Person:

Gibson, Greg

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https://hdl.handle.net/1853/71291

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Organizational Unit

School of Biological Sciences

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Now showing 1 - 9 of 9

Impact of Population Structure on Genetic Diversity of a Potential Vaccine Target in the Canine Hookworm (Ancylostoma caninum)

(Georgia Institute of Technology, 2007-08) Moser, Jennifer M. ; Carbone, Ignazio ; Arasu, Prema ; Gibson, Greg

Ancylostoma caninum is a globally distributed canine parasitic nematode. To test whether positive selection, population structure, or both affect genetic variation at the candidate vaccine target Ancylostoma secreted protein 1 (asp-1), we have quantified the genetic variation in A. caninum at asp-1 and a mitochondrial gene, cytochrome oxidase subunit 1 (cox-1), using the statistical population analysis tools found in the SNAP Workbench. The mitochondrial gene cox-1 exhibits moderate diversity within 2 North American samples, comparable to the level of variation observed in other parasitic nematodes. The protein coding portion for the C-terminal half of asp-1 shows similar levels of genetic variation in a Wake County, North Carolina, sample as cox-1. Standard tests of neutrality provide little formal evidence for selection acting on this locus, but haplotype networks for 2 of the exon regions have significantly different topologies, consistent with different evolutionary forces shaping variation at either end of a 1.3-kilobase stretch of sequence. Evidence for gene flow among geographically distinct samples suggests that the mobility of hosts of A. caninum is an important contributing factor to the population structure of the parasite.
Genetic Variation for Cardiac Dysfunction in Drosophila

(Georgia Institute of Technology, 2007-07-11) Ocorr, Karen A. ; Crawley, Timothy ; Gibson, Greg ; Bodmer, Rolf

Background Common diseases may be attributed to combinations of variant alleles, but there are few model systems where the interactions among such variants can be studied in controlled genetic crosses. While association studies are designed to detect common polymorphisms of moderate effect, new approaches are required to characterize the impact on disease of interactions among rare alleles. Methodology/Principal Findings We show that wild populations of Drosophila melanogaster harbor rare polymorphisms of major effect (RAME) that predispose flies to a specific disease phenotype, age-dependent cardiac dysfunction. A screen of fifty inbred wild-type lines revealed a continuous spectrum of pacing-induced heart failure that generally increases in frequency with age. High-speed video analysis of the inbred lines with high rates of inducible heart failure indicates specific defects in cardiac function, including arrhythmias and contractile disorders (‘cardiomyopathies’). A combination of bulked segregant analysis and single feature polymorphism (SFP) detection localizes one of the cardiac susceptibility loci to the 97C interval on the fly genome. Conclusions/Significance Wild-type Drosophila, like humans, are predisposed to cardiac dysfunction. Identification of factors associated with these naturally occurring cardiac traits promises to provide important insights into the epidemiology of cardiac disease.
Simultaneous clustering of gene expression data with clinical chemistry and pathological evaluations reveals phenotypic prototypes

(Georgia Institute of Technology, 2007-02-23) Bushel, Pierre R. ; Wolfinger, Russell D. ; Gibson, Greg

Background: Commonly employed clustering methods for analysis of gene expression data do not directly incorporate phenotypic data about the samples. Furthermore, clustering of samples with known phenotypes is typically performed in an informal fashion. The inability of clustering algorithms to incorporate biological data in the grouping process can limit proper interpretation of the data and its underlying biology. Results: We present a more formal approach, the modk-prototypes algorithm, for clustering biological samples based on simultaneously considering microarray gene expression data and classes of known phenotypic variables such as clinical chemistry evaluations and histopathologic observations. The strategy involves constructing an objective function with the sum of the squared Euclidean distances for numeric microarray and clinical chemistry data and simple matching for histopathology categorical values in order to measure dissimilarity of the samples. Separate weighting terms are used for microarray, clinical chemistry and histopathology measurements to control the influence of each data domain on the clustering of the samples. The dynamic validity index for numeric data was modified with a category utility measure for determining the number of clusters in the data sets. A cluster's prototype, formed from the mean of the values for numeric features and the mode of the categorical values of all the samples in the group, is representative of the phenotype of the cluster members. The approach is shown to work well with a simulated mixed data set and two real data examples containing numeric and categorical data types. One from a heart disease study and another from acetaminophen (an analgesic) exposure in rat liver that causes centrilobular necrosis. Conclusion: The modk-prototypes algorithm partitioned the simulated data into clusters with samples in their respective class group and the heart disease samples into two groups (sick and buff denoting samples having pain type representative of angina and non-angina respectively) with an accuracy of 79%. This is on par with, or better than, the assignment accuracy of the heart disease samples by several well-known and successful clustering algorithms. Following modk-prototypes clustering of the acetaminophen-exposed samples, informative genes from the cluster prototypes were identified that are descriptive of, and phenotypically anchored to, levels of necrosis of the centrilobular region of the rat liver. The biological processes cell growth and/or maintenance, amine metabolism, and stress response were shown to discern between no and moderate levels of acetaminophen-induced centrilobular necrosis. The use of well-known and traditional measurements directly in the clustering provides some guarantee that the resulting clusters will be meaningfully interpretable.
Mixture modeling of transcript abundance classes in natural populations

(Georgia Institute of Technology, 2007) Hsieh, Wen-Ping ; Passador-Gurgel, Gisele ; Stone, Eric A. ; Gibson, Greg

Background. Populations diverge in genotype and phenotype under the influence of such evolutionary processes as genetic drift, mutation accumulation, and natural selection. Because genotype maps onto phenotype by way of transcription, it is of interest to evaluate how these evolutionary factors influence the structure of variation at the level of transcription. Here, we explore the distributions of cis-acting and trans-acting factors and their relative contributions to expression of transcripts that exhibit two or more classes of abundance among individuals within populations. Results. Expression profiling using cDNA microarrays was conducted in Drosophila melanogaster adult female heads for 58 nearly isogenic lines from a North Carolina population and 50 from a California population. Using a mixture modeling approach, transcripts were identified that exhibit more than one mode of transcript abundance across the samples. Power studies indicate that sample sizes of 50 individuals will generally be sufficient to detect divergent transcript abundance classes. The distribution of transcript abundance classes is skewed toward low frequency minor classes, which is reminiscent of the typical skew in genotype frequencies. Similar results are observed in reported data on gene expression in human lymphoblast cell lines, in which analysis of association with linked polymorphisms implies that cis-acting single nucleotide polymorphisms make only a modest contribution to bimodal distributions of transcript abundance. Conclusion. Population surveys of gene expression may complement genetical genomics as a general approach to quantifying sources of transcriptional variation. Differential expression of transcripts among individuals is due to a complex interplay of cis-acting and trans-acting factors.
Tests for the replication of an association between Egfr and natural variation in Drosophila melanogaster wing morphology

(Georgia Institute of Technology, 2005-08-15) Palsson, Arnar ; Dodgson, James ; Dworkin, Ian ; Gibson, Greg

Background.Quantitative differences between individuals stem from a combination of genetic and environmental factors, with the heritable variation being shaped by evolutionary forces. Drosophila wing shape has emerged as an attractive system for genetic dissection of multi-dimensional traits. We utilize several experimental genetic methods to validation of the contribution of several polymorphisms in the Epidermal growth factor receptor (Egfr) gene to wing shape and size, that were previously mapped in populations of Drosophila melanogaster from North Carolina (NC) and California (CA). This re-evaluation utilized different genetic testcrosses to generate heterozygous individuals with a variety of genetic backgrounds as well as sampling of new alleles from Kenyan stocks.Results Only one variant, in the Egfr promoter, had replicable effects in all new experiments. However, expanded genotyping of the initial sample of inbred lines rendered the association non-significant in the CA population, while it persisted in the NC sample, suggesting population specific modification of the quantitative trait nucleotide QTN effect.Conclusion Dissection of quantitative trait variation to the nucleotide level can identify sites with replicable effects as small as one percent of the segregating genetic variation. However, the testcross approach to validate QTNs is both labor intensive and time-consuming, and is probably less useful than resampling of large independent sets of outbred individuals.
Anomalies in the Expression Profile of Interspecific Hybrids of Drosophila melanogaster and Drosophila simulans

(Georgia Institute of Technology, 2004-03) Ranz, José M. ; Namgyal, Kalsang ; Gibson, Greg ; Hartl, Daniel L.

When females of Drosophila melanogaster and males of Drosophila simulans are mated, the male progeny are inviable, whereas the female progeny display manifold malformations and are sterile. These abnormalities result from genetic incompatibilities accumulated since the time the lineages of the species diverged, and may have their origin in aberrant gene transcription. Because compensatory changes within species may obscure differences at the regulatory level in conventional comparisons of the expression profile between species, we have compared the gene-expression profile of hybrid females with those of females of the parental species in order to identify regulatory incompatibilities. In the hybrid females, we find abnormal levels of messenger RNA for a large fraction of the Drosophila transcriptome. These include a gross underexpression of genes preferentially expressed in females, accompanying gonadal atrophy. The hybrid females also show significant overexpression of male-biased genes, which we attribute to incompatibilities in the regulatory mechanisms that normally act to control the expression of these genes in females. The net result of the multiple incompatibilities is that the gene-expression profiles of the parental females are more similar to each other than either is to that of the hybrid.
A mixed model approach to identify yeast transcriptional regulatory motifs via microarray experiments

(Georgia Institute of Technology, 2004) Yu, Xiang ; Chu, Tzu-Ming ; Gibson, Greg ; Wolfinger, Russell D.

A genome-wide location analysis method has been introduced as a means to simultaneously study protein-DNA binding interactions for a large number of genes on a microarray platform. Identification of interactions between transcription factors (TF) and genes provide insight into the mechanisms that regulate a variety of cellular responses. Drawing proper inferences from the experimental data is key to finding statistically significant TFgene binding interactions. We describe how the analysis and interpretation of genome-wide location data can be fit into a traditional statistical modeling framework that considers the data across all arrays and formulizes appropriate hypothesis tests. The approach is illustrated with data from a yeast transcription factor binding experiment that illustrates how identified TF-gene interactions can enhance initial exploration of transcriptional regulatory networks. Examples of five kinds of transcriptional regulatory structure are also demonstrated. Some stark differences with previously published results are explored.
Identification of target genes of the homeotic gene Antennapedia by enhancer detection

(Georgia Institute of Technology, 2003-08) Wagner-Bernholz, Juliane T. ; Wilson, Clive ; Gibson, Greg ; Schuh, Reinhard ; Gehring, Walter J.

Localized expression of the homeotic gene Antennapedia (Antp) in Drosophila melanogaster is required for normal development of the thoracic segments. When the Antp gene is expressed ectopically in the larval primordium of the antenna, the antennal imaginal disc, the developmental fate of the disc is switched and the adult antenna is transformed to a mesothoracic leg. We screened approximately 550 different fly strains carrying single copies of an enhancer-detector transposon to identify regulatory elements and corresponding genes that are either activated or repressed in antennal discs in response to this transformation. Several regulatory elements that are either direct or indirect targets of Antp were found. One transposant that expresses the reporter gene (lacZ) in the antennal disc, but not in the leg disc, was studied in more detail. The enhancer detector in this strain is located near a similarly regulated gene at the spalt (sal) locus, which encodes a homeotic function involved in embryonic head and tail development. The expression of this newly discovered gene, spalt major (salm) is strongly repressed in gain-of-function mutants that express Antp in the antennal disc. Recessive loss-of-function mutations (Antp-) have the opposite developmental effect; they cause the differentiation of antennal structures in the second leg disc. Accordingly, salm is derepressed in clones of homozygous Antp- cells. Therefore, we conclude that Antp negatively regulates salm. The time course of the interaction and reporter gene fusion experiments suggests (but does not prove) a direct interaction between Antp and cis-regulatory elements of salm. Our analysis of several enhancer-detector strains suggests that the basic patterning information in the antennal and leg imaginal discs is very similar.
Assessing gene significance from cDNA microarray expression data via mixed models

(Georgia Institute of Technology, 2001) Wolfinger, Russell D. ; Gibson, Greg ; Wolfinger, Elizabeth D. ; Bennett, Lee ; Hamadeh, Hisham ; Ashari, Cynthia ; Paules, Richard S.

The determination of a list of differentially expressed genes is a basic objective in many cDNA microarray experiments. We present a statistical approach that allows direct control over the percentage of false positives in such a list and, under certain reasonable assumptions, improves on existing methods with respect to the percentage of false negatives. The method accommodates a wide variety of experimental designs and can simultaneously assess signi cant differences between multiple types of biological samples. Two interconnected mixed linear models are central to the method and provide a exible means to properly account for variability both across and within genes. The mixed model also provides a convenient framework for evaluating the statistical power of any particular experimental design and thus enables a researcher to a priori select an appropriate number of replicates. We also suggest some basic graphics for visualizing lists of signi cant genes. Analyses of published experiments studying human cancer and yeast cells illustrate the results.