Functional genomic analysis to understand neuronal stress and behaviors

목차 (Table of Contents)

• 1. Introduction 1
• 1.1 Importance of functional genomics integrated with neurobiology 1
• 1.2 Age dependent iron accumulation in brain induce neurodegenerative disease 3
• 1.2.1 Iron is essential elements in human body 3
• 1.2.2 Iron metabolism 4
• 1.2.2.1 Iron uptake metabolism 4
• 1.2.2.2 Iron storage and export metabolism 4
• 1.2.2.3 Iron metabolism regulation 4
• 1.2.2.4 Iron metabolism in brain 5
• 1.2.3 Iron metabolism in aging 6
• 1.2.4 Iron and neurodegenerative disease 7
• 1.2.4.1 Parkinson’s disease 7
• 1.2.4.2 Alzheimer’s disease 7
• 1.3 Behavior analysis in social isolation and early-life experience 8
• 1.3.1 Social behavior analysis in human 8
• 1.3.2 Impact of social isolation 9
• 1.3.2.1 Acute isolation 9
• 1.3.2.2 Chronic isolation 9
• 1.3.3 Early life experience in behavior 10
• 1.3.3.1 Early life deprivation experience 10
• 1.3.3.2 Early life threat experience 10
• 1.3.3.3 Early life isolation experience 10
• 1.4 Research synopsis 11
• 2. Integrative Analyses of Magnetic Resonance Imaging (MRI) and The Substantia nigra
• Transcriptome Following Age-related Iron Accumulation-induced Cellular Stress 12
• 2.1 Introduction 12
• 2.2 Methods 14
• 2.2.1 RNA sequencing of rat SN 14
• 2.2.2 Cell culture 14
• 2.2.3 Iron-treated SH-SY5Y transcriptome analysis 14
• 1.2.5 RNA sequencing data analysis 15
• 1.2.6 Functional pathway analysis 15
• 1.2.7 Iron stress related genes identification 15
• 1.2.8 Validation of iron stress related genes 15
• 2.3 Results 17
• 2.3.1 Transcriptome profile analysis uncovers significant alteration in gene expression in the midbrain of aged rats 17
• 2.3.2. Genes related to ER stress due to incorrect protein folding exhibit active expression in response to excessive iron accumulation in vitro 23
• 2.3.3 HERPUD1 and CLU act as protective factors in the SN against age-dependent iron-overload toxicity. 30
• 2.4 Discussion 34
• 3. Drosulfakinin Signaling Encodes Early-life Experience that Contribute to Adaptable Social Flexibility and Serotonergic Neuron Proportions 38
• 3.1 Introduction 38
• 3.2 Methods 40
• 3.2.1 Quantification of fly social behaviors 40
• 3.2.2 RNA sequencing 40
• 3.2.3 RNA sequencing data analysis 40
• 3.2.4 Cell-type deconvolution of adult fly head samples 41
• 3.3 Results 42
• 3.3.1 Quantitative behavior analysis of natural Drosophila population 42
• 3.3.2 The capacity of social plasticity is obtained through early life social experiences .. 47
• 3.3.3 Unraveling genetic background contributing to social interaction behaviors 49
• 3.3.4 The neuronal population differences by early-life social experiences were identified 55
• 3.4 Discussion 57
• 4. Conclusion 59