Biology subjects

Yan, C.

Publications and source records attributed to Yan, C..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

ILSM: A package for analyzing the interconnection structure of tripartite interaction networks

O_LIIn natural or human-disturbed ecosystems, ecological networks often comprise multiple interaction types, which have been often represented by multipartite ecological networks. One important aspect of their network architecture is how different interaction types or subnetworks are interconnected by shared species, here defined as the interconnection structure. Previous studies have proposed various indices of shared species to characterize macro-scale interconnection patterns and micro-scale centrality, but the meso-scale interconnection structures (here defined as interconnection motifs) remain largely unexplored. Furthermore, there is no package available in the R programming language for conducting analyses of various interconnection structures. C_LIO_LIWithin a tripartite network with two interaction subnetworks, we define the forms of interconnection motifs and unique roles within these motifs. Then we introduce the R package ILSM for analyzing interconnection patterns, interconnection centrality, and interconnection motif. Specifically, we derive mathematical expressions for the frequencies of interconnection motifs and species roles within motifs. C_LIO_LIWe describe the main functions in the package and demonstrate their uses with an example pollinator-plant-herbivore network. C_LIO_LIILSM will help ecologists understand how different types of interactions are interconnected together by shared species using interconnection pattern, centrality and motif. C_LI

ecology↗

bioRxiv2024

Fishnet mesh of centrin-Sfi1 drives ultrafast calcium-activated contraction of the giant cell Spirostomum ambiguum

Spirostomum is a giant unicellular ciliate that contracts to a quarter of its body length in less than five milliseconds, achieving an order of magnitude higher fractional shortening rate than actomyosin-based systems. This ultrafast contraction is powered by myonemes, calcium-activated protein networks at the cortex whose biochemical mechanism remain unclear. We quantify changes in cortical microtubules, membrane ruffles, and the fishnet-like myoneme mesh during contraction, and develop multiscale models that connect local myoneme shortening to whole-cell shape change. Centrin and an Sfi1 homolog co-localize with the myoneme by immunofluorescence and localize to the myoneme by immunogold electron microscopy. Coarse-grained mesh simulations reproduce the measured deformations and show that fishnet geometry, together with volume conservation, leads to uniform contraction. Finally, we reconstitute a Spirostomum centrin-Sfi1 repeat complex in vitro and measure calcium-dependent compaction and self-association, supporting a molecular basis for myoneme contractility. Together, these results support a multiscale model in which calcium-responsive centrin- Sfi1 structures are the central contractile element in Spirostomum and suggest design principles for fast, calcium-triggered, chemomechanical contractile networks that operate without actomyosin or ATP. SIGNIFICANCE STATEMENTMany cells change shape using actomyosin, but some protists contract using calcium-activated protein networks called myonemes. We combine quantitative imaging, electron microscopy, multiscale modeling, and in vitro reconstitution to link molecular-scale mechanisms to the millisecond shortening of the giant ciliate Spirostomum. Centrin and an Sfi1 homolog co-localize in a fishnet-like cortical mesh, and simulations show that this geometry can reproduce the observed whole-cell shape change under volume conservation. Purified centrin-Sfi1 complexes undergo calcium-dependent compaction and self-association, supporting a protein-scale switch that can drive myoneme contraction. These results connect calcium signaling to whole-cell mechanics and suggest principles for designing fast, ATP-independent bioin-spired actuators and synthetic cellular machinery.

cell biology↗

bioRxiv2024

Switch of TIR signaling by a Ca2+ sensor activates ADR1 recognition of pRib-AMP-EDS1-PAD4 for stomatal immunity

Plants swiftly close stomata upon detecting pathogen entry, a crucial defense termed stomatal immunity. The process is initiated by cell-surface pattern recognition receptors (PRRs) that perceive pathogen-associated molecular patterns (PAMPs) and evoke a series of early cellular responses including calcium ions (Ca2+) influx, and is conducted by the intracellular nucleotide-binding leucine-rich-repeat receptors (NLRs) ADR1s within an EDS1-PAD4-ADR1 module. However, the underlying mechanisms linking PRR signaling to the NLRs ADR1s remain unclear. Here, we show that the Nicotiana benthamiana Toll/interleukin-1 receptor (TIR)-only protein Stomatal TIR1 (STIR1) produces the immune molecule pRib-AMP, induces formation of EDS1-PAD4-ADR1 complexes, and mediates stomatal immunity. The Inhibitor of Stomatal Immunity C2-domain protein 1 (ISIC1) interacts with and constrains STIR1 function at basal condition, whereas upon pathogen infection, ISIC1 senses Ca2+ signals and de-represses STIR1 signaling. Cryo-electron microscopy structure of pathogen infection-elicited Arabidopsis AtEDS1-AtPAD4-AtADR1-L2 complex reveals the pRib-AMP binding to AtEDS1-AtPAD4 receptor and the AtADR1-L2 recognition of pRib-AMP-AtPAD4-AtEDS1 for stomatal immunity. Collectively, this study uncovers a repression/de-repression mechanism linking PRR signaling to NLRs by a Ca2+ sensor/TIR-only node, and elucidates an NLR recognition mechanism of the pRib-AMP-EDS1-PAD4 complex in governing innate immunity. SynopsisAt basal condition, the Ca2+ sensor ISIC1 interacts with and inhibits the TIR-only protein STIR1; upon pathogen infection, ISIC1 perceives Ca2+ signal and releases STIR1 to produce pRib-AMP; the EDS1-PAD4 receptor binds pRib-AMP and is recognized by the NLR ADR1-L2, thereby activating stomatal immunity.

plant biology↗

bioRxiv2024

Deep contrastive learning enables genome-wide virtual screening

Numerous protein-coding genes are associated with human diseases, yet approximately 90% of them lack targeted therapeutic intervention. While conventional computational methods, such as molecular docking, have facilitated the discovery of potential hit compounds, the development of genome-wide virtual screening against the expansive chemical space remains a formidable challenge. Here we introduce DrugCLIP, a novel framework that combines contrastive learning and dense retrieval to achieve rapid and accurate virtual screening. Compared to traditional docking methods, DrugCLIP improves the speed of virtual screening by up to seven orders of magnitude. In terms of performance, DrugCLIP not only surpasses docking and other deep learning-based methods across two standard benchmark datasets, but also demonstrates high efficacy in wet-lab experiments. Specifically, DrugCLIP successfully identified agonists with < 100 nM affinities for 5HT2AR, a key target in psychiatric diseases. For another target NET, whose structure is newly solved and not included in the training set, our method achieved a hit rate of 15%, with 12 diverse molecules exhibiting affinities better than bupropion. Additionally, two chemically novel inhibitors were validated by structure determination with Cryo-EM. Finally, a novel potential drug target TRIP12, with no experimental structures and inhibitors for reference, was used to challenge DrugCLIP. DrugCLIP achieved a hit rate of 17.5% by screening a pocket identified on an AlphaFold2-predicted structure, verified with multi-cycle SPR assays. Molecules with the highest affinities also showed a dose-dependent inhibition to the enzymatic function of TRIP12. Building on this foundation, we present the results of a pioneering trillion-scale genome-wide virtual screening, encompassing approximately 10,000 AlphaFold2 predicted proteins within the human genome and 500 million molecules from the ZINC and Enamine REAL database. This work provides an innovative perspective on drug discovery in the post-AlphaFold era, where comprehensive targeting of all disease-related proteins is within reach.

bioinformatics↗

bioRxiv2024

Cell of origin alters myeloid-mediated immunosuppression in lung adenocarcinoma

Solid carcinomas are often highly heterogenous cancers, arising from multiple epithelial cells of origin. Yet, how the cell of origin influences the response of the tumor microenvironment is poorly understood. Lung adenocarcinoma (LUAD) arises in the distal alveolar epithelium which is populated primarily by alveolar epithelial type I (AT1) and type II (AT2) cells. It has been previously reported that Gramd2+ AT1 cells can give rise to a histologically-defined LUAD that is distinct in pathology and transcriptomic identity from that arising from Sftpc+ AT2 cells1,2. To determine how cells of origin influence the tumor immune microenvironment (TIME) landscape, we comprehensively characterized transcriptomic, molecular, and cellular states within the TIME of Gramd2+ AT1 and Sftpc+ AT2-derived LUAD using KRASG12D oncogenic driver mouse models. Myeloid cells within the Gramd2+AT1-derived LUAD TIME were increased, specifically, immunoreactive monocytes and tumor associated macrophages (TAMs). In contrast, the Sftpc+ AT2 LUAD TIME was enriched for Arginase-1+ myeloid derived suppressor cells (MDSC) and TAMs expressing profiles suggestive of immunosuppressive function. Validation of immune infiltration was performed using flow cytometry, and intercellular interaction analysis between the cells of origin and major myeloid cell populations indicated that cell-type specific markers SFTPD in AT2 cells and CAV1 in AT1 cells mediated unique interactions with myeloid cells of the differential immunosuppressive states within each cell of origin mouse model. Taken together, Gramd2+ AT1-derived LUAD presents with an anti-tumor, immunoreactive TIME, while the TIME of Sftpc+ AT2-derived LUAD has hallmarks of immunosuppression. This study suggests that LUAD cell of origin influences the composition and suppression status of the TIME landscape and may hold critical implications for patient response to immunotherapy.

cancer biology↗

bioRxiv2024

Single-Cell and Spatial Transcriptomic Analyses Reveals the Dynamic Transcript Profiles of Myocardial Lymphangiogenesis post Myocardial Infarction

Cardiac lymphatics play an important role in myocardial edema and inflammation. This study integrated single-cell sequencing data and spatial transcriptome data from mouse heart tissue at different time points post-myocardial infarction (MI), and identified four transcriptionally distinct subtypes of lymphatic endothelial cells (LECs) and localized them in space. Interestingly, LECs subgroups was found to be localized in different zones of infarcted heart related to different functions. Additionally, LEC capillary III(LEC ca III) may be involved in the direct regulation of myocardial injuries in infarcted zone from the perspective of metabolic stress, while LEC ca II may be related to the rapid immune inflammatory responses of the border zone in the early stage of MI. LEC ca I, as well as LEC collection mainly participate in the regulation of myocardial tissue edema resolution in the middle and late stages post-MI. Cell trajectory and Cell-Chat analyses further identified that LECs may regulate myocardial edema through Aqp1, and might affect the infiltration of macrophages through the Galectin9-CD44 pathway. Collectively, our study revealed the dynamic transcriptional heterogeneity distribution of LECs in different regions of the infarcted heart, in detail; these LECs formed different functional subgroups, that might exhibit different bioeffects in myocardial tissue post-MI.

bioinformatics↗

bioRxiv2024

Machine Learning Models for Cardiovascular Disease Prediction: A Comparative Study

Cardiovascular diseases (CVDs) pose a significant threat to global public health, affecting individuals across various age groups. Factors such as cholesterol levels, smoking, alcohol consumption, and physical inactivity contribute to their onset and progression. Enhancing our understanding of CVD etiology and informing targeted interventions for disease prevention and management remains a critical challenge. In this study, we address the task of predicting the likelihood of individuals developing CVDs using machine learning techniques. Specifically, we explore three approaches: the k-nearest neighbors (KNN) algorithm, logistic regression, and the random forest algorithm. Leveraging a comprehensive dataset sourced from Kaggle, encompassing 11 relevant factors, we conduct a series of experiments to identify the most influential predictors of CVDs. Our analysis aims not only to forecast disease occurrence but also to elucidate the primary determinants contributing to its manifestation. Through comparative analysis of the three methodologies, we demonstrate that the random forest algorithm exhibits superior performance in terms of predictive accuracy. This research represents a significant step towards leveraging machine learning techniques to enhance our understanding of CVD dynamics and inform targeted interventions for disease prevention and management.

cancer biology↗

bioRxiv2024

PIGOME: An Integrated and Comprehensive Multi-omics Database for Pig Functional Genomics Studies

In addition to being a major source of animal protein, pigs are important model for the study of development and diseases in humans. During the past two decades, thousands of high-throughput sequencing studies in pigs have been performed using a variety of tissues from different breeds and developmental stages. However, the multi-omics database specifically used for pig functional genomic research is still limited. Here, we present a user-friendly database of pig multi-omics named PIGOME. PIGOME contains seven types of pig omics datasets, including whole-genome sequencing, RNA-seq, miRNA-seq, ChIP-seq, ATAC-seq, bisulfite-seq, and MeRIP-seq, from 6,901 samples and 392 projects with manually curated metadata, integrated gene annotation, and quantitative trait locus information. Furthermore, various explore and browse functions have been established for user-friendly access to omics information. PIGOME implemented several tools to visualize genomic variants, gene expression, and epigenetic signals of a given gene in the pig genome, enabling efficient exploration of spatial-temporal expression/epigenetic pattern, function, regulatory mechanism, and associated economic traits. Collectively, PIGOME provides valuable resources for pig breeding and is helpful for human biomedical research. PIGOME is available at https://pigome.com.

bioinformatics↗

bioRxiv2024

High-Throughput Phenotyping of Seed Quality Traits Using Imaging and Deep Learning in Dry Pea

Seed traits, such as seed color and seed size, directly impact seed quality, affecting the marketability and value of dry peas [1]. Assessing seed quality is integral to a plant breeding programs to ensure optimal seed standards. This research introduced a phenotyping tool to assess seed quality traits specifically tailored for pulse crops, which integrates image processing with cutting-edge deep learning models. The proposed method is designed for automation, seamlessly processing a sequence of images while minimizing human intervention. The pipeline standardized red-green-blue (RGB) images captured from a color light box and used deep learning models to segment and detect seed features. Our method extracted up to 86 distinct seed characteristics, ranging from basic size metrics to intricate texture details and color nuances. Compared to traditional methods, our pipeline demonstrated a 95 percent similarity in seed quality assessment and increased time efficiency (from 2 weeks to 30 minutes for processing time). Specifically, we observed an improvement in the accuracy of seed trait identification by simply using an RGB value instead of a categorical, non-standard description, which allowed for an increase in the range of detectable seed quality characteristics. By integrating conventional image processing techniques with foundational deep learning models, this approach emerges as a pivotal instrument in pulse breeding programs, guaranteeing the maintenance of superior seed quality standards.

plant biology↗

bioRxiv2024

BayVarC: an ultra-sensitive ctDNA variant caller using Bayesian approach

In liquid biopsy, it is critical to detect variants of allele frequencies as low as 0.1% or even lower, especially when used to monitor secondary resistant mutations and minimal residual disease. Despite the efforts on improving experimental design, it remains challenging to distinguish low-frequency variants from technical noises in the downstream bioinformatic analysis. Here, we introduce BayVarC, a novel variant caller specifically designed for variant calling in liquid biopsy. It applies Bayesian inference to accurately quantify noise level in a locus-specific manner, enabling the discrimination between technical noise and low-frequency cancer variants. Detailed in-silico simulation and in-vitro experiments demonstrated BayVarC superior performance over existing state-of-the-art tools. BayVarC can effectively detect low frequency variants while maintaining low false positive rate (0.05 FP/KB). Meanwhile, it achieves Limit of Detection (LoD) as low as 0.1%. Furthermore, empowered by its architecture, BayVarC shows promising applicability in Minimal Residual Disease (MRD) detection. BayVarC is freely available at https://github.com/GenetronBioinfomatics/BayVarC.

bioinformatics↗

bioRxiv2024

Architecture of intact mammalian pyruvate dehydrogenase complex revealed by in-situ structural analysis

The multi-enzyme pyruvate dehydrogenase complex (PDC) links glycolysis to the citric acid cycle by converting pyruvate into acetyl-coenzyme A and is essential for cellular energy metabolism. Although individual components have been characterized, the structure of intact PDC remains unclear, hampering our understanding of its composition and multi-step catalytic reactions. Here, we report the in-situ architecture of intact PDC within mammalian mitochondria by cryo-electron tomography. The organization of peripheral E1 and E3 multimers varies substantially among PDCs. We discovered 1-46 E1 heterotetramers surrounding each PDC core, and up to 12 E3 dimers locating primarily along the pentagonal openings. Furthermore, we observed dynamic interactions of the substrate translocating lipoyl domains (LDs) with both E1 and E2, implicating the mechanism of substrate channeling. Our findings reveal the intrinsic dynamics of PDC peripheral compositions, suggesting an additional model in which the number of assembled E1 heterotetramer, E3 dimer, and functional LDs of PDC may be regulated to further control its catalytic activity.

cell biology↗

bioRxiv2024

The EGF/EGFR-YAP1/TEAD2 axis-mediated BRAF inhibitor vemurafenib resistance upregulates STIM1 in melanoma

STIM1 is the endoplasmic reticulum (ER) Ca2+ sensor for store-operated entry (SOCE) and closely correlated to carcinogenesis and tumor progression. Previously we found that STIM1 is upregulated in melanoma cells resistant to the BRAF inhibitor vemurafenib, but the regulation mechanism is unknown. Here, we show that vemurafenib resistance upregulates STIM1 through an EGF/EGFR-YAP1/TEAD2 axis. Vemurafenib resistance can lead to the increase of EGF and EGFR levels to activate the EGFR signaling pathway. Reactivated EGFR signal promotes YAP1 nuclear localization to increase the expression of STIM1. Our finding not only demonstrates the mechanism by which vemurafenib resistance promotes STIM1 expression, but also provides combined targeting EGF/EGFR-YAP1/TEAD2-STIM1 to improve the therapeutic efficiency of BRAF inhibitor in melanoma patients.

cancer biology↗

bioRxiv2023

The role of neutrophil typing in homeostatic resilience protective model of inflammatory preconditioning

Sepsis is a systemic inflammatory response syndrome (SIRS) characterized by a dysregulated host response to infection that results in organ dysfunction. The response of neutrophils to early inflammation is critical, interferon regulatory factors 4 (IRF4) and interferon regulatory factors 5 (IRF5) are expressed in most cell types of the immune system, but the relationship between the role of IRF4 and IRF5 in preconditioning-protected septic peritonitis mouse model and neutrophils response remains unknown. In this study, we used an E.coli-induced septic peritonitis mouse model and zebrafish model to explore the relationship between neutrophil inflammation and IRF subtype changes in the process of septic peritonitis. Mechanistically, we found that the protein complex formed by polymorphonuclear neutrophils (PMN) and IRF5/MyD88 can secrete pro-inflammatory factors and directly kill invading bacteria. Author SummaryNumerous animal and clinical sepsis studies have shown that markedly impaired recruitment of neutrophils to sites of infection and failure to clear bacteria contribute to excessive inflammation and increased mortality in sepsis. In our previous work, we established an Escherichia coli (E.coli) lethal septic peritonitis model and a preconditioning-protected septic peritonitis mouse model. In the early stage of septic peritonitis, a large number of PMN infiltrate the peritoneal cavity, which produces an inflammatory response to invasive bacteria. In this study, the switching process between pro-inflammatory and anti-inflammatory attracted our attention. Our research shows that IRF5-IRF4 regulatory axis leads to a PMN phenotype switch in sepsis and the expression of IRF5 and IRF4 was related to PMN pro-inflammatory (N1 type) and anti-inflammatory (N2 type) phenotypes, respectively.

immunology↗

bioRxiv2023

Biophysical Mechanism of Allosteric Regulation of Actin Capping Protein

Actin capping protein (CP) can be regulated by steric and allosteric mechanisms. The molecular mechanism of the allosteric regulation at a biophysical level includes linkage between the binding sites for three ligands: F-actin, Capping-Protein-Interacting (CPI) motifs, and V-1/myotrophin, based on biochemical functional studies and solvent accessibility experiments. Here, we investigated the mechanism of allosteric regulation at the atomic level using single-molecule Forster resonance energy transfer (FRET) and molecular dynamics (MD) to assess the conformational and structural dynamics of CP in response to linked-binding site ligands. In the absence of ligand, both single-molecule FRET and MD revealed two distinct conformations of CP in solution; previous crystallographic studies revealed only one. CPI-motif peptide association induced conformational changes within CP that propagate in one direction, while V-1 association induced conformational changes in the opposite direction. Comparing CPI-motif peptides from different proteins, we identified variations in CP conformations and dynamics that are specific to each CPI motif. MD simulations for CP alone and in complex with a CPI motif and V-1 reveal atomistic details of the conformational changes. Analysis of the interaction of CP with wildtype (wt) and chimeric CPI-motif peptides using single-molecule FRET, isothermal calorimetry (ITC) and MD simulation indicated that conformational and affinity differences are intrinsic to the C-terminal portion of the CPI-motif. We conclude that allosteric regulation of CP involves changes in conformation that disseminate across the protein to link distinct binding-site functions. Our results provide novel insights into the biophysical mechanism of the allosteric regulation of CP.

biochemistry↗

bioRxiv2023

FAM210A Regulates Mitochondrial Translation and Maintains Cardiac Mitochondrial Homeostasis

AimsMitochondria play a vital role in cellular metabolism and energetics and support normal cardiac function. Disrupted mitochondrial function and homeostasis cause a variety of heart diseases. Fam210a (family with sequence similarity 210 member A), a novel mitochondrial gene, is identified as a hub gene in mouse cardiac remodeling by multi-omics studies. Human FAM210A mutations are associated with sarcopenia. However, the physiological role and molecular function of FAM210A remain elusive in the heart. We aim to determine the biological role and molecular mechanism of FAM210A in regulating mitochondrial function and cardiac health in vivo. Methods and ResultsTamoxifen-induced MHCMCM-driven conditional knockout of Fam210a in the mouse cardiomyocytes induced progressive dilated cardiomyopathy and heart failure, ultimately causing mortality. Fam210a deficient cardiomyocytes exhibit severe mitochondrial morphological disruption and functional decline accompanied by myofilament disarray at the late stage of cardiomyopathy. Furthermore, we observed increased mitochondrial reactive oxygen species production, disturbed mitochondrial membrane potential, and reduced respiratory activity in cardiomyocytes at the early stage before contractile dysfunction and heart failure. Multi-omics analyses indicate that FAM210A deficiency persistently activates integrated stress response (ISR), resulting in transcriptomic, translatomic, proteomic, and metabolomic reprogramming, ultimately leading to pathogenic progression of heart failure. Mechanistically, mitochondrial polysome profiling analysis shows that FAM210A loss of function compromises mitochondrial mRNA translation and leads to reduced mitochondrial encoded proteins, followed by disrupted proteostasis. We observed decreased FAM210A protein expression in human ischemic heart failure and mouse myocardial infarction tissue samples. To further corroborate FAM210A function in the heart, AAV9-mediated overexpression of FAM210A promotes mitochondrial-encoded protein expression, improves cardiac mitochondrial function, and partially rescues murine hearts from cardiac remodeling and damage in ischemia-induced heart failure. ConclusionThese results suggest that FAM210A is a mitochondrial translation regulator to maintain mitochondrial homeostasis and normal cardiomyocyte contractile function. This study also offers a new therapeutic target for treating ischemic heart disease. Translational PerspectiveMitochondrial homeostasis is critical for maintaining healthy cardiac function. Disruption of mitochondrial function causes severe cardiomyopathy and heart failure. In the present study, we show that FAM210A is a mitochondrial translation regulator required for maintaining cardiac mitochondrial homeostasis in vivo. Cardiomyocyte-specific FAM210A deficiency leads to mitochondrial dysfunction and spontaneous cardiomyopathy. Moreover, our results indicate that FAM210A is downregulated in human and mouse ischemic heart failure samples and overexpression of FAM210A protects hearts from myocardial infarction induced heart failure, suggesting that FAM210A mediated mitochondrial translation regulatory pathway can be a potential therapeutic target for ischemic heart disease.

pathology↗

bioRxiv2023

Site effects depth denoising and signal enhancement using dual-projection based ICA model

Combining magnetic resonance imaging (MRI) data from multi-site studies is a popular approach for constructing larger datasets to greatly enhance the reliability and reproducibility of neuroscience research. However, the scanner/site variability is a significant confound that complicates the interpretation of the results, so effective and complete removal of the scanner/site variability is necessary to realize the full advantages of pooling multi-site datasets. Independent component analysis (ICA) and general linear model (GLM) based denoising methods are the two primary methods used to denoise scanner/site-related effects. Unfortunately, there are challenges with both ICA-based and GLM-based denoising methods to remove site effects completely when the signals of interest and scanner/site-related noises are correlated, which may occur in neuroscience studies. In this study, we propose an effective and powerful denoising strategy that implements dual-projection (DP) theory based on ICA to remove the scanner/site-related effects more completely. This method can separate the signal effects correlated with noise variables from the identified noise effects for removal without losing signals of interest. Both simulations and vivo structural MRI datasets, including a dataset from Autism Brain Imaging Data Exchange II and a traveling subject dataset from the Strategic Research Program for Brain Sciences, were used to test the proposed GLM- and ICA-based denoising methods and our DP-based ICA denoising method. Results show that DP-based ICA

neuroscience↗

bioRxiv2023

The genomic landscape of adaptation to a new host plant

Adaptation to novel ecological niches is known to be rapid. However, how the loci underlying ecological divergence are coupled to traits reproductively isolating populations, ultimately enabling the formation of persistent species, remains a consequential question in speciation research. Here, we investigated the genomic differences underpinning colonization of a new niche and formation of two partly sympatric host races of Tephritis conura peacock flies. We took advantage of two independent sympatric zones west and east of the Baltic Sea, where host plant specialists using the thistle species Cirsium heterophyllum and C. oleraceum co-occur, and address what regions of the genome maintain the host races in parallel. Using genome-wide association, differentiation and divergence statistics, we identified a large, highly divergent region associated with host use among western and eastern populations. Within this region, we identified unique haplotypes associated with each host race, indicative of a large inversion, adding to the growing body of evidence that structural changes to the genome are important for adaptations to persist in the face of gene flow. We further showed strong signatures of selection in this region, especially in populations of the derived C. oleraceum specialist host race. The region also had reduced introgression, especially in western populations, while the rest of the genome showed signs of extensive gene flow. Genes within highly differentiated windows within the putative inversion were not only enriched for functions involved in host adaptation, including phenology and metabolic responses to different metabolites in the two host plants, but also enriched for gametogenesis, fertilization and embryological development, all of which suggest sequence divergence could have large consequences on reproductive isolation between the host races. In conclusion, this study suggests that structural changes in the genome may facilitate the formation of persistent host races, and ultimately speciation, in face of gene flow.

evolutionary biology↗

bioRxiv2023

Cell-type specific EWAS identifies genes involved in HIV pathogenesis andoncogenesis among people with chronic HIV infection

Epigenome-wide association studies (EWAS) of heterogenous blood cells have identified CpG sites associated with chronic HIV infection, which offer limited knowledge of cell-type specific methylation patterns associated with HIV infection. Applying a computational deconvolution method validated by capture bisulfite DNA methylation sequencing, we conducted a cell type-based EWAS and identified differentially methylated CpG sites specific for chronic HIV infection among five immune cell types in blood: CD4+ T-cells, CD8+ T-cells, B cells, Natural Killer (NK) cells, and monocytes in two independent cohorts (Ntotal=1,134). Differentially methylated CpG sites for HIV-infection were highly concordant between the two cohorts. Cell-type level meta-EWAS revealed distinct patterns of HIV-associated differential CpG methylation, where 67% of CpG sites were unique to individual cell types (false discovery rate, FDR <0.05). CD4+ T-cells had the largest number of HIV-associated CpG sites (N=1,472) compared to any other cell type. Genes harboring statistically significant CpG sites are involved in immunity and HIV pathogenesis (e.g. CX3CR1 in CD4+ T-cells, CCR7 in B cells, IL12R in NK cells, LCK in monocytes). More importantly, HIV-associated CpG sites were overrepresented for hallmark genes involved in cancer pathology (FDR<0.05) (e.g. BCL family, PRDM16, PDCD1LGD, ESR1, DNMT3A, NOTCH2). HIV-associated CpG sites were enriched among genes involved in HIV pathogenesis and oncogenesis such as Kras-signaling, interferon- and -{gamma}, TNF-, inflammatory, and apoptotic pathways. Our findings are novel, uncovering cell-type specific modifications in the host epigenome for people with HIV that contribute to the growing body of evidence regarding pathogen-induced epigenetic oncogenicity, specifically on HIV and its comorbidity with cancers.

cancer biology↗