1. Introduction
2. Materials and Methods
3. Results and Discussion
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
References
- Monson, F.; Sanudo, C.; Sierra, C. Influence of cattle breed and ageing time textural breed quality. Meat Sci. 2004, 68, 595–602. [Google Scholar] [CrossRef] [PubMed]
- Neely, T.R.; Lorenzen, C.L.; Miller, R.K.; Tatum, J.D.; Wise, J.W.; Taylor, J.F.; Buyck, M.J.; Reagan, J.O.; Savell, J.W. Beef customer satisfaction: Role of cut, USDA quality grade, and city on in-home consumer ratings. J. Anim. Sci. 1998, 76, 1027–1033. [Google Scholar] [CrossRef] [PubMed]
- Obuz, E.; Dikeman, M.E.; Grobbel, J.P.; Stephans, J.W.; Loughin, T.M. Beef longissimus lumborum, biceps femoris, and deep pectoralis Warner-Bratzler shear force is affected differently by endpoint temperature, cooking method, and USDA quality grade. Meat Sci. 2004, 68, 243–248. [Google Scholar] [CrossRef] [PubMed]
- Emerson, M.R.; Woerner, D.R.; Belk, K.E.; Tatum, J.D. Effectiveness of USDA instrument-based marbling measurements for categorizing beef carcasses according to differences in longissimus muscle sensory attributes. J. Anim. Sci. 2013, 91, 1024–1034. [Google Scholar] [CrossRef] [PubMed]
- Shackleford, S.D.; Koohmaraie, M.; Whipple, G.; Wheeler, T.L.; Miller, M.F.; Crouse, J.D.; Reagan, J.O. Predictors of Beef Tenderness: Development and Verification. J. Food Sci. 1991, 56, 1130–1135. [Google Scholar] [CrossRef]
- Tatum, J.D.; Smith, G.C.; Carpenter, Z.L. Interrelationships between marbling, subcutaneous fat thickness and cooked beef palatability. J. Anim. Sci. 1980, 54, 777–784. [Google Scholar] [CrossRef]
- Eggen, A.; Hocquette, J.F. Genomic approaches to economic trait loci and tissue expression profiling: Application to muscle biochemistry and beef quality. Meat Sci. 2004, 66, 1–9. [Google Scholar] [CrossRef]
- Leal-Gutiérrez, J.D.; Elzo, M.A.; Carr, C.; Mateescu, R.G. RNA-seq analysis identifies cytoskeletal structural genes and pathways for meat quality in beef. PLoS ONE 2020, 15, e0240895. [Google Scholar] [CrossRef]
- Fonseca, L.F.; Gimenez, D.F.; dos Santos Silva, D.B.; Barthelson, R.; Baldi, F.; Ferro, J.A.; Albuquerque, L.G. Differences in global gene expression in muscle tissue of Nellore cattle with divergent meat tenderness. BMC Genom. 2017, 18, 945. [Google Scholar] [CrossRef] [PubMed]
- Sheng, X.; Ni, H.; Liu, Y.; Li, J.; Zhang, L.; Guo, Y. RNA-seq analysis of bovine intramuscular, subcutaneous and perirenal adipose tissues. Mol. Biol. Rep. 2014, 41, 1631–1637. [Google Scholar] [CrossRef]
- Ladeira, M.M.; Schoonmaker, J.P.; Gionbelli, M.P.; Dias, J.C.O.; Gionbelli, T.R.S.; Carvalho, J.R.R.; Teixeira, P.D. Nutrigenomics and Beef Quality: A Review about Lipogenesis. Int. J. Mol. Sci. 2016, 17, 918. [Google Scholar] [CrossRef]
- Ladeira, M.; Schoonmaker, J.; Swanson, K.; Duckett, S.; Gionbelli, M.; Rodrigues, L.; Teixeira, P. Review: Nutrigenomics of marbling and fatty acid profile in ruminant meat. Animal 2018, 12, S282–S294. [Google Scholar] [CrossRef]
- Liang, R.; Han, B.; Li, Q.; Yuan, Y.; Li, J.; Sun, D. Using RNA sequencing to identify putative competing endogenous RNAs (ceRNAs) potentially regulating fat metabolism in bovine liver. Sci. Rep. 2017, 7, 6396. [Google Scholar] [CrossRef] [PubMed]
- USDA—United States Department of Agriculture. United States Standards for Grades of Carcass Beef. 2017. Available online: https://www.ams.usda.gov/sites/default/files/media/CarcassBeefStandard.pdf (accessed on 26 June 2021).
- Huang, D.W.; Sherman, B.T.; Lempicki, R.A. Bioinformatics enrichment tools: Paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009, 37, 1–13. [Google Scholar] [CrossRef]
- Das, S.; Shyamal, S.; Durica, D.S. Analysis of Annotation and Differential Expression Methods used in RNA-seq Studies in Crustacean Systems. Integr. Comp. Biol. 2016, 56, 1067–1079. [Google Scholar] [CrossRef] [PubMed]
- Robinson, M.D.; Oshlack, A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 2010, 11, R25. [Google Scholar] [CrossRef] [PubMed]
- Boles, J.A.; Kohlbeck, K.S.; Meyers, M.C.; Perz, K.A.; Davis, K.C.; Thomson, J.M. The use of blood lactate concentration as an indicator of temperament and its impact on growth rate and tenderness of steaks from Simmental× Angus steers. Meat Sci. 2015, 103, 68–74. [Google Scholar] [CrossRef]
- Boles, J.A.; Boss, D.L.; Neary, K.I.; Davis, K.C.; Tess, M.W. Growth implants reduced tenderness of steaks from steers and heifers with different genetic potentials for growth and marbling. J. Anim. Sci. 2009, 87, 269–274. [Google Scholar] [CrossRef]
- May, S.G.; Dolezal, H.G.; Gill, D.R.; Ray, F.K.; Buchanan, D.S. Effect of days fed, carcass grade traits, and subcutaneous fat removal on postmortem muscle characteristics and beef palatability. J. Anim. Sci. 1992, 70, 444–453. [Google Scholar] [CrossRef]
- Kern, S.A.; Pritchard, R.H.; Blair, A.D.; Scramlin, S.M.; Underwood, K.R. The influence of growth stage on carcass composition and factors associated with marbling development in beef cattle. J. Anim. Sci. 2014, 92, 5275–5284. [Google Scholar] [CrossRef] [PubMed]
- Nurnberg, K.; Wegner, J.; Ender, K. Factors influencing fat composition in muscle and adipose tissue of farm animals. Live Prod. Sci. 1998, 56, 145–156. [Google Scholar] [CrossRef]
- Robelin, J. Growth of adipose tissues in cattle; partitioning between depots, chemical composition and cellularity. Rev. Live Prod. Sci. 1986, 14, 349–364. [Google Scholar] [CrossRef]
- Legako, J.F.; Brooks, J.C.; O’Quinn, T.G.; Hagan, T.D.J.; Polkinghorne, R.; Farmer, L.J.; Miller, M.F. Consumer palatability scores and volatile beef flavor compounds of five USDA quality grades and four muscles. Meat Sci. 2015, 100, 291–300. [Google Scholar] [CrossRef]
- Smith, G.C.; Carpenter, Z.L.; Cross, H.R.; Murphey, C.E.; Abraham, H.C.; Savell, J.W.; Davis, G.W.; Berry, B.W.; Parrish, F.C., Jr. Relationship of USDA marbling groups to palatability of cooked beef. J. Food Qual. 1985, 7, 289–308. [Google Scholar] [CrossRef]
- Bratcher, C.L.; Johnson, D.D.; Littell, R.C.; Gwartney, B.L. The effects of quality grade, aging, and location within muscle on Warner–Bratzler shear force in beef muscles of locomotion. Meat Sci. 2005, 70, 279–284. [Google Scholar] [CrossRef]
- Gruber, S.L.; Tatum, J.D.; Scanga, J.A.; Chapman, P.L.; Smith, G.C.; Belk, K.E. Effects of postmortem aging and USDA quality grade on Warner-Bratzler shear force values of seventeen individual beef muscles. J. Anim. Sci. 2006, 84, 3387–3396. [Google Scholar] [CrossRef] [PubMed]
- Marino, R.; Albenzio, M.; dell Malva, A.; Santillo, A.; Loizzp, P.; Sevi, A. Proteolytic pattern of myofibrillar protein and meat tenderness as affected by breed and aging time. Meat Sci. 2013, 95, 281–287. [Google Scholar] [CrossRef] [PubMed]
- Purchas, R.W.; Aungsupakorn, R. Further investigations into the relationship between ultimate pH and tenderness for beef samples from bulls and steers. Meat Sci. 1993, 34, 163–178. [Google Scholar] [CrossRef]
- Clark, D.L.; Boler, D.D.; Kutzler, L.W.; Jones, K.A.; McKeith, F.K.; Killefer, J.; Carr, T.R.; Dilger, A.C. Muscle gene expression associated with increased marbling in beef cattle. Anim. Biotech. 2011, 22, 51–63. [Google Scholar] [CrossRef] [PubMed]
- Roberts, S.L.; Lancaster, P.A.; DeSilva, U.; Horn, G.W.; Krehbiel, C.R. Coordinated gene expression between skeletal muscle and intramuscular adipose tissue in growing beef cattle. J. Anim. Sci. 2015, 93, 4302–4311. [Google Scholar] [CrossRef] [PubMed]
- Le Grand, F.; Rudnicki, M.A. Skeletal muscle satellite cells and adult myogenesis. Curr. Opin. Cell Biol. 2007, 19, 628–633. [Google Scholar] [CrossRef]
- Zammit, P.S. Function of the myogenic regulatory factors Myf5, MyoD, Myogenin and MRF4 in skeletal muscle, satellite cells and regenerative myogenesis. In Seminars in Cell & Developmental Biology; Academic Press: Cambridge, MA, USA, 2017; Volume 72, pp. 19–32. [Google Scholar]
- Goodman, C. The Role of mTORC1 in Mechanically-Induced Increases in Translation and Skeletal Muscle Mass. J. Appl. Phys. 2019, 127, 581–590. [Google Scholar] [CrossRef]
- Flück, M.; Carson, J.A.; Gordon, S.E.; Ziemiecki, A.; Booth, F.W. Focal adhesion proteins FAK and paxillin increase in hypertrophied skeletal muscle. Am. J. Physiol. 1999, 277, C152–C162. [Google Scholar] [CrossRef] [PubMed]
- Crossland, H.; Kazi, A.A.; Lang, C.H.; Timmons, J.A.; Pierre, P.; Wilkinson, D.J.; Smith, K.; Szewczyk, N.J.; Atherton, P.J. Focal adhesion kinase is required for IGF-I-mediated growth of skeletal muscle cells via a TSC2/mTOR/S6K1-associated pathway. Am. J. Physiol. Endocrinol. Metab. 2013, 15, E183–E193. [Google Scholar] [CrossRef] [PubMed]
- Tao, X.; Liang, Y.; Yang, X.; Pang, J.; Zhong, Z.; Chen, X.; Yang, Y.; Zeng, K.; Kang, R.; Lei, Y.; et al. Transcriptomic profiling in muscle and adipose tissue identifies genes related to growth and lipid deposition. PLoS ONE 2017, 6, e0184120. [Google Scholar] [CrossRef] [PubMed]
- Raza, S.H.A.; Kaster, N.; Khan, R.; Abdelnour, S.A.; El-Hack, M.E.A.; Khafaga, A.F.; Taha, A.; Ohran, H.; Swelum, A.A.; Schreurs, N.M.; et al. The Role of MicroRNAs in Muscle Tissue Development in Beef Cattle. Genes 2020, 11, 295. [Google Scholar] [CrossRef]
- Keady, S.M.; Kenny, D.A.; Keane, M.G.; Waters, S.M. Effect of sire breed and genetic merit for carcass weight on the transcriptional regulation of the somatotropic axis in longissimus dorsi of crossbred steers. J. Anim. Sci. 2011, 89, 4007–4016. [Google Scholar] [CrossRef]
Grade | Shear Force (N ± SD) | HCW (k ± SDg) | Fat (cm ± SD) | REA (cm2 ± SD) | KPH (% ± SD) | Yield Grade (±SD) | Marbling 1 (±SD) |
---|---|---|---|---|---|---|---|
Standard | 66.3 b ± 12.4 | 250.6 b ± 33.0 | 0.43 b ± 0.21 | 57.68 c ± 5.27 | 1.60 c ± 0.22 | 2.46 ab ± 0.4 | 266 c ± 16.7 |
Select | 84.3 a ± 13.9 | 282.9 a ± 23.0 | 0.64 a ± 0.21 | 67.23 b ± 2.72 | 1.80 b ± 2.27 | 2.62 a ± 0.37 | 330 b ± 18.7 |
Choice | 71.3 b ± 13.0 | 283.2 a ± 15.9 | 0.58 a ± 0.23 | 72.13 a ± 4.87 | 2.08 a ± 0.38 | 2.35 b ± 0.24 | 463 a ± 15.0 |
p value | <0.0001 | <0.0001 | 0.0104 | <0.0001 | <0.0001 | 0.0077 | <0.0001 |
Age (days) | Shear Force (N ± SD) |
---|---|
1 | 89.9 a ± 16.5 |
3 | 80.7 b ± 17.8 |
7 | 71.0 b ± 13.7 |
14 | 65.3 b ± 11.9 |
21 | 62.9 c ±9.7 |
Gene ID | Gene Name | Fold Change | Corrected p-Value | Function |
---|---|---|---|---|
TET1 | Tet methylcytosine dioxygenase 1 | 12.37 | 0.031 | DNA and iron binding |
ETV5 | ETS variant 5 | 9.89 | 0.045 | Regulation of transcription, neuromuscular transmission |
BRB | Brain ribonuclease | 9.89 | 0.002 | Nucleic acid binding, endonuclease activity, hydrolase activity |
DKK3 | Dickkopf WNT signaling pathway inhibitor 3 | 9.89 | 0.002 | Multicellular organism development, negative regulation of WNT signaling |
BASE2 | Beta-secretase 2 | 9.28 | 0.003 | Proteolysis, protein catabolic processes |
TNFAIP2 | TNF-alpha-induced protein 2 | 8.67 | 0.008 | SNARE binding, exocytosis |
HPGD | 5-hydroxyprostaglandin dehydrogenase | 6.80 | 0.016 | Growth factor receptor signaling |
PCGF6 | Polycomb group ring finger 6 | 6.18 | 0.025 | Negative regulation of transcription |
SERPINE1 | Serpin family E member 1 | 4.93 | 0.006 | Angiogenesis, protease binding, enzyme inhibitor activity |
ANKRD2 | Ankyrin repeat domain 2 | 2.06 | 0.016 | Protein/titin binding, skeletal muscle development/differentiation |
Gene ID | Gene Name | Fold Change | Corrected p-Value | Function |
---|---|---|---|---|
RFC2 | Replication factor C subunit | 11.77 | 0.0008 | DNA binding, DNA replication, Cell cycle activity |
PQLC2 | PQ loop repeat containing 2 | 9.01 | 0.0003 | Amino acid transmembrane transport |
PPM1F | Protein phosphatase, Mg2+/Mn2+ dependent 1F | 8.09 | 0.0008 | Protein dephosphorylation, positive regulation of transcription, negative regulation of protein kinase |
TBPL1 | TATA-box binding protein-like 1 | 4.56 | 0.027 | DNA binding, positive regulation of transcription |
GLB1 | Galactosidase beta 1 | 4.31 | 0.028 | Carbohydrate metabolic process, hydrolase activity |
INSIG2 | Insulin-induced gene | 3.9 | 0.027 | Lipid metabolic process |
GALNT11 | Polypeptide N-acetylgalactosaminyltransferase 11 | 3.74 | 0.027 | Notch binding, protein glycosylation, transferase activity |
TAF7-201 | TATA-box binding protein associated factor 7 | 3.07 | 0.0004 | Negative regulation of transcription, thyroid hormone signaling |
NKTR | Natural killer cell triggering receptor | 2.75 | 0.0005 | Protein folding and protein refolding |
PSMA4 | Proteasome subunit alpha 4 | 2.17 | 0.0008 | Proteolysis, protein catabolic processes |
Gene ID | Gene Name | Fold Change | Corrected p-Value | Function |
---|---|---|---|---|
MX1 | MX1 MX dynamin-like GTPase 1 | 11.25 | <0.000 | Extracellular signaling, immune response, recognition of pregnancy |
CHRND | Cholinergic receptor nicotinic delta subunit | 7.59 | 0.002 | Muscle acetylcholine receptor |
UBA7 | Brain ribonuclease | 7.24 | <0.000 | Cytokine signaling |
RSAD2 | Radical S-adenosyl methionine domain-containing 2 | 6.9 | <0.001 | Iron and sulfur binding, catalytic activity, protein self-association |
OAS1Z | 2′,5′-oligoadenylate synthetase 1 | 6.12 | <0.001 | Cytokine signaling, neutrophil gene expression |
NUDT8 | Nudix hydrolase 8 | 5.55 | 0.004 | Coenzyme A diphosphatase |
NMRAL1 | NmrA-like redox sensor 1 | 5.52 | <0.001 | Protein binding, nuclear signaling |
CELSR1 | Cadherin EGF LAG seven-pass G-type receptor 1 | 5.42 | 0.005 | Positive regulation of cell migration and angiogenesis |
SQLE | Squalene epoxidase | 5.23 | 0.01 | Modulator of plasma membrane lipid profile, cholesterol synthesis inhibition |
BOLA-DOB | Major histocompatibility complex, class II, DO beta | 5.2 | 0.044 | Immune function, self-recognition, |
Gene ID | Gene Name | Fold Change | Corrected p-Value | Function |
---|---|---|---|---|
PLA2G7 | Phospholipase A2 group VII | 7.00 | Anti-inflammatory activity, lipoprotein metabolism | |
BACH2 | BTB domain and CNC homolog 2 | 6.52 | 0.01 | Innate immune response, PAX5 signaling |
ALK | ALK receptor tyrosine kinase | 6.28 | 0.027 | Cellular signaling |
ZNF184 | Zinc finger protein 184 | 6.02 | 0.001 | Cellular signaling |
ZP2 | Zona pellucida glycoprotein 2 | 5.71 | 0.01 | Reproduction, Ca2+ transport |
SMOX | Spermine oxidase | 5.67 | 0.02 | ROS mediation, catabolism of polyamines |
PRDM15 | PR/SET domain 15 | 5.05 | 0.05 | Neurogenesis, epigenetic modifier |
TNFRSF12A | TNF receptor superfamily member 12A | 4.86 | 0.006 | Cytokine signaling |
CD8A | CD8a molecule | 4.61 | 0.016 | T-cell activity, immune function |
DNAJB14 | DNAJ heat-shock protein family (Hsp40) member B14 | 4.53 | 0.001 | Endoplasmic reticulum function, protein catabolism |
KEGG Pathways | ||
---|---|---|
Pathway Name | Count | p-Value |
TNF signaling pathway | 15 | <0.001 |
Signaling pathway regulating pluripotency of stem cells | 16 | 0.004 |
Thyroid hormone signaling pathway | 14 | 0.004 |
Neurotrophin signaling pathway | 14 | 0.009 |
Apoptosis | 8 | 0.01 |
Insulin resistance | 12 | 0.02 |
Type 2 diabetes mellitus | 7 | 0.03 |
FoxO signaling pathway | 13 | 0.03 |
Focal adhesion | 17 | 0.05 |
Gene Ontology | ||
Cellular Compartment | ||
Proteinaceous extracellular matrix | 27 | <0.001 |
Cortical actin cytoskeleton | 8 | 0.01 |
Biological process | ||
Canonical Wnt signaling pathway | 13 | <0.01 |
Negative regulation of catalytic activity | 7 | 0.03 |
Regulation of cell migration | 17 | 0.05 |
Molecular Function | ||
Endopeptidase activity | 7 | 0.03 |
Metal ion binding | 90 | 0.06 |
KEGG Pathways | ||
---|---|---|
Pathway Name | Count | p-Value |
RNA transport | 24 | <0.001 |
RNA Degradation | 25 | <0.001 |
Spliceosome | 19 | 0.002 |
cGMP-PKG signaling pathway | 20 | 0.007 |
NF-kappa B signaling pathway | 13 | 0.01 |
Lysosome | 16 | 0.02 |
Basal transcription factors | 8 | 0.02 |
Metabolic pathways | 98 | 0.02 |
Vascular smooth muscle contraction | 14 | 0.04 |
Gene Ontology | ||
Cellular Compartment | ||
Cytoplasm | 288 | <0.001 |
Small-subunit processome | 8 | 0.009 |
Biological Process | ||
RNA methylation | 4 | 0.002 |
Positive regulation of interferon-beta production | 7 | 0.003 |
DNA repair | 19 | 0.003 |
mRNA splicing | 16 | 0.003 |
Negative regulation of MAP kinase activity | 8 | 0.004 |
Molecular Function | ||
Metal ion binding | 137 | <0.001 |
Nucleic acid binding | 58 | <0.001 |
RNA methyltransferase activity | 5 | <0.001 |
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