Understanding factors that affect gene co-regulation patterns

The study of traits involved with behavior disorders and immune system can be complex and challenging. Gene expression and network analysis can help to elucidate the main molecules and pathways that influence complex traits. The goal of these studies is to understand factors that affect gene co-regulation patterns related to attention-deficit/hyperactivity disorder (ADHD), drug addiction, depression-like behavior, and immune challenge. ADHD is a common neuropsychiatric disorder that affects people of different ages. People with ADHD also have a predisposition to high levels of physical activity, and some drugs like amphetamine, are used to treat these type of disorders. The molecular mechanisms that contribute to the effectiveness of amphetamine therapy to ameliorate the symptoms of attention-deficit hyperactivity disorder (ADHD) are partially understood. The first experiment aimed to understand the molecular profiles supporting the ameliorating effect of amphetamine in a mouse hyperactivity line that exhibits ADHD-like behavior using mice striatum transcriptome. The findings support the development of therapies to ameliorate ADHD-like behaviors that target gene sub-networks while minimizing the disruption in other pathways triggered by amphetamine-based treatments. The second experiment implicated in understand the association between inflammation mechanism of action and behavioral disorders such as depression-like behavior. The tryptophan (Trp) metabolic route has been linked with chronic inflammatory diseases and psychiatric disorders, being tryptophan-degrading enzyme Indoleamine 2,3-dioxygenase (IDO1) activated during the inflammatory process. The goal of this study was to understand pathways associated with depression-like symptoms after recovery from immune challenge and deficiency of a gene associated with depression-like symptoms. The results confirmed that the genes identified can be used as potential candidates to understand the mechanisms involved in the infection leading to inflammation and depression-like behavior. The third study is a continuation of the first experiment, where a systems biology approach was used to elucidate mechanisms that regulate functional processes and pathways that are shared between genes found in the differential expression analyses. Differential co-expression analysis was also used to compare the structure of two co-expression networks between the conditions. Both weighted gene co-expression network analysis (WGCNA) and differential co-expression analysis were powerful alternatives to find more answers about complex systems. Differences in gene expression correlation across treatments and lines helped to understand changes in connectivity associated with the factors studied.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Animal Sciences

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2018

Author dc:creator

• Mangetti Goncalves, Tassia

Contributors dc:contributor

• Rodriguez-Zas, Sandra
• Caetano-Anollés, Gustavo
• Villamil, Maria Bonita
• Gonzalez-Pena, Dianelys

• transcriptome
• networks

Statement dc:rights

• Copyright 2018 Tassia Mangetti Goncalves

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/101266

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/101266