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Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with the feed conversion ratio in beef cattle (2016)

  • Authors:
  • USP affiliated authors: SILVA, SAULO DA LUZ E - FZEA ; LEME, PAULO ROBERTO - FZEA ; FUKUMASU, HEIDGE - FZEA ; COUTINHO, LUIZ LEHMANN - ESALQ ; FERRAZ, JOSE BENTO STERMAN - FZEA
  • USP Schools: FZEA; FZEA; FZEA; ESALQ; FZEA
  • DOI: 10.1007/s13353-016-0344-7
  • Subjects: ALIMENTOS PARA ANIMAIS; BOVINOS DE CORTE; GENÔMICA; MELHORAMENTO GENÉTICO ANIMAL; GADO NELORE (METABOLISMO)
  • Language: Inglês
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    Informações sobre o DOI: 10.1007/s13353-016-0344-7 (Fonte: oaDOI API)
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    Versões disponíveis em Acesso Aberto do: 10.1007/s13353-016-0344-7 (Fonte: Unpaywall API)

    Título do periódico: Journal of Applied Genetics

    ISSN: 1234-1983,2190-3883



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  • Título: Journal of Applied Genetics

    ISSN: 1234-1983

    Citescore - 2017: 1.58

    SJR - 2017: 0.704

    SNIP - 2017: 0.7


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    • ABNT

      SANTANA, Miguel Henrique de Almeida; OLIVEIRA JUNIOR, Gerson Antônio; CESAR, Aline Silva Mello; et al. Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with the feed conversion ratio in beef cattle. Journal of Applied Genetics, Heidelberg, v. No 2016, n. 4, p. 495-504, 2016. Disponível em: < http://dx.doi.org/10.1007/s13353-016-0344-7 > DOI: 10.1007/s13353-016-0344-7.
    • APA

      Santana, M. H. de A., Oliveira Junior, G. A., Cesar, A. S. M., Freua, M. C., Gomes, R. da C., Silva, S. da L. e, et al. (2016). Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with the feed conversion ratio in beef cattle. Journal of Applied Genetics, No 2016( 4), 495-504. doi:10.1007/s13353-016-0344-7
    • NLM

      Santana MH de A, Oliveira Junior GA, Cesar ASM, Freua MC, Gomes R da C, Silva S da L e, Leme PR, Fukumasu H, Carvalho ME, Ventura RV, Coutinho LL, Kadarmideen HN, Ferraz JBS. Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with the feed conversion ratio in beef cattle [Internet]. Journal of Applied Genetics. 2016 ; No 2016( 4): 495-504.Available from: http://dx.doi.org/10.1007/s13353-016-0344-7
    • Vancouver

      Santana MH de A, Oliveira Junior GA, Cesar ASM, Freua MC, Gomes R da C, Silva S da L e, Leme PR, Fukumasu H, Carvalho ME, Ventura RV, Coutinho LL, Kadarmideen HN, Ferraz JBS. Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with the feed conversion ratio in beef cattle [Internet]. Journal of Applied Genetics. 2016 ; No 2016( 4): 495-504.Available from: http://dx.doi.org/10.1007/s13353-016-0344-7

    Referências citadas na obra
    Alexandre PA, Kogelman LJA, Santana MHA et al 2015. Liver transcriptomic networks reveal main biological processes associated with feed efficiency in beef cattle. BMC Genomics 16:1073 doi: 10.1186/s12864-015-2292-8
    Arthur PF, Archer JA, Johnston DJ, Herd RM, Richardson EC, Parnell PF (2001) Genetic and phenotypic variance and covariance components for feed intake, feed efficiency, and other postweaning traits in Angus cattle. J Anim Sci 79:2805–2811
    Arthur PF, Archer JA, Herd RM (2004) Feed intake and efficiency in beef cattle: overview of recent Australian research and challenges for the future. Aust J Exp Agric 44:361–369. doi: 10.1071/EA02162
    Barendse W, Reverter A, Bunch RJ, Harrison BE, Barris W, Thomas MB (2007) A validated whole-genome association study of efficient food conversion in cattle. Genetics 176:1893–1905. doi: 10.1534/genetics.107.072637
    Bickhart DM, Liu GE (2014) The challenges and importance of structural variation detection in livestock. Front Genet 5:37. doi: 10.3389/fgene.2014.00037
    Bishop SC, Woolliams JA (2014) Genomics and disease resistance studies in livestock. Livest Sci 166:190–198. doi: 10.1016/j.livsci.2014.04.034
    Bolormaa S, Hayes BJ, Savin K et al (2011) Genome-wide association studies for feedlot and growth traits in cattle. J Anim Sci 89:1684–1697. doi: 10.2527/jas.2010-3079
    Carbonetto P, Stephens M (2013) Integrated enrichment analysis of variants and pathways in genome-wide association studies indicates central role for IL-2 signaling genes in type 1 diabetes, and cytokine signaling genes in Crohn’s disease. PLoS Genet 9:e1003770. doi: 10.1371/journal.pgen.1003770
    Castro Bulle FCP, Paulino PV, Sanches AC, Sainz RD (2007) Growth, carcass quality, and protein and energy metabolism in beef cattle with different growth potentials and residual feed intakes. J Anim Sci 85:928–936. doi: 10.2527/jas.2006-373
    Cesar ASM, Regitano LCA, Mourão GB et al (2014) Genome-wide association study for intramuscular fat deposition and composition in Nellore cattle. BMC Genet 15:39. doi: 10.1186/1471-2156-15-39
    Clop A, Vidal O, Amills M (2012) Copy number variation in the genomes of domestic animals. Anim Genet 43:503–517. doi: 10.1111/j.1365-2052.2012.02317.x
    Dellinger AE, Saw SM, Goh LK, Seielstad M, Young TL, Li YJ (2010) Comparative analyses of seven algorithms for copy number variant identification from single nucleotide polymorphism arrays. Nucleic Acids Res 38:1–14. doi: 10.1093/nar/gkq040
    Do DN, Strathe AB, Ostersen T, Pant SD, Kadarmideen HN (2014) Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake. Front Genet 5:307. doi: 10.3389/fgene.2014.00307
    Fernando RL, Garrick DJ (2008) GenSel—User manual for a portfolio of genomic selection related analyses
    Garrick DJ, Fernando RL (2013) Implementing a QTL detection study (GWAS) using genomic prediction methodology. Methods Mol Biol 1019:275–298. doi: 10.1007/978-1-62703-447-0_11
    Gomes RC, Silva SL, Carvalho ME et al (2013) Protein synthesis and degradation gene SNPs related to feed intake, feed efficiency, growth, and ultrasound carcass traits in Nellore cattle. Genet Mol Res 12:2923–2936
    Gurgul A, Jasielczuk I, Szmatoła T et al (2015) Genome-wide characteristics of copy number variation in Polish Holstein and Polish Red cattle using SNP genotyping assay. Genetica 143(2):145–155. doi: 10.1007/s10709-015-9822-9
    Habier D, Fernando RL, Kizilkaya K, Garrick DJ (2011) Extension of the bayesian alphabet for genomic selection. BMC Bioinformatics 12:186. doi: 10.1186/1471-2105-12-186
    Hayes BJ, Chamberlain AJ, McPartlan H, Macleod I, Sethuraman L, Goddard ME (2007) Accuracy of marker-assisted selection with single markers and marker haplotypes in cattle. Genet Res 89:215–220. doi: 10.1017/S0016672307008865
    Herd RM, Arthur PF (2009) Physiological basis for residual feed intake. J Anim Sci 87:E64–E71. doi: 10.2527/jas.2008-1345
    Hoque MA, Hosono M, Oikawa T, Suzuki K (2009) Genetic parameters for measures of energetic efficiency of bulls and their relationships with carcass traits of field progeny in Japanese Black cattle. J Anim Sci 87:99–106. doi: 10.2527/jas.2007-0766
    Hou Y, Bickhart DM, Chung H et al (2012a) Analysis of copy number variations in Holstein cows identify potential mechanisms contributing to differences in residual feed intake. Funct Integr Genomics 12:717–723. doi: 10.1007/s10142-012-0295-y
    Hou Y, Bickhart DM, Hvinden ML et al (2012b) Fine mapping of copy number variations on two cattle genome assemblies using high density SNP array. BMC Genomics 13:376. doi: 10.1186/1471-2164-13-376
    Huang DW, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4:44–57. doi: 10.1038/nprot.2008.211
    Jang Y-N, Baik EJ (2013) JAK-STAT pathway and myogenic differentiation. JAK-STAT 2:e23282. doi: 10.4161/jkst.23282
    Kadarmideen HN (2014) Genomics to systems biology in animal and veterinary sciences: Progress, lessons and opportunities. Livest Sci 166:232–248. doi: 10.1016/j.livsci.2014.04.028
    Kadri NK, Koks PD, Meuwissen TH (2012) Prediction of a deletion copy number variant by a dense SNP panel. Genet Sel Evol 44:7. doi: 10.1186/1297-9686-44-7
    Karisa B, Moore S, Plastow G (2014) Analysis of biological networks and biological pathways associated with residual feed intake in beef cattle. Anim Sci J 85:374–387. doi: 10.1111/asj.12159
    Kelly AK, Waters SM, McGee M, Fonseca RG, Carberry C, Kenny DA (2011) mRNA expression of genes regulating oxidative phosphorylation in the muscle of beef cattle divergently ranked on residual feed intake. Physiol Genomics 43:12–23. doi: 10.1152/physiolgenomics.00213.2009
    Kijas JW, Barendse W, Barris W et al (2011) Analysis of copy number variants in the cattle genome. Gene 482:73–77. doi: 10.1016/j.gene.2011.04.011
    Kim J-H, Hu H-J, Yim S-H, Bae JS, Kim S-Y, Chung Y-J (2012) CNVRuler: a copy number variation-based case–control association analysis tool. Bioinformatics 28:1790–1792. doi: 10.1093/bioinformatics/bts239
    Kinsella RJ, Kähäri A, Haider S et al (2011) Ensembl BioMarts: a hub for data retrieval across taxonomic space. Database (Oxford) 2011:bar030. doi: 10.1093/database/bar030
    Lindholm-Perry AK, Kern RJ, Kuehn LA et al (2015) Differences in transcript abundance of genes on BTA15 located within a region associated with gain in beef steers. Gene 572:42–48. doi: 10.1016/j.gene.2015.06.076
    Liu GE, Hou Y, Zhu B et al (2010) Analysis of copy number variations among diverse cattle breeds. Genome Res 20:693–703. doi: 10.1101/gr.105403.110
    Lkhagvadorj S, Qu L, Cai W et al (2010) Gene expression profiling of the short-term adaptive response to acute caloric restriction in liver and adipose tissues of pigs differing in feed efficiency. Am J Physiol Regul Integr Comp Physiol 298:R494–R507. doi: 10.1152/ajpregu.00632.2009
    Lu D, Miller S, Sargolzaei M et al (2013) Genome-wide association analyses for growth and feed efficiency traits in beef cattle. J Anim Sci 91:3612–3633. doi: 10.2527/jas.2012-5716
    Mamiya PC, Hennesy Z, Zhou R, Wagner GC (2008) Changes in attack behavior and activity in EphA5 knockout mice. Brain Res 1205:91–99. doi: 10.1016/j.brainres.2008.02.047
    Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829
    Moore KL, Johnston DJ, Graser H-U, Herd R (2005) Genetic and phenotypic relationships between insulin-like growth factor-I (IGF-I) and net feed intake, fat, and growth traits in Angus beef cattle. Aust J Agric Res 56:211–218. doi: 10.1071/AR04248
    Moore SS, Mujibi FD, Sherman EL (2009) Molecular basis for residual feed intake in beef cattle. J Anim Sci 87:E41–E47. doi: 10.2527/jas.2008-1418
    Nkrumah JD, Sherman EL, Li C et al (2007) Primary genome scan to identify putative quantitative trait loci for feedlot growth rate, feed intake, and feed efficiency of beef cattle. J Anim Sci 85:3170–3181. doi: 10.2527/jas.2007-0234
    Onteru SK, Fan B, Nikkilä MT, Garrick DJ, Stalder KJ, Rothschild MF (2011) Whole-genome association analyses for lifetime reproductive traits in the pig. J Anim Sci 89:988–995. doi: 10.2527/jas.2010-3236
    Palouzier-Paulignan B, Lacroix M-C, Aimé P et al (2012) Olfaction under metabolic influences. Chem Senses 37:769–797. doi: 10.1093/chemse/bjs059
    Pérez O’Brien AM, Utsunomiya YT, Mészáros G et al (2014) Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle. Genet Sel Evol 46:19. doi: 10.1186/1297-9686-46-19
    Plata-Salamán CR (2001) Cytokines and feeding. Int J Obes Relat Metab Disord 25(Suppl 5):S48–S52. doi: 10.1038/sj.ijo.0801911
    R Development Core Team (2008) R: A language and environment for statistical computing
    Redon R, Ishikawa S, Fitch KR et al (2006) Global variation in copy number in the human genome. Nature 444:444–454. doi: 10.1038/nature05329
    Richardson EC, Herd RM (2004) Biological basis for variation in residual feed intake in beef cattle. 2. Synthesis of results following divergent selection. Aust J Exp Agric 44:431–440. doi: 10.1071/EA02221
    Ritchie MD, Holzinger ER, Li R, Pendergrass SA, Kim D (2015) Methods of integrating data to uncover genotype–phenotype interactions. Nat Rev Genet 16:85–97. doi: 10.1038/nrg3868
    Rolf MM, Taylor JF, Schnabel RD et al (2012) Genome-wide association analysis for feed efficiency in Angus cattle. Anim Genet 43:367–374. doi: 10.1111/j.1365-2052.2011.02273.x
    Santana MHA, Rossi Junior P, Almeida RD, Schuntzemberger AMDS (2013) Blood cell and metabolic profile of Nellore bulls and their correlations with residual feed intake and feed conversion ratio. Rev Bras Saúde e Produção Anim 14:527–537. doi: 10.1590/S1519-99402013000300018
    Santana MHA, Utsunomiya YT, Neves HHR et al (2014a) Genome-wide association study for feedlot average daily gain in Nellore cattle (Bos indicus). J Anim Breed Genet 131:210–216. doi: 10.1111/jbg.12084
    Santana MHA, Utsunomiya YT, Neves HHR et al (2014b) Genome-wide association analysis of feed intake and residual feed intake in Nellore cattle. BMC Genet 15:21. doi: 10.1186/1471-2156-15-21
    Santana MHA, Ventura RV, Utsunomiya YT et al (2015) A genomewide association mapping study using ultrasound-scanned information identifies potential genomic regions and candidate genes affecting carcass traits in Nellore cattle. J Anim Breed Genet 132:420–427. doi: 10.1111/jbg.12167
    Sargolzaei M, Chesnais JP, Schenkel FS (2014) A new approach for efficient genotype imputation using information from relatives. BMC Genomics 15:478. doi: 10.1186/1471-2164-15-478
    Scherer SW, Lee C, Birney E et al (2007) Challenges and standards in integrating surveys of structural variation. Nat Genet 39:S7–S15. doi: 10.1038/ng2093
    Senn JJ (2006) Toll-like receptor-2 is essential for the development of palmitate-induced insulin resistance in myotubes. J Biol Chem 281:26865–26875. doi: 10.1074/jbc.M513304200
    Seroussi E, Glick G, Shirak A et al (2010) Analysis of copy loss and gain variations in Holstein cattle autosomes using BeadChip SNPs. BMC Genomics 11:673. doi: 10.1186/1471-2164-11-673
    Sherman EL, Nkrumah JD, Murdoch BM et al (2008) Polymorphisms and haplotypes in the bovine neuropeptide Y, growth hormone receptor, ghrelin, insulin-like growth factor 2, and uncoupling proteins 2 and 3 genes and their associations with measures of growth, performance, feed efficiency, and carcass merit in beef cattle. J Anim Sci 86:1–16. doi: 10.2527/jas.2006-799
    Sherman EL, Nkrumah JD, Li C, Bartusiak R, Murdoch B, Moore SS (2009) Fine mapping quantitative trait loci for feed intake and feed efficiency in beef cattle. J Anim Sci 87:37–45. doi: 10.2527/jas.2008-0876
    Sherman EL, Nkrumah JD, Moore SS (2010) Whole genome single nucleotide polymorphism associations with feed intake and feed efficiency in beef cattle. J Anim Sci 88:16–22. doi: 10.2527/jas.2008-1759
    Snelling WM, Allan MF, Keele JW et al (2011) Partial-genome evaluation of postweaning feed intake and efficiency of crossbred beef cattle. J Anim Sci 89:1731–1741. doi: 10.2527/jas.2010-3526
    Stick DA, Davis ME, Loerch SC, Simmen RC (1998) Relationship between blood serum insulin-like growth factor I concentration and postweaning feed efficiency of crossbred cattle at three levels of dietary intake. J Anim Sci 76:498–505
    Tamari M, Tanaka S, Hirota T (2013) Genome-wide association studies of allergic diseases. Allergol Int 62:21–28. doi: 10.2332/allergolint.13-RAI-0539
    Veerkamp RF, Coffey MP, Berry DP et al (2012) Genome-wide associations for feed utilisation complex in primiparous Holstein-Friesian dairy cows from experimental research herds in four European countries. Animal 6:1738–1749. doi: 10.1017/S1751731112001152
    Wang K, Li M, Hadley D et al (2007) PennCNV: an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data. Genome Res 17:1665–1674. doi: 10.1101/gr.6861907
    Wannemacher RW Jr, Wannemacher CF, Yatvin MB (1971) Amino acid regulation of synthesis of ribonucleic acid and protein in the liver of rats. Biochem J 124:385–392
    Winchester L, Yau C, Ragoussis J (2009) Comparing CNV detection methods for SNP arrays. Brief Funct Genomic Proteomic 8:353–366. doi: 10.1093/bfgp/elp017
    Wu Y, Fan H, Jing S et al (2015) A genome-wide scan for copy number variations using high-density single nucleotide polymorphism array in Simmental cattle. Anim Genet 46(3):289–298. doi: 10.1111/age.12288
    Xu L, Cole JB, Bickhart DM et al (2014a) Genome wide CNV analysis reveals additional variants associated with milk production traits in Holsteins. BMC Genomics 15:683. doi: 10.1186/1471-2164-15-683
    Xu L, Hou Y, Bickhart DM et al (2014b) A genome-wide survey reveals a deletion polymorphism associated with resistance to gastrointestinal nematodes in Angus cattle. Funct Integr Genomics 14:333–339. doi: 10.1007/s10142-014-0371-6
    Yan X, Zhu MJ, Xu W et al (2010) Up-regulation of Toll-like receptor 4/nuclear factor-kappaB signaling is associated with enhanced adipogenesis and insulin resistance in fetal skeletal muscle of obese sheep at late gestation. Endocrinology 151:380–387. doi: 10.1210/en.2009-0849
    Zhang F, Gu W, Hurles ME, Lupski JR (2009) Copy number variation in human health, disease, and evolution. Annu Rev Genomics Hum Genet 10:451–481. doi: 10.1146/annurev.genom.9.081307.164217