EQTL Epistasis - Challenges and Computational Approaches

Overview

Journal Front Genet

Date 2013 Jun 12

PMID 23755066

Citations 18

Authors

Yang Huang

Stefan Wuchty

Teresa M Przytycka

Affiliations

Soon will be listed here.

Abstract

The determination of expression quantitative trait loci (eQTL) epistasis - a form of functional interaction between genetic loci that affect gene expression - is an important step toward the thorough understanding of gene regulation. Since gene expression has emerged as an "intermediate" molecular phenotype eQTL epistasis might help to explain the relationship between genotype and higher level organismal phenotypes such as diseases. A characteristic feature of eQTL analysis is the big number of tests required to identify associations between gene expression and genetic loci variability. This problem is aggravated, when epistatic effects between eQTLs are analyzed. In this review, we discuss recent algorithmic approaches for the detection of eQTL epistasis and highlight lessons that can be learned from current methods.

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References

Kim Y, Wuchty S, Przytycka T . Identifying causal genes and dysregulated pathways in complex diseases. PLoS Comput Biol. 2011; 7(3):e1001095. PMC: 3048384. DOI: 10.1371/journal.pcbi.1001095. View

Barabasi A, Oltvai Z . Network biology: understanding the cell's functional organization. Nat Rev Genet. 2004; 5(2):101-13. DOI: 10.1038/nrg1272. View

Azevedo L, Carneiro J, van Asch B, Moleirinho A, Pereira F, Amorim A . Epistatic interactions modulate the evolution of mammalian mitochondrial respiratory complex components. BMC Genomics. 2009; 10:266. PMC: 2711975. DOI: 10.1186/1471-2164-10-266. View

Piepho H, Gauch Jr H . Marker pair selection for mapping quantitative trait loci. Genetics. 2001; 157(1):433-44. PMC: 1461460. DOI: 10.1093/genetics/157.1.433. View

Kang H, Yang X, Chen R, Zhang B, Corona E, Schadt E . Integration of disease-specific single nucleotide polymorphisms, expression quantitative trait loci and coexpression networks reveal novel candidate genes for type 2 diabetes. Diabetologia. 2012; 55(8):2205-13. PMC: 3390705. DOI: 10.1007/s00125-012-2568-3. View

van Wageningen S, Kemmeren P, Lijnzaad P, Margaritis T, Benschop J, de Castro I . Functional overlap and regulatory links shape genetic interactions between signaling pathways. Cell. 2010; 143(6):991-1004. PMC: 3073509. DOI: 10.1016/j.cell.2010.11.021. View

Yang C, He Z, Wan X, Yang Q, Xue H, Yu W . SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies. Bioinformatics. 2008; 25(4):504-11. DOI: 10.1093/bioinformatics/btn652. View

Jiang R, Tang W, Wu X, Fu W . A random forest approach to the detection of epistatic interactions in case-control studies. BMC Bioinformatics. 2009; 10 Suppl 1:S65. PMC: 2648748. DOI: 10.1186/1471-2105-10-S1-S65. View

Zou W, Zeng Z . Multiple interval mapping for gene expression QTL analysis. Genetica. 2009; 137(2):125-34. DOI: 10.1007/s10709-009-9365-z. View

10.

Herold C, Steffens M, Brockschmidt F, Baur M, Becker T . INTERSNP: genome-wide interaction analysis guided by a priori information. Bioinformatics. 2009; 25(24):3275-81. DOI: 10.1093/bioinformatics/btp596. View

11.

Ritchie M, Hahn L, Roodi N, BAILEY L, Dupont W, Parl F . Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. Am J Hum Genet. 2001; 69(1):138-47. PMC: 1226028. DOI: 10.1086/321276. View

12.

Lehner B . Molecular mechanisms of epistasis within and between genes. Trends Genet. 2011; 27(8):323-31. DOI: 10.1016/j.tig.2011.05.007. View

13.

Brem R, Storey J, Whittle J, Kruglyak L . Genetic interactions between polymorphisms that affect gene expression in yeast. Nature. 2005; 436(7051):701-3. PMC: 1409747. DOI: 10.1038/nature03865. View

14.

Kapur K, Schupbach T, Xenarios I, Kutalik Z, Bergmann S . Comparison of strategies to detect epistasis from eQTL data. PLoS One. 2011; 6(12):e28415. PMC: 3242756. DOI: 10.1371/journal.pone.0028415. View

15.

Zhang X, Zou F, Wang W . FastChi: an efficient algorithm for analyzing gene-gene interactions. Pac Symp Biocomput. 2009; :528-39. PMC: 2728448. View

16.

Brem R, Yvert G, Clinton R, Kruglyak L . Genetic dissection of transcriptional regulation in budding yeast. Science. 2002; 296(5568):752-5. DOI: 10.1126/science.1069516. View

17.

Huang Y, Siwo G, Wuchty S, Ferdig M, Przytycka T . Symmetric Epistasis Estimation (SEE) and its application to dissecting interaction map of Plasmodium falciparum. Mol Biosyst. 2012; 8(5):1544-52. PMC: 3480327. DOI: 10.1039/c2mb05333k. View

18.

Wan X, Yang C, Yang Q, Xue H, Tang N, Yu W . Predictive rule inference for epistatic interaction detection in genome-wide association studies. Bioinformatics. 2009; 26(1):30-7. DOI: 10.1093/bioinformatics/btp622. View

19.

Cookson W, Liang L, Abecasis G, Moffatt M, Lathrop M . Mapping complex disease traits with global gene expression. Nat Rev Genet. 2009; 10(3):184-94. PMC: 4550035. DOI: 10.1038/nrg2537. View

20.

Van Steen K . Travelling the world of gene-gene interactions. Brief Bioinform. 2011; 13(1):1-19. DOI: 10.1093/bib/bbr012. View