Association of a single nucleotide polymorphism in the 5' upstream region of the porcine <i>myosin heavy chain 4</i> gene with meat quality traits in pigs

Cho, Eun Seok; Lee, Kyung Tai; Kim, Jun Mo; Lee, Si Woo; Jeon, Hyeon Jeong; Lee, Seung Hwan; Hong, Kyung Pyo; Kim, Tae Hun

doi:10.1111/asj.12442

Cited by 7 publications

(4 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The longissimus dorsi muscle fiber type differs between wild and commercial pig breeds [35]. It has been reported that Myh4 is associated with lean muscle mass and growth rate [36], and that the proportion of Myh4 expression in the longissimus dorsi muscle of YP was the highest. These results suggest that QYP and TP have great potential for genetic improvement in carcass traits.…”

Section: Carcass Traits and Meat Quality Differences Between Yorkshirmentioning

confidence: 99%

High Altitude Adaptability and Meat Quality in Tibetan Pigs: A Reference for Local Pork Processing and Genetic Improvement

Gan

Shen

Yuan

et al. 2019

Animals

View full text Add to dashboard Cite

The carcass and meat quality traits of pig breeds living at three different altitudes (Yorkshire pigs, YP: 500m; Qingyu Pigs, QYP: 1500m; Tibetan pigs, TP: 2500m) were compared. It was observed that there are obvious differences in pig breeds with respect to performance parameters. Specifically, YP had the best carcass traits, showing high slaughter rates and leanest meat. Conversely, QYP had the highest back fat thickness and intramuscular fat (IMF) content. For the high-altitude breed TP, the animals exhibited low L* and high a* values. The genotypes contributing to the observed phenotypes were supported by a PCR analysis. The glycolytic genes expression (HK, PFK, PK) were highest in YP, whereas expression of genes related to adipogenesis (C/EBPα, FABP4, SCD1) were highest in QYP. As expected, genes associated with angiogenesis and hypoxia (HIF1a, VEGFA) were expressed at the highest levels in TP. The composition and proportion of amino and fatty acids in pig muscles at the three altitudes examined also varied substantially. Among the breeds, TP had the highest proportion of umami amino acids, whereas QYP had the highest proportion of sweet amino acids. However, TP also exhibited the highest proportion of essential fatty acids and the lowest proportion of n6:n3. This study explains the high-altitude adaptive evolution and the formation of meat quality differences in different altitude pigs from various angles and provides a reference for local pork food processing and genetic improvement of local pigs.

show abstract

Section: Carcass Traits and Meat Quality Differences Between Yorkshirmentioning

confidence: 99%

High Altitude Adaptability and Meat Quality in Tibetan Pigs: A Reference for Local Pork Processing and Genetic Improvement

Gan

Shen

Yuan

et al. 2019

Animals

View full text Add to dashboard Cite

show abstract

“…The TNNI2 gene was associated with pH, meat color value, and intramuscular fat content in pigs (Yang et al, 2010). The myosin heavy chains are relevant to muscle contraction velocity and power, MYH4 is one of the isoforms associated with IIb fibers types (Cho et al, 2016) and myotube hypertrophy in beef cattle (Bordbar et al, 2020). Our findings suggest new hypotheses of the impact of these proteins of prot2 could affect the REA and carcass traits.…”

Section: Biological Meaning Of Latent Variables and Their Relationshipsmentioning

confidence: 63%

Multi-omic data integration for the study of production, carcass, and meat quality traits in Nellore cattle

Novais

Hyeong-keun²,

Cesar³

et al. 2022

Front. Genet.

View full text Add to dashboard Cite

Data integration using hierarchical analysis based on the central dogma or common pathway enrichment analysis may not reveal non-obvious relationships among omic data. Here, we applied factor analysis (FA) and Bayesian network (BN) modeling to integrate different omic data and complex traits by latent variables (production, carcass, and meat quality traits). A total of 14 latent variables were identified: five for phenotype, three for miRNA, four for protein, and two for mRNA data. Pearson correlation coefficients showed negative correlations between latent variables miRNA 1 (mirna1) and miRNA 2 (mirna2) (−0.47), ribeye area (REA) and protein 4 (prot4) (−0.33), REA and protein 2 (prot2) (−0.3), carcass and prot4 (−0.31), carcass and prot2 (−0.28), and backfat thickness (BFT) and miRNA 3 (mirna3) (−0.25). Positive correlations were observed among the four protein factors (0.45–0.83): between meat quality and fat content (0.71), fat content and carcass (0.74), fat content and REA (0.76), and REA and carcass (0.99). BN presented arcs from the carcass, meat quality, prot2, and prot4 latent variables to REA; from meat quality, REA, mirna2, and gene expression mRNA1 to fat content; from protein 1 (prot1) and mirna2 to protein 5 (prot5); and from prot5 and carcass to prot2. The relations of protein latent variables suggest new hypotheses about the impact of these proteins on REA. The network also showed relationships among miRNAs and nebulin proteins. REA seems to be the central node in the network, influencing carcass, prot2, prot4, mRNA1, and meat quality, suggesting that REA is a good indicator of meat quality. The connection among miRNA latent variables, BFT, and fat content relates to the influence of miRNAs on lipid metabolism. The relationship between mirna1 and prot5 composed of isoforms of nebulin needs further investigation. The FA identified latent variables, decreasing the dimensionality and complexity of the data. The BN was capable of generating interrelationships among latent variables from different types of data, allowing the integration of omics and complex traits and identifying conditional independencies. Our framework based on FA and BN is capable of generating new hypotheses for molecular research, by integrating different types of data and exploring non-obvious relationships.

show abstract

“…Muscle fibers of Type I and Type IIa possess higher myoglobin levels, resulting in a bright red appearance, while Type IIb muscle fibers exhibit lower myoglobin levels, leading to a paler meat color (14). Generally, research indicates a positive correlation between the intensity of redness of meat and the proportion of Type I and Type IIa muscle fibers within the muscle structure (15). Meat color can be measured using a variety of techniques, including sensory evaluation, colorimetric measurement, myoglobin measurement, computer vision measurement, and multispectral vision systems.…”

Section: Meat Colormentioning

confidence: 99%

Molecular mechanisms underlying the impact of muscle fiber types on meat quality in livestock and poultry

Mo,

Zhang,

Wang

et al. 2023

Front. Vet. Sci.

View full text Add to dashboard Cite

In the past, the primary emphasis of livestock and poultry breeding was mainly on improving the growth rate, meat production efficiency and disease resistance. However, the improvement of meat quality has become a major industrial focus due to the ongoing advancements in livestock and poultry breeding. Skeletal muscles consist of multinucleated myofibers formed through the processes of myoblast proliferation, differentiation and fusion. Muscle fibers can be broadly classified into two main types: slow-twitch (Type I) and fast-twitch (Type II). Fast-twitch fibers can be further categorized into Type IIa, Type IIx, and Type IIb. The proportion of Type I and Type IIa muscle fibers is positively associated with meat quality, while the presence of Type IIb muscle fibers in skeletal muscle tissue is inversely related to meat quality. Consequently, muscle fiber composition directly influences meat quality. The distribution of these fiber types within skeletal muscle is governed by a complex network, which encompasses numerous pivotal regulators and intricate signaling pathways. This article aims to succinctly outline the parameters utilized for assessing meat quality, elucidate the relationship between muscle fiber composition and meat quality as well as elaborate on the relevant genetic factors and their molecular mechanisms that regulate muscle fiber types in livestock and poultry. This summary will enrich our comprehension of how to improve meat quality in livestock and poultry, providing valuable insights for future improvements.

show abstract

Association of a single nucleotide polymorphism in the 5' upstream region of the porcine myosin heavy chain 4 gene with meat quality traits in pigs

Cited by 7 publications

References 29 publications

High Altitude Adaptability and Meat Quality in Tibetan Pigs: A Reference for Local Pork Processing and Genetic Improvement

High Altitude Adaptability and Meat Quality in Tibetan Pigs: A Reference for Local Pork Processing and Genetic Improvement

Multi-omic data integration for the study of production, carcass, and meat quality traits in Nellore cattle

Molecular mechanisms underlying the impact of muscle fiber types on meat quality in livestock and poultry

Contact Info

Product

Resources

About