Quantitative and qualitative proteome characteristics extracted from in-depth integrated genomics and proteomics analysis

Cell Reports

Volumn 5, Issue 5, 2013, Pages 1469-1478

  Low, TeckYew ^a,b   vanHeesch, Sebastiaan ^c   vandenToorn, Henk ^a,b   Giansanti, Piero ^a,b   Cristobal, Alba ^a,b   Toonen, Pim ^c   Schafer, Sebastian ^d   Hübner, Norbert ^d,e   vanBreukelen, Bas ^a,b   Mohammed, Shabaz ^a,b,f   Cuppen, Edwin ^c   Heck, AlbertJ R ^a,b   Guryev, Victor ^c,g  

^a UTRECHT UNIVERSITY   (Netherlands)

^b NETHERLANDS PROTEOMICS CENTRE   (Netherlands)

^c UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

^d MAX DELBRÜCK CENTER FOR MOLECULAR MEDICINE   (Germany)

^e DZHK GERMAN CENTRE FOR CARDIOVASCULAR RESEARCH   (Germany)

^f UNIVERSITY OF OXFORD   (United Kingdom)

^g UNIVERSITY MEDICAL CENTER GRONINGEN   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ISOPROTEIN; PROTEOME; RNA; TRANSCRIPTOME;

ANIMAL TISSUE; ARTICLE; CONTROLLED STUDY; CORRELATION ANALYSIS; CYP17A1 GENE; GENE; GENETIC ASSOCIATION; GENETIC REGULATION; GENETIC VARIABILITY; GENOMICS; HYPERTENSION; LIVER; MOLECULAR DYNAMICS; NONHUMAN; PREDICTION; PRIORITY JOURNAL; PROMOTER REGION; PROTEOMICS; QUALITATIVE ANALYSIS; QUANTITATIVE ANALYSIS; RAT; REGULATORY MECHANISM; RNA SEQUENCE; RNA SPLICING; STRAIN DIFFERENCE; VALIDATION STUDY;

RATTUS;

ANIMALS; GENOME; HYPERTENSION; LIVER; PROTEOME; RATS; RATS, INBRED SHR; RNA EDITING; RNA SPLICING; STEROID 17-ALPHA-HYDROXYLASE; TRANSCRIPTOME;

EID: 84890231620     PISSN: None     EISSN: 22111247     Source Type: Journal    
DOI: 10.1016/j.celrep.2013.10.041     Document Type: Article

References (69)

1. Ahrens C.H., Brunner E., Qeli E., Basler K., Aebersold R. Generating and navigating proteome maps using mass spectrometry. Nat. Rev. Mol. Cell Biol. 2010, 11:789-801.
2. Aitman T.J., Gotoda T., Evans A.L., Imrie H., Heath K.E., Trembling P.M., Truman H., Wallace C.A., Rahman A., Doré C., et al. Quantitative trait loci for cellular defects in glucose and fatty acid metabolism in hypertensive rats. Nat. Genet. 1997, 16:197-201.
3. Aitman T.J., Glazier A.M., Wallace C.A., Cooper L.D., Norsworthy P.J., Wahid F.N., Al-Majali K.M., Trembling P.M., Mann C.J., Shoulders C.C., et al. Identification of Cd36 (Fat) as an insulin-resistance gene causing defective fatty acid and glucose metabolism in hypertensive rats. Nat. Genet. 1999, 21:76-83.
4. Altelaar A.F.M., Munoz J., Heck A.J.R. Next-generation proteomics: towards an integrative view of proteome dynamics. Nat. Rev. Genet. 2013, 14:35-48.
5. Atanur S.S., Birol I., Guryev V., Hirst M., Hummel O., Morrissey C., Behmoaras J., Fernandez-Suarez X.M., Johnson M.D., McLaren W.M., et al. The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance. Genome Res. 2010, 20:791-803.
6. Bensimon A., Heck A.J.R., Aebersold R. Mass spectrometry-based proteomics and network biology. Annu. Rev. Biochem. 2012, 81:379-405.
7. Biglieri E.G. 17 alpha-Hydroxylase deficiency: 1963-1966. J.Clin. Endocrinol. Metab. 1997, 82:48-50.
8. Biglieri E.G., Herron M.A., Brust N. 17-hydroxylation deficiency in man. J.Clin. Invest. 1966, 45:1946-1954.
9. Birney E., Andrews T.D., Bevan P., Caccamo M., Chen Y., Clarke L., Coates G., Cuff J., Curwen V., Cutts T., et al. An overview of Ensembl. Genome Res. 2004, 14:925-928.
10. Burge C., Karlin S. Prediction of complete gene structures in human genomic DNA. J.Mol. Biol. 1997, 268:78-94.
11. Cox J., Mann M. Quantitative, high-resolution proteomics for data-driven systems biology. Annu. Rev. Biochem. 2011, 80:273-299.
12. Curwen V., Eyras E., Andrews T.D., Clarke L., Mongin E., Searle S.M.J., Clamp M. The Ensembl automatic gene annotation system. Genome Res. 2004, 14:942-950.
13. Danielson P.B. The cytochrome P450 superfamily: biochemistry, evolution and drug metabolism in humans. Curr. Drug Metab. 2002, 3:561-597.
14. de Sousa Abreu R., Penalva L.O., Marcotte E.M., Vogel C. Global signatures of protein and mRNA expression levels. Mol. Biosyst. 2009, 5:1512-1526.
15. Dormeyer W., Mohammed S., Breukelen Bv., Krijgsveld J., Heck A.J.R. Targeted analysis of protein termini. J.Proteome Res. 2007, 6:4634-4645.
16. Dwinell M.R., Worthey E.A., Shimoyama M., Bakir-Gungor B., DePons J., Laulederkind S., Lowry T., Nigram R., Petri V., Smith J., et al. The Rat Genome Database 2009: variation, ontologies and pathways. Nucleic Acids Res. 2009, 37(Database issue):D744-D749. RGD Team.
17. Farajollahi S., Maas S. Molecular diversity through RNA editing: a balancing act. Trends Genet. 2010, 26:221-230.
18. Geller D.H., Auchus R.J., Mendonça B.B., Miller W.L. The genetic and functional basis of isolated 17,20-lyase deficiency. Nat. Genet. 1997, 17:201-205.
19. Gibbs R.A., Weinstock G.M., Metzker M.L., Muzny D.M., Sodergren E.J., Scherer S., Scott G., Steffen D., Worley K.C., Burch P.E., et al. Genome sequence of the Brown Norway rat yields insights into mammalian evolution. Nature 2004, 428:493-521. Rat Genome Sequencing Project Consortium.
20. Goldsmith O., Solomon D.H., Horton R. Hypogonadism and mineralocorticoid excess. The 17-hydroxylase deficiency syndrome. N.Engl. J. Med. 1967, 277:673-677.
21. Grobei M.A., Qeli E., Brunner E., Rehrauer H., Zhang R., Roschitzki B., Basler K., Ahrens C.H., Grossniklaus U. Deterministic protein inference for shotgun proteomics data provides new insights into Arabidopsis pollen development and function. Genome Res. 2009, 19:1786-1800.
22. Heinig M., Petretto E., Wallace C., Bottolo L., Rotival M., Lu H., Li Y., Sarwar R., Langley S.R., Bauerfeind A., et al. A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk. Nature 2010, 467:460-464. Cardiogenics Consortium.
23. Hubbard T., Barker D., Birney E., Cameron G., Chen Y., Clark L., Cox T., Cuff J., Curwen V., Down T., et al. The Ensembl genome database project. Nucleic Acids Res. 2002, 30:38-41.
24. Hubner N., Wallace C.A., Zimdahl H., Petretto E., Schulz H., Maciver F., Mueller M., Hummel O., Monti J., Zidek V., et al. Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease. Nat. Genet. 2005, 37:243-253.
25. Hurst J.M., McMillan L.E.M., Porter C.T., Allen J., Fakorede A., Martin A.C.R. The SAAPdb web resource: a large-scale structural analysis of mutant proteins. Hum. Mutat. 2009, 30:616-624.
26. Jaffe J.D., Berg H.C., Church G.M. Proteogenomic mapping as a complementary method to perform genome annotation. Proteomics 2004, 4:59-77.
27. Jansen R.C., Nap J.P. Genetical genomics: the added value from segregation. Trends Genet. 2001, 17:388-391.
28. Jensen O.N. Modification-specific proteomics: characterization of post-translational modifications by mass spectrometry. Curr. Opin. Chem. Biol. 2004, 8:33-41.
29. Johnson M.D., He L., Herman D., Wakimoto H., Wallace C.A., Zidek V., Mlejnek P., Musilova A., Simakova M., Vorlicek J., et al. Dissection of chromosome 18 blood pressure and salt-sensitivity quantitative trait loci in the spontaneously hypertensive rat. Hypertension 2009, 54:639-645.
30. Käll L., Canterbury J.D., Weston J., Noble W.S., MacCoss M.J. Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat. Methods 2007, 4:923-925.
31. Kent W.J. BLAT-the BLAST-like alignment tool. Genome Res. 2002, 12:656-664.
32. Kinoshita K., Ashenagar M.S., Tabuchi M., Higashino H. Whole rat DNA array survey for candidate genes related to hypertension in kidneys from three spontaneously hypertensive rat substrains at two stages of age and with hypotensive induction caused by hydralazine hydrochloride. Exp Ther Med 2011, 2:201-212.
33. Kleinman C.L., Majewski J. Comment on "Widespread RNA and DNA sequence differences in the human transcriptome". Science 2012, 335:1302. author reply 1302.
34. Lee S.J., Liu J., Qi N., Guarnera R.A., Lee S.Y., Cicila G.T. Use of a panel of congenic strains to evaluate differentially expressed genes as candidate genes for blood pressure quantitative trait loci. Hypertens. Res. 2003, 26:75-87.
35. Li X., Ling Y., Lu D., Lu Z., Liu Y., Chen H., Gao X. Common polymorphism rs11191548 near the CYP17A1 gene is associated with hypertension and systolic blood pressure in the Han Chinese population. Am. J. Hypertens. 2013, 26:465-472.
36. Lin W., Piskol R., Tan M.H., Li J.B. Comment on "Widespread RNA and DNA sequence differences in the human transcriptome". Science 2012, 335:1302. author reply 1302.
37. Liu C., Li H., Qi Q., Lu L., Gan W., Loos R.J., Lin X. Common variants in or near FGF5, CYP17A1 and MTHFR genes are associated with blood pressure and hypertension in Chinese Hans. J.Hypertens. 2011, 29:70-75.
38. Merrihew G.E., Davis C., Ewing B., Williams G., Käll L., Frewen B.E., Noble W.S., Green P., Thomas J.H., MacCoss M.J. Use of shotgun proteomics for the identification, confirmation, and correction of C. elegans gene annotations. Genome Res. 2008, 18:1660-1669.
39. Mohammed S., Lorenzen K., Kerkhoven R., van Breukelen B., Vannini A., Cramer P., Heck A.J.R. Multiplexed proteomics mapping of yeast RNA polymerase II and III allows near-complete sequence coverage and reveals several novel phosphorylation sites. Anal. Chem. 2008, 80:3584-3592.
40. Munoz J., Low T.Y., Kok Y.J., Chin A., Frese C.K., Ding V., Choo A., Heck A.J.R. The quantitative proteomes of human-induced pluripotent stem cells and embryonic stem cells. Mol. Syst. Biol. 2011, 7:550.
41. Nagaraj N., Wisniewski J.R., Geiger T., Cox J., Kircher M., Kelso J., Pääbo S., Mann M. Deep proteome and transcriptome mapping of a human cancer cell line. Mol. Syst. Biol. 2011, 7:548.
42. Nesvizhskii A.I., Aebersold R. Interpretation of shotgun proteomic data: the protein inference problem. Mol. Cell. Proteomics 2005, 4:1419-1440.
43. Nesvizhskii A.I., Roos F.F., Grossmann J., Vogelzang M., Eddes J.S., Gruissem W., Baginsky S., Aebersold R. Dynamic spectrum quality assessment and iterative computational analysis of shotgun proteomic data: toward more efficient identification of post-translational modifications, sequence polymorphisms, and novel peptides. Mol. Cell. Proteomics 2006, 5:652-670.
44. Newton-Cheh C., Johnson T., Gateva V., Tobin M.D., Bochud M., Coin L., Najjar S.S., Zhao J.H., Heath S.C., Eyheramendy S., et al. Genome-wide association study identifies eight loci associated with blood pressure. Nat. Genet. 2009, 41:666-676. Wellcome Trust Case Control Consortium.
45. Ning K., Fermin D., Nesvizhskii A.I. Comparative analysis of different label-free mass spectrometry based protein abundance estimates and their correlation with RNA-Seq gene expression data. J.Proteome Res. 2012, 11:2261-2271.
46. Okamoto K., Aoki K. Development of a strain of spontaneously hypertensive rats. Jpn. Circ. J. 1963, 27:282-293.
47. Ozsolak F., Milos P.M. RNA sequencing: advances, challenges and opportunities. Nat. Rev. Genet. 2011, 12:87-98.
48. Peng M., Taouatas N., Cappadona S., van Breukelen B., Mohammed S., Scholten A., Heck A.J.R. Protease bias in absolute protein quantitation. Nat. Methods 2012, 9:524-525.
49. Pickrell J.K., Gilad Y., Pritchard J.K. Comment on "Widespread RNA and DNA sequence differences in the human transcriptome". Science 2012, 335:1302. author reply 1302.
50. Pravenec M., Kurtz T.W. Recent advances in genetics of the spontaneously hypertensive rat. Curr. Hypertens. Rep. 2010, 12:5-9.
51. Printz M.P., Jirout M., Jaworski R., Alemayehu A., Kren V. Genetic Models in Applied Physiology. HXB/BXH rat recombinant inbred strain platform: a newly enhanced tool for cardiovascular, behavioral, and developmental genetics and genomics. J.Appl. Physiol. 2003, 94:2510-2522.
52. Renuse S., Chaerkady R., Pandey A. Proteogenomics. Proteomics 2011, 11:620-630.
53. Sandelin A., Alkema W., Engström P., Wasserman W.W., Lenhard B. JASPAR: an open-access database for eukaryotic transcription factor binding profiles. Nucleic Acids Res. 2004, 32(Database issue):D91-D94.
54. Schwanhäusser B., Busse D., Li N., Dittmar G., Schuchhardt J., Wolf J., Chen W., Selbach M. Global quantification of mammalian gene expression control. Nature 2011, 473:337-342.
55. Simonis M., Atanur S.S., Linsen S., Guryev V., Ruzius F.-P., Game L., Lansu N., de Bruijn E., van Heesch S., Jones S.J.M., et al. Genetic basis of transcriptome differences between the founder strains of the rat HXB/BXH recombinant inbred panel. Genome Biol. 2012, 13:r31.
56. Slavoff S.A., Mitchell A.J., Schwaid A.G., Cabili M.N., Ma J., Levin J.Z., Karger A.D., Budnik B.A., Rinn J.L., Saghatelian A. Peptidomic discovery of short open reading frame-encoded peptides in human cells. Nat. Chem. Biol. 2013, 9:59-64.
57. Soon W.W., Hariharan M., Snyder M.P. High-throughput sequencing for biology and medicine. Mol. Syst. Biol. 2013, 9:640.
58. Starheim K.K., Gevaert K., Arnesen T. Protein N-terminal acetyltransferases: when the start matters. Trends Biochem. Sci. 2012, 37:152-161.
59. Su Z.-D., Sun L., Yu D.-X., Li R.-X., Li H.-X., Yu Z.-J., Sheng Q.-H., Lin X., Zeng R., Wu J.-R. Quantitative detection of single amino acid polymorphisms by targeted proteomics. J.Mol. Cell Biol. 2011, 3:309-315.
60. Sun A., Jiang Y., Wang X., Liu Q., Zhong F., He Q., Guan W., Li H., Sun Y., Shi L., et al. Liverbase: a comprehensive view of human liver biology. J.Proteome Res. 2010, 9:50-58.
61. Swaney D.L., Wenger C.D., Coon J.J. Value of using multiple proteases for large-scale mass spectrometry-based proteomics. J.Proteome Res. 2010, 9:1323-1329.
62. Takeuchi F., Isono M., Katsuya T., Yamamoto K., Yokota M., Sugiyama T., Nabika T., Fujioka A., Ohnaka K., Asano H., et al. Blood pressure and hypertension are associated with 7 loci in the Japanese population. Circulation 2010, 121:2302-2309.
63. Trapnell C., Roberts A., Goff L., Pertea G., Kim D., Kelley D.R., Pimentel H., Salzberg S.L., Rinn J.L., Pachter L. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc. 2012, 7:562-578.
64. Uhlen M., Ponten F. Antibody-based proteomics for human tissue profiling. Mol. Cell. Proteomics 2005, 4:384-393.
65. Valentine S.J., Sevugarajan S., Kurulugama R.T., Koeniger S.L., Merenbloom S.I., Bohrer B.C., Clemmer D.E. Split-field drift tube/mass spectrometry and isotopic labeling techniques for determination of single amino acid polymorphisms. J.Proteome Res. 2006, 5:1879-1887.
66. Venter E., Smith R.D., Payne S.H. Proteogenomic analysis of bacteria and archaea: a 46 organism case study. PLoS ONE 2011, 6:e27587.
67. Vizcaíno J.A., CÔté R.G., Csordas A., Dianes J.A., Fabregat A., Foster J.M., Griss J., Alpi E., Birim M., Contell J., et al. The PRoteomics IDEntifications (PRIDE) database and associated tools: status in 2013. Nucleic Acids Res. 2013, 41(Database issue):D1063-D1069.
68. Vogel C., Marcotte E.M. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat. Rev. Genet. 2012, 13:227-232.
69. Volkening J.D., Bailey D.J., Rose C.M., Grimsrud P.A., Howes-Podoll M., Venkateshwaran M., Westphall M.S., Ané J.-M., Coon J.J., Sussman M.R. A proteogenomic survey of the Medicago truncatula genome. Mol. Cell. Proteomics 2012, 11:933-944.