Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-25T10:08:05.289Z Has data issue: false hasContentIssue false
  • English
  • Français

Longitudinal muscle gene expression patterns associated with differential intramuscular fat in cattle

Published online by Cambridge University Press:  13 November 2014

N. J. Hudson ,
A. Reverter ,
P. L. Greenwood ,
B. Guo ,
L. M. Cafe  and
B. P. Dalrymple
N. J. Hudson*
Affiliation:
Computational and Systems Biology, CSIRO Agriculture Flagship, 306 Carmody Road, St Lucia, Brisbane, QLD 4067, Australia
A. Reverter
Affiliation:
Computational and Systems Biology, CSIRO Agriculture Flagship, 306 Carmody Road, St Lucia, Brisbane, QLD 4067, Australia
P. L. Greenwood
Affiliation:
NSW Department of Primary Industries Beef Industry Centre, University of New England, Armidale, NSW 2350, Australia
B. Guo
Affiliation:
Computational and Systems Biology, CSIRO Agriculture Flagship, 306 Carmody Road, St Lucia, Brisbane, QLD 4067, Australia
L. M. Cafe
Affiliation:
NSW Department of Primary Industries Beef Industry Centre, University of New England, Armidale, NSW 2350, Australia
B. P. Dalrymple
Affiliation:
Computational and Systems Biology, CSIRO Agriculture Flagship, 306 Carmody Road, St Lucia, Brisbane, QLD 4067, Australia
*
†E-mail: [email protected]
Get access

Abstract

Intramuscular fat (IMF) can improve meat product quality through its impact on flavour and juiciness. High marbling cuts can command premium prices in some countries and grading systems, but there is substantial cost involved in choosing to grain feed animals in an effort to deposit more IMF. There would be value in developing methods to predict predisposition to ‘marble’ well. Unfortunately, the biological mechanisms underpinning marbling remain a mystery: the key adipocyte cell populations have not been defined, there are no reliable DNA markers, no known (if any) causal mutations and gene expression analyses in the main have tended to characterise increases in expression of end-point fat metabolism proteins such as the fatty acid-binding proteins. To shed light on expression-based markers of marbling potential, we contrasted LD gene expression in high IMF Wagyu cross animals with a low IMF Piedmontese cross at various time points. The expected divergence in the fat metabolism genes FABP4, THRSP, CIDEC and ACACA between the breeds occurs surprisingly late in postnatal development at about 20 months. On the other hand, divergent expression of WISP2, RAI14 and CYP4F2 was discovered in animals at or before 12 months of age, suggesting these genes may have potential as earlier predictors of marbling potential. In line with other researchers, we found intriguing links between IMF development and connective tissue remodelling. WISP2 – a novel adipokine highly expressed and secreted by adipose precursor cells and an inhibitor of the pro-fibrotic connective tissue growth factor – emerges as a particularly attractive candidate. It is relatively upregulated in high marbling Wagyu before admission to feedlotting, somewhere between 7 and 12 months. This difference is subsequently maintained until 25 months, but not thereafter. RAI14, thought to play a role in porcine adipocyte differentiation and with links to retinoic acid metabolism, has an unusual expression profile. Its expression level increases monotonically with postnatal development, and is always higher in Wagyu than Piedmontese. Strong, sustained upregulation of the anti-inflammatory CYP4F2 in Piedmontese is consistent with Wagyu adiposity being a pro-inflammatory state. Application of regulatory impact factor analysis, a network method for identifying causal effector molecules, suggests marbling roles for transcription factors previously implicated in (1) the formation of liposarcoma (unconstrained fatty masses) (YEATS4, MDM2), (2) adipogenesis (CREBL2, SP1, STAT1) and (3) inflammation (ISGF3G, HOXB13, PML).

Keywords

marblingcattlePiedmonteseWagyuadipocyte
Type
Research Article
Information
animal , Volume 9 , Issue 4 , April 2015 , pp. 650 - 659
Copyright
© The Animal Consortium 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bonet, ML, Ribot, J and Palou, A 2012. Lipid metabolism in mammalian tissues and its control by retinoic acid. Biochimica et Biophysica Acta 1821, 177–189.CrossRefGoogle ScholarPubMed
Bonnet, M, Cassar-Malek, I, Chilliard, Y and Picard, B 2010. Ontogenesis of muscle and adipose tissues and their interactions in ruminants and other species. Animal 4, 1093–1109.CrossRefGoogle ScholarPubMed
Dahlman, I, Elsen, M, Tennagels, N, Korn, M, Brockmann, B, Sell, H, Eckel, J and Arner, P 2012. Functional annotation of the human fat cell secretome. Archives of Physiology and Biochemistry 118, 84–91.CrossRefGoogle ScholarPubMed
De Jager, N, Hudson, NJ, Reverter, A, Barnard, R, Cafe, LM, Greenwood, PL, Dalrymple, BP 2013. Gene expression phenotypes for lipid metabolism and intramuscular fat in skeletal muscle of cattle. Journal of Animal Science 91, 1112–1128.CrossRefGoogle ScholarPubMed
Eden, E, Lipson, D, Yogev, S and Yakhini, Z 2007. Discovering motifs in ranked lists of DNA sequences. PLoS Computational Biology 3, e39.CrossRefGoogle ScholarPubMed
Gotoh, T, Albrecht, E, Teuscher, F, Kawabata, K, Sakashita, K, Iwamoto, H and Wegner, J 2009. Differences in muscle and fat accretion in Japanese black and European cattle. Meat Science 82, 300–308.Google Scholar
Greenwood, PL, Cafe, LM, Hearnshaw, H, Hennessy, DW, Thompson, RF and Morris, SG 2006. Long-term consequences of birth weight and growth to weaning on carcass, yield and beef quality characteristics of Piedmontese- and Wagyu-sired cattle. Australian Journal of Experimental Agriculture 46, 257–269.Google Scholar
Hammarstedt, A, Hedjazifar, S, Jenndahl, L, Gogg, S, Grunberg, J, Gustafson, B, Klimcakova, E, Stich, V, Langin, D, Laakso, M and Smith, U 2013. WISP2 regulates preadipocyte commitment and PPARgamma activation by BMP4. Proceedings of the National Academy of Science USA 110, 2563–2568.CrossRefGoogle ScholarPubMed
Hardwick, JP 2008. Cytochrome P450 omega hydroxylase (CYP4) function in fatty acid metabolism and metabolic diseases. Biochemical Pharmacology 75, 2263–2275.CrossRefGoogle ScholarPubMed
Harper, GS and Pethick, DW 2004. How might marbling begin. Australian Journal of Experimental Agriculture 44, 653–662.Google Scholar
Huang da, W, Sherman, BT and Lempicki, RA 2009. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols 4, 44–57.CrossRefGoogle ScholarPubMed
Hudson, NJ, Reverter, A and Dalrymple, BP 2009a. A differential wiring analysis of expression data correctly identifies the gene containing the causal mutation. PLoS Computational Biology 5, e1000382.Google Scholar
Hudson, NJ, Dalrymple, BP and Reverter, A 2012. Beyond differential expression: the quest for causal mutations and effector molecules. BMC Genomics 13, 356.CrossRefGoogle ScholarPubMed
Hudson, NJ, Reverter, A, Wang, Y, Greenwood, PL and Dalrymple, BP 2009b. Inferring the transcriptional landscape of bovine skeletal muscle by integrating co-expression networks. PLoS One 4, e7249.CrossRefGoogle ScholarPubMed
Hudson, NJ, Lyons, RE, Reverter, A, Greenwood, PL and Dalrymple, BP 2013. Inferring the in vivo cellular program of developing bovine skeletal muscle from expression data. Gene Expression Patterns 13, 109–125.CrossRefGoogle ScholarPubMed
Italiano, A, Bianchini, L, Keslair, F, Bonnafous, S, Cardot-Leccia, N, Coindre, JM, Dumollard, JM, Hofman, P, Leroux, A, Mainguene, C, Peyrottes, I, Ranchere-Vince, D, Terrier, P, Tran, A, Gual, P and Pedeutour, F 2008. HMGA2 is the partner of MDM2 in well-differentiated and dedifferentiated liposarcomas whereas CDK4 belongs to a distinct inconsistent amplicon. International Journal of Cancer 122, 2233–2241.CrossRefGoogle ScholarPubMed
Kalsotra, A, Du, L, Wang, Y, Ladd, PA, Kikuta, Y, Duvic, M, Boyd, AS, Keeney, DS and Strobel, HW 2008. Inflammation resolved by retinoid X receptor-mediated inactivation of leukotriene signaling pathways. FASEB Journal 22, 538–547.Google Scholar
Lee, SH, Gondro, C, van der Werf, J, Kim, NK, Lim, DJ, Park, EW, Oh, SJ, Gibson, JP and Thompson, JM 2010. Use of a bovine genome array to identify new biological pathways for beef marbling in Hanwoo (Korean Cattle). BMC Genomics 11, 623.Google Scholar
Lehnert, SA, Reverter, A, Byrne, KA, Wang, Y, Nattrass, GS, Hudson, NJ and Greenwood, PL 2007. Gene expression studies of developing bovine longissimus muscle from two different beef cattle breeds. BMC Developmental Biology 7, 95.Google Scholar
Li, DL, Chen, JL, Wen, J, Zhao, GP, Zheng, MQ and Liu, C 2013. Growth, carcase and meat traits and gene expression in chickens divergently selected for intramuscular fat content. British Poultry Science 54, 183–189.Google Scholar
Li, G, Wu, Z, Li, X, Ning, X, Li, Y and Yang, G 2010. Biological role of microRNA-103 based on expression profile and target genes analysis in pigs. Molecular Biology Reports 38, 4777–4786.CrossRefGoogle ScholarPubMed
Mariman, EC and Wang, P 2010. Adipocyte extracellular matrix composition, dynamics and role in obesity. Cellular and Molecular Life Sciences 67, 1277–1292.CrossRefGoogle ScholarPubMed
Pannier, L, Mullen, AM, Hamill, RM, Stapleton, PC and Sweeney, T 2010. Association analysis of single nucleotide polymorphisms in DGAT1, TG and FABP4 genes and intramuscular fat in crossbred Bos taurus cattle. Meat Science 85, 515–518.Google Scholar
Pethick, DW, Harper, GS and Oddy, VH 2004. Growth, development and nutritional manipulation of marbling in cattle: a review. Australian Journal of Experimental Agriculture 44, 705–715.Google Scholar
Ramayo-Caldas, Y, Fortes, MR, Hudson, NJ, Porto-Neto, LR, Bolormaa, S, Barendse, W, Kelly, M, Moore, SS, Goddard, ME, Lehnert, SA and Reverter, A 2014. A marker-derived gene network reveals the regulatory role of PPARGC1A, HNF4G and FOXP3 in intramuscular fat deposition of beef cattle. Journal of Animal Science 92, 2832–2845.CrossRefGoogle ScholarPubMed
Ren, ZQ, Wu, WJ, Liu, WH, Zheng, R, Li, JL, Zuo, B, Xu, DQ, Li, FE, Lei, MG, Ni, DB and Xiong, YZ 2014. Differential expression and effect of the porcine ANGPTL4 gene on intramuscular fat. Genetics and Molecular Research 13, 2949–2958.CrossRefGoogle ScholarPubMed
Reverter, A, Hudson, NJ, Nagaraj, SH, Perez-Enciso, M and Dalrymple, BP 2010. Regulatory impact factors: unraveling the transcriptional regulation of complex traits from expression data. Bioinformatics 26, 896–904.Google Scholar
Rhinn, H, Fujita, R, Qiang, L, Cheng, R, Lee, JH and Abeliovich, A 2013. Integrative genomics identifies APOE epsilon4 effectors in Alzheimer’s disease. Nature 500, 45–50.Google Scholar
Rhinn, H, Qiang, L, Yamashita, T, Rhee, D, Zolin, A, Vanti, W and Abeliovich, A 2012. Alternative alpha-synuclein transcript usage as a convergent mechanism in Parkinson’s disease pathology. Nature Communications 3, 1084.CrossRefGoogle ScholarPubMed
Sabbah, M, Prunier, C, Ferrand, N, Megalophonos, V, Lambein, K, De Wever, O, Nazaret, N, Lachuer, J, Dumont, S and Redeuilh, G 2011. CCN5, a novel transcriptional repressor of the transforming growth factor beta signaling pathway. Molecular and Cell Biology 31, 1459–1469.Google Scholar
Saez, G, Davail, S, Gentes, G, Hocquette, JF, Jourdan, T, Degrace, P and Baeza, E 2009. Gene expression and protein content in relation to intramuscular fat content in Muscovy and Pekin ducks. Poultry Science 88, 2382–2391.Google Scholar
Sato-Kusubata, K, Jiang, Y, Ueno, Y and Chun, TH 2011. Adipogenic histone mark regulation by matrix metalloproteinase 14 in collagen-rich microenvironments. Molecular Endocrinology 25, 745–753.CrossRefGoogle ScholarPubMed
Wang, W, Xue, W, Jin, B, Zhang, X, Ma, F and Xu, X 2013. Candidate gene expression affects intramuscular fat content and fatty acid composition in pigs. Journal of Applied Genetics 54, 113–118.Google Scholar
Wang, YH, Byrne, KA, Reverter, A, Harper, GS, Taniguchi, M, McWilliam, SM, Mannen, H, Oyama, K and Lehnert, SA 2005. Transcriptional profiling of skeletal muscle tissue from two breeds of cattle. Mammalian Genome 16, 201–210.CrossRefGoogle ScholarPubMed
Wang, YH, Bower, NI, Reverter, A, Tan, SH, De Jager, N, Wang, R, McWilliam, SM, Cafe, LM, Greenwood, PL and Lehnert, SA 2009. Gene expression patterns during intramuscular fat development in cattle. Journal of Animal Science 87, 119–130.Google Scholar
Welle, S, Cardillo, A, Zanche, M and Tawil, R 2009. Skeletal muscle gene expression after myostatin knockout in mature mice. Physiological Genomics 38, 342–350.Google Scholar
Supplementary material: File

Hudson Supplementary Material

Table S1

Download Hudson Supplementary Material(File)
File 17.5 KB
Supplementary material: File

Hudson Supplementary Material

Table S2

Download Hudson Supplementary Material(File)
File 55.8 KB
Supplementary material: File

Hudson Supplementary Material

Table S3

Download Hudson Supplementary Material(File)
File 13.2 KB