期刊论文详细信息
BMC Genomics
Global liver gene expression differences in Nelore steers with divergent residual feed intake phenotypes
Luciana CA Regitano4  Jeremy F Taylor2  Mauricio A Mudadu4  Adhemar Zerlotini-Neto3  Dante PD Lanna6  Amália S Chaves6  Rymer R Tullio4  Gerson B Mourão6  Marcela M Souza1  Priscila SN Oliveira1  Kamila O Rosa5  Robert D Schnabel2  Jared E Decker2  Luiz L Coutinho6  Polyana C Tizioto2 
[1]Department of Genetics and Evolution, Federal University of Sao Carlos, São Carlos, SP, Brazil
[2]Division of Animal Sciences, University of Missouri Columbia, Columbia, MO, USA
[3]Embrapa Agricultural Informatics, Campinas, SP, Brazil
[4]Embrapa Southeast Livestock, São Carlos, SP, Brazil
[5]Department of Animal Science, State University of Sao Paulo, Jaboticabal, SP, Brazil
[6]Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, São Paulo, Brazil
关键词: Transcriptomics;    Feed efficiency;    RFI;    Bos indicus;   
Others  :  1149194
DOI  :  10.1186/s12864-015-1464-x
 received in 2014-10-15, accepted in 2015-03-13,  发布年份 2015
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【 摘 要 】

Background

Efficiency of feed utilization is important for animal production because it can reduce greenhouse gas emissions and improve industry profitability. However, the genetic basis of feed utilization in livestock remains poorly understood. Recent developments in molecular genetics, such as platforms for genome-wide genotyping and sequencing, provide an opportunity to identify genes and pathways that influence production traits. It is known that transcriptional networks influence feed efficiency-related traits such as growth and energy balance. This study sought to identify differentially expressed genes in animals genetically divergent for Residual Feed Intake (RFI), using RNA sequencing methodology (RNA-seq) to obtain information from genome-wide expression profiles in the liver tissues of Nelore cattle.

Results

Differential gene expression analysis between high Residual Feed Intake (HRFI, inefficient) and low Residual Feed Intake (LRFI, efficient) groups was performed to provide insights into the molecular mechanisms that underlie feed efficiency-related traits in beef cattle. A total of 112 annotated genes were identified as being differentially expressed between animals with divergent RFI phenotypes. These genes are involved in ion transport and metal ion binding; act as membrane or transmembrane proteins; and belong to gene clusters that are likely related to the transport and catalysis of molecules through the cell membrane and essential mechanisms of nutrient absorption. Genes with functions in cellular signaling, growth and proliferation, cell death and survival were also differentially expressed. Among the over-represented pathways were drug or xenobiotic metabolism, complement and coagulation cascades, NRF2-mediated oxidative stress, melatonin degradation and glutathione metabolism.

Conclusions

Our data provide new insights and perspectives on the genetic basis of feed efficiency in cattle. Some previously identified mechanisms were supported and new pathways controlling feed efficiency in Nelore cattle were discovered. We potentially identified genes and pathways that play key roles in hepatic metabolic adaptations to oxidative stress such as those involved in antioxidant mechanisms. These results improve our understanding of the metabolic mechanisms underlying feed efficiency in beef cattle and will help develop strategies for selection towards the desired phenotype.

【 授权许可】

   
2015 Tizioto et al.; licensee Biomed Central.

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【 参考文献 】
  • [1]Archer JA, Richardson EC, Herd RM, Arthur PH: Potential for selection to improve efficiency of feed use in beef cattle: a review. Aust J Agric Res 1999, 50(2):147-162.
  • [2]Nkrumah JD, Okine EK, Mathison GW, Schmid K, Li C, Basarab JA, et al.: Relationships of feedlot feed efficiency, performance and feeding behaviour with metabolic rate, methane production, and energy partitioning in beef cattle. J Anim Sci 2006, 84(1):145-153.
  • [3]Basarab JA, Price MA, Aalhus JL, Okine EK, Snelling WM, Lyle KL: Residual feed intake and body composition in young growing cattle. Can J Anim Sci 2003, 83(2):189-204.
  • [4]Arthur PF, Archer JA, Johnston DJ, Herd RM, Richardson EC, Parnell PF: Genetic and phenotypic variance and covariance components for feed intake, feed efficiency, and other postweaning traits in Angus cattle. J Anim Sci 2001, 79(11):2805-2811.
  • [5]Spurlock DM, Dekker JCM, Fernando R, Koltes DA, Wolc A: Genetic parameters for energy balance, feed efficiency, and related traits in Holstein cattle. J Dairy Sci 2012, 95(9):5393-5402.
  • [6]Nkrumah JD, Basarab JA, Wang Z, Li C, Price MA, Okine EK, et al.: Genetic and phenotypic relationships of feed intake and measures of efficiency with growth and carcass merit of beef cattle. J Anim Sci 2007, 85(10):2711-20.
  • [7]Robinson DL, Oddy VH: Genetic parameters for feed efficiency, fatness, muscle area and feeding behavior of feedlot finished beef cattle. Livest Prod Sci 2014, 90(2–3):255-270.
  • [8]Oliveira PSN, Cesar SM, Nascimento ML, Chaves AM, Tizioto PC, Tullio RR, et al.: Identification of genomic regions associated with feed efficiency in Nelore cattle. BMC Genet 2014, 15:100.
  • [9]Herd RM, Arthur PF: Physiological basis for residual feed intake. J Anim Sci 2009, 87(14 Suppl.):E64-E71.
  • [10]Muers M: Sequencing for disease architecture. Nat Rev Genet 2013, 14:518.
  • [11]Santana MH, Utsunomiya YT, Neves HH, Gomes RC, Garcia JF, Fukumasu H, et al.: Genome-wide association analysis of feed intake and residual feed intake in Nellore cattle. BMC Genet 2014, 15:21.
  • [12]Chen Y, Gondro C, Quinn K, Herd RM, Parnell PF, Vanselow B: Global gene expression profiling reveals genes expressed differentially in cattle with high and low residual feed intake. Anim Genet 2011, 42(5):475-490.
  • [13]Trapnell C, Pachter L, Salzberg SL: TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 2009, 25(9):1105-1111.
  • [14]Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, et al.: Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc 2012, 7(3):562-578.
  • [15]Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, Pacther L: Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat Biotechnol 2013, 31:46-53.
  • [16]Wang ET, Sandberg R, Luo S, Khrebtukova I, Zhang L, Mayr C, et al.: Alternative isoform regulation in human tissue transcriptomes. Nature 2008, 456(7221):470-476.
  • [17]Newberry EP, Xie Y, Kennedy S, Han X, Buhman KK, Luo J, et al.: Decreased hepatic triglyceride accumulation and altered fatty acid uptake in mice with deletion of the liver fatty acid-binding protein gene. J Biol Chem 2003, 278(51):51664-51672.
  • [18]Kuhla B, Albrecht D, Kuhla S, Metges CC: Proteome analysis of fatty liver in feed-deprived dairy cows reveals interaction of fuel sensing, calcium, fatty acid, and glycogen metabolism. Physiol Genomics 2009, 37(2):88-98.
  • [19]McCarthy SD, Waters SM, Kenny DA, Diskin MG, Fitzpatrick R, Patton J, et al.: Negative energy balance and hepatic gene expression patterns in high-yielding dairy cows during the early postpartum period: a global approach. Physiol Genomics 2010, 42A(3):188-199.
  • [20]Stoffel W, Hammels I, Jenke B, Binczeck E, Schmidt-Soltau I, Brodesser S, et al.: Obesity resistance and deregulation of lipogenesis in D6-fatty acid desaturase (FADS2) deficiency. EMBO Rep 2014, 15(1):110-119.
  • [21]Brand MD, Esteves TC: Physiological functions of the mitochondrial uncoupling proteins UCP2 and UCP3. Cell Metab 2005, 2(2):85-93.
  • [22]Fonseca LF, Gimenez DF, Mercadante ME, Bonilha SF, Ferro JA, Baldi F, et al.: Expression of genes related to mitochondrial function in Nellore cattle divergently ranked on residual feed intake. Mol Biol Rep 2015, 42(2):559-565.
  • [23]G-Jr D, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, et al.: DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol 2003, 4(5):3.
  • [24]Hearne JL, Colman RF: Delineation of xenobiotic substrate sites in rat glutathione S-transferase M1-1. Protein Sci 2005, 14(10):2526-2536.
  • [25]Björkholm B, Bok CM, Lundin A, Rafter J, Hibberd ML, Pettersson S: Intestinal microbiota regulate xenobiotic metabolism in the liver. PLoS One 2009, 4(9):e6958.
  • [26]Nelson DR, Koymans L, Kamataki T, Stegeman JJ, Feyereisen R, Waxman DJ, et al.: P-450 superfamily: update on new sequences, gene mapping, accession numbers and nomenclature. Pharmacogenetics 1996, 6(1):1-42.
  • [27]Court MH, Hazarika S, Krishnaswamy S, Finel M, Williams JA: Novel polymorphic human UDP-glucuronosyltransferase 2A3: cloning, functional characterization of enzyme variants, comparative tissue expression, and gene induction. Mol Pharmacol 2008, 74(3):744-754.
  • [28]Zhang YK, Wu KC, Klaassen CD: Genetic activation of Nrf2 protects against fasting-induced oxidative stress in livers of mice. PLoS One 2013, 8(3):e59122.
  • [29]Ojano-Dirain C, Iqbal M, Wing T, Cooper M, Bottje W: Glutathione and respiratory chain complex activity in duodenal mitochondria of broilers with low and high feed efficiency. Poult Sci 2005, 84:782-788.
  • [30]Wood BJ, Archer JA, van der Werf JHJ: Response to selection in beef cattle using IGF-1 as a selection criterion for residual feed intake under different Australian breeding objectives. Livest Prod Sci 2004, 91(1–2):69-81.
  • [31]Saarela S, Reiter RJ: Function of melatonin in thermoregulatory processes. Life Sci 1994, 54(5):295-311.
  • [32]Cipolla-Neto J, Amaral FG, Afeche SC, Tan DX, Reiter RJ: Melatonin, energy metabolism, and obesity: a review. J Pineal Res 2014, 56(4):371-381.
  • [33]Hatzis G, Ziakas P, Kavantzas N, Triantafyllou A, Sigalas P, Andreadou I, et al.: Melatonin attenuates high fat diet-induced fatty liver disease in rats. World J Hepatol 2013, 5(4):160-169.
  • [34]Lee KS, Buck M, Houglum K, Chojkier M: Activation of hepatic stellate cells by TGF alpha and collagen type I is mediated by oxidative stress through c-myb expression. J Clin Invest 1995, 96(5):2461-2468.
  • [35]Solís-Muñoz P, Solís-Herruzo JA, Fernández-Moreira D, Gómez-Izquierdo E, García-Consuegra I, Muñoz-Yagüe T, et al.: Melatonin improves mitochondrial respiratory chain activity and liver morphology in ob/ob mice. J Pineal Res 2011, 51(1):113-123.
  • [36]Nunn C, Zhao P, Zou MX, Summers K, Guglielmo CG, Chidiac P: Resistance to age-related, normal body weight gain in RGS2 deficient mice. Cell Signal 2011, 23:1375-1386.
  • [37]Zmijewski JW, Song L, Harkins L, Cobbs CS, Jope RS: Oxidative stress and heat shock stimulate RGS2 expression in 1321 N1 astrocytoma cells. Arch Biochem Biophys 2001, 392(2):192-6.
  • [38]Carbon S, Ireland A, Mungall CJ, Shu S, Marshall B, Lewis S, et al.: AmiGO: online access to ontology and annotation data. Bioinformatics 2009, 25(2):288-289.
  • [39]Serão NV, González-Peña D, Beever JE, Faulkner DB, Southey BR, Rodriguez-Zas SL: Single nucleotide polymorphisms and haplotypes associated with feed efficiency in beef cattle. BMC Genet 2013, 14:94.
  • [40]Solakivi T, Kunnas T, Jaakkola O, Renko J, Lehtimäki T, Nikkari ST: Delta-6-desaturase gene polymorphism is associated with lipoprotein oxidation in vitro. Lipids Health Dis 2013, 12:80.
  • [41]Krämer A, Green J, Pollard J Jr, Tugendreich S: Causal analysis approaches in ingenuity pathway analysis. Bioinformatics 2014, 30(4):523-30.
  • [42]Getz GS, Reardon CA: Apoprotein E as a lipid transport and signaling protein in the blood, liver, and artery wall. J Lipid Res 2009, 50(Suppl):S156-61.
  • [43]Takahashi Y, Sato K, Itoh F, Miyamoto T, Oohashi T, Katoh N: Bovine apolipoprotein E in plasma: increase of ApoE concentration induced by fasting and distribution in lipoprotein fractions. J Vet Med Sci 2003, 65:199-205.
  • [44]Wilcox HG, Heimberg M: Secretion and uptake of nascent hepatic very low density lipoprotein by perfused livers from fed and fasted rats. J Lipid Res 1987, 28:351-360.
  • [45]Meunier-Durmort C, Poirier H, Niot I, Forest C, Besnard P: Up-regulation of the expression of the gene for liver fatty acid-binding protein by long-chain fatty acids. Biochem J 1996, 319(Pt 2):483-487.
  • [46]Chevillotte E, Rieusset J, Roques M, Desage M, Vidal H: The regulation of uncoupling protein-2 gene expression by omega-6 polyunsaturated fatty acids in human skeletal muscle cells involves multiple pathways, including the nuclear receptor peroxisome proliferator-activated receptor beta. J Biol Chem 2001, 276:10853-10860.
  • [47]Xie Z, Gong MC, Su W, Turk J, Guo Z: Group VIA phospholipase A2 (iPLA2beta) participates in angiotensin II-induced transcriptional up-regulation of regulator of g-protein signaling-2 in vascular smooth muscle cells. J Biol Chem 2007, 282:25278-25289.
  • [48]Wijendran V, Downs I, Srigley CT, Kothapalli KS, Park WJ, Blank BS, et al.: Dietary arachidonic acid and docosahexaenoic acid regulate liver fatty acid desaturase (FADS) alternative transcript expression in suckling piglets. Prostaglandins Leukot Essent Fatty Acids 2013, 89:345-350.
  • [49]Ward LD, Kellis M: Interpreting non-coding variation in complex disease genetics. Nat Biotechnol 2012, 30:1095-1106.
  • [50]Jo M, Lester RD, Montel V, Eastman B, Takimoto S, Gonias SL: Reversibility of epithelial-mesenchymal transition (EMT) induced in breast cancer cells by activation of urokinase receptor-dependent cell signaling. J Biol Chem 2009, 284:22825-22833.
  • [51]Meznarich J, Malchodi L, Helterline D, Ramsey SA, Bertko K, Plummer T, et al.: Urokinase plasminogen activator induces pro-fibrotic/m2 phenotype in murine cardiac macrophages. PLoS One 2013, 8:e57837.
  • [52]Pagel JI, Deindl E: Disease progression mediated by egr-1 associated signaling in response to oxidative stress. Int J Mol Sci 2012, 13(10):13104-13117.
  • [53]Schiaffonati L, Tiberio L: Gene expression in liver after toxic injury: analysis of heat shock response and oxidative stress-inducible genes. Liver 1997, 17(4):183-191.
  • [54]Iqbal M, Pumford NR, Tang ZX, Lassiter K, Ojano-Dirain C, Wing T, et al.: Compromised liver mitochondrial function and complex activity in low feed efficient broilers are associated with higher oxidative stress and differential protein expression. Poult Sci 2005, 84:933-941.
  • [55]Grummer RR: Etiology of lipid-related metabolic disorders in periparturient dairy cows. J Dairy Sci 1993, 76:3882-3896.
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