Thesis (MSc)--University of Stellenbosch, 2008. / Bibliography. Also available via the Internet.

Thesis (MSc)--University of Stellenbosch, 2008. / Bibliography. Also available via the Internet.

<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>

A novel approach for screening metagenomic libraries by merging both metagenomic and microarray platforms was developed and optimized. This high-throughput screening strategy termed "metagenomic microarrays" involved the construction of two Arctic soil large-insert libraries and the high density arraying of the clone plasmid DNA (~50 kb) onto glass slides. A standard alkaline lysis technique used for the purification of plasmid DNA was adapted and optimized to function efficiently in a 96-well format, providing an economically viable means of producing sufficient high-quality plasmid DNA for direct printing onto microarrays. The amounts of printed material and probe, required for maximal clone detection, were optimized. To examine catabolic clone detection libraries were first screened by PCR for catabolic genes of interest. Two PCR-positive clones were printed onto microarrays, and detection of these specific clones in the printed libraries was achieved using labeled probes produced from PCR fragments of known sequence. Also, hybridizations were performed using labeled PCR fragments derived from the amplification of a catabolic gene from the total community DNA. The ability of selected probes to specifically target clones of interest was demonstrated. This merger of metagenomics and microarray technologies has shown great promise as a tool for screening the natural microbial community for catabolic potential and could also be used to profile microbial diversity in different environments.

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (MSc)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: Biopolymers and bio-degradable polymers are of utmost importance to ensure a sustainable economy. Industry depends on raw material, which in many cases are derived from fossil fuels, but in light of looming energy crises and green revolutions attention is being directed at cellulose and starch biopolymers. This study was therefore set forth to investigate novel genetic key elements of cell wall metabolism in Arabidopsis thaliana and starch synthesis in an under-utilized southern African crop plant, Tylosema esculentum. In the first section of the study a cDNA library of good quality was constructed from regenerating A. thaliana protoplasts as it was expected to be enriching for genes involved in cell wall biosynthesis. Small scale EST sequencing of the library confirmed that a few sequences were similar to genes identified to be highly expressed during protoplast regeneration. The library was to be screened by expression in a microalgae as it is anticipated that cell wall metabolising genes would change the wall structure and visibly alter the colony morphology. An attempt was made at establishing a high-throughput transformation system in the unicellular algae Chlorella protothecoides in which the library was proposed to be screened. Conventional microalgal transformation techniques do not appear to be effective in this strain as the study produced no transgenic algae. Alternative studies into a screening system within another species could still lead to the identification of cell wall biosynthetic genes, which was the first objective in the study. The second objective in the study was to investigate the potential of the orphan crop T. esculentum as starch-producing cash-crop in developing southern African countries. In this section of the study a cDNA library of good quality was produced form the tuber of T. esculentum. The library was transferred to an expression vector and screened functionally in E. coli for the presence of sequences with starch synthase activity. No sequences have been identified yet and screening procedures are still on-going. The starch content in the tuber has also been determined for the first time. The relatively high starch content in combination with low agricultural inputs indicate the potential of the plant as an industrial starch source. Further investigations into the nature of the starch are proposed to identify prospective buyers within the industry. / AFRIKAANSE OPSOMMING: Biopolimere en bio-afbreekbare polimere is van kardinale belang om ‘n volhoubare ekonomie te ontwikkel. Industriële toepassings maak op die oomblik hoofsaaklik staat op fossielbrandstof verwante bronne, maar met die oog op ‘n groen revolusie en energie krissise wat dreig word meer belangstelling getoon in sellulose en stysel biopolimere. Hierdie studie is daarom onderneem om genetiese elemente te identifiseer wat betrokke is by die sintese van die selwand in Arabidopsis thaliana en stysel sintese in die suider Afrikaanse gewas Tylosema esculentum wat grotendeels onderbenut is. In die eerste deel van die studie is ‘n cDNA biblioteek, van goeie kwaliteit, geskep vanuit A. thaliana protoplaste wat besig was om hulle selwande te herbou. Dit word verwag dat die protoplaste gedurende die tydperk aktief besig sal wees om gene uit te druk wat betrokke is by selwandsintese. DNA volgordebepaling het bevestig dat ‘n klein aantal volgordes ooreengestem het met gene wat voorheen gevind was om in ‘n oormaat uitgedruk te word tydens die herbou van protoplas-selwande. Daar was beoog om die biblioteek in ‘n mikroalge uit te druk en sodoende die morfologie op kolonievlak waar te neem vir verandering wat in die selwand meegebring is. Om hierdie rede was die doel om ‘n hoë opbrengs transformasie sisteem te ontwikkel in die mikroalge Chlorella protothecoides. Algemene mikroalge transformasie tegnieke blyk om nie effektief in die spesie te wees nie aangesien geen transgeniese alge waargeneem is nie. Die ontwikkeling van ‘n soortgelyke proses in ‘n ander spesie kan steeds lei na die ontdekking van gene betrokke by selwandsintese in A. thaliana wat die eerste uitkoms van die projek as geheel was. Die tweede uitkoms van die projek was om te ondersoek wat die waarskynlikheid was om T. esculentum te kommersialiseer as ‘n stysel gewas en sodoende ‘n inkomste te skep vir arm boere in ontwikkelende lande in suider Afrika. In hierdie gedeelte van die projek was daar ‘n goeie cDNA biblioteek geskep uit die knol van T. esculentum. Die biblioteek is oorgedra na ‘n plasmied waarop dit aktief uitgedruk kon word in Escherischia coli G6MD2 en daar is gesoek na volgordes wat lei na die sintese van stysel in hierdie bakterieë. Tot op hede is geen sulke volgordes gevind nie, maar die ondersoek gaan steeds voort. Die styselinhoud van die knol is ook vir die eerste keer bepaal in hierdie ondersoek. ‘n Styselinhoud wat relatief hoog is en die lae moeite wat geverg word om die gewas te verbou toon dat die plant potensieel het as ‘n kommersiële bron van stysel. Verdere ondersoeke in die aard van die stysel word ook voorgestel om toekomstige industriële kopers te identifiseer.

Philosophiae Doctor - PhD / 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.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). / South Africa

No description available.

Seven years into the postgenomic era, we sit atop a mountain of data whose generation was enabled by gene sequencing. The creation, integration, and analysis of these large scale data sets allow us to move forward toward the complementary goals of determining the individual roles of the thousands of uncharacterized mammalian genes and understanding how they work together to produce a healthy human being -- or, perhaps more importantly, how their malfunction results in disease. Collapsing the results of large-scale assays into gene networks provides a useful framework from which we can glean information that advances both of these goals. However, the utility of networks is limited by the quality of the data that goes into them. This study offers seeks to shed some light on the quality and breadth of protein interaction networks, describes a new experimental technique for functional genetic assays in mammalian cell lines, and ultimately suggests a strategy for how to improve the overall utility of the output generated by the systems biology community. / text