Biology subjects

Ji, Z.

Publications and source records attributed to Ji, Z..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Reference-free and cost-effective automated cell type annotation with GPT-4 in single-cell RNA-seq analysis

Cell type annotation is an essential step in single-cell RNA-seq analysis. However, it is a time-consuming process that often requires expertise in collecting canonical marker genes and manually annotating cell types. Automated cell type annotation methods typically require the acquisition of high-quality reference datasets and the development of additional pipelines. We assessed the performance of GPT-4, a highly potent large language model, for cell type annotation, and demonstrated that it can automatically and accurately annotate cell types by utilizing marker gene information generated from standard single-cell RNA-seq analysis pipelines. Evaluated across hundreds of tissue types and cell types, GPT-4 generates cell type annotations exhibiting strong concordance with manual annotations and has the potential to considerably reduce the effort and expertise needed in cell type annotation. We also developed GPTCelltype, an open-source R software package to facilitate cell type annotation by GPT-4.

bioinformatics↗

bioRxiv2023

Identification of the glycosylphosphatidylinositol-specific phospholipase A2 (GPI-PLA2) of GPI fatty acid remodelling in Trypanosoma brucei

The biosynthesis of glycosylphosphatidylinositol (GPI) anchored proteins (GPI-APs) in the parasitic protozoan Trypanosoma brucei involves fatty acid remodelling of the GPI precursor molecules before they are transferred to protein in the endoplasmic reticulum. The genes encoding the requisite phospholipase A2 and A1 activities for this remodelling have thus far been elusive. Here, we identify a gene, Tb927.7.6110, that encodes a protein that is necessary and sufficient for GPI-phospholipase A2 (GPI-PLA2) activity in the procyclic form of the parasite. The predicted protein product belongs to the alkaline ceramidase, PAQR receptor, Per1, SID-1, and TMEM8 (CREST) superfamily of transmembrane hydrolase proteins and shows sequence similarity to Post-GPI-Attachment to Protein 6 (PGAP6), a GPI-PLA2 that acts after transfer of GPI precursors to protein in mammalian cells. The trypanosome Tb927.7.6110 GPI-PLA2 gene resides in a locus with two closely related genes Tb927.7.6150 and Tb927.7.6170, one of which (Tb927.7.6150) most likely encodes a catalytically inactive protein. The absence of GPI-PLA2 in the null mutant procyclic cells not only affected fatty acid remodelling but also reduced GPI anchor sidechain size on mature GPI-anchored procyclin glycoproteins. This reduction in GPI anchor sidechain size was reversed upon the add back of Tb927.7.6110 and of Tb927.7.6170, despite the latter not encoding GPI precursor GPI-PLA2 activity.

biochemistry↗

bioRxiv2023

Integrating multiple single-cell multi-omics samples with Smmit

Multi-sample single-cell multi-omics datasets, which simultaneously measure multiple data modalities in the same cells across multiple samples, facilitate the study of gene expression, gene regulatory activities, and protein abundances on a population scale. We developed Smmit, a computational method for integrating data both across samples and modalities. Compared to existing methods, Smmit more effectively removes batch effects while preserving relevant biological information, resulting in superior integration outcomes. Additionally, Smmit is more computationally efficient and builds upon existing computational pipelines, requiring minimal effort for implementation. Smmit is an R software package that is freely available on Github: https://github.com/zji90/Smmit.

bioinformatics↗

bioRxiv2023

Distinct Myeloid Derived Suppressor Cell Populations Promote Tumor Aggression in Glioblastoma

The diversity of genetic programs and cellular plasticity of glioma-associated myeloid cells, and thus their contribution to tumor growth and immune evasion, is poorly understood. We performed single cell RNA-sequencing of immune and tumor cells from 33 glioma patients of varying tumor grades. We identified two populations characteristic of myeloid derived suppressor cells (MDSC), unique to glioblastoma (GBM) and absent in grades II and III tumors: i) an early progenitor population (E-MDSC) characterized by strong upregulation of multiple catabolic, anabolic, oxidative stress, and hypoxia pathways typically observed within tumor cells themselves, and ii) a monocytic MDSC (M-MDSC) population. The E-MDSCs geographically co-localize with a subset of highly metabolic glioma stem-like tumor cells with a mesenchymal program in the pseudopalisading region, a pathognomonic feature of GBMs associated with poor prognosis. Ligand-receptor interaction analysis revealed symbiotic cross-talk between the stemlike tumor cells and E-MDSCs in GBM, whereby glioma stem cells produce chemokines attracting E-MDSCs, which in turn produce growth and survival factors for the tumor cells. Our large-scale single-cell analysis elucidated unique MDSC populations as key facilitators of GBM progression and mediators of tumor immunosuppression, suggesting that targeting these specific myeloid compartments, including their metabolic programs, may be a promising therapeutic intervention in this deadly cancer. One-Sentence SummaryAggressive glioblastoma harbors two unique myeloid populations capable of promoting stem-like properties of tumor cells and suppressing T cell function in the tumor microenvironment.

immunology↗

bioRxiv2023

GeneTuring tests GPT models in genomics

Large language models (LLMs) show promise in biomedical research, but their effectiveness for genomic inquiry remains unclear. We developed GeneTuring, a benchmark consisting of 16 genomics tasks with 1,600 curated questions, and manually evaluated 48,000 answers from ten LLM configurations, including GPT-4o (via API, ChatGPT with web access, and a custom GPT setup), GPT-3.5, Claude 3.5, Gemini Advanced, GeneGPT (both slim and full), BioGPT, and BioMedLM. A custom GPT-4o configuration integrated with NCBI APIs, developed in this study as SeqSnap, achieved the best overall performance. GPT-4o with web access and GeneGPT demonstrated complementary strengths. Our findings highlight both the promise and current limitations of LLMs in genomics, and emphasize the value of combining LLMs with domain-specific tools for robust genomic intelligence. GeneTuring offers a key resource for benchmarking and improving LLMs in biomedical research. Biographical NoteDr. Wenpin Hou is an Assistant Professor (tenure-track) in the Department of Biostatistics at Columbia University and member of its Data Science Institute, developing AI and statistical methods for decoding gene regulatory programs from single-cell and spatial multiomics data.

bioinformatics↗

bioRxiv2023

Path integration selectively predicts midlife risk of Alzheimer's disease

The entorhinal cortex (EC) is the first cortical region to exhibit neurodegeneration in Alzheimers disease (AD), associated with EC grid cell dysfunction. Given the role of grid cells in path integration, we predicted that path integration impairment would represent the first behavioural change in adults at-risk of AD. Using immersive virtual reality, we found that midlife path integration impairments predicted both hereditary and physiological AD risk, with no corresponding impairment on tests of episodic memory or other spatial behaviours. Impairments related to poorer angular estimation and were associated with hexadirectional grid-like fMRI signal in the posterior-medial EC. These results indicate that altered path integration may represent the transition point from at-risk state to disease onset in AD, prior to impairment in other cognitive domains.

neuroscience↗

bioRxiv2023

ZMYM2 controls transposable element transcription through distinct co-regulatory complexes.

ZMYM2 is a zinc finger transcriptional regulator that plays a key role in promoting and maintaining cell identity. It has been implicated in several diseases such as congenital anomalies of the kidney where its activity is diminished and cancer where it participates in oncogenic fusion protein events. ZMYM2 is thought to function through promoting transcriptional repression and here we provide more evidence to support this designation. Here we studied ZMYM2 function in human cells and demonstrate that ZMYM2 is part of distinct chromatin-bound complexes including the established LSD1-CoREST-HDAC1 corepressor complex. We also identify new functional and physical interactions with ADNP and TRIM28/KAP1. The ZMYM2-TRIM28 complex forms in a SUMO-dependent manner and is associated with repressive chromatin. ZMYM2 and TRIM28 show strong functional similarity and co-regulate a large number of genes. However, there are no strong links between ZMYM2-TRIM28 binding events and nearby individual gene regulation. Instead, ZMYM2-TRIM28 appears to regulate genes in a more regionally defined manner within TADs where it can directly regulate co-associated retrotransposon expression. We find that different types of ZMYM2 binding complex associate with and regulate distinct subclasses of retrotransposons, with ZMYM2-ADNP complexes at SINEs and ZMYM2-TRIM28 complexes at LTR elements. We propose a model whereby ZMYM2 acts directly through retrotransposon regulation, which may then potentially affect the local chromatin environment and associated coding gene expression. Genome browser sessionUCSC browser session containing the peak tracks: http://genome.ucsc.edu/cgi-bin/hgTracks?db=hg19&position=chr1:18,078,462-18,084,961&hide=all&hgct_customText=http://bartzabel.ls.manchester.ac.uk/sharrockslab/yaoyong/ZNF198/index_file_hg19_chipSeq_ZMYM2_final.txt Original ChIP-seq and ATAC-seq data from U2OS cells can be viewed On ArrayExpress at: E-MTAB-12292 (ADNP and TRIM28 ChIP-seq), E-MTAB-12293 (SUMO ChIP-seq) and E-MTAB-12294 (ATAC-seq)

molecular biology↗

bioRxiv2022

DNA methylation entropy is associated with DNA sequence featuresand developmental epigenetic divergence

Epigenetic information defines tissue identity and is largely inherited in development through DNA methylation. While studied mostly for mean differences, methylation also encodes stochastic change, defined as entropy in information theory. Analyzing allelespecific methylation in 48 human tissue sample datasets, we find that methylation entropy is associated with specific DNA binding motifs, regulatory DNA, and CpG density. Then applying information theory to 42 mouse embryo methylation datasets, we find that time- and tissue-specific patterns of development are more strongly correlated with methylation entropy than with mean, and methylation entropy is associated with sequence and chromatin features conserved with human. Moreover, methylation entropy is directly related to gene expression variability in development, suggesting a role for epigenetic entropy in developmental plasticity.

genomics↗

bioRxiv2022

GeneSegNet: A deep learning framework for cell segmentation by integrating gene expression and imaging

When analyzing data from in situ RNA detection technologies, cell segmentation is an essential step in identifying cell boundaries, assigning RNA reads to cells, and studying the gene expression and morphological features of cells. We developed a deep-learning-based method, GeneSegNet, that integrates both gene expression and imaging information to perform cell segmentation. GeneSegNet also employs a recursive training strategy to deal with noisy training labels. We show that GeneSegNet significantly improves cell segmentation performances over existing methods that either ignore gene expression information or underutilize imaging information.

bioinformatics↗

bioRxiv2022

Lung tumor-infiltrating Treg have divergent transcriptional profiles and function linked to checkpoint blockade response

Regulatory T cells (Treg) are conventionally viewed to suppress endogenous and therapyinduced anti-tumor immunity; however, their role in modulating responses to immune checkpoint blockade (ICB) is unclear. In this study, we integrated single-cell RNAseq/TCRseq of >73,000 tumor-infiltrating Treg (TIL-Treg) from anti-PD-1-treated and treatment naive non-small cell lung cancers (NSCLC) with single cell analysis of tumor-associated antigen (TAA)-specific Treg derived from a murine tumor model. We identified 10 subsets of human TIL-Treg, most of which have high concordance with murine TIL-Treg subsets. Notably, one subset selectively expresses high levels of OX40 and GITR, whose engangement by cognate ligand mediated proliferative programs and NF-kB activation, as well as multiple genes involved in Treg suppression, in particular LAG3. Functionally, the OX40hiGITRhi subset in the most highly suppressive ex vivo and Treg expression of OX40, GITR and LAG3, correlated with resistance to PD-1 blockade. Surprisingly, in the murine tumor model, we found that virtually all TIL-Treg expressing T cell receptors that are specific for TAA fully develop a distinct Th1-like signature over a two-week period after entry into the tumor, down-regulating FoxP3 and up-regulating expression of TBX21 (Tbet), IFN{gamma} and certain pro-inflammatory granzymes. Application of a gene score from the murine TAA-specific Th1-like Treg subset to the human single-cell dataset revealed a highly analogous subcluster that was enriched in anti-PD-1 responding tumors. These findings demonstrate that TIL-Treg partition into multiple distinct transcriptionally-defined subsets with potentially opposing effects on ICB-induced anti-tumor immunity and suggest that TAA-specific TIL-Treg may positively contribute to anti-tumor responses. One-Sentence SummaryWe define 10 subsets of lung cancer-infiltrating regulatory T cells, one of which is highly suppressive and enriched in anti-PD-1 non-responders and the other is Th1-like and is enriched in PD-1 responders.

immunology↗

bioRxiv2022

Firing rate adaptation in continuous attractor neural networks accounts for theta phase shift of hippocampal place cells

Hippocampal place cells in freely moving rodents display both theta phase precession and procession, which is thought to play important roles in cognition, but the neural mechanism for producing theta phase shift remains largely unknown. Here we show that firing rate adaptation within a continuous attractor neural network causes the neural activity bump to oscillate around the external input, resembling theta sweeps of decoded position during locomotion. These forward and backward sweeps naturally account for theta phase precession and procession of individual neurons, respectively. By tuning the adaptation strength, our model explains the difference between "bimodal cells" showing interleaved phase precession and procession, and "unimodal cells" in which phase precession predominates. Our model also explains the constant cycling of theta sweeps along different arms in a T-maze environment, the speed modulation of place cells firing frequency, and the continued phase shift after transient silencing of the hippocampus. We hope that this study will aid an understanding of the neural mechanism supporting theta phase coding in the brain.

neuroscience↗

bioRxiv2022

CRISPR/FnCas12a-mediated efficient multiplex and iterative genome editing in bacterial plant pathogens without donor DNA templates

CRISPR-based genome editing technology is revolutionizing prokaryotic research, but it has been rarely studied in bacterial plant pathogens. Here, we have developed a targeted genome editing method with no requirement of donor templates for convenient and efficient gene knockout in Xanthomonas oryzae pv. oryzae (Xoo), one of the most important bacterial pathogens on rice, by employing the heterogenous CRISPR/Cas12a from Francisella novicida and NHEJ proteins from Mycobacterium tuberculosis. FnCas12a nuclease generated both small and large DNA deletions at the target sites as well as it enabled multiplex genome editing, gene cluster deletion and plasmid cure in the Xoo PXO99A strain. Accordingly, a non-TAL effector-free polymutant strain PXO99AD25E, which lacks all 25 Xop genes involved in Xoo pathogenesis, has been engineered through iterative genome editing. Whole-genome sequencing analysis indicated that FnCas12a did not have a noticeable off-target effect. In addition, we revealed that these strategies are also suitable for targeted genome editing in another bacterial plant pathogen Pseudomonas syringae pv. tomato (Pst). We believe that our bacterial genome editing method will greatly expand the CRISPR study on microorganisms and advance our understanding of the physiology and pathogenesis of Xoo.

microbiology↗

bioRxiv2022

Identification of regulatory elements in primary sensory neurons involved in neuropathic pain

Chronic pain is a significant public health issue that is often refractory to existing therapies. Here we use a multiomic approach to identify cis-regulatory elements that show differential chromatin accessibility, and reveal transcription factor (TF) binding motifs with functional regulation in the dorsal root ganglion (DRG), which contain cell bodies of primary sensory neurons, after nerve injury. We integrated RNA-seq to understand how differential chromatin accessibility after nerve injury may influence gene expression. Using TF protein arrays and chromatin immunoprecipitation-qPCR, we confirmed C/EBP{gamma} binding to a differentially accessible sequence and used RNA-seq to identify processes in which C/EBP{gamma} plays an important role. Our findings offer insights into TF motifs that are associated with chronic pain. These data show how interactions between chromatin landscapes and TF expression patterns may work together to determine gene expression programs in DRG neurons after nerve injury.

neuroscience↗

bioRxiv2022

Decomposing spatial heterogeneity of cell trajectories with Paella

Spatial transcriptomics provides a unique opportunity to study continuous biological processes in a spatial context. We developed Paella, a computational method to decompose a cell trajectory into multiple spatial sub-trajectories and identify genes with differential temporal patterns across spatial sub-trajectories. Applied to spatial transcriptomics datasets of cancer, Paella identified spatially varying genes associated with tumor progression, providing insights into the spatial heterogeneity of cancer development.

bioinformatics↗

bioRxiv2022

Controlling taxa abundance improves metatranscriptomics differential analysis

A common task in analyzing metatranscriptomics data is to identify microbial metabolic pathways with differential RNA abundances across multiple sample groups. With information from paired metagenomics data, current differential methods control for either DNA or taxa abundances to address their strong correlation with RNA abundance. We discovered that when either DNA or taxa abundance is controlled for, RNA abundance still has a strong partial correlation with the other factor. Thus, both factors need to be controlled for in the differential model. In both simulation studies and a real data analysis, we demonstrated that controlling for both DNA and taxa abundances leads to superior performance compared to only controlling for one factor.

microbiology↗

bioRxiv2022

Palo: Spatially-aware color palette optimization for single-cell and spatial data

SummaryIn the exploratory data analysis of single-cell or spatial genomic data, single cells or spatial spots are often visualized using a two-dimensional plot where cell clusters or spot clusters are marked with different colors. With tens of clusters, current visualization methods often assigns visually similar colors to spatially neighboring clusters, making it hard to identify the distinction between clusters. To address this issue, we developed Palo that optimizes the color palette assignment for single-cell and spatial data in a spatially-aware manner. Palo identifies pairs of clusters that are spatially neighboring to each other and assigns visually distinct colors to those neighboring pairs. We demonstrate that Palo leads to improved visualization in real single-cell and spatial genomic datasets. AvailabilityPalo R package is freely available at https://github.com/Winnie09/Palo. Contactzhicheng.ji@duke.edu

bioinformatics↗

bioRxiv2021

Tree-based Correlation Screen and Visualization for Exploring Phenotype-Cell Type Association in Multiple Sample Single-Cell RNA-Sequencing Experiments

Single-cell RNA-seq experiments with multiple samples are increasingly used to discover cell types and their molecular features that may influence samples phenotype (e.g. disease). However, analyzing and visualizing the complex cell type-phenotype association remains nontrivial. TreeCorTreat is an open source R package that tackles this problem by using a tree-based correlation screen to analyze and visualize the association between phenotype and transcriptomic features and cell types at multiple cell type resolution levels. With TreeCorTreat, one can conveniently explore and compare different feature types, phenotypic traits, analysis protocols and datasets, and evaluate the impacts of potential confounders.

bioinformatics↗

bioRxiv2021

Translocation of polyubiquitinated protein substrates by the hexameric Cdc48 ATPase

The hexameric Cdc48 ATPase (p97 or VCP in mammals) cooperates with its cofactor Ufd1/Npl4 to extract polyubiquitinated proteins from membranes or macromolecular complexes for degradation by the proteasome. Here, we clarify how the Cdc48 complex unfolds its substrates and translocates polypeptides with branchpoints. The Cdc48 complex recognizes primarily polyubiquitin chains, rather than the attached substrate. Cdc48 and Ufd1/Npl4 cooperatively bind the polyubiquitin chain, resulting in the unfolding of one ubiquitin molecule (initiator). Next, the ATPase pulls on the initiator ubiquitin and moves all ubiquitin molecules linked to its C-terminus through the central pore of the hexameric double-ring, causing transient ubiquitin unfolding. When the ATPase reaches the isopeptide bond of the substrate, it can translocate and unfold both N- and C-terminal segments. Ubiquitins linked to the branchpoint of the initiator dissociate from Ufd1/Npl4 and move outside the central pore, resulting in the release of unfolded, polyubiquitinated substrate from Cdc48.

biochemistry↗