Mammalian Genome

, Volume 17, Issue 6, pp 575–583 | Cite as

Combining gene expression QTL mapping and phenotypic spectrum analysis to uncover gene regulatory relationships

  • Lei Bao
  • Lai Wei
  • Jeremy L. Peirce
  • Ramin Homayouni
  • Hongqiang Li
  • Mi Zhou
  • Hao Chen
  • Lu Lu
  • Robert W. Williams
  • Lawrence M. Pfeffer
  • Dan Goldowitz
  • Yan Cui
Article

Abstract

Gene expression QTL (eQTL) mapping can suggest candidate regulatory relationships between genes. Recent advances in mammalian phenotype annotation such as mammalian phenotype ontology (MPO) enable systematic analysis of the phenotypic spectrum subserved by many genes. In this study we combined eQTL mapping and phenotypic spectrum analysis to predict gene regulatory relationships. Five pairs of genes with similar phenotypic effects and potential regulatory relationships suggested by eQTL mapping were identified. Lines of evidence supporting some of the predicted regulatory relationships were obtained from biological literature. A particularly notable example is that promoter sequence analysis and real-time PCR assays support the predicted regulation of protein kinase C epsilon (Prkce) by cAMP responsive element binding protein 1 (Creb1). Our results show that the combination of gene eQTL mapping and phenotypic spectrum analysis may provide a valuable approach to uncovering gene regulatory relations underlying mammalian phenotypes.

Notes

Acknowledgments

The authors thank the reviewers for helpful suggestions. This work was supported by a PhRMA Foundation grant (YC); NIH grants HD52472 (DG), AA14425 (LL), AA13499 (RWW), and CA73753 (LMP); and by funds from the Muirhead Chair Endowment at the University of Tennessee Health Science Center (LMP).

Supplementary material

supp.pdf (66 kb)

References

  1. Aksoy E, Goldman M, Willems F (2004) Protein kinase C epsilon: a new target to control inflammation and immune-mediated disorders. Int J Biochem Cell Biol 36: 183–188PubMedCrossRefGoogle Scholar
  2. Asthana S, King OD, Gibbons FD, Roth FP (2004) Predicting protein complex membership using probabilistic network reliability. Genome Res 14: 1170–1175PubMedCrossRefGoogle Scholar
  3. Badano JL, Katsanis N (2002) Beyond Mendel: an evolving view of human genetic disease transmission. Nat Rev Genet 3: 779–789PubMedCrossRefGoogle Scholar
  4. Bao L, Sun Z (2002) Identifying genes related to drug anticancer mechanisms using support vector machine. FEBS Lett 521: 109–114PubMedCrossRefGoogle Scholar
  5. Basu A, Lu D, Sun B, Moor AN, Akkaraju GR, et al. (2002) Proteolytic activation of protein kinase C-epsilon by caspase-mediated processing and transduction of antiapoptotic signals. J Biol Chem 277: 41850–41856PubMedCrossRefGoogle Scholar
  6. Bing N, Hoeschele I (2005) Genetical genomics analysis of a yeast segregant population for transcription network inference. Genetics 170: 533–542PubMedCrossRefGoogle Scholar
  7. Bolstad BM, Irizarry RA, Astrand M, Speed TP (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19: 185–193PubMedCrossRefGoogle Scholar
  8. Brem RB, Kruglyak L (2005) The landscape of genetic complexity across 5,700 gene expression traits in yeast. Proc Natl Acad Sci USA 102: 1572–1577PubMedCrossRefGoogle Scholar
  9. Brem RB, Yvert G, Clinton R, Kruglyak L (2002) Genetic dissection of transcriptional regulation in budding yeast. Science 296: 752–755PubMedCrossRefGoogle Scholar
  10. Brem RB, Storey JD, Whittle J, Kruglyak L (2005) Genetic interactions between polymorphisms that affect gene expression in yeast. Nature 436: 701–703PubMedCrossRefGoogle Scholar
  11. Bystrykh L, Weersing E, Dontje B, Sutton S, Pletcher MT, et al. (2005) Uncovering regulatory pathways that affect hematopoietic stem cell function using “genetical genomics.” Nat Genet 37: 225–232PubMedCrossRefGoogle Scholar
  12. Chesler EJ, Lu L, Shou S, Qu Y, Gu J, et al. (2005) Complex trait analysis of gene expression uncovers polygenic and pleiotropic networks that modulate nervous system function. Nat Genet 37: 233–242PubMedCrossRefGoogle Scholar
  13. Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138: 963–971PubMedGoogle Scholar
  14. Clare A, King RD (2002) Machine learning of functional class from phenotype data. Bioinformatics 18: 160–166PubMedCrossRefGoogle Scholar
  15. de Koning DJ, Haley CS (2005) Genetical genomics in humans and model organisms. Trends Genet 21: 377–381PubMedCrossRefGoogle Scholar
  16. de Koning D-J, Carlborg O, Haley CS (2005) The genetic dissection of immune response using gene-expression studies and genome mapping. Vet Immunol Immunopathol 105: 343PubMedCrossRefGoogle Scholar
  17. DeCoy DL, Snapper JR, Breyer MD (1995) Anti sense DNA down-regulates proteins kinase C-epsilon and enhances vasopressin-stimulated Na+ absorption in rabbit cortical collecting duct. J Clin Invest 95: 2749–2756PubMedCrossRefGoogle Scholar
  18. Doss S, Schadt EE, Drake TA, Lusis AJ (2005) Cis-acting expression quantitative trait loci in mice. Genome Res 15: 681–691PubMedCrossRefGoogle Scholar
  19. Dupuis J, Siegmund D (1999) Statistical methods for mapping quantitative trait loci from a dense set of markers. Genetics 151: 373–386PubMedGoogle Scholar
  20. Gkoutos GV, Green EC, Mallon AM, Hancock JM, Davidson D (2004) Building mouse phenotype ontologies. Pac Symp Biocomput, 178–189Google Scholar
  21. Gruber T, Thuille N, Hermann–Kleiter N, Leitges M, Baier G (2005) Protein kinase Cepsilon is dispensable for TCR/CD3-signaling. Mol Immunol 42: 305–310PubMedCrossRefGoogle Scholar
  22. Gunsalus KC, Ge H, Schetter AJ, Goldberg DS, Han J-DJ, et al. (2005) Predictive models of molecular machines involved in Caenorhabditis elegans early embryogenesis. Nature 436, 861PubMedCrossRefGoogle Scholar
  23. Hubner N, Wallace CA, Zimdahl H, Petretto E, Schulz H, et al. (2005) Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease. Nat Genet 37: 243–253PubMedCrossRefGoogle Scholar
  24. Jansen RC, Nap JP (2001) Genetical genomics: the added value from segregation. Trends Genet 17: 388–391PubMedCrossRefGoogle Scholar
  25. Kel AE, Gossling E, Reuter I, Cheremushkin E, Kel–Margoulis OV, et al. (2003) MATCH: A tool for searching transcription factor binding sites in DNA sequences. Nucleic Acids Res 31: 3576–3579PubMedCrossRefGoogle Scholar
  26. Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, et al. (2002) The human genome browser at UCSC. Genome Res 12: 996–1006PubMedCrossRefGoogle Scholar
  27. Khasar SG, Lin YH, Martin A, Dadgar J, McMahon T, et al. (1999) A novel nociceptor signaling pathway revealed in protein kinase C epsilon mutant mice. Neuron 24: 253–260PubMedCrossRefGoogle Scholar
  28. King OD, Lee JC, Dudley AM, Janse DM, Church GM, et al. (2003) Predicting phenotype from patterns of annotation. Bioinformatics 19 Suppl 1: i183–189CrossRefGoogle Scholar
  29. Kirst M, Myburg AA, De Leon JP, Kirst ME, Scott J, et al. (2004) Coordinated genetic regulation of growth and lignin revealed by quantitative trait locus analysis of cDNA microarray data in an interspecific backcross of eucalyptus. Plant Physiol 135: 2368–2378PubMedCrossRefGoogle Scholar
  30. Lander ES, Botstein D (1989) Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121: 185–199PubMedGoogle Scholar
  31. Li H, Lu L, Manly KF, Chesler EJ, Bao L, et al. (2005) Inferring gene transcriptional modulatory relations: a genetical genomics approach. Hum Mol Genet 14: 1119–1125PubMedCrossRefGoogle Scholar
  32. Li H, Chen H, Bao L, Manly KF, Chesler EJ, et al. (2006) Integrative genetic analysis of transcription modules: towards filling the gap between genetic loci and inherited traits. Hum Mol Genet 15: 481–492PubMedCrossRefGoogle Scholar
  33. Li J, Burmeister M (2005) Genetical genomics: combining genetics with gene expression analysis. Hum Mol Genet 14: R163–R169PubMedCrossRefGoogle Scholar
  34. Lord PW, Stevens RD, Brass A, Goble CA (2003) Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation. Bioinformatics 19: 1275–1283PubMedCrossRefGoogle Scholar
  35. Manly KF, Cudmore RH, Jr., Meer JM (2001) Map Manager QTX, cross-platform software for genetic mapping. Mamm Genome 12: 930–932PubMedCrossRefGoogle Scholar
  36. Mayr B, Montminy M (2001) Transcriptional regulation by the phosphorylation-dependent factor CREB. Nat Rev Mol Cell Biol 2: 599–609PubMedCrossRefGoogle Scholar
  37. McCarthy J, McLeod CJ, Minners J, Essop MF, Ping P, et al. (2005) PKCepsilon activation augments cardiac mitochondrial respiratory post-anoxic reserve—a putative mechanism in PKCepsilon cardioprotection. J Mol Cell Cardiol 38: 697–700PubMedCrossRefGoogle Scholar
  38. McKusick VA (1998) Mendelian Inheritance in Man. A Catalog of Human Genes and Genetic Disorders (Baltimore, MD: Johns Hopkins University Press)Google Scholar
  39. Mehrabian M, Allayee H, Stockton J, Lum PY, Drake TA, et al. (2005) Integrating genotypic and expression data in a segregating mouse population to identify 5-lipoxygenase as a susceptibility gene for obesity and bone traits. Nat Genet 37: 1224–1233PubMedCrossRefGoogle Scholar
  40. Monks SA, Leonardson A, Zhu H, Cundiff P, Pietrusiak P, et al. (2004) Genetic inheritance of gene expression in human cell lines. Am J Hum Genet 75: 1094–1105PubMedCrossRefGoogle Scholar
  41. Morley M, Molony CM, Weber TM, Devlin JL, Ewens KG, et al. (2004) Genetic analysis of genome-wide variation in human gene expression. Nature 430: 743–747PubMedCrossRefGoogle Scholar
  42. Nadeau JH, Balling R, Barsh G, Beier D, Brown SD, et al. (2001) Sequence interpretation. Functional annotation of mouse genome sequences. Science 291: 1251–1255PubMedCrossRefGoogle Scholar
  43. Parada CA, Reichling DB, Levine JD (2005) Chronic hyperalgesic priming in the rat involves a novel interaction between cAMP and PKCepsilon second messenger pathways. Pain 113: 185–190PubMedCrossRefGoogle Scholar
  44. Rikke BA, Johnson TE (1998) Towards the cloning of genes underlying murine QTLs. Mamm Genome 9: 963–968PubMedCrossRefGoogle Scholar
  45. Ronald J, Brem RB, Whittle J, Kruglyak L (2005) Local regulatory variation in Saccharomyces cerevisiae. PLoS Genet 1: e25PubMedCrossRefGoogle Scholar
  46. Schadt EE, Monks SA, Drake TA, Lusis AJ, Che N, et al. (2003) Genetics of gene expression surveyed in maize, mouse and man. Nature 422: 297–302PubMedCrossRefGoogle Scholar
  47. Schadt EE, Lamb J, Yang X, Zhu J, Edwards S, et al. (2005) An integrative genomics approach to infer causal associations between gene expression and disease. Nat Genet 37: 710–717PubMedCrossRefGoogle Scholar
  48. Shaywitz AJ, Greenberg ME (1999) CREB: a stimulus-induced transcription factor activated by a diverse array of extracellular signals. Annu Rev Biochem 68: 821–861PubMedCrossRefGoogle Scholar
  49. Skarnes WC, von Melchner H, Wurst W, Hicks G, Nord AS, et al. (2004) A public gene trap resource for mouse functional genomics. Nat Genet 36: 543–544PubMedCrossRefGoogle Scholar
  50. Smith CL, Goldsmith CA, Eppig JT (2005) The Mammalian Phenotype Ontology as a tool for annotating, analyzing and comparing phenotypic information. Genome Biol 6:R7PubMedCrossRefGoogle Scholar
  51. Stenson PD, Ball EV, Mort M, Phillips AD, Shiel JA, et al. (2003) Human Gene Mutation Database (HGMD): 2003 update. Hum Mutat 21: 577–581PubMedCrossRefGoogle Scholar
  52. Storey JD, Akey JM, Kruglyak L (2005) Multiple locus linkage analysis of genomewide expression in yeast. PLoS Biol 3: e267PubMedCrossRefGoogle Scholar
  53. Wayne ML, McIntyre LM (2002) Combining mapping and arraying: An approach to candidate gene identification. Proc Natl Acad Sci U S A 99: 14903–14906PubMedCrossRefGoogle Scholar
  54. Williams RW, Gu J, Qi S, Lu L (2001) The genetic structure of recombinant inbred mice: high-resolution consensus maps for complex trait analysis. Genome Biol 2:RESEARCH0046PubMedGoogle Scholar
  55. Wiltshire T, Pletcher MT, Batalov S, Barnes SW, Tarantino LM, et al. (2003) Genome-wide single-nucleotide polymorphism analysis defines haplotype patterns in mouse. Proc Natl Acad Sci USA 100: 3380–3385PubMedCrossRefGoogle Scholar
  56. Wu JM, Xiao L, Cheng XK, Cui LX, Wu NH, et al. (2003) PKC epsilon is a unique regulator for hsp90 beta gene in heat shock response. J Biol Chem 278: 51143–51149PubMedCrossRefGoogle Scholar
  57. Yvert G, Brem RB, Whittle J, Akey JM, Foss E, et al. (2003) Trans-acting regulatory variation in Saccharomyces cerevisiae and the role of transcription factors. Nat Genet 35: 57–64PubMedCrossRefGoogle Scholar
  58. Zeidman R, Troller U, Raghunath A, Pahlman S, Larsson C (2002) Protein kinase Cepsilon actin-binding site is important for neurite outgrowth during neuronal differentiation. Mol Biol Cell 13: 12–24PubMedCrossRefGoogle Scholar
  59. Zhang XM, Odom DT, Koo SH, Conkright MD, Canettieri G, et al. (2005) Genome-wide analysis of cAMP-response element binding protein occupancy, phosphorylation, and target gene activation in human tissues. Proc Natl Acad Sci USA 102: 4459–4464PubMedCrossRefGoogle Scholar
  60. Zhu J, Lum PY, Lamb J, GuhaThakurta D, Edwards SW et al. (2004) An integrative genomics approach to the reconstruction of gene networks in segregating populations. Cytogenet Genome Res 105: 363–374PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Lei Bao
    • 1
    • 2
  • Lai Wei
    • 3
    • 4
  • Jeremy L. Peirce
    • 2
    • 4
  • Ramin Homayouni
    • 2
    • 4
  • Hongqiang Li
    • 1
    • 2
  • Mi Zhou
    • 1
    • 2
  • Hao Chen
    • 5
  • Lu Lu
    • 2
    • 4
  • Robert W. Williams
    • 2
    • 4
    • 6
  • Lawrence M. Pfeffer
    • 3
  • Dan Goldowitz
    • 2
    • 4
  • Yan Cui
    • 1
    • 2
    • 7
  1. 1.Department of Molecular SciencesUniversity of Tennessee Health Science CenterMemphisUSA
  2. 2.Center of Genomics and BioinformaticsUniversity of Tennessee Health Science CenterMemphisUSA
  3. 3.Department of Pathology and Laboratory MedicineUniversity of Tennessee Health Science CenterMemphisUSA
  4. 4.Department of Anatomy and NeurobiologyUniversity of Tennessee Health Science CenterMemphisUSA
  5. 5.Department of PharmacologyUniversity of Tennessee Health Science CenterMemphisUSA
  6. 6.Department of PediatricsUniversity of Tennessee Health Science CenterMemphisUSA
  7. 7.Department of Molecular SciencesUniversity of Tennessee Health Science CenterMemphisUSA

Personalised recommendations