Effects of phenotypical patterns on epigenetic markers

Ray Hashemi, Azita Bahrami, Jeffrey Young, Aaron Schrey, Travis Robbins Robbins, Alexandria Ragsdale, Tracy Langkilde

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The Eastern Fence Lizards (specie S1) are exposed to Fire Ants (specie S2) in some areas of their habitat (space B1) and not exposed in some other areas (space B2.) The population of S1 in B1 have responded phenotypically in patterns that are both evolutionary (cross-generational) and plastic (within lifetime.) Existence of relationships, if any, between phenotypical patterns and epigenetic markers is the proof that patterns affect epigenetic markers and not DNA sequence. We investigate such relationships on a dataset (D) with 189 epigenetic markers and four phenotypes of Sex (SEX), Right-hind Limb (RHL), Snout Vent Length (SVL), and ratio of RHL/SVL collected for two groups (g0 and g1) of specie S1 from B1 and B2, respectively. The goal is threefold: (a) whether there is a subset of epigenetic markers in D that differentiates between members in g0 and g1, (b) which subset is the best, if more than one such subset exists, and (c) whether there are epigenetic markers that significantly differ between the lizards in g0 and g1. Part (a) was met by introducing eight algorithms that identified eight subsets of epigenetic markers from which four strict and four relaxed representatives of D were generated. Part (b) was met by use of inductive learning algorithm C4.5. One of the eight algorithms (Entropy-Thinning) delivered the best representative (R) of D (with 14 markers.) R predicted four phenotypes separately with high accuracies (≥85%) as a proof of strong relationships between phenotypical patterns and markers. Part (c) was met by using One-Way Classification approach on R. Four epigenetic markers of Loci 036, 060, 071, and 101 were significantly differ (99.5% certainty) between g0 and g1.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1351-1356
Number of pages6
ISBN (Electronic)9781728113609
DOIs
StatePublished - Dec 2018
Event2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018 - Las Vegas, United States
Duration: Dec 13 2018Dec 15 2018

Publication series

NameProceedings - 2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018

Conference

Conference2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018
CountryUnited States
CityLas Vegas
Period12/13/1812/15/18

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems and Management
  • Control and Optimization
  • Modeling and Simulation
  • Artificial Intelligence

Cite this

Hashemi, R., Bahrami, A., Young, J., Schrey, A., Robbins, T. R., Ragsdale, A., & Langkilde, T. (2018). Effects of phenotypical patterns on epigenetic markers. In Proceedings - 2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018 (pp. 1351-1356). [8947676] (Proceedings - 2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSCI46756.2018.00262