUMO and a SUMO-Interacting-Motif (SIM) in the C-terminal region of Ulk4 drives Ulk4 self-assembly to form biomolecular condensates that also recruit Stk36 and Gli2. SUMOylation or SIM-deficient Ulk4 failed to accumulate at ciliary tip to activate Gli2 whereas phospho-mimetic mutation of Ulk4 sufficed to drive Ulk4/Stk36/Gli2 condensation at ciliary tip, leading to constitutive Shh pathway activation in a manner dependent on Ulk4 SUMOylation. Taken together, our results suggest that phosphorylation-dependent SUMOylation of Ulk4 promotes kinase-substrate condensation at ciliary tip to transduce the Hh signal.

cell biology↗

bioRxiv2024

Cancer Interception During Treatment: Using Growth Kinetics to Create a Continuous Variable for Assessing Disease Response

BackgroundWe applied 11 mathematical models of tumor growth to clinical trial data available from public and private sources. We have previously described the remarkable capacity for a simple biexponential model of tumor growth to fit thousands of datasets, and to correlate with overall survival. The goal of this study was to extend our analysis to additional tumor types and to evaluate whether alternate growth models could describe the time course of disease burden in the small subset of patients in whom the biexponential model failed. MethodsFor this analysis, we obtained data for tumor burden from 17,140 patients with six different tumor types. Imaging data and serum levels of tumor markers were available for 3,346 and 13,794 patients, respectively. Data from patients were first analyzed using the biexponential model to determine rates of tumor growth (g) and regression (d); for those whose data could not be described by this model, fit of their data was assessed using seven alternative models. The model that minimized the Akaike Information Criterion was selected as the best fit. Using the model that best fit an individual patients data, we estimated the rates of growth (g) and regression (d) of disease burden over time. The rates of tumor growth (g) were examined for association with a traditional endpoint (overall survival). FindingsFor each model, the number of patient datasets that fit the model were obtained. As we have previously reported, data from most patients fit a simple model of exponential growth and exponential regression (86%). Data from another 7% of patients fit an alternative model, including 3% fitting to a model of constant or linear regression and exponential growth of tumor on the surface and 3% fitting to model of exponential decay on tumor surface with asymmetric growth. As previously reported, we found that growth rate correlates well with overall survival, remarkably even when data from various histologies are considered together. For patients with multiple timepoints of tumor measurement, the growth rate could often be estimated even during the phase when only net regression of tumor quantity could be discerned. InterpretationThe validation of a simple mathematical model across different cancers and its application to existing clinical data allowed estimation of the rate of growth of a treatment resistant subpopulation of cancer cells. The quantification of available clinical data using the growth rate of tumors in individual patients and its strong correlation with overall survival makes the growth rate an excellent marker of the efficacy of therapy specific to the individual patient.

cancer biology↗

bioRxiv2024

Phytop: A tool for visualizing and recognizing signals of incomplete lineage sorting and hybridization using species trees output from ASTRAL

Incomplete lineage sorting (ILS) and introgression/hybridization (IH) is prevalent in nature and thus frequently result in discrepancies within phylogenetic tree topologies, leading to misinterpretation of phylogenomic data. Despite the availability of numerous tools for detecting ILS and IH among species, many of these tools are lacking effective visualization, or are time-consuming, or require prior predetermination. Here, we addressed these shortcomings by developing a fast-running, user-friendly tool called Phytop. By defining ILS and IH indices to quantify ILS and IH, this tool can detect the extent of ILS and IH among lineages with high reliability, and can visualize them based on the gene tree topology patterns constructed using ASTRAL. We tested Phytop extensively using both simulated and real data, and found that it enables users to quickly and conveniently estimate the extent of ILS and IH, thus clarifying the phylogenetic uncertainty. Phytop is available at https://github.com/zhangrengang/phytop and is expected to conveniently contribute to the intuitive inference of genetic relationships among lineages in future research.

bioinformatics↗

bioRxiv2024

Single-cell analysis of the somatic mutational landscape in human chondrocytes during aging and in osteoarthritis

Somatic mutation is now recognized as a cause of multiple human diseases other than cancer. Osteoarthritis (OA), a highly prevalent age-related disease, has been associated with increased chromosomal abnormalities in articular cartilage of OA patients. Thus far no systematic attempt has been made to characterize the somatic mutational landscape of chondrocytes during normal aging and in affected cartilage of OA patients. Here we used single-cell whole genome sequencing to quantitatively analyze single-nucleotide variants (SNVs) and small insertions and deletions (InDels) in 100 single chondrocytes isolated from the cartilage of hip femoral heads of 17 subjects aged from 26 to 90 years, including 9 OA patients and 8 non-OA donors. Both SNVs and InDels were found to accumulate with age in chondrocytes with a clock-like mutational signature. Surprisingly, the age-related accumulation rate of these mutations was found to be lower in OA chondrocytes compared with chondrocytes from non-OA control subjects.

genomics↗

bioRxiv2024

Chickpea NCR13 disulfide cross-linking variants exhibit profound differences in antifungal activity and modes of action

Small cysteine-rich antifungal peptides with multi-site modes of action (MoA) have potential for development as biofungicides. In particular, legumes of the inverted-repeat lacking clade express a large family of nodule-specific cysteine-rich (NCR) peptides that orchestrate differentiation of nitrogen-fixing bacteria into bacteroids. These NCRs can form 2 or 3 intramolecular disulfide bonds and a subset of these peptides with high cationicity exhibits antifungal activity. However, the importance of intramolecular disulfide pairing and MoA against fungal pathogens for most of these plant peptides remains to be elucidated. Our study focused on a highly cationic chickpea NCR13, which has a net charge of +9 and contains six cysteines capable of forming three disulfide bonds. NCR13 expression in Pichia pastoris resulted in formation of two peptide folding variants, NCR13_PFV1 and NCR13_PFV2, that differed in the pairing of two out of three disulfide bonds despite having an identical amino acid sequence. The NMR structure of each PFV revealed a unique three-dimensional fold with the PFV1 structure being more compact but less dynamic. Surprisingly, PFV1 and PFV2 differed profoundly in the potency of antifungal activity against several fungal plant pathogens and their multi-faceted MoA. PFV1 showed significantly faster fungal cell-permeabilizing and cell entry capabilities as well as greater stability once inside the fungal cells. Additionally, PFV1 was more effective in binding fungal ribosomal RNA and inhibiting protein translation in vitro. Furthermore, when sprayed on pepper and tomato plants, PFV1 was more effective in reducing disease symptoms caused by Botrytis cinerea, causal agent of gray mold disease in fruits, vegetables and flowers. In conclusion, our work highlights the significant impact of disulfide pairing on the antifungal activity and MoA of NCR13 and provides structural framework for design of novel, potent antifungal peptides for agricultural use. Author SummaryFungal pathogens cause significant pre-harvest and post-harvest losses of crop yield, making them a serious biological threat to global food security. Chemical fungicides are effective in controlling fungal diseases across various crops. However, rapid evolution of fungal pathogen resistance to single-site chemical fungicides in agriculture has created an urgent need for development of safe, sustainable, and cost-effective multi-site fungicides. Nodule-specific cysteine-rich (NCR) peptides expressed in the inverted-repeat lacking clade legume plants exhibit potent antifungal activity; however, their modes of action (MoA) are poorly understood. Particularly, the specific contribution of disulfide pairing to the potency and spectrum of antifungal activity against fungal plant pathogens and MoA of these peptides remains to be identified. Chickpea NCR13 expressed in P. pastoris generates two peptide variants that differ in their disulfide cross-linking pattern. These variants exhibit striking differences in their three-dimensional structures and potency of antifungal activity against multiple fungal pathogens and MoA. They also differ in their ability to confer resistance to gray mold in pepper and tomato plants. Our study highlights the major impact a specific pattern of disulfide pairing can have on the in vitro and in planta antifungal activity of an NCR peptide.

plant biology↗

bioRxiv2024

Celastrol binds to pyruvate kinase and imitates the metabolic reprogramming of ATP

ATP is the final product of glycolysis and the TCA cycle. However, the counter-regulation of glycosis and TCA by ATP is poorly understood. Here we show that ATP analog celastrol (CLT) binds to the ATP binding pocket on pyruvate kinase PKM (PKM) while inducing allosteric regulation of PKM. Quantum calculation predicts hydrogen bond formation between CLT and asparagine. Liquid chromatography-mass spectrometry further identifies PKM as CLTs target. The inhibition of PKM is stronger and longer for CLT while weak and short for ATP. Notably, CLT-PKM interaction perfectly underlies the hypoglycemic effects by forming glucose carbon flux U turn before PKM. Besides, the PKM allostery induces a tricarboxylic acid (TCA) vortex which could promote amino acid and lipid degradation as the energy compensation, leading to a significant weight loss. Additionally, CLT exerts efficient antioxidant effects by altering the glucose flux to strengthen the pentose phosphate pathway. Consequently, the CLT-PKM interaction vividly reproduces the ATP-PKM interaction named "ATP resistance" in the diabetes pathogenesis.

pharmacology and toxicology↗

bioRxiv2024

Episodic Transport of Protein Aggregates Achieves a Positive Size Selectivity in Aggresome Formation

Eukaryotic cells direct toxic misfolded proteins to various protein quality control pathways based on their chemical features and aggregation status. Aggregated proteins are targeted to selective autophagy or specifically sequestered into the "aggresome," a perinuclear inclusion at the microtubule-organizing center (MTOC). However, the mechanism for selectively sequestering protein aggregates into the aggresome remains unclear. To investigate aggresome formation, we reconstituted MTOC-directed aggregate transport in Xenopus laevis egg extract using AgDD, a chemically inducible aggregation system. High-resolution single-particle tracking revealed that dynein-mediated transport of aggregates was highly episodic, with average velocity positively correlated with aggregate size. Our mechanistic model suggests that the recurrent formation of the dynein transport complex biases larger aggregates towards the active transport state, compensating for the slowdown due to viscosity. Both episodic transport and positive size selectivity are specifically associated with aggresome-dynein adaptors. Coupling conventional dynein-activating adaptors to the aggregates perturbs aggresome formation and reverses size selectivity.

cell biology↗

bioRxiv2024

Optimization of gene knockout approaches and practical solutions to sgRNA selection challenges in hPSCs with inducible Cas9 system

RationaleCRISPR/Cas9 has been extensively used to knock out genes, allowing the study of genetic loss-of-function in human pluripotent stem cells (hPSCs). However, the current use of the Cas9-sgRNA plasmid or iCas9 system for gene editing in hPSCs has resulted in limited and inconsistent editing efficiency, as well as labor-intensive work. Additionally, identifying single-guide RNAs (sgRNAs) with high cleavage efficiency and distinguishing them from ineffective ones, which efficiently induce frameshift INDELs (Indels and Deletions) but fail to eliminate target proteins expression, are major challenges in gene knockout experiments. MethodsThis study addresses above issues using an optimized doxycycline-induced spCas9-expressing hPSCs (hPSCs-iCas9) system. We initially developed this system by optimizing a number of parameters to maximize INDELs introducing efficiency in hPSCs-iCas9 cells. The INDELs determined by this system were then compared to predicted scores from three cleavage efficiency scoring algorithms to validate the algorithms accuracy and consistency. Furthermore, we conducted gene knockout using a set of sgRNAs targeting different exons of the ACE2 gene to achieve approximately 80% INDELs for each targeting locus. Western blotting was then performed to detect ACE2 protein expression levels, enabling the identification of potentially ineffective sgRNAs. ResultsSeveral critical factors, including cell tolerance to nucleofection stress, sgRNA stability, nucleofection frequency, and the cell-to-sgRNA ratio, were found to have significant impact on editing efficiency in hPSCs-iCas9. Fine-tuning these parameters markedly improved this efficiency, resulting in up to 93% INDELs for single gene knockout. The three scoring algorithms exhibited significant differences or even conflicts in scoring cleavage efficiency. Through comparing experimental observations to predicted scores, we discovered that the Benchling algorithm outperformed the other two in terms of accuracy and consistency. Furthermore, a sgRNA targeting exon 2 of ACE2 gene was quickly identified as ineffective, as evidenced by the edited cells pool containing 80% INDELs while ACE2 protein expression retained unchanged detected by Western blot. ConclusionThe findings of this study offer valuable insights into the optimal design of gene knockout experiments in hPSCs and provide practical solutions to sgRNA selection challenges for gene editing.

cell biology↗

bioRxiv2024

Native mass spectrometry of membrane protein-lipid interactions in different detergent environments

Native mass spectrometry (MS) is revealing the role of specific lipids in modulating membrane protein structure and function. Membrane proteins solubilized in detergents are often introduced into the mass spectrometer; however, commonly used detergents for structural studies, such as dodecylmaltoside, tend to generate highly charged ions, leading to protein unfolding, thereby diminishing their utility for characterizing protein-lipid interactions. Thus, there is a critical need to develop approaches to investigate protein-lipid interactions in different detergents. Here, we demonstrate how charge-reducing molecules, such as spermine and trimethylamine-N-oxide, enable characterization of lipid binding to the bacterial water channel (AqpZ) and ammonia channel (AmtB) in complex with regulatory protein GlnK in different detergent environments. We find protein-lipid interactions are not only protein-dependent but can also be influenced by the detergent and type of charge-reducing molecule. AqpZ-lipid interactions are enhanced in LDAO (n-dodecyl-N,N-dimethylamine-N-oxide), whereas the interaction of AmtB-GlnK with lipids is comparable among different detergents. A fluorescent lipid binding assay also shows detergent dependence for AqpZ-lipid interactions, consistent with results from native MS. Taken together, native MS will play a pivotal role in establishing optimal experimental parameters that will be invaluable for various applications, such as drug discovery, as well as biochemical and structural investigations.

biochemistry↗

bioRxiv2024

GLARE: DISCOVERING HIDDEN PATTERNS IN SPACEFLIGHT TRANSCRIPTOME USING REPRESENTATION LEARNING

AO_SCPLOWBSTRACTC_SCPLOWSpaceflight studies present novel insights into biological processes through exposure to stressors outside the evolutionary path of terrestrial organisms. Despite limited access to space environments, numerous transcriptomic datasets from spaceflight experiments are now available through NASAs GeneLab data repository, which allows public access to these datasets, encouraging further analysis. While various computational pipelines and methods have been used to process these transcriptomic datasets, learning-model-driven analyses have yet to be applied to a broad array of such spaceflight-related datasets. In this study, we propose an open-source pipeline, GLARE: GeneLAb Representation learning pipelinE, which consists of training different representation learning approaches from manifold learning to self-supervised learning that enhance the performance of downstream analytical tasks. We illustrate the utility of GLARE by applying it to gene-level transcriptional values from the results of the CARA spaceflight experiment, an Arabidopsis root tip transcriptome dataset that spanned light, dark, and microgravity treatments. We show that GLARE not only substantiated the findings of the original study concerning cell wall remodeling but also revealed additional patterns of gene expression affected by the treatments, including evidence of hypoxia. This work suggests there is great potential to supplement the insights drawn from initial studies on spaceflight omics-level data through further machine-learning-enabled analyses.

plant biology↗

bioRxiv2024

Fungal pathogens exposed - genomic and phenotypic insights into Candida auris and its relatives of the Candida haemulonii species complex

Candida auris showed the world the ability of fungi to rapidly emerge as an urgent threat to public health. Close relatives of the Candida haemulonii complex exhibit also a similar multi-drug resistant nature and are increasingly reported as nosocomial pathogens. Here, we analyze both complete genomes assemblies and extensive phenotypic data for the five C. auris clades and pathogenic and non-pathogenic species related to the C. haemulonii species complex. First, we resolved the phylogeny of the species complex. Next, comparing C. auris to its pathogenic and non-pathogenic relatives we identified a pathogenic potential for the whole C. haemulonii species complex by shared gene content and phenotypic traits linked to drug resistance and virulence. In vivo virulence assays using the Galleria mellonella fungal infection model show that C. auris strains are significantly more virulent than any of the sibling species in the C. haemulonii complex. Phenotypic analysis links the increased virulence of C. auris to a more stress resistant phenotype compared to its siblings.

microbiology↗

bioRxiv2024

Accelerated growth increases the somatic epimutation rate in trees

Trees are critical components of ecosystems and of major economic importance. Due to their extraordinary longevity and well-defined modular architecture they have also emerged as model systems to study the long-term accumulation of somatic mutations in plants. Coupled with retrospective life-history and environmental data, trees can offer unique insights into mutational processes that would be difficult to obtain with prospective studies. In addition to genetic mutations, somatic epimutations in the form of stochastic gains and losses of DNA cytosine methylation have been shown to accumulate rapidly during ontogeny. One hypothesis is that somatic epimutations originate from DNA methylation maintenance errors during mitotic cell divisions, which would predict that their rate of accumulation scales with growth rate, rather than with age. Here we test this hypothesis in European beech. We analyzed one of the oldest continuously measured experimental plots in the world. The plot contains an even-aged beech stand that was established in 1822 and monitored for growth at regular intervals until the present. Starting [~]150 years ago, alternative thinning strategies were applied to subplots of this experiment, resulting in differential stem growth rates among trees. We show that accelerated growth significantly increased the per-year somatic epimutation rate at CG dinucleotides, and that this effect is accompanied by differences in cell division rates. Hence, faster growth elevates the chances for methylation maintenance errors during DNA replication per unit time. As somatic CG epimutations can be stably inherited to subsequent generations in plants, our insights have direct ecological and evolutionary implications.

genomics↗

bioRxiv2024

LaGrACE: Estimating gene program dysregulation using latent gene regulatory network for biomedical discovery

Gene expression programs that establish and maintain specific cellular states are orchestrated through a regulatory network composed of transcription factors, cofactors, and chromatin regulators. Dysregulation of this network can lead to a broad range of diseases by altering gene programs. This article presents LaGrACE, a novel method designed to estimate dysregulation of gene programs utilizing omics data with clinical information. This approach facilitates grouping of samples exhibiting similar patterns of gene program dysregulation, thereby enhancing the discovery of underlying molecular mechanisms. We rigorously evaluated LaGrACEs performance using synthetic data, bulk RNA-seq clinical datasets (breast cancer, chronic obstructive pulmonary disease (COPD)), and single-cell RNA-seq drug perturbation datasets. Our findings demonstrate that LaGrACE is exceptionally robust in identifying biologically meaningful and prognostic molecular subtypes. Additionally, it effectively discerns drug-response signals at a single-cell resolution. Moreover, the COPD analysis revealed a new association between LEF1 and COPD molecular mechanisms and mortality. Collectively, these results underscore the utility of LaGrACE as a valuable tool for elucidating underlying mechanisms of diseases.

bioinformatics↗