Applications of next-generation sequencing technologies and advanced analytical methods to understand gene by environment interactions

Caetano, Kelsey

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https://hdl.handle.net/2142/90866 Copy

Description

Title

Applications of next-generation sequencing technologies and advanced analytical methods to understand gene by environment interactions

Author(s)

Caetano, Kelsey

Issue Date

2016-04-20

Director of Research (if dissertation) or Advisor (if thesis)

Rodriguez-Zas, Sandra

Doctoral Committee Chair(s)

Rodriguez-Zas, Sandra

Committee Member(s)

• Wheeler, Matthew
• Villamil, Maria
• Steelman, Andrew

Department of Study

Animal Sciences

Discipline

Animal Sciences

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Bioinformatics
• Computational Biology
• Genetics
• Next-Generation Sequencing
• RNA-Sequencing

Abstract

Addiction to activity and to psychoactive substances share psychologically and physiological characteristics. A transcriptome study compared a mouse line selected for high voluntary activity to a control line in environments restricting or enabling a rewarding activity. Results offered insights into genetic factors behind activity dependence and provided a model for understanding addiction and other reward-dependent behaviors.Most genes differentially expressed betweenactivity genotypes were only moderately differentially expressed between activity environments, suggesting that environmental effects were not confounded with activity genotype effects. Adora2a had a significant genotype-by-environment interaction effect evidenced by over-expression in the activity genotype relative to control in high activity environment and under-expression in the low activity environment.Our findings of differentially expressed genes related to dopaminergic transmission between activity genotypes support the association between these genes and activity. Acentral theme from the functional analysis of activity genotype-environment was neuron morphogenesis. Gene network analysis identified connected genes that exhibited similar (e.g. Lhx9) and opposite (e.g. Nrgn) expression patterns between activity genotypes across reward availability environment.Our findings suggest that some transcriptomic changes in mice selected for high voluntary activity are shared with other reward-dependent behaviors. Results from this study support that high voluntary activity selection lines in mice are a helpful model to understand molecular mechanisms behind addition. Also, identification of genes and biological processes associated with both high voluntary activity and the pleasurable neurological response to physical activity may allow forthe development of drugs which make it more pleasurable for people to exercise or less pleasurable to be sedentary as a treatment approach for overweight/obesity as well as a way to improve health overall in the general population.

Graduation Semester

2016-05

Type of Resource

text

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http://hdl.handle.net/2142/90866

Copyright and License Information

Copyright 2016 Kelsey Caetano

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