BMC Genomics | |
A genome-wide association analysis for porcine serum lipid traits reveals the existence of age-specific genetic determinants | |
Marcel Amills5  Jules Hernández-Sánchez4  Nitdia Aznárez4  Anna Castelló5  Anna Mercadé5  Joan Tibau3  Ramona N Pena1  Rayner González-Prendes2  Raquel Quintanilla4  Joaquim Casellas5  Arianna Manunza2  | |
[1] Departament de Producció Animal, Agrotecnio Center, Universitat de Lleida, Lleida 25198, Spain;Department of Animal Genetics, Center for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB), Universitat Autònoma de Barcelona, Bellaterra 08193, Spain;IRTA, Finca Camps i Armet, 17121 Monells, Spain;IRTA, Genètica i Millora Animal, Lleida 25198, Spain;Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain | |
关键词: Gene expression; Genome-wide analysis; Lipids and lipoproteins; Animal model; | |
Others : 1140921 DOI : 10.1186/1471-2164-15-758 |
|
received in 2013-09-12, accepted in 2014-07-25, 发布年份 2014 | |
【 摘 要 】
Background
The genetic determinism of blood lipid concentrations, the main risk factor for atherosclerosis, is practically unknown in species other than human and mouse. Even in model organisms, little is known about how the genetic determinants of lipid traits are modulated by age-specific factors. To gain new insights into this issue, we have carried out a genome-wide association study (GWAS) for cholesterol (CHOL), triglyceride (TRIG) and low (LDL) and high (HDL) density lipoprotein concentrations measured in Duroc pigs at two time points (45 and 190 days).
Results
Analysis of data with mixed-model methods (EMMAX, GEMMA, GenABEL) and PLINK showed a low positional concordance between trait-associated regions (TARs) for serum lipids at 45 and 190 days. Besides, the proportion of phenotypic variance explained by SNPs at these two time points was also substantially different. The four analyses consistently detected two regions on SSC3 (124 Mb, CHOL and LDL at 190 days) and SSC6 (135 Mb, CHOL and TRIG at 190 days) with highly significant effects on the porcine blood lipid profile. Moreover, we have found that SNP variation within SSC3, SSC6, SSC10, SSC13 and SSC16 TARs is associated with the expression of several genes mapping to other chromosomes and related to lipid metabolism.
Conclusions
Our data demonstrate that the effects of genomic determinants influencing lipid concentrations in pigs, as well as the amount of phenotypic variance they explain, are influenced by age-related factors.
【 授权许可】
2014 Manunza et al.; licensee BioMed Central Ltd.
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
20150325152919189.pdf | 302KB | download |
【 参考文献 】
- [1]Wang X, Paigen B: Genetics of variation in HDL cholesterol in humans and mice. Circ Res 2005, 96:27-42.
- [2]Leduc MS, Hageman RS, Verdugo RA, Tsaih SW, Walsh K, Churchill GA, Paigen B: Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice. J Lipid Res 2011, 52:1672-1682.
- [3]Mustard JF, Packham MA: The unrealized potential of animal diseases in the study of human diseases. Can Med Assoc J 1968, 98:887-890.
- [4]Casellas J, Vidal O, Pena RN, Gallardo D, Manunza A, Quintanilla R, Amills M: Genetics of serum and muscle lipids in pigs. Anim Genet 2013, 44:609-619.
- [5]Gallardo D, Pena RN, Amills M, Varona L, Ramírez O, Reixach J, Díaz I, Tibau J, Soler J, Prat-Cuffi JM, Noguera JL, Quintanilla R: Mapping of quantitative trait loci for cholesterol, LDL, HDL, and triglyceride serum concentrations in pigs. Physiol Genomics 2008, 35:199-209.
- [6]Chen R, Ren J, Li W, Huang X, Yan X, Yang B, Zhao Y, Guo Y, Mao H, Huang L: A genome-wide scan for quantitative trait loci affecting serum glucose and lipids in a White Duroc x Erhualian intercross F2 population. Mamm Genome 2009, 20:386-392.
- [7]Uddin MJ, Duy Do N, Cinar MU, Tesfaye D, Tholen E, Juengst H, Looft C, Schellander K: Detection of quantitative trait loci affecting serum cholesterol, LDL, HDL, and triglyceride in pigs. BMC Genet 2011, 12:62.
- [8]Yoo CK, Cho IC, Lee JB, Jung EJ, Lim HT, Han SH, Lee SS, Ko MS, Kang T, Hwang JH, Park YS, Park HB: QTL analysis of clinical-chemical traits in an F2 intercross between Landrace and Korean native pigs. Physiol Genomics 2012, 44:657-668.
- [9]Chen C, Yang B, Zeng Z, Yang H, Liu C, Ren J, Huang L: Genetic dissection of blood lipid traits by integrating genome-wide association study and gene expression profiling in a porcine model. BMC Genomics 2013, 14:848. BioMed Central Full Text
- [10]Snieder H, van Doornen LJ, Boomsma DI: Dissecting the genetic architecture of lipids, lipoproteins, and apolipoproteins: lessons from twin studies. Arterioscler Thromb Vasc Biol 1999, 19:2826-2834.
- [11]Casellas J, Noguera JL, Reixach J, Díaz I, Amills M, Quintanilla R: Bayes factor analyses of heritability for serum and muscle lipid traits in Duroc pigs. J Anim Sci 2010, 88:2246-2254.
- [12]Cánovas A, Quintanilla R, Amills M, Pena RN: Muscle transcriptomic profiles in pigs with divergent phenotypes for fatness traits. BMC Genomics 2010, 11:372-392. BioMed Central Full Text
- [13]Xu X, Zhao Y, Simon R: Gene set expression comparison kit for BRB-ArrayTools. Bioinformatics 2008, 24:137-139.
- [14]Naraballobh W, Chomdej S, Murani E, Wimmers K, Ponsuksili S: Annotation and in silico localization of the Affymetrix GeneChip porcine genome array. Archiv Tierzucht 2010, 53:230-238.
- [15]Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC: PLINK: a toolset for whole-genome association and population-based linkage analysis. Am J Hum Genet 2007, 81:559-575.
- [16]Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB, Sabatti C, Eskin E: Variance component model to account for sample structure in genome-wide association studies. Nat Genet 2010, 42:348-354.
- [17]Aulchenko YS, Ripke S, Isaacs A, van Duijn CM: GenABEL: an R library for genome-wide association analysis. Bioinformatics 2007, 23:1294-1296.
- [18]Zhou X, Stephens M: Genome-wide efficient mixed-model analysis for association studies. Nature Genet 2012, 44:821-824.
- [19]Benjamini Y, Hochberg Y: Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B 1995, 57:289-300.
- [20]Kinsella RJ, Kähäri A, Haider S, Zamora J, Proctor G, Spudich G, Almeida-King J, Staines D, Derwent P, Kerhornou A, Kersey P, Flicek P: Ensembl BioMarts: a ahub for data retrieval across taxonomic space. Database 2011, 23:bar030.
- [21]Croft D, Mundo AF, Haw R, Milacic M, Weiser J, Wu G, Caudy M, Garapati P, Gillespie M, Kamdar MR, Jassal B, Jupe S, Matthews L, May B, Palatnik S, Rothfels K, Shamovsky V, Song H, Williams M, Birney E, Hermjakob H, Stein L, D’Eustachio P: The Reactome pathway knowledgebase. Nucleic Acids Res 2014, 42(Database issue):D472-D477.
- [22]Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, Klemm A, Flicek P, Manolio T, Hindorff L, Parkinson H: The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res 2014, 42(Database issue):D1001-D1006.
- [23]Svishcheva GR, Axenovich TI, Belonogova NM, van Duijn CM, Aulchenko YS: Rapid variance components-based method for whole-genome association analysis. Nat Genet 2012, 44:1166-1170.
- [24]Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Ripatti S, Chasman DI, Willer CJ, Johansen CT, Fouchier SW, Isaacs A, Peloso GM, Barbalic M, Ricketts SL, Bis JC, Aulchenko YS, Thorleifsson G, Feitosa MF, Chambers J, Orho-Melander M, Melander O, Johnson T, Li X, Guo X, Li M, Shin Cho Y, Jin Go M, Jin Kim Y, et al.: Biological, clinical and population relevance of 95 loci for blood lipids. Nature 2010, 466:707-713.
- [25]Waterworth DM, Ricketts SL, Song K, Chen L, Zhao JH, Ripatti S, Aulchenko YS, Zhang W, Yuan X, Lim N, Luan J, Ashford S, Wheeler E, Young EH, Hadley D, Thompson JR, Braund PS, Johnson T, Struchalin M, Surakka I, Luben R, Khaw KT, Rodwell SA, Loos RJ, Boekholdt SM, Inouye M, Deloukas P, Elliott P, Schlessinger D, Sanna S, et al.: Genetic variants influencing circulating lipid levels and risk of coronary artery disease. Arterioscler Thromb Vasc Biol 2010, 30:2264-2276.
- [26]Ramayo-Caldas Y, Mercadé A, Castelló A, Yang B, Rodríguez C, Alves E, Díaz I, Ibáñez-Escriche N, Noguera JL, Pérez-Enciso M, Fernández AI, Folch JM: Genome-wide association study for intramuscular fatty acid composition in an Iberian × Landrace cross. J Anim Sci 2012, 90:2883-2893.
- [27]Fontanesi L, Schiavo G, Galimberti G, Calò DG, Scotti E, Martelli PL, Buttazzoni L, Casadio R, Russo V: A genome wide association study for backfat thickness in Italian Large White pigs highlights new regions affecting fat deposition including neuronal genes. BMC Genomics 2012, 13:583. BioMed Central Full Text
- [28]Becker D, Wimmers K, Luther H, Hofer A, Leeb T: A genome-wide association study to detect QTL for commercially important traits in Swiss Large White boars. PLoS One 2013, 8:e55951.
- [29]Asselbergs FW, Guo Y, van Iperen EP, Sivapalaratnam S, Tragante V, Lanktree MB, Lange LA, Almoguera B, Appelman YE, Barnard J, Baumert J, Beitelshees AL, Bhangale TR, Chen YD, Gaunt TR, Gong Y, Hopewell JC, Johnson T, Kleber ME, Langaee TY, Li M, Li YR, Liu K, McDonough CW, Meijs MF, Middelberg RP, Musunuru K, Nelson CP, O’Connell JR, Padmanabhan S, et al.: Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci. Am J Hum Genet 2012, 91:823-838.
- [30]Jeffreys H: The Theory of Probability. Oxford, United Kingdom: Oxford University Press; 1961.
- [31]Friedlander Y, Austin MA, Newman B, Edwards K, Mayer-Davis EI, King MC: Heritability of longitudinal changes in coronary-heart-disease risk factors in women twins. Am J Hum Genet 1997, 60:1502-1512.
- [32]Dumitrescu L, Brown-Gentry K, Goodloe R, Glenn K, Yang W, Kornegay N, Pui CH, Relling MV, Crawford DC: Evidence for age as a modifier of genetic associations for lipid levels. Ann Hum Genet 2011, 75:589-597.
- [33]Tian C, Gregersen PK, Seldin MF: Accounting for ancestry: population substructure and genome-wide association studies. Hum Mol Genet 2008, 17(R2):R143-R150.
- [34]Wang D, Sun Y, Stang P, Berlin JA, Wilcox MA, Li Q: Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling. BMC Proc 2009, 3:S109. BioMed Central Full Text
- [35]Blasiole DA, Davis RA, Attie AD: The physiological and molecular regulation of lipoprotein assembly and secretion. Mol Biosyst 2007, 3:608-619.
- [36]Stanford KI, Bishop JR, Foley EM, Gonzales JC, Niesman IR, Witztum JL, Esko JD: Syndecan-1 is the primary heparan sulfate proteoglycan mediating hepatic clearance of triglyceride-rich lipoproteins in mice. J Clin Invest 2009, 119:3236-3245.
- [37]Igel M, Lindenthal B, Giesa U, von Bergmann K: Evidence that leptin contributes to intestinal cholesterol absorption in obese (ob/ob) mice and wild-type mice. Lipids 2002, 37:153-157.
- [38]Huynh FK, Neumann UH, Wang Y, Rodrigues B, Kieffer TJ, Covey SD: A role for hepatic leptin signaling in lipid metabolism via altered very low density lipoprotein composition and liver lipase activity in mice. Hepatology 2013, 57:543-554.
- [39]Benn M: Apolipoprotein B levels, APOB alleles, and risk of ischemic cardiovascular disease in the general population, a review. Atherosclerosis 2009, 206:17-30.
- [40]Pena RN, Cánovas A, Varona L, Díaz I, Gallardo D, Ramírez O, Noguera JL, Quintanilla R: Nucleotide sequence and association analysis of pig apolipoprotein-B and LDL-receptor genes. Anim Biotechnol 2009, 20:110-123.
- [41]Musunuru K, Pirruccello JP, Do R, Peloso GM, Guiducci C, Sougnez C, Garimella KV, Fisher S, Abreu J, Barry AJ, Fennell T, Banks E, Ambrogio L, Cibulskis K, Kernytsky A, Gonzalez E, Rudzicz N, Engert JC, DePristo MA, Daly MJ, Cohen JC, Hobbs HH, Altshuler D, Schonfeld G, Gabriel SB, Yue P, Kathiresan S: Exome sequencing, ANGPTL3 mutations, and familial combined hypolipidemia. N Engl J Med 2010, 363:2220-2227.
- [42]Yang YT, Wang CL, Van Aelst L: DOCK7 interacts with TACC3 to regulate interkinetic nuclear migration and cortical neurogenesis. Nat Neurosci 2012, 15:1201-1210.
- [43]Oram JF, Lawn RM: ABCA1: the gatekeeper for eliminating excess tissue cholesterol. J Lipid Res 2001, 42:1173-1179.
- [44]Fu J, Festen EA, Wijmenga C: Multi-ethnic studies in complex traits. Hum Mol Genet 2011, 20(R2):R206-R213.
- [45]Hedges SB, Dudley J, Kumar S: TimeTree: a public knowledge-base of divergence times among organisms. Bioinformatics 2006, 22:2971-2972.
- [46]Nicolae DL, Gamazon E, Zhang W, Duan S, Dolan ME, Cox NJ: Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet 2010, 6:e1000888.
- [47]Szánto M, Brunyánszki A, Márton J, Vámosi G, Nagy L, Fodor T, Kiss B, Virág L, Gergely P, Bai P: Deletion of PARP-2 induces hepatic cholesterol accumulation and decrease in HDL levels. Biochim Biophys Acta 2014, 1842:594-602.
- [48]Clifford AJ, Rincon G, Owens JE, Medrano JF, Moshfegh AJ, Baer DJ, Novotny JA: Single nucleotide polymorphisms in CETP, SLC46A1, SLC19A1, CD36, BCMO1, APOA5, and ABCA1 are significant predictors of plasma HDL in healthy adults. Lipids Health Dis 2013, 12:66. BioMed Central Full Text
- [49]Cocquet J, Ellis PJ, Yamauchi Y, Riel JM, Karacs TP, Rattigan A, Ojarikre OA, Affara NA, Ward MA, Burgoyne PS: Deficiency in the multicopy Sycp3-like X-linked genes Slx and Slxl1 causes major defects in spermatid differentiation. Mol Biol Cell 2010, 21:3497-3505.
- [50]Wu CY, Chen YF, Wang CH, Kao CH, Zhuang HW, Chen CC, Chen LK, Kirby R, Wei YH, Tsai SF, Tsai TF: A persistent level of Cisd2 extends healthy lifespan and delays aging in mice. Hum Mol Genet 2012, 21:3956-3968.
- [51]Turcot V, Bouchard L, Faucher G, Tchernof A, Deshaies Y, Pérusse L, Bélisle A, Marceau S, Biron S, Lescelleur O, Biertho L, Vohl MC: DPP4 gene DNA methylation in the omentum is associated with its gene expression and plasma lipid profile in severe obesity. Obesity 2011, 19:388-395.
- [52]Cheung VG, Nayak RR, Wang IX, Elwyn S, Cousins SM, Morley M, Spielman RS: Polymorphic cis- and trans-regulation of human gene expression. PLoS Biol 2010, 8:e1000480.