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Greg Gibson

Publications and source records attributed to Greg Gibson.

At least 19 recordsLinked to original sources
PubMed2026

Gene expression profiling identifies potential biomarkers for vaso-occlusive episodes in sickle cell disease.

Vaso-occlusive episodes (VOEs) or acute pain events, involving complex interactions between sickle erythrocytes and other blood cells, are a hallmark of sickle cell disease (SCD). In this study, we analyzed changes in peripheral blood transcriptomes between steady state and VOEs in individuals with SCD. We followed a cohort of 174 individuals with SCD with or without chronic pain and collected peripheral blood at clinic visits (steady state) and during hospitalizations (VOEs). We performed RNA-Seq profiling of CD45+ leukocytes and CD71+ erythroid cells. Pathways linked to complement activation, coagulation, and IL-6/JAK/STAT3 signaling were enriched during VOEs in the CD45+ cells. Contrastingly, the CD71+ cells showed an enrichment of pathways related to the cell cycle, such as mTORC1 signaling and the G2M checkpoint during VOEs. We then analyzed the expression changes of genes in patients with longitudinal data to determine potential biomarkers for VOEs. Expression of 4 genes - FAM20A, IL1B, MS4A4A, and SERPINB2 - was elevated during VOEs compared with steady state in the majority of patients. Furthermore, our results indicate that patients experiencing chronic pain exhibited 44% increased enrichment of significant pathways during VOEs when compared with patients without chronic pain.

Humans↗
PubMed2006

Epidermal growth factor receptor and transforming growth factor-beta signaling contributes to variation for wing shape in Drosophila melanogaster.

Wing development in Drosophila is a common model system for the dissection of genetic networks and their roles during development. In particular, the RTK and TGF-beta regulatory networks appear to be involved with numerous aspects of wing development, including patterning, cell determination, growth, proliferation, and survival in the developing imaginal wing disc. However, little is known as to how subtle changes in the function of these genes may contribute to quantitative variation for wing shape, per se. In this study 50 insertional mutations, representing 43 loci in the RTK, Hedgehog, TGF-beta pathways, and their genetically interacting factors were used to study the role of these networks on wing shape. To concurrently examine how genetic background modulates the effects of the mutation, each insertion was introgressed into two wild-type genetic backgrounds. Using geometric morphometric methods, it is shown that the majority of these mutations have profound effects on shape but not size of the wing when measured as heterozygotes. To examine the relationships between how each mutation affects wing shape hierarchical clustering was used. Unlike previous observations of environmental canalization, these mutations did not generally increase within-line variation relative to their wild-type counterparts. These results provide an entry point into the genetics of wing shape and are discussed within the framework of the dissection of complex phenotypes.

Animals↗
PubMed2006

Evolution: the plastic transcriptome.

Studies across a wide range of species point to a surprising degree of plasticity in the transcriptional states that organisms can adopt, suggesting that organisms often respond to environmental challenges through wholesale reprogramming of their gene expression.

Animals↗
PubMed2006

Analysis of variance of microarray data.

Analysis of variance (ANOVA) is an approach used to identify differentially expressed genes in complex experimental designs. It is based on testing for the significance of the magnitude of effect of two or more treatments taking into account the variance within and between treatment classes. ANOVA is a highly flexible analytical approach that allows investigators to simultaneously assess the contributions of multiple factors to gene expression variation, including technical (dye, batch) effects and biological (sex, genotype, drug, time) ones, as well as interactions between factors. This chapter provides an overview of the theory of linear mixture modeling and the sequence of steps involved in fitting gene-specific models and discusses essential features of experimental design. Commercial and open-source software for performing ANOVA is widely available.

Analysis of Variance↗
PubMed2005

The quantitative genetics of transcription.

Quantitative geneticists have become interested in the heritability of transcription and detection of expression quantitative trait loci (eQTLs). Linkage mapping methods have identified major-effect eQTLs for some transcripts and have shown that regulatory polymorphisms in cis and in trans affect expression. It is also clear that these mapping strategies have little power to detect polygenic factors, and some new statistical approaches are emerging that paint a more complex picture of transcriptional heritability. Several studies imply pervasive non-additivity of transcription, transgressive segregation and epistasis, and future studies will soon document the extent of genotype-environment interaction and population structure at the transcriptional level. The implications of these findings for genotype-phenotype mapping and modeling the evolution of transcription are discussed.

Chi-Square Distribution↗
PubMed2005

Tests for the replication of an association between Egfr and natural variation in Drosophila melanogaster wing morphology.

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.

Animals↗
PubMed2005

Greg Gibson.

Explore the source record for details and available documents.

Biological Evolution↗
PubMed2005

Replication of an Egfr-wing shape association in a wild-caught cohort of Drosophila melanogaster.

Linkage disequilibrium mapping has been used extensively in medical and evolutionary genetics to map causal polymorphisms within genes associated with disease status or phenotypic variation for a trait. However, the initial findings of most nonhuman studies have not been replicated in subsequent studies, due in part to false positives, as well as additional factors that can render true positives unreplicable. These factors may be more severe when the initial study is performed using an experimental population of organisms reared under controlled lab conditions. We demonstrate that despite considerable phenotypic differences for wing shape between a lab-reared experimental population and a wild-caught cohort of Drosophila melanogaster, an association between a putative regulatory polymorphism in Egfr and wing shape can be replicated. These results are discussed both within the framework of future association-mapping studies and within the context of the evolutionary dynamics of alleles in populations.

Alleles↗
PubMed2005

Gene expression profiles associated with the transition to parasitism in Ancylostoma caninum larvae.

Ancylostoma caninum is a common canine parasite responsible for anemia and death in infected dogs. Gene expression profiling was used to investigate molecular differences between two different forms of the third larval stage (L3s): infective free-living larvae and in vitro serum-stimulated larvae that mimic the initial stages of parasitism of a host. We developed an A. caninum cDNA microarray consisting of 4191 EST clones, and used it to identify a set of 113 genes that are differentially regulated between infective and parasitic larval stages. Real-time RT-PCR was used to confirm the expression differences of a subset of the genes. Of the genes repressed upon serum stimulation, seven encode members of the 'Ancylostoma secreted protein' ASP family, while another transcript encoding a 24 kDa excretory protein with similarity to ASP was up-regulated in serum-stimulated L3s. This suggests that different members of a protein family that has important implications for the hookworm's parasitic lifestyle are regulated in a complementary manner in response to serum stimulation. Comparison of two strains of A. caninum from North Carolina and Maryland only identified a single gene, one of the members of the ASP family, that was differentially repressed upon serum stimulation.

Ancylostoma↗
PubMed2004

A mixed model approach to identify yeast transcriptional regulatory motifs via microarray experiments.

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 TF-gene 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.

Journal Article↗
PubMed2004

Genes regulated by mating, sperm, or seminal proteins in mated female Drosophila melanogaster.

In Drosophila melanogaster, sperm and accessory gland proteins ("Acps," a major component of seminal fluid) transferred by males during mating trigger many physiological and behavioral changes in females (reviewed in ). Determining the genetic changes triggered in females by male-derived molecules and cells is a crucial first step in understanding female responses to mating and the female's role in postcopulatory processes such as sperm competition, cryptic female choice, and sexually antagonistic coevolution. We used oligonucleotide microarrays to compare gene expression in D. melanogaster females that were either virgin, mated to normal males, mated to males lacking sperm, or mated to males lacking both sperm and Acps. Expression of up to 1783 genes changed as a result of mating, most less than 2-fold. Of these, 549 genes were regulated by the receipt of sperm and 160 as a result of Acps that females received from their mates. The remaining genes whose expression levels changed were modulated by nonsperm/non-Acp aspects of mating. The mating-dependent genes that we have identified contribute to many biological processes including metabolism, immune defense, and protein modification.

Animals↗
PubMed2004

Cross-species comparison of genome-wide expression patterns.

The rapid accumulation of microarray data from multiple species provides unprecedented opportunities to study the evolution of biological systems. Recent studies have used cross-species comparisons of expression profiles to annotate gene functions, to draw evolutionary inferences concerning specific biological processes and to study the global properties of expression networks.

Animals↗
PubMed2004

Anomalies in the expression profile of interspecific hybrids of Drosophila melanogaster and Drosophila simulans.

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.

Animals↗
PubMed2004

Use of regression methods to identify motifs that modulate germline transcription in Drosophila melanogaster.

Identification of cis-regulatory motifs has been difficult due to the short and variable length of the sequences that bind transcription factors. Using both sequence and microarray expression data, we present a method for identifying cis-regulatory motifs that uses regression trees to refine results from simple linear regression of expression levels on motif counts. Analysis of expression patterns from two separate datasets for genes showing significant differences in expression between the sexes in Drosophila melanogaster resulted in a model that identified known binding sites upstream of genes that are differentially expressed in the germline. We obtained a strong result for motif TCGATA, part of the larger, characterized binding site of dGATAb protein. We also identified an uncharacterized motif that is positively associated with sex-biased expression and was assembled from smaller motifs grouped by our model. A regression tree model provides a grouping of independent variables into multiple linear models, an advantage over a single multivariate model. In our case, this grouping of motifs suggests binding sites for cooperating factors in sex-specific expression, as well as a way of combining smaller motifs into larger binding sites.

Animals↗
PubMed2004

Uncovering cryptic genetic variation.

Cryptic genetic variation is the dark matter of biology: it is variation that is not normally seen, but that might be an essential source of physiological and evolutionary potential. It is uncovered by environmental or genetic perturbations, and is thought to modify the penetrance of common diseases, the response of livestock and crops to artificial selection and the capacity of populations to respond to the emergence of a potentially advantageous macro-mutation. We argue in this review that cryptic genetic variation is pervasive but under-appreciated, we highlight recent progress in determining the nature and identity of genes that underlie cryptic genetic effects and we outline future research directions.

Animals↗
PubMed2004

Comparison of regional gene expression differences in the brains of the domestic dog and human.

Comparison of the expression profiles of 2,721 genes in the cerebellum, cortex and pituitary gland of three American Staffordshire terriers, one beagle and one fox hound revealed regional expression differences in the brain but failed to reveal marked differences among breeds, or even individual dogs. Approximately 85 per cent (42 of 49 orthologue comparisons) of the regional differences in the dog are similar to those that differentiate the analogous human brain regions. A smaller percentage of human differences were replicated in the dog, particularly in the cortex, which may generally be evolving more rapidly than other brain regions in mammals. This study lays the foundation for detailed analysis of the population structure of transcriptional variation as it relates to cognitive and neurological phenotypes in the domestic dog.

Animals↗