Transcriptomics and proteomics analysis to identify molecular mechanisms associated with meat quality traits

Boar taint and water holding capacity (WHC) are important quality criteria in pig production and affect the financial output, the nutritional composition as well as the consumer appeal of pork. Both, boar taint and WHC are measured by several traits which can be characterized by complex genetic architecture and molecular mechanisms. Thus, the analysis of the transcriptome and proteome using high-throughput technologies are necessary to elucidate the molecular mechanisms and to identify biomarkers with the potential to be developed as markers that can be monitored in such traits. The aim of this study was therefore to provide a transcriptome and proteome analysis in liver and muscle samples from crossbred animals with as well different androstenone and skatole levels and high and low drip loss. In the first study, microarray analysis using the porcine Affymetrix gene chip in liver tissues from 10 boars of a Pietrain F2 crossbred with high and low androstenone, high and low skatole levels and grouping of combined phenotypes revealed 264 differentially expressed genes (DEGs). Only two genes could be identified in liver between high and low androstenone group, whereas 92 DEGs (p ≤ 0.05) between high and low skatole group were identified. Out of these genes, 49 were up - and 43 downregulated in samples with high skatole level. In addition, when a combined phenotype of androstenone and skatole was analyzed, 170 DEGs were identified of which 86 showed an increased and 84 a decreased level of expression. The differentially expressed genes were mainly assigned in metabolic processes, oxidative reductase activity and lipid metabolism. In summary, this study could be obtained an insight into the biology of complex characteristic. The high number of genes identified by comparing groups of combined phenotypes suggests a strong relationship between androstenone and skatole and should be considered in future investigation. In the second study samples of musculus longissimus dorsi with high and low drip loss from a Duroc × Pietrain (DuPi) F2 resource population (n = 42) was used. The relative protein quantification was done using isotope-coded protein labeling techniques (ICPL) and electrospray ionization liquidchromatography- tandem mass spectrometry (LC-MS/MS). In total, 763 different proteins were identified. Among these different proteins, PYGL, PYGM, HSPA8, EE1A1, ACTA1, CASQ1, FLN-C, MYOM1, TNNT3, and HSP27 were up-regulated and TNNI1, MYL3, MYL2, MB, MYBPC1, FHL1C, TPM1, TPM2, AK1, TNNC2, MYL11, CK, PGK1 and MYH7 down-regulated in animals with low drip loss compared to animals with high drip loss. Results revealed that with high drip loss meat was characterized by a higher level of glycolytic enzymes than in low drip loss meat. Additionally, we could observe that higher levels of chaperone proteins were associated with a low drip loss level. In conclusion, proteomics studies contribute to understand the underlying metabolisms of different meat quality traits. In further steps combining genomics, proteomics and metabolomics data should enable a holistic view of the relevant biological systems.Transcriptomics und Proteomics-Analyse zur Identifizierung molekularer Mechanismen von Fleischqualitätsmerkmalen Ebergeruch und Wasserbindungsvermögen sind wichtige Qualitätskriterien des Schweinefleisches und beeinflussen sowohl den finanziellen Output, die Nährwertzusammensetzung als auch die Attraktivität für den Verbraucher von Schweinefleisch. Beide Merkmale werden von einer Vielzahl an Genen beeinflusst weshalb man von einer komplexen Vererbung mit komplexen molekularen Mechanismen ausgehen kann. Die Analysen des Transkriptoms und Proteoms mittels High-Throughput- Technologien sind daher von Nutzen für die Aufklärung dieser Mechanismen, um im Anschluss geeignete Biomarker entwickeln zu können. Das Ziel dieser Studie war es, eine Transkriptom und Proteom Untersuchung in Leber- und Muskelproben von Kreuzungstieren mit sowohl unterschiedlichen Androstenon- und Skatolgehalten sowie mit hohem und niedrigem Tropfsaftverlust durchzuführen. Im ersten Experiment konnten mittels des porcinen Affymetrix Genchip in Leberproben von jeweils 10 Ebern mit hohem/niedrigem Androstenon/Skatol Gehalt einer Pietrain F2 Kreuzung 264 unterschiedlich exprimierte Gene aufgedeckt werden. Nur zwei Gene konnten im Vergleich der Gruppe hohem mit niedrigem Androstenongehalt identifiziert werden, während 92 Gene beim Vergleich zwischen hohem und niedrigem Skatolgehalt ein unterschiedliches (p = 0.05) Expressionsniveau aufwiesen. Von diesen waren 49 Gene hoch- und 43 runter reguliert in Proben mit hohem Skatolgehalt. Darüber hinaus wurden bei der Untersuchung eines kombinierten Androstenon/Skatolphänotyps 170 unterschiedlich regulierte Gene identifiziert, wovon 86 ein erhöhtes und 84 ein niedrigeres Expressionsniveau zeigten. Die unterschiedlich exprimierten Gene konnten überwiegend Stoffwechselprozessen, oxidativer und reduktiver Aktivitäten und dem Lipidmetabolismus zugewiesen werden. Zusammenfassend konnte mit dieser Studie ein Einblick in die Biologie des komplexen Merkmales gewonnen werden. Die hohe Anzahl der identifizierten Gene beim Vergleich des kombinierten Phänotypes lässt auf eine starke Beziehung zwischen Androstenon und Skatol schließen und sollte in zukünftigen Untersuchen berücksichtigt werden. In der zweiten Studie wurden Proben vom musculus longissimus dorsi einer Duroc × Pietrain (DuPi) F2 Kreuzungspopulation (n = 42) mit hohem und niedrigem Tropfsaftverlust verwendet. Die relative Quantifizierung von Proteinen erfolgte mittels Isotope coded proteine labeling (ICPL) und Elektrospray Ionisation Flüssigchromatographie/Tandem-Massenspektrometrie (LC-MS/MS). Insgesamt wurden 763 Proteine identifiziert. Von diesen Proteinen, waren PYGL, PYGM, HSPA8, EE1A1, ACTA1, CASQ1, FLN -C, MYOM1, TNNT3 und HSP27 hoch und TNNI1, MYL3, MYL2, MB, MYBPC1, FHL1C, TPM1, TPM2, AK1, TNNC2, MYL11, CK, PGK1 und MYH7 herunter reguliert bei Tieren mit niedrigem Tropfsaftverlust im Vergleich zu Tieren mit hoher Tropfsaftverlust. Die Ergebnisse zeigten, dass ein erhöhter Tropfsaftverlust im Fleisch durch eine höhere Regulation von glykolytischen Enzymen gekennzeichnet war. Zusätzlich konnte festgestellt werden, dass eine höhere Regulation von Chaperon-Proteinen mit einem niedrigen Tropfverlust verbunden war. Proteomics Untersuchungen sind bei komplexen Merkmalen notwendig um die zugrunde liegenden Stoffwechselvorgänge besser verstehen zu können. In weiteren Schritten sollte die Kombination von genomischen, proteomischen und metabolomischen Daten eine ganzheitliche Sicht auf die relevanten biologischen Systeme ermöglichen

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

Molecular genetic analysis of boar taint

Boar taint is an unpleasant smell and taste of pork meat derived from some entire male pigs. The main causes of boar taint are the two compounds androstenone (5α-androst-16-en-3-one) and skatole (3-methylindole). It is crucial to understand the genetic mechanism of boar taint to select pigs for lower androstenone levels and thus reduce boar taint. The aim of this study was the identification of genes and pathways influencing boar taint and involved in androstenone and skatol metabolism. Therefore polymorphisms in relevant genes were identified and transcriptome analysis using Affymetrix-Chips and RNA-Seq in the two major organs involved in androstenone metabolism i.e the testis and the liver was performed. Differentially regulated genes in high androstenone testis and liver samples were involved in metabolic processes such as retinol metabolism, metabolism of xenobiotics by cytochrome P450 and fatty acid metabolism. Moreover, a number of genes encoding biosynthesis of steroids were highly expressed in high androstenone testis samples. Gene polymorphism analysis revealed potential mutations in HSP40, IGFBP1, CYP7A1 and FMO5 genes affecting androstenone levels. Further studies are required for verify the role of candidate genes to be used in genomic selection against boar taint in pig breeding programs. According to the results of association studies, FMO5, CYP21 and ESR1 turned out to be the most promising candidates for boar taint

eQTL Analysis and Association of MYF6 mRNA Expression with Meat Quality Traits in Pigs

The aim of this research was to measure mRNA expression of porcine MYF6 (myogenic factor 6, also known in the medical literature as herculin and myogenic regulatory factor 4, MRF4) and to perform association study with meat quality traits as well as to unravel the transcriptional regulation of this gene by expression QTL (eQTL) study. For this purpose, Duroc x Pietrain F2 resource population (DuPi; n = 313) were used for association and eQTL study. The mRNA levels in Longissimus dorsi muscle tissue of MYF6 gene were evaluated by using qRT-PCR to identify association between gene expression and meat quality traits as well as to analyse eQTL. The mRNA expression of MYF6 associated with conductivity24L (P<0.01) and pH24L (P<0.1). Expression of MYF6 gene was higher in animals with high pH and conductivity of muscle. Linkage analysis using GridQTL revealed 4 trans-regulated eQTL on four porcine autosomes. Significant eQTL [p<0.01, CW (chromosome-wide)] were found for MYF6 on SSC2. A suggestive eQTL (P<0.05, CW) was identified on SSC8. These results revealed that gene expression of MYF6 associated with the meat quality traits and this gene could be potential functional candidate gene for meat quality traits in pigs. However, the analysis of eQTL also suggested that additional genes encoding for transcription factors (TF) could be considered, via fine-mapping underlying the eQTL peaks, in order to understand interaction among these genes

Different Statistical Approaches to Investigate Porcine Muscle Metabolome Profiles to Highlight New Biomarkers for Pork Quality Assessment.

The aim of this study was to elucidate the underlying biochemical processes to identify potential key molecules of meat quality traits drip loss, pH of meat 1 h post-mortem (pH1), pH in meat 24 h post-mortem (pH24) and meat color. An untargeted metabolomics approach detected the profiles of 393 annotated and 1,600 unknown metabolites in 97 Duroc × Pietrain pigs. Despite obvious differences regarding the statistical approaches, the four applied methods, namely correlation analysis, principal component analysis, weighted network analysis (WNA) and random forest regression (RFR), revealed mainly concordant results. Our findings lead to the conclusion that meat quality traits pH1, pH24 and color are strongly influenced by processes of post-mortem energy metabolism like glycolysis and pentose phosphate pathway, whereas drip loss is significantly associated with metabolites of lipid metabolism. In case of drip loss, RFR was the most suitable method to identify reliable biomarkers and to predict the phenotype based on metabolites. On the other hand, WNA provides the best parameters to investigate the metabolite interactions and to clarify the complex molecular background of meat quality traits. In summary, it was possible to attain findings on the interaction of meat quality traits and their underlying biochemical processes. The detected key metabolites might be better indicators of meat quality especially of drip loss than the measured phenotype itself and potentially might be used as bio indicators

Untersuchung der angeborenen Immunkompetenz von Schweinen stimuliert mit PRRS-Virus Impfstoff

Die vorliegende Arbeit zielt darauf ab, Kandidatengene des funktionellen Netzwerks der wirtsspezifischen Immunantwort auf den PRRS-Virus (PRRSV) Impfstoff bei Schweinen zu identifizieren; um transkriptionale Unterschiede durch den induzierten Impfstoff in den zwei Schweinerassen Deutschen Landrasse (DL) und Piétrain (Pi) zu erkunden; und die Aufklärung von Post-transkriptionellen Mechanismen bedingt durch den Impfstoff in den mononukleären Zellen des peripheren Blutes (PBMCs). Zur Erstellung der Transkriptomprofile der Boten-RNA (mRNA) sowie der microRNA (miRNA) in reinrassigen DL und Pi Schweinen zu unterschiedlichen Zeitpunkten nach der PRRSV Impfung wurde die Affymetrix Gen-Chip-Microarray-Technik eingesetzt. Zusätzlich wurden die Microarray Ergebnisse mittels qRT-PCR validiert und die PRRSV-spezifischen Plasma Antikörpertiter durch ELISA bestimmt. Durch den PRRSV-spezifischen Plasma Antikörpertiter zeigte sich, dass die Ferkel frei von mütterlichen Antikörpern zum Zeitpunkt der Erstimpfung waren. Nach der ersten Impfung stieg der Titer in den folgenden zwei Wochen über dem Grenzwert, und erreichte sein Plateau vier Wochen nach der Impfung. Die Betrachtung der globalen mRNA Profile von PBMCs von PRRSV geimpft und ungeimpften DL Schweinen unmittelbar vor 0 und mit 6, 24 und 72 h nach der Impfung ergab eine deutlich angeborene transkriptionelle Wirts Immunreaktion. Insgesamt waren 14.231 Transkripte in PBMCs von geimpften und nicht geimpften Schweine exprimiert. Die Expressionsanalyse (FDR <0,01 und FC> ± 1,5) identifiziert 542, 2263 und 357 differentiell exprimierte Gene 6, 24 und 72 h nach der Impfung. Als potenzielle Kandidatengene für das frühe Stadium der Impfreaktion konnten APP, TRAF6, PIN1, FOS, CDKN1A und TNFAIP3 identifiziert werden. In Piétrain Schweinen waren 295 und 116 Transkripte in PBMCs an Tag 1 und 28 nach der Impfung unterschiedlich exprimiert. Diese Ergebnisse zeigen, dass das angeborene Immunnetzwerk wahrscheinlich durch LCK, STAT3, ATP5B, UBB und RSP17 geregelt wird; während sich TGFβ1, IL7R, Rad21, SP1 und GZMB für die adaptive Immunreaktion auf den PRRSVImpfstoff in PBMCs von Pi-Schweinen als prädiktiv erwiesen. Die microRNA-Profile von PBMCs identifiziert 12, 259 und 14 unterschiedlich exprimiert miRNAs in DL; und 0, 222 und 13 miRNAs in Pi, 6, 24 und 72 h nach der Impfung. Es gab deutliche Unterschiede bei der Expressionsdynamik sowohl bei der mRNAs als auch miRNAs zwischen DL und Pi Schweine. Integrierte mRNA-miRNA-Netzwerke zeigen eine inverse Korrelation zwischen der durch den Impfstoff induzierten veränderten mRNAs und miRNAs Expression in PBMCs. Die Ergebnisse dieser immunogenomischen Studie erweitert unser Verständnis über die genetische Kontrolle von PRRS.This dissertation aims to identify the candidate genes of the functional network of host immune response to porcine reproductive and respiratory syndrome virus (PRRSV) vaccine in pigs; to explore the breed differences on vaccine induced transcriptional response between German Landrace (DL) and Piétrain (Pi) pigs; and to elucidate the post transcriptional regulatory mechanism of vaccine induced gene expression in the peripheral blood mononuclear cells (PBMCs). The Affymetrix gene chip microarray technique was employed for global expression profiling of messenger RNA (mRNA) and microRNA (miRNA) in PBMCs collected in a time series manner following PRRSV vaccination in purebred DL and Pi pigs. Additionally, microarray expression results were validated by qRT-PCR and the PRRSV-specific plasma antibody titre was monitored by ELISA. The PRRSV-specific plasma antibody titre indicated the piglets free from maternal antibody at the time of primary vaccination and rose above the threshold following two weeks of the primary vaccination that subsequently reached a plateau at four weeks post vaccination. The global mRNA profiling of PBMCs from PRRSV vaccinated and age-matched unvaccinated Landrace pigs at immediately before (0 h), and at 6, 24 and 72 h after PRRSV vaccination revealed a distinct host innate immune transcriptional response. A total of 14,231 transcripts were found to be expressed in PBMCs of vaccinated and unvaccinated pigs. Differential expression analysis (FDR ±1.5) identified 542, 2,263 and 357 differentially expressed genes at 6, 24 and 72 h post vaccination. APP, TRAF6, PIN1, FOS, CDKN1A and TNFAIP3 identified to be potential candidate genes for early stage PRRSV vaccine response in Landrace pigs. In Pietrain pigs, 295 and 116 transcripts were found to be differentially expressed in PBMCs at 1 and 28 days post vaccination, respectively. This study suggested that the innate immune transcriptional network is likely to be regulated by LCK, STAT3, ATP5B, UBB and RSP17; while TGFβ1, IL7R, RAD21, SP1 and GZMB were found to be predictive for the adaptive immune transcriptional response to PRRSV vaccine in PBMCs of Pi pigs. The global microRNA profiles of PBMCs identified 12, 259 and 14 differentially expressed (DE) miRNAs in DL; and 0, 222 and 13 DE miRNAs in Pietrain at 6, 24 and 72 h post vaccination, respectively. There were remarkable differences on expression dynamics of both mRNAs and miRNAs between DL and Pi pigs. Integrated mRNA-miRNA network revealed the inverse correlation between vaccine induced altered mRNAs and miRNAs in PBMCs. Results of this immunogenomics study advances our understanding on the genetic control of PRRS