Browsing by Author "Bruce Weir, Committee Member"

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Carbohydrate Utilization Pathway Analysis in the Hyperthermophile Thermotoga maritima
(2006-03-01) Conners, Shannon Burns; Todd Klaenhammer, Committee Member; Robert Kelly, Committee Chair; Greg Gibson, Committee Member; Bruce Weir, Committee Member; Jason Osborne, Committee Member
Carbohydrate utilization and production pathways identified in Thermotoga species likely contribute to their ubiquity in hydrothermal environments. Many carbohydrate-active enzymes from Thermotoga maritima have been characterized biochemically; however, sugar uptake systems and regulatory mechanisms that control them have not been well defined. Transcriptional data from cDNA microarrays were examined using mixed effects statistical models to predict candidate sugar substrates for ABC (ATP-binding cassette) transporters in T. maritima. Genes encoding proteins previously annotated as oligopeptide/dipeptide ABC transporters responded transcriptionally to various carbohydrates. This finding was consistent with protein sequence comparisons that revealed closer relationships to archaeal sugar transporters than to bacterial peptide transporters. In many cases, glycosyl hydrolases, co-localized with these transporters, also responded to the same sugars. Putative transcriptional repressors of the LacI, XylR, and DeoR families were likely involved in regulating genomic units for beta-1,4-glucan, beta-1,3-glucan, beta-1,4-mannan, ribose, and rhamnose metabolism and transport. Carbohydrate utilization pathways in T. maritima may be related to ecological interactions within cell communities. Exopolysaccharide-based biofilms composed primarily of β-linked glucose, with small amounts of mannose and ribose, formed under certain conditions in both pure T. maritima cultures and mixed cultures of T. maritima and M. jannaschii. Further examination of transcriptional differences between biofilm-bound sessile cells and planktonic cells revealed differential expression of beta-glucan-specific degradation enzymes, even though maltose, an alpha-1,4 linked glucose disaccharide, was used as a growth substrate. Higher transcripts of genes encoding iron and sulfur compound transport, iron-sulfur cluster chaperones, and iron-sulfur cluster proteins suggest altered redox environments in biofilm cells. Further direct comparisons between cellobiose and maltose-grown cells suggested that transcription of cellobiose utilization genes is highly sensitive to the presence of cellobiose, or a cellobiose-maltose mixture. Increased transcripts of genes related to polysulfide reductases in cellobiose-grown cells and biofilm cells suggested that T. maritima cells in pure culture biofilms escaped hydrogen inhibition by preferentially reducing sulfur compounds, while cells in mixed culture biofilms form close associations with hydrogen-utilizing methanogens. In addition to probing issues related to the microbial physiology and ecology of T. maritima, this work illustrates the strategic use of DNA microarray-based transcriptional analysis for functional genomics studies.
D.R.EVOL: Three Dimensional Realistic Evolution
(2003-11-04) Robinson, Douglas Michael; Bruce Weir, Committee Member; Spencer Muse, Committee Member; Bill Atchley, Committee Member; Ed Buckler, Committee Member; Jeffrey Thorne, Committee Chair
Simplifying assumptions are necessary to model complex biological processes. Although some assumptions may make sense mathematically, they are often implausible when literally translated. This is especially true of the independence among codons assumption, which states that the evolutionary rate at one codon isindependent of the evolutionary rate at surrounding codons. Sites within proteinsmust interact in order to form intricate three-dimensional binding sites and activation domains. This dissertation details the derivation of a procedure for statistical inference when independent change is not assumed. The procedure is implemented in a Bayesian framework where Markov chain Monte Carlo methods permit approximation of posterior distributions. Analyses with the procedure on data sets with two and three taxa are explored and biologically plausible values of the solvent accessibility and pairwise interaction parameters are inferred. Via these analyses, we illustrate the chronological ordering of amino acid replacements and the detection of specific events to be positively selected. We also find spatial clustering of the amino acid replacements that have most affected sequence-structure compatibility during the evolution of primate eosinophil-derived neurotoxin proteins.
The Genetic Architecture of Locomotor Behavior in Drosophila melanogaster
(2006-12-20) Jordan, Katherine Wells; Trudy Mackay, Committee Chair; Bruce Weir, Committee Member; Robert Grossfeld, Committee Member; Michael Puruganan, Committee Member
Locomotion is an integral component of most animal behaviors: movement is required for localization of food and mates, escape from predators, defense of territory, and response to stress. Many human neurological diseases (e.g., Parkinson's Disease and Huntington's Disease) are associated with locomotor deficits. Locomotion is a complex behavior, with variation in nature attributable to the joint segregation of multiple interacting quantitative trait loci (QTLs), with effects that are sensitive to the environment. Thus, understanding the genetic architecture of locomotor behavior is important from the dual perspectives of evolutionary biology and human health. However, our current knowledge falls short of the level of detail with which we ultimately seek to describe variation in locomotor behavior. We used complementary approaches in the model system Drosophila melanogaster to identify genes affecting locomotion: QTL mapping, followed by linkage disequilbrium mapping and association testing; artificial selection to derive lines for transcriptome analysis using microarrays; and P-element insertional mutagenesis to confirm the microarray results. QTL mapping uncovered four regions that contribute to variation in locomotor reactivity (a component of locomotor behavior) between two lab stocks. Deficiency complementation mapping refined our large QTL into 12 smaller QTL, then complementation tests to mutations identified 13 positional candidate genes affecting locomotor reactivity, including Dopa decarboxylase (Ddc) and Catecholamines Up (Catsup). Linkage disequilibrium mapping in a natural population of 164 second chromosome substitution lines suggested polymorphisms at Ddc and Catsup were associated with naturally occurring genetic variation in locomotion. Another strategy to discover genes affecting complex behaviors is to combine artificial selection for divergent phenotypes with whole genome expression profiling. Artificial selection lines created from a genetically heterogeneous background were selected for 25 generations to derive replicate lines with divergent levels of locomotor reactivity. Transcription profiling identified nearly 1,800 probe sets that were differentially expressed between the selection lines. Functional tests of P-element mutations in ten differentially expressed genes confirmed seven novel candidate genes affecting locomotion. Many of the genes identified in this study have other functions in metabolism, nervous system development, and response to different stimuli, suggesting extensive pleiotropy among the genes affecting locomotor behavior.
Morphological and Genetic Description of the Freshwater Mussel, Elliptio complanata (Lightfoot, 1786) in the Cape Fear River System, N.C.
(2004-05-21) Molina, Reverie Alvarez; Jay F. Levine, Committee Chair; Bruce Weir, Committee Member; Fred Gould, Committee Member; Wondwossen Gebreyes, Committee Member; Arthur Bogan, Committee Member
The purpose of this research is to provide a preliminary description of the morphological and genetic variation of a cosmopolitan freshwater mussel E. complanata from one North Carolina river system, Cape Fear River (CFR). Individuals from CFR were collected and compared with known specimens of E. complanata (topotype). Multivariate analyses, such as factor and discriminant analyses were utilized to differentiate the individuals based on thirty morphological shell landmarks. Genetic analyses involved the use of diversity estimates and cluster analyses based on cytochrome oxidase I (COI) sequence and Amplified Fragment Length Polymorphism (AFLP) fingerprint data. Factor analysis suggest that E. complanata from CFR maybe differentiated based on the thickness of posterior and anterior shell angles, and obesity of the shells. Significant differences between the CFR samples and topotypes were demonstrated by discriminant analysis of morphological data and by COI gene diversity estimates. This difference corroborated earlier work suggesting geographic delineation of E. complanata shell form. Genomic fingerprinting suggests further variation even within the topotypes. Phenotype of the topotypic materials seems to support this genomic variability. Heirarchical cluster analyses of morphometry and genetic data further showed different groups supporting earlier research suggesting high form variation within the E. complanata species.
Population Estimates with Age and Genetic Structure of a Harvested Bear Population in Eastern North Carolina
(2007-03-11) Langer, Timothy Joseph; Bruce Weir, Committee Member; Kenneth H. Pollock, Committee Member; Phillip David Doerr, Committee Chair; David T. Cobb, Committee Member
Noninvasive genetic sampling (NGS) is appealing because it facilitates the use of more robust, capture-recapture models to estimate population size. NGS is expensive, however, and current sub-sampling approaches, though made a priori, are made with incomplete knowledge of the ramifications. I compared model selection and population estimates from all hair samples to those from subsets of samples chosen by simulating 4 published sub-sampling approaches. I used 4 weeks of samples collected from black bears (Ursus americanus) at scented DNA hair traps during Spring 2003 and again during Spring 2004 in Hyde County, North Carolina. I found that follicle filters deleted individuals from the data set without altering sex ratio, but random sub-sampling both deleted capture histories and altered the sex ratio. Collectively, these decisions biased population estimates low and produced inconsistent model selection among 10 replications. I also conducted a 13-week study in Spring⁄Summer 2004 to investigate effects of using food and scent to lure bears to DNA hair traps. Food and scent collected twice as many hair samples as just scent, but produced similar estimates. I do not recommend using follicle filters or sub-sampling; my data suggest they may reduce NGS to an expensive population index. Instead, I recommend using only scent to lure bears, identifying all samples for gender, and genotyping just female samples. This approach estimates the female population size and, combined with ages from trapped bears and ages with fecundity data from hunter harvested bears, allows estimation of reproductive rate, which are especially valuable for population monitoring. Model Mo fit females best and model Mb fit males best for both 2003 and 2004 and produced population estimates of 223 females and 160 males. Using reproductive tract data from hunter harvested bears and Spring estimates of breeding-age females, I estimated yearly cub production as 97 cubs of each sex for a total population estimate of 577 bears in our 404.3 mi2 (1,047.2 km2) study area. My study area has averaged about 120 hunter harvested bears the past 15 years. Because I estimated the net reproductive rate was 1.0, the maximum sustainable yield appeared to be 20.7 %.
Probe Design and Data Analysis for Gene Expression Microarrays
(2003-04-13) Warren, Liling Li; Greg Gibson, Committee Member; Spencer Muse, Committee Member; Ben Liu, Committee Chair; Bruce Weir, Committee Member
This thesis work focuses on several bioinformatics aspects of DNA microarray experiments. DNA microarrays are breakthrough technologies for large scale gene expression profiling. Instead of measuring transcription levels one gene at a time, expression levels for many thousands of genes can be quantified simultaneously on one microarray. Depending on the array format, cDNA or pre-synthesized oligo nucleotides can be deposited as probes onto the array. Oligo probes can also be synthesized on the array. During the complete process of a DNA microarray experiment, many steps involve bioinformatics tasks; from probe design, image analysis, data normalization to data analysis and data mining. This thesis deals with oligo probe design issues and comparisons of data normalization methods. Methods on how to select a relatively small number of short probes and use them in a combinatorial fashion to quantify large scale expression levels are also explored. In Chapter one, a novel algorithm to design gene specific probes is described. When gene specific oligos are used as probes, it is crucial to select a set of probes that have desirable properties in order for many hybridization reactions to take place in parallel on an array. Given a set of sequences, the algorithm works by finding the range of melting temperatures for all possible probe choices. Then for each possible melting temperature within the range, one probe having the closest melting temperature is picked from each sequence to form a probe set. Among all the probe sets, the one that has the most homogeneous melting temperatures is the optimized choice. The major significance of our approach is the reduction of computation amount, which increases linearly as the number of genes increases rather than exponentially. Detailed steps on how to implement the algorithm are outlined and examples are given. With some modifications, the algorithm can also be applied to design allele specific probes for SNP genotyping or point mutation detections. In Chapter two, five normalization methods are compared with each other and also compared with analysis skipping the normalization step. Overall, performing normalization can reduce systematic variations and identify more genes as differentially expressed than without the normalization step. Among different normalization methods being compared, ANOVA based normalization method has the most power to detect differentially expressed genes. When the same normalization and analysis methods are used, ratio based method has more power than the one based on absolute signal intensity values. When different number of genes are detected by different normalization methods, one way to plan for future experiment is to use the set of genes that have been detected by all methods. Alternatively, one can use all the genes that have been identified to be differentially expressed regardless which method was used to design further experiments. Insights from this study on how to incorporate biological variation into future experimental designs are also discussed. In Chapter three, we present methods to choose a set of short oligos to design a genome or tissue specific biochip and then to solve a set of equations for gene expression levels to determine genes that are differentially expressed between samples. The methods have been tested to define a set of 4000 8mers as probes to identify genes that have fold changes for more than 6000 identified yeast ORFs. These methods can also be expanded to design genome specific or tissue specific biochips for other organisms with full gene sequence information. The major advantages of using our methods is to significantly reduce overall cost in array fabrication and oligo synthesis. The process of mining probe sets depends on knowing gene sequence information in a specific genome or tissue. As more genomes are being sequenced, this method holds great promise towards enabling more accurate and less expensive microarray experiments.
Quantitative Molecular Genetics of Longevity in Drosophila melanogaster.
(2004-08-18) Thornsberry, Gretchen Lindsay Geiger; Bruce Weir, Committee Member; Trudy F. C. Mackay, Committee Chair; Greg Gibson, Committee Member; Michael Purugganan, Committee Member
Limited life span and senescence are universal phenomena, controlled by genetic and environmental factors whose interactions both limit life span and generate variation in life span between individuals, populations and species. To understand the genetic architecture of aging it is necessary to know what loci affect variation in life span, what are the allelic effects at these loci and what molecular polymorphisms define quantitative trait locus (QTL) alleles. Here, quantitative complementation tests were used to determine whether candidate life span genes such as Superoxide dismutase (Sod), Catalase (Cat), heat shock proteins, DNA repair enzymes, glucose metabolism or male accessory gland proteins interact genetically with naturally occurring QTL affecting variation in life span in Drosophila melanogaster. Inbred strains derived from a natural population were crossed to stocks containing null mutations or deficiencies uncovering the above genes. Life span of the heterozygous progeny was assayed. A significant cross (mutant versus wild-type allele of the candidate gene) by inbred line interaction term from analysis of variance of the life span data indicates a genetic interaction between the candidate gene allele and the naturally occurring life span QTL. Of the sixteen candidate regions and genes tested, Df(2L)cl7, Df(3L)Ly, Df(3L)AC1, Df(3R)e-BS2, and α-Glycerol phosphate dehydrogenase showed significant failure to complement wild-type alleles in both sexes, and an Alcohol dehydrogenase mutant failed to complement in females. Several genes known to regulate life span (Sod, Cat, and rosy) complemented the life span effects of alleles, suggesting little natural variation affecting longevity at these loci, at least in this sample of alleles. Quantitative complementation tests are therefore useful for identifying candidate genes contributing to segregating genetic variation in life span in nature. Mutations in most vital genes can potentially affect life history traits, but it is not known what subset of these loci harbor naturally occurring variation affecting the rate of aging and the ability to resist stress. While the gene Punch (Pu) was not significant in the quantitative complementation test, it has been implicated in starvation resistance. As there is a direct relationship between stress resistance and longevity, Pu, which encodes GTP cyclohydrolase (GTPCH), is a candidate gene for associating molecular variation and variation in life pan. GTPCH regulates the catecholamine biosynthesis pathway by catalyzing the formation of tetrahydrobiopterin, the rate-limiting molecule, and by regulating tyrosine hydroxylase, a key enzyme in the pathway. The extent to which molecular variation at Pu contributes to phenotypic variation was assessed by associating single nucleotide polymorphisms (SNPs) at Pu with longevity. Nucleotide variation was determined for ten Pu alleles. Genotypes of 28 SNPs were determined on a sample of 178 isogenic second chromosomes sampled from the Raleigh, USA population and substituted into the highly inbred Samarkand background. Life span was determined for the chromosome substitution lines and the association between longevity phenotype and SNP genotype was assessed for each polymorphic marker. Three SNPs were significantly associated with life span (C6291A, P = 0.0183; A6389T, P = 0.0466; G6894C, P = 0.0024). None of these SNPs was significant individually following a permutation test accounting for multiple tests and partially correlated markers. However, the three SNPs associated with life span were in global linkage disequilibrium. Haplotypes of these SNPs were highly significantly associated with variation in longevity (P < 0.0001), and accounted for 13.5 % of the genetic variance and 1.86 % of the phenotypic variance in longevity attributable to chromosomes 2. As Pu is a regulator of the catecholamine biosynthetic pathway, these findings suggest the importance of the production of biogenic amines in determining variation for longevity.
Site-to-site Rate Variation in Protein Coding Genes
(2006-04-28) Mannino, Frank Vincent; Spencer Muse, Committee Chair; William Atchley, Committee Member; Jeffrey Thorne, Committee Member; Bruce Weir, Committee Member
The ability to realistically model gene evolution improved dramatically with the rejection of the assumption that rates are constant across sites. Rate heterogeneity models allow for better estimates of parameters and site specific inferences such as the detection of positive selection. Recently developed models of codon evolution allow for both synonymous and nonsynonymous rates to vary independently according to discretized gamma distributions. I applied this model to mitochondrial genomes and concluded that synonymous rate variation is present in many genes, and is of appreciable magnitude relative to the amount of nonsynonymous heterogeneity. I then extending this model to allow for the two rates to vary according to a dependent bivariate distribution, permitting tests for the significance of correlation of rates within a gene. I present here the algorithm to discretize this bivariate distribution and the application of the model to many real data sets. Significant correlation between synonymous and nonsynonymous rates exists in roughly half of the data sets that I examined, and the correlation is typically positive. These data sets range over a wide group of taxa and genes, implying that the trend of correlation is general. Finally, I performed a thorough investigation of the statistical properties of using discretized gamma distributions to model rate variation, looking at the bias and variance in parameter estimates. These discretized distributions are common in modeling heterogeneity, but have weaknesses that must be well understood before making inferences.
Spectral Analysis of Protein Sequences
(2005-10-25) Wang, Zhi; Jeffrey Thorne, Committee Member; William Atchley, Committee Co-Chair; Charles Smith, Committee Chair; Bruce Weir, Committee Member
The purpose of this research is to elucidate how to apply spectral analysis methods to understand the structure, function and evolution of protein sequences. In the first part of this research, spectral analyses have been applied to the basic- helix-loop-helix (bHLH) family of transcription factors. It is shown that the periodicity of the bHLH variability pattern (entropy profile) conforms to the classical alpha-helix periodicity of 3.6 amino acids per turn. Further, the underlying physiochemical attributes profiles (factor score profiles) are examined and their periodicities also have significant implications of the alpha-helix secondary structure. It is suggested that the entropy profile can be well explained by the five factor score variance components that reflect the polarity/hydrophobicity, secondary structure information, molecular volume, codon composition and electrostatic charge attributes of amino acids. In the second part of this research, complex demodulation (CDM) method is introduced in an attempt to quantify the amplitude of periodic components in protein sequences. Proteins are often considered to be 'multiple domain entities' because they are composed of a number of functionally and structurally distinct domains with potentially independent origins. The analyses of bZIP and bHLH-PAS protein domains found that complex demodulation procedures can provide important insight about functional and structural attributes. It is found that the local amplitude minimums or maximums are associated with the boundary between two structural or functional components. In the third part of this research, the periodicity evaluation of a leucine zipper protein domain with a well-known structure is used to rank 494 published indices summarized in a database (http://www.genome.jp/dbget/aaindex.html). This application allows us to select those amino acid indices that are strongly associated with the protein structure and hereby to promote the protein structure prediction. This procedure can be used to reduce some redundancy of the amino acid indices.
Transcriptional Regulatory Pattern in Yeast Revealed through Expression Quantitative Trait Locus Mapping
(2007-08-04) Zou, Wei; Bruce Weir, Committee Member; Sujit K. Ghosh, Committee Member; Zhaobang Zeng, Committee Chair; Trudy F.C. Mackay, Committee Member