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Wu, J.

Publications and source records attributed to Wu, J..

At least 451 records · Page 25Linked to original sources

Identifying dysregulated regions in amyotrophic lateral sclerosis through DNA accessibility outliers

The high heritability of ALS and similar rare diseases contrasts with their low molecular diagnosis rate post-genetic testing, pointing to potential undiscovered genetic factors. Chromatin accessibility assays quantify the activity of functional elements genome-wide, offering invaluable insights into dysregulated regions. In this research, we introduced EpiOut, a computational toolbox to identify outliers in chromatin accessibility. These outliers represent dysregulated regions where chromatin accessibility uniquely diverges from the population baseline in a single or few samples. Annotation of accessible regions with histone ChIP-seq and Hi-C indicates that outliers are concentrated in functional loci, especially among promoters interacting with active enhancers. Across different omics levels, outliers are robustly replicated, and chromatin accessibility outliers are reliable predictors of gene expression outliers and aberrant protein levels. For example, 59% of gene expression outliers can be linked to aberration in chromatin accessibility. When promoter accessibility does not align with gene expression, our results indicate that molecular aberrations are more likely to be linked to post-transcriptional regulation rather than transcriptional regulation. Our findings demonstrate that the outlier detection paradigm can uncover dysregulated regions in rare diseases. EpiOut is open-sourced and freely available at github.com/uci-cbcl/EpiOut.

bioinformatics↗

A highly connected river network continuum is not resilient to non-point source pollution from anthropogenic activity

Urbanization significantly impacts the community structure of aquatic organisms and poses a major threat to river biodiversity. However, the extent to which urbanization is linked to the homogenization of microbial communities and the underlying mechanisms remains poorly understood. In this study, we investigated the bacterial and archaeal communities from cities and neighboring natural rivers across river network located in the Qinling Mountains, Northwest China, and further investigated the alpha and beta diversity patterns and the mechanisms influenced by urbanization. We found that the influx of urban non-point source pollutants created a eutrophic condition, and enhanced the urban river microbial populations. Meanwhile, the rapid urbanization tends to decrease the overall habitat heterogeneity, and imposed stronger homogeneous selection and caused microbial communities biotic homogenization. The mechanisms of biotic homogenization can be attributed to modulating generalist/specialist species and invasion of nonnative species. For instance, the urban river had a greater proportion of fast-growing bacteria, algae, nitrifiers, PAH-degrading bacteria, pathogens, fecal bacteria and antibiotic-resistant bacteria than natural river ecosystems. Overall, urbanization leads to a more uniform river biosphere, causing the extinction of unique local species and a subsequent decrease in the regional species pool.

microbiology↗

A neurogenetic toolkit to decode Anopheles gambiae olfaction

The African malaria mosquito Anopheles gambiae exhibits a strong innate sensory drive to seek out human scent. To detect human odorants, An. gambiae uses olfactory sensory neurons (OSNs) that can be divided into different classes by unique repertoires of chemoreceptor gene expression. We applied CRISPR-Cas9-mediated T2A-In Frame Fusions and the QF2/QUAS system to gain genetic access to specific OSN subsets in An. gambiae expressing the chemoreceptor genes Ir25a, Ir76b, Gr22 and orco. We first optimized methods to generate cell-type specific QF2 driver and QUAS responder lines to map expression patterns of these chemoreceptors across mosquito sensory appendages. We next applied transcuticular calcium imaging to record neurophysiological responses to select human-related odorants for each OSN class. This neurogenetic toolkit tiling OSN subsets in An. gambiae, including those responsive to CO2, stands to support systematic efforts to decode olfaction in this prolific disease vector at high-resolution to combat malaria.

neuroscience↗

ccTCM: a quantitative component and compound platform for promoting the research of traditional Chinese medicine

Traditional Chinese medicine (TCM) databases play a vital role in bridging the gap between TCM and modern medicine, as well as in promoting the popularity of TCM. Elucidating the bioactive ingredients of Chinese medicinal materials is key to TCM modernization and new drug discovery. However, one drawback of current TCM databases is the lack of quantitative data on the constituents of Chinese medicinal materials. Herein, we present ccTCM, a web-based platform designed to provide a component and compound-content-based resource on TCM and analysis services for medical experts. In terms of design features, ccTCM combines resource distribution, similarity analysis, and molecular-mechanism analysis to accelerate the discovery of bioactive ingredients in TCM. ccTCM contains 273 Chinese medicinal materials commonly used in clinical settings, covering 29 functional classifications. By searching and comparing, we finally adopted 2043 studies, from which we collected the compounds contained in each TCM with content greater than 0.001%, and a total of 1 449 were extracted. Subsequently, we collected 40767 compound-target pairs by integrating multiple databases. Taken together, ccTCM is a versatile platform for that can be used by TCM scientists to perform scientific and clinical TCM studies based on quantified ingredients of Chinese medicinal materials. ccTCM is freely accessible at http://www.cctcm.org.cn.

bioinformatics↗

CAVE: Connectome Annotation Versioning Engine

Advances in Electron Microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create new annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses. For analysis, users require immediate and reproducible access to this constantly changing and expanding data landscape. Here, we present the Connectome Annotation Versioning Engine (CAVE), a computational infrastructure for immediate and reproducible connectome analysis in up-to petascale datasets ([~]1mm3) while proofreading and annotating is ongoing. For segmentation, CAVE provides a distributed proofreading infrastructure for continuous versioning of large reconstructions. Annotations in CAVE are defined by locations such that they can be quickly assigned to the underlying segment which enables fast analysis queries of CAVEs data for arbitrary time points. CAVE supports schematized, extensible annotations, so that researchers can readily design novel annotation types. CAVE is already used for many connectomics datasets, including the largest datasets available to date.

neuroscience↗

Physicochemical Targeting of Lipid Nanoparticles to the Lungs Induces Clotting: Mechanisms and Solutions

Lipid nanoparticles (LNPs) have become the dominant drug delivery technology in industry, holding the promise to deliver RNA to up- or down-regulate any protein of interest. LNPs have been targeted to specific cell types or organs by physicochemical targeting, in which LNPs lipid compositions are adjusted to find mixtures with the desired tropism. In a popular approach, physicochemical targeting is accomplished by formulating with charged lipids. Negatively charged lipids localize LNPs to the spleen, and positively charged lipids to the lungs. Here we found that lung-tropic LNPs employing cationic lipids induce massive thrombosis. We demonstrate that thrombosis is induced in the lungs and other organs, and greatly exacerbated by pre-existing inflammation. This clotting is induced by a variety of formulations with cationic lipids, including LNPs and non-LNP nanoparticles. The mechanism depends on the LNPs binding to fibrinogen and inducing platelet and thrombin activation. Based on these mechanisms, we engineered multiple solutions which enable positively charged LNPs to target the lungs while not inducing thrombosis. Our findings implicate thrombosis as a major barrier that blood erects against LNPs with cationic components and illustrate how physicochemical targeting approaches must be investigated early for risks and re-engineered with a careful understanding of biological mechanisms.

bioengineering↗

Characterization of Tumor-Associated Endothelial Cells and the Development of a Prognostic Model in Pancreatic Ductal Adenocarcinoma

BackgroundPancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by a complex tumor microenvironment. Angiogenesis is of paramount importance in the proliferation and metastasis of PDAC. However, currently, there are no well-defined biomarkers available to guide the prognosis and treatment of PDAC. ResultsIn this study, we investigated the interactions between tumor-associated endothelial cells (TAECs) and tumor cells in PDAC, and identified a specific subset of TAECs characterized by high expression of COL4A1. COL4A1+ endothelial cells interact with tumor cells through the COLLAGEN signaling pathway to promote tumor cell proliferation, migration, and invasion. We also observed activation of HOXD9 in COL4A1+ endothelial cells. Based on these findings, we developed a prognostic model called TaEMS, which accurately predicts patient prognosis. TaEMS identified high-risk patients enriched in cell cycle-related pathways and low-risk patients enriched in focal adhesions, smooth muscle regulation, and immune pathways. Moreover, high-risk patients displayed a reduced level of immune cell infiltration, indicating the presence of a "cold tumor" phenotype. ConclusionsOverall, our study uncovered an intricate crosstalk between TAECs and tumor cells in PDAC, emphasizing the role of HOXD9 and highlighting the potential of TaEMS as a prognostic biomarker for precise therapies.

cancer biology↗

Autoencoder-transformed transcriptome improves genotype-phenotype association studies

Transcriptome-wide association study (TWAS) is an emerging model leveraging gene expressions to direct genotype-phenotype association mapping. A key component in TWAS is the prediction of gene expressions; and many statistical approaches have been developed along this line. However, a problem is that many genes have low expression heritability, limiting the performance of any predictive model. In this work, hypothesizing that appropriate denoising may improve the quality of expression data (including heritability), we propose AE-TWAS, which adds a transformation step before conducting standard TWAS. The transformation is composed of two steps by first splitting the whole transcriptome into co-expression networks (modules) and then using autoencoder (AE) to reconstruct the transcriptome data within each module. This transformation removes noise (including nonlinear ones) from the transcriptome data, paving the path for downstream TWAS. We showed two inspiring properties of AE-TWAS: (1) After transformation, the transcriptome data enjoy higher expression heritability at the low-heritability spectrum and possess higher connectivity within the modules. (2) The transferred transcriptome indeed enables better performance of TWAS; and moreover, the newly formed highly connected genes (i.e., hub genes) are more functionally relevant to diseases, evidenced by their functional annotations and overlap with TWAS hits.

bioinformatics↗

Sorcin-STAT3-Serpin E1/CCL5 axis can be the trigger of pancreatic cancer-associated new-onset diabetes

A rise in blood glucose is the early warning signs of underlying pancreatic cancer (PC), which could be the externalization of genetic events in PC progression. But there is still a vacancy in the field of mechanism research on pancreatic cancer-associated new-onset diabetes (PCAND). Using siRNA-mediated gene knockdown in vitro, we made MIN6 cells incubated with conditioned media from transfected PC cells, and detected its response. Immunological techniques were used to explore the interaction between sorcin and STAT3. Human cytokine array was performed to explore the inflammatory cytokines downstream of sorcin. In the present study, we have identified a PCAND driver gene SRI. In PC cells, sorcin and STAT3 form a positive feedback loop to enhance the transcription of serpin E1 and CCL5, which can impair nearby islet {beta}-cells, likely by activating the p38 pathway. In 88 biopsies, expression of sorcin was elevated in PC tissues, especially so in PCAND patient samples. Furthermore, clinical-SRI gene combination model can better distinguish PCAND from T2DM, and serpin E1 level is higher in the peripheral blood samples from PCAND than T2DM. Thus, Sorcin could be the key driver in PCAND, and figuring out sorcin-STAT3-serpin E1/CCL5 signaling axis can help us better understand the pathogenesis of PCAND and identify potential biomarkers. Statement of significanceThis study mapped out a novel sorcin-STAT3-Serpin E1/CCL5 signaling axis in pancreatic cancer cells, which explains how early pre-symptomatic pancreatic cancer may coincide with new-onset diabetes in some patients.

cancer biology↗

BL-Hi-C reveals the 3D genome structure of Brassica crops with high efficiency and sensitivity

High-throughput chromatin conformation capture (Hi-C) technologies can be used to investigate the three-dimensional genomic structure of plants. However, complex protocol and high background noise in Hi-C hinder its practical application in plant 3D genomics. Here, we took the approach of modified Bridge Linker Hi-C technology (BL-Hi-C) to explore plant 3D landscape. We modified the BL-Hi-C method by simplifing nuclei extraction step. By using Brassica rapa and Brassica oleracea, BL-Hi-C showed higher signal value and lower background noise than Hi-C. The high sensitivity of BL-Hi-C was further demonstrated by its capacity to identify gene loops involving BrFLC1, BrFLC2 and BrFLC3 which were undetectable in Hi-C. BL-Hi-C also showed promising performance with input as low as 100 mg leaf tissue. By analyzing of the generated data from BL-Hi-C, we found that the simulated 3D genome structure of B. rapa leaf cells was Bouquet configuration. Our results showed that the modified BL-Hi-C is a powerful tool for the investigation of plants genomic organization, gene regulation, and genome assembly. IN A NUTSHELL Background3D genome structure play a critical role in regulating spatiotemporal gene expression. However, there is a lack of simple, efficient and sensitive Hi-C technique in plants. QuestionHow to study plant 3D genomics more simple and efficientHow to detect plant chromatin loops more sensitive? FindingsWe showed that BL-Hi-C is more simple, efficient and sensitive than coventional Hi-C by using Brassica rapa and Brassica oleracea. Furthermore, BL-Hi-C demonstrated its high sensitivity by detecting gene loops involving BrFLC1, BrFLC2, and BrFLC3 which could not be detected by Hi-C. In addition, BL-Hi-C demonstrated promising performance with inputs as low as 100 mg leaf tissue. By analyzing BL-Hi-C data, we found that the simulated 3D genome structure of B. rapa leaf cells was Bouquet configuration. Next stepsHow chromatin loops are formed and regulated gene expression are key questions to be answered in plants. Our dataset of BL-Hi-C will enable future investigations to improve our understanding of chromatin loops.

genomics↗

Genome editing induces the transfer of mitochondrial DNA into the nuclear genome

Mitochondria serve as the cellular powerhouse, and their distinct DNA makes them a prospective target for gene editing to treat genetic disorders. However, the impact of genome editing on mitochondrial DNA (mtDNA) stability remains a mystery. Our study reveals previously unknown risks of genome editing that both nuclear and mitochondrial editing cause broad transfer of mitochondrial DNA segments into the nuclear genome in various cell types including human cell lines, primary T cells, retinal cells, and mouse embryos. Furthermore, drug-induced mitochondrial stresses and mtDNA breaks exacerbate this transfer of mtDNA into the nuclear genome. Notably, we observe that the newly developed mitochondrial base editor DdCBE can also cause widespread mtDNA integrations. However, we provide a practical solution to suppress the transfer of mtDNA by co-expressing TREX1 or TREX2 exonucleases during DdCBE editing. These findings also shed light on the origins of mitochondrial-nuclear DNA segments.

genomics↗

AMPK targets PDZD8 to trigger carbon source shift to glutamine

The shift of carbon utilisation from glucose to other nutrients is a fundamental metabolic adaptation to cope with the decreased glucose oxidation during fasting or starvation1. AMP-activated protein kinase (AMPK) plays crucial roles in manifesting physiological benefits accompanying glucose starvation or calorie restriction2. However, the underlying mechanisms are unclear. Here, we show that low glucose-induced activation of AMPK plays a decisive role in the shift of carbon utilisation from glucose to glutamine. We demonstrate that endoplasmic reticulum (ER)-localised PDZD8, which we identify to be a new substrate of AMPK, is required for the glucose starvation-promoted glutaminolysis. AMPK phosphorylates PDZD8 at threonine 527 (T527), and promotes it to interact with and activate the mitochondrial glutaminase 1 (GLS1), a rate-limiting enzyme of glutaminolysis3-5, and as a result the ER-mitochondria contact is strengthened. In vivo, PDZD8 enhances glutaminolysis, and triggers mitohormesis that is required for extension of lifespan and healthspan in Caenorhabditis elegans subjected to glucose starvation or caloric restriction. Muscle-specific re-introduction of wildtype PDZD8, but not the AMPK-unphosphorylable PDZD8-T527A mutant, to PDZD8-/- mice is able to rescue the increase of glutaminolysis, and the rejuvenating effects of caloric restriction in aged mice, including grip strength and running capacity. Together, these findings reveal an AMPK-PDZD8-GLS1 axis that promotes glutaminolysis and executes the anti-ageing effects of calorie restriction by promoting inter-organelle crosstalk between ER and mitochondria.

cell biology↗

T2T-YAO: a Telomere-to-telomere Assembled Diploid Reference Genome for Han Chinese

Since its initial release in 2001, the human reference genome has been continuously improved in both continuity and accuracy, and the recently-released telomere-to-telomere version--T2T-CHM13--reaches its top quality after 20 years of effort. However, T2T-CHM13 does not represent an authentic diploid human genome, but rather one derived from a simplified, nearly homozygous genome of a hydatidiform mole cell line. To address this limitation and provide an alternative pertinent to the Chinese population, the largest ethnic group in the world, we have assembled a complete diploid human genome of a male Han Chinese, T2T-YAO, which includes telomere-to-telomere assemblies for all the 22+X+M and 22+Y chromosomes in his two haploids inherited separately from his parents. Both haplotypes contain no artificial sequences or model nucleotides and possess a high quality comparable to CHM13, with fewer than one error per [~]14 Mb. Derived from the individual who lives in the aboriginal region of Han Chinese, T2T-YAO shows clear ancestry and potential genetic continuity from the ancient ancestors of the Han population. Each haplotype of T2T-YAO possesses [~]340 Mb exclusive sequences and [~]3100 unique genes as compared to CHM13, and their genome sequences show greater genetic distance to CHM13 than to each other in terms of nucleotide polymorphism and structural variations. The construction of T2T-YAO would serve as a high-quality diploid reference that enables precise delineation of genomic variations in a haplotype-sensitive manner, which could advance our understandings in human evolution, hereditability of diseases and phenotypes, especially within the context of the unique variations of the Chinese population.

genetics↗

The super-pangenome of Populus unveil genomic facets for adaptation and diversification in widespread forest trees

Understanding the underlying mechanisms between genome evolution and phenotypic and adaptive innovations is a key goal of evolutionary studies. Poplars are the worlds most widely distributed and cultivated trees, with extensive phenotypic diversity and environmental adaptability. Here we report a genus-level super-pangenome of 19 Populus genomes. After integrating pan-genomes with transcriptomes, methylomes and chromatin accessibility mapping, we reveal that the evolutionary fate of pan-genes and duplicated genes are largely associated with local genomic landscapes of regulatory and epigenetic architectures. Further comparative genomic analyses enabled to identify 142,202 structural variations (SVs) across species, which overlap with substantial genes and play key roles in both phenotypic and adaptive divergence. We experimentally validated a [~]180 bp presence/absence variant located in the promoter of the CUC2 gene, which contributed critically to leaf serration divergence between species. Together, this first super-pangenome resource in forest trees will not only accelerate molecular functional studies and genetic breeding of this globally important tree genus, but also lays a foundation for our understanding of tree biology.

evolutionary biology↗

Arabidopsis Transcription Factor WRKY45 Confers Cadmium Tolerance via Activating PCS1 and PCS2 Expression

Cadmium (Cd) has long been recognized as toxic pollutant to crops worldwide. The biosynthesis of glutathione-dependent phytochelatin plays crucial roles in the detoxification of Cd in plants. However, its regulatory mechanism remains elusive. Here, we revealed that Arabidopsis transcription factor WRKY45 confers Cd tolerance via promoting the expression of PC synthesis-related genes PCS1 and PCS2, respectively. Firstly, we found that Cd stress induces the transcript levels of WRKY45 and its protein abundance. Accordingly, in contrast to wild type Col-0, the increased sensitivity to Cd is observed in wrky45 mutant, while overexpressing WRKY45 plants are more tolerant to Cd. Secondly, quantitative real-time PCR revealed that the expression of AtPCS1 and AtPCS2 is stimulated in overexpressing WRKY45 plants, but decreased in wrky45 mutant. Thirdly, WRKY45 promotes the expression of PCS1 and PCS2, electrophoresis mobility shift assay analysis uncovered that WRKY45 directly bind to the W-box cis-element of PCS2 promoter. Lastly, the overexpression of WRKY45 in Col-0 leads to more accumulation of PCs in Arabidopsis, and the overexpression of PCS1 or PCS2 in wrky45 mutant plants rescues the phenotypes induced by Cd stress. In conclusion, our results show that AtWRKY45 positively regulate Cd tolerance in Arabidopsis via activating PCS1 and PCS2 expression. Environmental implicationAccumulation of cadmium (Cd) in soils poses a threat to crop productivity and food safety. It has been revealed that phytochelatin (PC) plays an essential role in plants to alleviate Cd toxicity, yet the regulatory mechanisms governing its expression remain unclear. We have demonstrated that the Arabidopsis transcription factor WRKY45 directly activates the expression of PCS1 and PCS2, which encode PC synthase, thereby increasing the content of PC and enhancing Arabidopsis tolerance to Cd stress. These findings offer insights into precise regulation strategies for crop Cd tolerance via modulation of WRKY45 homologue in crops.

molecular biology↗

Using UAV-based temporal spectral indices to dissect changes in the stay green trait in wheat

Stay green (SG) in wheat, a beneficial trait for increasing yield and stress resistance, needs to be supported by analysis of the underlying genetic basis. Spectral reflectance indices (SIs) provide non-destructive tools to evaluate crop temporal senescence. However, few SI-based SG quantification pipelines for analyzing diverse wheat panels in the field are available. Here, we first applied SIs to monitor the senescence dynamics of 565 diverse wheat accessions from anthesis to maturation stages during two field seasons. Based on over 12,000 SIs data set, four SIs (NDVI, GNDVI, NDRE and OSAVI) were selected to develop relative stay green scores (RSGS) and the senescence of wheat populations occurs mainly at four developmental stages stage 1 (S1) to S4, accounting for the final SG indicators. A RSGS-based genome-wide association study identified 47 high-confidence quantitative trait loci (QTL) harboring 3,079 SNPs significantly associated with RSGS and 1,085 corresponding candidate genes in the two seasons; 15 QTL overlapped or were adjacent to known SG-related QTL or genes and the remaining QTL were novel. Finally, we selected three superior candidate genes (TraesCS6B03G0356400, TraesCS2B03G1299500, and TraesCS2A03G1081100) as examples by transcriptomes, gene annotation, and gene-based association analysis for further analysis and found that utilization of superior SG-related variation in China gradually increased following the Green Revolution. The study provides a useful reference for further SG-related gene discovery of favorable variations in diverse wheat panels.

genetics↗

An expression-directed linear mixed model (edLMM) discovering low-effect genetic variants

Detecting genetic variants with low effect sizes using a moderate sample size is difficult, hindering downstream efforts to learn pathology and estimating heritability. In this work, by utilizing informative weights learned from training genetically predicted gene expression models, we formed an alternative approach to estimate the polygenic term in a linear mixed model (LMM). Our LMM estimates the genetic background by incorporating their relevance to gene expression. Our protocol, expression-directed linear mixed model (edLMM), enables the discovery of subtle signals of low-effect variants using moderate sample size. By applying edLMM to cohorts of around 5,000 individuals with either binary (WTCCC) or quantitative (NFBC1966) traits, we demonstrated its power gain at the low-effect end of the genetic etiology spectrum. In aggregate, the additional low-effect variants detected by edLMM substantially improved estimation of missing heritability. edLMM moves precision medicine forward by accurately detecting the contribution of low-effect genetic variants to human diseases.

genetics↗

Exploiting the therapeutic vulnerability of IDH-mutant gliomas with zotiraciclib

Isocitrate dehydrogenase (IDH)-mutant gliomas have distinctive metabolic and biological traits that may render them susceptible to targeted treatments. Here, by conducting a high-throughput drug screen, we pinpointed a specific susceptibility of IDH-mutant gliomas to zotiraciclib (ZTR). ZTR exhibited selective growth inhibition across multiple IDH-mutant glioma in vitro and in vivo models. Mechanistically, ZTR at low doses suppressed CDK9 and RNA Pol II phosphorylation in IDH-mutant cells, disrupting mitochondrial function and NAD+ production, causing oxidative stress. Integrated biochemical profiling of ZTR kinase targets and transcriptomics unveiled that ZTR-induced bioenergetic failure was linked to the suppression of PIM kinase activity. We posit that the combination of mitochondrial dysfunction and an inability to adapt to oxidative stress resulted in significant cell death upon ZTR treatment, ultimately increasing the therapeutic vulnerability of IDH-mutant gliomas. These findings prompted a clinical trial evaluating ZTR in IDH-mutant gliomas towards precision medicine (NCT05588141). HighlightsO_LIZotiraciclib (ZTR), a CDK9 inhibitor, hinders IDH-mutant glioma growth in vitro and in vivo. C_LIO_LIZTR halts cell cycle, disrupts respiration, and induces oxidative stress in IDH-mutant cells. C_LIO_LIZTR unexpectedly inhibits PIM kinases, impacting mitochondria and causing bioenergetic failure. C_LIO_LIThese findings led to the clinical trial NCT 05588141, evaluating ZTR for IDH-mutant gliomas. C_LI

cancer biology↗