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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Covid-19 Rapid Response Virtual Showcase

(Georgia Institute of Technology, 2021-01-12) Butera, Robert J. ; Choi, Katherine ; Craig, Kentez ; Farrugia, Sherry N. ; Fisher, Michael ; Gibson, Greg ; Harris, T. Robert ; Montreuil, Benoit ; Ng, Nga Lee ; Saldaña, Christopher J. ; Saxena, Rahul ; Zheng, Talia

The battle against COVID-19 is a worldwide challenge unlike any in living memory. The Georgia Tech community has joined the fight, contributing our expertise, innovation, and indomitable spirit to the effort. Even as we remain committed to serving our students, faculty, and staff, we have accelerated our advancement of technology in response to our world's new reality. In fact, our work has deepened the understanding of Covid-19’s trajectory, the risks associated with gatherings, Covid-19's impact on the economy, and helped to save lives and improve health outcomes locally around the world.
Using blood informative transcripts in geographical genomics: impact of lifestyle on gene expression in Fijians

(Georgia Institute of Technology, 2012-11-09) Nath, Artika Praveeta ; Arafat, Dalia ; Gibson, Greg

In previous geographical genomics studies of the impact of lifestyle on gene expression inferred from microarray analysis of peripheral blood samples, we described the complex influences of culture, ethnicity, and gender in Morocco, and of pregnancy in Brisbane. Here we describe the use of nanofluidic Fluidigm quantitative RT-PCR arrays targeted at a set of 96 transcripts that are broadly informative of the major axes of immune gene expression, to explore the population structure of transcription in Fiji. As in Morocco, major differences are seen between the peripheral blood transcriptomes of rural villagers and residents of the capital city, Suva.The effect is much greater in Indian villages than in Melanesian high-landers and appears to be similar with respect to the nature of at least two axes of variation. Gender differences are much smaller than ethnicity or lifestyle effects. Body mass index is shown to associate with one of the axes as it does in Atlanta and Brisbane, establishing a link between the epidemiological transition of human metabolic disease, and gene expression profiles.
Parent-Offspring Transmission of Adipocytokine Levels and Their Associations with Metabolic Traits

(Georgia Institute of Technology, 2011-04-04) Al-Daghri, Nasser M. ; Al-Attas, Omar S. ; Alokail, Majed S. ; Alkharfy, Khalid M. ; Yakout, Sobhy M. ; Sabico, Shaun B. ; Gibson, Greg ; Chrousos, George P. ; Kumar, Sudhesh

Adipose tissue secreted cytokines (adipocytokines) have significant effects on the physiology and pathology of human metabolism relevant to diabetes and cardiovascular disease. We determined the relationship of the pattern of these circulating hormones with obesity-related phenotypes and whether such pattern is transmitted from parent to offspring. A combined total of 403 individuals from 156 consenting Saudi families divided into initial (119 families with 123 adults and 131 children) and replication (37 families with 58 adults and 91 children) cohorts were randomly selected from the RIYADH Cohort study. Anthropometrics were evaluated and metabolic measures such as fasting serum glucose, lipid profiles, insulin, leptin, adiponectin, resistin, tumor necrosis factor alpha (TNFa), activated plasminogen activator inhibitor 1 (aPAI1), high sensitivity C-reactive protein (hsCRP) and angiotensin II were also assessed. Parent-offspring regressions revealed that with the exception of hsCRP, all hormones measured showed evidence for significant inheritance. Principal component (PC) analysis of standardized hormone levels demonstrated surprising heritability of the three most common axes of variation. PC1, which explained 21% of the variation, was most strongly loaded on levels of leptin, TNFa, insulin, and aPAI1, and inversely with adiponectin. It was significantly associated with body mass index (BMI) and phenotypically stronger in children, and showed a heritability of ,50%, after adjustment for age, gender and generational effects. We conclude that adipocytokines are highly heritable and their pattern of co-variation significantly influences BMI as early as the pre-teen years. Investigation at the genomic scale is required to determine the variants affecting the regulation of the hormones studied.
The Center for Integrative Genomics and Predictive Health in Atlanta

(Georgia Institute of Technology, 2010-11-09) Gibson, Greg

I will give a two-part talk that starts with a discussion of my groups research on genomic profiling in human populations, and leads to a presentation of my vision of the relationship of the Center for Integrative Genomics to the IBB and Systems Biology programs at Georgia Tech. We are broadly interested in the question of how environmental and cultural factors interact with genetic predisposition to shape human phenotypic variation, from gene expression in peripheral blood to facial expression in growing infants. Genomic profiling is built around genome-wide association studies (GWAS) of gene expression, metabolomics, and epigenetic marks in a variety of cohorts available through collaborators at Emory and our own contacts in places like Fiji and Morocco. I'll discuss the Center for Health Discovery and Wellbeing cohort at Emory midtown, as well as initiatives in cystic fibrosis, cardiology, cancer survivorship, and newborn children.
A Genome-Wide Gene Expression Signature of Environmental Geography in Leukocytes of Moroccan Amazighs

(Georgia Institute of Technology, 2008-04-11) Idaghdour, Youssef ; Storey, John D. ; Jadallah, Sami J. ; Gibson, Greg

The different environments that humans experience are likely to impact physiology and disease susceptibility. In order to estimate the magnitude of the impact of environment on transcript abundance, we examined gene expression in peripheral blood leukocyte samples from 46 desert nomadic, mountain agrarian and coastal urban Moroccan Amazigh individuals. Despite great expression heterogeneity in humans, as much as one third of the leukocyte transcriptome was found to be associated with differences among regions. Genome-wide polymorphism analysis indicates that genetic differentiation in the total sample is limited and is unlikely to explain the expression divergence. Methylation profiling of 1,505 CpG sites suggests limited contribution of methylation to the observed differences in gene expression. Genetic network analysis further implies that specific aspects of immune function are strongly affected by regional factors and may influence susceptibility to respiratory and inflammatory disease. Our results show a strong genome-wide gene expression signature of regional population differences that presumably include lifestyle, geography, and biotic factors, implying that these can play at least as great a role as genetic divergence in modulating gene expression variation in humans.
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.