Bayesian mapping of genotype x expression interactions in quantitative and qualitative traits

被引:63
作者
Hoti, F. [1 ]
Sillanpaa, M. J. [1 ]
机构
[1] Univ Helsinki, Rolf Nevanlinna Inst, Dept Math & Stat, FIN-00014 Helsinki, Finland
关键词
gene expression; QTL; molecular markers; sparse method; Bayes;
D O I
10.1038/sj.hdy.6800817
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
A novel Bayesian gene mapping method, which can simultaneously utilize both molecular marker and gene expression data, is introduced. The approach enables a quantitative or qualitative phenotype to be expressed as a linear combination of the marker genotypes, gene expression levels, and possible genotype x gene expression interactions. The interaction data, given as marker-gene pairs, contains possible in cis and in trans effects obtained from earlier allelic expression studies, genetical genomics studies, biological hypotheses, or known pathways. The method is presented for an inbred line cross design and can be easily generalized to handle other types of populations and designs. The model selection is based on the use of effect-specific variance components combined with Jeffreys' non-informative prior - the method operates by adaptively shrinking marker, expression, and interaction effects toward zero so that non-negligible effects are expected to occur only at very few positions. The estimation of the model parameters and the handling of missing genotype or expression data is performed via Markov chain Monte Carlo sampling. The potential of the method including heritability estimation is presented using simulated examples and novel summary statistics. The method is also applied to a real yeast data set with known pathways.
引用
收藏
页码:4 / 18
页数:15
相关论文
共 67 条
[1]   BAYESIAN-ANALYSIS OF BINARY AND POLYCHOTOMOUS RESPONSE DATA [J].
ALBERT, JH ;
CHIB, S .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1993, 88 (422) :669-679
[2]   A haplotype map of the human genome [J].
Altshuler, D ;
Brooks, LD ;
Chakravarti, A ;
Collins, FS ;
Daly, MJ ;
Donnelly, P ;
Gibbs, RA ;
Belmont, JW ;
Boudreau, A ;
Leal, SM ;
Hardenbol, P ;
Pasternak, S ;
Wheeler, DA ;
Willis, TD ;
Yu, FL ;
Yang, HM ;
Zeng, CQ ;
Gao, Y ;
Hu, HR ;
Hu, WT ;
Li, CH ;
Lin, W ;
Liu, SQ ;
Pan, H ;
Tang, XL ;
Wang, J ;
Wang, W ;
Yu, J ;
Zhang, B ;
Zhang, QR ;
Zhao, HB ;
Zhao, H ;
Zhou, J ;
Gabriel, SB ;
Barry, R ;
Blumenstiel, B ;
Camargo, A ;
Defelice, M ;
Faggart, M ;
Goyette, M ;
Gupta, S ;
Moore, J ;
Nguyen, H ;
Onofrio, RC ;
Parkin, M ;
Roy, J ;
Stahl, E ;
Winchester, E ;
Ziaugra, L ;
Shen, Y .
NATURE, 2005, 437 (7063) :1299-1320
[3]  
[Anonymous], 5 WORLD C GEN APPL L
[4]   Gene Ontology: tool for the unification of biology [J].
Ashburner, M ;
Ball, CA ;
Blake, JA ;
Botstein, D ;
Butler, H ;
Cherry, JM ;
Davis, AP ;
Dolinski, K ;
Dwight, SS ;
Eppig, JT ;
Harris, MA ;
Hill, DP ;
Issel-Tarver, L ;
Kasarskis, A ;
Lewis, S ;
Matese, JC ;
Richardson, JE ;
Ringwald, M ;
Rubin, GM ;
Sherlock, G .
NATURE GENETICS, 2000, 25 (01) :25-29
[5]   Nonadditive gene expression in diploid and triploid hybrids of maize [J].
Auger, DL ;
Gray, AD ;
Ream, TS ;
Kato, A ;
Coe, EH ;
Birchler, JA .
GENETICS, 2005, 169 (01) :389-397
[6]   Co-localization of differentially expressed genes and shared susceptibility loci in human autoimmunity [J].
Aune, TM ;
Parker, JS ;
Maas, K ;
Liu, Z ;
Olsen, NJ ;
Moore, JH .
GENETIC EPIDEMIOLOGY, 2004, 27 (02) :162-172
[7]  
Basten CJ, 2003, QTL CARTOGRAPHER VER
[8]   Genetic dissection of transcriptional regulation in budding yeast [J].
Brem, RB ;
Yvert, G ;
Clinton, R ;
Kruglyak, L .
SCIENCE, 2002, 296 (5568) :752-755
[9]   A model selection approach for the identification of quantitative trait loci in experimental crosses [J].
Broman, KW ;
Speed, TP .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2002, 64 :641-656
[10]   The use and analysis of microarray data [J].
Butte, A .
NATURE REVIEWS DRUG DISCOVERY, 2002, 1 (12) :951-960