Genomic imprinting refers to the parent-of-origin specific monoallelic expression of a gene. Imprinted genes are often clustered in the genome and their expression is regulated by an imprinting centre (IC). ICs are regions of DNA that propagate the parental specific regulation of gene expression, which are usually characterized by differential DNA methylation, histone marks and the presence of non-coding RNAs. Beckwith-Wiedemann syndrome (BWS) is an overgrowth syndrome associated with the dysregulation of imprinted gene expression on human chromosome band 11p15.5. The 11p15.5 imprinted region has two imprinting centres, IC1 and IC2. IC1 is telomeric and regulates the imprinted expression of the genes H19 and IGF2. IC2 is ~700kb centromeric and is associated with a cluster of nine imprinted genes including CDKN1C, KCNQ1 and an imprinted non-coding RNA associated with IC2, KCNQ1OT1. Loss of differential DNA methylation at IC2 is seen in 50% of patients with BWS with loss of imprint of the non-coding RNA KCNQ1OT1 and associated with a decreased expression of the putative tumour suppressor CDKN1C. Patients with BWS also have a thousand-fold increased risk of pediatric cancer. The focus of this thesis involves investigation of dysregulation of imprinting in three groups of BWS patients. Firstly, I show that BWS patients with alveolar rhabdomyosarcoma have constitutional loss of methylation at IC2 and biallelic expression of KCNQ1OT1. Secondly, loss of methylation at IC2 has been previously associated with female monozygotic twins discordant for BWS. In male monozygotic twins with BWS, however, the molecular lesions reflect the molecular heterogeneity seen in BWS singletons. Thirdly, BWS patients associated with translocations and inversions that have breakpoints within the KCNQ1 gene near IC2 show regional gain of DNA methylation around the breakpoint and decreased expression of CDKN1C. Therefore, using a rare collection of BWS patients, I have attempted to determine the various roles of the imprinting centres IC1 and IC2 and their involvement in tumourigenesis, monozygotic twinning and structural chromosomal rearrangements causing BWS.

Genomic rearrangements, particularly deletions and duplications, are known to cause many genetic disorders. The chromosome 7q11.23 region in humans is prone to recurrent chromosomal rearrangement, due to the presence of low copy repeats that promote non-allelic homologous recombination. The most well characterized rearrangement of 7q11.23 is a hemizygous 1.5 million base pair (Mb) deletion spanning more than 25 genes. This deletion causes Williams-Beuren Syndrome (WBS; OMIM 194050), a multisystem developmental disorder with distinctive physical and behavioural features. Other rearrangements of the region lead to phenotypes distinct from that of WBS. Here we describe the first individual identified with duplication of the same 1.5 Mb region, resulting in severe impairment of expressive language, in striking contrast to people with WBS who have relatively well preserved language skills. We also describe the identification of a new gene for a severe form of childhood epilepsy through the analysis of individuals with deletions on chromosome 7 that extend beyond the boundaries typical for WBS. This gene, MAGI2, is part of the large protein scaffold at the post-synaptic membrane and provides a new avenue of research into both the molecular basis of infantile spasms and the development of effective therapies. Individuals with smaller than typical deletions of 7q11.23 have delineated a minimal critical region for WBS and have implicated two members of the TFII-I transcription factor family. To better understand the contribution of these genes to WBS, I have generated animal models with these genes deleted singly and in combination. Disruption of the first gene, Gtf2ird1, resulted in phenotypes reminiscent of WBS including alterations in social behaviour, natural fear response and anxiety. An alteration in serotonin function was identified in the frontal cortex and may be linked to these behavioural phenotypes. Together with a model for the second gene, Gtf2i, and the double deletion model that was generated using Cre-loxP technology, these resources will permit the study of the individual and additive effects of hemizygosity for Gtf2i and Gtf2ird1 and will greatly expand our understanding of the role the TFII-I gene family in WBS.

Genomic imprinting refers to the parent-of-origin specific monoallelic expression of a gene. Imprinted genes are often clustered in the genome and their expression is regulated by an imprinting centre (IC). ICs are regions of DNA that propagate the parental specific regulation of gene expression, which are usually characterized by differential DNA methylation, histone marks and the presence of non-coding RNAs. Beckwith-Wiedemann syndrome (BWS) is an overgrowth syndrome associated with the dysregulation of imprinted gene expression on human chromosome band 11p15.5. The 11p15.5 imprinted region has two imprinting centres, IC1 and IC2. IC1 is telomeric and regulates the imprinted expression of the genes H19 and IGF2. IC2 is ~700kb centromeric and is associated with a cluster of nine imprinted genes including CDKN1C, KCNQ1 and an imprinted non-coding RNA associated with IC2, KCNQ1OT1. Loss of differential DNA methylation at IC2 is seen in 50% of patients with BWS with loss of imprint of the non-coding RNA KCNQ1OT1 and associated with a decreased expression of the putative tumour suppressor CDKN1C. Patients with BWS also have a thousand-fold increased risk of pediatric cancer. The focus of this thesis involves investigation of dysregulation of imprinting in three groups of BWS patients. Firstly, I show that BWS patients with alveolar rhabdomyosarcoma have constitutional loss of methylation at IC2 and biallelic expression of KCNQ1OT1. Secondly, loss of methylation at IC2 has been previously associated with female monozygotic twins discordant for BWS. In male monozygotic twins with BWS, however, the molecular lesions reflect the molecular heterogeneity seen in BWS singletons. Thirdly, BWS patients associated with translocations and inversions that have breakpoints within the KCNQ1 gene near IC2 show regional gain of DNA methylation around the breakpoint and decreased expression of CDKN1C. Therefore, using a rare collection of BWS patients, I have attempted to determine the various roles of the imprinting centres IC1 and IC2 and their involvement in tumourigenesis, monozygotic twinning and structural chromosomal rearrangements causing BWS.

Genomic rearrangements, particularly deletions and duplications, are known to cause many genetic disorders. The chromosome 7q11.23 region in humans is prone to recurrent chromosomal rearrangement, due to the presence of low copy repeats that promote non-allelic homologous recombination. The most well characterized rearrangement of 7q11.23 is a hemizygous 1.5 million base pair (Mb) deletion spanning more than 25 genes. This deletion causes Williams-Beuren Syndrome (WBS; OMIM 194050), a multisystem developmental disorder with distinctive physical and behavioural features. Other rearrangements of the region lead to phenotypes distinct from that of WBS. Here we describe the first individual identified with duplication of the same 1.5 Mb region, resulting in severe impairment of expressive language, in striking contrast to people with WBS who have relatively well preserved language skills. We also describe the identification of a new gene for a severe form of childhood epilepsy through the analysis of individuals with deletions on chromosome 7 that extend beyond the boundaries typical for WBS. This gene, MAGI2, is part of the large protein scaffold at the post-synaptic membrane and provides a new avenue of research into both the molecular basis of infantile spasms and the development of effective therapies. Individuals with smaller than typical deletions of 7q11.23 have delineated a minimal critical region for WBS and have implicated two members of the TFII-I transcription factor family. To better understand the contribution of these genes to WBS, I have generated animal models with these genes deleted singly and in combination. Disruption of the first gene, Gtf2ird1, resulted in phenotypes reminiscent of WBS including alterations in social behaviour, natural fear response and anxiety. An alteration in serotonin function was identified in the frontal cortex and may be linked to these behavioural phenotypes. Together with a model for the second gene, Gtf2i, and the double deletion model that was generated using Cre-loxP technology, these resources will permit the study of the individual and additive effects of hemizygosity for Gtf2i and Gtf2ird1 and will greatly expand our understanding of the role the TFII-I gene family in WBS.

Although DNA microarray can detect multiple DNA samples simultaneously, current detection techniques involve PCR and other traditional procedures. In this study, a sensitive, specific and rapid detection method, which eliminates PCR and other lengthy processes, for pathogenic DNA is presented. This technology is based on the hybridization of target DNA to the immobilized probe, extension of probe DNAs using the target-DNA as a template and signal generation by streptavidin-horseradish peroxidase and substrate. This method is highly specific and sensitive, allowing single-nucleotide-base mismatches discrimination and the detection at femtomole level. The experiments are designed to achieve short hybridization time. Therefore, satisfactory signal can be detected within minutes, allowing the rapid detection of multiple pathogenic DNA. Most importantly, the E. coli genomic DNA can be detected using this technology. In conclusion, this detection method is useful for applications including on-site pathogenic disease detection, crime scene investigation, and pathogen inspection in the environment.

<p>Genetic variation is a natural occurrence in the genome that contributes to the phenotypic differences observed between individuals as well as the phenotypic outcomes of various diseases, including infectious disease and cancer. Single nucleotide polymorphisms (SNPs) have been identified as genetic factors influencing host susceptibility to infectious disease while the study of copy number variation (CNV) in various cancers has led to the identification of causal genetic factors influencing tumor formation and severity. In this work, we evaluated the association between genomic variation and disease phenotypes to identify SNPs contributing to host susceptibility in Staphylococcus aureus (<italic>S. aureus</italic>) infection and to characterize a nervous system brain tumor, known as oligodendroglioma (OD), using the CNV observed in tumors with varying degree of malignancy.</p><p>Using SNP data, we utilized a computational approach, known as in silico haplotype mapping (ISHM), to identify genomic regions significantly associated with susceptibility to <italic>S. aureus</italic> infection in inbred mouse strains. We conducted ISHM on four phenotypes collected from <italic>S. aureus</italic> infected mice and identified genes contained in the significant regions, which were considered to be potential candidate genes. Gene expression studies were then conducted on inbred mice considered to be resistant or susceptible to <italic>S. aureus</italic> infection to identify genes differentially expressed between the two groups, which provided biological validation of the genes identified in significant ISHM regions. Genes identified by both analyses were considered our top priority genes and known biological information about the genes was used to determine their function roles in susceptibility to <italic>S. aureus</italic> infection.</p><p> We then evaluated CNV in subtypes of ODs to characterize the tumors by their genomic aberrations. We conducted array-based comparative genomic hybridization (CGH) on 74 ODs to generate genomic profiles that were classified by tumor grade, providing insight about the genomic changes that typically occur in patients with OD ranging from the less to more severe tumor types. Additionally, smaller genomic intervals with substantial copy number differences between normal and OD DNA samples, known as minimal critical regions (MCRs), were identified among the tumors. The genomic regions with copy number changes were interrogated for genes and assessed for their biological roles in the tumors' phenotype and formation. This information was used to assess the validity of using genomic variation in these tumors to further classify these tumors in addition to standard classification techniques. </p><p> The studies described in this project demonstrate the utility of using genetic variation to study disease phenotypes and applying computational and experimental techniques to identify the underlying genetic factors contributing to disease pathogenesis. Moreover, the continued development of similar approaches could aid in the development of new diagnostic procedures as well as novel therapeutics for the generation of more personalized treatments. The genomic regions with copy number changes were interrogated for genes and assessed for their biological roles in the tumors' phenotype and formation. This information was used to assess the validity of using genomic variation in these tumors to further classify these tumors in addition to standard classification techniques.</p><p> The studies described in this project demonstrate the utility of using genetic variation to study disease phenotypes and applying computational and experimental techniques to identify the underlying genetic factors contributing to disease pathogenesis. Moreover, the continued development of similar approaches could aid in the development of new diagnostic procedures as well as novel therapeutics for the generation of more personalized treatments.</p> / Dissertation

The last decade has been marked by unprecedented growth in both the production of biomedical data and the amount of published literature discussing it. Almost every known or postulated piece of information pertaining to genes, proteins, and their role in biological processes is reported somewhere in the vast amount of published biomedical literature. We believe the ability to rapidly survey and analyze this literature and extract pertinent information constitutes a necessary step toward both the design and the interpretation of any large-scale experiment. Moreover, automated literature mining offers a yet untapped opportunity to integrate many fragments of information gathered by researchers from multiple fields of expertise into a complete picture exposing the interrelated roles of various genes, proteins, and chemical reactions in cells and organisms. In this thesis, we show that functional keywords in biomedical literature, particularly Medline, represent very valuable information and can be used to discover new genomic knowledge. To validate our claim we present an investigation into text mining biomedical literature to assist microarray data analysis, yeast gene function classification, and biomedical literature categorization. We conduct following studies: 1. We test sets of genes to discover common functional keywords among them and use these keywords to cluster them into groups; 2. We show that it is possible to link genes to diseases by an expert human interpretation of the functional keywords for the genes- none of these diseases are as yet mentioned in public databases; 3. By clustering genes based on commonality of functional keywords it is possible to group genes into meaningful clusters that reveal more information about their functions, link to diseases and roles in metabolism pathways; 4. Using extracted functional keywords, we are able to demonstrate that for yeast genes, we can make a better functional grouping of genes in comparison to available public microarray and phylogenetic databases; 5. We show an application of our approach to literature classification. Using functional keywords as features, we are able to extract epidemiological abstracts automatically from Medline with higher sensitivity and accuracy than a human expert.

Genomic sequence databases, like GenBank, EMBL, are widely used by molecular biologists for homology searching. Because of the long length of each genomic sequence and the increase of the size of genomic sequence databases, the importance of efficient searching methods for fast queries grows. The DNA sequences are composed of four kinds of nucleotides, and these genomic sequences can be regarded as the text strings. However, there is no concept of words in a genomic sequence, which makes the search of the genomic sequence in the genomic database much difficult. Approximate String Matching (ASM) with k errors is considered for genomic sequences, where k errors would be caused by insertion, deletion, and replacement operations. Filtration of the DNA sequence is a widely adopted technique to reduce the number of the text areas (i.e., candidates) for further verification. In most of the filter methods, they first split the database sequence into q-grams. A sequence of grams (subpatterns) which match some part of the text will be passed as a candidate. The match problem of grams with the part of the text could be speed up by using the index structure for the exact match. Candidates will then be examined by dynamic programming to get the final result. However, in the previous methods for ASM, most of them considered the local order within each gram. Only the (k + s) h-samples filter considers the global order of the sequence of matched grams. Although the (k + s) h-samples filter keeps the global order of the sequence of the grams, it still has some disadvantages. First, to be a candidate in the (k + s) h-samples filter, the number of the ordered matched grams, s, is always fixed to 2 which results in low precision. Second, the (k + s) h-samples filter uses the query time to build the index for query patterns. In this thesis, we propose a new approximate string matching method, the hash trie filter, for efficiently searching in genomic databases. We build a hash trie in the pre-computing time for the genomic sequence stored in database. Although the size q of each split grams is also decided by the same formula used in the (k + s) h-samples filter, we have proposed a different way to find the ordered subpatterns in text T. Moreover, we reduce the number of candidates by pruning some unreasonable matched positions. Furthermore, unlike the (k + s) h-samples filter which always uses s = 2 to decide whether s matched subpatterns could be a candidate or not, our method will dynamically decide s, resulting in the increase of precision. The simulation results show that our hash trie filter outperforms the (k +s) h-samples filter in terms of the response time, the number of verified candidates, and the precision under different length of the query patterns and different error levels.

Cattle are vitally important to American agriculture industry, generating over 24.6 billion pounds of beef (by carcass weight), and 79.5 billion dollars in 2005, and over 27 billion dollars in milk sales in 2004. As of July 2006, the U.S. beef and dairy industry is comprised of 104.5 million head of cattle, 32.4 million of which were processed in 2005. The health of the animals has always been an important concern for breeders, as healthy animals grow faster and are more likely to reach market weight. Animals that exhibit natural resistance to disease do not require chemicals to stimulate normal weight gain, and are less prone to disease related wasting. The major histocompatibility complex (MHC) is a collection of genes, many of which function in antigen processing and presentation. The bovine MHC (BoLA) differs from typical mammalian MHCs in that the class II region was disrupted by a chromosomal inversion into two subregions, designated BoLA IIa and BoLA IIb. BoLA IIb was transposed to a position near the centromere on bovine chromosome 23,while BoLA IIa retains its position in BoLA. Comparative sequence analysis of BoLA IIb with the human MHC revealed the location of the region containing the proximal inversion breakpoint. Gene content, order and orientation of BoLA IIb are consistent with the single inversion hypothesis when compared to the corresponding region of the human class II MHC (HLA class II). BoLA IIb spans approximately 450 kb. The genomic sequence of BoLA IIb was used to detect sequence variation through comparison to other bovine sequences, including data from the bovine genome project, and two regions in the BAC scaffold used to develop the BoLA IIb sequence. Analysis of the bovine genome project sequence revealed a total of 10,408 mismatching bases, 30 out of 231 polymorphic microsatellites, and 15 sequences corresponding to the validated SNP panel generated by the bovine genome sequencing project. The two overlapping regions in the BoLA IIb BAC scaffold were found to have 888 polymorphisms, including a total of 6 out of 42 polymorphic microsatellites indicating that each BAC derived from a different chromosome.

<p>The increasing number of biological databases today requires that users are able to search more efficiently among as well as in individual databases. One of the most widespread problems is redundancy, i.e. the problem of duplicated information in sets of data. This thesis aims at implementing an algorithm that distinguishes from other related attempts by using the genomic positions of sequences, instead of similarity based sequence comparisons, when making a sequence data set non-redundant. In an automatic updating procedure the algorithm drastically increases the possibility to update and to maintain the topicality of a non-redundant database. The procedure creates a biologically sound non-redundant data set with accuracy comparable to other algorithms focusing on making data sets non-redundant</p>