scholarly journals Expression quantitative trait loci for ETV4 and MEOX1 are associated with adult asthma in Japanese populations

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yohei Yatagai ◽  
Hisayuki Oshima ◽  
Tohru Sakamoto ◽  
Rie Shigemasa ◽  
Haruna Kitazawa ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Epithelial Cell Line ◽  
Expression Quantitative Trait Loci ◽  
Adult Asthma ◽  
Asthma Risk ◽  
Trait Loci

AbstractETS variant transcription factor 4 (ETV4) is a recently identified transcription factor that regulates gene expression-based biomarkers of asthma and IL6 production in an airway epithelial cell line. Given that ETV4 has not yet been implicated in asthma genetics, we performed genetic association studies of adult asthma in the ETV4 region using two independent Japanese cohorts (a total of 1532 controls and 783 cases). SNPs located between ETV4 and mesenchyme homeobox 1 (MEOX1) were significantly associated with adult asthma, including rs4792901 and rs2880540 (P = 5.63E−5 and 2.77E−5, respectively). The CC haplotype of these two SNPs was also significantly associated with adult asthma (P = 8.43E−7). Even when both SNPs were included in a logistic regression model, the association of either rs4792901 or rs2880540 remained significant (P = 0.013 or 0.007, respectively), suggesting that the two SNPs may have independent effects on the development of asthma. Both SNPs were expression quantitative trait loci, and the asthma risk alleles at both SNPs were correlated with increased levels of ETV4 mRNA expression. In addition, the asthma risk allele at rs4792901 was associated with increased serum IL6 levels (P = 0.041) in 651 healthy adults. Our findings imply that ETV4 is involved in the pathogenesis of asthma, possibly through the heightened production of IL6.

Quantitative trait loci identification by estimating the genetic model based on the extremal samples

2021 ◽  
Vol 22 ◽  
Author(s):  
Zining Yang ◽  
Yaning Yang ◽  
Xu Steven Xu ◽  
Min Yuan
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genetic Model ◽  
Association Studies ◽  
Genetic Association Studies ◽  
T Test ◽  
Model Specification ◽  
F Test ◽  
Quantitative Trait Analysis ◽  
Trait Loci

Background: In genetic association studies with quantitative trait loci (QTL), the association between a candidate genetic marker and the trait of interest is commonly examined by the omnibus F test or by the t-test corresponding to a given genetic model or mode of inheritance. It is known that the t-test with a correct model specification is more powerful than the F test. However, since the underlying genetic model is rarely known in practice, the use of a model-specific t-test may incur substantial power loss. Robust-efficient tests, such as the Maximin Efficiency Robust Test (MERT) and MAX3 have been proposed in the literature. Methods: In this paper, we propose a novel two-step robust-efficient approach, namely, the genetic model selection (GMS) method for quantitative trait analysis. GMS selects a genetic model by testing Hardy-Weinberg disequilibrium (HWD) with extremal samples of the population in the first step and then applies the corresponding genetic model-specific t-test in the second step. Results: Simulations show that GMS is not only more efficient than MERT and MAX3, but also has comparable power to the optimal t-test when the genetic model is known. Conclusion: Application to the data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort demonstrate that the proposed approach can identify meaningful biological SNPs on chromosome 19.

scholarly journals Expression quantitative trait loci: present and future

2013 ◽  
Vol 368 (1620) ◽  
pp. 20120362 ◽  
Author(s):  
Alexandra C. Nica ◽  
Emmanouil T. Dermitzakis
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Sequence Variation ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Expression Quantitative Trait Loci ◽  
Genome Wide ◽  
Trait Loci ◽  
Gene Expression Levels

The last few years have seen the development of large efforts for the analysis of genome function, especially in the context of genome variation. One of the most prominent directions has been the extensive set of studies on expression quantitative trait loci (eQTLs), namely, the discovery of genetic variants that explain variation in gene expression levels. Such studies have offered promise not just for the characterization of functional sequence variation but also for the understanding of basic processes of gene regulation and interpretation of genome-wide association studies. In this review, we discuss some of the key directions of eQTL research and its implications.

A functional strategy to characterize expression Quantitative Trait Loci

2017 ◽  
Vol 136 (11-12) ◽  
pp. 1477-1487 ◽  
Author(s):  
Elena Grassi ◽  
Elisa Mariella ◽  
Mattia Forneris ◽  
Federico Marotta ◽  
Marika Catapano ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Expression Quantitative Trait Loci ◽  
Functional Strategy ◽  
Trait Loci

scholarly journals Delineamento de experimentos em genética genômica

2007 ◽  
Vol 36 (suppl) ◽  
pp. 211-218 ◽  
Author(s):  
Guilherme Jordão de Magalhães Rosa
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Expression Quantitative Trait Loci ◽  
Trait Loci

Genética genômica é um termo utilizado para representar o estudo de processos genéticos controladores de caracteres fenotípicos de herança complexa, a partir da análise conjunta de informação relativa a fenótipos, estruturas de parentesco, marcadores moleculares e expressão gênica. Estudos de genética genômica são utilizados, por exemplo, para a estimação da herdabilidade de níveis de transcrição, para o mapeamento de locos controladores da expressao gênica (eQTL, do inglês expression Quantitative Trait Loci), e para o estudo de redes regulatórias. Genética genômica geralmente envolve experimentos com microarrays, os quais são ainda bastante caros e trabalhosos, limitando o tamanho amostral e conseqüentemente o poder estatístico de tais estudos. Desta maneira, é essencial que tais experimentos sejam otimizados do ponto de vista do delineamento, a partir de criteriosa escolha das amostras (indivíduos) a serem utilizadas, e do controle rigoroso dos vários fatores que podem afetar as variáveis-resposta de interesse. Outro ponto fundamental na condução de tais experimentos refere-se à marcação das amostras de mRNA com os fluoróforos e ao pareamento das mesmas em cada lâmina de microarray, os quais devem ser cuidadosamente planejados para que não haja confundimento entre estes efeitos e os fatores biológicos de interesse. Nesta apresentação serão discutidas algumas estratégias para o planejamento de estudos de genética genômica, incluindo a seleção de indivíduos objetivando-se a maximização da dissimilaridade genética ou do número de eventos de recombinação, bem como a condução eficiente dos ensaios com microarrays para diferentes objetivos experimentais.

scholarly journals Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice

2012 ◽  
Vol 2 (2) ◽  
pp. 213-221 ◽  
Author(s):  
Daniel Bottomly ◽  
Martin T. Ferris ◽  
Lauri D. Aicher ◽  
Elizabeth Rosenzweig ◽  
Alan Whitmore ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Host Response ◽  
Influenza A ◽  
Collaborative Cross ◽  
Expression Quantitative Trait Loci ◽  
Trait Loci
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