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

published_or_final_version / abstract / Statistics and Actuarial Science / Doctoral / Doctor of Philosophy

In this thesis, we propose to discover co-regulated genes using microarray expression data, as well as providing visualization functionalities for domain experts to study relationships among discovered co-regulated genes. To discover co-regulated genes, we first use existing gene selection methods to select a small portion of genes which are relevant to the target diseases, on which we build an ordered similarity matrix by using nearest neighbor based similarity assessment criteria. We then apply a threshold based clustering algorithm named Spectral Clustering to the matrix to obtain a number of clusters. The genes which are clustered together in one cluster represent a group of co-regulated genes and to visualize them, we use Java Swings as the tool and develop a visualization platform which provides functionalities for domain experts to study relationships between different groups of co-regulated genes; study internal structures within each group of genes, and investigate details of each individual gene and of course for gene function prediction. Results are analyzed based on microarray expression datasets collected from brain tumor, lung cancers and leukemia samples. / by Vaibhan Lad. / Thesis (M.S.C.S.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

by Chu Kin Kan Astley. / Thesis submitted in: December 2000. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves xi-xx (3rd gp.)). / Abstracts in English and Chinese. / Abstract (English) --- p.i / Abstract (Chinese) --- p.iii / Acknowledgments --- p.iv / Table of Contents --- p.v / List of Tables --- p.ix / List of Figures --- p.x / Chapter Chapter 1 --- General Introduction / Chapter 1.1 --- Popularity of Shiitake Mushroom --- p.1 / Chapter 1.2 --- Inheritance of Genetic Materials in L.edodes --- p.1 / Chapter 1.3 --- Genetic Markers and Linkage Maps of L.edodes --- p.2 / Chapter 1.4 --- Aims of Study --- p.5 / Chapter Chapter 2 --- Mapping of Sequence Tagged Sites (STSs) and Expressed Sequence Tags (ESTs) on the Linkage Map of L.edodes by PCR-Single Strand Conformational Polymorphism (SSCP) Test / Chapter 2.1 --- Literature Review --- p.7 / Chapter 2.1.1 --- Construction of Genetic Linkage Map --- p.7 / Chapter 2.1.2 --- Logarithm of the Odds (LOD) Score --- p.8 / Chapter 2.1.3 --- MAPMAKER Program --- p.10 / Chapter 2.1.4 --- Sequence Tagged Site (STS) and Expressed Sequence Tag (EST) --- p.11 / Chapter 2.1.5 --- Polymerase Chain Reaction - Single Strand Conformational Polymorphism (PCR-SSCP) --- p.13 / Chapter 2.2 --- Material and Methods --- p.18 / Chapter 2.2.1. --- Detection of the STS and EST markers with PCR-SSCP test --- p.18 / Chapter 2.2.1.1 --- Biological Material and Growth Conditions --- p.18 / Chapter 2.2.1.2 --- DNA Samples Preparation --- p.18 / Chapter 2.2.1.3 --- PCR Primers Designation --- p.20 / Chapter 2.2.1.4 --- PCR Amplification --- p.21 / Chapter 2.2.1.5 --- SSCP Test --- p.21 / Chapter 2.2.1.6 --- Silver Staining of the Polyacrylamide Gel --- p.22 / Chapter 2.2.2. --- Mapping of the STS and EST Markers --- p.22 / Chapter 2.2.2.1 --- Biological Material and Growth Conditions --- p.22 / Chapter 2.2.2.2 --- SSI DNA Preparation --- p.22 / Chapter 2.2.2.3 --- PCR-SSCP Test among SSIs --- p.24 / Chapter 2.2.2.4 --- Chi Square (X2) Test --- p.24 / Chapter 2.2.2.5 --- LOD Score Test and Mapping of the Markers --- p.26 / Chapter 2.3 --- Results --- p.27 / Chapter 2.3.1 --- Detection of the STS and EST Markers from PCR-SSCP Test --- p.27 / Chapter 2.3.1.1 --- DNA Sample Preparation --- p.27 / Chapter 2.3.1.2 --- Primers Designed for STS and EST Amplification --- p.27 / Chapter 2.3.1.3 --- Size Differences between Experimental and Expected PCR Products --- p.38 / Chapter 2.3.1.4 --- Markers of PCR Polymorphism (PCRP) --- p.38 / Chapter 2.3.1.5 --- Markers of PCR-SSCP and PCR Length Polymorphism (PCR-LP) --- p.42 / Chapter 2.3.2 --- Mapping of the STS/EST Markers --- p.49 / Chapter 2.3.2.1 --- DNA Templates of SSIs --- p.49 / Chapter 2.3.2.2 --- Polymorphism Profiles of STSs and ESTs among the L54-SSIs --- p.49 / Chapter 2.3.2.3 --- Chi-square Test --- p.55 / Chapter 2.3.2.4 --- Repeated EST Markers --- p.58 / Chapter 2.3.2.5 --- Anonymous Expressed Sequence Tag - EST31 --- p.58 / Chapter 2.3.2.6 --- Linkage Analysis and Mapping of Markers --- p.59 / Chapter 2.3.2.6.1 --- Linkage Relationships between the16 STS/EST Markers --- p.59 / Chapter 2.3.2.6.2 --- Mapping of the STS/EST Markers onto the RAPD Linkage Map --- p.62 / Chapter 2.4 --- Discussion --- p.69 / Chapter 2.4.1 --- DNA Template Preparation --- p.69 / Chapter 2.4.2 --- Size Difference Between Expected and Experimental PCR Product --- p.69 / Chapter 2.4.3 --- PCR Polymorphism (PCRP) --- p.70 / Chapter 2.4.4 --- PCR-LP --- p.70 / Chapter 2.4.5 --- PCR-SSCP --- p.71 / Chapter 2.4.5.1 --- Primer Designed for PCR-SSCP --- p.71 / Chapter 2.4.5.2 --- Markers Producing Efficiency of PCR-SSCP Test --- p.72 / Chapter 2.4.6 --- Linkage Map of L.edodes --- p.73 / Chapter 2.4.6.1 --- Map Distance --- p.73 / Chapter 2.4.6.2 --- Linkage Groups --- p.74 / Chapter 2.4.6.3 --- Map Markers --- p.75 / Chapter Chapter 3 --- Mapping of Agronomic Features of L.edodes / Chapter 3.1 --- Literature Review --- p.77 / Chapter 3.1.1 --- Aroma Feature of L.edodes --- p.77 / Chapter 3.1.1.1 --- Volatile Compounds in Shiitake (L.edodes) Mushroom --- p.77 / Chapter 3.1.1.2 --- Fragrance Signature of Shiitake Mycelium --- p.79 / Chapter 3.1.2 --- Mapping of Quantitative Trait Loci (QTL) --- p.84 / Chapter 3.1.2.1 --- Complex Traits --- p.84 / Chapter 3.1.2.2 --- Quantitative Traits Locus (QTL) --- p.85 / Chapter 3.1.2.3 --- Maximum-likelihood Estimate in QTL mapping --- p.86 / Chapter 3.1.2.4 --- MAPMAKER/QTL --- p.87 / Chapter 3.2 --- Material and Methods --- p.88 / Chapter 3.2.1 --- Aroma feature of Mycelium --- p.88 / Chapter 3.2.1.1 --- Preliminary Screening of Volatiles in the SSI Mycelia of L.edodes --- p.88 / Chapter 3.2.1.1.1 --- Biological Material and Growth Conditions --- p.88 / Chapter 3.2.1.1.2 --- Volatile Extraction from SSI Mycelia --- p.88 / Chapter 3.2.1.1.3 --- Screening of Volatile Compounds with GC-MS --- p.89 / Chapter 3.2.1.2 --- Quantification of the Target Aromatic Volatile in the Mycelia of SSI and Parents --- p.90 / Chapter 3.2.1.2.1 --- Sample Preparations --- p.90 / Chapter 3.2.1.2.2 --- Quantification of the Target Volatile --- p.90 / Chapter 3.2.2 --- Measurement of Mycelial Growth --- p.91 / Chapter 3.2.3 --- Observation of Pigment Secretion during Mycelial Growth --- p.91 / Chapter 3.2.4 --- Locating Putative QTL on the Genetic Map of L.edodes --- p.92 / Chapter 3.3 --- Results --- p.93 / Chapter 3.3.1 --- Aroma Feature --- p.93 / Chapter 3.3.1.1 --- Preliminary Screening of Volatiles in Mycelia of L.edodes --- p.93 / Chapter 3.3.1.2 --- Quantification of l-octen-3-ol in SSI Mycelia --- p.103 / Chapter 3.3.1.2.1 --- Sample Preparation --- p.103 / Chapter 3.3.1.2.2 --- l-Octen-3-ol contents in SSI Mycelia --- p.103 / Chapter 3.3.1.3 --- Mapping of QTL for l-octen-3-ol level on the genetic map --- p.106 / Chapter 3.3.2 --- Mycelial Growth Rate (MGR) --- p.111 / Chapter 3.3.2.1 --- Measurement of Mycelial Growth Rate --- p.111 / Chapter 3.3.2.2 --- Mapping of QTL for MGR on the genetic map --- p.111 / Chapter 3.3.3 --- Pigment Secretion form SSI mycelia --- p.116 / Chapter 3.4 --- Discussion --- p.118 / Chapter 3.4.1 --- Significance of the QTLs --- p.118 / Chapter 3.4.2 --- QTL for Aroma Feature --- p.119 / Chapter 3.4.2.1 --- Trait of Aroma: l-octen-3-ol level --- p.119 / Chapter 3.4.2.2 --- QTL of l-octen-3-ol level --- p.120 / Chapter 3.4.3 --- Mycelial Growth Rate (MGR) --- p.123 / Chapter 3.4.4 --- Pigment Secretion --- p.125 / Chapter Chapter 4 --- General Discussion and Conclusions --- p.127 / Chapter 4.1 --- Future Works --- p.127 / Chapter 4.1.1 --- Mapping of L.edodes Genes --- p.127 / Chapter 4.1.2 --- Characterizing and Mapping of Agronomic Traits --- p.128 / Chapter 4.2 --- Conclusions --- p.128 / Referencesxi

No description available.

Pedigree dog breeds are genetically isolated and inbred populations with characteristics specific to each breed. Some breeds carry genetic diseases which affect the health of the animals, but may also serve as a valuable model to identify genes involved in human disease. In the Border Collie breed in Australia, the identification of two disease genes would enable breeders to DNA test their animals and prevent future cases. Over 530 samples were collected to identify the genes responsible for these diseases through linkage mapping and candidate gene approaches. Collie Eye Anomaly (CEA) defines a group of symptoms that cause the incorrect development of different regions within the eye, and may also result in the detachment of the retina. The presence of the disease in different breeds of collies suggests that the disease originated before the differentiation of the collie breeds. The CEA gene was mapped to a region of CFA37, but the disease gene was identified by another research group. Neuronal Ceroid Lipofuscinosis (NCL) is a fatal neurodegenerative disorder that affects Border Collie dogs from approximately 16 months of age. The disease is inherited in an autosomal recessive manner and affected animals display a range of physiological and behavioural symptoms that include loss of muscular control, nervousness and sometimes aggression. Due to the debilitating nature of the disease, dogs rarely survive beyond 28 months of age. Microsatellite markers were used to exclude the Border Collie NCL gene from the region of the English Setter NCL gene (homolog of human NCL gene CLN8). Further work mapped the disease gene to CFA22, in a region containing the homolog for CLN5, one of the identified human disease genes for NCL. Subsequent sequencing of canine CLN5 revealed a nonsense mutation (c.619C>T, Q206X) that co-segregated with NCL in Border Collie pedigrees. This truncation mutation resulted in a protein product of similar size to some mutations identified in human CLN5 and therefore the Border Collie may make a good model for future NCL studies. With DNA testing now available, breeders of Border Collies can now ensure that no animal will die of NCL.

Autoimmune disease is comprised of a wide variety of disorders characterised by a loss of self-tolerance towards a target organ or systemic region leading to its eventual destruction. Type 1 diabetes (T1D), autoimmune thyroid disease (AITD) and inflammatory bowel disease (IBD) are debilitating organ-specific disorders. These disorders arise from a combination of genetic factors and environmental triggers. A greater level of basic understanding of these disorders is required to delay and/or prevent their effects. Numerous autoimmune susceptibility loci have been implicated in the development of these disorders, but only a few causative genes have been identified. The aim of this project was to use comparative mapping between the human and mouse genomes to provide a greater understanding of the human autoimmune susceptibility locus, IDDM6, shown to be involved in a number of autoimmune disease conditions. Hall et al., (2003) previously demonstrated that the mouse autoimmune diabetes locus, Idd21, on distal mouse chr18 contains orthology to human IDDM6, IDDM10, IDDM18 and rat Iddm3. As part of this project the Idd21 locus was fine mapped using the congenic mapping technique. Beginning with the consomic mouse strain, NOD.ABHChr18 (90Mb of Biozzi/ABH-derived diabetes-resistant chr18 introgressed onto a non-obese diabetic (NOD) genetic background), 13 NOD.ABHIdd21 congenic mouse strains were established. The diabetes incidences of these congenic mouse strains were statistically compared stepwise along mouse chr18 and Idd21 was fine mapped to at least four independent autoimmune diabetes loci. Idd21.1 and Idd21.2 were located on distal mouse chr18 in regions orthologous to human IDDM6 and rat Iddm3 and Idd21.3a/b and Idd21.4 were located on proximal mouse chr18 in regions orthologous to human IDDM18 and IDDM10 respectively. Candidate genes of notable interest include Map3k8, Spink5, Cd14, Dcc, Smad4 and 7, Miz1, Nfatc1 and Cd226. Idd21.1 was further fine mapped. Beginning with the NOD.ABHD18Mit8-D18Mit214[(75-85.1Mb)] (Idd21.1) congenic strain (containing at least 10.1Mb of distal chr18 Biozzi/ABH diabetes-resistant DNA introgressed onto a NOD genetic background), seven subcongenic mouse strains were created. The diabetes incidence of these subcongenic mouse strains were statistically compared stepwise along mouse chr18 and Idd21.1 was fine mapped to at least three independent autoimmune diabetes loci; Idd21.11 (72.6-76.1Mb), Idd21.12a/b (75-76.1Mb and 80.6-81.4Mb) and Idd21.13 (84.8-85.1Mb). Candidate genes of interest in these regions include Dcc, Smad4 and 7, Miz1, Nfatc1, and Cd226. Functional characterisation of the Idd21.1 locus was performed by adoptively transferring splenocytes from female NOD or NOD.ABHIdd21.1 mice into cohorts of severe combined immune deficient (scid) female mice, NOD/LtSz.Prkdc[scid] and NOD/LtSz.Prkdc[scid].ABHIdd21.1. There were two notable findings from this work. Firstly, NOD.ABHIdd21.1 splenocytes are not as effective as NOD at transferring diabetes to either NOD/LtSz.Prkdc[scid] (P = 0.0004) or NOD/LtSz.Prkdc[scid].ABHIdd21.1 (P = 0.0178), suggesting that Idd21.1 acquired immune cells are not as diabetogenic as NOD. Secondly, NOD/LtSz.Prkdc[scid].ABHIdd21.1 mice are more resistant to autoimmune attack than NOD/LtSz.Prkdc[scid] when injected with either NOD (P = 0.0015) or NOD.ABHIdd21.1 splenocytes (P = 0.0014), suggesting that Idd21.1 either acts by altering the intrinsic resistance of beta-cells to autoimmune attack or due to changes in the innate immune system. Other NOD-based models of autoimmune disease, spontaneous and experimental autoimmune thyroiditis and spontaneous colitis, were also investigated to determine whether Idd21.1 is a common autoimmune disease locus. When bred onto the NOD.Cg-H2[h4] (thyroiditis model) genetic background Idd21.1 was demonstrated to increase the development of thyroiditis and reduce the incidence of insulitis in spontaneous (untreated) but not experimental (NaI-induced) NOD.Cg-H2[h4] mice. When bred onto the NOD.Cg-Il10[tm1Cgn] (colitis) genetic background Idd21.1 was demonstrated to inhibit the development of rectal prolapse in breeding female NOD.Cg-Il10[tm1Cgn] mice. Data from this thesis demonstrate that the IDDM6 orthologous region in mouse, Idd21.1, contains several loci that influence autoimmune diabetes, thyroiditis and colitis in NOD-based mouse models. These findings are consistent with previous knowledge that IDDM6 is a common autoimmune susceptibility locus.

This thesis concerns the identification of quantitative trait loci (QTL) for important traits in cattle line crosses. One of these traits is birth weight of calves, which affects both animal production and welfare through correlated effects on parturition and subsequent growth. Birth weight was one of the traits measured in the Davies' Gene Mapping Project. These data form the motivation for the methods presented in this thesis. Multiple QTL models have been previously proposed and are likely to be superior to single QTL models. The multiple QTL models can be loosely divided into two categories : 1 ) model building methods that aim to generate good models that contain only a subset of all the potential QTL ; and 2 ) methods that consider all the observed marker explanatory variables. The first set of methods can be misleading if an incorrect model is chosen. The second set of methods does not have this limitation. However, a full fixed effect analysis is generally not possible as the number of marker explanatory variables is typically large with respect to the number of observations. This can be overcome by using constrained estimation methods or by making the marker effects random. One method of constrained estimation is the least absolute selection and shrinkage operator (LASSO). This method has the appealing ability to produce predictions of effects that are identically zero. The LASSO can also be specified as a random model where the effects follow a double exponential distribution. In this thesis, the LASSO is investigated from a random effects model perspective. Two methods to approximate the marginal likelihood are presented. The first uses the standard form for the double exponential distribution and requires adjustment of the score equations for unbiased estimation. The second is based on an alternative probability model for the double exponential distribution. It was developed late in the candidature and gives similar dispersion parameter estimates to the first approximation, but does so in a more direct manner. The alternative LASSO model suggests some novel types of predictors. Methods for a number of different types of predictors are specified and are compared for statistical efficiency. Initially, inference for the LASSO effects is performed using simulation. Essentially, this treats the random effects as fixed effects and tests the null hypothesis that the effect is zero. In simulation studies, it is shown to be a useful method to identify important effects. However, the effects are random, so such a test is not strictly appropriate. After the specification of the alternative LASSO model, a method for making probability statements about the random effects being above or below zero is developed. This method is based on the predictive distribution of the random effects (posterior in Bayesian terminology). The random LASSO model is not sufficiently flexible to model most QTL mapping data. Typically, these data arise from large experiments and require models containing terms for experimental design. For example, the Davies' Gene Mapping experiment requires fixed effects for different sires, a covariate for birthdate within season and random normal effects for management group. To accommodate these sources of variation a mixed model is employed. The marker effects are included into this model as random LASSO effects. Estimation of the dispersion parameters is based on an approximate restricted likelihood (an extension of the first method of estimation for the simple random effects model). Prediction of the random effects is performed using a generalisation of Henderson's mixed model equations. The performance of the LASSO linear mixed model for QTL identification is assessed via simulation. It performs well against other commonly used methods but it may lack power for lowly heritable traits in small experiments. However, the rate of false positives in such situations is much lower. Also, the LASSO method is more precise in locating the correct marker rather than a marker in its vicinity. Analysis of the Davies' Gene Mapping Data using the methods described in this thesis identified five non-zero marker-within-sire effects ( there were 570 such effects). This analysis clearly shows that most of the genome does not affect the trait of interest. The simulation results and the analysis of the Davies' Gene Mapping Project Data show that the LASSO linear mixed model is a competitive method for QTL identification. It provides a flexible method to model the genetic and experimental effects simultaneously. / Thesis (Ph.D.)--School of Agriculture, Food and Wine, 2006.

"September 2002" / Bibliography: leaves 142-159. / viii, 159, [17] leaves : ill. (some col.), plates, photograph ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Investigates self- and cross-compatibility using 5 common commercial cultivars of olive. Frantoio is found to b a good general polliniser for the other cultivars. The sex ratio of flowers, pollen viability, and male sterility were also examined Another objective was the construction of a molecular linkage map for olives, using a cross between Frantoio and Kalamata and microsatellite markers using the pseudo-testcross strategy. Approximately 45% of the genome was mapped. / Thesis (Ph.D.)--University of Adelaide, Dept. of Horticulture, Viticulture and Oenology, 2002

Bibliography: leaves 127-166. This study describes the isolation, sequencing and characterization of two cDNAs encoding barley (1-4)-B-xylanase isoenzymes X-I and X-II and the gene corresponding to isoenzyme X. The results of genomic Southern blot analyses indicate that the barley (1-4)-B-xylanase gene family consists of at least 3 genes which are mapped to a single locus on the long arm of chromosome 7(5H). The cDNA is used to monitor tissue-specific expression, developmental regulation and hormonal control of the (1-4)-B-xylanase genes.