Optimization Techniques For Next-Generation Sequencing Data Analysis

High-throughput RNA sequencing (RNA-Seq) is a popular cost-efficient technology with many medical and biological applications. This technology, however, presents a number of computational challenges in reconstructing full-length transcripts and accurately estimate their abundances across all cell types. Our contributions include (1) transcript and gene expression level estimation methods, (2) methods for genome-guided and annotation-guided transcriptome reconstruction, and (3) de novo assembly and annotation of real data sets. Transcript expression level estimation, also referred to as transcriptome quantification, tackle the problem of estimating the expression level of each transcript. Transcriptome quantification analysis is crucial to determine similar transcripts or unraveling gene functions and transcription regulation mechanisms. We propose a novel simulated regression based method for transcriptome frequency estimation from RNA-Seq reads. Transcriptome reconstruction refers to the problem of reconstructing the transcript sequences from the RNA-Seq data. We present genome-guided and annotation-guided transcriptome reconstruction methods. Empirical results on both synthetic and real RNA-seq datasets show that the proposed methods improve transcriptome quantification and reconstruction accuracy compared to currently state of the art methods. We further present the assembly and annotation of Bugula neritina transcriptome (a marine colonial animal), and Tallapoosa darter genome (a species-rich radiation freshwater fish)

Computational Methods for Sequencing and Analysis of Heterogeneous RNA Populations

Next-generation sequencing (NGS) and mass spectrometry technologies bring unprecedented throughput, scalability and speed, facilitating the studies of biological systems. These technologies allow to sequence and analyze heterogeneous RNA populations rather than single sequences. In particular, they provide the opportunity to implement massive viral surveillance and transcriptome quantification. However, in order to fully exploit the capabilities of NGS technology we need to develop computational methods able to analyze billions of reads for assembly and characterization of sampled RNA populations. In this work we present novel computational methods for cost- and time-effective analysis of sequencing data from viral and RNA samples. In particular, we describe: i) computational methods for transcriptome reconstruction and quantification; ii) method for mass spectrometry data analysis; iii) combinatorial pooling method; iv) computational methods for analysis of intra-host viral populations

October 3, 2008, Ohio University Board of Trustees Meeting Minutes

Meeting minutes document the activities of Ohio University\u27s Board of Trustees

Sequence-specific sequence comparison using pairwise statistical significance

Sequence comparison is one of the most fundamental computational problems in bioinformatics for which many approaches have been and are still being developed. In particular, pairwise sequence alignment forms the crux of both DNA and protein sequence comparison techniques, which in turn forms the basis of many other applications in bioinformatics. Pairwise sequence alignment methods align two sequences using a substitution matrix consisting of pairwise scores of aligning different residues with each other (like BLOSUM62), and give an alignment score for the given sequence-pair. The biologists routinely use such pairwise alignment programs to identify similar, or more specifically, related sequences (having common ancestor). It is widely accepted that the relatedness of two sequences is better judged by statistical significance of the alignment score rather than by the alignment score alone. This research addresses the problem of accurately estimating statistical significance of pairwise alignment for the purpose of identifying related sequences, by making the sequence comparison process more sequence-specific. The major contributions of this research work are as follows. Firstly, using sequence-specific strategies for pairwise sequence alignment in conjunction with sequence-specific strategies for statistical significance estimation, wherein accurate methods for pairwise statistical significance estimation using standard, sequence-specific, and position-specific substitution matrices are developed. Secondly, using pairwise statistical significance to improve the performance of the most popular database search program PSI-BLAST. Thirdly, design and implementation of heuristics to speed-up pairwise statistical significance estimation by an factor of more than 200. The implementation of all the methods developed in this work is freely available online. With the all-pervasive application of sequence alignment methods in bioinformatics using the ever-increasing sequence data, this work is expected to offer useful contributions to the research community

Role of aquaporins during hepatocellular carcinoma initiation and progression.

Aquaporins (AQPs) are a family of proteinaceous water channels involved in bile production and apoptosis. Aquaporins 8, 9 and 0 are expressed in hepatocytes and cAMP dependent signalling regulates AQP8 expression and localization in normal hepatocytes. Also, AQP9 has promoter binding sites for AP-1, a downstream transcription factor in IL-6 signaling. The role of AQP8 and 9 in hepatocellular carcinoma (HCC) initiation and progression has not been determined. The role of AQP8/9 in HCC initiation and progression was examined in rodent models of HCC as well as human HCC. Further, the role of cAMP and IL6 in regulating AQP8/9 expression and/or localization was examined. To examine the role of AQP8/9 in HCC initiation and progression both a rat, hepatoma cell inoculation model and a diethylnitrosamine (DEN) initiated, hepatocarcinogenic, progressive mouse model, were used. A rat hepatoma cell line was used to examine the role of cAMP and IL6 on AQP8/9 expression and localization. While IL6 significantly affected AQP8 membrane localization, cAMP did not. Further, there was no significant affect on AQP8/9 expression from cAMP pathway modulation or IL6 exposure. However, cAMP pathway modulation did significantly affect cell responsiveness to osmotic challenge. In a mouse model of HCC, AQP8 expression in plasma membrane was significantly higher in mice euthanized 24 weeks after DEN injection compared to control mice. However, AQP8 and 9 membrane localization was significantly lower in mice euthanized 48 weeks after DEN injection compared to control mice. In human HCC, AQP9 membrane localization is significantly decreased in tumor tissue compared to non-tumor tissue. Also, AQP8/9 expression did not correlate with known risk factors for HCC. Lastly, doxycycline controlled expression of AQP8, in a rat model of HCC, significantly inhibited tumor progression in vivo. In summary, AQP8 membrane localization is affected by IL6 exposure but cAMP significantly affects cell responsiveness to osmotic stress. Also, AQP9 membrane expression is reduced in rodent models of HCC as well as human HCC. Finally, expression of AQP8 in a rat model HCC, in vivo, reduced tumor proliferation

Complementary Pediatrics

Complementary Pediatrics covers complementary issues of pediatric subspecialties consisting of ophthalmologic, surgical, psychosocial and administrative issues of frequently used medications. This book volume with its 16 chapters will help get us and patients enlightened with the new developments on these subspecialties' area

Major v. Security Equipment Corp. Clerk\u27s Record v. 1 Dckt. 39414

https://digitalcommons.law.uidaho.edu/idaho_supreme_court_record_briefs/2187/thumbnail.jp