Thesis (Ph.D.) -- University of Texas at Arlington, 2008.

Thesis (Ph. D.)--University of Chicago, Dept. of Statistics, August 2001. / Includes bibliographical references. Also available on the Internet.

Clouston hidrotic ectodermal dysplasia (BED) is an autosomal dominant skin disorder that is characterized by nail dystrophy, hair defects and palmoplantar hyperkeratosis. This condition has been described in families of various ethnic origins but is particularly common in the French Canadian population. Using linkage analysis in eight French Canadian families segregating HED, we mapped the HED gene to the pericentromeric region of chromosome 13q with a combined two-point lod score of 8.12 at zero recombination from the marker D13S175. Haplotype analysis allowed us to define D13S143 as the telomeric flanking marker for the HED candidate region. We tested five genes that map to this region, connexin 26, connexin 46, fibroblast growth factor 9, zinc-finger ZNF198 and alpha tubulin TUBA2, for involvement in HED by PCR-SSCP analysis. No mutation specific to HED was found in any of them suggesting that they most likely are not defective in this disease. / To facilitate the identification of the HED gene, we constructed a radiation hybrid (RH) map of 48 loci surrounding the HED locus on chromosome 13q. This map integrates 3 genes (TUBA2, GJbeta2 and FGF-9) and 18 ESTs with 27 markers including 19 polymorphic loci. A major inconsistency in order involving a reversed interval of six loci was found between our RH map and a YAC contig established in the region. We used Fiber-FISH and FISH on interphase nuclei to confirm our order. To refine the localization of the HED gene, we isolated eight new chromosome 13q polymorphic (CA)n markers and used seven of them along with three others in genetic analysis of a multiethnic group of 29 HED families. We demonstrated genetic homogeneity in HED in four families of French, Spanish, African and Malaysian origins and showed evidence for a strong founder effect in families of French Canadian origin. Recombination mapping placed the HED gene in a 2.4 cM region flanked by D13S1828 proximally and D13S1830 distally. Multipoint linkage and linkage disequilibrium analyses finely mapped the HED gene at 0--0.08 cM telomeric to D13S1835. These studies will greatly facilitate the physical mapping and positional cloning of the HED gene.

This thesis takes the DNA molecule and its circulation between scientific researchers as an object of analysis. The study's objective was to investigate the techno-social mechanisms through which certain individual's genetic materials are imputed with research value. Two cases, representing two contrasting kinds of circulation practices, are presented. In the first, DNA samples from families diagnosed with hereditary disorders, which allow researchers a shot at the all-or-nothing game of finding genes, are a protected resource. In the second, the DNA reference panel of the CEPH (Centre d'Etude du Polymorphisme Humain), made up of samples from large multi-generation families, is a widely distributed public resource. The CEPH panel was originally intended for use in genome mapping, but more recently has acted as a technology that aids in the innovation of new techniques and theories. It is argued that the difference in utility (limited or flexible) between these two types of DNA (privately or publicly held) is not found in any inherent property of the samples themselves but rather derives from the extent of the molecule's network of circulation.

The pattern of inactivation in the DXS8237E-UBE1-PCTK1 region is of particular interest, since the mechanisms of X chromosome inactivation and the escape from inactivation are, as yet, not fully understood. The inactivation status of the DXS8237E and PCTKl gene differ: the first undergoes normal inactivation and the second escapes this process. The status of the UBEl gene has been controversial, although it is widely excepted that it does escape X chromosome inactivation. Physical mapping of the region employing YACs and subsequently P ACs has been undertaken, but was restricted in scope by the high frequency of rearrangements occurring. DNA sequences between DXS8237E, UBE1, PCTKl and the distal gene, UHX1, have been investigated with regard to LINEI elements, which are thought to playa role in X-inactivation. The results obtained strongly suggest a link between LINE1 elements and X chromosome inactivation. Sequence analysis results also contributed to the understanding of difficulties with restriction mapping of the region. Further, this work includes the first reported establishment of the UBEl exonintron boundaries. Additionally, genomic sequence analysis showed that only 46kb separate DXS8237E from UHX1, which confirms that this region is extremely gene rich.

Thesis (M.Sc.)--York University, 2005. Graduate Programme in Mathematics and Statistics. / Typescript. Includes bibliographical references (leaves 201-205). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url%5Fver=Z39.88-2004&res%5Fdat=xri:pqdiss &rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR11838

Philosophiae Doctor - PhD / The pattern of inactivation in the DXS8237E-UBE1-PCTK1 region is of particular interest, since the mechanisms of X chromosome inactivation and the escape from inactivation are, as yet, not fully understood. The inactivation status of the DXS8237E and PCTKl gene differ: the first undergoes normal inactivation and the second escapes this process. The status of the UBEl gene has been controversial, although it is widely excepted that it does escape X chromosome inactivation. Physical mapping of the region employing YACs and subsequently P ACs has been undertaken, but was restricted in scope by the high frequency of rearrangements occurring. DNA sequences between DXS8237E, UBE1, PCTKl and the distal gene, UHX1, have been investigated with regard to LINEI elements, which are thought to playa role in X-inactivation. The results obtained strongly suggest a link between LINE1 elements and X chromosome inactivation. Sequence analysis results also contributed to the understanding of difficulties with restriction mapping of the region. Further, this work includes the first reported establishment of the UBEl exonintron boundaries. Additionally, genomic sequence analysis showed that only 46kb separate DXS8237E from UHX1, which confirms that this region is extremely gene rich. / South Africa

No description available.

<p>With easy access to technology to generate expressed sequence tags (ESTs), several groups have sequenced from thousands to several thousands of ESTs. These ESTs benefit from consolidation and organization to deliver significant biological value. A number of EST projects are underway to extract maximum value from fragmented EST resources by constructing gene indices, where all transcripts are partitioned into index classes such that transcripts are put into the same index class if they represent the same gene. Therefore a gene index should ideally represent a non-redundant set of transcripts. Indeed, most gene indices aim to reconstruct the gene complement of a genome and their technological developments are directed at achieving this goal. The South African National Bioinformatics Institute (SANBI), on the other hand, embarked on the development of the sequence alignment and consensus knowledgebase (STACK) database that focused on the detection and visualisation of transcript variation in the context of developmental and pathological states, using all publicly available ESTs. Preliminary work on the STACK project employed an approach of partitioning the EST data into arbitrarily chosen tissue categories as a means of reducing the EST sequences to manageable sizes for subsequent processing. The tissue partitioning provided the template material for developing error-checking tools to analyse the information embedded in the error-laden EST sequences. However, tissue partitioning increases redundancy in the sequence data because one gene can be expressed in multiple tissues, with the result that multiple tissue partitioned transcripts will correspond to the same gene.</p> <p><br /> Therefore, the sequence data represented by each tissue category had to be merged in order to obtain a comprehensive view of expressed transcript variation across all available tissues. The need to consolidate all EST information provided the impetus for developing a STACK human gene index, also referred to as a whole-body index. In this dissertation, I report on the development of a STACK human gene index represented by consensus transcripts where all constituent ESTs sample single or multiple tissues in order to provide the correct development and pathological context for investigating sequence variation. Furthermore, the availability of a human gene index is assessed as a diseasecandidate gene discovery resource. A feasible approach to construction of a whole-body index required the ability to process error-prone EST data in excess of one million sequences (1,198,607 ESTs as of December 1998). In the absence of new clustering algorithms, at that time, we successfully ported D2_CLUSTER, an EST clustering algorithm, to the high performance shared multiprocessor machine, Origin2000. Improvements to the parallelised version of D2_CLUSTER included: (i) ability to cluster sequences on as many as 126 processors. For example, 462000 ESTs were clustered in 31 hours on 126 R10000 MHz processors, Origin2000. (ii) enhanced memory management that allowed for clustering of mRNA sequences as long as 83000 base pairs. (iii) ability to have the input sequence data accessible to all processors, allowing rapid access to the sequences. (iv) a restart module that allowed a job to be restarted if it was interrupted. The successful enhancements to the parallelised version of D2_CLUSTER, as listed above, allowed for the processing of EST datasets in excess of 1 million sequences. An hierarchical approach was adopted where 1,198,607 million ESTs from GenBank release 110 (October 1998) were partitioned into &quot / tissue bins&quot / and each tissue bin was processed through a pipeline that included masking for contaminants, clustering, assembly, assembly analysis and consensus generation. A total of 478,707 consensus transcripts were generated for all the tissue categories and these sequences served as the input data for the generation of the wholebody index sequences. The clustering of all tissue-derived consensus transcripts was followed by the collapse of each consensus sequence to its individual ESTs prior to assembly and whole-body index consensus sequence generation. The hierarchical approach demonstrated a consolidation of the input EST data from 1,198607 ESTs to 69,158 multi-sequence clusters and 162,439 singletons (or individual ESTs). Chromosomal locations were added to 25,793 whole-body index sequences through assignment of genetic markers such as radiation hybrid markers and g&eacute / n&eacute / thon markers. The whole-body index sequences were made available to the research community through a sequence-based search engine (http://ziggy.sanbi.ac.za/~alan/researchINDEX.html).</p>

<p>With easy access to technology to generate expressed sequence tags (ESTs), several groups have sequenced from thousands to several thousands of ESTs. These ESTs benefit from consolidation and organization to deliver significant biological value. A number of EST projects are underway to extract maximum value from fragmented EST resources by constructing gene indices, where all transcripts are partitioned into index classes such that transcripts are put into the same index class if they represent the same gene. Therefore a gene index should ideally represent a non-redundant set of transcripts. Indeed, most gene indices aim to reconstruct the gene complement of a genome and their technological developments are directed at achieving this goal. The South African National Bioinformatics Institute (SANBI), on the other hand, embarked on the development of the sequence alignment and consensus knowledgebase (STACK) database that focused on the detection and visualisation of transcript variation in the context of developmental and pathological states, using all publicly available ESTs. Preliminary work on the STACK project employed an approach of partitioning the EST data into arbitrarily chosen tissue categories as a means of reducing the EST sequences to manageable sizes for subsequent processing. The tissue partitioning provided the template material for developing error-checking tools to analyse the information embedded in the error-laden EST sequences. However, tissue partitioning increases redundancy in the sequence data because one gene can be expressed in multiple tissues, with the result that multiple tissue partitioned transcripts will correspond to the same gene.</p> <p><br /> Therefore, the sequence data represented by each tissue category had to be merged in order to obtain a comprehensive view of expressed transcript variation across all available tissues. The need to consolidate all EST information provided the impetus for developing a STACK human gene index, also referred to as a whole-body index. In this dissertation, I report on the development of a STACK human gene index represented by consensus transcripts where all constituent ESTs sample single or multiple tissues in order to provide the correct development and pathological context for investigating sequence variation. Furthermore, the availability of a human gene index is assessed as a diseasecandidate gene discovery resource. A feasible approach to construction of a whole-body index required the ability to process error-prone EST data in excess of one million sequences (1,198,607 ESTs as of December 1998). In the absence of new clustering algorithms, at that time, we successfully ported D2_CLUSTER, an EST clustering algorithm, to the high performance shared multiprocessor machine, Origin2000. Improvements to the parallelised version of D2_CLUSTER included: (i) ability to cluster sequences on as many as 126 processors. For example, 462000 ESTs were clustered in 31 hours on 126 R10000 MHz processors, Origin2000. (ii) enhanced memory management that allowed for clustering of mRNA sequences as long as 83000 base pairs. (iii) ability to have the input sequence data accessible to all processors, allowing rapid access to the sequences. (iv) a restart module that allowed a job to be restarted if it was interrupted. The successful enhancements to the parallelised version of D2_CLUSTER, as listed above, allowed for the processing of EST datasets in excess of 1 million sequences. An hierarchical approach was adopted where 1,198,607 million ESTs from GenBank release 110 (October 1998) were partitioned into &quot / tissue bins&quot / and each tissue bin was processed through a pipeline that included masking for contaminants, clustering, assembly, assembly analysis and consensus generation. A total of 478,707 consensus transcripts were generated for all the tissue categories and these sequences served as the input data for the generation of the wholebody index sequences. The clustering of all tissue-derived consensus transcripts was followed by the collapse of each consensus sequence to its individual ESTs prior to assembly and whole-body index consensus sequence generation. The hierarchical approach demonstrated a consolidation of the input EST data from 1,198607 ESTs to 69,158 multi-sequence clusters and 162,439 singletons (or individual ESTs). Chromosomal locations were added to 25,793 whole-body index sequences through assignment of genetic markers such as radiation hybrid markers and g&eacute / n&eacute / thon markers. The whole-body index sequences were made available to the research community through a sequence-based search engine (http://ziggy.sanbi.ac.za/~alan/researchINDEX.html).</p>