Deciphering transcriptional patterns of gene regulation : a computational approach

With rapid advancements in sequencing technology, we now have the ability to sequence the entire human genome, and to quantify expression of tens of thousands of genes from hundreds of individuals. This provides an extraordinary opportunity to learn phenotype relevant genomic patterns that can improve our understanding of molecular and cellular processes underlying a trait. The high dimensional nature of genomic data presents a range of computational and statistical challenges. This dissertation presents a compilation of projects that were driven by the motivation to efficiently capture gene regulatory patterns in the human transcriptome, while addressing statistical and computational challenges that accompany this data. We attempt to address two major difficulties in this domain: a) artifacts and noise in transcriptomic data, and b) limited statistical power. First, we present our work on investigating the effect of artifactual variation in gene expression data and its impact on trans-eQTL discovery. Here we performed an in-depth analysis of diverse pre-recorded covariates and latent confounders to understand their contribution to heterogeneity in gene expression measurements. Next, we discovered 673 trans-eQTLs across 16 human tissues using v6 data from the Genotype Tissue Expression (GTEx) project. Finally, we characterized two trait-associated trans-eQTLs; one in Skeletal Muscle and another in Thyroid. Second, we present a principal component based residualization method to correct gene expression measurements prior to reconstruction of co-expression networks. In this work, we demonstrated theoretically, in simulation, and empirically, that principal component correction of gene expression measurements prior to network inference can reduce false positive edges. Using data from the GTEx project in multiple tissues, we showed that this approach reduced false discoveries beyond correcting only for known confounders. Third, we present a multi-study integration approach to identify universal transcriptional patterns underlying epithelial to mesenchymal transition (EMT) across different cancer types. With informed statistical analysis and functional validation, we identified consensus ranked universal EMT genes. This gene list consisted of a) known EMT genes, b) genes studied in a subset of carcinomas, unknown in prostate cancer, and c) novel unknown EMT and cancer genes such as C1orf116. Finally we present methods to integrate co-expression signals across multiple human RNA-seq data to reconstruct networks with increased power. First, we considered multiple aggregation strategies to build context-agnostic networks using data from recount2. These networks captured ubiquitous patterns of gene co-expression shared across tissues and cell types. Next, we briefly describe a hierarchical mixture model groupNet that leverages signal from multiple datasets to learn the structure of a Gaussian Markov random field (GRMF) to build context-specific co-expression networks

Endoscopic Excision of Juvenile Nasopharyngeal Angiofibroma: Case Series of 20 Patients

Introduction Juvenile Nasopharyngeal Angiofibroma (JNA) is a highly vascular, benign, locally aggressive tumour of the nasopharynx. Endoscopic approach is the current accepted modality for the excision of Juvenile Nasopharyngeal Angiofibroma. The current study was undertaken to assess the outcome of this procedure at our institute. Materials and Methods A total of 20 patients of JNA at a medical college in Ahmedabad between the period of July 2015 to July 2017 were included. The tumour was staged according to Fisch system and clinical presentation, local examination, nasal endoscopy findings, radiological findings, approach of surgical resection, complications and recurrence were noted. Results  We found that endoscopic approach for the excision of juvenile nasopharyngeal angiofibroma is safe and effective technique associated with reduced post operative morbidity and low recurrence rates.  Conclusions  JNA is a rare but a potentially life-threatening disease. All young males presenting with profuse, spontaneous and recurrent epistaxis should be evaluated for JNA. Endoscopic approaches have become the procedure of choice for resection of these tumours

Optical spectroscopy-based imaging techniques for the diagnosis of breast cancer: A novel approach

There have been substantial advancements in optical spectroscopy-based imaging techniques in recent years. These developments can potentially herald a transformational change in the diagnostic pathway for diseases such as cancer. In this paper, we review the clinical and engineering aspects of novel optical spectroscopy-based imaging tools. We provide a comprehensive analysis of optical and non-optical spectroscopy-based breast cancer diagnosis techniques vis-à-vis the current standard techniques such as X-Ray mammography, ultrasonography, and tissue biopsy. The recent advancements in optical spectroscopy-based imaging systems such as Transillumination Imaging (TI) and the various types of Diffuse Optical Imaging (DOI) systems (parallel-plate, bed-based, and handheld) are examined. The engineering aspects, including mechanical, electronics, optics, automatic interpretation using artificial intelligence (AI), and ergonomics are discussed. The abilities of these technologies for measuring several cancer biomarkers such as hemoglobin, water, lipid, collagen, oxygen saturation (SO2), and tissue oxygenation index (TOI) are investigated. This article critically assesses the diagnostic ability and practical deployment of these new technologies to differentiate between the normal and cancerous tissue

Comparative analysis of transcriptional changes in zebrafish cep290 and bbs2 mutants by RNA-seq reveals upregulation of inflammatory and stress-related pathways

Acute injury to the adult zebrafish retina triggers the release of pro-inflammatory cytokines and growth factors that stimulate multiple gene regulatory networks, which ultimately stimulate Müller glia to proliferate and regenerate neurons. In contrast, zebrafish carrying mutations in cep290 or bbs2 undergo progressive loss of cone photoreceptors and exhibit signs of microglia activation and inflammation, but the mutants fail to stimulate a regeneration response. To identify transcriptional changes that occur in zebrafish mutants undergoing progressive photoreceptor degeneration, RNA-seq transcriptional profiling was performed on cep290−/− and bbs2−/− retinas. The PANTHER Classification System was used to identify biological processes and signaling pathways that were differentially expressed between mutants and wild-type siblings during degeneration. As expected, genes associated with phototransduction were downregulated in cep290 and bbs2 mutants compared to wild-type siblings. Although both cep290 and bbs2 mutants undergo proliferation of rod precursors in response to retinal degeneration, the process of negatively regulating proliferation is enriched for upregulated genes, and this negative regulation may restrict proliferation of Müller glia and inhibit regeneration. A total of 815 differentially expressed genes (DEGs) were shared by cep290 and bbs2 retinas. Genes in pathways associated with inflammation, apoptosis, stress response, and PDGF signaling were overrepresented. Identifying the genes and biological pathways that are common in zebrafish models of inherited retinal degeneration provides a foundation for future studies on the mechanisms that regulate cell death as well as processes that prohibit Müller cell reprogramming or proliferation in a model capable of retinal regeneration. The pathways will provide targets for future interventions that may promote successful regeneration of lost photoreceptors

Alterations of immune response of non-small lung cancer with azacytidine

Innovative therapies are needed for advanced Non-Small Cell Lung Cancer (NSCLC). We have undertaken a genomics based, hypothesis driving, approach to query an emerging potential that epigenetic therapy may sensitize to immune checkpoint therapy targeting PD-L1/PD-1 interaction. NSCLC cell lines were treated with the DNA hypomethylating agent azacytidine (AZA - Vidaza) and genes and pathways altered were mapped by genome-wide expression and DNA methylation analyses. AZA-induced pathways were analyzed in The Cancer Genome Atlas (TCGA) project by mapping the derived gene signatures in hundreds of lung adeno (LUAD) and squamous cell carcinoma (LUSC) samples. AZA up-regulates genes and pathways related to both innate and adaptive immunity and genes related to immune evasion in a several NSCLC lines. DNA hypermethylation and low expression of IRF7, an interferon transcription factor, tracks with this signature particularly in LUSC. In concert with these events, AZA up-regulates PD-L1 transcripts and protein, a key ligand-mediator of immune tolerance. Analysis of TCGA samples demonstrates that a significant proportion of primary NSCLC have low expression of AZA-induced immune genes, including PD-L1. We hypothesize that epigenetic therapy combined with blockade of immune checkpoints - in particular the PD-1/PD-L1 pathway - may augment response of NSCLC by shifting the balance between immune activation and immune inhibition, particularly in a subset of NSCLC with low expression of these pathways. Our studies define a biomarker strategy for response in a recently initiated trial to examine the potential of epigenetic therapy to sensitize patients with NSCLC to PD-1 immune checkpoint blockade

Continuity of transcriptomes among colorectal cancer subtypes based on meta-analysis

Background: Previous approaches to defining subtypes of colorectal carcinoma (CRC) and other cancers based on transcriptomes have assumed the existence of discrete subtypes. We analyze gene expression patterns of colorectal tumors from a large number of patients to test this assumption and propose an approach to identify potentially a continuum of subtypes that are present across independent studies and cohorts. Results: We examine the assumption of discrete CRC subtypes by integrating 18 published gene expression datasets and \u3e3700 patients, and contrary to previous reports, find no evidence to support the existence of discrete transcriptional subtypes. Using a meta-analysis approach to identify co-expression patterns present in multiple datasets, we identify and define robust, continuously varying subtype scores to represent CRC transcriptomes. The subtype scores are consistent with established subtypes (including microsatellite instability and previously proposed discrete transcriptome subtypes), but better represent overall transcriptional activity than do discrete subtypes. The scores are also better predictors of tumor location, stage, grade, and times of disease-free survival than discrete subtypes. Gene set enrichment analysis reveals that the subtype scores characterize T-cell function, inflammation response, and cyclin-dependent kinase regulation of DNA replication. Conclusions: We find no evidence to support discrete subtypes of the CRC transcriptome and instead propose two validated scores to better characterize a continuity of CRC transcriptomes

The impact of sex on gene expression across human tissues

Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation

The impact of sex on gene expression across human tissues

Many complex human phenotypes exhibit sex-differentiated characteristics, however the underlying molecular mechanisms of these differences remain largely unknown. Here, we present an extensive catalog of both sex differences in gene expression and its genetic regulation across 44 human tissue sources surveyed by GTEx (v8 release). We demonstrate that sex strongly influences gene expression levels and cellular composition of tissue samples across the human body. The effect of sex on gene expression is widespread, with a total of 37% of all genes exhibiting sex-biased expression in at least one tissue. This suggests that many if not most biological processes, and thus complex traits and diseases, are impacted by sex effects on the transciptome. We expand the identification of cis-eQTLs with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation in a single sex, including novel associations not detected with sex-agnostic approaches. Altogether we provide the most comprehensive characterization of sex differences in the human transcriptome and its regulation to date.Peer ReviewedPreprin

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas