The single nucleotide variant rs12722489 determines differential estrogen receptor binding and enhancer properties of an IL2RA intronic region

Afanasyeva, Marina; Putlyaeva, Lidia V.; Demin, D. E.; Kulakovskiy, Ivan V.; Vorontsov, Ilya E.; Фридман, М. В.; Makeev, Vsevolod J.; Kuprash, Dmitry V.; Schwartz, Anton M.

doi:10.1371/journal.pone.0172681

Cited by 10 publications

(8 citation statements)

References 57 publications

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“…In the case of TFBS prediction for the analysis of regulatory networks, the D-quality models may notably reduce performance ( 41 ). However, other applications such as annotation of regulatory sequence variants ( 42 , 43 ) may benefit from additional TFs and alternative binding models. Thus, starting from this release we provide two collections: the CORE collection of the most precise models (ABC quality) recommended for TFBS predictions for annotation of regulatory regions, and the FULL collection that includes alternative models and models of lower quality (D), which can be used for exploratory purposes.…”

Section: Discussionmentioning

confidence: 99%

HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis

Kulakovskiy

Vorontsov

Yevshin³

et al. 2017

Nucleic Acids Research

740

702

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We present a major update of the HOCOMOCO collection that consists of patterns describing DNA binding specificities for human and mouse transcription factors. In this release, we profited from a nearly doubled volume of published in vivo experiments on transcription factor (TF) binding to expand the repertoire of binding models, replace low-quality models previously based on in vitro data only and cover more than a hundred TFs with previously unknown binding specificities. This was achieved by systematic motif discovery from more than five thousand ChIP-Seq experiments uniformly processed within the BioUML framework with several ChIP-Seq peak calling tools and aggregated in the GTRD database. HOCOMOCO v11 contains binding models for 453 mouse and 680 human transcription factors and includes 1302 mononucleotide and 576 dinucleotide position weight matrices, which describe primary binding preferences of each transcription factor and reliable alternative binding specificities. An interactive interface and bulk downloads are available on the web: http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco11. In this release, we complement HOCOMOCO by MoLoTool (Motif Location Toolbox, http://molotool.autosome.ru) that applies HOCOMOCO models for visualization of binding sites in short DNA sequences.

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Section: Discussionmentioning

confidence: 99%

HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis

Kulakovskiy

Vorontsov

Yevshin³

et al. 2017

Nucleic Acids Research

740

702

View full text Add to dashboard Cite

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“…There are a few examples where, among the many signals resulting from GWAS, the causal variant and the underlying mechanism has been defined, such as the following. SNPs in the interleukin 2 receptor gene seem to differently influence various autoimmune diseases [17][18][19]. Likewise, variants of TYK 2 locus resulting from GWAS in different immune-mediated conditions normally mediate a balanced genetic effect, warranting a trade-off between autoimmunity and immunodeficiency [20].…”

Section: Introductionmentioning

confidence: 99%

Reworking GWAS Data to Understand the Role of Nongenetic Factors in MS Etiopathogenesis

Mechelli

Umeton

Manfrè

et al. 2020

Genes

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Genome-wide association studies have identified more than 200 multiple sclerosis (MS)-associated loci across the human genome over the last decade, suggesting complexity in the disease etiology. This complexity poses at least two challenges: the definition of an etiological model including the impact of nongenetic factors, and the clinical translation of genomic data that may be drivers for new druggable targets. We reviewed studies dealing with single genes of interest, to understand how MS-associated single nucleotide polymorphism (SNP) variants affect the expression and the function of those genes. We then surveyed studies on the bioinformatic reworking of genome-wide association studies (GWAS) data, with aggregate analyses of many GWAS loci, each contributing with a small effect to the overall disease predisposition. These investigations uncovered new information, especially when combined with nongenetic factors having possible roles in the disease etiology. In this context, the interactome approach, defined as “modules of genes whose products are known to physically interact with environmental or human factors with plausible relevance for MS pathogenesis”, will be reported in detail. For a future perspective, a polygenic risk score, defined as a cumulative risk derived from aggregating the contributions of many DNA variants associated with a complex trait, may be integrated with data on environmental factors affecting the disease risk or protection.

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“…This finding suggested that patients carrying the "TT" genotype at rs9679162, actually harbor a 5 kb genomic region (around GALNT14-rs9679162), which is genetically different from those from the "non-TT" genotype. The sequence differences may thereby impact GALNT14 mRNA and protein expression, as variations in the intron region have been found to affect many aspects of regulatory events for gene expression, including transcription efficiencies and alternative splicing [17][18][19][20][21]. This view is supported by the findings that the expression levels of GALNT14 are different between patients with the "TT" and "non-TT" genotypes.…”

Section: Discussionmentioning

confidence: 94%

The GALNT14 Genotype Predicts Postoperative Outcome of Pancreatic Ductal Adenocarcinoma

Chiang

Yeh

Hwang

et al. 2019

JCM

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Pancreatic ductal adenocarcinoma (PDA) is notorious for its poor prognosis. The current mainstay of treatment for PDA is surgical resection followed by adjuvant chemotherapy. However, it is difficult to predict the post-operative outcome because of the lack of reliable markers. The single-nucleotide polymorphism (SNP) of N-acetylgalactosaminyltransferase14 (GALNT14) has been proven to predict the progression-free survival (PFS), overall survival (OS) and response to chemotherapy in various types of gastrointestinal (GI) cancers. However, its role in PDA has not been studied. This study aims to investigate whether the GALNT14 SNP genotype can be a prognostic marker for PDA. A cohort of one hundred and three PDA patients having received surgical resection were retrospectively enrolled. GALNT14 genotypes and the clinicopathological parameters were correlated with postoperative prognosis. The genotype analysis revealed that 19.4%, 60.2% and 20.4% of patients had the GALNT14 “TT”, “TG” and “GG” genotypes, respectively. The patients with the “GG” genotype had a mean OS time of 37.1 months (95% confidence interval [CI]: 18.2–56.1) and those with the “non-GG” genotype had a mean OS time of 16.1 months (95% CI: 13.1–19.2). Kaplan–Meier analysis showed that the “GG” genotype had a significantly better OS compared to the “non-GG” genotype (p = 0.005). However, there was no significant difference between the “GG” and “non-GG” genotypes in PFS (p = 0.172). The baseline characteristics between patients with the “GG” and “non-GG” genotypes were compared, and no significant difference was found. Univariate followed by multivariate Cox proportional hazard models demonstrated the GALNT14 “GG” genotype, negative resection margin, and locoregional disease as independent predictors for favorable OS (p = 0.003, p = 0.037, p = 0.021, respectively). Sensitivity analysis was performed in each subgroup to examine the relationship of GALNT14 with different clinicopathological variables and no heterogeneity was found. The GALNT14 “GG” genotype is associated with favorable survival outcome, especially OS, in patients with resected PDA and could serve as a prognostic marker.

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The single nucleotide variant rs12722489 determines differential estrogen receptor binding and enhancer properties of an IL2RA intronic region

Cited by 10 publications

References 57 publications

HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis

HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis

Reworking GWAS Data to Understand the Role of Nongenetic Factors in MS Etiopathogenesis

The GALNT14 Genotype Predicts Postoperative Outcome of Pancreatic Ductal Adenocarcinoma

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