Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies

Genome Biology

Volumn 15, Issue 4, 2014, Pages

  J Joo, Jong W ^a   Sul, Jae H ^b   Han, Buhm ^c,d   Ye, Chun ^d   Eskin, Eleazar ^a,b,e  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Engineering IV   (United States)

^c BRIGHAM AND WOMEN S HOSPITAL   (United States)

^d BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^e UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CONTROLLED STUDY; GENE EXPRESSION; GENE LOCATION; GENE MAPPING; GENETIC HETEROGENEITY; GENETIC REGULATION; HEREDITY; QUANTITATIVE TRAIT LOCUS; STATISTICAL ANALYSIS; ALGORITHM; GENE EXPRESSION PROFILING; GENETICS; PROCEDURES; REGULATORY SEQUENCE; SENSITIVITY AND SPECIFICITY; SINGLE NUCLEOTIDE POLYMORPHISM; YEAST;

ALGORITHMS; GENE EXPRESSION PROFILING; POLYMORPHISM, SINGLE NUCLEOTIDE; QUANTITATIVE TRAIT LOCI; REGULATORY SEQUENCES, NUCLEIC ACID; SENSITIVITY AND SPECIFICITY; YEASTS;

EID: 84899636211     PISSN: None     EISSN: 1474760X     Source Type: Journal    
DOI: 10.1186/gb-2014-15-4-r61     Document Type: Article

References (34)

1. Brem RB, Yvert G, Clinton R, Kruglyak L. Genetic dissection of transcriptional regulation in budding yeast. Science 2002, 296:752-755. doi: 10.1126/science.1069516, 10.1126/science.1069516, 11923494.
2. Brem RB, Kruglyak L. The landscape of genetic complexity across 5,700 gene expression traits in yeast. Proc Natl Acad Sci USA 2005, 102:1572-1577. doi: 10.1073/pnas.0408709102, 10.1073/pnas.0408709102, 547855, 15659551.
3. Keurentjes JJB, Fu J, Terpstra IR, Garcia JM, van den Ackerveken G, Snoek LB, Peeters AJM, Vreugdenhil D, Koornneef M, Jansen RC. Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci. Proc Natl Acad Sci USA 2007, 104:1708-1713. [doi: 10.1073/pnas.0610429104], 10.1073/pnas.0610429104, 1785256, 17237218.
4. Chesler EJ, Lu L, Shou S, Qu Y, Gu J, Wang J, Hsu HC, Mountz JD, Baldwin NE, Langston MA, Threadgill DW, Manly KF, Williams RW. Complex trait analysis of gene expression uncovers polygenic and pleiotropic networks that modulate nervous system function. Nat Genet 2005, 37:233-242. doi: 10.1038/ng1518, 10.1038/ng1518, 15711545.
5. Bystrykh L, Weersing E, Dontje B, Sutton S, Pletcher MT, Wiltshire T, Su AI, Vellenga E, Wang J, Manly KF, Lu L, Chesler EJ, Alberts R, Jansen RC, Williams RW, Cooke MP, de Haan G. Uncovering regulatory pathways that affect hematopoietic stem cell function using 'genetical genomics'. Nat Genet 2005, 37:225-232. doi: 10.1038/ng1497, 10.1038/ng1497, 15711547.
6. Cheung VG, Spielman RS, Ewens KG, Weber TM, Morley M, Burdick JT. Mapping determinants of human gene expression by regional and genome-wide association. Nature 2005, 437:1365-1369. doi: 10.1038/nature04244, 10.1038/nature04244, 3005311, 16251966.
7. Stranger BE, Nica AC, Forrest MS, Dimas A, Bird CP, Beazley C, Ingle CE, Dunning M, Flicek P, Koller D, Montgomery S, Deloukas P, Tavaré S Population genomics of human gene expression. Nat Genet 2007, 39:1217-1224. doi: 10.1038/ng2142, 10.1038/ng2142, 2683249, 17873874, Tavaré S.
8. Emilsson V, Thorleifsson G, Zhang B, Leonardson AS, Zink F, Zhu J, Carlson S, Helgason A, Walters GB, Gunnarsdottir S, Mouy M, Steinthorsdottir V, Eiriksdottir GH, Bjornsdottir G, Reynisdottir I, Gudbjartsson D, Helgadottir A, Jonasdottir A, Jonasdottir A, Styrkarsdottir U, Gretarsdottir S, Magnusson KP, Stefansson H, Fossdal R, Kristjansson K, Gislason HG, Stefansson T, Leifsson BG, Thorsteinsdottir U, Lamb JR, et al. Genetics of gene expression and its effect on disease. Nature 2008, 452:423-428. doi: 10.1038/nature06758, 10.1038/nature06758, 18344981.
9. Spielman RS, Bastone LA, Burdick JT, Morley M, Ewens WJ, Cheung VG. Common genetic variants account for differences in gene expression among ethnic groups. Nat Genet 2007, 39:226-231. doi: 10.1038/ng1955, 10.1038/ng1955, 3005333, 17206142.
10. Michaelson JJ, Loguercio S, Beyer A. Detection and interpretation of expression quantitative trait loci (eQTL). Methods 2009, 48:265-276. doi: 10.1016/j.ymeth.2009.03.004, 10.1016/j.ymeth.2009.03.004, 19303049.
11. Cervino AC, Li G, Edwards S, Zhu J, Laurie C, Tokiwa G, Lum PY, Wang S, Castellani LW, Castellini LW, Lusis AJ, Carlson S, Sachs AB, Schadt EE. Integrating QTL and high-density SNP analyses in mice to identify Insig2 as a susceptibility gene for plasma cholesterol levels. Genomics 2005, 86:505-517. doi: 10.1016/j.ygeno.2005.07.010, 10.1016/j.ygeno.2005.07.010, 16126366.
12. Hillebrandt S, Wasmuth HE, Weiskirchen R, Hellerbrand C, Keppeler H, Werth A, Schirin-Sokhan R, Wilkens G, Geier A, Lorenzen J, Köhl J, Gressner AM, Matern S, Lammert F Complement factor 5 is a quantitative trait gene that modifies liver fibrogenesis in mice and humans. Nat Genet 2005, 37:835-843. doi: 10.1038/ng1599, 10.1038/ng1599, 15995705, Lammert F.
13. Wang X, Korstanje R, Higgins D, Paigen B. Haplotype analysis in multiple crosses to identify a QTL gene. Genome Res 2004, 14:1767-1772. doi: 10.1101/gr.2668204, 10.1101/gr.2668204, 515323, 15310659.
14. Peirce JL, Li H, Wang J, Manly KF, Hitzemann RJ, Belknap JK, Rosen GD, Goodwin S, Sutter TR, Williams RW, Lu L. How replicable are mRNA expression QTL?. Mamm Genome 2006, 17:643-656. doi: 10.1007/s00335-005-0187-8, 10.1007/s00335-005-0187-8, 16783644.
15. Churchill GA. Fundamentals of experimental design for cDNA microarrays. Nat Genet 2002, 32 Suppl:490-495. doi: 10.1038/ng1031.
16. Fare TL, Coffey EM, Dai H, He YD, Kessler DA, Kilian KA, Koch JE, LeProust E, Marton MJ, Meyer MR, Stoughton RB, Tokiwa GY, Wang Y. Effects of atmospheric ozone on microarray data quality. Anal Chem 2003, 75:4672-4675. 10.1021/ac034241b, 14632079.
17. Branham WS, Melvin CD, Han T, Desai VG, Moland CL, Scully AT, Fuscoe JC. Elimination of laboratory ozone leads to a dramatic improvement in the reproducibility of microarray gene expression measurements. BMC Biotechnol 2007, 7:8. doi: 10.1186/1472-6750-7-8, 10.1186/1472-6750-7-8, 1800842, 17295919.
18. Kang HM, Ye C, Eskin E. Accurate discovery of expression quantitative trait loci under confounding from spurious and genuine regulatory hotspots. Genetics 2008, 180:1909-1925. doi: 10.1534/genetics.108.094201, 10.1534/genetics.108.094201, 2600931, 18791227.
19. Leek JT, Storey JD. Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genet 2007, 3:1724-1735. doi: 10.1371/journal.pgen.0030161, 1994707, 17907809.
20. Listgarten J, Kadie C, Schadt EE, Heckerman D. Correction for hidden confounders in the genetic analysis of gene expression. Proc Natl Acad Sci USA 2010, 107:16465-16470. doi: 10.1073/pnas.1002425107, 10.1073/pnas.1002425107, 2944732, 20810919.
21. Fusi N, Stegle O, Lawrence ND. Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studies. PLoS Comput Biol 2012, 8:1002330. doi: 10.1371/journal.pcbi.1002330.
22. Foss EJ, Radulovic D, Shaffer SA, Ruderfer DM, Bedalov A, Goodlett DR, Kruglyak L. Genetic basis of proteome variation in yeast. Nat Genet 2007, 39:1369-1375. doi: 10.1038/ng.2007.22, 10.1038/ng.2007.22, 17952072.
23. Perlstein EO, Ruderfer DM, Roberts DC, Schreiber SL, Kruglyak L. Genetic basis of individual differences in the response to small-molecule drugs in yeast. Nat Genet 2007, 39:496-502. doi: 10.1038/ng1991, 10.1038/ng1991, 17334364.
24. Han B, Eskin E. Interpreting meta-analyses of genome-wide association studies. PLoS Genet 2012, 8:1002555. doi: 10.1371/journal.pgen.1002555.
25. Smith EN, Kruglyak L. Gene-environment interaction in yeast gene expression. PLoS Biol 2008, 6:83. doi: 10.1371/journal.pbio.0060083.
26. Devlin B, Roeder K. Genomic control for association studies. Biometrics 1999, 55:997-1004. 10.1111/j.0006-341X.1999.00997.x, 11315092.
27. Yvert G, Brem RB, Whittle J, Akey JM, Foss E, Smith EN, Mackelprang R, Kruglyak L. Trans-acting regulatory variation in Saccharomyces cerevisiae, and the role of transcription factors. Nat Genet 2003, 35:57-64.
28. Kang HM, Zaitlen NA, Wade CM, Kirby A, Heckerman D, Daly MJ, Eskin E. Efficient control of population structure in model organism association mapping. Genetics 2008, 178:1709-1723. doi: 10.1534/genetics.107.080101, 10.1534/genetics.107.080101, 2278096, 18385116.
29. Yu J, Pressoir G, Briggs WH, Vroh Bi I, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 2006, 38:203-208. doi: 10.1038/ng1702, 10.1038/ng1702, 16380716.
30. Zhao K, Aranzana MJ, Kim S, Lister C, Shindo C, Tang C, Toomajian C, Zheng H, Dean C, Marjoram P, Nordborg M. An Arabidopsis example of association mapping in structured samples. PLoS Genet 2007, 3:4. doi: 10.1371/journal.pgen.0030004.
31. Han B, Eskin E. Random-effects model aimed at discovering associations in meta-analysis of genome-wide association studies. Am J Hum Genet 2011, 88:586-598. doi: 10.1016/j.ajhg.2011.04.014, 10.1016/j.ajhg.2011.04.014, 3146723, 21565292.
32. Stephens M, Balding DJ. Bayesian statistical methods for genetic association studies. Nat Rev Genet 2009, 10:681-690. doi: 10.1038/nrg2615, 10.1038/nrg2615, 19763151.
33. Marchini J, Howie B, Myers S, McVean G, Donnelly P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 2007, 39:906-913. doi: 10.1038/ng2088, 10.1038/ng2088, 17572673.
34. Lippert C, Listgarten J, Liu Y, Kadie CM, Davidson RI, Heckerman D. Fast linear mixed models for genome-wide association studies. Nat Methods 2011, 8:833-835. doi: 10.1038/nmeth.1681, 10.1038/nmeth.1681, 21892150.