Identification of Transcription Factors involved in Obesity.
Lane, Jacqueline.
2011
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Abstract: Obesity
is a leading cause of preventable death in the United States. With the prevalence of
obesity >30% in the United States, to effectively treat this complex disorder we must
identify the underlying genetic components. To understand complex disorders,
understanding complex regulatory networks where many genes are affected is critical.
Transcription factors lie at the heart of ... read moreregulatory networks, small changes in the
binding affinity or concentration can perturb entire networks of genes. Therefore we
seek to identify transcription factors that are involved in obesity. In order to do this
we developed a novel computational methodology to extract information about
transcriptional gene networks in genome-scale data, yielding a list of 53 transcription
factors potentially involved in obesity. We validated SPI1, our top candidate, by
examining the effects of gene knock down in adipogenesis. First we generated and
characterized a rapidly differentiating clonal OP9 preadipocyte cell population. We
conclude that our cells differentiate in 72 hours, are readily transfectable, and
differentiate through gene expression changes comparable to established preadipocyte
lines. Gene expression profiles of differentiating OP9 cells express the classical
adipogenic marker genes C/EBPbeta, C/EBPalpha, Gata2, and Plin1. Depletion of SPI1
increases lipid accumulation OP9 adipogenesis. In addition, variation in the human SPI1
gene modulates obesity risk. Individuals with the AA genotype of SNP rs4752829 have
increased body mass index (BMI) compared to carriers of the G allele. SNP rs3740689
modulates the effect of dietary saturated fatty acid and omega-3 polyunsaturated
(N3-PUFA) on BMI. These approaches demonstrate a strong role for SPI1 in obesity, with
the potential to target SPI1 with pharmacological or dietary modifications. In addition,
by describing the transcriptome of OP9 preadipocytes, we have validated an adipogenesis
model for potential high-throughput screening of the effects of gene depletion on fat
cell generation. For the first time the transcriptome of OP9 adipogenesis has been
described and a gene-diet interaction influencing BMI has been found in SPI1. Our
computational approach directed us to SPI1 and was validated in this study. This study
demonstrates that our computational approach can be used to investigate the role of
transcription factors in many other
disorders.
Thesis (Ph.D.)--Tufts University, 2011.
Submitted to the Dept. of Genetics.
Advisor: Jose Ordovas.
Committee: Donna Slonim, Alan Kopin, Acacia Alcivar Warren, Inga Peter, Diana Bianchi, and Lu Qi.
Keywords: Genetics, Nutrition, and Biology.read less - ID:
- pn89dj993
- Component ID:
- tufts:20409
- To Cite:
- TARC Citation Guide EndNote