BAHS-Basic Animal Husbandry & Fisheries Statistics, Government of India, Ministry of Agriculture, Department of Animal Husbandry, dairying & Fisheries, Krishi Bhavan, New Delhi, 1–132 (2019).
Mullen, A. M., Stapleton, P. C., Corcoran, D., Hamill, R. M. & White, A. Understanding meat quality through the application of genomic and proteomic approaches. Meat. Sci. 74(1), 3–16. https://doi.org/10.1016/j.meatsci.2006.04.015 (2006).
Google Scholar
Kopuzlu, S. et al. Effects of slaughter age and muscle type on meat quality characteristics of Eastern Anatolian Red bulls. Arch. Anim. Breed 61(4), 497–504. https://doi.org/10.5194/aab-61-497-2018 (2018).
Google Scholar
Li, Q. et al. Effects of age on slaughter performance and meat quality of Binlangjang male buffalo. Saudi J. Biol. Sci. 25(2), 248–252. https://doi.org/10.1016/j.sjbs.2017.10.001 (2018).
Google Scholar
Byrne, K. et al. A gene network switch enhances the oxidative capacity of ovine skeletal muscle during late fetal development. BMC Genomics 11, 378. https://doi.org/10.1186/1471-2164-11-378 (2010).
Google Scholar
Lin, Y., Zhu, J., Wang, Y., Li, Q. & Lin, S. Identification of differentially expressed genes through RNA sequencing in goats (Capra hircus) at different postnatal stages. PLoS ONE 12(8), e0182602. https://doi.org/10.1371/journal.pone.0182602 (2017).
Google Scholar
Sadkowski, T., Jank, M., Oprzadek, J. & Motyl, T. Age-dependent changes in bovine skeletal muscle transcriptomic profile. J. Physiol Pharmacol. 57(Suppl 7), 95–110 (2006).
Google Scholar
Bongiorni, S. et al. Transcriptomic investigation of meat tenderness in two Italian cattle breeds. Anim Genet. 47(3), 273–287. https://doi.org/10.1111/age.12418 (2016).
Google Scholar
Ayuso, M. et al. Comparative analysis of muscle transcriptome between pig genotypes identifies genes and regulatory mechanisms associated to growth, fatness and metabolism. PLoS ONE 10(12), e0145162. https://doi.org/10.1371/journal.pone.0145162 (2015).
Google Scholar
Kumar, A. et al. Transcriptomic diversity in longissimus thoracis muscles of Barbari and Changthangi goat breeds of India. Genomics S0888–7543(21), 00146–00154. https://doi.org/10.1016/j.ygeno.2021.04.019 (2021).
Google Scholar
Hocquette, J. F. et al. The GENOTEND chip: A new tool to analyse gene expression in muscles of beef cattle for beef quality prediction. BMC Vet. Res. 8, 135. https://doi.org/10.1186/1746-6148-8-135 (2012).
Google Scholar
Arora, R. et al. Transcriptome profiling of longissimus thoracis muscles identifies highly connected differentially expressed genes in meat type sheep of India. PLoS ONE 14(6), e0217461. https://doi.org/10.1371/journal.pone.0217461 (2019).
Google Scholar
Kaur, M. et al. Differential expression of miRNAs in skeletal muscles of Indian sheep with diverse carcass and muscle traits. Sci. Rep. 10(1), 16332. https://doi.org/10.1038/s41598-020-73071-7 (2020).
Google Scholar
Zhao, Y. et al. Dynamic transcriptome profiles of skeletal muscle tissue across 11 developmental stages for both Tongcheng and Yorkshire pigs. BMC Genomics 16, 377. https://doi.org/10.1186/s12864-015-1580-7 (2015).
Google Scholar
Weston, A. R., Rogers Pas, R. W. & Althen, T. G. The role of collagen in meat tenderness. Profess. Anim. Sci. 18, 107–111 (2002).
Google Scholar
Polidori, P., Pucciarelli, S., Cammertoni, N., Polzonetti, V. & Vincenzetti, S. The effects of slaughter age on carcass and meat quality of Fabrianese lambs. Small Rumin. Res. 155, 12–15 (2017).
Google Scholar
Hogarth, M. W. et al. Analysis of the ACTN3 heterozygous genotype suggests that α-actinin-3 controls sarcomeric composition and muscle function in a dose-dependent fashion. Hum. Mol. Genet. 25(5), 866–877. https://doi.org/10.1093/hmg/ddv613 (2016).
Google Scholar
Lee, L. A., Karabina, A., Broadwell, L. J. & Leinwand, L. A. The ancient sarcomeric myosins found in specialized muscles. Skelet. Muscle. 9(1), 7. https://doi.org/10.1186/s13395-019-0192-3 (2019).
Google Scholar
Gomes, A. V., Potter, J. D. & Szczesna-Cordary, D. The role of troponins in muscle contraction. IUBMB Life 54(6), 323–333. https://doi.org/10.1080/15216540216037 (2002).
Google Scholar
Johnston, J. R., Chase, P. B. & Pinto, J. R. Troponin through the looking-glass: Emerging roles beyond regulation of striated muscle contraction. Oncotarget 9, 1461–1482 (2018).
Google Scholar
Wojtysiak, D., Kaczor, U., Połtowicz, K. & Krzysztoforski, K. The effects of sex and slaughter weight on muscle fibre characteristics and physico-chemical properties of lamb longissimus thoracis muscle. Anim. Sci. Papers Rep. 28(1), 61–69 (2010).
Lian, T., Wang, L. & Liu, Y. A new insight into the role of calpains in post-mortem meat tenderization in domestic animals: A review. Asian-Australas. J. Anim. Sci. 26(3), 443–454. https://doi.org/10.5713/ajas.2012.12365 (2013).
Google Scholar
Cruzen, S. M., Paulino, P. V., Lonergan, S. M. & Huff-Lonergan, E. Postmortem proteolysis in three muscles from growing and mature beef cattle. Meat Sci. 96(2 Pt A), 854–861. https://doi.org/10.1016/j.meatsci.2013.09.021 (2014).
Google Scholar
Nixon, R. A. The calpains in aging and aging-related diseases. Ageing Res Rev. 2(4), 407–418. https://doi.org/10.1016/s1568-1637(03)00029-1 (2003).
Google Scholar
Dimitrova, Y. et al. TFAP2A is a component of the ZEB1/2 network that regulates TGFB1-induced epithelial to mesenchymal transition. Biol. Direct. https://doi.org/10.1186/s13062-017-0180-7 (2017).
Google Scholar
Muñoz-Cánoves, P., Scheele, C., Pedersen, B. K. & Serrano, A. L. Interleukin-6 myokine signaling in skeletal muscle: A double-edged sword?. FEBS J. 280(17), 4131–4148. https://doi.org/10.1111/febs.12338 (2013).
Google Scholar
Baeza-Raja, B. & Munoz-Canoves, P. p38 MAPK-induced nuclear factor-kappa B activity is required for skeletal muscle differentiation: Role of interleukin-6. Mol. Biol Cell. 15, 2013–2026 (2004).
Google Scholar
Mukund, K. & Subramaniam, S. Skeletal muscle: A review of molecular structure and function, in health and disease. Wiley Interdiscip. Rev. Syst. Biol. Med. 12(1), e1462. https://doi.org/10.1002/wsbm.1462 (2020).
Google Scholar
Cassar-Malek, I., Passelaigue, F., Bernard, C., Léger, J. & Hocquette, J. F. Target genes of myostatin loss-of-function in muscles of late bovine fetuses. BMC Genomics https://doi.org/10.1186/1471-2164-8-63 (2007).
Google Scholar
Goldspink, G., Fernandes, K., Williams, P. E. & Wells, D. J. Age-related changes in collagen gene expression in the muscles of mdx dystrophic and normal mice. Neuromuscul. Disord. 4(3), 183–191. https://doi.org/10.1016/0960-8966(94)90019-1 (1994).
Google Scholar
McBryan, J., Hamill, R. M., Davey, G., Lawlor, P. & Mullen, A. M. Identification of suitable reference genes for gene expression analysis of pork meat quality and analysis of candidate genes associated with the trait drip loss. Meat Sci. 86(2), 436–439. https://doi.org/10.1016/j.meatsci.2010.05.030 (2010).
Google Scholar
Hamill, R. M. et al. Transcriptome analysis of porcine M semimembranosus divergent in intramuscular fat as a consequence of dietary protein restriction. BMC Genomics 14, 453. https://doi.org/10.1186/1471-2164-14-453 (2013).
Google Scholar
Mudry, J. M., Massart, J., Szekeres, F. L. & Krook, A. TWIST1 and TWIST2 regulate glycogen storage and inflammatory genes in skeletal muscle. J. Endocrinol. 224(3), 303–313. https://doi.org/10.1530/JOE-14-0474.Erratum.In:J.Endocrinol.2015Sep;226(3):X1 (2015).
Google Scholar
Miraoui, H. & Marie, P. J. Pivotal role of twist in skeletal biology and pathology. Gene 468, 1–7. https://doi.org/10.1016/j.gene.2010.07.013 (2010).
Google Scholar
Cortez-Toledo, O., Schnair, C., Sangngern, P., Metzger, D. & Chao, L. C. Nur77 deletion impairs muscle growth during developmental myogenesis and muscle regeneration in mice. PLoS ONE 12(2), e0171268 (2017).
Google Scholar
Pan, X. et al. Nr4a1 as a myogenic factor is upregulated in satellite cells/myoblast under proliferation and differentiation state. Biochem. Biophys. Res. Commun. 513(3), 573–581. https://doi.org/10.1016/j.bbrc.2019.04.026 (2019).
Google Scholar
Jean-Baptiste, G., Yang, Z., Khoury, C., Gaudio, S. & Greenwood, M. T. Peptide and non-peptide G-protein coupled receptors (GPCRs) in skeletal muscle. Peptides 26(8), 1528–1536. https://doi.org/10.1016/j.peptides.2005.03.011 (2005).
Google Scholar
Collins, B. C. et al. Deletion of estrogen receptor α in skeletal muscle results in impaired contractility in female mice. J. Appl. Physiol. 124(4), 980–992. https://doi.org/10.1152/japplphysiol.00864.2017 (2018).
Google Scholar
Lee, S. J. et al. IL-17A promotes trans differentiation of mouse myoblast cells (C2C12) into adipocytes by increasing the expression of peroxisome proliferator-activated receptor γ through CAAT/enhancer binding protein β signaling. Biotechnol. Lett. 33(2), 229–235. https://doi.org/10.1007/s10529-010-0440-4 (2011).
Google Scholar
Khan, R. et al. Genetic variants in the TORC2 gene promoter and their association with body measurement and carcass quality traits in Qinchuan cattle. PLoS ONE 15(2), e0227254. https://doi.org/10.1371/journal.pone.0227254 (2020).
Google Scholar
Umansky, K. B. et al. Runx1 transcription factor is required for myoblasts proliferation during muscle regeneration. PLoS Genet. 11(8), e1005457. https://doi.org/10.1371/journal.pgen.1005457 (2015).
Google Scholar
Kuang, S., Kuroda, K., Le Grand, F. & Rudnicki, M. A. Asymmetric self-renewal and commitment of satellite stem cells in muscle. Cell 129, 999–1010 (2007).
Google Scholar
Ganassi, M., Badodi, S., Wanders, K., Zammit, P. S. & Hughes, S. M. Myogenin is an essential regulator of adult myofibre growth and muscle stem cell homeostasis. Elife 9, e60445 (2020).
Google Scholar
Choi, I. Y. et al. Transcriptional landscape of myogenesis from human pluripotent stem cells reveals a key role of TWIST1 in maintenance of skeletal muscle progenitors. Elife 9, e46981. https://doi.org/10.7554/eLife.46981 (2020).
Google Scholar
Kokabu, S. et al. The transcriptional co-repressor TLE3 regulates myogenic differentiation by repressing the activity of the MyoD transcription factor. J. Biol. Chem. 292(31), 12885–12894. https://doi.org/10.1074/jbc.M116.774570 (2017).
Google Scholar
Swiderski, K. et al. Deletion of suppressor of cytokine signaling 3 (SOCS3) in muscle stem cells does not alter muscle regeneration in mice after injury. PLoS ONE 14(2), e0212880. https://doi.org/10.1371/journal.pone.0212880 (2019).
Google Scholar
Nikawa, T. & Ishidoh, K. Ubiquitin ligase Cbl-b and inhibitory Cblin peptides. Biochim. Biophys. Acta Proteins Proteom. 1868(11), 140495. https://doi.org/10.1016/j.bbapap.2020.140495 (2020).
Google Scholar
Tower, J. Hsps and aging. Trends Endocrinol. Metab. 20(5), 216–222. https://doi.org/10.1016/j.tem.2008.12.005 (2009).
Google Scholar
Mymrikov, E. V., Seit-Nebi, A. S. & Gusev, N. B. Large potentials of small heat shock proteins. Physiol. Rev. 91(4), 1123–1159. https://doi.org/10.1152/physrev.00023.2010 (2011).
Google Scholar
Malheiros, J. M. et al. Association of CAST2, HSP90AA1, DNAJA1 and HSPB1 genes with meat tenderness in Nellore cattle. Meat Sci. https://doi.org/10.1016/j.meatsci.2018.01.003 (2018).
Google Scholar
Picard, B. et al. Skeletal muscle proteomics in livestock production. Brief Funct. Genomics 9(3), 259–278. https://doi.org/10.1093/bfgp/elq005 (2010).
Google Scholar
Guillemin, N. et al. Variations in the abundance of 24 protein biomarkers of beef tenderness according to muscle and animal type. Animal 5(6), 885–894. https://doi.org/10.1017/S1751731110002612 (2011).
Google Scholar
Ueda, S. et al. Chicken heat shock protein HSPB1 increases and interacts with αB-crystallin in aged skeletal muscle. Biosci. Biotechnol. Biochem. 79(11), 1867–1875. https://doi.org/10.1080/09168451.2015.1061419 (2015).
Google Scholar
Carra, S., Seguin, S. J. & Landry, J. HspB8 and Bag3: A new chaperone complex targeting misfolded proteins to macro autophagy. Autophagy 4, 237–239 (2008).
Google Scholar
Miguel, E., Blázquez, B. & Ruiz de Huidobro, F. Live weight and sex effects on instrumental meat quality of Rubia de El Molar autochthonous ovine breed. Animals 11, 1323. https://doi.org/10.3390/ani11051323 (2021).
Google Scholar
Walsh, R. J. et al. Type I interferon-inducible gene expression in blood is present and reflects disease activity in dermato myositis and poly myositis. Arthritis Rheum. 56(11), 3784–3792. https://doi.org/10.1002/art.22928 (2007).
Google Scholar
Morgan, D. O. Principles of CDK regulation. Nature 374(6518), 131–134. https://doi.org/10.1038/374131a0 (1995).
Google Scholar
Winey, M. Cell cycle: Driving the centrosome cycle. Curr Biol. 9(12), R449–R452. https://doi.org/10.1016/s0960-9822(99)80279-6 (1999).
Google Scholar
Li, L. et al. CDKL2 promotes epithelial-mesenchymal transition and breast cancer progression. Oncotarget 5(21), 10840–10853. https://doi.org/10.18632/oncotarget.2535 (2014).
Google Scholar
Fang, C. L. et al. Loss of cyclin-dependent kinase-like 2 predicts poor prognosis in gastric cancer, and its overexpression suppresses cells growth and invasion. Cancer Med. 7(7), 2993–3002. https://doi.org/10.1002/cam4.1577 (2018).
Google Scholar
Gong, X., Tang, H. & Yang, K. PER1 suppresses glycolysis and cell proliferation in oral squamous cell carcinoma via the PER1/RACK1/PI3K signaling complex. Cell Death Dis. 12(3), 276. https://doi.org/10.1038/s41419-021-03563-5 (2021).
Google Scholar
Andrews, S. FastQC: A quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc (2010).
Untergasser, A. et al. Primer3-new capabilities and interfaces. Nucleic Acids Res. 40(15), e115. https://doi.org/10.1093/nar/gks596 (2012).
Google Scholar
Banerjee, D. et al. Seasonal variation in expression pattern of genes under HSP70 family in heat- and cold-adapted goats (Capra hircus). Cell Stress Chaperones 19(3), 401–408. https://doi.org/10.1007/s12192-013-0469-0 (2014).
Google Scholar
Bernard, C. et al. New indicators of beef sensory quality revealed by expression of specific genes. J. Agric. Food Chem. 55(13), 5229–5237. https://doi.org/10.1021/jf063372l (2007).
Google Scholar
Zhu, W., Lin, Y., Liao, H. & Wang, Y. Selection of reference genes for gene expression studies related to intramuscular fat deposition in Capra hircus skeletal muscle. PLoS ONE 10(3), e0121280. https://doi.org/10.1371/journal.pone.0121280 (2015).
Google Scholar
Huang, D. W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4(1), 44–57 (2009).
Google Scholar
Kamburov, A. et al. ConsensusPathDB: Toward a more complete picture of cell biology. Nucleic Acids Res. 39, D712-717 (2011).
Google Scholar
Jassal, B. et al. The reactome pathway knowledge base. Nucleic Acids Res. 8(48), D498–D503. https://doi.org/10.1093/nar/gkz1031 (2020).
Google Scholar
Shannon, P. et al. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 13(11), 2498–2504. https://doi.org/10.1101/gr.1239303 (2003).
Google Scholar
Chin, C. H. et al. cytoHubba: Identifying hub objects and sub-networks from complex interactome. BMC Syst. Biol. 8(Suppl 4), S11. https://doi.org/10.1186/1752-0509-8-S4-S11 (2014).
Google Scholar
Vandesompele, J. et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 3(7), RESEARCH0034. https://doi.org/10.1186/gb-2002-3-7-research0034 (2002).
Google Scholar
Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-delta deltaC(T)) method. Methods 25, 402–408 (2001).
Google Scholar
