Computational Pipeline for Human Transcriptome Quantification Using RNA-seq Data

The main theme of this thesis research is concerned with developing a computational pipeline for processing Next-generation RNA sequencing (RNA-seq) data. RNA-seq experiments generate tens of millions of short reads for each DNA/RNA sample. The alignment of a large volume of short reads to a reference genome is a key step in NGS data analysis. Although storing alignment information in the Sequence Alignment/Map (SAM) or Binary SAM (BAM) format is now standard, biomedical researchers still have difficulty accessing useful information. In order to assist biomedical researchers to conveniently access essential information from NGS data files in SAM/BAM format, we have developed a Graphical User Interface (GUI) software tool named SAMMate to pipeline human transcriptome quantification. SAMMate allows researchers to easily process NGS data files in SAM/BAM format and is compatible with both single-end and paired-end sequencing technologies. It also allows researchers to accurately calculate gene expression abundance scores

RNA CoMPASS: RNA Comprehensive Multi-Processor Analysis System for Sequencing

The main theme of this dissertation is to develop a distributed computational pipeline for processing next-generation RNA sequencing (RNA-seq) data. RNA-seq experiments generate hundreds of millions of short reads for each DNA/RNA sample. There are many existing bioinformatics tools developed for the analysis and visualization of this data, but very large studies present computational and organizational challenges that are difficult to overcome manually. We designed a comprehensive pipeline for the analysis of RNA sequencing which leverages many existing tools and parallel computing technology to facilitate the analysis of extremely large studies. RNA CoMPASS provides a web-based graphical user interface and distributed computational pipeline including endogenous transcriptome quantification and additionally the investigation of exogenous sequences

RNA CoMPASS: RNA Comprehensive Multi-Processor Analysis System for Sequencing

The main theme of this dissertation is to develop a distributed computational pipeline for processing next-generation RNA sequencing (RNA-seq) data. RNA-seq experiments generate hundreds of millions of short reads for each DNA/RNA sample. There are many existing bioinformatics tools developed for the analysis and visualization of this data, but very large studies present computational and organizational challenges that are difficult to overcome manually. We designed a comprehensive pipeline for the analysis of RNA sequencing which leverages many existing tools and parallel computing technology to facilitate the analysis of extremely large studies. RNA CoMPASS provides a web-based graphical user interface and distributed computational pipeline including endogenous transcriptome quantification and additionally the investigation of exogenous sequences

SAMMate: a GUI tool for processing short read alignments in SAM/BAM format

<p>Abstract</p> <p>Background</p> <p>Next Generation Sequencing (NGS) technology generates tens of millions of short reads for each DNA/RNA sample. A key step in NGS data analysis is the short read alignment of the generated sequences to a reference genome. Although storing alignment information in the Sequence Alignment/Map (SAM) or Binary SAM (BAM) format is now standard, biomedical researchers still have difficulty accessing this information.</p> <p>Results</p> <p>We have developed a Graphical User Interface (GUI) software tool named SAMMate. SAMMate allows biomedical researchers to quickly process SAM/BAM files and is compatible with both single-end and paired-end sequencing technologies. SAMMate also automates some standard procedures in DNA-seq and RNA-seq data analysis. Using either standard or customized annotation files, SAMMate allows users to accurately calculate the short read coverage of genomic intervals. In particular, for RNA-seq data SAMMate can accurately calculate the gene expression abundance scores for customized genomic intervals using short reads originating from both exons and exon-exon junctions. Furthermore, SAMMate can quickly calculate a whole-genome signal map at base-wise resolution allowing researchers to solve an array of bioinformatics problems. Finally, SAMMate can export both a wiggle file for alignment visualization in the UCSC genome browser and an alignment statistics report. The biological impact of these features is demonstrated via several case studies that predict miRNA targets using short read alignment information files.</p> <p>Conclusions</p> <p>With just a few mouse clicks, SAMMate will provide biomedical researchers easy access to important alignment information stored in SAM/BAM files. Our software is constantly updated and will greatly facilitate the downstream analysis of NGS data. Both the source code and the GUI executable are freely available under the GNU General Public License at <url>http://sammate.sourceforge.net</url>.</p

Pathology Steered Stratification Network for Subtype Identification in Alzheimer's Disease

Alzheimer's disease (AD) is a heterogeneous, multifactorial neurodegenerative disorder characterized by beta-amyloid, pathologic tau, and neurodegeneration. There are no effective treatments for Alzheimer's disease at a late stage, urging for early intervention. However, existing statistical inference approaches of AD subtype identification ignore the pathological domain knowledge, which could lead to ill-posed results that are sometimes inconsistent with the essential neurological principles. Integrating systems biology modeling with machine learning, we propose a novel pathology steered stratification network (PSSN) that incorporates established domain knowledge in AD pathology through a reaction-diffusion model, where we consider non-linear interactions between major biomarkers and diffusion along brain structural network. Trained on longitudinal multimodal neuroimaging data, the biological model predicts long-term trajectories that capture individual progression pattern, filling in the gaps between sparse imaging data available. A deep predictive neural network is then built to exploit spatiotemporal dynamics, link neurological examinations with clinical profiles, and generate subtype assignment probability on an individual basis. We further identify an evolutionary disease graph to quantify subtype transition probabilities through extensive simulations. Our stratification achieves superior performance in both inter-cluster heterogeneity and intra-cluster homogeneity of various clinical scores. Applying our approach to enriched samples of aging populations, we identify six subtypes spanning AD spectrum, where each subtype exhibits a distinctive biomarker pattern that is consistent with its clinical outcome. PSSN provides insights into pre-symptomatic diagnosis and practical guidance on clinical treatments, which may be further generalized to other neurodegenerative diseases

Selective reconstitution of liver cholesterol biosynthesis promotes lung maturation but does not prevent neonatal lethality in Dhcr7 null mice

BACKGROUND: Targeted disruption of the murine 3β-hydroxysterol-Δ7-reductase gene (Dhcr7), an animal model of Smith-Lemli-Opitz syndrome, leads to loss of cholesterol synthesis and neonatal death that can be partially rescued by transgenic replacement of DHCR7 expression in brain during embryogenesis. To gain further insight into the role of non-brain tissue cholesterol deficiency in the pathophysiology, we tested whether the lethal phenotype could be abrogated by selective transgenic complementation with DHCR7 expression in the liver. RESULTS: We generated mice that carried a liver-specific human DHCR7 transgene whose expression was driven by the human apolipoprotein E (ApoE) promoter and its associated liver-specific enhancer. These mice were then crossed with Dhcr7+/- mutants to generate Dhcr7-/- mice bearing a human DHCR7 transgene. Robust hepatic transgene expression resulted in significant improvement of cholesterol homeostasis with cholesterol concentrations increasing to 80~90 % of normal levels in liver and lung. Significantly, cholesterol deficiency in brain was not altered. Although late gestational lung sacculation defect reported previously was significantly improved, there was no parallel increase in postnatal survival in the transgenic mutant mice. CONCLUSION: The reconstitution of DHCR7 function selectively in liver induced a significant improvement of cholesterol homeostasis in non-brain tissues, but failed to rescue the neonatal lethality of Dhcr7 null mice. These results provided further evidence that CNS defects caused by Dhcr7 null likely play a major role in the lethal pathogenesis of Dhcr7(-/- )mice, with the peripheral organs contributing the morbidity

Supramolecular Assembly and Stimuli-Responsive Behavior of Multielement Hybrid Copolymers

Toward the organic polymer, hybrid elements can be defined as those beyond C, H, O, and N. Polymers comprising hybrid elements, such as Si, P, B, or metal ions have attracted great attention in the design of high performance or smart materials. Introduction of hybrid elements into a polymeric network may also lead to the formation of new intermolecular interactions, thus promote the self-organization of polymer chains to form controllable structures and morphologies. In this chapter, we introduce some of the recent important development in the design and self-assembly of hybrid amphiphilic copolymers. Specific attention was paid on the hybrid amphiphilic copolymers containing POSS, boronic acid, or boronate functional moieties. We introduce the design, synthesis, self-assembly behavior, and properties of these hybrid amphiphilic copolymers in detail. Also, the advantages and drawbacks of these polymers and their corresponding nanoassemblies are discussed

A global transcriptional network connecting noncoding mutations to changes in tumor gene expression.

Although cancer genomes are replete with noncoding mutations, the effects of these mutations remain poorly characterized. Here we perform an integrative analysis of 930 tumor whole genomes and matched transcriptomes, identifying a network of 193 noncoding loci in which mutations disrupt target gene expression. These 'somatic eQTLs' (expression quantitative trait loci) are frequently mutated in specific cancer tissues, and the majority can be validated in an independent cohort of 3,382 tumors. Among these, we find that the effects of noncoding mutations on DAAM1, MTG2 and HYI transcription are recapitulated in multiple cancer cell lines and that increasing DAAM1 expression leads to invasive cell migration. Collectively, the noncoding loci converge on a set of core pathways, permitting a classification of tumors into pathway-based subtypes. The somatic eQTL network is disrupted in 88% of tumors, suggesting widespread impact of noncoding mutations in cancer

Exopolysaccharide, Isolated From a Novel Strain Bifidobacterium breve lw01 Possess an Anticancer Effect on Head and Neck Cancer – Genetic and Biochemical Evidences

Probiotic bacteria exopolysaccharides (EPS) have been recognized as molecules that regulate immune development and have anti-inflammation and anticancer effects. Yet, these bioactivities are of interspecies diversity; thus, examining the gene clusters of EPS and biosynthesis pathways are essential for selecting the better application of specific EPS. In this study, we isolated a new Bifidobacterium strain, named B. breve lw01. A complete genome of B. breve lw01 was sequenced revealing a circular 2,313,172 bp chromosome. Furthermore, a deep excavation of genome sequence from different database based on the comparison-selected results was performed to explore the gene cluster responsible for EPS synthesis. We found that B. breve lw01 harbors a new EPS-encoding cluster with 14 predicted genes, which could be divided into three groups according to the biosynthesis pathway hypothesis. Using tertiary purification, high purity EPS were obtained. EPS is composed of rhamnose (Rha), arabinose (Ara), galactose (Gal), glucose (Glc), and mannose (Man) in a molar ratio of 0.35:0.44:1.38:0.67:1.65. With reference to its bioactivity, it showed to possess anticancer activity against Head and Neck Squamous Cell Carcinoma cell line by regulating cell cycle arrest and cell apoptosis promotion. To sum up, this study examined the biosynthesis and bioactivity of EPS using a new isolated B. breve strain, which could be used to clarify its further application in functional food or drug industry