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Early mortality: a major breeding issue in pig farming
Background
Pig sector is an important economic motor of the livestock industry in France. In 2016, around 8.9% (24.3 million pigs) of the global production in the European Union (EU) was obtained in France (data obtained from the National Establishment of Agricultural and Sea products, FranceAgriMer, 2017). This makes the French swine sector into the third producer in EU after Germany and Spain. Actually, pork is the most consumed meat in France, before poultry and cattle, which makes France the fourth consumer (FranceAgriMer, 2017). To ensure this demand of meat, farmers have had to find strategies in order to increase their production.
Selection towards prolificacy
Beyond the breeding conditions (feeding, bedding, health, etc.), genetics and breed selection programs are among the most important aspects handled by farmers to increase their production. In this context, cross-breeding plans are used to combine different genotypes and select the best animals regarding genealogy, reproductive performance, growth, carcass type, and meat quality. For instance, pig males have been selected to improve feed conversion efficiency and carcass quality criteria, and sows from Large White (LW) line have been prolificness-enhanced to increase the number of live-born piglets per litter.
The selection towards increasing the prolificacy and meet production, has been unfortunately associated to an increment of perinatal mortality. Figure 1 shows data collected from the French Porc and Pig Institute (IFIP). A shift is observed between the years 1975 and 2015, with an increase in: (i) progeny (4.1 more piglets per litter), (ii) premature mortality (0.6 more still-born per litter) and (iii) postnatal mortality (1.5 of piglets died before reaching the weaning age in 1975 while 1.9 perished before weaning in 2015). The last, presenting the highest rate around the first 48-72 hours (corresponding to the perinatal mortality). In brief, the incidence of mortality has considerably raised in the last forty years, especially during the last fifteen years because of the application of novel selection practices for genetic improvement. This early mortality generates not only important economic losses (10-20% of total operating costs) for the swine industry but also raises ethical questions about animal welfare.
Early mortality is not a phenomenon restricted to the swine industry, other species in the agronomic sector suffer from the same losses. In the sheep industry, the mortality rate before the sixtieth day after birth is 13.6% and, before 48 hours of lambs’ life, mortality represents more than 50% (data obtained from the Sheep Breeding Institute, Idele, 2016). Although less pronounced than in the pig and sheep sectors, the proportion of perinatal mortality in the cattle industry is 5.2% (Perrin et al., 2011).
To finish with this overview of perinatal mortality, I would like to underline that humans are unfortunately not exempt from this problem, despite all the advances in medicine in the last years. In 2016, 5.6 million deaths were registered in children under five years old. Neonatal deaths (the first 28 days of life) accounted for 46% of all under-five deaths. Although the majority of them were attributable to neonatal infections, intrapartum-related events and congenital abnormalities, almost 35% of the neonatal mortality was due to preterm birth complications (data obtained from UNICEF, “Levels and Trends in Child Mortality Report 2017”), the last, especially regarding immaturity problems of newborns (hypothermia, hypoglycemia, respiratory distress, etc.).
Critical factors of piglets mortality
Many factors are responsible of pig losses, the most commons, the ones affecting the perinatal period and involved in stillbirths (prenatal stage), and deaths during the first 72 hours after birth (neonatal stage). Fetal losses can be explained by maternal effects (uterus anatomy, placenta development, and number of embryos). Neonatal deaths happening during farrowing can also be explained by maternal effects (farrowing issues, intrauterine hypoxia and hyperthermia caused by acidosis). Those happening in early breastfeeding can be due to maternal effects, breeding conditions or effects specific to the piglets. The piglet’s weakness (malnutrition by low-quality colostrum and/or milk production from the sow) and maternal crushing are the most common causes of pre-weaned mortality. Other factors are important for piglet survival like the maternal skills/abilities (resource management (relationship with its appetite and body condition), its dairy milk production, the farrowing efficiency, the weight and size of the piglets and the maternal behavior). And last, but not less important, the vitality of the piglet defined as the piglet characteristics that will influence its survival and growth during the breastfeeding stage (Canario, 2006). This thesis is focused on this last item which is developed in the coming section.
Maturity and survival
Critical factors for piglets survival
Some studies have been performed to investigate and understand which conditions during pig fetal development alter the genetic merit for piglet survival. It has been observed that postnatal performance in pigs is mainly affected by the placental development, the size and weight of fetuses, and the levels of cortisone and glycogen. For instance, litters with high estimated breeding values for piglet survival present smaller and more regular placenta, smaller fetuses, higher cortisol concentrations, higher concentrations of glycogen in liver and skeletal muscle (longissimus dorsi) and higher percentages of carcass fat (Leenhouwers et al., 2002a). Similarly, intrauterine growth retardation (IUGR) have been associated with variation in birth weight within litters, pre-weaning survival and postnatal growth. Actually, IUGR is often produced due to high ovulation leading to high fetuses surviving to 30 days gestation. This is in detriment of a proper placenta development, especially limiting the availability of nutrients to the embryo during myogenesis (Foxcroft et al., 2006). These aspects support the idea that by selecting hyperprolific females to increase the number of pigs born, piglet survival is strongly impacted. Therefore, this strategy of selection should be critically evaluated in the context of pork production, as well as selection should be optimized to obtain slightly smaller but stronger piglets in terms of piglet survival.
Piglet’s maturity
The ability of piglets to cope with hazards during birth or within the first days of life is closely linked to the fetal physiological maturity (van der Lende et al., 2001). A state of full development, due to a successful maturation process, promotes early survival after birth (Leenhouwers et al., 2002b, 2002a). Concretely, the maturity is described by the weight of birth, the body composition, the levels of metabolites, the ability to thermoregulate, the immune response and behavioral aspects (Canario, 2006; Foxcroft et al., 2006; Leenhouwers et al., 2002a). The fetal maturation process in pigs involves biological processes occurring between the 90th day and the term of gestation (around the 114th day) (Leenhouwers et al., 2002a). During this period, the most important events happening over the maturation process are the ones described in the previous section: an increase of plasma cortisol, the glycogen accumulation in muscle and liver and the maturation of tissues (Figure 2, (Voillet, 2016)).
Experimental results have also shown that breed-specific mechanisms could influence the physiological processes at the end of development and during the maturation process. Indeed, there are examples of breeds having different performances for piglet survival. For instance, the survival rate differs between the LW European breed and the Meishan (MS), a Chinese domestic breed. The LW breed which has been highly selected, presents a high incidence of mortality, while the primitive breed MS exhibits a strong potential for survival (Herpin et al., 1993). This disparity between extreme breeds in terms of maturity can be explained by breed-specific particularities happening during the muscle development and maturation, due to the fact that a proper functioning of this tissue is essential for piglet postnatal performance as mentioned before. The role of muscle maturity in survival at birth will be discussed in the following section, by focusing attention on the skeletal muscle.
The role of muscle maturity in survival at birth
There are three types of muscle in vertebrates, the skeletal muscle (“voluntary muscle” responsible of the skeletal movement), the smooth muscle (“involuntary muscle”, in organs, blood vessels, skin, etc.) and the cardiac muscle (also “involuntary” but more similar in structure to the skeletal muscle). In this thesis, the interest is focused on the skeletal muscle, concretely on the longuissimus dorsi which is located in the trunk and it extends from the thoracic region to the sacrolumbar.
Myogenesis: the fetal skeletal muscle development
Skeletal muscle in the trunk of vertebrate embryo derives from the somites, segments of the paraxial mesoderm germ layer which is formed in the primitive blastopore during gastrulation (Figure 3). Somites are located at both sides of the neural tube and notocorde, and they are composed by three structures: the sclerotome (ventral compartment that originates vertebrae, ribs and cartilage), the myotome (middle layer originated from the dermomyotome, gives rise to skeletal striated muscles), and the dermomyotome (dorsal compartment originates dermis and hypodermis). After demomyotome formation, myogenesis is initiated by delamination of cells from the inward-curled borders (lips) of the dermomyotome. These detached cells move under the dermomyotome to generate the primary myotome and rapidly differentiate into skeletal muscle of the myotome. The dorsomedial portion of the myotome gives rise to the intrinsic back muscles (Buckingham, 2006; Chal and Pourquié, 2017; Yusuf and Brand-Saberi, 2012).
Cells in the dermomyotome express the Pax3 and Pax7 transcription factors, they are myogenic proliferating precursors in somites and do not express myogenic regulatory factors (MRFs) or muscle proteins (Figure 4). This is the so-called proliferation step. The determination step happens during the myotome formation, when myogenic precursors retreat from the cell-cycle. Then, these cells start to express Myf5 (myogenic factor 5), MyoD (MyoD1, myogenic determination factor), MRF4 (Myf6, myogenic factor 6) and to downregulate Pax3 (Paired box 3), becoming committed myoblasts (Buckingham, 2006; Chal and Pourquié, 2017; Yusuf and Brand-Saberi, 2012). In early development, myoblasts can either proliferate or differentiate. The differentiation step begins when myoblasts start expressing myogenin (Myf4/MYOG), MyoD and MRF4 (Buckingham, 2006). At this stage, the differentiating myoblasts are often named myocytes, which express specialized cytoskeletal proteins: Myh7 and Myh3 myosin heavy chains (MyHC), α-actine (Actc1), desmin, the Notch ligand jagged 2 and metabolic enzymes. Myocytes elongate and align to span the entire somite length and this process is controlled by Wnt11 signaling. Then they fuse leading to the formation of multinucleated myotubes which latter mature into myofibers. Myogenesis separated into two phases: an early embryonic or primary phase and a latter fetal or secondary phase. The first one results in the formation of primary myofibers (muscle cell polynucleated) (expressing slow MyHC and myosine light chain 1, MyLC1). During the second phase, myogenic precursors fuse among themselves or to the primary fibers and give rise to secondary myofibers expressing β-enolase, Nfix or MyLC3. Then these fibers also start to express fast MyHC isoforms (Chal and Pourquié, 2017).
Myofibers are filled of myofibrils which are bundles of protein filaments and responsible of muscle contraction. The process of myofibrils formation is called myofibrillogenesis. Myofibrils are composed of a repetitive contractile modules called sarcomeres and they are surrounded by the sarcolemma, a specialized plasma membrane for neural signal transduction by depolarization upon neural excitation. The filaments in a sarcomere are composed of actin and myosin (Chal and Pourquié, 2017).
It exists three main types of myofibers classified depending on their MyHC isoforms and metabolism. These are the slow-twitch oxidative (oxidative metabolism), the fast-twith oxydative (oxido-glycolytic meatabolism) and the fast-twitch glycolytic (glycolitic metabolism) fibers (Picard et al., 2002). There are eight isoforms of MyHC: four adult (I, IIa, IIx and IIb), 3 developmental (embryonic, fetal and α-cardiac), and one extraocular isoform (Perruchot et al., 2012). Oxidative slow-twitch fibers express slow MyHC (type I, Myh7), whereas glycolytic fast-twitch fibers express fast MyHC (types IIa (Myh2), IIb (Myh4) and IIx (Myh1)). Being the embryonic (Myh3) and slow MyHC the first to be expressed in early myogenesis phase, then fetal and neonatal fibers express perinatal MyHC (Myh8), finally the fast isoforms start to be expressed during late fetal myogenesis (Chal and Pourquié, 2017).
To finish with this section, hereafter a brief introduction about the adult muscle stem cells. They are the so-called satellite cells and are located between the basal lamina and the sarcolemma of each myofiber. They origined during embryogenesis from myogenic progenitors of the central dermomyotome expressing Pax7. The Pax7 progenitors pool is maintained by the Notch signaling. Satellite cells have a limited ability to replicate and will remain as quiescent Pax7+ satellite cells in adult muscle. They are required for skeletal muscle regeneration, growth and maintenance through adulhood (Chal and Pourquié, 2017) (see (Crist et al., 2012) for more details).
Peculiarities of pig skeletal myogenesis and muscle metabolism
In pigs, and more generally in livestock animals, muscle fiber characteristics and ontogenesis influence the quality of meat. As discussed before, during myogenesis, two succesive waves of myoblasts are responsible of the myofiber ontogenesis and will lead to the formation of primary and secondary myofibers. In larger species as bovines, sheeps, pigs, but also in humans, it exists a third generation of myofibers (Picard et al., 2002; Rehfeldt et al., 2000). These tertiary myofibers appear during fetal life except for pigs, in which the third generation appears during the early postnatal period. Therefore, in the pig gestational timeline, the first wave of myoblast generation arrives around the 35th day of fetal life, the second around the 55thday, and the third between birth and the first 15thdays after birth (Picard et al., 2002). The total number of muscle fibers (TNF) and the myofibers size are important parameters playing a key role in meat quality and they have been influenced by lean meat growth selection (Rehfeldt et al., 2000). In pigs, the TNF is fixed around the 90th day of gestation suggesting that the third generation of fibers (postnatal) is not quantitatively important. Primary and secondary fibers are under genetic and epigenetic (environmental) control respectively. The genetic aspect is explained by differences between breeds and the epigenetic one is mainly explained by maternal effects (maternal nutrition and offspring) (Picard et al., 2002; Rehfeldt et al., 2000). Regarding the maternal effects, intrauterin growth retardation has been observed in some fetuses of hyperprolific sows presenting high rates of conceptuses surviving to 30 days of gestation, resulting in detrimental effects of placental development. This limites the availability of nutrients to the embryo during the myogenesis and is translated into a decrease of the number of muscle fibers at 90 days of gestation (Foxcroft et al., 2006). Muscle mass is determinated not only by the TNF but also by the size of those fibers. Increases in muscle mass due to the fiber size are subjected to the prenatal and postnatal fiber hypertrophy (Figure 5). The hypertrophy depends on the accumulation of myonuclei (satellite cell proliferation) and muscle specific proteins.
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.
