Epistatic effects on carcass composition and meat quality in pigs

The analysis of epistasis is not yet a routine, but it has been shown by few studies in livestock animals that interaction effects contribute with considerable proportions to the phenotypic variance. Therefore the objective of this study was to evaluate the importance of epistatic effects in the Bonn Duroc × Pietrain resource population (DuPi) for carcass composition and meat quality traits. This population was investigated so far for single quantitative trait loci (QTL) considering additive, dominance and imprinting effects. In the first approach, 585 F2 pigs of DuPi were used to perform a two dimensional QTL scan. All animals were genotyped using 125 genetic markers (microsatellites and SNP) spread across the 18 pig autosomes. Phenotypic information for 26 carcass composition and meat quality traits was available for all F2 animals. Linkage analysis was performed in a two-step procedure using a maximum likelihood approach implemented in the QxPak program. A number of 56 interacting QTL was observed for 19 different traits. These interacting QTL pairs explained up to 8% of the phenotypic variance. Based on these results a variety of networks among chromosomal regions throughout the porcine genome were identified. Moreover, considering interactions between loci allowed to detect several novel QTL and trait-specific relationships of loci within and across chromosomes. In a second step the causes of an epistatic QTL pair between Sus scrofa chomsosome (SSC) 8 and 15 influencing pH value 1 h post mortem in M. long. dorsi were investigated. Gene expression data was obtained from loin tissue of 74 F2 which were selected from 585 animals. Gene expression profiles, genotypes and phenotypes of these pigs were investigated jointly applying three alternative models. Method A considered the phenotypic differences in pH values between groups of pigs with extreme values. Method B was based on differences between the genotype combinations of relevant epistatic QTL pairs between SSC8 and SSC15. Finally, method C was a linear model comprising the epistatic QTL genotypes as fixed effects. Overall method A, B and C revealed 1182, 480 and 1823 differentially expressed or associated genes, respectively. By means of a functional analysis it was possible to set up networks which contained mainly interactions between genes located within the specific regions on SSC8 and SSC15 and allowed a meaningful biological discussion. Expression QTL (eQTL) analyses were performed for functional and positional transcripts in order to assume regulations patterns. This approach showed that combining phenotype, genotype and transcriptome data helped to uncover the involved molecules of observed epistasis. In conclusion, this study revealed the importance of epistasis for the expression of complex traits. Furthermore, it was possible to uncover potential biological causes of observed epistatic QTL pairs applying different statistical models as well as bioinformatic tools.Epistatische Effekte auf die Schlachtkörperzusammensetzung und Fleischqualität beim Schwein Epistasie wird bisher nur selten in Untersuchungen komplexer Merkmale berücksichtigt. Dabei wurde bereits in einer Vielzahl von Studien gezeigt, dass die zu beobachtenden Variationen von quantitativen Merkmalen nicht alleine durch additive Effekte erklärt werden können. Daher war das Ziel dieser Studie, die Bedeutung von epistatischen Effekten auf Schlachtkörper- und Fleischqualitätsmerkmale innerhalb der Bonner Duroc × Piétain Ressourcenpopulation (DuPi) zu untersuchen. Bisherige Studien in der DuPi Population berücksichtigten nur einfache Quantitative Trait Loci (QTL), die additive, Dominanz oder Imprintingeffekte beinhalteten. In der ersten Analyse wurden 585 Schweine der F2-Generation verwendet um epistatische QTL Paare zu identifizieren. Diese Tiere sind mit 125 genetischen Markern genotypisiert worden, die sich gleichmäßig über alle 18 Autosomen verteilten. Als phänotypische Informationen wurden 26 verschiedene Schlachtkörper- und Fleischqualitätsmerkmale erfasst. Die Koppelungsanalyse wurde in einer zweistufigen Prozedur innerhalb des Programms Qxpak, basierend auf einem Maximum Likelihood Ansatzes, durchgeführt. Insgesamt konnten 56 interagierende QTL für 19 verschiedene Merkmale beobachtet werden. Für Schlachtkörpermerkmale konnten 17 und für Fleischqualitätsmerkmale 39 epistatische QTL Paare identifiziert werden. Diese interagierenden QTL Paare erklärten bis zu 8% der phänotypischen Varianz. Auf Grundlage dieser Ergebnisse konnten verschiedene Netzwerkstrukturen zwischen den verschiedenen Chromosomensegmenten identifiziert werden. Die Berücksichtigung der Beziehung zwischen zwei Genorten ermöglichte es einige neue QTL zu identifizieren, sowie merkmalsbezogene Beziehungen innerhalb eines Chromosoms und zwischen Chromosomen zu charakterisieren. In einer zweiten Untersuchung wurde versucht, die biologischen Gründe des epistatischen QTL Paares zwischen den porcinen Chromosomen (SSC) 8 und 15 aufzuklären. Für die Analyse standen die Muskeltranskriptionsprofile von 74 ausgewählten F2 Tieren der DuPi Population zur Verfügung. Die Interaktion zwischen SSC8 und 15 war assoziiert mit früh post mortalem pH Wert im M. long. dorsi. Genexpressionsprofile, Genotypen und Phänotypen dieser Tiere wurden mit drei verschiedenen statistischen Ansätzen und Modellen untersucht. Methode A berücksichtigte phänotypische Unterschiede des pH Wertes zwischen zwei Tiergruppen mit extremen Werten, Methode B basierte auf den Unterschieden zwischen den Genotypgruppen des relevanten epistatischen QTL Paares und Methode C berücksichtigte die Genotypen des epistatischen QTL Paares als fixen Effekt innerhalb eines linearen Modells. Insgesamt ließen sich mit Methode A, B und C 1182 und 480 unterschiedlich exprimierte Gene sowie 1823 linear assoziierte Gene identifizieren. Durch funktionale Analysen war es möglich Netzwerke zu erstellen, die nur Gene beinhalteten, die innerhalb der epistatischen Regionen lagen. Die daraus erzielten Ergebnisse erlaubten eine biologisch sinnvolle Diskussion möglicher Kandidatengene der epistatischen Regionen. Des Weiteren wurden Expressions-QTL Analysen durchgeführt um eine Aussage über die Genregulation zu treffen. Schlussfolgernd konnte gezeigt werden, dass Epistasie eine bedeutende Rolle bei der Ausprägung von komplexen Merkmalen beim Schwein hat. Es war des Weiteren möglich biologische Ursachen beobachteter epistatischer Beziehungen mit Hilfe verschiedener statistischer Methoden zu identifizieren

Heppenheimer Tage

Bericht zu den 7. Heppenheimer Tagenzur christlichen Gesellschaftsethi

Deciphering transcriptome profiles of peripheral blood mononuclear cells in response to PRRSV vaccination in pigs

List of DEGs in PBMCs of pigs at 6 hpv of PRRSV vaccination in pigs compared to control. (XLSX 57 kb

Transcriptome profile of lung dendritic cells after in vitro porcine reproductive and respiratory syndrome virus (PRRSV) infection

The porcine reproductive and respiratory syndrome (PRRS) is an infectious disease that leads to high financial and production losses in the global swine industry. The pathogenesis of this disease is dependent on a multitude of factors, and its control remains problematic. The immune system generally defends against infectious diseases, especially dendritic cells (DCs), which play a crucial role in the activation of the immune response after viral infections. However, the understanding of the immune response and the genetic impact on the immune response to PRRS virus (PRRSV) remains incomplete. In light of this, we investigated the regulation of the host immune response to PRRSV in porcine lung DCs using RNA-sequencing (RNA-Seq). Lung DCs from two different pig breeds (Pietrain and Duroc) were collected before (0 hours) and during various periods of infection (3, 6, 9, 12, and 24 hours post infection (hpi)). RNA-Seq analysis revealed a total of 20,396 predicted porcine genes, which included breed-specific differentially expressed immune genes. Pietrain and Duroc infected lung DCs showed opposite gene expression courses during the first time points post infection. Duroc lung DCs reacted more strongly and distinctly than Pietrain lung DCs during these periods (3, 6, 9, 12 hpi). Additionally, cluster analysis revealed time-dependent co-expressed groups of genes that were involved in immune-relevant pathways. Key clusters and pathways were identified, which help to explain the biological and functional background of lung DCs post PRRSV infection and suggest IL-1β1 as an important candidate gene. RNA-Seq was also used to characterize the viral replication of PRRSV for each breed. PRRSV was able to infect and to replicate differently in lung DCs between the two mentioned breeds. These results could be useful in investigations on immunity traits in pig breeding and enhancing the health of pigs

Loneliness and social media: A qualitative investigation of young people's motivations for use and perceptions of social networking sites

The democratisation of Internet access has incrementally changed every domain of activity and has created new business and economic models. From answering work emails to learning a new language, shopping, booking medical appointments or managing one’s finances, almost everything is attainable at the click of a button. The added implications of the rapid rise of social networking websites (SNSs), such as Facebook, Twitter, Instagram or Snapchat, have further contributed to changing the way we communicate and build new friendships. Indeed most of our social relationships are now being ‘increasingly developed and maintained online’ (Nowland, Necka & Cacioppo, 2017: 1). Ostensibly, despite improved Internet access and enhanced social connectedness, modern societies are struggling to combat loneliness. It is reported to affect people of all ages, especially young adults (16-24 and 25-34 years old) who are avid Internet and social media users (see Office for National Statistics, 2018)

Livestock 2.0 – genome editing for fitter, healthier, and more productive farmed animals

Abstract The human population is growing, and as a result we need to produce more food whilst reducing the impact of farming on the environment. Selective breeding and genomic selection have had a transformational impact on livestock productivity, and now transgenic and genome-editing technologies offer exciting opportunities for the production of fitter, healthier and more-productive livestock. Here, we review recent progress in the application of genome editing to farmed animal species and discuss the potential impact on our ability to produce food

Centrality evolution of the charged-particle pseudorapidity density over a broad pseudorapidity range in Pb-Pb collisions at root s(NN)=2.76TeV

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