Detecting regulatory gene-environment interactions with unmeasured environmental factors

Bioinformatics

Volumn 29, Issue 11, 2013, Pages 1382-1389

  Fusi, Nicoló ^a   Lippert, Christoph ^b   Borgwardt, Karsten ^c,d   Lawrence, Neil D ^a   Stegle, Oliver ^c,e  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

^b MICROSOFT RESEARCH   (United States)

^c Machine Learning and Computational Biology Research Group   (Germany)

^d UNIVERSITY OF TÜBINGEN   (Germany)

^e EUROPEAN BIOINFORMATICS INSTITUTE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BIOLOGICAL MODEL; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENOTYPE; GENOTYPE ENVIRONMENT INTERACTION; HUMAN; QUANTITATIVE TRAIT LOCUS; STATISTICAL MODEL;

GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENE EXPRESSION REGULATION, FUNGAL; GENE-ENVIRONMENT INTERACTION; GENOTYPE; HUMANS; LINEAR MODELS; MODELS, GENETIC; QUANTITATIVE TRAIT LOCI;

EID: 84878318376     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btt148     Document Type: Article

References (40)

1. Anders, S. and Huber, W. (2010) Differential expression analysis for sequence count data. Genome Biol., 11, R106.
2. Auesukaree, C. et al. (2009) Genome-wide identification of genes involved in tolerance to various environmental stresses in Saccharomyces cerevisiae. J. Appl. Genet., 50, 301-310.
3. Brem, R.B. et al. (2002) Genetic dissection of transcriptional regulation in budding yeast. Science, 296, 752-755.
4. Fu, J. et al. (2012) Unraveling the regulatory mechanisms underlying tissue-dependent genetic variation of gene expression. PLoS Genet., 8, e1002431.
5. Fusi, N. et al. (2012) Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studies. PLoS Comput. Biol., 8, e1002330.
6. Gan, X. et al. (2011) Multiple reference genomes and transcriptomes for Arabidopsis thaliana. Nature, 477, 419-423.
7. Gibson, G. (2008) The environmental contribution to gene expression profiles. Nat. Rev. Genet., 9, 575-581.
8. Grundberg, E. et al. (2012) Mapping cis-and trans-regulatory effects across multiple tissues in twins. Nat. Genet., 44, 1084-1089.
9. Hallgrímsdó ttir, I. and Yuster, D. (2008) A complete classification of epistatic twolocus models. BMC Genet., 9, 17.
10. Kang, H.M. et al. (2008a) Accurate discovery of expression quantitative trait loci under confounding from spurious and genuine regulatory hotspots. Genetics, 180, 1909-1925.
11. Kang, H.M. et al. (2008b) Efficient control of population structure in model organism association mapping. Genetics, 178, 1709-1723.
12. Kang, H.M. et al. (2010) Variance component model to account for sample structure in genome-wide association studies. Nat. Genet., 42, 348-354.
13. Lawrence, N. (2005) Probabilistic non-linear principal component analysis with Gaussian process latent variable models. J. Mach. Learn. Res., 6, 1783-1816.
14. Leek, J.T. and Storey, J.D. (2007) Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genet., 3, e161.
15. Lin, S. et al. (2008) Model-based variance-stabilizing transformation for illumine microarray data. Nucleic Acids Res., 36, e11.
16. Lippert, C. et al. (2011) FaST linear mixed models for genome-wide association studies. Nat. Methods, 8, 833-835.
17. Listgarten, J. et al. (2010) Correction for hidden confounders in the genetic analysis of gene expression. Proc. Natl Acad. Sci. USA, 107, 16465-16470.
18. Litvin, O. et al. (2009) Modularity and interactions in the genetics of gene expression. Proc. Natl Acad. Sci. USA, 106, 6441-6446.
19. Mackay, D.J. (1995) Probable networks and plausible predictions - a review of practical Bayesian methods for supervised neural networks. Network, 6, 469-505.
20. McCarthy, M.I. et al. (2008) Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat. Rev. Genet., 9, 356-369.
21. Montgomery, S. et al. (2010) Transcriptome genetics using second generation sequencing in a caucasian population. Nature, 464, 773-777.
22. Nath, A. et al. (2012) Using blood informative transcripts in geographical genomics: impact of lifestyle on gene expression in fijians. Front. Genet., 3, 243.
23. Nica, A. et al. (2011) The architecture of gene regulatory variation across multiple human tissues: the muther study. PLoS Genet., 7, e1002003.
24. Patton, E. et al. (1998) Cdc53 is a scaffold protein for multiple cdc34/skp1/f-box protein complexes that regulate cell division and methionine biosynthesis in yeast. Genes Dev., 12, 692-705.
25. Pickrell, J. et al. (2010) Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature, 464, 768-772.
26. Price, A.L. et al. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet., 38, 904-909.
27. Price, A.L. et al. (2010) New approaches to population stratification in genome-wide association studies. Nat. Rev. Genet., 11, 459-463.
28. Schadt, E. et al. (2005) An integrative genomics approach to infer causal associations between gene expression and disease. Nat. Genet., 37, 710-717.
29. Shimon, L. et al. (2008) ATP-induced allostery in the eukaryotic chaperonin cct is abolished by the mutation g345d in cct4 that renders yeast temperature-sensitive for growth. J. Mol. Biol., 377, 469-477.
30. Smith, E.N. and Kruglyak, L. (2008) Gene-environment interaction in yeast gene expression. PLoS Biol., 6, e83.
31. Stegle, O. et al. (2010) A Bayesian framework to account for complex non-genetic factors in gene expression levels greatly increases power in eQTL studies. PLoS Comput. Biol., 6, e1000770.
32. Stegle, O. et al. (2012) Using probabilistic estimation of expression residuals (peer) to obtain increased power and interpretability of gene expression analyses. Nat. Protoc., 7, 500-507.
33. Stoler, S. et al. (2007) Scm3, an essential Saccharomyces cerevisiae centromere protein required for g2/m progression and cse4 localization. Proc. Natl Acad. Sci. USA, 104, 10571.
34. Storey, J. and Tibshirani, R. (2003) Statistical significance for genomewide studies. Proc. Natl Acad. Sci. USA, 100, 9440.
35. Stranger, B. et al. (2007) Population genomics of human gene expression. Nat. Genet., 39, 1217-1224.
36. Stranger, B. et al. (2012) Patterns of cis regulatory variation in diverse human populations. PLoS Genet., 8, e1002639.
37. Tiedje, C. et al. (2008) The rho gdi rdi1 regulates rho gtpases by distinct mechanisms. Mol. Biol. Cell, 19, 2885-2896.
38. Vinuela, A. et al. (2010) Genome-wide gene expression regulation as a function of genotype and age in C. elegans. Genome Res., 20, 929-937.
39. West, M. et al. (2007) Global eqtl mapping reveals the complex genetic architecture of transcript-level variation in arabidopsis. Genetics, 175, 1441-1450.
40. Zhu, C. et al. (1997) Algorithm 778: L-bfgs-b: Fortran subroutines for large-scale bound-constrained optimization. ACM Trans. Math. Softw., 23, 550-560.