Single nucleotide polymorphisms affect both cis- and trans-eQTLs

Chen, Lang; Page, Grier P.; Mehta, Tapan; Feng, Rui; Cui, Xiangqin

doi:10.1016/j.ygeno.2009.01.011

Cited by 24 publications

(24 citation statements)

References 32 publications

(36 reference statements)

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“…We discovered 7,316 SNP-CpG pairs on 866 aDMSs with significant cis -dMeQTLs in the older comparison set (FDR < 0.05), and 3,534 SNP-CpG pairs (48.3%) were replicated in the younger comparison set (same direction of effects and nominal P < 0.05). 113 potentially false-positive dMeQTLs were removed due to SNP-under-the-probe effects [20]. The remaining 3,421 (46.8%) SNP-CpG pairs are listed in Additional file 5, consisting of 2734 SNPs regulating 101 a-DMSs (60 da-DMSs and 41 ia-DMSs) that changed with age and showed methylation change was partly under genetic control.…”

Section: Resultsmentioning

confidence: 99%

The emerging landscape of dynamic DNA methylation in early childhood

Bonder

Söderhäll

et al. 2017

BMC Genomics

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BackgroundDNA methylation has been found to associate with disease, aging and environmental exposure, but it is unknown how genome, environment and disease influence DNA methylation dynamics in childhood.ResultsBy analysing 538 paired DNA blood samples from children at birth and at 4–5 years old and 726 paired samples from children at 4 and 8 years old from four European birth cohorts using the Illumina Infinium Human Methylation 450 k chip, we have identified 14,150 consistent age-differential methylation sites (a-DMSs) at epigenome-wide significance of p < 1.14 × 10−7. Genes with an increase in age-differential methylation were enriched in pathways related to ‘development’, and were more often located in bivalent transcription start site (TSS) regions, which can silence or activate expression of developmental genes. Genes with a decrease in age-differential methylation were involved in cell signalling, and enriched on H3K27ac, which can predict developmental state. Maternal smoking tended to decrease methylation levels at the identified da-DMSs. We also found 101 a-DMSs (0.71%) that were regulated by genetic variants using cis-differential Methylation Quantitative Trait Locus (cis-dMeQTL) mapping. Moreover, a-DMS-associated genes during early development were significantly more likely to be linked with disease.ConclusionOur study provides new insights into the dynamic epigenetic landscape of the first 8 years of life.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3452-1) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

The emerging landscape of dynamic DNA methylation in early childhood

Bonder

Söderhäll

et al. 2017

BMC Genomics

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“…As has been established for several years, SNP position and the number of SNPs overlapping the microarray probes have a significant impact on the discovery rate and the size of apparent expression differences for cis- (Schadt et al 2003;Alberts et al, 2005Alberts et al, , 2007Doss et al 2005;Chen et al 2009) and trans-modulated transcripts (Chen et al 2009). Our analysis found that the longer Illumina 50-mers have approximately the same sensitivity to sequence differences as the shorter Affymetrix 25-mer probes ( Figure S1 and Figure S2).…”

Section: Resultsmentioning

confidence: 99%

“…While this study is by no means the first to point out the potential difficulty of sorting out sources of variation in array hybridization (Schadt et al 2003;Alberts et al 2005Alberts et al , 2007Alberts et al , 2008Doss et al 2005;Chen et al 2009), we have extended previous work in three ways. First, we provide a comparatively quantitative assessment of the severity of the problem for two of the preeminent array platforms (Affymetrix and Illumina) by exploiting several large expression data sets and allele-specific expression protocols.…”

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confidence: 95%

Detection, Validation, and Downstream Analysis of Allelic Variation in Gene Expression

Ciobanu

Mozhui

et al. 2010

Genetics

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Common sequence variants within a gene often generate important differences in expression of corresponding mRNAs. This high level of local (allelic) control-or cis modulation-rivals that produced by gene targeting, but expression is titrated finely over a range of levels. We are interested in exploiting this allelic variation to study gene function and downstream consequences of differences in expression dosage. We have used several bioinformatics and molecular approaches to estimate error rates in the discovery of cis modulation and to analyze some of the biological and technical confounds that contribute to the variation in gene expression profiling. Our analysis of SNPs and alternative transcripts, combined with eQTL maps and selective gene resequencing, revealed that between 17 and 25% of apparent cis modulation is caused by SNPs that overlap probes rather than by genuine quantitative differences in mRNA levels. This estimate climbs to 40-50% when qualitative differences between isoform variants are included. We have developed an analytical approach to filter differences in expression and improve the yield of genuine cis-modulated transcripts to $80%. This improvement is important because the resulting variation can be successfully used to study downstream consequences of altered expression on higherorder phenotypes. Using a systems genetics approach we show that two validated cis-modulated genes, Stk25 and Rasd2, are likely to control expression of downstream targets and affect disease susceptibility.

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“…Recent studies have demonstrated that probe sequences including SNPs would influence the hybridization on microarrays and cause false cis eQTL [30]. The rationale for this effect is that the mRNA with an identical sequence as the probe designed would hybridize better.…”

Section: Methodsmentioning

confidence: 99%

Modeling expression quantitative trait loci in data combining ethnic populations

Hsiao¹,

Lian

Hsieh³

et al. 2010

BMC Bioinformatics

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BackgroundCombining data from different ethnic populations in a study can increase efficacy of methods designed to identify expression quantitative trait loci (eQTL) compared to analyzing each population independently. In such studies, however, the genetic diversity of minor allele frequencies among populations has rarely been taken into account. Due to the fact that allele frequency diversity and population-level expression differences are present in populations, a consensus regarding the optimal statistical approach for analysis of eQTL in data combining different populations remains inconclusive.ResultsIn this report, we explored the applicability of a constrained two-way model to identify eQTL for combined ethnic data that might contain genetic diversity among ethnic populations. In addition, gene expression differences resulted from ethnic allele frequency diversity between populations were directly estimated and analyzed by the constrained two-way model. Through simulation, we investigated effects of genetic diversity on eQTL identification by examining gene expression data pooled from normal quantile transformation of each population. Using the constrained two-way model to reanalyze data from Caucasians and Asian individuals available from HapMap, a large number of eQTL were identified with similar genetic effects on the gene expression levels in these two populations. Furthermore, 19 single nucleotide polymorphisms with inter-population differences with respect to both genotype frequency and gene expression levels directed by genotypes were identified and reflected a clear distinction between Caucasians and Asian individuals.ConclusionsThis study illustrates the influence of minor allele frequencies on common eQTL identification using either separate or combined population data. Our findings are important for future eQTL studies in which different datasets are combined to increase the power of eQTL identification.

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Single nucleotide polymorphisms affect both cis- and trans-eQTLs

Cited by 24 publications

References 32 publications

The emerging landscape of dynamic DNA methylation in early childhood

The emerging landscape of dynamic DNA methylation in early childhood

Detection, Validation, and Downstream Analysis of Allelic Variation in Gene Expression

Modeling expression quantitative trait loci in data combining ethnic populations

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