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https://www.readbyqxmd.com/read/27933535/systems-genetics-analysis-to-identify-the-genetic-modulation-of-a-glaucoma-associated-gene
#1
Sumana R Chintalapudi, Monica M Jablonski
Loss of retinal ganglion cells (RGCs) is one of the hallmarks of retinal neurodegenerative diseases, glaucoma being one of the most common. Recently, γ-synuclein (SNCG) was shown to be highly expressed in the somas and axons of RGCs. In various mouse models of glaucoma, downregulation of Sncg gene expression correlates with RGC loss. To investigate the regulation of Sncg in RGCs, we used a systems genetics approach to identify a gene that modulates the expression of Sncg, followed by confirmatory studies in both healthy and diseased retinas...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/27933530/visualization-of-results-from-systems-genetics-studies-in-chromosomal-context
#2
Karen Y Oróstica, Ricardo A Verdugo
This chapter describes methods currently available for visualizing results from systems genetics experiments. Here, we abstract from the statistical methods used for genetic mapping, which are dependent on the specific resource being used, i.e. F2, RILs, or outbred populations among others. We use a public dataset with results from a mouse eQTL experiment for three examples of visualization: genome-wide dot plots of marker-by-gene association, karyotype-like plots, and circos plots. Dot plots give a first overview of the results from eQTL mapping, allowing detecting genome-wide patterns of cis- and trans-genetic association to transcription level...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/27933526/epigenetics-and-control-of-rnas
#3
Henrike Maatz, Sebastiaan van Heesch, Franziska Kreuchwig, Allison Faber, Eleonora Adami, Norbert Hubner, Matthias Heinig
Histone modifications are epigenetic marks that fundamentally impact the regulation of gene expression. Integrating histone modification information in the analysis of gene expression traits (eQTL mapping) has been shown to significantly enhance the prediction of eQTLs. In this chapter, we describe (1) how to perform quantitative trait locus (QTL) analysis using histone modification levels as traits and (2) how to integrate these data with information on RNA expression for the elucidation of the epigenetic control of transcript levels...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/27933525/expression-qtls-mapping-and-analysis-a-bayesian-perspective
#4
Martha Imprialou, Enrico Petretto, Leonardo Bottolo
The aim of expression Quantitative Trait Locus (eQTL) mapping is the identification of DNA sequence variants that explain variation in gene expression. Given the recent yield of trait-associated genetic variants identified by large-scale genome-wide association analyses (GWAS), eQTL mapping has become a useful tool to understand the functional context where these variants operate and eventually narrow down functional gene targets for disease. Despite its extensive application to complex (polygenic) traits and disease, the majority of eQTL studies still rely on univariate data modeling strategies, i...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/27926527/meqtl-analysis-of-childhood-obesity-links-epigenetics-with-a-risk-snp-rs17782313-near-mc4r-from-meta-analysis
#5
Yuping Tang, Bo Jin, Lingling Zhou, Weifeng Lu
Earlier GWAS has identified that rs17782313 near MC4R was associated with obesity. However, subsequent studies showed conflicting results, especially among childhood. Besides, the mechanisms underlying the association between rs17782313 and childhood obesity remain largely unexplored, and genetic and epigenetic may interact and together affect the development of childhood obesity. We conducted a comprehensive meta-analysis to assess the association between rs17782313 and childhood obesity. MeQTL and eQTL analysis was applied to explore the effect of rs17782313 on DNA methylation and MC4R expression...
December 1, 2016: Oncotarget
https://www.readbyqxmd.com/read/27918535/disease-variants-alter-transcription-factor-levels-and-methylation-of-their-binding-sites
#6
Marc Jan Bonder, René Luijk, Daria V Zhernakova, Matthijs Moed, Patrick Deelen, Martijn Vermaat, Maarten van Iterson, Freerk van Dijk, Michiel van Galen, Jan Bot, Roderick C Slieker, P Mila Jhamai, Michael Verbiest, H Eka D Suchiman, Marijn Verkerk, Ruud van der Breggen, Jeroen van Rooij, Nico Lakenberg, Wibowo Arindrarto, Szymon M Kielbasa, Iris Jonkers, Peter van 't Hof, Irene Nooren, Marian Beekman, Joris Deelen, Diana van Heemst, Alexandra Zhernakova, Ettje F Tigchelaar, Morris A Swertz, Albert Hofman, André G Uitterlinden, René Pool, Jenny van Dongen, Jouke J Hottenga, Coen D A Stehouwer, Carla J H van der Kallen, Casper G Schalkwijk, Leonard H van den Berg, Erik W van Zwet, Hailiang Mei, Yang Li, Mathieu Lemire, Thomas J Hudson, P Eline Slagboom, Cisca Wijmenga, Jan H Veldink, Marleen M J van Greevenbroek, Cornelia M van Duijn, Dorret I Boomsma, Aaron Isaacs, Rick Jansen, Joyce B J van Meurs, Peter A C 't Hoen, Lude Franke, Bastiaan T Heijmans
Most disease-associated genetic variants are noncoding, making it challenging to design experiments to understand their functional consequences. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer the downstream effects of disease-associated variants, but most of these variants remain unexplained. The analysis of DNA methylation, a key component of the epigenome, offers highly complementary data on the regulatory potential of genomic regions. Here we show that disease-associated variants have widespread effects on DNA methylation in trans that likely reflect differential occupancy of trans binding sites by cis-regulated transcription factors...
December 5, 2016: Nature Genetics
https://www.readbyqxmd.com/read/27918533/identification-of-context-dependent-expression-quantitative-trait-loci-in-whole-blood
#7
Daria V Zhernakova, Patrick Deelen, Martijn Vermaat, Maarten van Iterson, Michiel van Galen, Wibowo Arindrarto, Peter van 't Hof, Hailiang Mei, Freerk van Dijk, Harm-Jan Westra, Marc Jan Bonder, Jeroen van Rooij, Marijn Verkerk, P Mila Jhamai, Matthijs Moed, Szymon M Kielbasa, Jan Bot, Irene Nooren, René Pool, Jenny van Dongen, Jouke J Hottenga, Coen D A Stehouwer, Carla J H van der Kallen, Casper G Schalkwijk, Alexandra Zhernakova, Yang Li, Ettje F Tigchelaar, Niek de Klein, Marian Beekman, Joris Deelen, Diana van Heemst, Leonard H van den Berg, Albert Hofman, André G Uitterlinden, Marleen M J van Greevenbroek, Jan H Veldink, Dorret I Boomsma, Cornelia M van Duijn, Cisca Wijmenga, P Eline Slagboom, Morris A Swertz, Aaron Isaacs, Joyce B J van Meurs, Rick Jansen, Bastiaan T Heijmans, Peter A C 't Hoen, Lude Franke
Genetic risk factors often localize to noncoding regions of the genome with unknown effects on disease etiology. Expression quantitative trait loci (eQTLs) help to explain the regulatory mechanisms underlying these genetic associations. Knowledge of the context that determines the nature and strength of eQTLs may help identify cell types relevant to pathophysiology and the regulatory networks underlying disease. Here we generated peripheral blood RNA-seq data from 2,116 unrelated individuals and systematically identified context-dependent eQTLs using a hypothesis-free strategy that does not require previous knowledge of the identity of the modifiers...
December 5, 2016: Nature Genetics
https://www.readbyqxmd.com/read/27907186/inter-tissue-gene-co-expression-networks-between-metabolically-healthy-and-unhealthy-obese-individuals
#8
Lisette J A Kogelman, Jingyuan Fu, Lude Franke, Jan Willem Greve, Marten Hofker, Sander S Rensen, Haja N Kadarmideen
BACKGROUND: Obesity is associated with severe co-morbidities such as type 2 diabetes and nonalcoholic steatohepatitis. However, studies have shown that 10-25 percent of the severely obese individuals are metabolically healthy. To date, the identification of genetic factors underlying the metabolically healthy obese (MHO) state is limited. Systems genetics approaches have led to the identification of genes and pathways in complex diseases. Here, we have used such approaches across tissues to detect genes and pathways involved in obesity-induced disease development...
2016: PloS One
https://www.readbyqxmd.com/read/27906459/integrative-genomic-analysis-identifies-ancestry-related-expression-quantitative-trait-loci-on-dna-polymerase-%C3%AE-and-supports-the-association-of-genetic-ancestry-with-survival-disparities-in-head-and-neck-squamous-cell-carcinoma
#9
Meganathan P Ramakodi, Karthik Devarajan, Elizabeth Blackman, Denise Gibbs, Danièle Luce, Jacqueline Deloumeaux, Suzy Duflo, Jeffrey C Liu, Ranee Mehra, Rob J Kulathinal, Camille C Ragin
BACKGROUND: African Americans with head and neck squamous cell carcinoma (HNSCC) have a lower survival rate than whites. This study investigated the functional importance of ancestry-informative single-nucleotide polymorphisms (SNPs) in HNSCC and also examined the effect of functionally important genetic elements on racial disparities in HNSCC survival. METHODS: Ancestry-informative SNPs, RNA sequencing, methylation, and copy number variation data for 316 oral cavity and laryngeal cancer patients were analyzed across 178 DNA repair genes...
December 1, 2016: Cancer
https://www.readbyqxmd.com/read/27903611/the-genomic-architecture-of-interactions-between-natural-genetic-polymorphisms-and-environments-in-yeast-growth
#10
Xinzhu Wei, Jianzhi Zhang
Gene-environment interaction (G×E) refers to the phenomenon that the same mutation has different phenotypic effects in different environments. Although quantitative trait loci (QTLs) exhibiting G×E have been reported, little is known about the general properties of G×E and those of its underlying QTLs. Here we use the genotypes of 1005 segregants from a cross between two Saccharomyces cerevisiae strains and the growth rates of these segregants in 47 environments to identify growth rate QTLs (gQTLs) in each environment and QTLs that have different growth effects in each pair of environments (g×eQTLs)...
November 30, 2016: Genetics
https://www.readbyqxmd.com/read/27902686/genomic-characterization-of-metformin-hepatic-response
#11
Marcelo R Luizon, Walter L Eckalbar, Yao Wang, Stacy L Jones, Robin P Smith, Megan Laurance, Lawrence Lin, Paul J Gallins, Amy S Etheridge, Fred Wright, Yihui Zhou, Cliona Molony, Federico Innocenti, Sook Wah Yee, Kathleen M Giacomini, Nadav Ahituv
Metformin is used as a first-line therapy for type 2 diabetes (T2D) and prescribed for numerous other diseases. However, its mechanism of action in the liver has yet to be characterized in a systematic manner. To comprehensively identify genes and regulatory elements associated with metformin treatment, we carried out RNA-seq and ChIP-seq (H3K27ac, H3K27me3) on primary human hepatocytes from the same donor treated with vehicle control, metformin or metformin and compound C, an AMP-activated protein kinase (AMPK) inhibitor (allowing to identify AMPK-independent pathways)...
November 2016: PLoS Genetics
https://www.readbyqxmd.com/read/27901618/genome-wide-interaction-analysis-of-air-pollution-exposure-and-childhood-asthma-with-functional-follow-up
#12
Anna Gref, Simon Kebede Merid, Olena Gruzieva, Stéphane Ballereau, Allan Becker, Tom Bellander, Anna Bergström, Yohan Bossé, Matteo Bottai, Moira Chan-Yeung, Elaine Fuertes, Despo Ierodiakonou, Ruiwei Jiang, Stéphane Joly, Meaghan Jones, Michael S Kobor, Michal Korek, Anita L Kozyrskyj, Ashish Kumar, Nathanaël Lemonnier, Elaina MacIntyre, Camille Ménard, David Nickle, Ma'en Obeidat, Johann Pellet, Marie Standl, Annika Sääf, Cilla Söderhäll, Carla Mt Tiesler, Maarten van den Berge, Judith M Vonk, Hita Vora, Cheng-Jian Xu, Josep M Antó, Charles Auffray, Michael Brauer, Jean Bousquet, Bert Brunekreef, W James Gauderman, Joachim Heinrich, Juha Kere, Gerard H Koppelman, Dirkje Postma, Christopher Carlsten, Göran Pershagen, Erik Melén
RATIONALE: The evidence supporting an association between traffic-related air pollution exposure and incident childhood asthma is inconsistent, and may depend on genetic factors. OBJECTIVES: To identify gene-environment interaction effects on childhood asthma using genome-wide single nucleotide polymorphism (SNP) data and air pollution exposure. Identified loci were further analyzed at epigenetic and transcriptomic levels. METHODS: We used land use regression models to estimate individual air pollution exposure (represented by outdoor NO2 levels) at the birth address and performed a genome-wide interaction study for doctor's diagnosis of asthma up to 8 years in three European birth cohorts (n=1,534) with look-up for interaction in two separate North American cohorts, CHS and CAPPS/SAGE (n=1,602 and 186 subjects, respectively)...
November 30, 2016: American Journal of Respiratory and Critical Care Medicine
https://www.readbyqxmd.com/read/27899575/ensembl-2017
#13
Bronwen L Aken, Premanand Achuthan, Wasiu Akanni, M Ridwan Amode, Friederike Bernsdorff, Jyothish Bhai, Konstantinos Billis, Denise Carvalho-Silva, Carla Cummins, Peter Clapham, Laurent Gil, Carlos García Girón, Leo Gordon, Thibaut Hourlier, Sarah E Hunt, Sophie H Janacek, Thomas Juettemann, Stephen Keenan, Matthew R Laird, Ilias Lavidas, Thomas Maurel, William McLaren, Benjamin Moore, Daniel N Murphy, Rishi Nag, Victoria Newman, Michael Nuhn, Chuang Kee Ong, Anne Parker, Mateus Patricio, Harpreet Singh Riat, Daniel Sheppard, Helen Sparrow, Kieron Taylor, Anja Thormann, Alessandro Vullo, Brandon Walts, Steven P Wilder, Amonida Zadissa, Myrto Kostadima, Fergal J Martin, Matthieu Muffato, Emily Perry, Magali Ruffier, Daniel M Staines, Stephen J Trevanion, Fiona Cunningham, Andrew Yates, Daniel R Zerbino, Paul Flicek
Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access methods ensure uniform data analysis and distribution for all supported species...
November 28, 2016: Nucleic Acids Research
https://www.readbyqxmd.com/read/27881992/molecular-mapping-and-qtl-for-expression-profiles-of-flavonoid-genes-in-brassica-napus
#14
Cunmin Qu, Huiyan Zhao, Fuyou Fu, Kai Zhang, Jianglian Yuan, Liezhao Liu, Rui Wang, Xinfu Xu, Kun Lu, Jia-Na Li
Flavonoids are secondary metabolites that are extensively distributed in the plant kingdom and contribute to seed coat color formation in rapeseed. To decipher the genetic networks underlying flavonoid biosynthesis in rapeseed, we constructed a high-density genetic linkage map with 1089 polymorphic loci (including 464 SSR loci, 97 RAPD loci, 451 SRAP loci, and 75 IBP loci) using recombinant inbred lines (RILs). The map consists of 19 linkage groups and covers 2775 cM of the B. napus genome with an average distance of 2...
2016: Frontiers in Plant Science
https://www.readbyqxmd.com/read/27881906/genetic-and-immunohistochemical-analysis-of-hspa5-in-mouse-and-human-retinas
#15
Sumana R Chintalapudi, XiaoFei Wang, Huiling Li, Yin H Chan Lau, Robert W Williams, Monica M Jablonski
PURPOSE: Photoreceptor degenerative diseases are among the leading causes of vision loss. Although the causative genetic mutations are often known, mechanisms leading to photoreceptor degeneration remain poorly defined. We have previously demonstrated that the photoreceptor membrane-associated protein XAP-1 antigen is a product of the HSPA5 gene. In this study, we used systems genetic methods, statistical modeling, and immunostaining to identify and analyze candidate genes that modulate Hspa5 expression in the retina...
2016: Molecular Vision
https://www.readbyqxmd.com/read/27881077/sex-difference-in-egfr-pathways-in-mouse-kidney-potential-impact-on-the-immune-system
#16
Fengxia Liu, Yan Jiao, Yun Jiao, Franklin Garcia-Godoy, Weikuan Gu, Qingyi Liu
BACKGROUND: Epidermal growth factor receptor (Egfr) has been the target of several drugs for cancers. The potential gender differences in genes in the Egfr axis have been suggested in humans and in animal models. Female and male mice from the same recombinant inbred (RI) strain have the same genomic components except the sex difference. A population of different RI mouse strains allows to conduct precise analysis of molecular pathways and regulation of Egfr between female and male mice...
November 24, 2016: BMC Genetics
https://www.readbyqxmd.com/read/27866706/colocalization-of-gwas-and-eqtl-signals-detects-target-genes
#17
Farhad Hormozdiari, Martijn van de Bunt, Ayellet V Segrè, Xiao Li, Jong Wha J Joo, Michael Bilow, Jae Hoon Sul, Sriram Sankararaman, Bogdan Pasaniuc, Eleazar Eskin
The vast majority of genome-wide association study (GWAS) risk loci fall in non-coding regions of the genome. One possible hypothesis is that these GWAS risk loci alter the individual's disease risk through their effect on gene expression in different tissues. In order to understand the mechanisms driving a GWAS risk locus, it is helpful to determine which gene is affected in specific tissue types. For example, the relevant gene and tissue could play a role in the disease mechanism if the same variant responsible for a GWAS locus also affects gene expression...
December 1, 2016: American Journal of Human Genetics
https://www.readbyqxmd.com/read/27862526/systems-genetics-reveals-a-transcriptional-network-associated-with-susceptibility-in-the-maize-gray-leaf-spot-pathosystem
#18
Nanette Christie, Alexander A Myburg, Fourie Joubert, Shane L Murray, Maryke Carstens, Yao-Cheng Lin, Jacqueline Meyer, Bridget G Crampton, Shawn A Christensen, Jean F Ntuli, Sara S Wighard, Yves Van de Peer, Dave K Berger
We used a systems genetics approach to elucidate molecular mechanisms of maize responses to gray leaf spot (GLS) disease, caused by Cercospora zeina, a threat to maize production globally. Expression analysis of earleaf samples in a sub-tropical maize RIL population (CML444 X SC Malawi) subjected in field to C. zeina infection allowed detection of 20,206 expression QTLs (eQTL). Four trans-eQTL hotspots coincided with GLS disease QTLs mapped in the same field experiment. Co-expression network analysis identified three expression modules correlated with GLS disease scores...
November 12, 2016: Plant Journal: for Cell and Molecular Biology
https://www.readbyqxmd.com/read/27861356/a-childhood-acute-lymphoblastic-leukemia-genome-wide-association-study-identifies-novel-sex-specific-risk-variants
#19
Sandeep K Singh, Philip J Lupo, Michael E Scheurer, Anshul Saxena, Amy E Kennedy, Boubakari Ibrahimou, Manuel Alejandro Barbieri, Ken I Mills, Jacob L McCauley, Mehmet Fatih Okcu, Mehmet Tevfik Dorak
Childhood acute lymphoblastic leukemia (ALL) occurs more frequently in males. Reasons behind sex differences in childhood ALL risk are unknown. In the present genome-wide association study (GWAS), we explored the genetic basis of sex differences by comparing genotype frequencies between male and female cases in a case-only study to assess effect-modification by sex.The case-only design included 236 incident cases of childhood ALL consecutively recruited at the Texas Children's Cancer Center in Houston, Texas from 2007 to 2012...
November 2016: Medicine (Baltimore)
https://www.readbyqxmd.com/read/27836907/regulatory-architecture-of-gene-expression-variation-in-the-threespine-stickleback-gasterosteus-aculeatus
#20
Victoria L Pritchard, Heidi M Viitaniemi, R J Scott McCairns, Juha Merilä, Mikko Nikinmaa, Craig R Primmer, Erica H Leder
Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus), an important model in the study of adaptive evolution...
November 11, 2016: G3: Genes—Genomes—Genetics
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