Geoscience Reference
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addressed the implications of epigenetics in the carcinogenic mode of action of
nitrobenzene, but only two original research publications that provided experi-
mental data from EPA have directly assessed epigenetic mechanisms. One study
(Grace et al. 2011) evaluated the role of maternal influences on epigenetic pro-
gramming in the in utero development of endocrine signaling in the brain. The
second (DeAngelo et al. 2008) provided dose-response data on the development
of hepatocellular neoplasia in male mice exposed over a lifetime to trichloroace-
tic acid, a putative carcinogenic product of trichloroethylene solvent breakdown
and a chlorination disinfection byproduct. Although they did not assess epige-
netic changes experimentally, they suggested that epigenetic mechanisms might
explain the observed tumors inasmuch as the compound was not genotoxic. EPA
has not published many original papers on epigenetics, but the EPA grants data-
base lists 36 extramural research grants to universities across the country that are
exploring the role of epigenetics in environmental response (EPA 2012). Given
the relevance of this emerging field, it is important that EPA scientists and regu-
lators become more active in the accumulation of epigenetic knowledge and its
application to human and environmental health risk assessment. Although much
remains to be learned about epigenetic phenomena, it is likely to be a critical
contributor to many diseases that have both a genetic and environmental com-
ponent, and will be especially important in understanding how exposures early
in life might contribute to disease onset later in life.
BIOINFORMATICS
Rapid advances in biotechnology have resulted in an explosion in -omics
data and in information on biochemical and physiologic processes in complex
biologic systems. The advent of the internet, new technologies, and high-
throughput sequencing has spurred further growth of -omics data and has made
it possible to disseminate data globally (Attwood et al. 2011). Since the 1990s,
the field of bioinformatics has seen growth in response to the need for the gen-
eration, storage, retrieval, processing, analysis, and interpretation of -omics data.
It draws on the principles, theories, and methods of the biologic sciences, com-
puter science and engineering, mathematics, and statistics, and it has always
been at the core of understanding of biologic processes and disease pathways
(Attwood et al. 2011). As the -omics revolution continues, bioinformatics will
continue to evolve, and EPA will continue to require inhouse expertise and
state-of-the-science capacity in the field.
Analysis of biologic data has evolved from comparisons of various kinds
of sequence data (Needleman and Wunsch 1970; Smith and Waterman 1981;
Lipman and Pearson 1985) to algorithms that can search various sequence data-
bases. Methods and tools have also been developed for the analysis of sequence,
annotation, and expression data in support of a wide variety of applications, such
as pattern recognition, protein and RNA structure prediction, micro data analysis
(Attwood et al. 2011), and biomarker discovery (Baumgartner et al. 2011; Roy
et al. 2011). There is an increasing emphasis on understanding biologic systems
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