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Browsing by Author "Wang, Yue"
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Item 38766 Massively Parallel Reporter Assay Reveals Functional Impact of 3™-UTR SNPs Associated with Neurological and Psychiatric Disorders(Cambridge University Press, 2021) Chen, Andy B.; Thapa, Kriti; Gao, Hongyu; Reiter, Jill L.; Zhang, Junjie; Xuei, Xiaoling; Gu, Hongmei; Wang, Yue; Edenberg, Howard J.; Liu, Yunlong; Medical and Molecular Genetics, School of MedicineABSTRACT IMPACT: Screening the effect of thousands of non-coding genetic variants will help identify variants important in the etiology of diseases OBJECTIVES/GOALS: Massively parallel reporter assays (MPRAs) can experimentally evaluate the impact of genetic variants on gene expression. In this study, our objective was to systematically evaluate the functional activity of 3’-UTR SNPs associated with neurological disorders and use those results to help understand their contributions to disease etiology. METHODS/STUDY POPULATION: To choose variants to evaluate with the MPRA, we first gathered SNPs from the GWAS Catalog that were associated with any neurological disorder trait with p-value < 10-5. For each SNP, we identified the region that was in linkage disequilibrium (r2 > 0.8) and retrieved all the common 3’-UTR SNPs (allele-frequency > 0.05) within that region. We used an MPRA to measure the impact of these 3’-UTR variants in SH-SY5Y neuroblastoma cells and a microglial cell line. These results were then used to train a deep-learning model to predict the impact of variants and identify features that contribute to the predictions. RESULTS/ANTICIPATED RESULTS: Of the 13,515 3’-UTR SNPs tested, 400 and 657 significantly impacted gene expression in SH-SY5Y and microglia, respectively. Of the 84 SNPs significantly impacted in both cells, the direction of impact was the same in 81. The direction of eQTL in GTEx tissues agreed with the assay SNP effect in SH-SY5Y cells but not microglial cells. The deep-learning model predicted sequence activity level correlated with the experimental activity level (Spearman’s corr = 0.45). The deep-learning model identified several predictive motifs similar to motifs of RNA-binding proteins. DISCUSSION/SIGNIFICANCE OF FINDINGS: This study demonstrates that MPRAs can be used to evaluate the effect of non-coding variants, and the results can be used to train a machine learning model and interpret its predictions. Together, these can help identify causal variants and further understand the etiology of diseases.Item Aberrant gene expression induced by a high fat diet is linked to H3K9 acetylation in the promoter-proximal region(Elsevier, 2021-03) Morral, Núria; Liu, Sheng; Conteh, Abass M.; Chu, Xiaona; Wang, Yue; Dong, X. Charlie; Liu, Yunlong; Linnemann, Amelia K.; Wan, Jun; Medical and Molecular Genetics, School of MedicineNon-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, with an estimated global prevalence of 1 in 4 individuals. Aberrant transcriptional control of gene expression is central to the pathophysiology of metabolic diseases. However, the molecular mechanisms leading to gene dysregulation are not well understood. Histone modifications play important roles in the control of transcription. Acetylation of histone 3 at lysine 9 (H3K9ac) is associated with transcriptional activity and is implicated in transcript elongation by controlling RNA polymerase II (RNAPII) pause-release. Hence, changes in this histone modification may shed information on novel pathways linking transcription control and metabolic dysfunction. Here, we carried out genome-wide analysis of H3K9ac in the liver of mice fed a control or a high-fat diet (an animal model of NAFLD), and asked whether this histone mark associates with changes in gene expression. We found that over 70% of RNAPII peaks in promoter-proximal regions overlapped with H3K9ac, consistent with a role of H3K9ac in the regulation of transcription. When comparing high-fat with control diet, approximately 17% of the differentially expressed genes were associated with changes in H3K9ac in their promoters, showing a strong correlation between changes in H3K9ac signal and gene expression. Overall, our data indicate that in response to a high-fat diet, dysregulated gene expression of a subset of genes may be attributable to changes in transcription elongation driven by H3K9ac. Our results point at an added mechanism of gene regulation that may be important in the development of metabolic diseases.Item AIscEA: unsupervised integration of single-cell gene expression and chromatin accessibility via their biological consistency(Oxford University Press, 2022) Jafari, Elham; Johnson, Travis; Wang, Yue; Liu, Yunlong; Huang, Kun; Wang, Yijie; Biostatistics and Health Data Science, School of MedicineMotivation: The integrative analysis of single-cell gene expression and chromatin accessibility measurements is essential for revealing gene regulation, but it is one of the key challenges in computational biology. Gene expression and chromatin accessibility are measurements from different modalities, and no common features can be directly used to guide integration. Current state-of-the-art methods lack practical solutions for finding heterogeneous clusters. However, previous methods might not generate reliable results when cluster heterogeneity exists. More importantly, current methods lack an effective way to select hyper-parameters under an unsupervised setting. Therefore, applying computational methods to integrate single-cell gene expression and chromatin accessibility measurements remains difficult. Results: We introduce AIscEA-Alignment-based Integration of single-cell gene Expression and chromatin Accessibility-a computational method that integrates single-cell gene expression and chromatin accessibility measurements using their biological consistency. AIscEA first defines a ranked similarity score to quantify the biological consistency between cell clusters across measurements. AIscEA then uses the ranked similarity score and a novel permutation test to identify cluster alignment across measurements. AIscEA further utilizes graph alignment for the aligned cell clusters to align the cells across measurements. We compared AIscEA with the competing methods on several benchmark datasets and demonstrated that AIscEA is highly robust to the choice of hyper-parameters and can better handle the cluster heterogeneity problem. Furthermore, AIscEA significantly outperforms the state-of-the-art methods when integrating real-world SNARE-seq and scMultiome-seq datasets in terms of integration accuracy. Availability and implementation: AIscEA is available at https://figshare.com/articles/software/AIscEA_zip/21291135 on FigShare as well as {https://github.com/elhaam/AIscEA} onGitHub.Item AIscEA: unsupervised integration of single-cell gene expression and chromatin accessibility via their biological consistency(Oxford, 2022-12-01) Jafari, Elham; Johnson, Travis; Wang, Yue; Liu, Yunlong; Huang, Kun; Wang, Yijie; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthMotivation The integrative analysis of single-cell gene expression and chromatin accessibility measurements is essential for revealing gene regulation, but it is one of the key challenges in computational biology. Gene expression and chromatin accessibility are measurements from different modalities, and no common features can be directly used to guide integration. Current state-of-the-art methods lack practical solutions for finding heterogeneous clusters. However, previous methods might not generate reliable results when cluster heterogeneity exists. More importantly, current methods lack an effective way to select hyper-parameters under an unsupervised setting. Therefore, applying computational methods to integrate single-cell gene expression and chromatin accessibility measurements remains difficult. Results We introduce AIscEA—Alignment-based Integration of single-cell gene Expression and chromatin Accessibility—a computational method that integrates single-cell gene expression and chromatin accessibility measurements using their biological consistency. AIscEA first defines a ranked similarity score to quantify the biological consistency between cell clusters across measurements. AIscEA then uses the ranked similarity score and a novel permutation test to identify cluster alignment across measurements. AIscEA further utilizes graph alignment for the aligned cell clusters to align the cells across measurements. We compared AIscEA with the competing methods on several benchmark datasets and demonstrated that AIscEA is highly robust to the choice of hyper-parameters and can better handle the cluster heterogeneity problem. Furthermore, AIscEA significantly outperforms the state-of-the-art methods when integrating real-world SNARE-seq and scMultiome-seq datasets in terms of integration accuracy. Availability and implementation AIscEA is available at https://figshare.com/articles/software/AIscEA_zip/21291135 on FigShare as well as {https://github.com/elhaam/AIscEA} onGitHub.Item Allele-specific expression and high-throughput reporter assay reveal functional genetic variants associated with alcohol use disorders(Springer Nature, 2021-04) Rao, Xi; Thapa, Kriti S.; Chen, Andy B.; Lin, Hai; Gao, Hongyu; Reiter, Jill L.; Hargreaves, Katherine A.; Ipe, Joseph; Lai, Dongbing; Xuei, Xiaoling; Wang, Yue; Gu, Hongmei; Kapoor, Manav; Farris, Sean P.; Tischfield, Jay; Foroud, Tatiana; Goate, Alison M.; Skaar, Todd C.; Mayfield, R. Dayne; Edenberg, Howard J.; Liu, Yunlong; Medical and Molecular Genetics, School of MedicineGenome-wide association studies (GWAS) of complex traits, such as alcohol use disorders (AUD), usually identify variants in non-coding regions and cannot by themselves distinguish whether the associated variants are functional or in linkage disequilibrium with the functional variants. Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with AUD may cause expression differences, we integrated data from deep RNA-seq and GWAS of four postmortem brain regions from 30 subjects with AUD and 30 controls to analyze allele-specific expression (ASE). We identified 88 genes with differential ASE in subjects with AUD compared to controls. Next, to test one potential mechanism contributing to the differential ASE, we analyzed single nucleotide polymorphisms (SNPs) in the 3′ untranslated regions (3′UTR) of these genes. Of the 88 genes with differential ASE, 61 genes contained 437 SNPs in the 3′UTR with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these SNPs are in binding sites of miRNAs and RNA-binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE. In sum, we demonstrate that a combination of computational and experimental approaches provides a powerful strategy to uncover functionally relevant variants associated with the risk for AUD.Item Allele-specific expression and high-throughput reporter assay reveal functional genetic variants associated with alcohol use disorders.(Springer, 2021-04) Rao, Xi; Thapa, Kriti S.; Chen, Andy B.; Lin, Hai; Gao, Hongyu; Reiter, Jill L.; Hargreaves, Katherine A.; Ipe, Joseph; Lai, Dongbing; Xuei, Xiaoling; Wang, Yue; Gu, Hongmei; Kapoor, Manav; Farris, Sean P.; Tischfield, Jay; Foroud, Tatiana; Goate, Alison M.; Skaar, Todd C.; Mayfield, R. Dayne; Edenberg, Howard J.; Liu, YunlongGenome-wide association studies (GWAS) of complex traits, such as alcohol use disorders (AUD), usually identify variants in non-coding regions and cannot by themselves distinguish whether the associated variants are functional or in linkage disequilibrium with the functional variants. Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with AUD may cause expression differences, we integrated data from deep RNA-seq and GWAS of four postmortem brain regions from 30 subjects with AUD and 30 controls to analyze allele-specific expression (ASE). We identified 88 genes with differential ASE in subjects with AUD compared to controls. Next, to test one potential mechanism contributing to the differential ASE, we analyzed single nucleotide polymorphisms (SNPs) in the 3' untranslated regions (3'UTR) of these genes. Of the 88 genes with differential ASE, 61 genes contained 437 SNPs in the 3'UTR with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these SNPs are in binding sites of miRNAs and RNA-binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE. In sum, we demonstrate that a combination of computational and experimental approaches provides a powerful strategy to uncover functionally relevant variants associated with the risk for AUD.Item Attraction and Compaction of Migratory Breast Cancer Cells by Bone Matrix Proteins through Tumor-Osteocyte Interactions(Nature Publishing Group, 2018-04-03) Chen, Andy; Wang, Luqi; Liu, Shengzhi; Wang, Yue; Liu, Yunlong; Wang, Mu; Nakshatri, Harikrishna; Li, Bai-Yan; Yokota, Hiroki; Biomedical Engineering, School of Engineering and TechnologyBone is a frequent site of metastasis from breast cancer. To understand the potential role of osteocytes in bone metastasis, we investigated tumor-osteocyte interactions using two cell lines derived from the MDA-MB-231 breast cancer cells, primary breast cancer cells, and MLO-A5/MLO-Y4 osteocyte cells. When three-dimensional (3D) tumor spheroids were grown with osteocyte spheroids, tumor spheroids fused with osteocyte spheroids and shrank. This size reduction was also observed when tumor spheroids were exposed to conditioned medium isolated from osteocyte cells. Mass spectrometry-based analysis predicted that several bone matrix proteins (e.g., collagen, biglycan) in conditioned medium could be responsible for tumor shrinkage. The osteocyte-driven shrinkage was mimicked by type I collagen, the most abundant organic component in bone, but not by hydroxyapatite, a major inorganic component in bone. RNA and protein expression analysis revealed that tumor-osteocyte interactions downregulated Snail, a transcription factor involved in epithelial-to-mesenchymal transition (EMT). An agarose bead assay showed that bone matrix proteins act as a tumor attractant. Collectively, the study herein demonstrates that osteocytes attract and compact migratory breast cancer cells through bone matrix proteins, suppress tumor migration, by Snail downregulation, and promote subsequent metastatic colonization.Item Characterizing Restorative Dental Treatments of Sjögren's Syndrome Patients Using Electronic Dental Records Data(IOS Press, 2017) Siddiqui, Zasim; Wang, Yue; Makkad, Payal; Thyvalikakath, Thankam; Cariology, Operative Dentistry and Dental Public Health, School of DentistryScant knowledge exists on the type of restorative treatments Sjögren's syndrome patients (SSP) receive in spite of their high dental disease burden due to hyposalivation. Increased adoption of electronic dental records (EDR) could help in leveraging information from these records to assess dental treatment outcomes in SSP. In this study, we evaluated the feasibility of using EDR to characterize the dental treatments SSP received and assess the longevity of implants in these patients. We identified 180 SSP in ten years of patients' data at the Indiana University School of Dentistry clinics. A total of 104 (57.77%) patients received restorative or endodontic treatments. Eleven patients received 23 implants with a survival rate of 87% at 40 months follow-up. We conclude that EDR data could be used for characterizing the treatments received by SSP and for assessing treatment outcomes.Item Differences in medication usage of dental patients by age, gender, race/ethnicity and insurance status(IOS, 2021) Siddiqui, Zasim; Wang, Yue; Patel, Jay; Thyvalikakath, Thankam; Cariology, Operative Dentistry and Dental Public Health, School of DentistryBACKGROUND: Limited studies have investigated the medication profile of young adult dental patients despite the high prevalence of prescription opioid abuse in this population. OBJECTIVE: This study investigated the extent and differences in medication usage of dental patients older than 18 years by age, race/ethnicity, gender, insurance status and mechanism of action in an academic dental clinic setting. METHODS: Using an automated approach, medication names in the electronic dental record were retrieved and classified according to the National Drug Code directory. Descriptive statistics, multivariable ANOVA and Post hoc tests were performed to detect differences in the number of medications by patient demographics. RESULTS: Of the 11,220 adult patients, 53 percent reported taking at least one medication with significant differences in medication usage by demographics. Hydroxymethylglutaryl-coenzyme A reductase inhibitors (21–36%), and angiotensin-converting enzyme inhibitors (19–23%) ranked the top two medication classes among patients 55 years and older. Opioid agonists (7–14%), and Selective Serotonin Reuptake Inhibitors (SSRIs) (5–12%) ranked the top two medication classes among patients aged 18–54 years. CONCLUSIONS: The results underscore the importance of dental providers to review medical and medication histories of patients regardless of their age to avoid adverse events and to determine patient’s risk for opioid abuse.Item Dissecting the role of the CRMP2–neurofibromin complex on pain behaviors(Wolters Kluwer, 2017-11) Moutal, Aubin; Wang, Yue; Yang, Xiaofang; Ji, Yingshi; Luo, Shizhen; Dorame, Angie; Bellampalli, Shreya S.; Chew, Lindsey A.; Cai, Song; Dustrude, Erik T.; Keener, James E.; Marty, Michael T.; Vanderah, Todd W.; Khanna, Rajesh; Psychiatry, School of MedicineNeurofibromatosis type 1 (NF1), a genetic disorder linked to inactivating mutations or a homozygous deletion of the Nf1 gene, is characterized by tumorigenesis, cognitive dysfunction, seizures, migraine, and pain. Omic studies on human NF1 tissues identified an increase in the expression of collapsin response mediator protein 2 (CRMP2), a cytosolic protein reported to regulate the trafficking and activity of presynaptic N-type voltage-gated calcium (Cav2.2) channels. Because neurofibromin, the protein product of the Nf1 gene, binds to and inhibits CRMP2, the neurofibromin-CRMP2 signaling cascade will likely affect Ca channel activity and regulate nociceptive neurotransmission and in vivo responses to noxious stimulation. Here, we investigated the function of neurofibromin-CRMP2 interaction on Cav2.2. Mapping of >275 peptides between neurofibromin and CRMP2 identified a 15-amino acid CRMP2-derived peptide that, when fused to the tat transduction domain of HIV-1, inhibited Ca influx in dorsal root ganglion neurons. This peptide mimics the negative regulation of CRMP2 activity by neurofibromin. Neurons treated with tat-CRMP2/neurofibromin regulating peptide 1 (t-CNRP1) exhibited a decreased Cav2.2 membrane localization, and uncoupling of neurofibromin-CRMP2 and CRMP2-Cav2.2 interactions. Proteomic analysis of a nanodisc-solubilized membrane protein library identified syntaxin 1A as a novel CRMP2-binding protein whose interaction with CRMP2 was strengthened in neurofibromin-depleted cells and reduced by t-CNRP1. Stimulus-evoked release of calcitonin gene-related peptide from lumbar spinal cord slices was inhibited by t-CNRP1. Intrathecal administration of t-CNRP1 was antinociceptive in experimental models of inflammatory, postsurgical, and neuropathic pain. Our results demonstrate the utility of t-CNRP1 to inhibit CRMP2 protein-protein interactions for the potential treatment of pain.