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Table of contents
1 Abstract
2 General introduction
3 Bibliographic review
3.1 Chapter 1. Breeding context
3.1.1 Early mortality: a major breeding issue in pig farming
3.1.1.1 Background
3.1.1.2 Selection towards prolificacy
3.1.1.3 Critical factors of piglets mortality
3.1.2 Maturity and survival
3.1.2.1 Critical factors for piglets survival
3.1.2.2 Piglet’s maturity
3.1.3 The role of muscle maturity in survival at birth
3.1.3.1 Myogenesis: the fetal skeletal muscle development
3.1.3.2 Peculiarities of pig skeletal myogenesis and muscle metabolism
3.1.3.3 Muscle and maturity
3.2 Chapter 2. Muscle transcriptome studies
3.2.1 Functional Annotation of porcine genome
3.2.1.1 Main efforts in pig genome sequencing and annotation
3.2.2 Transcriptome technologies and approaches
3.2.2.1 DNA microarray and RNA-seq
3.2.2.2 Co-expression networks
3.2.3 Muscle transcriptome studies in pigs
3.3 Chapter 3. Nuclear architecture
3.3.1 Higher order genome organization
3.3.1.1 Generalities
3.3.1.2 Chromosome territories
3.3.1.3 NPCs, LADs, NADs, TFs and PcG domains
3.3.1.4 A and B compartments
3.3.1.5 Topologically associated domains
3.3.2 Chromatin loops and gene-gene interactions
3.3.2.1 CTCF and cohesin functions
3.3.2.2 Insulated neighborhoods (CTCF/cohesin-mediated loops)
3.3.2.3 Gene-gene interactions
3.3.3 Dynamic organization of the genome
3.3.4 Single cell genome organization
3.3.5 3D genome architecture and disease
3.3.6 3D genome architecture approaches
3.3.6.1 Population-based methods (3C, 4C, 5C, Capture-C, Hi-C, ChIA-PET)
3.3.6.2 Single-cell methods (single-cell Hi-C, 3D DNA and RNA-FISH)
3.3.6.3 Comparison between FISH and 3C-based methods
3.3.7 3D Pig genome organization
3.3.7.1 Assessed by 3D DNA FISH
3.3.7.2 Assessed by population-based methods
3.4 Chapter 4: Objective and strategy of this thesis
3.4.1 Combining 3D DNA FISH and gene expression for network inference
3.4.2 Global genome organization assessed by Hi-C and gene expression analysis
4 Materials and methods
4.1 Ethics statement
4.2.1 Transcriptome data
4.2.1.1 Microarray data description
4.2.1.2 Microarray data pre-processing
4.2.2 Network inference and analysis
4.2.2.1 Network inference
4.2.2.2 Practical implementation of network inference
4.2.2.3 Network inference interactions and 3D FISH validations
4.2.2.4 Network mining and clustering
4.2.3 Functional analysis of the networks
4.2.3.1 Gene Ontology (Webgestalt)
4.2.3.2 Ingenuity Pathway Analysis
4.2.4 Gene-gene nuclear associations
4.2.4.1 3D DNA FISH in interphase nuclei
4.2.4.2 Confocal microscopy and image analysis
4.3 Nuclear architecture and gene expression approach
4.3.1 Transcriptome data
4.3.1.1 Microarray data description
4.3.1.2 Microarray probes alignment and annotation
4.3.2 High-throughput chromosome conformation capture (Hi-C)
4.3.2.1 Hi-C experiments
4.3.2.2 Quality control of Hi-C experiment
4.3.2.3 Hi-C libraries production and sequencing
4.3.2.4 Hi-C data processing
4.3.3 Chromatin Immunoprecipitation sequencing (ChIP-seq)
4.3.3.1 ChIP-seq experiments
4.3.3.2 ChIP-seq libraries production and sequencing
4.3.3.3 ChIP-seq data analyses
4.3.4 Differential analyses
4.3.5 Gene ontology (GO) analysis
4.3.6 Integrative analysis with expression data
5 Combining 3D DNA FISH and gene expression for network inference
5.1 Results
5.1.1 Network inference iteration and 3D FISH validations
5.1.2 Network mining (network structure with key genes)
5.1.3 Network clustering
5.1.4 Functional enrichment analysis
5.2 Discussion
6 Global genome organization assessed by Hi-C and gene expression
6.1 Results
6.1.1 Descriptive analysis of genome global organization in fetal muscle by Hi-C
6.1.1.1 Read statistics
6.1.1.2 Construction of genome-wide contact maps
6.1.1.3 Hi-C intra-matrices normalization
6.1.2 Identification of higher order chromosomal structures
6.1.2.1 A and B compartments
6.1.2.2 Topologically associated domains (TADs)
6.1.3 Differential analysis of the genome organization
6.1.3.1 Global differences in the 3D genome organization of fetal muscle between 90 and 110 days of gestation
6.1.3.2 Differential genome regions in late fetal muscle development
6.1.3.3 Functional analysis of differential bin pairs
6.1.4 Gene expression and nuclear organization
6.1.4.1 Gene expression in A and B compartments
6.1.4.2 Gene expression in A/B switching compartments
6.1.4.3 Gene expression in differentially located genomic regions
6.2 Discussion
6.2.1 First insights in porcine muscle genome architecture at late gestation
6.2.2 Adaptation of the in situ Hi-C protocol to porcine fetal muscle
6.2.3 High resolution porcine genome maps
6.2.4 Main features of 3D genome folding in fetal muscle
6.2.5 Major changes on chromatin conformation at late gestation
6.2.5.1 Switching compartments
6.2.5.2 Dynamic interacting regions
6.2.5.3 Differentially distal adjacent regions
6.2.5.4 Inter-chromosomal telomeres clustering
6.2.6 Genome organization and gene expression
7 General conclusion
8 Perspectives
9 References
10 Appendix. Supplementary data
