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Stable patterns of gene expression regulating carbohydrate metabolism determined by geographic ancestry.

ABSTRACT: Individuals of African descent in the United States suffer disproportionately from diseases with a metabolic etiology (obesity, metabolic syndrome, and diabetes), and from the pathological consequences of these disorders (hypertension and cardiovascular disease).Using a combination of genetic/genomic and bioinformatics approaches, we identified a large number of genes that were both differentially expressed between American subjects self-identified to be of either African or European ancestry and that also contained single nucleotide polymorphisms that distinguish distantly related ancestral populations. Several of these genes control the metabolism of simple carbohydrates and are direct targets for the SREBP1, a metabolic transcription factor also differentially expressed between our study populations.These data support the concept of stable patterns of gene transcription unique to a geographic ancestral lineage. Differences in expression of several carbohydrate metabolism genes suggest both genetic and transcriptional mechanisms contribute to these patterns and may play a role in exacerbating the disproportionate levels of obesity, diabetes, and cardiovascular disease observed in Americans with African ancestry.

SUBMITTER: Schisler JC

PROVIDER: S-EPMC2790609 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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Stable patterns of gene expression regulating carbohydrate metabolism determined by geographic ancestry.

Schisler Jonathan C JC Charles Peter C PC Parker Joel S JS Hilliard Eleanor G EG Mapara Sabeen S Meredith Dane D Lineberger Robert E RE Wu Samuel S SS Alder Brian D BD Stouffer George A GA Patterson Cam C

PloS one 20091209 12

<h4>Background</h4>Individuals of African descent in the United States suffer disproportionately from diseases with a metabolic etiology (obesity, metabolic syndrome, and diabetes), and from the pathological consequences of these disorders (hypertension and cardiovascular disease).<h4>Methodology/principal findings</h4>Using a combination of genetic/genomic and bioinformatics approaches, we identified a large number of genes that were both differentially expressed between American subjects self- ...[more]

PMID: 20016837

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Project description:Individuals of African descent in the United States suffer disproportionately from diseases with a metabolic etiology (obesity, metabolic syndrome, and diabetes), and from the pathological consequences of these disorders (hypertension and cardiovascular disease). Using a combination of genetic/genomic and bioinformatics approaches, we identified a large number of genes that were both differentially expressed between American subjects self-identified to be of either African or European ancestry and that also contained single nucleotide polymorphisms that distinguish distantly related ancestral populations. Several of these genes control the metabolism of simple carbohydrates and are direct targets for the SREBP1, a metabolic transcription factor also differentially expressed between our study populations. These data support the concept of stable patterns of gene transcription unique to a geographic ancestral lineage. The coordinated transcriptional adaptation of carbohydrate metabolism to dietary environmental pressures suggests a genetic and transcriptional mechanism for the disproportionate levels of obesity, diabetes, and cardiovascular disease observed in Americans with African ancestry. Keywords: Ancestry-dependent gene expression, functional genomics, personalized medicine, multi-factoral disease, nutrition, diabetes We utilized a “sample x reference” experimental design strategy in which RNA extracted from human peripheral blood mononuclear cells was hybridized to the microarray slide in the presence of labeled Universal Human Reference RNA (UHRR, Stratagene, LaJolla, CA). A total of 161 subjects were used in this analysis. Briefly, five hundred nanograms of total RNA were used for gene expression profiling following reverse transcription and T-7 polymerase-mediated amplification/labeling with Cyanine-5 CTP. Labeled subject cRNA was co-hybridized to Agilent G4112A Whole Human Genome 44K oligonucleotide arrays with equimolar amounts of Cyanine-3 labeled UHRR. Slides were hybridized, washed, and scanned on an Axon 4000b microarray scanner. The data were processed using GenePix Pro 6 software

Project description:This proposal is aimed at providing transcriptome data to underpin a long-term joint research programme of Steve Smith and Alison Smith. We are jointly studying starch synthesis and breakdown in Arabidopsis leaves, and individually studying other enzymes of carbohydrate metabolism (eg. sucrose synthases, invertases, sugar transporters). Collectively these enzymes are encoded by up to 100 known genes, but there are many others of relevance to our studies. For several years we have employed a defined set of growth conditions for this work (resulting in numerous publications). We have extensive data for changes in the amounts of starch, malto-oligosaccharides and sugars throughout the diurnal cycle in these plants, and we intend to quantitate numerous key enzymes. We now wish to profile changes in transcripts in these plants, so that this information can be correlated with changes in the amounts of key enzymes and metabolites. Analysis of the data sets will help us to relate the synthesis of certain enzymes to particular metabolic functions, and also to help identify genes encoding novel proteins involved in carbohydrate metabolism. Current research is aimed at discovering such novel proteins using proteomics approaches (BBSRC Grant: _Discovery and Functional Analysis of the Starch Proteome_). While the growth conditions (12h photoperiod, 150 umol/m2/s, 20C) and ecotype (Col-0) are specifically tailored to our experiments, they will be of value to the wider community, and could form the basis for collaborative studies with other groups. The experiment has involved sampling leaves at eleven different time points as follows: 0, 1, 2, 4, 8, 12, 13, 14, 16, 20, and 24 h (where time 0 is the onset of dark and 12 h is the onset of light). The 24 h time point is a repeat of 0 h. This sequence provides relatively more samples immediately after the light-dark transitions, when changes in metabolism are most pronounced. Plants were grown in a controlled environment chamber under defined conditions, and selected for harvest according to a random number generator. Three fully expanded leaves were harvested from each of 20 plants for each sample. Leaves were frozen at -80 C and a portion saved for metabolite and enzyme assays while RNA was isolated from the remainder. The RNA has been purified and is ready to send to Nottingham. Keywords: time_series_design; growth_condition_design

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Stable patterns of gene expression regulating carbohydrate metabolism determined by geographic ancestry.

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Stable patterns of gene expression regulating carbohydrate metabolism determined by geographic ancestry.

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