期刊论文详细信息
BMC Genetics
Identification of genomic regions associated with feed efficiency in Nelore cattle
Luciana CA Regitano5  Luiz L Coutinho6  Maurício A Mudadu5  Dorian J Garrick2  James M Reecy2  Gerson B Mourao6  Tad S Sonstegard4  Antonio N Rosa3  Dante PD Lanna6  Rymer R Tullio5  Polyana C Tizioto1  Amália S Chaves6  Michele L do Nascimento6  Aline SM Cesar6  Priscila SN de Oliveira1 
[1] Department of Genetics and Evolution, Federal University of Sao Carlos, Sao Carlos, 13565-905, SP, Brazil;Department of Animal Science, Iowa State University, Ames 50011, IA, USA;Embrapa Beef Cattle, Campo Grande, 79002-970, MS, Brazil;USDA ARS Bovine Functional Genomics Laboratory, Beltsville 20705, MD, USA;Embrapa Southeast-Cattle Research Center, Sao Carlos, 13560-970, SP, Brazil;Department of Animal Science, University of Sao Paulo, Piracicaba, 13418-900, SP, Brazil
关键词: Single nucleotide polymorphisms;    Residual feed intake;    Candidate gene;    Bos indicus;   
Others  :  1085573
DOI  :  10.1186/s12863-014-0100-0
 received in 2013-12-06, accepted in 2014-09-10,  发布年份 2014
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【 摘 要 】

Background

Feed efficiency is jointly determined by productivity and feed requirements, both of which are economically relevant traits in beef cattle production systems. The objective of this study was to identify genes/QTLs associated with components of feed efficiency in Nelore cattle using Illumina BovineHD BeadChip (770 k SNP) genotypes from 593 Nelore steers. The traits analyzed included: average daily gain (ADG), dry matter intake (DMI), feed-conversion ratio (FCR), feed efficiency (FE), residual feed intake (RFI), maintenance efficiency (ME), efficiency of gain (EG), partial efficiency of growth (PEG) and relative growth rate (RGR). The Bayes B analysis was completed with Gensel software parameterized to fit fewer markers than animals. Genomic windows containing all the SNP loci in each 1 Mb that accounted for more than 1.0% of genetic variance were considered as QTL region. Candidate genes within windows that explained more than 1% of genetic variance were selected by putative function based on DAVID and Gene Ontology.

Results

Thirty-six QTL (1-Mb SNP window) were identified on chromosomes 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 18, 19, 20, 21, 22, 24, 25 and 26 (UMD 3.1). The amount of genetic variance explained by individual QTL windows for feed efficiency traits ranged from 0.5% to 9.07%. Some of these QTL minimally overlapped with previously reported feed efficiency QTL for Bos taurus. The QTL regions described in this study harbor genes with biological functions related to metabolic processes, lipid and protein metabolism, generation of energy and growth. Among the positional candidate genes selected for feed efficiency are: HRH4, ALDH7A1, APOA2, LIN7C, CXADR, ADAM12 and MAP7.

Conclusions

Some genomic regions and some positional candidate genes reported in this study have not been previously reported for feed efficiency traits in Bos indicus. Comparison with published results indicates that different QTLs and genes may be involved in the control of feed efficiency traits in this Nelore cattle population, as compared to Bos taurus cattle.

【 授权许可】

   
2014 de Oliveira et al.; licensee BioMed Central Ltd.

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【 参考文献 】
  • [1]Basarab JA, Price MA, Aalhus JL, Okine EK, Snelling WM, Lyle KL: Residual feed intake and body composition in young growing cattle. J Anim Sci 2003, 83:189-204.
  • [2]Koch RM, Swinger LA, Chambers D, Gregory KE: Efficiency of feed use in beef cattle. J Anim Sci 1963, 22:486-494.
  • [3]Archer JA, Richardson EC, Herd RM, Arthur PF: Potential for selection to improve efficiency of feed use in beef cattle: a review. J Agric Res 1999, 50:147-161.
  • [4]Kellner O: The Scientific Feeding Of Animals. McMillan, New York; 1909.
  • [5]Fitzhugh HA, Taylor CS: Genetic analysis of degree of maturity. J Anim Sci 1971, 33:717-725.
  • [6]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, 79:2805-2811.
  • [7]Sherman EL, Nkrumah JD, Moore SS: Whole genome single nucleotide polymorphism associations with feed intake and feed efficiency in beef cattle. J Anim Sci 2010, 88(1):16-22. doi:10.2527/jas.2008-1759
  • [8]Nkrumah JD, Basarab JA, Wang Z, Li C, Price MA, Okine EK, Crews DH Jr, Moore SS: Genetic and phenotypic relationships of feed intake and measures of efficiency with growth and carcass merit of beef cattle. J Anim Sci 2007, 85:2711-2720.
  • [9]Bolormaa S, Pryce JE, Kemper K, Savin K, Hayes BJ, Barendse W, Zhang Y, Reich CM, Mason BA, Bunch RJ, Harrison BE, Reverter A, Herd RM, Tier B, Graser H-U, Goddard ME: Accuracy of prediction of genomic breeding values for residual feed intake, carcass and meat quality traits in Bos taurus, Bos indicus and composite beef cattle. J Anim Sci 2013, 91(7):3088-3104.
  • [10]Santana MHA, Utsunomiya YT, Neves HHR, Gomes RC, Garcia JF, Fukumasu H, Ferraz JBS: Genome-wide association analysis of feed intake and residual feed intake in Nellore cattle. BMC Genet 2014, ᅟ:ᅟ. doi:10.1186/1471-2156-15-21
  • [11]Fortes MRS, Snelling WM, Reverter A, Nagaraji SH, Lehnert SA, Hawken RJ, DeAtley KL, Peters SO, Silver GA, Rincon G, Medrano JF, Isla-Trejo A, Thomas MG: Gene network analyses of first service conception in Brangus heifers: Use of genome and trait associations, hypo-thalamic-transcriptome information, and transcription factors. J Anim Sci 2012, 90:2894-2906.
  • [12]Snelling WM, Cushman RA, Fortes MRS, Reverter A, Bennett GL, Keele JW, Kuehn LA, McDaneld TG, Thallman RM, Thomas MG: How SNP chips will advance our knowledge of factors controlling puberty and aid in selecting replacement females. J Anim Sci 2012, 90:1152-1165.
  • [13]Nkrumah JD, Basarab JA, Price MA, Okine EK, Ammoura A, Guercio S, Hansen C, Li C, Benkel B, Moore SS: Different measures of energetic efficiency and their relationships with growth, feed intake, ultrasound and carcass measurementsin hybrid cattle. J Anim Sci 2004, 82:2451-2459.
  • [14]Elzo MA, Riley DG, Hansen GR, Johnson DD, Myer RO, Coleman SW, Chase CC, Wasdin JG, Driver JD: Effect of breed composition on phenotypic residual feed intake and growth in Angus, Brahman, and Angus × Brahman crossbred cattle. J Anim Sci 2009, 87:3877-3886.
  • [15]Crowley JJ, Evans RD, Mc Hugh N, Kenny DA, McGee M, Crews D Jr, Berry DP: Genetic relationships between feed efficiency in growing males and beef cow performance. J Anim Sci 2010, 89:3372-3381.
  • [16]Corvino TLS, Branco RH, Bonilha SFM, Castilhos AM, Figueiredo LA, Razook AG, Mercadante MEZ: Residual feed intake and relationships with performance of Nelore cattle selected for post weaning weight. Rev Bras Zootec 2011, 40:929-937.
  • [17]Bonilha EFM, Branco RH, Bonilha SFM, Araujo FL, Magnani E, Mercadante MEZ: Body chemical composition of Nelore bulls with different residual feed intakes. J Anim Sci 2013, 91(7):3457-3464.
  • [18]Meuwissen THE, Hayes BJ, Goddard ME: Prediction of total genetic value using genome-wide dense marker maps. Genetics 2001, 157:1819-1829.
  • [19]Saatchi M, Ward J, Garrick DJ: Accuracies of direct genomic breeding values in Hereford beef cattle using national or international training populations. J Anim Sci 2013, 91(4):1538-1551.
  • [20]Bolormaa S, Hayes BJ, Hawken RJ, Zhang Y, Reverter A, Goddard ME: Detection of chromosome segments of zebu and taurin origin and their effect on beef production and growth. J Anim Sci 2011, 89:2050-2060.
  • [21]Elzo MA, Lamb GC, Johnson DD, Thomas MG, Misztal I, Rae DO, Martinez CA, Wasdin JG, Driver JD: Genomic-polygenic evaluation of Angus-Brahman multibreed cattle for feed efficiency and postweaning growth using the Illumina 3 K chip. J Anim Sci 2012, 90:2488-2497.
  • [22]Rolf MM, Taylor JF, Schnabel RD, Mckay SD, McClure MC, Northcutt SL, Kerley MS, Weaber RL: Genome-wide association analysis for feed efficiency in Angus cattle. Anim Genet 2011, 43:367-374.
  • [23]Barendse W, Reverter A, Bunch RJ, Harrison BE, Barris W, Thomas MB: A validated whole-genome association study of efficient food conversion in cattle. Genetics 2007, 176:1893-1905.
  • [24]Sherman EL, Nkrumah JD, Li C, Bartusiak R, Murdoch B, Moore SS: Fine mapping quantitative trait loci for feed intake and feed efficiency in beef cattle. J Anim Sci 2009, 87(1):37-45.
  • [25]Karisa BK, Thomson J, Wang Z, Stothard P, Moore SS, Plastow GS: Candidate genes and single nucleotide polymorphisms associated with variation in residual feed intake in beef cattle. J Anim Sci 2013, 91(8):3502-3513.
  • [26]Jones BL, Kearns GL: Histamine: new thoughts about a familia mediator. Clin Pharmacol Ther 2011, 89:189-197.
  • [27]Rangachari PK: Histamine: mercurial messenger in the gut. Am J PhysiolGastrointest Liver Physiol 1992, 262:G1-G13.
  • [28]Ji Y, Sakata Y, Li X, Zhang C, Yang Q, Xu M, Wollin A, Langhans W, Tso P: Lymphatic diamine oxidase secretion stimulated by fat absorption is linked with histamine release. Am J Physiol Gastrointest Liver Physiol 2013, 304(8):G732-G740.
  • [29]Welle S, Barnard RR, Statt M, Amatruda JM: Increased protein turnover in obese women. Metabolism 1992, 41(9):1028-1034.
  • [30]Berg JM, Tymoczko JL, Stryer L: Biochemistry. W H Freeman, New York; 2002.
  • [31]Visinoni S, Khalid NF, Joannides CN: The role of liver fructose-1,6-bisphosphatase in regulating appetite and adiposity. Diabetes 2012, 61:1122-1132.
  • [32]Joo JI, Oh TS, Kim DH, Choi DK, Wang X, Choi JW, Yun JW: Differential expression of adipose tissue proteins between obesity-susceptible and -resistant rats fed a high-fat diet. Proteomics 2011, 11:1-20.
  • [33]Kalopissis AD, Pastier D, Chambaz J: Apolipoprotein A-II: Beyond genetic associations with lipid disorders and insulin resistance. Curr Opin Lipidol 2003, 14:165-172.
  • [34]Corella D, Tai ES, Sorlí JV, Chew SK, Coltell O, SotosPrieto M, García-Rios A, Estruch R, Ordovas JM: Association between the APOA2 promoter polymorphism and body weight in Mediterranean and Asian populations: Replication of a gene-saturated fat interaction. Int J Obes 2011, 35:666-675.
  • [35]Fontanesi L, Galimberti G, Calò DG, Fronza R, Martelli PL, Scotti E, Colombo M, Schiavo G, Casadio R, Buttazzoni L, Russo V: Identification and association analysis of several hundred single nucleotide poly morphisms within candidate genes for back fat thickness in Italian Large White pigs using a selective genotyping approach. J Anim Sci 2012, 90:2450-2464.
  • [36]Ernst A, Avvakumov G, Tong J, Fan Y, Zhao Y, Alberts P, Persaud A, Walker JR, Neculai AM, Neculai D, Vorobyov A, Garg P, Beatty L, Chan PK, Juang YC, Landry MC, Yeh C, Zeqiraj E, Karamboulas K, Allali-Hassani A, Vedadi M, Tyers M, Moffat J, Sicheri F, Pelletier L, Durocher D, Raught B, Rotin D, Yang J, Moran MF, et al.: A strategy for modulation of enzymes in the ubiquitin system. Science 2013, 1:339(6119):590-595. doi: 10.1126/science.1230161
  • [37]Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry MJ, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G: Gene ontology: tool for the unification of biology. Nat Genet 2000, 25:25-29.
  • [38]Karisa B, Moore S, Plastow G: Analysis of biological networks and biological pathways associated with residual feed intake in beef cattle. Anim Sci J 2013, ᅟ:374-387. doi:10.1111/asj.12159
  • [39]Ng MC, Tam CH, So WY, Ho JS, Chan AW, Lee HM, Wang Y, Lam VK, Chan JC, Ma RC: Implication of genetic variants near NEGR1, SEC16B, TMEM18, ETV5/DGKG, GNPDA2, LIN7C/BDNF, MTCH2, BCDIN3D/FAIM2, SH2B1, FTO, MC4R, and KCTD15 with Obesity and Type 2 Diabetes in 7705 Chinese. Clin Endocrinol Metab 2010, 95(5):2418-2425.
  • [40]Fradette J, Wolfe D, Goins WF, Huang S, Flanigan RM, Glorioso JC: HSV vector-mediated transduction and GDNF secretion from adipose cells. Gene Ther 2005, 12:48-58.
  • [41]Richard AJ, Stephens JM: Emerging roles of JAK-STAT signaling pathways in adipocytes. Trends Endocrinol Metab 2011, 22:325-332.
  • [42]Richardson EC, Herd RM: Biological basis for variation in residual feed intake in beef cattle. Synthesis of results following divergent selection. Aust J Exp Agric 2002, 44:431-440.
  • [43]Abo-Ismail M, Kelly M: Identification of single nucleotide polymorphisms in genes involved in digestive and metabolic processes associated with feed efficiency and performance traits in beef. J Anim Sci 2013, ᅟ:2512-2529. doi:10.2527/jas2012-5756
  • [44]Hossain MS, Chowdhury AA, Rahman MS, Nishimura K, Jisaka M, Nagaya T: Development of enzyme-linked immunosorbent assay forΔ12-PGJ2and its application to the measurement of the endogenous product generated by cultured adipocytes during the maturation phase. Prostaglandins Other Lipid Mediat 2011, 94:73-80.
  • [45]Rahman MS, Syeda PK, Khan F, Nishimura K, Jisaka M, Nagaya T, Shono F, Yokota K: Cultured preadipocytes undergoing stable transfection with cyclooxygenase-1 in the antisense direction accelerate adipogenesis during the maturation phase of adipocytes. Appl Biochem Biotechnol 2013, 171(1):128-144.
  • [46]Liu S, Wiggins JF, Sreenath T, Kulkarni AB, Ward JM, Leppla S: Dph3, a small protein required for diphthamide biosynthesis, is essential in mouse development. Mol Cell Biol 2006, 26(10):3835-3841.
  • [47]Bär C, Zabel R, Liu S, Stark MJR, Schaffrath R: A versatile partner of eukaryotic protein complexes that is involved in multiple biological processes: Kti11/Dph3. Mol Microbiol 2008, 69(5):1221-1233. doi:10.1111/j.1365-2958.2008.06350
  • [48]Skelding KA, Rostas JAP, Verrills NM: Controlling the cell cycle: The role of calcium/calmodulin-stimulated protein kinases I and II. Cell Cycle 2011, 10(4):631-639. doi:10.4161/cc.10.4.14798
  • [49]Shetty PB, Tang H, Tayo BO, Morrison AC, Hanis CL, Rao DC, Young JH, Fox ER, Boerwinkle E, Cooper RS, Risch NJ, Zhu X: Variants in CXADR and F2RL1 are associated with blood pressure and obesity in African-Americans in regions identified through admixture mapping. J Hypertens 2012, 30(10):1970-1976.
  • [50]Lisewski U, Shi Y, Wrackmeyer U, Fischer R, Chen C, Schirdewan A, Jüttner R, Rathjen F, Poller W, Radke MH, Gotthardt M: The tight junction protein CAR regulates cardiac conduction and cell-cell communication. J Exp Med 2008, 205(10):2369-2379.
  • [51]Coles C, Wadeson J: A disintegrin and metalloprotease-12 is type I myofiber specific in Bos taurus and Bos indicus cattle. J Anim 2014, ᅟ:1473-1483. doi:10.2527/jas2013-7069
  • [52]Cao Y, Zhao Z, Gruszczynska-Biegala J, Zolkiewska A: Role of metalloprotease disintegrin ADAM 12 in determination of quiescent reserve cells during myogenic differentiation in vitro. Mol Cell Biol 2003, 23:6725-6738.
  • [53]Kawaguchi N, Sundberg C, Kveiborg M, Moghadaszadeh B, Asmar M, Dietrich N, Thodeti CK, Moller P, Mercurio AM, Albrechtsen R, Wewer U: ADAM12 induces actin cytoskeleton and extracellular matrix reorganization during early adipocyte differentiation by regulating beta1 integrin function. J Cell Sci 2003, 116:3893-3904.
  • [54]Kim YM, Kim J, Heo SC, Shin SH, Do EK: Proteomic identification of ADAM12 as a regulator for TGF-b1-induced differentiation of human mesenchymal stem cells to smooth muscle cells. PLoS One 2012, 7(7):e40820.
  • [55]Goll DE, Kleese WC, Szpacenko A: Skeletal Muscle Proteases and Protein Turnover. In Animal Growth Regulation. Edited by Campion DR, Hausman GJ, Martin RJ. Plenum Press, New York; 1989:141-183.
  • [56]Maltin C, Delday M, Sinclair K, Steven J, Sneddon A: Impact of manipulations of myogenesis in utero on the performance of adult skeletal muscle. Reproduction 2001, 122:359-374.
  • [57]Metzger T, Gache V, Xu M, Cadot B, Folker ES, Richardson BE, Baylies MK: MAP and kinesin-dependent nuclear positioning is required for skeletal muscle function. Nature 2012, 484(7392):120-124. doi:10.1038/nature10914
  • [58]Braverman N, Zhang R, Chen L, Nimmo G, Scheper S, Tran T, Chaudhury R, Moser A, Steinberg S: A Pex7 hypomorphic mouse model for plasmalogen deficiency affecting the lens and skeleton. Mol Genet Metab 2010, 99:408-416.
  • [59]McClure MC, Morsci NS, Schabel RD, Kim JW, Yao P, Rolf MM, McKay SD, Gregg SJ, Chapple RH, Northcutt SL, Taylor JF: A genome scan for quantitative trait loci influencing carcass, post-natal growth and reproductive traits in commercial Angus cattle. Anim Genet 2010, 41:597-607.
  • [60]Peters S, Kizilkaya K: Bayesian genome-wide association analysis of growth and yearling ultrasound measures of carcass traits in Brangus heifers. J Anim Sci 2012, ᅟ:3398-3409. doi:10.2527/jas2012-4507
  • [61]Veneroni GB, Meirelles SL, Grossi D, Gasparin G, Ibelli AMG, Tizioto PC, Regitano LCA: Prospecting candidate SNPs for backfat in Canchim beef cattle. Genet Mol Res 2010, 9(4):1997-2003. doi:10.4238/vol9-4gmr788
  • [62]Pryce JE, Arias J, Bowman PJ, Davis SR, Macdonald KA, Waghorn GC, Wales WJ, Williams YJ, Spelman RJ, Hayes BJ: Accuracy of genomic predictions of residual feed 14 intake and 250 day bodyweight in 15 growing heifers using 625,000 SNP markers. J Dairy Sci 2012, 95:2108-2119.
  • [63]Do DN, Strathe AB, Ostersen T, Jensen J, Mark T, Kadarmideen HN: Genome-wide association study reveals genetic architecture of eating behavior in pigs and its implications for humans obesity by comparative mapping. PLoS One 2013, 8(8):e71509.
  • [64]Casas E, Shackelford SD, Keele JW, Koohmaraie M, Smith TPL, Stone RT: Detection of quantitative trait loci for growth and carcass composition in cattle. J Anim Sci 2003, 81:2976-2983.
  • [65]Tizioto PC, Decker JE, Taylor JF, Schnabel RD, Mudadu MA, Silva FL, Regitano LCA: Genome scan for meat quality traits in Nelore beef cattle. Physiol Genomics 2013, 45(21):1012-1020. doi:10.1152/physiolgenomics.00066.2013
  • [66]Zinn A, Shen YA: An evaluation of ruminal degradable intake protein and metabolizable amino acid requirements of feedlot calves. J Anim Sci 1998, 76:1280-1289.
  • [67]Base SAS® 9.2 Procedures Guide. SAS Institute Inc., Cary, NC; 2010.
  • [68]Garrick DJ, Fernando RL: Implementing a QTL detection study [GWAS] using genomic prediction methodology. Methods Mol Biol 2013, 1019:275-298.
  • [69]Onteru SK, Fan B, Nikkila MT, Garrick DJ, Stalder KJ, Rothschild MF: Whole-genome association analyses for lifetime reproductive traits in pig. J Anim Sci 2011, 89:988-995.
  • [70]Peters S, Kizilkaya K: Heritability and Bayesian genome-wide association study of first service conception and pregnancy in Brangus heifers. J Anim 2013, ᅟ:605-612. doi:10.2527/jas2012-5580
  • [71]Kizilkaya K, Fernando RL, Garrick DJ: Genomic prediction of simulated multibreed and purebred performance using observed fifty thousand single nucleotide polymorphism genotypes. J Anim Sci 2010, 88:544-551.
  • [72]Habier D, Fernando RL, Kizilkaya K, Garrick DJ: Extension of the Bayesian alphabet for genomic selection. BMC Bioinformatics 2011, 12:186. BioMed Central Full Text
  • [73]Cesar AS, Regitano LC, Tullio RR, Lanna DP, Nassu RT, Mudado MA, Coutinho LL: Genome-wide association study for intramuscular fat deposition and composition in Nellore cattle. BMC Genet 2014, 15(1):39. doi:10.1186/1471-2156-15-39 BioMed Central Full Text
  • [74]Fernando R, Garrick DJ: User Manual For A Portfolio Of Genomic Selection Related Analyses, 2nd Ed. For Version 2.12. In Animal Breeding and Genetics. 2nd edition. Iowa State University, Ames, IA; 2009.
  • [75]Huang DW, Sherman BT, Lempicki RA: Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 2009, 37:1-13.
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