Microarray and Genome Informatics

National Institute Of Environmental Health Sciences

Investigators

Linked publications, trials & patents

Abstract

Completed the collaborative support of investigators' research: 1) Investigated acetaminophen (APAP) toxicity gene expression in human subjects. The responsive genes serve as early indicators of an APAP exposure and their gene expression profiles can potentially be evaluated as molecular indicators. 2) Developed a high-performance computing mixed model approach to test significance of nuclear and mitochondrial SNPs interactions with kinship relationships in mice. The model identifies synergistic effects on phenotypic endpoints in mice exposed to an environmental stressor. 3) Developed a bioinformatics strategy to select gene content that represents >90% of gene expression perturbation space for inclusion on the TempO-Seq gene expression platform. The computational framework allows for the identification of a purely data-driven subset of 1500 sentinel genes, referred to as the S1500 set, which is also augmented using a knowledge-driven selection of additional genes to create the final S1500+ gene set. The sentinel genes can be used to accurately predict pathway perturbations and biological relationships for gene expression analysis of treated samples. 4) Compared the gene expression of rat liver mode of action chemical exposures measured using the TempO-Seq platform with the same samples assayed by microarray and RNA-Seq. The TempO-Seq platform is consistent with the aforementioned more established approaches for measuring the genome-wide transcriptome. 5) Analyzed exome sequencing data from mice with chemically-induced liver tumors or spontaneously-induced tumors. Cancer spectrums and signatures are compared to those generated from human cancers in an attempt to classify the biology of chemically-induced tumors. 6) Derived of the p53 human tumor suppressor cistrome which consists of regulatory factor binding and gene expression of p53 targets. This provides a global understanding of requirements for in vivo interactions between the p53 transcription factor and DNA along with transcriptional relationships across human biological systems in response to various p53 activating situations. 6) Analyzed mouse methylation data to establish baseline methylation patterns in C57BL/6N and C3H/HeN parental strains, F1 progeny lines from the parental crosses and mouse naive B cells. We established dosage compensation for chromosome X-linked inactivation of gene products and also the base-resolution of DNA methylation status downstream of the DNA methyltransferase gene Dnmt3a. 7) Using gene expression analysis and DNA methylation analysis we demonstrate that mitochondrial dysfunction leads to an early transcriptional response and metabolic reprogramming centered on the metabolism of various amino acids, including those involved in the methionine cycle. This work expands our knowledge on how mitochondrial function alters DNA methylation patterns in the nucleus.