RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION

My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status. Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We observe that accuracy improves along with the increasing sequencing depth. To model the overdispersion, we use the beta-binomial distribution with a new parameter indicating the dependency between overdispersion and sequencing depth. Our modified beta-binomial model performs better than the binomial or the pure beta-binomial model with a lower false discovery rate. Section 2: Although a number of methods have been proposed in order to accurately analyze differential RNA expression on the gene level, modeling on the base pair level is required. Here, we find that the overdispersion rate decreases as the sequencing depth increases on the base pair level. Also, we propose four models and compare them with each other. As expected, our beta binomial model with a dynamic overdispersion rate is shown to be superior. Section 3: We investigate biases in RNA-seq by exploring the measurement of the external control, spike-in RNA. This study is based on two datasets with spike-in controls obtained from a recent study. We observe an undiscovered bias in the measurement of the spike-in transcripts that arises from the influence of the sample transcripts in RNA-seq. Also, we find that this influence is related to the local sequence of the random hexamer that is used in priming. We suggest a model of the inequality between samples and to correct this type of bias. Section 4: The expression of a gene can be turned off when its promoter is highly methylated. Several studies have reported that a clear threshold effect exists in gene silencing that is mediated by DNA methylation. It is reasonable to assume the thresholds are specific for each gene. It is also intriguing to investigate genes that are largely controlled by DNA methylation. These genes are called “L-shaped” genes. We develop a method to determine the DNA methylation threshold and identify a new CIMP of BRCA. In conclusion, we provide a detailed understanding of the relationship between the overdispersion rate and sequencing depth. And we reveal a new bias in RNA-seq and provide a detailed understanding of the relationship between this new bias and the local sequence. Also we develop a powerful method to dichotomize methylation status and consequently we identify a new CIMP of breast cancer with a distinct classification of molecular characteristics and clinical features

miRecords: an integrated resource for microRNA–target interactions

MicroRNAs (miRNAs) are an important class of small noncoding RNAs capable of regulating other genes’ expression. Much progress has been made in computational target prediction of miRNAs in recent years. More than 10 miRNA target prediction programs have been established, yet, the prediction of animal miRNA targets remains a challenging task. We have developed miRecords, an integrated resource for animal miRNA–target interactions. The Validated Targets component of this resource hosts a large, high-quality manually curated database of experimentally validated miRNA–target interactions with systematic documentation of experimental support for each interaction. The current release of this database includes 1135 records of validated miRNA–target interactions between 301 miRNAs and 902 target genes in seven animal species. The Predicted Targets component of miRecords stores predicted miRNA targets produced by 11 established miRNA target prediction programs. miRecords is expected to serve as a useful resource not only for experimental miRNA researchers, but also for informatics scientists developing the next-generation miRNA target prediction programs. The miRecords is available at http://miRecords.umn.edu/miRecords

Population Effect Model Identifies Gene Expression Predictors of Survival Outcomes in Lung Adenocarcinoma for Both Caucasian and Asian Patients

Background: We analyzed and integrated transcriptome data from two large studies of lung adenocarcinomas on distinct populations. Our goal was to investigate the variable gene expression alterations between paired tumor-normal tissues and prospectively identify those alterations that can reliably predict lung disease related outcomes across populations. Methods: We developed a mixed model that combined the paired tumor-normal RNA-seq from two populations. Alterations in gene expression common to both populations were detected and validated in two independent DNA microarray datasets. A 10-gene prognosis signature was developed through a l1 penalized regression approach and its prognostic value was evaluated in a third independent microarray cohort. Results: Deregulation of apoptosis pathways and increased expression of cell cycle pathways were identified in tumors of both Caucasian and Asian lung adenocarcinoma patients. We demonstrate that a 10-gene biomarker panel can predict prognosis of lung adenocarcinoma in both Caucasians and Asians. Compared to low risk groups, high risk groups showed significantly shorter overall survival time (Caucasian patients data: HR = 3.63, p-value = 0.007; Asian patients data: HR = 3.25, p-value = 0.001). Conclusions: This study uses a statistical framework to detect DEGs between paired tumor and normal tissues that considers variances among patients and ethnicities, which will aid in understanding the common genes and signalling pathways with the largest effect sizes in ethnically diverse cohorts. We propose multifunctional markers for distinguishing tumor from normal tissue and prognosis for both populations studied

Targeting EZH2 Regulates Tumor Growth and Apoptosis Through Modulating Mitochondria Dependent Cell-Death Pathway in HNSCC

EZH2 is a negative prognostic factor and is overexpressed or activated in most human cancers including head and neck squamous cell carcinoma (HNSCC). Analysis of The Cancer Genome Atlas (TCGA) HNSCC data indicated that EZH2 over-expression was associated with high tumor grade and conferred poor prognosis. EZH2 inhibition triggered cell apoptosis, cell cycle arrest and decreased cell growth in vitro. MICU1 (mitochondrial calcium uptake1) was shown to be down regulated when EZH2 expression was inhibited in HNSCC. When the EZH2 and MICU1 were inhibited, HNSCC cells became susceptible to cell cycle arrest and apoptosis. Mitochondrial membrane potential and cytosolic Ca2+ concentration analysis suggested that EZH2 and MICU1 were required to maintain mitochondrial membrane potential stability. A xenograft tumor model was used to confirm that EZH2 depletion inhibited HNSCC cell growth and induced tumor cell apoptosis. In summary, EZH2 is a potential anti-tumor target in HNSCC

Long Non Coding RNA MALAT1 Promotes Tumor Growth and Metastasis by Inducing Epithelial-Mesenchymal Transition in Oral Squamous Cell Carcinoma

The prognosis of advanced oral squamous cell carcinoma (OSCC) patients remains dismal, and a better understanding of the underlying mechanisms is critical for identifying effective targets with therapeutic potential to improve the survival of patients with OSCC. This study aims to clarify the clinical and biological significance of metastasis-associated long non-coding RNA, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in OSCC. We found that MALAT1 is overexpressed in OSCC tissues compared to normal oral mucosa by real-time PCR. MALAT1 served as a new prognostic factor in OSCC patients. When knockdown by small interfering RNA (siRNA) in OSCC cell lines TSCCA and Tca8113, MALAT1 was shown to be required for maintaining epithelial-mesenchymal transition (EMT) mediated cell migration and invasion. Western blot and immunofluorescence staining showed that MALAT1 knockdown significantly suppressed N-cadherin and Vimentin expression but induced E-cadherin expression in vitro. Meanwhile, both nucleus and cytoplasm levels of β-catenin and NF-κB were attenuated, while elevated MALAT1 level triggered the expression of β-catenin and NF-κB. More importantly, targeting MALAT1 inhibited TSCCA cell-induced xenograft tumor growth in vivo. Therefore, these findings provide mechanistic insight into the role of MALAT1 in regulating OSCC metastasis, suggesting that MALAT1 is an important prognostic factor and therapeutic target for OSCC

A Systematic Review and Meta-Analysis on the Efficacy of Repeated Transcranial Direct Current Stimulation for Migraine

Purpose: Transcranial direct current stimulation (tDCS) may have therapeutic potential in the management of migraine. However, studies to date have yielded conflicting results. We reviewed studies using repeated tDCS for longer than 4 weeks in migraine treatment, and performed meta-analysis on the efficacy of tDCS in migraine. Methods: In this meta-analysis, we included the common outcome measurements reported across randomized controlled trials (RCTs). Subgroup analysis was performed at different post-treatment endpoints, and with different stimulation intensities and polarities. Results: Five RCTs were included in the quantitative meta-analysis with a total of 104 migraine patients. We found a significant reduction of migraine pain intensity (MD: − 1.44; CI: [− 2.13, − 0.76]) in active vs sham tDCS treated patients. Within active treatment groups, pain intensity and duration were significantly improved from baseline after tDCS treatment (intensity MD: − 1.86; CI: [− 3.30, − 0.43]; duration MD: − 4.42; CI: [− 8.11, − 0.74]) and during a follow-up period (intensity MD: − 1.52; CI: [− 1.84, − 1.20]; duration MD: − 1.94; CI: [− 3.10, − 0.77]). There was a significant reduction of pain intensity by both anodal (MD: − 1.74; CI: [− 2.80, − 0.68]) and cathodal (MD: − 1.49; CI: [− 1.89, − 1.09]) stimulation conditions. Conclusion: tDCS treatment repeated over days for a period of 4 weeks or more is effective in reducing migraine pain intensity and duration of migraine episode. The benefit of tDCS can persist for at least 4 weeks after the completion of last tDCS session. Both anodal and cathodal stimulation are effective for reducing migraine pain intensity

Accuracy of RNA-Seq and its Dependence on Sequencing Depth

The cost of DNA sequencing has undergone a dramatical reduction in the past decade. As a result, sequencing technologies have been increasingly applied to genomic research. RNA-Seq is becoming a common technique for surveying gene expression based on DNA sequencing. As it is not clear how increased sequencing capacity has affected measurement accuracy of mRNA, we sought to investigate that relationship. Result: We empirically evaluate the accuracy of repeated gene expression measurements using RNA-Seq. We identify library preparation steps prior to DNA sequencing as the main source of error in this process. Studying three datasets, we show that the accuracy indeed improves with the sequencing depth. However, the rate of improvement as a function of sequence reads is generally slower than predicted by the binomial distribution. We therefore used the beta-binomial distribution to model the overdispersion. The overdispersion parameters we introduced depend explicitly on the number of reads so that the resulting statistical uncertainty is consistent with the empirical data that measurement accuracy increases with the sequencing depth. The overdispersion parameters were determined by maximizing the likelihood. We shown that our modified beta-binomial model had lower false discovery rate than the binomial or the pure beta-binomial models. Conclusion: We proposed a novel form of overdispersion guaranteeing that the accuracy improves with sequencing depth. We demonstrated that the new form provides a better fit to the data.NIH/NCI 5K25CA123344Keck Center for Quantitative Biomedical Sciences of the Gulf Coast Consortia from the Cancer Prevention and Research Institute of Texas (CPRIT) RP101489Center for Computational Biology and Bioinformatic

FastPop: a rapid principal component derived method to infer intercontinental ancestry using genetic data.

BACKGROUND: Identifying subpopulations within a study and inferring intercontinental ancestry of the samples are important steps in genome wide association studies. Two software packages are widely used in analysis of substructure: Structure and Eigenstrat. Structure assigns each individual to a population by using a Bayesian method with multiple tuning parameters. It requires considerable computational time when dealing with thousands of samples and lacks the ability to create scores that could be used as covariates. Eigenstrat uses a principal component analysis method to model all sources of sampling variation. However, it does not readily provide information directly relevant to ancestral origin; the eigenvectors generated by Eigenstrat are sample specific and thus cannot be generalized to other individuals. RESULTS: We developed FastPop, an efficient R package that fills the gap between Structure and Eigenstrat. It can: 1, generate PCA scores that identify ancestral origins and can be used for multiple studies; 2, infer ancestry information for data arising from two or more intercontinental origins. We demonstrate the use of FastPop using 2318 SNP markers selected from the genome based on high variability among European, Asian and West African (African) populations. We conducted an analysis of 505 Hapmap samples with European, African or Asian ancestry along with 19661 additional samples of unknown ancestry. The results from FastPop are highly consistent with those obtained by Structure across the 19661 samples we studied. The correlations of the results between FastPop and Structure are 0.99, 0.97 and 0.99 for European, African and Asian ancestry scores, respectively. Compared with Structure, FastPop is more efficient as it finished ancestry inference for 19661 samples in 16 min compared with 21-24 h required by Structure. FastPop also provided scores based on SNP weights so the scores of reference population can be applied to other studies provided the same set of markers are used. We also present application of the method for studying four continental populations (European, Asian, African, and Native American). CONCLUSIONS: We developed an algorithm that can infer ancestries on data involving two or more intercontinental origins. It is efficient for analyzing large datasets. Additionally the PCA derived scores can be applied to multiple data sets to ensure the same ancestry analysis is applied to all studies

Risks of suicide in migraine, non-migraine headache, back, and neck pain: a systematic review and meta-analysis

ObjectiveTo conduct a systematic review and meta-analysis on suicidal ideation, attempts, and death in patients with head, neck, and back pain.MethodSearch was performed using PubMed, Embase, and Web of Science from the date of the first available article through September 31, 2021. A random effects model was used to estimate the pooled odds ratios (ORs) and 95% confidence intervals (95% CI) for the association between suicidal ideation and/or attempt and head, back/neck pain conditions. Articles describing non-migraine headache disorders and death by suicide were also reviewed but not included in the meta-analysis due to an insufficient number of studies.ResultsA total of 20 studies met criteria for systemic review. A total of 186,123 migraine patients and 135,790 of neck/back pain patients from 11 studies were included in the meta-analysis. The meta-analysis showed that the estimated risk of combined suicidal ideation and attempt in migraine [OR 2.49; 95% CI: 2.15–2.89] is greater than that in back/neck pain pain [OR 2.00; 95% CI: 1.63–2.45] compared to non-pain control groups. Risk of suicide ideation/planning is 2 folds higher [OR: 2.03; 95% CI: 1.92–2.16] and risk of suicide attempt is more than 3 folds higher [OR: 3.47; 95% CI: 2.68–4.49] in migraine as compared to healthy controls.ConclusionThere is an elevated risk of suicidal ideation and attempt in both migraine and neck/back pain patients in comparison to healthy controls, and this risk is particularly higher among migraine patients. This study underscores the critical need for suicide prevention in migraine patients

SARS-CoV-2 Impairs Dendritic Cells and Regulates DC-Sign Gene Expression in Tissues

The current spreading coronavirus SARS-CoV-2 is highly infectious and pathogenic. In this study, we screened the gene expression of three host receptors (ACE2, DC-SIGN and L-SIGN) of SARS coronaviruses and dendritic cells (DCs) status in bulk and single cell transcriptomic datasets of upper airway, lung or blood of COVID-19 patients and healthy controls. In COVID-19 patients, DC-SIGN gene expression was interestingly decreased in lung DCs but increased in blood DCs. Within DCs, conventional DCs (cDCs) were depleted while plasmacytoid DCs (pDCs) were augmented in the lungs of mild COVID-19. In severe cases, we identified augmented types of immature DCs (CD22+ or ANXA1+ DCs) with MHCII downregulation. In this study, our observation indicates that DCs in severe cases stimulate innate immune responses but fail to specifically present SARS-CoV-2. It provides insights into the profound modulation of DC function in severe COVID-19