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Genetics of global gene expression
Abstract
A new field of genetic analysis of global gene expression has emerged in recent years, driven by the realization that traditional techniques of linkage and association analysis can be applied to thousands of transcript levels measured by microarrays. Genetic dissection of transcript abundance has shed light on the architecture of quantitative traits, provided a new approach for connecting DNA sequence variation with phenotypic variation, and improved our understanding of transcriptional regulation and regulatory variation.
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“Previous eQTL studies in genetically diverse populations suggest that the most significant eQTL tend to be local (Rockman and Kruglyak 2006; Pickrell et al. 2010; Aylor et al. 2011; Lappalainen et al. 2013).”
From RNA-Seq Alignment to Individualized Genomes Improves Transcript Abundance Estimates in Multiparent Populations (2014) · cites this paper as Rockman and Kruglyak 2006
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The genetics of plant metabolism
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Keurentjes, J. J. B., Koornneef, M., & Vreugdenhil, D. (2008) · Current Opinion in Plant Biology · doi:10.1016/j.pbi.2008.01.006 · Cited by 80
“Current Opinion in Plant Biology 2008, 11:123–128 other mechanisms of local and distant regulation, both in cis and in trans, are imaginable [30 ].”
BackgroundSanto, S. D., Zenoni, S., Sandri, M., Lorenzis, G. D., Magris, G., Paoli, E. D., Gaspero, G. D., Fabbro, C. D., Morgante, M., Brancadoro, L., et al. (2018) · The Plant Journal · doi:10.1111/tpj.13834 · Cited by 80
“Variations in gene expression reflecting different types of genetic and epigenetic regulation can be used as a proxy to define genotype–phenotype relationships in a changing environment (Rockman and Kruglyak, 2006; Perry and Mank, 2014).”
BackgroundSex- and age-interacting eQTLs in human complex diseases
Yao, C., Joehanes, R., Johnson, A. D., Huan, T., Esko, T., Ying, S., Freedman, J. E., Murabito, J. M., Lunetta, K. L., Metspalu, A., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt582 · Cited by 78
Microarray challenges in ecology.
Kammenga, J., Herman, M. A., Ouborg, N., Johnson, L., & Breitling, R. (2007) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2007.01.013 · Cited by 79
“discoveries with regard to the genetics of evolutionary trajectories [45].”
Cis -regulatory elements explain most of the mRNA stability variation across genes in yeast
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BackgroundPapeta, N., Chan, K.-T., Prakash, S., Martino, J., Kiryluk, K., Ballard, D., Bruggeman, L. A., Frankel, R. Z., Zheng, Z., Klotman, P. E., et al. (2009) · Journal of Clinical Investigation · doi:10.1172/jci37131 · Cited by 71
“Because genes that share a common transregulator are likely to participate in a functionally related pathway, they can be used to build molecular networks underlying complex traits (26, 29, 30).”
BackgroundResultAsymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical Model
Chen, M., Ren, Z., Zhao, H.-Y., & Zhou, H. H. (2013) · Journal of the American Statistical Association · doi:10.1080/01621459.2015.1010039 · Cited by 69
Computational drug repositioning for rare diseases in the era of precision medicine
Delavan, B., Roberts, R. A., Huang, R., Bao, W., Tong, W., & Liu, Z. (2017) · Drug Discovery Today · doi:10.1016/j.drudis.2017.10.009 · Cited by 88
The genetic basis of evolutionary change in gene expression levels
Emerson, J. J., & Li, W. (2010) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2010.0005 · Cited by 72
Genetics of gene expression in immunity to infection
Fairfax, B. P., & Knight, J. C. (2014) · Current Opinion in Immunology · doi:10.1016/j.coi.2014.07.001 · Cited by 122
“This variation has a strong genetic component, with polymorphisms associating with gene expression known as expression quantitative trait loci (eQTL) [2,3].”
BackgroundGaertner, B. E., & Phillips, P. C. (2010) · Genetics Research · doi:10.1017/s0016672310000601 · Cited by 61
“These effects are usually interpreted as being in either cis or trans, respectively, but in fact mapping resolution is usually too low to be particularly firm in this regard, especially for cis-acting factors (Rockman & Kruglyak, 2006).”
BackgroundEhrenreich, I. M., Gerke, J., & Kruglyak, L. (2009) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.2009.74.013 · Cited by 67
“Once the basic principles of the genetics of gene expression were understood in yeast, this new approach to studying quantitative genetic variation was quickly expanded to other organisms (for review, see Rockman and Kruglyak 2006).”
BackgroundSelf-citationData-driven assessment of eQTL mapping methods
Michaelson, J. J., Alberts, R., Schughart, K., & Beyer, A. (2010) · BMC Genomics · doi:10.1186/1471-2164-11-502 · Cited by 50
“A QTL where mRNA expression is the complex trait of interest is generally referred to as an expression QTL or eQTL [1].”
BackgroundGenomic characterization of esophageal squamous cell carcinoma from a high-risk population in China
Hu, N., Wang, C.-Y., Ng, D., Clifford, R., Yang, H., Tang, Z.-Z., Wang, Q.-H., Han, X.-Y., Giffen, C. A., Goldstein, A., et al. (2009) · Cancer Research · doi:10.1158/0008-5472.can-08-4622 · Cited by 66
“Thus far, analyses based on the identification of genetic loci have not been resolved at the level of individual genes and polymorphic alleles that affect gene expression (17).”
Natural variation of histone modification and its impact on gene expression in the rat genomePreprint
Rintisch, C., Heinig, M., Bauerfeind, A., Schäfer, S., Mieth, C., Patone, G., Hummel, O., Chen, W., Cook, S. A., Cuppen, E. P. J. G., et al. (2014) · Genome Research · doi:10.1101/gr.169029.113 · Cited by 59
Fleury, E., Moal, J., Boulo, V., Daniel, J., Mazurais, D., Hénaut, A., Corporeau, C., Boudry, P., Favrel, P., & Huvet, A. (2010) · Marine Biotechnology · doi:10.1007/s10126-009-9227-9 · Cited by 64
“We clearly expect that genetic mapping of the identified genes of which the expression can explain summer survival will shed light on the architecture of this trait (see Rockman and Kruglyak 2006).”
BackgroundWang, S., Zhang, L., Meyer, E., & Matz, M. V. (2009) · Genome biology · doi:10.1186/gb-2009-10-11-r126 · Cited by 61
“physiological traits [5,6].”
Allele-specific expression and eQTL analysis in mouse adipose tissue
Hasin-Brumshtein, Y., Hormozdiari, F., Martin, L., van Nas, A., Eskin, E., Lusis, A. J., & Drake, T. A. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-471 · Cited by 70
“Importantly, although microarrays generally do not measure gene expression in an allele-specific manner, a commonly accepted assumption in eQTL studies is that local associations likely act in a cis fashion; therefore, local and distal associations are often termed cis and trans respectively in the literature [11].”
BackgroundTranscriptome Analysis of Silver Carp (Hypophthalmichthys molitrix) by Paired-End RNA Sequencing
Fu, B., & He, S. (2012) · DNA Research · doi:10.1093/dnares/dsr046 · Cited by 61
Genomic modulators of the immune response
Knight, J. C. (2012) · Trends in Genetics · doi:10.1016/j.tig.2012.10.006 · Cited by 60
Gene Expression and Genetic Variation Data Implicate PCLO in Bipolar Disorder
Choi, K. H., Higgs, B. W., Wendland, J. R., Song, J. C., McMahon, F. J., & Webster, M. J. (2010) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.09.042 · Cited by 65
High-Resolution Mapping of Gene Expression Using Association in an Outbred Mouse Stock
Ghazalpour, A., Doss, S., Kang, H. M., Farber, C. R., Wen, P.-Z., Brozell, A., Rivera, R. M. C., Eskin, E., Smith, D., Drake, T. A., et al. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000149 · Cited by 53
“In general, the presence of eQTL hotspots indicates either the presence of a master regulator gene which regulates the expression of group of genes together or the presence of several tightly linked genes within the hotspot, each of which regulates the expression of subset of the genes which map to this locus [30].”
BackgroundGenomics and the evolution of phenotypic traits
Wray, G. A. (2013) · Annual Review of Ecology, Evolution, and Systematics · doi:10.1146/annurev-ecolsys-110512-135828 · Cited by 68
Nürnberg, S., Zhang, H., Hand, N. J., Bauer, R. C., Saleheen, D., Reilly, M. P., & Rader, D. J. (2016) · Circulation Research · doi:10.1161/circresaha.115.306464 · Cited by 60
“lipid levels,(7) carotid intima-media thickness,(45) or gene expression levels (eQTL).(46,47) eQTL studies combine genotype with gene expression level information—the latter usually assessed”
BackgroundCuenca, J., Aleza, P., Navarro, L., & Ollitrault, P. (2013) · Annals of Botany · doi:10.1093/aob/mct032 · Cited by 70
Genome‐level analysis of genetic regulation of liver gene expression networks
Gatti, D. M., Maki, A., Chesler, E., Kirova, R., Kosyk, O., Lu, L., Manly, K., Williams, R. W., Perkins, A., Langston, M. A., et al. (2007) · Hepatology · doi:10.1002/hep.21682 · Cited by 61
Imputing Gene Expression in Uncollected Tissues Within and Beyond GTEx
Wang, J., Gamazon, E. R., Pierce, B. L., Stranger, B. E., Im, H. K., Gibbons, R. D., Cox, N. J., Nicolae, D. L., & Chen, L. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.02.020 · Cited by 52
“More specifically, the three sources of expression data were (1) only the observed nerve expression data (from which 50% of GTEx nerve tissue was missing), (2) the observed and imputed data with varying imputation quality, and (3) the complete GTEx nerve expression data.”
BackgroundMethodResultInfluentialBicc1 is a genetic determinant of osteoblastogenesis and bone mineral density
Mesner, L. D., Ray, B. J., Hsu, Y., Manichaikul, A. W., Lum, E., Bryda, E. C., Rich, S. S., Rosen, C. J., Criqui, M. H., Allison, M., et al. (2014) · Journal of Clinical Investigation · doi:10.1172/jci73072 · Cited by 60
“For example, by generating global gene expression profiles in a genetic-mapping population, genes whose transcript levels are influenced by local or distant expression QTLs (eQTLs) can be identified on a genome-wide scale (15, 16).”
Clément‐Ziza, M., Marsellach, X., Codlin, S., Papadakis, M. A., Reinhardt, S., Rodríguez‐López, M., Martin, S., Marguerat, S., Schmidt, A., Lee, E., et al. (2014) · Molecular Systems Biology · doi:10.15252/msb.20145123 · Cited by 52
“…is the established phenomenon that increasing statistical power of an eQTL study increases the number of detected trans-eQTLs, whereas the number of detected cis-eQTLs starts to plateau (Schadt et al, 2003; Doss et al, 2005; Rockman & Kruglyak, 2006; Gerrits et al, 2009; Ackermann et al, 2013).”
Zyl, J. V. V., den Haan, R., & van Zyl, W. V. (2014) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-014-5647-1 · Cited by 59
Advances in Genetical Genomics of Plants
Joosen, R. V. L., Ligterink, W., Hilhorst, H. W. M., & Keurentjes, J. J. B. (2009) · Current Genomics · doi:10.2174/138920209789503914 · Cited by 59
“The ease to generate large families from experimental crosses and the ability to store genotypes in the form of seeds or clonal propagation make plants ideal subjects to study the mechanistic basis of genetic regulation of traits.”
BackgroundMoscou, M., Lauter, N., Steffenson, B., & Wise, R. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002208 · Cited by 58
“The intricacies of genetic inheritance of gene expression have contributed significantly to our current understanding of gene regulation [18,21,56,57].”
BackgroundExplaining inter-individual variability in phenotype
Turan, N., Katari, S., Coutifaris, C., & Sapienza, C. (2010) · Epigenetics · doi:10.4161/epi.5.1.10557 · Cited by 58
Identification of optimal prediction models using multi-omic data for selecting hybrid rice
Wang, S., Wei, J., Li, R., Qu, H., Chater, J. M., Ma, R., Li, Y., Xie, W., & Jia, Z. (2019) · Heredity · doi:10.1038/s41437-019-0210-6 · Cited by 75
Epigenomics of Major Depressive Disorders and Schizophrenia: Early Life Decides
Hoffmann, A., Sportelli, V., Ziller, M. J., & Spengler, D. (2017) · International Journal of Molecular Sciences · doi:10.3390/ijms18081711 · Cited by 65
“A meQTL is therefore defined as a genomic region that contains one or more DNA sequence variants that regulate the methylation level of other DNA regions harboring regulatory or genic sequences or sequences of unknown functions [119].”
BackgroundHigh-resolution mapping of cis -regulatory variation in budding yeast
Kita, R., Venkataram, S., Zhou, Y., & Fraser, H. B. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1717421114 · Cited by 59
Methylation quantitative trait locus analysis of osteoarthritis links epigenetics with genetic risk
Rushton, M. D., Reynard, L. N., Young, D. A., Shepherd, C., Aubourg, G., Gee, F., Darlay, R., Deehan, D. J., Cordell, H. J., & Loughlin, J. A. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv433 · Cited by 55
“Such loci are referred to as expression quantitative trait loci, or eQTLs (15).”
BackgroundBioinformatics tools toward GC-MS and LC-MS data analysis, management and visualization
Zhubanova, A., & Ogryzko, V. (2015) · doi:10.4172/0974-276x.s1.077 · Cited by 56
Lu, Y. C., Biancotto, A., Cheung, F., Remmers, E. F., Shah, N., McCoy, J. P., & Tsang, J. S. (2016) · Immunity · doi:10.1016/j.immuni.2016.10.025 · Cited by 51
“, 2015), as well as the average transcript and protein levels in a cell population (Cookson et al., 2009; Gilad et al., 2008; Rockman and Kruglyak, 2006), including major immune cell types such as T and dendritic cells (Lee et al.”
Lewis, J. A., Broman, A. T., Will, J., & Gasch, A. P. (2014) · Genetics · doi:10.1534/genetics.114.167429 · Cited by 62
“E-mail: agasch@wisc.edu Genetics, Vol. 198, 369–382 September 2014 369 (Gilad et al. 2008) (arguably due to the higher statistical power for their detection; Rockman and Kruglyak 2006; Kliebenstein 2009), and a notable number of genes are affected by both local and distant effectors (Brem et al.…”
BackgroundGenome organization and function in the cell nucleus
Rippe, K. (2011) · doi:10.1002/9783527639991 · Cited by 55
Integrating Global Gene Expression Analysis and Genetics
Farber, C. R., & Lusis, A. J. (2008) · Advances in genetics · doi:10.1016/s0065-2660(07)00420-8 · Cited by 52
“Recently, Rockman and Kruglyak (2006) have proposed a more general lexicon to describe cis and trans effects.”
BackgroundSnake Venomics: Fundamentals, Recent Updates, and a Look to the Next Decade
Tan, C. H. (2022) · Toxins · doi:10.3390/toxins14040247 · Cited by 67
“High dynamic resolution has been well established for genome-wide gene expression either with RNA microarrays [159] or next-generation sequencing [160,161], but in the case of venom proteomics the quantitative analysis is much trickier and more challenging.”
BackgroundGene regulatory divergence between locally adapted ecotypes in their native habitats
Gould, B. A., Chen, Y., & Lowry, D. B. (2018) · Molecular Ecology · doi:10.1111/mec.14852 · Cited by 56
Global assessment of imprinted gene expression in the bovine conceptus by next generation sequencing
Chen, Z., Hagen, D. E., Wang, J., Elsik, C. G., Ji, T., Siqueira, L. G. B., Hansen, P. J., & Rivera, R. M. (2016) · Epigenetics · doi:10.1080/15592294.2016.1184805 · Cited by 69
“ciseQTL refers to the class of genetic variants that affect gene expression on the same DNA molecule thus leading to allelespecific or allele-biased gene expression.(58) To determine whether monoallelic gene expression identified in the B.”
BackgroundGenetics and Regulatory Impact of Alternative Polyadenylation in Human B-Lymphoblastoid Cells
Yoon, O. K., Hsu, T. Y., Im, J. H., & Brem, R. B. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002882 · Cited by 51
“within populations underlie phenotypes of evolutionary and biomedical interest [1–3] and can serve as the basis for inference”
BackgroundMosedale, M., Kim, Y., Brock, W. J., Roth, S. E., Wiltshire, T., Eaddy, J. S., Keele, G. R., Corty, R. W., Xie, Y., Valdar, W. S. J., et al. (2016) · Toxicological Sciences · doi:10.1093/toxsci/kfw269 · Cited by 50
“Following Rockman and Kruglyak (2006), the terms local eQTL and distal eQTL were used.”
MethodIntegrative clustering methods of multi‐omics data for molecule‐based cancer classifications
Wang, D., & Gu, J. (2016) · Quantitative Biology · doi:10.1007/s40484-016-0063-4 · Cited by 81
“Then, these alterations or perturbations are integrative analyzed with gene expression variations (either cis- or trans-acting effects), the functional indications of genetic alterations [57–61].”
BackgroundEvolution of Gene Regulation during Transcription and Translation
Wang, Z., Sun, X., Zhao, Y., Guo, X., Jiang, H., Li, H., & Gu, Z. (2015) · Genome Biology and Evolution · doi:10.1093/gbe/evv059 · Cited by 56
“Cis and Trans Effects Involved in the Evolution of Transcription Regulation Changes in gene transcription can result from either cis or trans effect (Rockman and Kruglyak 2006).”
BackgroundInfluentialApproaches for establishing the function of regulatory genetic variants involved in disease
Knight, J. C. (2014) · Genome Medicine · doi:10.1186/s13073-014-0092-4 · Cited by 45
“Mapping gene expression as a quantitative trait is a powerful way to define the regions and markers associated with differential expression between individuals [53].”
BackgroundZhao, F., Yan, C., Wang, X., Yang, Y., Wang, G., Lee, W., Xiang, Y., & Zhang, Y. (2013) · DNA Research · doi:10.1093/dnares/dst035 · Cited by 64
“Therefore, understanding global dynamics of the transcriptome is essential for interpreting genome expanded information and unravelling phenotypic variation.(5)”
BackgroundUsing Canonical Correlation Analysis to Discover Genetic Regulatory Variants
Naylor, M., Lin, X., Weiss, S. T., Raby, B. A., & Lange, C. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010395 · Cited by 52
“As Rockman and Kruglyak stated, ‘‘The road from genotype to phenotype runs through gene expression’’ [1].”
BackgroundFarber, C. R., van Nas, A., Ghazalpour, A., Aten, J. E., Doss, S., Sos, B. C., Schadt, E. E., Ingram-Drake, L. A., Davis, R. C., Horvath, S., et al. (2008) · Journal of Bone and Mineral Research · doi:10.1359/jbmr.080908 · Cited by 56
“eQTLs are classified as either local or distant, and these terms describe the proximity of eQTL and gene.((11)) Local eQTLs are located near the transcript they regulate, whereas distant eQTLs are removed (typically on different chromosomes) from their structural locus.”
BackgroundDetection of eQTL modules mediated by activity levels of transcription factors
Sun, W., Yu, T., & Li, K.-C. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm327 · Cited by 42
“While many eQTL modules can be detected statistically, (Bing and Hoeschele, 2005; Kulp and Jagalur, 2006) the molecular mechanism of associating the DNA polymorphism in the eQTL hot spot to the cis - or trans-linked genes is still poorly understood (Rockman and Kruglyak, 2006).”
The impact of species-wide gene expression variation on Caenorhabditis elegans complex traits
Zhang, G., Roberto, N. M., Lee, D., Hahnel, S. R., & Andersen, E. C. (2022) · Nature Communications · doi:10.1038/s41467-022-31208-4 · Cited by 48
An empirical Bayes approach for multiple tissue eQTL analysis
Li, G., Shabalin, A. A., Rusyn, I., Wright, F. A., & Nobel, A. B. (2017) · Biostatistics · doi:10.1093/biostatistics/kxx048 · Cited by 52
“For an overview of eQTL analysis and disease mapping, see Cookson et al. (2009), Mackay et al. (2009), Rockman and Kruglyak (2006), and the references therein.”
MethodPorth, I. M., Hamberger, B., White, R., & Ritland, K. (2011) · BMC Genomics · doi:10.1186/1471-2164-12-608 · Cited by 46
“Gene expression variation represents the phenotype most directly related to DNA sequence polymorphism, such that in principle each transcript has a corresponding gene with known position in the genome [42].”
BackgroundGene Expression During Development of Fetal and Adult Leydig Cells
Dong, L., Jelinsky, S., Finger, J. N., Johnston, D. S., Kopf, G., Sottas, C., Hardy, M. P., & Ge, R. (2007) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1411.016 · Cited by 50
Using GWAS to identify novel therapeutic targets for osteoporosis
Sabik, O. L., & Farber, C. R. (2016) · Translational research · doi:10.1016/j.trsl.2016.10.009 · Cited by 55
Buffering of Genetic Regulatory Networks inDrosophila melanogaster
Fear, J. M., León‐Novelo, L., Morse, A. M., Gerken, A. R., Lehmann, K.-V., Tower, J., Nuzhdin, S. V., & McIntyre, L. M. (2016) · Genetics · doi:10.1534/genetics.116.188797 · Cited by 52
“While eQTL studies often refer to cis- and transeffects, eQTL cis-effects are local effects and trans-effects are distal effects (Rockman and Kruglyak 2006).”
BackgroundHypergraph factorization for multi-tissue gene expression imputation
Viñas, R., Joshi, C. K., Georgiev, D., Lin, P., Dumitrascu, B., Gamazon, E. R., & Lió, P. (2023) · Nature Machine Intelligence · doi:10.1038/s42256-023-00684-8 · Cited by 36
“However, eQTL datasets are characterized by small sample sizes, especially for difficult-to-acquire tissues and cell types, reducing the statistical power to detect eQTLs 27 .”
BackgroundThe evolution of posttranscriptional regulation
Schaefke, B., Sun, W., Li, Y., Fang, L., & Chen, W. (2018) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1485 · Cited by 59
Impact of Natural Genetic Variation on Gene Expression Dynamics
Ackermann, M., Sikora-Wohlfeld, W., & Beyer, A. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003514 · Cited by 42
“Such GO enrichment analysis is non trivial for genetic regions causing eQTL, because these regions typically contain multiple genes and it is usually unknown which of them is the true causal gene [53].”
BackgroundZou, D., Lou, J., Ke, J., Mei, S., Li, J., Gong, Y., Yang, Y., Zhu, Y., Tian, J., Chang, J., et al. (2018) · European Journal of Cancer · doi:10.1016/j.ejca.2018.01.065 · Cited by 51
Negative feedback confers mutational robustness in yeast transcription factor regulation
Denby, C. M., Im, J. H., Yu, R. C., Pesce, C. G., & Brem, R. B. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1116360109 · Cited by 51
Ruden, D. M., Chen, L., Possidente, D. R., Possidente, B. P., Rasouli, P., Wang, L., Lu, X., Garfinkel, M. D., Hirsch, H. V. B., & Page, G. P. (2009) · NeuroToxicology · doi:10.1016/j.neuro.2009.08.011 · Cited by 45
“…multi-dimensional strategy, ‘‘genetical genomics,’’ has recently been developed to identify master-modulatory loci that regulate the expression of dozens or hundreds of other genes (Broman, 2005; de Koning and Haley, 2005; Jansen and Nap, 2001; Li and Burmeister, 2005; Rockman and Kruglyak, 2006).”
BackgroundExtensive Additivity of Gene Expression Differentiates Subspecies of the House Mouse
Rottscheidt, R., & Harr, B. (2007) · Genetics · doi:10.1534/genetics.107.076190 · Cited by 41
“Expression quantitative trait locus (eQTL) mapping identifies the genetic basis of expression differences among organisms (Rockman and Kruglyak 2006).”
BackgroundGenetic variation in radiation-induced cell death
Smirnov, D. A., Brady, L., Halasa, K., Morley, M., Solomon, S., & Cheung, V. G. (2012) · Genome Research · doi:10.1101/gr.122044.111 · Cited by 46
“…(within 5 Mb) to the target genes, suggesting a cis-acting regulation; the remaining linkage peaks were far away from the genomic locations of the target genes, suggesting that they harbor regulators that act in trans to influence the expression of the target genes (Rockman and Kruglyak 2006).”
BackgroundExplaining the disease phenotype of intergenic SNP through predicted long range regulation
Chen, J., & Tian, W. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw519 · Cited by 52
“Recently, a number of studies have been conducted to identify expression quantitative trait loci (eQTL) or methylation quantitative trait loci (mQTL) at genome-scale (37).”
BackgroundLagarrigue, S., Martin, L., Hormozdiari, F., Roux, P., Pan, C., van Nas, A., Demeure, O., Cantor, R. M., Ghazalpour, A., Eskin, E., et al. (2013) · Genetics · doi:10.1534/genetics.113.153882 · Cited by 46
Wang, D., Sung, H., Wang, T., Huang, C.-J., Yang, P., Chang, T., Wang, Y.-C., Tseng, D.-L., Wu, J.-P., Lee, T.-C., et al. (2007) · Genome Research · doi:10.1101/gr.6328907 · Cited by 47
“In some special circumstances, local regulatory variation identified through linkage analysis actually confers trans-regulatory effects (Ronald et al. 2005; Rockman and Kruglyak 2006).”
BackgroundFunctional genomics data: privacy risk assessment and technological mitigation
Gürsoy, G., Li, T., Liu, S. X., Ni, E., Brannon, C. M., & Gerstein, M. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-021-00428-7 · Cited by 53
Identification of functional candidate genes for drought tolerance in rice
Fu, B., Xiong, J., Zhu, L.-H., Zhao, X., Xu, H., Gao, Y., Li, Y.-S., Xu, J.-L., & Li, Z.-K. (2007) · Zeitschrift für Induktive Abstammungs- und Vererbungslehre · doi:10.1007/s00438-007-0276-3 · Cited by 45
“The same result was reported as the ‘neighborhood eVect of gene clusters’ in A. thaliana (Rockman and Kruglyak, 2006).”
Privacy-preserving genotype imputation with fully homomorphic encryption
Gürsoy, G., Chielle, E., Brannon, C. M., Maniatakos, M., & Gerstein, M. (2020) · bioRxiv · doi:10.1101/2020.05.29.124412 · Cited by 44
“Such data collection has tremendous clinical value in terms of understanding and characterizing rare diseases and genotype-phenotype associations [2, 3].”
BackgroundPark, Y. H., Hodges, A., Risacher, S. L., Lin, K., Jang, J., Ahn, S., Kim, S., Lovestone, S., Simmons, A., Weiner, M. W., et al. (2019) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2019.12.001 · Cited by 53
“Genetic data were also used for gene-based association analysis and expression quantitative trait locus (eQTL) analysis (Rockman and Kruglyak, 2006).”
MethodIshikawa, A., Kusakabe, M., Yoshida, K., Ravinet, M., Makino, T., Toyoda, A., Fujiyama, A., & Kitano, J. (2017) · Evolution · doi:10.1111/evo.13175 · Cited by 49
“…studies conducted in laboratory organisms, showing that variation in gene expression in response to environmental stimuli is largely due to distant regulatory changes (Li et al. 2006; Rockman and Kruglyak 2006; Wittkopp et al. 2008; Tirosh et al. 2009; Lowry et al. 2013; Cubillos et al. 2014).”
BackgroundInfluentialGenetic architecture of quantitative traits and complex diseases
Fu, W., O’Connor, T. D., & Akey, J. M. (2013) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2013.10.008 · Cited by 40
“For example, numerous studies have been performed to elucidate the genetics of gene expression, where transcript abundance is treated as a quantitative trait and expression QTL (eQTLs) are mapped by linkage or association methods [11,12].”
BackgroundZhang, L., Yu, Y., Shi, T., Kou, M., Sun, J., Xu, T., Li, Q., Wu, S.-Y., Cao, Q.-H., Hou, W., et al. (2020) · Horticulture Research · doi:10.1038/s41438-020-0314-4 · Cited by 43
Enhancer-gene specificity in development and disease
Pachano, T., Haro, E., & Rada-Iglesias, Á. (2022) · Development · doi:10.1242/dev.186536 · Cited by 58
Wang, C., Li, A., Cong, R., Qi, H., Wang, W., Zhang, G., & Li, L. (2023) · Molecular Biology and Evolution · doi:10.1093/molbev/msad015 · Cited by 42
“populations to climate-driven decline or extinction (Rockman and Kruglyak 2006; Kelly 2019).”
BackgroundInfluentialZeng, W.-W., Wang, Y., & Jiang, R. (2018) · bioRxiv · doi:10.1101/341214 · Cited by 40
“, 2009), computational biologists have long been interested in how well gene expression can be inferred by using TFs and regulatory elements (Rockman and Kruglyak, 2006), for deciphering the mechanism of gene regulation.”
BackgroundShen, X., Bai, X., Xu, J., Zhou, M., Xu, H., Nie, Q., Lu, X., & Zhang, X. (2016) · Molecular Biology Reports · doi:10.1007/s11033-016-4033-8 · Cited by 39
“Changes in gene expression and gene regulation have been proposed to be associated with behavioral changes and other phenotypic changes [28, 29].”
BackgroundArchitecture of the outbred brown fat proteome defines regulators of metabolic physiology
Xiao, H., Bozi, L. H. M., Sun, Y., Riley, C. L., Philip, V. M., Chen, M., Li, J., Zhang, T., Mills, E. L., Emont, M. P., et al. (2022) · Cell · doi:10.1016/j.cell.2022.10.003 · Cited by 46
Updates on genetics in systemic sclerosis
Ota, Y., & Kuwana, M. (2021) · Inflammation and Regeneration · doi:10.1186/s41232-021-00167-6 · Cited by 44
“, transcription factor binding sites in expression quantitative trait locus (eQTL) [68].”
BackgroundMapping and functional characterization of structural variation in 1060 pig genomes
Yang, L., Yin, H. H., Bai, L., Yao, W., Tao, T., Zhao, Q., Gao, Y., Teng, J., Xu, Z., Lin, Q., et al. (2024) · Genome biology · doi:10.1186/s13059-024-03253-3 · Cited by 37
“While GWAS report significant SNP signals associated with phenotype traits, eQTLs, and sQTLs are genetic variants that modulate gene expression and splicing, respectively [54, 55].”
BackgroundUsova, E., Alieva, A. S., Yakovlev, A. N., Алиева, М. С., Prokhorikhin, A. A., Конради, А. О., Shlyakhto, E. V., Magni, P., Catapano, A. L., & Baragetti, A. (2021) · Biomolecules · doi:10.3390/biom11111597 · Cited by 52
“Additional “multi-omic” studies for CAD, integrated these findings with data from global available tissue transcriptomic, harnessing the analysis of eQTL (genomic loci that explain variation in expression levels of the messenger RNA (mRNA) [28]).”
BackgroundPolonikov, A., Rymarova, L., Klyosova, E., Volkova, A., Azarova, I., Bushueva, O., Bykanova, M., Bocharova, I., Zhabin, S., Churnosov, M., et al. (2019) · Journal of Cellular Biochemistry · doi:10.1002/jcb.28815 · Cited by 38
“e genomic loci explaining all or a fraction of variation in expression levels of mRNAs.(30) For instance, meaningful eQTLs were found for SNP rs11225395 in whole blood (P=4.”
BackgroundQuantitative measurement of allele‐specific protein expression in a diploid yeast hybrid by LC‐MS
Khan, Z., Bloom, J. S., Amini, S., Singh, M., Perlman, D. H., Caudy, A. A., & Kruglyak, L. (2012) · Molecular Systems Biology · doi:10.1038/msb.2012.34 · Cited by 37
Self-citationDissecting the Genetics of Osteoporosis using Systems Approaches
Al-Barghouthi, B. M., & Farber, C. R. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.10.004 · Cited by 47
“There are two types of eQTL, local and distant [34].”
BackgroundThe Effect of Genetic and Environmental Variation on Metabolic Gene Expression
Scott, C. P., Williams, D. A., & Crawford, D. (2009) · Molecular Ecology · doi:10.1111/j.1365-294x.2009.04235.x · Cited by 37
“…measured by microarrays appears to be genetically based: it differs between inbred lines, is associated with quantitative trait loci and has narrow sense heritability (h2) greater than 30% (Cheung et al. 2003; Gibson & Weir 2005; Sharma et al. 2005; Tan et al. 2005; Rockman & Kruglyak 2006).”
Background
Metadata
- Authors
- Rockman, M. V., & Kruglyak, L.
- Affiliations
- Princeton University (US)
- Corresponding author
- Kruglyak, Leonid
- Venue
- Nature Reviews Genetics
- Published
- 2006-11
- Volume
- 7
- Issue
- 11
- Pages
- 862-872
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- OpenAlex
- W2040912377
- Cited by
- 666
- References
- 0
- Citations by year
- 2026: 9 · 2025: 18 · 2024: 18 · 2023: 19 · 2022: 24 · 2021: 50 · 2020: 27 · 2019: 35 · 2018: 26 · 2017: 29 · 2016: 36 · 2015: 33 · 2014: 41 · 2013: 39 · 2012: 41
- FWCI
- 4.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Genetics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- James S. McDonnell Foundation
- Jane Coffin Childs Memorial Fund for Medical Research
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- global gene expression, mRNA levels, quantitative traits, transcriptional regulation, regulatory variation, DNA sequence variation, phenotypic variability, gene expression microarrays, linkage analysis, association analysis
- MeSH terms
- Amino Acid Sequence, Animals, Fungal Proteins, Genetic Techniques, Humans, Molecular Sequence Data, Transcription, Genetic, Genetic Variation, Yeasts, Gene Expression, Sequence Homology, Amino Acid, Quantitative Trait Loci
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