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Research Project: Identification of the Ecological Niches and Development of Intervention Strategies to Reduce Pathogenic Foodborne Pathogens in Poultry

Location: Food and Feed Safety Research

Title: An introduction to metagenomic data generation, analysis, visualization, and interpretation

item SINGH, BANESHWAR - Virginia Commonwealth University
item Crippen, Tawni - Tc
item TOMBERLIN, JEFFERY - Texas A&M University

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 8/14/2016
Publication Date: 5/30/2017
Citation: Singh, B., Crippen, T.L., Tomberlin, J.K. 2017. An introduction to metagenomic data generation, analysis, visualization, and interpretation. In: Carter, D.O., Tomberlin, J.K., Benbow, M.E., Metcalf, J.L., editors. Forensic Science in Focus: Forensic Microbiology. 1st edition. New York, NY: John Wiley & Sons Ltd. p. 94-126.

Interpretive Summary:

Technical Abstract: As discussed in virtually every chapter of this book, the emergence of next-generation sequencing technology in the last decade has revolutionized the field of forensic microbiology and decomposition ecology. Because of such technological developments, we now recognize that 10^10 and 10^14 bacteria live on and within us, respectively, which outnumbers our mammalian cells by about 10 times (Schloss 2014). The taxonomic diversity in skin microbes can vary significantly between individuals (especially those that are rare in abundance), and thus can serve as a marker to establish individualization (Oh et al. 2014, Schloss 2014). Sequencing the enormity of individual microbes that exist in a given environmental community is no longer a limiting factor. In reality, managing the sheer volume of sequences generated through such analyses turns out to be the greater challenge. In concert with the utilization of these new technologies in scientific investigations, the number of microbial sequences entered into public databases has increased exponentially, and with the current rate of sequencing, it is predicted that most microbial taxa will have been described by the end of this decade (Yarza et al 2014). Thus the magnitude of sequence data that will be generated by these platforms creates huge challenges for scientists. This chapter will focus on current status of different next-generation sequencing methods, 16S ribosomal DNA (16S rDNA), and whole-community shotgun sequence data analysis, visualization, and interpretation of results (see Figure 1).