Defining gene and QTL networks
Tài liệu tham khảo
Doerge, 2002, Mapping and analysis of quantitative trait loci in experimental populations, Nat Rev Genet, 3, 43, 10.1038/nrg703
Jansen, 2003, Studying complex biological systems using multifactorial perturbation, Nat Rev Genet, 4, 145, 10.1038/nrg996
Gilad, 2008, Revealing the architecture of gene regulation: the promise of eQTL studies, Trends Genet, 24, 408, 10.1016/j.tig.2008.06.001
Johannes, 2008, Epigenome dynamics: a quantitative genetics perspective, Nat Rev Genet, 9, 883, 10.1038/nrg2467
Martienssen, 2005, Epigenomic mapping in Arabidopsis using tiling microarrays, Chromosome Res, 13, 299, 10.1007/s10577-005-1507-2
Jansen, 2001, Genetical genomics: the added value from segregation, Trends Genet, 17, 388, 10.1016/S0168-9525(01)02310-1
Li, 2008, Generalizing genetical genomics: getting added value from environmental perturbation, Trends Genet, 24, 518, 10.1016/j.tig.2008.08.001
Chaibub Neto, 2008, Inferring causal phenotype networks from segregating populations, Genetics, 179, 1089, 10.1534/genetics.107.085167
Schadt, 2005, An integrative genomics approach to infer causal associations between gene expression and disease, Nat Genet, 37, 710, 10.1038/ng1589
Li, 2006, Structural model analysis of multiple quantitative traits, PLoS Genet, 2, e114, 10.1371/journal.pgen.0020114
Adewale, 2008, Pathway analysis of microarray data via regression, J Comput Biol, 15, 269, 10.1089/cmb.2008.0002
Liu, 2008, Gene network inference via structural equation modeling in genetical genomics experiments, Genetics, 178, 1763, 10.1534/genetics.107.080069
Zhu, 2007, Increasing the power to detect causal associations by combining genotypic and expression data in segregating populations, PLoS Comput Biol, 3, e69, 10.1371/journal.pcbi.0030069
Wright, 1921, Correlation and causation, J Agric Res, 201, 557
DeCook, 2006, Genetic regulation of gene expression during shoot development in Arabidopsis, Genetics, 172, 1155, 10.1534/genetics.105.042275
Keurentjes, 2007, Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci, Proc Natl Acad Sci U S A, 104, 1708, 10.1073/pnas.0610429104
Wang, 2008, Combining classical trait and microarray data to dissect transcriptional regulation: a case study, Theor Appl Genet, 116, 683, 10.1007/s00122-007-0701-3
Kliebenstein, 2006, Identification of QTLs controlling gene expression networks defined a priori, BMC Bioinformatics, 7, 308, 10.1186/1471-2105-7-308
Juenger, 2006, Natural genetic variation in whole-genome expression in Arabidopsis thaliana: the impact of physiological QTL introgression, Mol Ecol, 15, 1351, 10.1111/j.1365-294X.2006.02774.x
West, 2007, Global eQTL mapping reveals the complex genetic architecture of transcript-level variation in Arabidopsis, Genetics, 175, 1441, 10.1534/genetics.106.064972
Vuylsteke, 2006, Genetic dissection of transcriptional regulation by cDNA-AFLP, Plant J, 45, 439, 10.1111/j.1365-313X.2005.02630.x
Druka, 2008, Exploiting regulatory variation to identify genes underlying quantitative resistance to the wheat stem rust pathogen Puccinia graminis f. sp. tritici in barley, Theor Appl Genet, 117, 261, 10.1007/s00122-008-0771-x
Kirst, 2005, Genetic architecture of transcript-level variation in differentiating xylem of a eucalyptus hybrid, Genetics, 169, 2295, 10.1534/genetics.104.039198
Potokina, 2008, Tissue-dependent limited pleiotropy affects gene expression in barley, Plant J, 56, 287, 10.1111/j.1365-313X.2008.03601.x
Potokina, 2008, Gene expression quantitative trait locus analysis of 16,000 barley genes reveals a complex pattern of genome-wide transcriptional regulation, Plant J, 53, 90, 10.1111/j.1365-313X.2007.03315.x
Shi, 2007, Identification of candidate genes associated with cell wall digestibility and eQTL (expression quantitative trait loci) analysis in a Flint×Flint maize recombinant inbred line population, BMC Genomics, 8, 22, 10.1186/1471-2164-8-22
Springer, 2007, Allele-specific expression patterns reveal biases and embryo-specific parent-of-origin effects in hybrid maize, Plant Cell, 19, 2391, 10.1105/tpc.107.052258
Gilad, 2006, Using DNA microarrays to study natural variation, Curr Opin Genet Dev, 16, 553, 10.1016/j.gde.2006.09.005
Alberts, 2007, Sequence polymorphisms cause many false cis eQTLs, PLoS ONE, 2, e622, 10.1371/journal.pone.0000622
Bing, 2005, Genetical genomics analysis of a yeast segregant population for transcription network inference, Genetics, 170, 533, 10.1534/genetics.105.041103
Kulp, 2006, Causal inference of regulator–target pairs by gene mapping of expression phenotypes, BMC Genomics, 7, 125, 10.1186/1471-2164-7-125
Stylianou, 2008, Applying gene expression, proteomics and single-nucleotide polymorphism analysis for complex trait gene identification, Genetics, 178, 1795, 10.1534/genetics.107.081216
de Koning, 2005, Genetical genomics in humans and model organisms, Trends Genet, 21, 377, 10.1016/j.tig.2005.05.004
Breitling, 2008, Genetical genomics: spotlight on QTL hotspots, PLoS Genet, 4, e1000232, 10.1371/journal.pgen.1000232
Fu, 2007, MetaNetwork: a computational protocol for the genetic study of metabolic networks, Nat Protoc, 2, 685, 10.1038/nprot.2007.96
Keurentjes, 2006, The genetics of plant metabolism, Nat Genet, 38, 842, 10.1038/ng1815
Rowe, 2008, Biochemical networks and epistasis shape the Arabidopsis thaliana metabolome, Plant Cell, 20, 1199, 10.1105/tpc.108.058131
Hill, 2008, Data and theory point to mainly additive genetic variance for complex traits, PLoS Genet, 4, e1000008, 10.1371/journal.pgen.1000008
Wentzell, 2007, Linking metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways, PLoS Genet, 3, 1687, 10.1371/journal.pgen.0030162
Schauer, 2008, Mode of inheritance of primary metabolic traits in tomato, Plant Cell, 20, 509, 10.1105/tpc.107.056523
Fu J, Keurentjes JJB, Bouwmeester H, America T, Verstappen FWA, Ward JL, Beale MH, de Vos RCH, Dijkstra M, Scheltema RA, et al.: System-wide molecular evidence for phenotypic buffering in Arabidopsis. Nat Genet 2009, in press, doi:10.1038/ng.308.
Coffman, 2005, Identification of co-regulated transcripts affecting male body size in Drosophila, Genome Biol, 6, R53, 10.1186/gb-2005-6-6-r53
Jansen, 2002, Errors in genomics and proteomics, Nat Biotechnol, 20, 19, 10.1038/nbt0102-19b
Franke, 2006, Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes, Am J Hum Genet, 78, 1011, 10.1086/504300
Wu, 2008, Gene set enrichment in eQTL data identifies novel annotations and pathway regulators, PLoS Genet, 4, e1000070, 10.1371/journal.pgen.1000070
Zhu, 2008, Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks, Nat Genet, 40, 854, 10.1038/ng.167
Chesler, 2008, The Collaborative Cross at Oak Ridge National Laboratory: developing a powerful resource for systems genetics, Mamm Genome, 19, 382, 10.1007/s00335-008-9135-8
Churchill, 2004, The Collaborative Cross, a community resource for the genetic analysis of complex traits, Nat Genet, 36, 1133, 10.1038/ng1104-1133
Aranzana, 2005, Genome-wide association mapping in Arabidopsis identifies previously known flowering time and pathogen resistance genes, PLoS Genet, 1, e60, 10.1371/journal.pgen.0010060
Gonzalez-Martinez, 2008, Association genetics in Pinus taeda L. II. Carbon isotope discrimination, Heredity, 101, 19, 10.1038/hdy.2008.21
Kim, 2006, Association mapping with single-feature polymorphisms, Genetics, 173, 1125, 10.1534/genetics.105.052720
Rosenberg, 2006, A general population-genetic model for the production by population structure of spurious genotype–phenotype associations in discrete, admixed or spatially distributed populations, Genetics, 173, 1665, 10.1534/genetics.105.055335
Zhao, 2007, Association mapping of leaf traits, flowering time, and phytate content in Brassica rapa, Genome, 50, 963, 10.1139/G07-078
Zhao, 2007, An Arabidopsis example of association mapping in structured samples, PLoS Genet, 3, e4, 10.1371/journal.pgen.0030004
Wayne, 2002, Combining mapping and arraying: an approach to candidate gene identification, Proc Natl Acad Sci U S A, 99, 14903, 10.1073/pnas.222549199