Biology subjects

Qin, X.

Publications and source records attributed to Qin, X..

At least 73 records · Page 4Linked to original sources

bioRxiv2022

Treg cells drive MYCN-mediated immunosuppression and tumor aggressiveness in high-risk neuroblastoma

Solid tumors, especially those with aberrant MYCN activation, harbor an immunosuppressive microenvironment to fuel malignant growth and trigger treatment resistance1,2, yet the underlying mechanisms are elusive and effective strategies to tackle this challenge are lacking. Here we demonstrated the crucial role of T regulatory (Treg) cells in MYCN-mediated immune repression and tumor aggression using high-risk neuroblastoma (NB) as a model system. Human MYCN-activated NB attracts CD4+ Treg cells, which are also found enriched in MYCN-high primary patient samples. Zebrafish MYCN-overexpressing neural crests recruit Cd4+ cells before tumor formation and induce an immunosuppressive microenvironment, thereby promoting tumor onset and progression. Strikingly, disruption of Treg cells through depletion of forkhead box protein 3a restores anti-tumor immunity and impairs NB development. Together, our studies establish Treg cells as the key driver of MYCN-mediated immunosuppression and tumor aggressiveness, providing mechanistic insights and therapeutic implications.

cancer biology↗

bioRxiv2022

The Potential Regulation of A-to-I RNA editing on Genes in Parkinson's Disease

Parkinsons disease (PD), the second most common neurodegenerative disorder, was characterized by alpha-synuclein pathology and dopaminergic neuron degeneration. In previous studies, multiple genes have been demonstrated to involve in the regulations of these two processes, including EIF2AK2, AGO2, MCL1, EEF1A1, and AIMP2. The molecular mechanisms to mediate the transcript diversity of these genetic biomarkers were important to understand neurodegenerative pathogenesis and helpful for treatment design. In this study, we analyzed 372 PD patients to identify 9,897 A-to-I RNA editing events probably responsible for the controls of 6,286 genes. Due to the most potentially trans-regulatory associations between RNA editing events and genes, we tried to explain one possible pathway from the view of disturbed miRNA regulations on genes due to A-to-I RNA editing events. Specifically, we identified 72 RNA editing events probably interfering in miRNA regulations on their host genes, eight RNA editing events possibly altering miRNA competitions between their host genes and 1,146 other genes, and one RNA editing event modifying miRNA seed regions to potentially disturb its regulations on four genes. All the analyses revealed 25 RNA editing biomarkers in Parkinsons pathogenesis through probably interfering in miRNA degradations on 133 PD-related genes.

bioinformatics↗

bioRxiv2022

Genome-wide identification of microsatellite markers and their application in genetic studies of wolfberry (Lycium barbarum)

The wolfberry (Lycium barbarum) has been an important traditional Chinese food and medicine for hundreds of years. However, few microsatellite markers have been developed for assessing the genetic diversity and genetic linkage maps among Lycium species in genetic research. In the present study, a total of 397,558 microsatellite loci were identified from whole wolfberry genome sequences with an overall density of 212.1 Mb/SSRs. Dinucleotide microsatellites were the most abundant type, representing 58.26% of the total microsatellite loci, followed by tri-, penta-, hexa-, and tetranucleotide. The AT motifs were the most abundant of all nucleotide repeat motifs, accounting for 44.52%. A set of 600 primer pairs were synthesized and preliminarily screened among four wolfberry accessions. Of these, 277 primer pairs were selected as polymorphic markers. In total, 22 highly polymorphic SSR markers were selected for the characterization of genetic diversity among 37 wolfberry accessions. A total of 323 alleles were detected with an average of 14.7 alleles per marker. The polymorphic information content (PIC) values ranged from 0.612 to 0.911. The dendrogram revealed that the phylogenetic relationships among these wolfberry accessions were consistent with their genetic background. Thus, the large number of genome-wide microsatellite markers developed from the wolfberry genome provides a valuable resource for genetic diversity, genetic map construction, quantitative trait locus (QTL) mapping, and marker-assisted selection breeding in Lycium species.

molecular biology↗

bioRxiv2022

Spatial-CITE-seq: spatially resolved high-plex protein and whole transcriptome co-mapping

We present spatial-CITE-seq for high-plex protein and whole transcriptome co-mapping, which was firstly demonstrated for profiling 189 proteins and transcriptome in multiple mouse tissue types. It was then applied to human tissues to measure 273 proteins and transcriptome that revealed spatially distinct germinal center reaction in tonsil and early immune activation in skin at the COVID-19 mRNA vaccine injection site. Spatial-CITE-seq may find a range of applications in biomedical research.

genomics↗

bioRxiv2022

Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program

The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic change over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). The MVP was divided into five birth cohorts (N-range=123,888 [born from 1943-1947] to 136,699 [born from 1948-1953]). Groups of participants were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP+HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010<Cohens d<0.259, p<7.80x10-4). Conversely, HARE-assigned East Asians showed an increase in European ancestry proportion over time. In GWAS of height using HARE assignments, genomic inflation due to population stratification was prevalent across all birth cohorts (linkage disequilibrium score regression intercept=1.08{+/-}0.042). The 1kGP+HGDP-based ancestry assignment significantly reduced the population stratification (mean intercept reduction=0.045{+/-}0.007, p<0.05) confounding in the GWAS statistics. This study provides a comprehensive characterization of ancestry diversity of the MVP cohort over time and highlights that more refined modeling of genetic diversity (e.g., the 1kGP+HGDP-based ancestry assignment) can more accurately capture the polygenic architecture of traits and diseases that could be affected by population stratification.

genomics↗

bioRxiv2021

MAL suppresses OSCC tumorigenesis by maintaining epithelial cell differentiation

Oral squamous cell carcinoma (OSCC) is widely recognized as an optimal model for precise medicine guided molecular biomarkers of cancer, however, few clinical practices were applied till now. Based on the data from our own studies and published papers, it was found that the expression of MAL was significantly decreased in epithelial cancer as compared with normal tissues, and exhibited a opposite association with pathological grade. To study the molecular events related to deficiency of MAL during carcinogenesis, occurrence and development, a Mal knockout mouse model was constructed and consistently reproduced and bred. The Mal knockout mice are highly vulnerable to tumor induction by carcinogen of 4NQO, evidenced by their extremely earlier carcinogenesis, higher incidence, and more aggressive growth. Analysis of scRNA-seq data indicated that Mal knockout mice lost the ability in maintaining epithelial cell differentiation and get more prone to carcinogen with a remarkably higher incidence of epithelial malignancy. Further analyses identified putative co-functional genes of MAL, including DSG1, AQP3 and S100A8, which are key factors in maintaining epithelial cell differentiation. To conclude, the current study exhibits the clinical significance and explains the tumor suppressing function of MAL. The results also suggest the potential of MAL and its co-functional genes being biomarkers for designing the prevention and/or differentiation therapy strategies in OSCC. SignificanceMAL is found to be strongly opposite with tumor pathological grade from clinical and in vivo studies in OSCC. We propose MAL and its co-functional genes, including DSG1, AQP3 and S100A8, as key factors in maintaining epithelial cell differentiation and are valuable targets for designing prevention and differentiation therapy strategies in OSCC.

cell biology↗

bioRxiv2021

AbmR is a mycobacterial dual-function transcription factor and ribonucleoprotein with distinct DNA and RNA-binding determinants

The bacterium Mycobacterium tuberculosis (Mtb) must adapt to myriad host-associated stressors. A recently identified transcription factor, AbmR (ATP-binding mcr11-regulator), regulates expression of an essential stress-responsive small RNA (Mcr11) and inhibits the growth of Mtb. Previously, AbmR was found to make 39S complexes of unknown function. Here we report that AbmR 39S complexes are comprised of AbmR and co-purifying RNAs and that RNA-binding inhibits AbmRs DNA-binding function. While AbmR binds DNA and regulates gene expression in a sequence specific manner, RNA-binding is not sequence specific. Amino acid R146 is important for DNA-binding but completely dispensable for RNA-binding and 39S complex formation, establishing that the RNA- and DNA-binding functions of AbmR are distinct. RNA bound by AbmR was protected from RNase digestion, supporting an RNA modulatory function for the 39S complex. We also found that abmR is required for optimal survival during treatment with the ATP-depleting antibiotic bedaquiline, which is associated with extended RNA stability. These data establish a paradigm wherein a transcription factor assembles into large complexes to transition between mutually exclusive DNA-binding gene regulatory and RNA-binding RNA modulatory functions. Our findings indicate that AbmR is a dual-function protein that may have novel RNA regulatory roles in stress adapted Mtb.

molecular biology↗

bioRxiv2021

Information-based summary statistics for spatial genetic structure inference

O_LIInference of spatial patterns of genetic structure often relies on parameter estimation and model evaluation using a set of summary statistics (SS) that summarise the information present in the data. An important subset of these SS is best described as diversity indices, which are based on information theory principles that can be classified as belonging to three different families encompassing a spectrum of information measures, qH. These include the richness family of order q = 0, ArSS; the Shannon family of order q = 1, HSS; and the heterozygosity family of order q = 2, HeSS. Although commonly used by ecologists, the Shannon family has been rather neglected by population geneticists and evolutionary biologists. However, recent population genetic studies have advocated their use, yet the power of these SS for spatial structure discrimination has not been systematically assessed. C_LIO_LIIn this study, we performed a comprehensive assessment of the three families of SS, as well as a fourth family consisting of SS belonging to the Shannon family but expressed in terms of Hill numbers [Formula], for spatial structure inference using simulated microsatellites data under typical spatial scenarios. To give an unbiased evaluation, we used three machine learning methods, Kernel Local Fisher discriminant analysis (KLFDA), random forest classification (RFC), and deep neural network (DL), to test the performance of different SS to discriminate between spatial scenarios, and then identified the most informative metrics for discriminatory power. C_LIO_LIResults showed that the SS family of order q = 1 expressed in terms of Hill numbers, [Formula], outperformed the other two families (Ar SS, He SS) as well as the untransformed Shannon entropy (H SS) family. Jaccard dissimilarity (J) and its Mantels r showed the highest discriminatory power to discriminate all spatial scenarios, followed by Shannon differentiation {Delta}D and its Mantels r. C_LIO_LIInformation-based summary statistics, especially the diversity of order q = 1 and Shannon differentiation measures, can increase the power of spatial structure inference. In addition, different sets of SS provide complementary power for discriminating between spatial scenarios. C_LI

genetics↗

bioRxiv2021

Spatial-ATAC-seq: spatially resolved chromatin accessibility profiling of tissues at genome scale and cellular level

Cellular function in tissue is dependent upon the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context. The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping, but it remains elusive to capture spatial epigenetic information of tissue at cellular level and genome scale. Here we report on spatial-ATAC-seq: spatially resolved chromatin accessibility profiling of tissue section via next-generation sequencing by combining in situ Tn5 transposition chemistry and microfluidic deterministic barcoding. Spatial chromatin accessibility profiling of mouse embryos delineated tissue region-specific epigenetic landscapes and identified gene regulators implicated in the central nerve system development. Mapping the accessible genome in human tonsil tissue with 20m pixel size revealed spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology takes spatial biology to a new realm by enabling spatially resolved epigenomics to improve our understanding of cell identity, state, and fate decision in relation to epigenetic underpinnings in development and disease.

genomics↗

bioRxiv2021

Deciphering signatures of natural selection via deep learning

Identifying genomic regions influenced by natural selection provides fundamental insights into the genetic basis of local adaptation. We propose a deep learning-based framework, DeepGenomeScan, that can detect signatures of local adaptation. We demonstrate that DeepGenomeScan outperformed PCA and RDA-based genome scans in identifying loci underlying quantitative traits subject to complex spatial patterns of selection. Noticeably, DeepGenomeScan increases statistical power by up to 47.25% under non-linear environmental selection patterns. We applied DeepGenomeScan to a European human genetic dataset and identified some well-known genes under selection and a substantial number of clinically important genes that were not identified using existing methods.

genomics↗

bioRxiv2021

Development and Application of Cas13a-based Diagnostic Assay for Neisseria Gonorrhoeae Detection and Identification of Azithromycin Resistance

Gonorrhea caused by Neisseria gonorrhoeae has spread world-wide. Antimicrobial-resistant strains have emerged to an alarming level to most antibiotics including to the ceftriaxone-azithromycin combination, currently recommended as first-line dual therapy. Rapid testing for antimicrobial resistance will contribute to clinical decision-making for rational drug use and will slow this trend. Herein, we developed a Cas13a-based assay for N. gonorrhoeae detection (porA target) and azithromycin resistance identification (A2059G and C2611T point mutations). We evaluated the sensitivity and specificity of this method, and 10 copies per reaction can be achieved in porA detection and C2611T identification, with no cross-reactions. Comparison of the Cas13a-based assay (porA target) with Roche Cobas 4800 assay (n=23 urine samples) revealed 100% concordance. Isolated N. gonorrhoeae strains were used to validate the identification of A2059G and C2611T resistance mutations. All tested strains (8 A2059G strains, 8 C2611T strains, and 8 wild-type strains) were successfully distinguished by our assay and verified by testing MIC for azithromycin and sequencing the 23S rRNA gene. We adopted lateral flow for the SHERLOCK assay readout, which showed a visible difference between test group and NC group results. To further evaluate the capability of our assay, we tested 27 urethral swabs from patients with urethritis for N. gonorrhoeae detection and azithromycin-resistance identification. Of these, 62.96% (17/27) strains were detected with no mutant strains and confirmed by sequencing. In conclusion, the novel Cas13a-based assay for rapid and accurate N. gonorrhoeae detection combined with azithromycin drug resistance testing is a promising assay for application in clinical practice.

microbiology↗

bioRxiv2021

Kernel Local Fisher Discriminant Analysis of Principal Components (KLFDAPC) significantly improves the accuracy of predicting geographic origin of individuals

Geographic patterns of human genetic variation provide important insights into human evolution and disease. A commonly used tool to detect geographic patterns from genetic data is principal components analysis (PCA) or the supervised linear discriminant analysis of principal components (DAPC). However, genetic features produced from both approaches could fail to correctly characterize population structure for complex scenarios involving admixture. In this study, we introduce Kernel Local Fisher Discriminant Analysis of Principal Components (KLFDAPC), a supervised nonlinear approach for inferring individual geographic genetic structure that could rectify the limitations of these approaches by preserving the multimodal space of samples. We tested the power of KLFDAPC to infer population structure and to predict individual geographic origin using neural networks. Simulation results showed that KLFDAPC significantly improved the population separability compared with PCA and DAPC. The application to POPRES and CONVERGE datasets indicated that the first two reduced features of KLFDAPC correctly recapitulated the geography of individuals, and significantly improved the accuracy of predicting individual geographic origin when compared to PCA and DAPC. Therefore, KLFDAPC can be useful for geographic ancestry inference, design of genome scans and correction for spatial stratification in GWAS that link genes to adaptation or disease susceptibility.

genomics↗

bioRxiv2021

APOBEC mutagenesis inhibits breast cancer growth through induction of a T cell-mediated antitumor immune response

The APOBEC family of cytidine deaminases is one of the most common endogenous sources of mutations in human cancer. Genomic studies of tumors have found that APOBEC mutational signatures are particularly enriched in the HER2 subtype of breast cancer and have been associated with immunotherapy response in diverse cancer types. However, the direct consequences of APOBEC mutagenesis on the tumor immune microenvironment have not been thoroughly investigated. To address this, we developed syngeneic murine mammary tumor models with inducible expression of APOBEC3B. We found that APOBEC activity induces an antitumor adaptive immune response and CD4+ T cell-mediated tumor growth inhibition. While polyclonal APOBEC tumors had a moderate growth defect, clonal APOBEC tumors were almost completely rejected by the immune system, suggesting that APOBEC-mediated genetic heterogeneity limits the antitumor adaptive immune response. Consistent with the observed immune infiltration in APOBEC tumors, APOBEC activity sensitized HER2-driven breast tumors to checkpoint inhibition. In human breast cancers, the relationship between APOBEC mutagenesis and immunogenicity varied by breast cancer subtype and the frequency of subclonal mutations. This work provides a mechanistic basis for the sensitivity of APOBEC tumors to checkpoint inhibitors and suggests a rationale for using APOBEC mutational signatures as a biomarker predicting immunotherapy response in HER2-positive breast cancers. SIGNIFICANCEAPOBEC mutational signatures are observed in many cancers, yet the consequences of these mutations on the tumor immune microenvironment are not well understood. Using a novel mouse model, we show that APOBEC activity sensitizes HER2-driven mammary tumors to checkpoint inhibition and could inform immunotherapy treatment strategies for HER2-positive breast cancer patients.

cancer biology↗

bioRxiv2021

A systematic CRISPR screen reveals an IL-20/IL20RA-mediated peritoneal immune crosstalk to prevent the ovarian cancer metastasis

Transcoelomic spread of cancer cells across the peritoneal cavity occurs in most initially diagnosed ovarian cancer (OC) patients and accounts for most cancer-related death. However, how OC cells interact with peritoneal stromal cells to evade the immune surveillance remains largely unexplored. Here, through an in vivo genome-wide CRISPR/Cas9 screen, we identified IL20RA, which decreased dramatically in OC patients during peritoneal metastasis, as a key factor preventing the transcoelomic metastasis of OC. Reconstitution of IL20RA in highly metastatic OC cells greatly suppresses the transcoelomic metastasis. OC cells, when disseminate into the peritoneal cavity, greatly induce peritoneum mesothelial cells to express IL-20 and IL-24, which in turn activate the IL20RA downstream signaling in OC cells to produce mature IL-18, eventually resulting in the polarization of macrophages into the M1-like subtype to clear the cancer cells. Thus, we show an IL-20/IL20RA-mediated crosstalk between OC and mesothelial cells that supports a metastasis-repressing immune microenvironment.

cancer biology↗

bioRxiv2020

Oligonucleotide Capture Sequencing of the SARS-CoV-2 Genome and Subgenomic Fragments from COVID-19 Individuals

The newly emerged and rapidly spreading SARS-CoV-2 causes coronavirus disease 2019 (COVID-19). To facilitate a deeper understanding of the viral biology we developed a capture sequencing methodology to generate SARS-CoV-2 genomic and transcriptome sequences from infected patients. We utilized an oligonucleotide probe-set representing the full-length genome to obtain both genomic and transcriptome (subgenomic open reading frames [ORFs]) sequences from 45 SARS-CoV-2 clinical samples with varying viral titers. For samples with higher viral loads (cycle threshold value under 33, based on the CDC qPCR assay) complete genomes were generated. Analysis of junction reads revealed regions of differential transcriptional activity and provided evidence of expression of ORF10. Heterogeneous allelic frequencies along the 20kb ORF1ab gene suggested the presence of a defective interfering viral RNA species subpopulation in one sample. The associated workflow is straightforward, and hybridization-based capture offers an effective and scalable approach for sequencing SARS-CoV-2 from patient samples.

genomics↗

bioRxiv2020

WEVar: a novel statistical learning framework for predicting noncoding regulatory variants

Understanding the functional consequence of noncoding variants is of great interest. Though genome-wide association studies (GWAS) or quantitative trait locus (QTL) analyses have identified variants associated with traits or molecular phenotypes, most of them are located in the noncoding regions, making the identification of causal variants a particular challenge. Existing computational approaches developed for for prioritizing non-coding variants produce inconsistent and even conflicting results. To address these challenges, we propose a novel statistical learning framework, which directly integrates the precomputed functional scores from representative scoring methods. It will maximize the usage of integrated methods by automatically learning the relative contribution of each method and produce an ensemble score as the final prediction. The framework consists of two modes. The first "context-free" mode is trained using curated causal regulatory variants from a wide range of context and is applicable to predict noncoding variants of unknown and diverse context. The second "context-dependent" mode further improves the prediction when the training and testing variants are from the same context. By evaluating the framework via both simulation and empirical studies, we demonstrate that it outperforms integrated scoring methods and the ensemble score successfully prioritizes experimentally validated regulatory variants in multiple risk loci.

bioinformatics↗

bioRxiv2020

emiRIT: A text-mining based resource for microRNA information

MotivationmicroRNAs (miRNAs) are essential gene regulators and their dysregulation often leads to diseases. Easy access to miRNA information is crucial for interpreting generated experimental data, connecting facts across publications, and developing new hypotheses built on previous knowledge. Here, we present emiRIT, a text mining-based resource, which presents miRNA information mined from the literature through a user-friendly interface. ResultsWe collected 149,233 miRNA-PubMed ID pairs from Medline between January 1997 to May 2020. emiRIT currently contains miRNA-gene regulation (60,491 relations); miRNA-disease (cancer) (12,300 relations); miRNA-biological process and pathways (23,390 relations); and circulatory miRNAs in extracellular locations (3,782 relations). Biological entities and their relation to miRNAs were extracted from Medline abstracts using publicly available and in-house developed text mining tools, and the entities were normalized to facilitate querying and integration. We built a database and an interface to store and access the integrated data, respectively. ConclusionWe provide an up-to-date and user-friendly resource to facilitate access to comprehensive miRNA information from the literature on a large-scale, enabling users to navigate through different roles of miRNA and examine them in a context specific to their information needs. To assess our resources information coverage, in the absence of gold standards, we have conducted two case studies focusing on the target and differential expression information of miRNAs in the context of diseases. Database URL: https://research.bioinformatics.udel.edu/emirit/

bioinformatics↗

bioRxiv2020

Activation of Notch1 drives the development of radiation-induced thymic lymphoma in p53 wild-type mice

Mouse models of radiation-induced thymic lymphoma are widely used to study the development of radiation-induced blood cancers and to gain insights into the biology of human T-lymphoblastic leukemia/lymphoma. Here, we aimed to determine key oncogenic drivers for the development of radiation-induced thymic lymphoma by performing whole-exome sequencing using tumors and paired normal tissues from mice with and without irradiation. Thymic lymphomas from irradiated wild-type (WT), p53+/- and KrasLA1 mice were not observed to harbor significantly higher numbers of non-synonymous somatic mutations compared to thymic lymphomas from unirradiated p53-/- mice. However, we observed distinct patterns of recurrent mutations in genes that control the Notch1 signaling pathway based on the mutational status of p53. Preferential activation of Notch1 signaling in p53 WT lymphomas was also observed at the RNA and protein level. Using reporter mice for activation of the Notch1 signaling we observed that TBI enriched Notch1hi CD44+ thymocytes, which are capable of self-renewal in vivo. Mechanistically, genetic inhibition of Notch1 signaling in thymocytes prevented the formation of radiation-induced thymic lymphoma in p53 WT mice. Taken together, our results demonstrate a critical role of activated Notch1 signaling in driving multi-step carcinogenesis of thymic lymphoma following total-body irradiation in p53 WT mice.

cancer biology↗