Noncoding SNPs associated with increased GDF15 levels located in a metformin-activated enhancer region upstream of GDF15

2020 ◽  
Vol 21 (8) ◽  
pp. 509-520
Author(s):  
Natália D Linhares ◽  
Daniela A Pereira ◽  
Izabela MCA Conceição ◽  
Glória R Franco ◽  
Walter L Eckalbar ◽  
...  
Keyword(s):  
Quantitative Trait ◽  
Chromatin Immunoprecipitation ◽  
Genome Wide Association Study ◽  
Tissue Expression ◽  
Regulatory Elements ◽  
Intervention Trial ◽  
Sequencing Data ◽  
Genome Wide ◽  
Dna Elements ◽  
Trait Locus

Aim: GDF15 levels are a biomarker for metformin use. We performed the functional annotation of noncoding genome-wide association study (GWAS) SNPs for GDF15 levels and the Genotype-Tissue Expression (GTEx)-expression quantitative trait loci (eQTLs) for GDF15 expression within metformin-activated enhancers around GDF15. Materials & methods: These enhancers were identified using chromatin immunoprecipitation followed by sequencing data for active (H3K27ac) and silenced (H3K27me3) histone marks on human hepatocytes treated with metformin, Encyclopedia of DNA Elements data and cis-regulatory elements assignment tools. Results: The GWAS lead SNP rs888663, the SNP rs62122429 associated with GDF15 levels in the Outcome Reduction with Initial Glargine Intervention trial, and the GTEx-expression quantitative trait locus rs4808791 for GDF15 expression in whole blood are located in a metformin-activated enhancer upstream of GDF15 and tightly linked in Europeans and East Asians. Conclusion: Noncoding variation within a metformin-activated enhancer may increase GDF15 expression and help to predict GDF15 levels.

scholarly journals A compendium of uniformly processed human gene expression and splicing quantitative trait loci

2021 ◽  
Vol 53 (9) ◽  
pp. 1290-1299
Author(s):  
Nurlan Kerimov ◽  
James D. Hayhurst ◽  
Kateryna Peikova ◽  
Jonathan R. Manning ◽  
Peter Walter ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quantitative Trait ◽  
Target Genes ◽  
Genome Wide Association Study ◽  
Cell Types ◽  
Summary Statistics ◽  
Genome Wide ◽  
Cell Type Specific ◽  
Trait Locus ◽  
Complex Human Traits

AbstractMany gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue (https://www.ebi.ac.uk/eqtl), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.

scholarly journals TCF7L2 lncRNA: a link between bipolar disorder and body mass index through glucocorticoid signaling

2021 ◽  
Author(s):  
Duan Liu ◽  
Thanh Thanh Le Nguyen ◽  
Huanyao Gao ◽  
Huaizhi Huang ◽  
Daniel C. Kim ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Bipolar Disorder ◽  
Body Mass ◽  
Genome Wide Association Study ◽  
Induced Pluripotent Stem Cell ◽  
Sequencing Data ◽  
Peripheral Tissues ◽  
Genome Wide ◽  
A Genome ◽  
Trait Locus

AbstractBipolar disorder (BD) and obesity are highly comorbid. We previously performed a genome-wide association study (GWAS) for BD risk accounting for the effect of body mass index (BMI), which identified a genome-wide significant single-nucleotide polymorphism (SNP) in the gene encoding the transcription factor 7 like 2 (TCF7L2). However, the molecular function of TCF7L2 in the central nervous system (CNS) and its possible role in the BD and BMI interaction remained unclear. In the present study, we demonstrated by studying human induced pluripotent stem cell (hiPSC)-derived astrocytes, cells that highly express TCF7L2 in the CNS, that the BD-BMI GWAS risk SNP is associated with glucocorticoid-dependent repression of the expression of a previously uncharacterized TCF7L2 transcript variant. That transcript is a long non-coding RNA (lncRNA-TCF7L2) that is highly expressed in the CNS but not in peripheral tissues such as the liver and pancreas that are involved in metabolism. In astrocytes, knockdown of the lncRNA-TCF7L2 resulted in decreased expression of the parent gene, TCF7L2, as well as alterations in the expression of a series of genes involved in insulin signaling and diabetes. We also studied the function of TCF7L2 in hiPSC-derived astrocytes by integrating RNA sequencing data after TCF7L2 knockdown with TCF7L2 chromatin-immunoprecipitation sequencing (ChIP-seq) data. Those studies showed that TCF7L2 directly regulated a series of BD risk genes. In summary, these results support the existence of a CNS-based mechanism underlying BD-BMI genetic risk, a mechanism based on a glucocorticoid-dependent expression quantitative trait locus that regulates the expression of a novel TCF7L2 non-coding transcript.

scholarly journals Integrative Analysis of Omics Data Reveals Regulatory Network of CDK10 in Vitiligo Risk

2021 ◽  
Vol 12 ◽  
Author(s):  
Minglong Cai ◽  
Tao Yuan ◽  
He Huang ◽  
Lan Gui ◽  
Li Zhang ◽  
...  
Keyword(s):  
Quantitative Trait ◽  
Association Studies ◽  
Regulatory Elements ◽  
Functional Genes ◽  
Large Sample Size ◽  
Genome Wide Association Studies ◽  
Omics Data ◽  
Genome Wide ◽  
Trait Locus ◽  
Destruction Of Melanocytes

Vitiligo is a multifactorial polygenic disorder, characterized by acquired depigmented skin and overlying hair resulting from the destruction of melanocytes. Genome-wide association studies (GWASs) of vitiligo have identified approximately 100 genetic variants. However, the identification of functional genes and their regulatory elements remains a challenge. To prioritize putative functional genes and DNAm sites, we performed a Summary data-based Mendelian Randomization (SMR) and heterogeneity in dependent instruments (HEIDI) test to integrate omics summary statistics from GWAS, expression quantitative trait locus (eQTL), and methylation quantitative trait loci (meQTL) analysis of large sample size. By integrating omics data, we identified two newly putative functional genes (SPATA2L and CDK10) associated with vitiligo and further validated CDK10 by qRT-PCR in independent samples. We also identified 17 vitiligo-associated DNA methylation (DNAm) sites in Chr16, of which cg05175606 was significantly associated with the expression of CDK10 and vitiligo. Colocalization analyses detected transcript of CDK10 in the blood and skin colocalizing with cg05175606 at single nucleotide polymorphism (SNP) rs77651727. Our findings revealed that a shared genetic variant rs77651727 alters the cg05175606 as well as up-regulates gene expression of CDK10 and further decreases the risk of vitiligo.

scholarly journals ColocQuiaL: A QTL-GWAS colocalization pipeline

2021 ◽  
Author(s):  
Brian Y Chen ◽  
William Paul Bone ◽  
Kimberly Lorenz ◽  
Michael Levin ◽  
Marylyn D Ritchie ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Tissue Expression ◽  
Data Availability ◽  
Genome Wide ◽  
Trait Loci ◽  
Causal Genes ◽  
Difficult Challenge

Summary: Identifying genomic features responsible for genome-wide association study (GWAS) signals has proven to be a difficult challenge; many researchers have turned to colocalization analysis of GWAS signals with expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) to connect GWAS signals to candidate causal genes. The ColocQuiaL pipeline provides a framework to perform these colocalization analyses at scale across the genome and returns summary files and locus visualization plots to allow for detailed review of the results. As an example, we used ColocQuiaL to perform colocalization between the latest type 2 diabetes GWAS data and Genotype-Tissue Expression (GTEx) v8 single-tissue eQTL and sQTL data. Availability and Implementation: ColocQuiaL is primarily written in R and is freely available at github: https://github.com/bychen9/eQTL_colocalizer. Contact: [email protected] Availability and Implementation: ColocQuiaL is primarily written in R and is freely available at github: https://github.com/bychen9/eQTL_colocalizer. Contact: [email protected]

scholarly journals Development of molecular markers associated with resistance to Meloidogyne incognita by performing quantitative trait locus analysis and genome-wide association study in sweetpotato

DNA Research ◽  
2019 ◽  
Vol 26 (5) ◽  
pp. 399-409 ◽  
Author(s):  
Rumi Sasai ◽  
Hiroaki Tabuchi ◽  
Kenta Shirasawa ◽  
Kazuki Kishimoto ◽  
Shusei Sato ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Association Study ◽  
Meloidogyne Incognita ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Single Nucleotide ◽  
Genome Wide ◽  
F1 Progeny ◽  
Trait Locus

Abstract The southern root-knot nematode, Meloidogyne incognita, is a pest that decreases yield and the quality of sweetpotato [Ipomoea batatas (L.) Lam.]. There is a demand to produce resistant cultivars and develop DNA markers to select this trait. However, sweetpotato is hexaploid, highly heterozygous, and has an enormous genome (∼3 Gb), which makes genetic linkage analysis difficult. In this study, a high-density linkage map was constructed based on retrotransposon insertion polymorphism, simple sequence repeat, and single nucleotide polymorphism markers. The markers were developed using F1 progeny between J-Red, which exhibits resistance to multiple races of M. incognita, and Choshu, which is susceptible to multiple races of such pest. Quantitative trait locus (QTL) analysis and a genome-wide association study detected highly effective QTLs for resistance against three races, namely, SP1, SP4, and SP6-1, in the Ib01-6 J-Red linkage group. A polymerase chain reaction marker that can identify genotypes based on single nucleotide polymorphisms located in this QTL region can discriminate resistance from susceptibility in the F1 progeny at a rate of 70%. Thus, this marker could be helpful in selecting sweetpotato cultivars that are resistant to multiple races of M. incognita.

Sign in / Sign up

Export Citation Format

Share Document