“-Omics” workflow for paleolimnological and geological archives: A review

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Abstract

“-Omics” is a powerful screening method with applications in molecular biology, toxicology, wildlife biology, natural product discovery, and many other fields. Genomics, proteomics, metabolomics, and lipidomics are common examples included under the “-omics” umbrella. This screening method uses combinations of untargeted, semi-targeted, and targeted analyses paired with data mining to facilitate researchers' understanding of the genome, proteins, and small organic molecules in biological systems. Recently, however, the use of “-omics” has expanded into the fields of geology, specifically petrology, and paleolimnology. Specifically, untargeted analyses stand to transform these fields as petroleomics, and sediment-“omics” become more prevalent. “-Omics” facilitates the visualization of small molecule profiles from environmental matrices (i.e. oil and sediment). Small molecule profiles can provide improved understanding of small molecules distributions throughout the environment, and how those compositions can change depending on conditions (i.e. climate change, weathering, etc.). “-Omics” also facilities discovery of next-generation biomarkers that can be used for oil source identification and as proxies for reconstructing past environmental changes. Untargeted analyses paired with data mining and multivariate statistical analyses represents a powerful suite of tools for hypothesis generation, and new method development for environmental reconstructions. Here we present an introduction to “-omics” methodology, technical terms, and examples of applications to paleolimnology and petrology. The purpose of this review is to highlight the important considerations at each step in the “-omics” workflow to produce high quality and statistically powerful data for petrological and paleolimnological applications.

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Bell, M., & Blais, J. M. (2019, July 1). “-Omics” workflow for paleolimnological and geological archives: A review. Science of the Total Environment. Elsevier B.V. https://doi.org/10.1016/j.scitotenv.2019.03.477

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