Meta-Analysis of Kindling-Induced Gene Expression Changes in the Rat Hippocampus

Numerous studies have been performed to examine gene expression patterns in the rodent hippocampus in the kindling model of epilepsy. However, recent reviews of this literature have revealed limited agreement among studies. Because this conclusion was based on retrospective comparison of reported “hit lists” from individual studies, we hypothesized that re-analysis of the original expression data would help address this concern. In this paper, we reanalyzed four genome-wide expression studies of excitotoxin-induced kindling in rat and performed a statistical meta-analysis. The meta-analysis revealed over 800 genes which show significant change in expression 24 h after initial seizure induction, and 59 genes altered after 10 days. To evaluate our results in light of previous work, we assembled a reference list of genes formed from a consensus of the published literature. Our profiles include most of the genes in this reference list, and most of the additional genes are from pathways or biological processes previously recognized to be altered in kindling. In addition our results emphasized expression changes in lipid metabolism and protein degradation pathways. We conclude that a cautious re-analysis of published expression data can help illuminate genes and pathways underling kindling. Supplementary Material is available at http://www.chibi.ubc.ca/faculty/pavlidis/meta-analysis-of-brain-kindling

Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma

Follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) are the two most common non-Hodgkin lymphomas (NHLs). Here we sequenced tumour and matched normal DNA from 13 DLBCL cases and one FL case to identify genes with mutations in B-cell NHL. We analysed RNA-seq data from these and another 113 NHLs to identify genes with candidate mutations, and then re-sequenced tumour and matched normal DNA from these cases to confirm 109 genes with multiple somatic mutations. Genes with roles in histone modification were frequent targets of somatic mutation. For example, 32% of DLBCL and 89% of FL cases had somatic mutations in MLL2, which encodes a histone methyltransferase, and 11.4% and 13.4% of DLBCL and FL cases, respectively, had mutations in MEF2B, a calcium-regulated gene that cooperates with CREBBP and EP300 in acetylating histones. Our analysis suggests a previously unappreciated disruption of chromatin biology in lymphomagenesis

Evaluating and improving the accuracy of computational gene-finding on mammalian DNA sequences

This thesis presents work in one of the main research areas in Computational Biology: computational gene-finding in higher eukaryotic genomic DNA. Programs for identification of gene structures have been in existence for more than a decade, but today they are used more extensively than ever to analyze the enormous amount of sequence data coming from various genome sequencing projects. Consequently, their impact on research in the area of genomics and beyond is substantial. The thesis has two distinguishable parts: the first presents an evaluation and comprehensive analysis of the current generation of gene-finding programs. For this purpose a new, thoroughly filtered and biologically validated test dataset of genomic sequences was assembled. The basic prediction accuracy of the programs tested was calculated and the relationships between various sequence and prediction features and programs' accuracy were analyzed. The second part of the thesis presents the development and results of methods for combination of the predictions from two gene-finding programs. Three methods were developed, each having some advantages over the other two, and each of them offering higher prediction accuracy on the test dataset than any gene-finding program currently available.Science, Faculty ofComputer Science, Department ofGraduat

The role of pre-mRNA secondary structure in gene splicing in Saccharomyces cerevisiae

The process of gene splicing, which involves the excision of introns from a pre-mRNA and joining of exons into mature mRNA is one of the essential steps in protein production. Although this process has been extensively studied, it is still not clear how the splice sites are accurately identified and correctly paired across the intron. It is currently believed that identification is accomplished through base-pairing interactions between the splice sites and the spliceosomal snRNAs. However, the relatively conserved sequences at the splice sites are often indistinguishable from similar sequences that are not involved in splicing. This suggests that not only sequence but other features of pre-mRNA may play a role in splicing. A number of authors have studied the effects of pre-mRNA secondary structure on splicing, but these studies are usually limited to one or a small number of genes, and therefore the conclusions are usually gene-specific. This thesis aims to complement previous studies of the role of pre-mRNA secondary structure in splicing by performing a comprehensive computational study of structural characteristics of Saccharomyces cerevisiae introns and their possible role in pre-mRNA splicing. We identify long-range interactions in the secondary structures of all long introns that effectively shorten the distance between the donor site and the branchpoint sequence. The shortened distances are distributed similarly to the branchpoint distances in short yeast introns, which are presumed to be optimal for splicing, and very different from the corresponding distances in random and exonic sequences. We show that in the majority of cases, these stems are conserved among closely related yeast species. Furthermore, we formulate a model of structural requirements for efficient splicing of yeast introns that explains previous splicing studies of the RP51B intron. We also test our model by laboratory experiments, which verify our computational predictions. Finally, we use different computational approaches to identify any structural context at the boundaries or within yeast introns. Our study reveals statistically significant biases, which we use to train machine learning classifiers to distinguish between real and pseudo splice sites.Science, Faculty ofComputer Science, Department ofGraduat

Evaluation of Gene-Finding Programs on Mammalian Sequences

We present an independent comparative analysis of seven recently developed gene-finding programs: FGENES, GeneMark.hmm, Genie, Genscan, HMMgene, Morgan, and MZEF. For evaluation purposes we developed a new, thoroughly filtered, and biologically validated dataset of mammalian genomic sequences that does not overlap with the training sets of the programs analyzed. Our analysis shows that the new generation of programs has substantially better results than the programs analyzed in previous studies. The accuracy of the programs was also examined as a function of various sequence and prediction features, such as G + C content of the sequence, length and type of exons, signal type, and score of the exon prediction. This approach pinpoints the strengths and weaknesses of each individual program as well as those of computational gene-finding in general. The dataset used in this analysis (HMR195) as well as the tables with the complete results are available at http://www.cs.ubc.ca/∼rogic/evaluation/