Genome‐wide association analyses of lesion counts in group‐housed pigs

Wurtz, Kaitlin; Siegford, Janice M.; Ernst, Catherine W.; Raney, Nancy E.; Bates, R. O.; Steibel, Juan P.

doi:10.1111/age.12713

Cited by 12 publications

(5 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Besides, PL and IMF of this resource population were not strongly selected, and their genetic variation was large. The pedigree information ( Costa et al, 2015 ) and chip data ( Won et al, 2018 ; Wurtz et al, 2018 ) were widely applied for quantitative trait locus (QTL) mapping. So far, no report on more than 10 million SNP markers used for estimating the heritability of quantitative traits in livestock and poultry is available.…”

Section: Discussionmentioning

confidence: 99%

Effect of host genetics and gut microbiome on fat deposition traits in pigs

Wang

Zhou

et al. 2022

Front. Microbiol.

View full text Add to dashboard Cite

Fat deposition affects meat quality, flavor, and production in pigs. Fat deposition is influenced by both genetics and environment. Symbiotic microbe with the host is an important environmental factor to influence fat deposition. In this study, the fat deposition traits were measured in 239 individuals obtained from Tongcheng pigs × Large White pigs resource population. The interactions between genetics and gut microbiome in fat deposition traits were investigated through whole-genome sequencing and cecum microbial 16S ribosomal RNA sequencing. The results showed that the percentage of leaf fat (PL) and intramuscular fat content (IMF) were significantly influenced by host genetics–gut microbiome interaction. The effects of interactions between host genetics and gut microbiome on PL and IMF were 0.13 and 0.29, respectively. The heritability of PL and IMF was estimated as 0.71 and 0.89, respectively. The microbiability of PL and IMF was 0.20 and 0.26, respectively. Microbiome-wide association analysis (MWAS) revealed Anaeroplasma, Paraprevotella, Pasteurella, and Streptococcus were significantly associated with PL, and Sharpea and Helicobacter exhibited significant association with IMF (p < 0.05). Furthermore, Paraprevotella was also identified as a critical microbe affecting PL based on the divergent Wilcoxon rank-sum test. Overall, this study reveals the effect of host genetics and gut microbiome on pig fat deposition traits and provides a new perspective on the genetic improvement of pig fat deposition traits.

show abstract

Section: Discussionmentioning

confidence: 99%

Effect of host genetics and gut microbiome on fat deposition traits in pigs

Wang

Zhou

et al. 2022

Front. Microbiol.

View full text Add to dashboard Cite

show abstract

“…These techniques can convert farms to research facilities that provide real-time outcomes. An example includes measuring pig aggression [139,140] in the presence of environmental enrichment, (3) Consumer acceptance and enhancement of consumer image of the swine industry: The public expects producers to provide individual attention with good human-animal interaction. While we presume that large commercial producers will become early adopters of technology, precision livestock farming can be farm-size neutral.…”

Section: Limitations and Opportunitiesmentioning

confidence: 99%

Precision Livestock Farming in Swine Welfare: A Review for Swine Practitioners

Benjamin

Yik

2019

Animals

154

132

View full text Add to dashboard Cite

The burgeoning research and applications of technological advances are launching the development of precision livestock farming. Through sensors (cameras, microphones and accelerometers), images, sounds and movements are combined with algorithms to non-invasively monitor animals to detect their welfare and predict productivity. In turn, this remote monitoring of livestock can provide quantitative and early alerts to situations of poor welfare requiring the stockperson’s attention. While swine practitioners’ skills include translation of pig data entry into pig health and well-being indices, many do not yet have enough familiarity to advise their clients on the adoption of precision livestock farming practices. This review, intended for swine veterinarians and specialists, (1) includes an introduction to algorithms and machine learning, (2) summarizes current literature on relevant sensors and sensor network systems, and drawing from industry pig welfare audit criteria, (3) explains how these applications can be used to improve swine welfare and meet current pork production stakeholder expectations. Swine practitioners, by virtue of their animal and client advocacy roles, interpretation of benchmarking data, and stewardship in regulatory and traceability programs, can play a broader role as advisors in the transfer of precision livestock farming technology, and its implications to their clients.

show abstract

“…Owing to these difficulties, only a few studies using omics technologies have been published to date on tail biting behaviour. Genetic association studies have identified a QTL for the number of lesions in Yorkshire pigs after mixing on chromosome 11 [ 142 ]. Being a victim of tail biting was associated with genomic regions on chromosomes 1, 9, 18 and an unassigned region [ 143 ].…”

Section: Omics To Study Tail Bitingmentioning

confidence: 99%

Omics Application in Animal Science—A Special Emphasis on Stress Response and Damaging Behaviour in Pigs

Kasper

Ribeiro

Almeida

et al. 2020

Genes

View full text Add to dashboard Cite

Increasing stress resilience of livestock is important for ethical and profitable meat and dairy production. Susceptibility to stress can entail damaging behaviours, a common problem in pig production. Breeding animals with increased stress resilience is difficult for various reasons. First, studies on neuroendocrine and behavioural stress responses in farm animals are scarce, as it is difficult to record adequate phenotypes under field conditions. Second, damaging behaviours and stress susceptibility are complex traits, and their biology is not yet well understood. Dissecting complex traits into biologically better defined, heritable and easily measurable proxy traits and developing biomarkers will facilitate recording these traits in large numbers. High-throughput molecular technologies (“omics”) study the entirety of molecules and their interactions in a single analysis step. They can help to decipher the contributions of different physiological systems and identify candidate molecules that are representative of different physiological pathways. Here, we provide a general overview of different omics approaches and we give examples of how these techniques could be applied to discover biomarkers. We discuss the genetic dissection of the stress response by different omics techniques and we provide examples and outline potential applications of omics tools to understand and prevent outbreaks of damaging behaviours.

show abstract

Genome‐wide association analyses of lesion counts in group‐housed pigs

Cited by 12 publications

References 19 publications

Effect of host genetics and gut microbiome on fat deposition traits in pigs

Effect of host genetics and gut microbiome on fat deposition traits in pigs

Precision Livestock Farming in Swine Welfare: A Review for Swine Practitioners

Omics Application in Animal Science—A Special Emphasis on Stress Response and Damaging Behaviour in Pigs

Contact Info

Product

Resources

About