Current transcriptomics in pig immunity research

Schroyen, Martine; Tuggle, Christopher K.

doi:10.1007/s00335-014-9549-4

Cited by 28 publications

(26 citation statements)

References 171 publications

(118 reference statements)

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“…Changes in expression of combinations of smaller subsets of genes may be coordinated and detection of these changes as biomarkers of production disease could be of immense value in improved diagnosis and risk analysis to determine best practice with an impact on increased economic output and animal welfare. In the last ten years we have seen a rise in the number of publications using whole genome arrays to analyse the pig transcriptome which Schroyen and Tuggle, 2015 reviewed in greater detail (Schroyen and Tuggle, 2015). In particular, there has been a great deal of focus on the pig's immune system and the response to various pathogens such as PRRSV (Miller et al, 2012;Wilkinson et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Molecular approaches to the diagnosis and monitoring of production diseases in pigs

Giles

Belkhiri

Barrow

et al. 2017

Research in Veterinary Science

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Production disease in pigs is caused by a variety of different pathogens, mainly enteric and respiratory and can result in significant economic loss. Other factors such as stress, poor husbandry and nutrition can also contribute to an animal's susceptibility to disease. Molecular biomarkers of production disease could be of immense value by improving diagnosis and risk analysis to determine best practice with an impact on increased economic output and animal welfare. In addition to the use of multiplex PCR or microarrays to detect individual or mixed pathogens during infection, these technologies can also be used to monitor the host response to infection via gene expression. The patterns of gene expression associated with cellular damage or initiation of the early immune response may indicate the type of pathology and, by extension the types of pathogen involved. Molecular methods can therefore be used to monitor both the presence of a pathogen and the host response to it during production disease. The field of biomarker discovery and implementation is expanding as technologies such as microarrays and next generation sequencing become more common. Whilst a large number of studies have been carried out in human medicine, further work is needed to identify molecular biomarkers in veterinary medicine and in particular those associated with production disease in the pig industry. The pig transcriptome is highly complex and still not fully understood. Further gene expression studies are needed to identify molecular biomarkers which may have predictive value in identifying the environmental, nutritional and other risk factors which are associated with production diseases in pigs.

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Section: Introductionmentioning

confidence: 99%

Molecular approaches to the diagnosis and monitoring of production diseases in pigs

Giles

Belkhiri

Barrow

et al. 2017

Research in Veterinary Science

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“…Blood constitutes a relevant tissue for phenotyping immune capacity (Flori et al, 2011;Mach et al, 2013;Schroyen and Tuggle, 2015), and evaluating the health status of pigs. To study the health status in piglets during the period after weaning, we conducted correlation analyses between the haematological traits collected at weaning (28 d) and one week after weaning (34 d), and the model parameter data.…”

Section: Applicability Of the Model In Porcine Productionmentioning

confidence: 99%

Towards the quantitative characterization of piglets’ robustness to weaning: A modelling approach

Revilla¹,

Friggens²,

Broudiscou³

et al. 2018

Preprint

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Short title: Piglets robustness to weaning: a modelling approach correlations between model parameters and individual diarrhoea scores and haematological traits. Overall, the parameters of our model can be useful for constructing weaning robustness indexes by using exclusively the growth curves. We foresee that this modelling approach will provide a step forward in the quantitative characterization of robustness.The quantitative characterization of animal robustness at weaning is a key step for management strategies to improve health and welfare. This characterization is also instrumental for the further design of selection strategies for productivity and robustness. Within a precision livestock farming optic, this study develops a mathematical modelling approach to describe the body weight of piglets from weaning with the rationale that weight trajectories provide central information to quantify the capability of the animal to cope with the weaning disturbance.

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“…The domestic pig (Sus scrofa) is an important farm animal for meat source worldwide and has been used as alternative models for studying genetics, nutrition, and disease as reviewed recently (Houpt et al 1979; Verma et al 2011; Bailey and Carlson 2019). The swine genome community has created a large amount of useful data about the transcriptome of pigs (Schroyen and Tuggle 2015). The recently released pig genome sequence (Sscrofa 10.2) (Groenen et al 2012) and associated annotation greatly enhance our knowledge of the pig biology (Dawson et al 2013; Beiki et al 2019).…”

Section: Introductionmentioning

confidence: 99%

“…In the pig, several Expressed Sequence Tag (EST) sequencing projects, microarray platforms, and deep sequencing projects have developed gene expression profiles across a range of tissues (Hornshoj et al 2007; Freeman et al 2012). Compared to the model organisms, the information of the pig transcriptome is still limited in terms of comprehensive tissue and gene coverage (Schroyen and Tuggle 2015). Here we present Super deepSAGE (serial analysis of gene expression by deep sequencing) profiling data for the normal pig tissues with wide gene coverage and annotation.…”

Section: Introductionmentioning

confidence: 99%

Identification of porcine RUNX1 as an LPS-dependent gene expression regulator in PBMCs by Super deepSAGE sequencing of multiple tissues

Huang

Yang

Dong

et al. 2019

Preprint

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Genome-wide identification of gene expression regulators may facilitate our understanding of the transcriptome constructed by gene expression profiling experiment. These regulators may be selected as targets for genetic manipulations in farm animals. In this study, we developed a gene expression profile of 76,000+ unique transcripts for 224 porcine samples from 28 normal tissues collected from 32 animals using Super deepSAGE (serial analysis of gene expression by deep sequencing) technology. Excellent sequencing depth has been achieved for each multiplexed library, and principal component analysis showed that duplicated samples from the same tissues cluster together, demonstrating the high quality of the Super deepSAGE data. Comparison with previous research indicated that our results not only have excellent reproducibility but also have greatly extended the coverage of the sample types as well as the number of genes. Clustering analysis discovered ten groups of genes showing distinct expression patterns among those samples. Binding motif over representative analysis identified 41 regulators responsible for the regulation of these gene clusters. Finally, we demonstrate a potential application of this dataset to infectious and immune research by identifying an LPS-dependent transcription factor, runt-related transcription factor 1 (RUNX1), in peripheral blood mononuclear cells (PBMCs). The selected genes are specifically responsible for the transcription of toll-like receptor 2 (TLR2), lymphocyte-specific protein tyrosine kinase (LCK), vav1 oncogene (VAV1), and other 32 genes. These genes belong to the T and B cell signaling pathways, making them potential novel targets for the diagnostic and therapy of bacterial infections and other immune disorders.

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Current transcriptomics in pig immunity research

Cited by 28 publications

References 171 publications

Molecular approaches to the diagnosis and monitoring of production diseases in pigs

Molecular approaches to the diagnosis and monitoring of production diseases in pigs

Towards the quantitative characterization of piglets’ robustness to weaning: A modelling approach

Identification of porcine RUNX1 as an LPS-dependent gene expression regulator in PBMCs by Super deepSAGE sequencing of multiple tissues

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