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Applying phylogenetic tree building in MEGA X to forensic applications for identifying unknown specimens

Author(s): Nicholas Lorusso1, Denise Gemmellaro2

1. University of North Texas at Dallas 2. Kean University

403 total view(s), 29 download(s)

Summary:

This exercise is designed to guide a learner through the construction of phylogenetic trees as a means of addressing research questions in forensic science such as the identification of previously unidentified species contributing to decomposition.

Description

This exercise is designed to guide a learner through the construction of phylogenetic trees as a means of addressing research questions in forensic science such as the identification of previously unidentified species contributing to decomposition. Students are introduced, over the course of roughly one lab period, to: metabarcoding and bioinformatics, databases for retrieving publicly available data, the construction of phylogenetic trees using MEGA, and the interpretation and implications of the trees they construct. Learners are provided with a novel sequence for the Cytochrome C Oxidase gene extracted from a real unknown specimen and are tasked with identifying the most likely identity of the specimen. To accomplish this the learner will construct their own data file of reference sequences by retrieving sequences from published databases before combining this with the provided record prior to phylogenetic tree construction. By creating this predicted phylogeny the student will identify the most likely identity of the unknown specimen and will be able to clearly explain their prediction based on the prepared dataset and phylogeny. This will not only expose students to how phylogenetics can be applied to forensic applications but will also demonstrate the use of such methods to real world biological questions.

The unknown specimen to be evaluated in this exercise comes from a forensic research study performed in New Jersey and was designed based on work conducted by the authors on the sequence provided.

Learning objectives

After successful completion of this exercise, students will be able to:

  • Apply the scientific method to questions relating phylogenetics to forensic science
  • Identify appropriate computational approaches to address biological questions
  • Evaluate evolutionary relationships using graphical methods
  • Critically assess results of barcoding datasets
  • Find and interpret data from major online databases such as Barcode Of Life.
  • Use the software package MEGA X to construct and evaluate phylogenetic trees
  • Apply bioinformatics methods to solving biological problems in forensic science
     

Resources:

  • A descriptive exercise handout with integrated assessment questions for students to complete
  • A datafile (UNKNOWN.fas) for students to use during the exercise
  • Two data files (GENUSMEGA.fas and FLYMEGA.fas) for instructors to use to make the exercise more accessible to their students, time frames, and needs.
  • An instructor PowerPoint file for use in introducing students to the topics and techniques covered

Additional requirements:

  • Internet access
  • Notepad or an alternative text editor for viewing FASTA files
  • MEGA X (download instructions in student handout)
    • Note: If using a version of MEGA X on a non-windows computer there may be slight differences in how certain steps are accessed. We have tried to make the instructions as general as possible but if  using an operating system other than Microsoft Windows we encourage reviewing the support documents on the MEGA website (Documentation (megasoftware.net)

References

DeSalle, R., & Goldstein, P. (2019). Review and interpretation of trends in DNA barcoding. Frontiers in Ecology and Evolution7, 302.

Joseph, I., Mathew, D. G., Sathyan, P., & Vargheese, G. (2011). The use of insects in forensic investigations: An overview on the scope of forensic entomology. Journal of forensic dental sciences3(2), 89.

Kumar, S., Stecher, G., Li, M., Knyaz, C., & Tamura, K. (2018). MEGA X: molecular evolutionary genetics analysis across computing platforms. Molecular biology and evolution35(6), 1547.

Pečnikar, Ž. F., & Buzan, E. V. (2014). 20 years since the introduction of DNA barcoding: from theory to application. Journal of applied genetics55(1), 43-52.

Team, R. C. (2013). R: A language and environment for statistical computing.

Tomberlin, J. K., Benbow, M. E., Tarone, A. M., & Mohr, R. M. (2011). Basic research in evolution and ecology enhances forensics. Trends in Ecology & Evolution26(2), 53-55.

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