Publications by authors named "Chun Jimmie Ye"
Background: Systemic lupus erythematosus (SLE) has numerous symptoms across organs and an unpredictable flare-remittance pattern. This has made it challenging to understand drivers of long-term SLE outcomes. Our objective was to identify whether changes in DNA methylation over time, in an actively flaring SLE cohort, were associated with remission and whether these changes meaningfully subtype SLE patients.
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- - The study investigates how impaired signaling in naïve CD4+ T cells leads to the development of pathogenic autoreactive cells, which play a role in autoimmune arthritis, specifically using SKG mice with a mutated Zap70 gene.
- - Researchers found these pathogenic T cells had increased expression of activation and cytokine-related genes, but reduced expression of markers that usually promote tolerance compared to healthy cells.
- - The presence of specific TCR variable beta chains linked to superantigens from mouse retroviruses suggests that these viral elements may disrupt normal immune tolerance, fostering the development of self-reactive CD4+ T cells into harmful effector cells, with potential therapeutic implications.
Article Synopsis
- Physical activity improves symptoms in people with systemic lupus erythematosus (SLE), but the underlying mechanisms were unclear until this study explored immune cell differences among active vs. inactive patients.
- A cohort of 123 SLE patients underwent analysis of immune cells and gene expression through advanced RNA sequencing, revealing that sedentary patients had greater CD4+ T cell lymphopenia and an overall proinflammatory gene expression profile.
- The study indicates that increased physical activity could reduce levels of proinflammatory cytokines and improve immune function in SLE patients, suggesting potential therapeutic benefits of regular exercise for this condition.
Article Synopsis
- Researchers discovered that these atypical B cells provide valuable insights into antibody sequences, analyzing large-scale single-cell sequencing data that reveal widespread instances of light chain allelic inclusion.
- Machine learning models were developed to identify unique antibody sequences associated with properties like polyreactivity and mutation usage, outperforming previous antibody modeling techniques and highlighting the importance of allelic inclusion data.
Differential expression analysis of single-cell RNA sequencing (scRNA-seq) data is central for characterizing how experimental factors affect the distribution of gene expression. However, distinguishing between biological and technical sources of cell-cell variability and assessing the statistical significance of quantitative comparisons between cell groups remain challenging. We introduce Memento, a tool for robust and efficient differential analysis of mean expression, variability, and gene correlation from scRNA-seq data, scalable to millions of cells and thousands of samples.
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- The text discusses how different cell types work together in biological processes, and recent single-cell assays allow researchers to understand variations in these cells across individuals.
- It introduces a method called single-cell interpretable tensor decomposition (scITD), which combines cell type data to uncover patterns of variation and interaction.
- By applying scITD to data from individuals with lupus and COVID-19, researchers found connections between cellular activity and disease severity, providing insights into potential signaling pathways and the complexities of disease stratification.
Article Synopsis
- - Kidney failure significantly impacts health, prompting a large-scale study of 406,504 participants to uncover genetic factors affecting kidney function, identifying 430 key genetic loci.
- - The research revealed that 56% of inherited differences in kidney function are linked to regulatory elements in kidney tubule epithelial cells, while 7% relate to podocyte cells, suggesting these are crucial for gene expression.
- - Further analysis using advanced techniques like enhancer assays and CRISPRi identified specific genes (NDRG1, CCNB1, and STC1) regulated by these genetic loci, shedding light on their roles in kidney function.
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- The study investigates the connection between interferon and systemic lupus erythematosus (SLE), focusing on how transposable elements (TEs) might influence SLE symptoms, particularly autoantibody production.
- Researchers analyzed RNA-sequencing data from immune cells in 120 SLE patients, identifying over 27,000 TEs and observing 731 that were differentially expressed among various SLE phenotypes.
- Results indicate that specific TEs are linked to genes responsible for antiviral responses and IFN signaling, highlighting their potential role in understanding and treating SLE.
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- Deep learning models are used to predict epigenetic features, but their performance varies, especially in cell type-specific regions crucial for gene regulation.
- The study compares general-purpose models and tissue-specific models, finding that tailored models can enhance accuracy in predicting chromatin accessibility in specific cells.
- It emphasizes the need for novel strategies to improve predictions on genetic variants, as high reference sequence accuracy does not guarantee better variant effect predictions.
Article Synopsis
- A variety of deep learning models are being developed to predict chromatin accessibility from DNA sequences, but evaluation results often overlook the significance of cell type specific regulatory elements (CREs), which are crucial for gene regulation and complex disease heritability.
- The study evaluates the accuracy of these genomic models, revealing that general purpose models like Enformer and Sei perform worse in regions that are specifically accessible to certain cell types.
- The research highlights that tailoring models for specific tissues and enhancing their capacity for cell type specific regulation can boost performance, but improving predictions of reference sequences doesn't necessarily translate to better predictions of variant effects, suggesting the need for new approaches in the field.
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- This study focused on managing rheumatoid arthritis (RA) by analyzing blood cells from patients and healthy individuals to identify specific cell types and their roles in disease activity.
- Researchers discovered 18 distinct types of immune cells, noting that patients with more severe RA had an increase in certain T cells, while those in remission showed fewer nonclassical monocytes.
- The study also highlighted key gene expressions related to inflammation and disease, providing insights into the complex biological processes that contribute to RA's variability in severity.
Article Synopsis
- Kidney disease is largely influenced by genetics, yet the specific genes and mechanisms involved are still not fully understood; a recent GWAS identified 462 genetic loci associated with kidney function.
- Researchers used single-cell ATAC-seq maps to explore chromatin accessibility in the kidney, finding that regulatory elements in kidney tubule epithelial cells accounted for the majority of genetic heritability related to kidney function.
- The study further utilized CRISPR interference to demonstrate how inherited variations in regulatory elements impact gene expression in tubule epithelial cells, ultimately linking these differences to a predisposition for kidney disease in humans.
Article Synopsis
- Researchers studied how cis-regulatory elements (CREs) work with trans regulators to control the expression of T cell genes CD28, CTLA4, and ICOS, which are important for immune responses.
- Using CRISPR interference (CRISPRi) screens, they identified specific CREs that vary depending on the type of T cell and stimulation, revealing the complexity of gene regulation.
- They found that the CCCTC-binding factor (CTCF) plays a key role in enhancing the interaction between CREs and CTLA4 while also preventing unintended activation of CD28, helping to clarify the regulatory landscape of these immune genes.
Article Synopsis
- Juvenile dermatomyositis (JDM) is an autoimmune disorder in children linked to abnormal immune responses and limited treatment options due to unclear disease mechanisms.
- The study analyzed the blood of JDM patients at various disease stages, revealing that B cells were skewed towards an immature state and T cells showed signs of sustained Th2-mediated inflammation even during inactive disease.
- By using network analysis, researchers found that a heightened type I IFN response across immune cells is connected to dysfunctional processes in CD4+ T cells and cell death regulation in other T cell types, highlighting the complex immune dysregulation in JDM and hinting at potential treatment strategies.
Article Synopsis
- Recent advances in single-cell RNA-sequencing (scRNA-seq) allow researchers to explore biological phenomena at the individual cell level.
- Using droplets that mix cells from different individuals, scientists can determine which cell came from whom by identifying genetic differences.
- A new tool called Demuxafy enhances this process by effectively distinguishing single cells from doubles (which contain multiple cells), improving the accuracy of assigning cells to their respective donors.
Article Synopsis
- The study investigates how genetic variation impacts gene expression in various brain cell types and subtypes using single-nucleus RNA sequencing from 424 older individuals.
- Researchers identified thousands of eGenes (genes with expression influenced by genetic variants) in different cell types and subtypes, revealing that some eGenes are unique to specific subtypes.
- Notably, a variant affecting APOE expression in microglia is linked to cerebral amyloid angiopathy, and findings were connected to diseases like Alzheimer's, schizophrenia, and Parkinson's through genome-wide association studies.
Article Synopsis
- Researchers are mapping expression quantitative trait loci (eQTLs) to better understand how genetic variants linked to diseases operate, but current databases use bulk RNA-seq data that lack specificity for cell types and environments.
- The new Single-cell eQTL Interactive Database offers a user-friendly platform for visualizing single-cell eQTL data across various cell types, filling a gap in existing resources.
- This database provides detailed summaries of the latest sc-eQTL studies, aiming to enhance our knowledge of gene regulation in specific cellular contexts and promote functional genomics research.
Article Synopsis
- Population-scale single-cell genomics is a key method for exploring how genetic and cellular differences are connected.
- Advances in high-throughput technologies and environmental perturbations allow researchers to see how genetic variants influence cellular behavior in different contexts.
- Future developments in sequencing and machine learning can enhance our understanding of genetics related to human diseases and traits.
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- Inborn errors of immunity (IEI) are a group of 485 disorders identified in 2022, highlighting genetic causes and their relevance in various immune-related conditions.
- Recent advancements in genomic technologies have accelerated the discovery of IEI and contributed to the development of new treatment strategies.
- This review will focus on the complexities of IEI, including the differences between primary immunodeficiencies (PIDD) and primary immune regulatory disorders (PIRD), Mendelian inheritance patterns, and the role of functional genomics in better understanding and treating these disorders.
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- Genetic regulation of gene expression varies based on different cell types and environmental contexts, making it a complex process.* -
- SURGE is a new method developed to discover context-specific expression quantitative trait loci (eQTLs) from single-cell transcriptomic data without needing prior information.* -
- When applied to peripheral blood data, SURGE effectively identifies specific cell types and their relationships, demonstrating its relevance to diseases through advanced analysis methods.*
Article Synopsis
- * The research identified two main categories of harmful variants in the polycystin-1 protein: those that prevent it from reaching the cell surface and those that impair its ion channel activity.
- * A small molecule was found to potentially rescue the surface localization of defective polycystin channels, suggesting that improving channel function through small-molecule therapies could be a promising treatment for ADPKD.
Article Synopsis
- CRISPR-enabled screening is a technique that helps discover genes affecting T cell function, pointing to potential immunotherapy targets, but there's a need for methods to study specific DNA sequences in these genes.
- A new platform for large-scale base-editing mutagenesis was developed to identify critical nucleotides that influence how T cells react and produce cytokines.
- The research revealed numerous genetic variants in key proteins that can either enhance or diminish T cell function, offering valuable insights for advancing immunotherapy strategies.*
Article Synopsis
- Juvenile Dermatomyositis (JDM) is an autoimmune disorder in children characterized by immune system dysfunction and limited treatment options due to unclear disease mechanisms.
- Researchers studied blood samples from JDM patients to examine the immune system's behavior, finding that B cells showed signs of immaturity and were linked to inflammation patterns.
- The study revealed a coordinated hyperactivation of the type I interferon response across immune cells, suggesting new ways to understand and potentially improve immune regulation in JDM.
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- Altered myeloid inflammation and lymphopenia are key characteristics of severe infections, particularly in patients with acute lung injuries from SARS-CoV-2.
- The upregulated EN-RAGE gene program found in airway and blood myeloid cells is linked to increased clinical severity, predicting outcomes like mechanical ventilation and mortality.
- IL-6 was identified as a major factor driving myeloid dysfunction, and blocking its signaling with tocilizumab effectively normalized EN-RAGE gene expression and improved T cell function in clinical trials.