Biology subjects

Qu, H.

Publications and source records attributed to Qu, H..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

EryDB: a transcriptomic profile database for erythropoiesis and erythroid-related diseases

Erythropoiesis is a finely regulated and complex process that involves multiple transformations from hematopoietic stem cells to mature red blood cells at hematopoietic sites from the embryonic to the adult stages. Investigations into its molecular mechanisms have generated a wealth of expression data, including bulk and single-cell RNA sequencing data. A comprehensively integrated and well-curated erythropoiesis-specific database will greatly facilitate the mining of gene expression data and enable large-scale research of erythropoiesis and erythroid related diseases. Here, we present EryDB, an open-access and comprehensive database dedicated to the collection, integration, analysis, and visualization of transcriptomic data for erythropoiesis and erythroid-related diseases. Currently, the database includes expertly curated quality-assured data of 3,803 samples and 1,187,119 single cells derived from 107 public studies of three species (Homo sapiens, Mus musculus, and Danio rerio), nine tissue types, and five diseases. EryDB provides users with the ability to not only browse the molecular features of erythropoiesis between tissues and species, but also perform computational analyses of single-cell and bulk RNA sequencing data, thus serving as a convenient platform for customized queries and analyses. EryDB v1.0 is freely accessible at https://ngdc.cncb.ac.cn/EryDB/home.

bioinformatics↗

bioRxiv2023

INTEGRATED GLOBAL CHICKEN REFERENCE PANEL FROM 13,187 CHICKEN GENOMES

Chickens are a crucial source of protein for humans and a popular model animal for bird research. Despite the emergence of imputation as a reliable genotyping strategy for large populations, the lack of a high-quality chicken reference panel has hindered progress in chicken genome research. To address this issue, here we introduce the first phase of the 100 K Global Chicken Reference Panel Project (100 K GCRPP). The project includes 13,187 samples and provides services for varied applications on its website (http://farmrefpanel.com/GCRP/). Currently, two panels are available: a Comprehensive Mix Panel (CMP) for domestication diversity research and a Commercial Breed Panel (CBP) for breeding broilers specifically. Evaluation of genotype imputation quality showed that CMP had the highest imputation accuracy compared to imputation using existing chicken panel in animal SNPAtlas, whereas CBP performed stably in the imputation of commercial populations. Additionally, we found that genome-wide association studies using GCRP-imputed data, whether on simulated or real phenotypes, exhibited greater statistical power. In conclusion, our study indicates that the GCRP effectively fills the gap in high-quality reference panels for chickens, providing an effective imputation platform for future genetic and breeding research.

bioinformatics↗

bioRxiv2023

Histone marks enable formation of immiscible phase-separated chromatin compartments

Eukaryotic chromatin is organized into compartments for gene expression regulation, but the underlying mechanisms remain unclear. Here, we demonstrate that multivalent H3K27me3 and its reader, CBX7-PRC1 complex, regulate facultative heterochromatin via a phase separation mechanism, similar to constitutive heterochromatin1. Facultative and constitutive heterochromatin represent distinct, coexisting condensates in nuclei. In vitro, H3K27me3- and H3K9me3-marked nucleosomal arrays and their reader complexes can phase separate into immiscible condensates that are analogous to the relationship between facultative and constitutive heterochromatin in vivo. Moreover, overexpression of CBX7-PRC1 causes aberrant chromatin compartmentalization in vivo as demonstrated by H3K9me3 CUT&Tag and up-regulation of genes related to cancer such as acute myeloblastic leukemia (AML). CBX7 inhibitor effectively inhibits cancer cell proliferation possibly through phase separation-mediated compartment reorganization. Our data demonstrated how the specificity of compartmentalization is achieved based on the formation of immiscible phase-separated condensates, and offer novel epigenetic mechanistic insights into tumor development.

biochemistry↗

bioRxiv2023

Trojan horse virus delivering CRISPR-AsCas12f1 controls plant bacterial wilt caused by Ralstonia solanacearum

Plant bacterial wilt caused by the Ralstonia solanacearum species complex results in huge food and economic losses. Accordingly, the development of an effective control method for this disease is urgently required. Traditional lytic phage biocontrol methods have inherent limitations. However, filamentous phages, which do not lyse host bacteria and exert minimal burden, offer a potential solution. A filamentous phage RSCq that infects R. solanacearum was isolated in this study through genome mining. We constructed engineered filamentous phages based on RSCq by employing our proposed approach with a wide applicability to non-model phages, enabling the infection of R. solanacearum in medium and soil and delivering exogenous genes into bacterial cells. Similar to the Greek soldiers hidden within the Trojan horse, CRISPR-AsCas12f1 gene editing system that targets the key virulence regulator gene hrpB was implanted into the engineered phage, generating the engineered phage RSCqCRISPR-Cas. Our findings demonstrated that RSCqCRISPR-Cas could disarm the key "weapon", hrpB, of R. solanacearum, in medium and in plants. Remarkably, pretreatment with RSCqCRISPR-Cas significantly controlled tobacco bacterial wilt, highlighting the potential of engineered filamentous phages as promising biocontrol agents against plant bacterial wilt and other bacterial diseases.

microbiology↗

bioRxiv2023

The ChickenGTEx pilot analysis: a reference of regulatory variants across 28 chicken tissues

Chicken is a valuable model for understanding fundamental biology, vertebrate evolution and diseases, as well as a major source of nutrient-dense and lean-protein-enriched food globally. Although it is the first non-mammalian amniote genome to be sequenced, the chicken genome still lacks a systematic characterization of functional impacts of genetic variants. Here, through integrating 7,015 RNA-Seq and 2,869 whole-genome sequence data, the Chicken Genotype- Tissue Expression (ChickenGTEx) project presents the pilot reference of regulatory variants in 28 chicken tissue transcriptomes, including millions of regulatory effects on primary expression (including protein-coding genes, lncRNA and exon) and post-transcriptional modifications (alternative splicing and 3 untranslated region alternative polyadenylation). We explored the tissue-sharing and context-specificity of these regulatory variants, their underlying molecular mechanisms of action, and their utility in interpreting adaptation and genome-wide associations of 108 chicken complex traits. Finally, we illustrated shared and lineage-specific features of gene regulation between chickens and mammals, and demonstrated how the ChickenGTEx resource can further assist with translating genetic findings across species. One-Sentence SummaryThe ChickenGTEx provides a multi-tissue reference of regulatory variants for chicken genetics and genomics, functional genomics, precision breeding, veterinary medicine, vertebrate evolution and even human biomedicine.

genetics↗

bioRxiv2022

IIIandMe: An Algorithm for Chromosome-scale Haplotype Determination Using Genome-wide Variants of Three Haploid Reproductive Cells

Our recent algorithm, Hapi, infers chromosome-scale haplotypes using genomic data of a small number of single gametes. Its advanced version, IIIandMe, is proposed here to achieve comparable phasing accuracy with as few as three gametes, pushing the analysis to its limit. The new method is validated with simulation and a citrus gamete dataset. The rapid advances in genotyping technologies promise a broad application of IIIandMe in disclosing important genetic information.

bioinformatics↗

bioRxiv2022

Allosteric Regulation of Aptamer Affinity through Mechano-Chemical Coupling

The capacity to precisely modulate aptamer affinity is important for a wide variety of applications. However, most such engineering strategies entail laborious trial-and-error testing or require prior knowledge of an aptamers structure and ligand-binding domain. We describe here a simple and generalizable strategy for allosteric modulation of aptamer affinity by employing a double-stranded molecular clamp that destabilizes aptamer secondary structure through mechanical tension. We demonstrate the effectiveness of the approach with a thrombin-binding aptamer and show that we can alter its affinity by as much as 65-fold. We also show that this modulation can be rendered reversible by introducing a restriction enzyme cleavage site into the molecular clamp domain and describe a design strategy for achieving even more finely-tuned affinity modulation. This strategy requires no prior knowledge of the aptamers structure and binding mechanism and should thus be generalizable across aptamers.

biochemistry↗

bioRxiv2022

VPS9D1-AS1 overexpression amplifies intratumoral TGF-β signaling and promotes tumor cell escape from CD8+ T cell killing in colorectal cancer

Efficacy of immunotherapy is limited in patients with colorectal cancer (CRC) because high expression of tumor-derived transforming growth factor (TGF)-{beta} pathway molecules and interferon (IFN)-stimulated genes (ISGs) promotes tumor immune evasion. Here, we identified a long noncoding RNA (lncRNA), VPS9D1-AS1, which was located in ribosomes and amplified TGF-{beta} signaling and ISG expression. We show that high expression of VPS9D1-AS1 was negatively associated with T lymphocyte infiltration in two independent cohorts of CRC. VPS9D1-AS1 served as a scaffolding lncRNA by binding with ribosome protein S3 (RPS3) and a competing endogenous RNA (ceRNA) to sponge miR-22-5p/514a-3p to increase the translation of TGF-{beta}, TGFBR1, and SMAD1/5/9. VPS9D1-AS1 knockout downregulated OAS1, an ISG gene, which further reduced IFNAR1 levels in tumor cells. Conversely, tumor cells overexpressing VPS9D1-AS1 were resistant to CD8+ T cell killing and lowered IFNAR1 expression in CD8+ T cells. In a conditional overexpression mouse model, VPS9D1-AS1 enhanced tumorigenesis and suppressed the infiltration of CD8+ T cells. Treating tumor-bearing mice with antisense oligonucleotide drugs targeting VPS9D1-AS1 significantly suppressed tumor growth. Our findings indicate that the tumor-derived VPS9D1-AS1/TGF-{beta}/ISG signaling cascade promotes tumor growth and enhances immune evasion and may thus serve as a potential therapeutic target for CRC.

cancer biology↗

bioRxiv2022

Detection of low numbers of bacterial cells in pharmaceutical drug product using Raman Spectroscopy and PLS-DA multivariate analysis.

Sterility testing is a laborious and slow process to detect contaminants present in drug products. Raman spectroscopy is a promising label-free tool to detect microorganisms and thus gaining relevance as future alternative culture-free method for sterility testing in pharmaceutical industry. However, reaching detection limits similar to standard procedures while keeping a high accuracy remains challenging, due to weak bacterial Raman signal. In this work, we show a new non-invasive approach focusing on detect different bacteria in concentrations below 100 CFU/ml within drug product containers using Raman spectroscopy and multivariate data analysis. Even though Raman spectra form drug product with and without bacteria are similar, a partial least squared discriminant analysis (PLS-DA) model shows great performance to distinguish samples with bacteria contaminants in limits below 10 CFU/ml. We use spiked samples with bacteria spores for independent validation achieving a detection accuracy of 99%. Our results indicate a great potential of this rapid, and cost-effective approach to be use in quality control of pharmaceutical industry.

bioengineering↗

bioRxiv2021

The dynamic interactive network of long non-coding RNAs and chromatin accessibility facilitates erythroid differentiation

Erythroid differentiation is a dynamic process regulated by multiple factors, while the interaction between long non-coding RNAs and chromatin accessibility and its influence on erythroid differentiation remains unclear. To elucidate this interaction, we employed hematopoietic stem cells, multipotent progenitor cells, common myeloid progenitor cells, megakaryocyte-erythroid progenitor cells, and erythroblasts from human cord blood as an erythroid differentiation model to explore the coordinated regulatory functions of lncRNAs and chromatin accessibility in erythropoiesis by integrating RNA-Seq and ATAC-Seq data. We revealed that the integrated network of chromatin accessibility and LncRNAs exhibits stage-specific changes throughout the erythroid differentiation process, and that the changes at the EB stage of maturation are dramatic. We identified a subset of stage-specific lncRNAs and transcription factors (TFs) that coordinate with chromatin accessibility during erythroid differentiation, in which lncRNAs are key regulators of terminal erythroid differentiation via a lncRNA-TF-gene network. LncRNA PCED1B-AS1 was revealed to regulate terminal erythroid differentiation by coordinating GATA1 dynamically binding to the chromatin during erythroid differentiation. DANCR, another lncRNA that is highly expressed at the MEP stage, was verified to promote erythroid differentiation by compromising megakaryocyte differentiation and coordinating with chromatin accessibility and TFs, such as RUNX1. Overall, our results identified the interactive network of lncRNAs and chromatin accessibility in erythropoiesis and provide novel insights into erythroid differentiation and abundant resources for further study. Key PointsO_LILncRNAs regulate erythroid differentiation through coordinating with chromatin accessibility. C_LIO_LIThe integrative multi-omics analysis reveals stage-specific interaction network of LncRNAs and chromatin accessibility in erythropoiesis. C_LI

genomics↗

bioRxiv2020

CancerMIRNome: a web server for interactive analysis and visualization of cancer miRNome data

MicroRNAs (miRNAs), which play critical roles in gene regulatory networks, have emerged as promising diagnostic and prognostic biomarkers for human cancer. In particular, circulating miRNAs that are secreted into circulation exist in remarkably stable forms, and have enormous potential to be leveraged as non-invasive biomarkers for early cancer detection. Novel and user-friendly tools are desperately needed to facilitate data mining of the vast amount of miRNA expression data from The Cancer Genome Atlas (TCGA) and large-scale circulating miRNA profiling studies. To fill this void, we developed CancerMIRNome, a comprehensive database for the interactive analysis and visualization of miRNA expression profiles based on 10,998 samples from 33 TCGA projects and 21,993 samples from 40 public circulating miRNome datasets. A series of cutting-edge bioinformatics tools and machine learning algorithms have been packaged in CancerMIRNome, allowing for the pan-cancer analysis of a miRNA of interest across multiple cancer types and the comprehensive analysis of miRNome profiles to identify dysregulated miRNAs and develop diagnostic or prognostic signatures. The data analysis and visualization modules will greatly facilitate the exploit of the valuable resources and promote translational application of miRNA biomarkers in cancer. The CancerMIRNome database is publicly available at http://bioinfo.jialab-ucr.org/CancerMIRNome.

bioinformatics↗

bioRxiv2020

DLDTI: A learning-based framework for identification of drug-target interaction using neural networks and network representation

To elucidate novel molecular mechanisms of known drugs, efficient and feasible computational methods for predicting potential drug-target interactions (DTI) would be of great importance. A novel calculation model called DLDTI was generated for predicting DTI based on network representation learning and convolutional neural networks. The proposed approach simultaneously fuses the topology of complex networks and diverse information from heterogeneous data sources and copes with the noisy, incomplete, and high-dimensional nature of large-scale biological data by learning low-dimensional and rich depth features of drugs and proteins. Low-dimensional feature vectors were used to train DLDTI to obtain optimal mapping space and infer new DTIs by ranking DTI candidates based on their proximity to optimal mapping space. DLDTI achieves promising performance under 5-fold cross-validation with AUC values of 0.9172, which was higher than that of the method based on different classifiers or different feature combination technique. Moreover, biomedical experiments were also completed to validate DLDTIs performance. Consistent with the predicted result, tetramethylpyrazine, a member of pyrazines, reduced atherosclerosis progression and inhibited signal transduction in platelets, via PI3K/Akt, cAMP and calcium signaling pathways. The source code and datasets explored in this work are available at https://github.com/CUMTzackGit/DLDTI

bioinformatics↗

bioRxiv2020

A single-cell transcriptome atlas of the aging human and macaque retina

The human retina is a complex neural tissue that detects light and sends visual information to the brain. However, the molecular and cellular processes that underlie aging primate retina remain unclear. Here, we provide a comprehensive transcriptomic atlas based on 119,520 single cells of the foveal and peripheral retina of humans and macaques covering different ages. The molecular features of retinal cells differed between the two species, suggesting the distinct regional and species specializations of the human and macaque retinae. In addition, human retinal aging occurred in a region- and cell-type- specific manner. Aging of human retina exhibited a foveal to peripheral gradient. MYO9A- rods and a horizontal cell subtype were greatly reduced in aging retina, indicating their vulnerability to aging. Moreover, we generated a dataset showing the cell-type- and region- specific gene expression associated with 55 types of human retinal disease, which provides a foundation to understand the molecular and cellular mechanisms underlying human retinal diseases. Together, these datasets are valuable for understanding the molecular characteristics of primate retina, as well as the molecular regulation of aging progression and related diseases.

neuroscience↗

bioRxiv2020

Extended Application of Genomic Selection to Screen Multi-Omics Data for Prognostic Signatures of Prostate Cancer

Prognostic tests using expression profiles of several dozen genes help provide treatment choices for prostate cancer (PCa). However, these tests require improvement to meet the clinical need for resolving overtreatment which continues to be a pervasive problem in PCa management. Genomic selection (GS) methodology, which utilizes whole-genome markers to predict agronomic traits, was adopted in this study for PCa prognosis. We leveraged The Cancer Genome Atlas (TCGA) database to evaluate the prediction performance of six GS methods and seven omics data combinations, which showed that the Best Linear Unbiased Prediction (BLUP) model outperformed the other methods regarding predictability and computational efficiency. Leveraging the BLUP-HAT method, an accelerated version of BLUP, we demonstrated that using expression data of a large number of disease-relevant genes and with an integration of other omics data (i.e., miRNAs) significantly increased outcome predictability when compared with panels consisting of small numbers of genes. Finally, we developed a novel stepwise forward selection BLUP-HAT method to facilitate searching multi-omics data for predictor variables with prognostic potential. The new method was applied to the TCGA data to derive mRNA and miRNA expression signatures for predicting relapse-free survival of PCa, which were validated in six independent cohorts. This is a transdisciplinary adoption of the highly efficient BLUP-HAT method and its derived algorithms to analyze multi-omics data for PCa prognosis. The results demonstrated the efficacy and robustness of the new methodology in developing prognostic models in PCa, suggesting a potential utility in managing other types of cancer.

bioinformatics↗

bioRxiv2020

Common postzygotic mutational signature in multiple healthy adult tissues related to embryonic hypoxia

Postzygotic mutations are acquired in all of the normal tissues throughout an individuals lifetime and hold clues for identifying mutagenesis causing factors. The process and underlying mechanism of postzygotic mutations in normal tissues is still poorly understood. In this study, we investigated postzygotic mutation spectra in healthy individuals by optimized ultra-deep exome sequencing of time series samples from the same volunteer and samples from different individuals. In cells of blood, sperm, and muscle, we resolved three common types of mutational signature. Two of them are known to represent clock-like mutational processes, and their proportions in mutation profiles associated with polymorphisms of epigenetic regulation genes, suggesting the contribution of personal genetic backgrounds to underlying biological process. Notably, the third signature, characterized by C>T transitions at GpCpN sites, tends to be a feature of diverse normal tissues. Mutations of this type were likely to occur early in embryo development even before the tissue differentiation, as indicated by their relatively high allele frequencies, sharing variants between multiple tissues, and lacking of age-related accumulation. Almost all tumors shown in public datasets did not have this signature detected except for 19.6% of clear cell renal cell carcinoma samples, which featured by activation of the hypoxia-induced signaling pathway. Moreover, in vitro activation of HIF signaling pathway successfully introduced the corresponding mutation profile of this signature in a culture-expanded human embryonic stem cell line. Therefore, embryonic hypoxia may explain this novel signature across multiple normal tissues. Our study suggest hypoxic conditions in the early stage of embryo development may be a crucial factor for the C>T transitions at GpCpN sites and individual genetic background also related to shaping human postzygotic mutation profiles.

genetics↗

bioRxiv2020

Measuring aptamer folding energy using a molecular clamp

Folding energy offers a useful metric for characterizing the stability and function of aptamers. However, experimentally measuring the folding energy is challenging and there is currently no general technique to measure this parameter directly. In this work, we present a simple approach for measuring aptamer folding energy. First, the aptamer is stretched under equilibrium conditions with a double-stranded DNA "molecular clamp" that is coupled to the aptamer ends. We then measure the total internal energy of stressed DNA molecules using time-lapse gel electrophoresis and compare the folding and unfolding behavior of molecular clamp-stressed molecules that incorporate either the aptamer or unstructured random single-stranded DNA in order to derive the aptamer folding energy. Using this approach, we measured a folding energy of 10.40 kJ/mol for the HD22 thrombin aptamer, which is consistent with other predictions and estimates. We also analyzed a simple hairpin structure, generating a folding energy result of 9.05 kJ/mol, consistent with the value predicted by computational models (9.24 kJ/mol). We believe our strategy offers an accessible and generalizable approach for obtaining such measurements with virtually any aptamer.

biophysics↗

bioRxiv2018

Munc18-1 catalyzes neuronal SNARE assembly by templating SNARE association

Sec1/Munc18-family (SM) proteins are required for SNARE-mediated membrane fusion, but their mechanism(s) of action remain controversial. Using single-molecule force spectroscopy, we found that the SM protein Munc18-1 catalyzes step-wise zippering of three synaptic SNAREs (syntaxin, VAMP2, and SNAP-25) into a four-helix bundle. Catalysis requires formation of an intermediate template complex in which Munc18-1 juxtaposes the N-terminal regions of the SNARE motifs of syntaxin and VAMP2, while keeping their C-terminal regions separated. Next, SNAP-25 binds the templated SNAREs to form a partially-zippered SNARE complex. Finally, full zippering displaces Munc18-1. Munc18-1 mutations modulate the stability of the template complex in a manner consistent with their effects on membrane fusion, indicating that chaperoned SNARE assembly is essential for exocytosis. Two other SM proteins, Munc18-3 and Vps33, similarly chaperone SNARE assembly via a template complex, suggesting that SM protein mechanism is conserved.

biophysics↗

bioRxiv2018

Inference of Chromosome-length Haplotypes Using Genomic Data of Three to Five Single Gametes

Knowledge of chromosome-length haplotypes will not only advance our understanding of the relationship between DNA and phenotypes, but also promote a variety of genetic applications. Here we present Hapi, an innovative method for chromosomal haplotype inference using only 3 to 5 gametes. Hapi outperformed all existing haploid-based phasing methods in terms of accuracy, reliability, and cost efficiency in both simulated and real gamete datasets. This highly cost-effective phasing method will make large-scale haplotype studies feasible to facilitate human disease studies and plant/animal breeding. In addition, Hapi can detect meiotic crossovers in gametes, which has promise in the diagnosis of abnormal recombination activity in human reproductive cells.

bioinformatics↗