The role of splicing factors and small nuclear RNAs in spliceosomal formation

Protein coding genes are comprised of protein-coding exons and non-protein-coding introns. The process of splicing involves removal of the introns and joining of the exons to form a mature messenger RNA, which subsequently undergoes translation into polypeptide. The spliceosome is a large, RNA/protein assembly of five small nuclear RNAs as well as over 300 proteins, which catalyzes intron removal and exon ligation. The selection of specific exons for inclusion in the mature messenger RNA is spatiotemporally regulated and results in production of an enormous diversity of polypeptides from a single gene locus. This phenomenon, known as alternative splicing, is regulated, in part, by protein splicing factors, which target the spliceosome to exon/intron boundaries. The first part of my dissertation (Chapters II and III) focuses on the discovery and characterization of the 45 kilodalton FK506 binding protein (FKBP45), which I discovered in the silk moth, Bombyx mori, as a U1 small nuclear RNA binding protein. This protein family binds the immunosuppressants FK506 and rapamycin and contains peptidyl-prolyl cis-trans isomerase activity, which converts polypeptides from cis to trans about a proline residue. This is the first time that an FKBP has been identified in the spliceosome. The second section of my dissertation (Chapters IV, V, VI and VII) is an investigation of the potential role of small nuclear RNA sequence variants in the control of splicing. I identified 46 copies of small nuclear RNAs in the 6X whole genome shotgun of the Bombyx mori p50T strain. These variants may play a role in differential binding of specific proteins that mediate alternative splicing. Along these lines, further investigation of U2 snRNA sequence variants in Bombyx mori demonstrated that some U2 snRNAs preferentially assemble into high molecular weight spliceosomal complexes over others. Expression of snRNA variants may represent another mechanism by which the cell is able to fine tune the splicing process.

Comparative transcriptome analyses of Pseudomonas aeruginosa

One of the hallmarks of bacterial survival is their ability to adapt rapidly to changing environmental conditions. Niche adaptation is a response to the signals received that are relayed, often to regulators that modulate gene expression. In the post-genomic era, DNA microarrays are used to study the dynamics of gene expression on a global scale. Numerous studies have used Pseudomonas aeruginosa--a Gram-negative environmental and opportunistic human pathogenic bacterium--as the model organism in whole-genome transcriptome analysis. This paper reviews the transcriptome studies that have led to immense advances in our understanding of the biology of this intractable human pathogen. Comparative analysis of 23 P. aeruginosa transcriptome studies has led to the identification of a unique set of genes that are signal specific and a core set that is differentially regulated. The 303 genes in the core set are involved in bacterial homeostasis, making them attractive therapeutic targets.

The Role of Splicing Factors and Small Nuclear RNAS in Spliceosomal Formation

Protein coding genes are comprised of protein-coding exons and non-protein-coding introns. The process of splicing involves removal of the introns and joining of the exons to form a mature messenger RNA, which subsequently undergoes translation into polypeptide. The spliceosome is a large, RNA/protein assembly of five small nuclear RNAs as well as over 300 proteins, which catalyzes intron removal and exon ligation. The selection of specific exons for inclusion in the mature messenger RNA is spatio-temporally regulated and results in production of an enormous diversity of polypeptides from a single gene locus. This phenomenon, known as alternative splicing, is regulated, in part, by protein splicing factors, which target the spliceosome to exon/intron boundaries. The first part of my dissertation (Chapters II and III) focuses on the discovery and characterization of the 45 kilodalton FK506 binding protein (FKBP45), which I discovered in the silk moth, Bombyx mori, as a U1 small nuclear RNA binding protein. This protein family binds the immunosuppressants FK506 and rapamycin and contains peptidyl-prolyl cis-trans isomerase activity, which converts polypeptides from cis to trans about a proline residue. This is the first time that an FKBP has been identified in the spliceosome. The second section of my dissertation (Chapters IV, V, VI and VII) is an investigation of the potential role of small nuclear RNA sequence variants in the control of splicing. I identified 46 copies of small nuclear RNAs in the 6X whole genome shotgun of the Bombyx mori p50T strain. These variants may play a role in differential binding of specific proteins that mediate alternative splicing. Along these lines, further investigation of U2 snRNA sequence variants in Bombyx mori demonstrated that some U2 snRNAs preferentially assemble into high molecular weight spliceosomal complexes over others. Expression of snRNA variants may represent another mechanism by which the cell is able to fine tune the splicing process.

Towards the prediction of mutations in genomic sequences

Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today's cancer research. Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the normal variants in the same patient. Analysis of this data provides a catalog of somatic variants, present in tumor genome but not in the normal tissue DNA. In this dissertation, we present a new computational framework to the problem of predicting the number of mutations on a chromosome for a certain patient, which is a fundamental problem in clinical and research fields. We begin this dissertation with the development of a framework system that is capable of utilizing published data from a longitudinal study of patients with acute myeloid leukemia (AML), who's DNA from both normal as well as malignant tissues was subjected to NGS analysis at various points in time. By processing the sequencing data at the time of cancer diagnosis using the components of our framework, we tested it by predicting the genomic regions to be mutated at the time of relapse and, later, by comparing our results with the actual regions that showed mutations (discovered at relapse time). We demonstrate that this coupling of the algorithm pipeline can drastically improve the predictive abilities of searching a reliable molecular signature. Arguably, the most important result of our research is its superior performance to other methods like Radial Basis Function Network, Sequential Minimal Optimization, and Gaussian Process. In the final part of this dissertation, we present a detailed significance, stability and statistical analysis of our model. A performance comparison of the results are presented. This work clearly lays a good foundation for future research for other types of cancer.^