scholarly journals Integrated Functional Genomic Analysis Enables Annotation of Kidney Genome-Wide Association Study Loci

2019 ◽  
Vol 30 (3) ◽  
pp. 421-441 ◽  
Author(s):  
Karsten B. Sieber ◽  
Anna Batorsky ◽  
Kyle Siebenthall ◽  
Kelly L. Hudkins ◽  
Jeff D. Vierstra ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Genetic Variants ◽  
Target Genes ◽  
Mesangial Cells ◽  
Genome Wide Association ◽  
Chromatin Conformation ◽  
Genome Wide ◽  
Dna Elements ◽  
Regulatory Dna

BackgroundLinking genetic risk loci identified by genome-wide association studies (GWAS) to their causal genes remains a major challenge. Disease-associated genetic variants are concentrated in regions containing regulatory DNA elements, such as promoters and enhancers. Although researchers have previously published DNA maps of these regulatory regions for kidney tubule cells and glomerular endothelial cells, maps for podocytes and mesangial cells have not been available.MethodsWe generated regulatory DNA maps (DNase-seq) and paired gene expression profiles (RNA-seq) from primary outgrowth cultures of human glomeruli that were composed mainly of podocytes and mesangial cells. We generated similar datasets from renal cortex cultures, to compare with those of the glomerular cultures. Because regulatory DNA elements can act on target genes across large genomic distances, we also generated a chromatin conformation map from freshly isolated human glomeruli.ResultsWe identified thousands of unique regulatory DNA elements, many located close to transcription factor genes, which the glomerular and cortex samples expressed at different levels. We found that genetic variants associated with kidney diseases (GWAS) and kidney expression quantitative trait loci were enriched in regulatory DNA regions. By combining GWAS, epigenomic, and chromatin conformation data, we functionally annotated 46 kidney disease genes.ConclusionsWe demonstrate a powerful approach to functionally connect kidney disease-/trait–associated loci to their target genes by leveraging unique regulatory DNA maps and integrated epigenomic and genetic analysis. This process can be applied to other kidney cell types and will enhance our understanding of genome regulation and its effects on gene expression in kidney disease.

scholarly journals Epigenomes of Human Hearts Reveal New Genetic Variants Relevant for Cardiac Disease and Phenotype

2020 ◽  
Vol 127 (6) ◽  
pp. 761-777 ◽  
Author(s):  
Wilson Lek Wen Tan ◽  
Chukwuemeka George Anene-Nzelu ◽  
Eleanor Wong ◽  
Chang Jie Mick Lee ◽  
Hui San Tan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Quantitative Trait Loci ◽  
Genetic Variants ◽  
Quantitative Trait ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Trait Loci

Rationale: Identifying genetic markers for heterogeneous complex diseases such as heart failure is challenging and requires prohibitively large cohort sizes in genome-wide association studies to meet the stringent threshold of genome-wide statistical significance. On the other hand, chromatin quantitative trait loci, elucidated by direct epigenetic profiling of specific human tissues, may contribute toward prioritizing subthreshold variants for disease association. Objective: Here, we captured noncoding genetic variants by performing epigenetic profiling for enhancer H3K27ac chromatin immunoprecipitation followed by sequencing in 70 human control and end-stage failing hearts. Methods and Results: We have mapped a comprehensive catalog of 47 321 putative human heart enhancers and promoters. Three thousand eight hundred ninety-seven differential acetylation peaks (FDR [false discovery rate], 5%) pointed to pathways altered in heart failure. To identify cardiac histone acetylation quantitative trait loci (haQTLs), we regressed out confounding factors including heart failure disease status and used the G-SCI (Genotype-independent Signal Correlation and Imbalance) test 1 to call out 1680 haQTLs (FDR, 10%). RNA sequencing performed on the same heart samples proved a subset of haQTLs to have significant association also to gene expression (expression quantitative trait loci), either in cis (180) or through long-range interactions (81), identified by Hi-C (high-throughput chromatin conformation assay) and HiChIP (high-throughput protein centric chromatin) performed on a subset of hearts. Furthermore, a concordant relationship between the gain or disruption of TF (transcription factor)-binding motifs, inferred from alternative alleles at the haQTLs, implied a surprising direct association between these specific TF and local histone acetylation in human hearts. Finally, 62 unique loci were identified by colocalization of haQTLs with the subthreshold loci of heart-related genome-wide association studies datasets. Conclusions: Disease and phenotype association for 62 unique loci are now implicated. These loci may indeed mediate their effect through modification of enhancer H3K27 acetylation enrichment and their corresponding gene expression differences (bioRxiv: https://doi.org/10.1101/536763 ). Graphical Abstract: A graphical abstract is available for this article.

scholarly journals Integrating genome-wide association and transcriptome predicted model identify novel target genes with osteoporosis

2019 ◽  
Author(s):  
Peng Yin ◽  
Muchun Zhu ◽  
Fan Hu ◽  
Jiaxin Jiang ◽  
Li Yin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Mineral Density ◽  
Candidate Genes ◽  
Bone Mineral ◽  
Target Genes ◽  
Causal Variant ◽  
Genome Wide Association ◽  
Mineral Density ◽  
Genome Wide ◽  
Causal Variants

AbstractOsteoporosis (OP) is a highly polygenetic disease which is usually characterized by low bone mineral density. Genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with bone mineral density. However, the biological mechanisms of these loci remain elusive. To identify potential causal genes of the associated loci, we detected trait-gene expression associations by transcriptome-wide association study (TWAS) method. It directly imputes gene expression effects from GWAS data, using a statistical prediction model trained on GTEx reference transcriptome data, with blood and skeletal tissues data. Then we performed a colocalization analysis to evaluate the posterior probability of biological patterns: association characterized by a single shared causal variant or two distinct causal variants. The ultimate analysis identified 276 candidate genes, including 3 novel loci, 204 novel candidate genes and 69 replicated from GWAS. The 3 novel loci located at chr6: 72417543, chr15: 69601206, chr21: 30530692, mapping to gene RIMS1, SPESP1, MAP3K7CL. The results of colocalization analysis indicated that 142 of them showing strong evidence of a single shared causal variant and 134 of them showing evidence of joint causal variants. Their biological function was directly or indirectly associated with the occurrence of OP validated by VarElect tool. Several important OP-associated pathways were detected by protein-protein interaction and pathway enrichment analysis. Target genes were further enriched for differential expression genes in osteoblasts expression profiles, e.g. IBSP, affecting calcium and hydroxyapatite binding, and CD44, regulating alternative splicing of gene transcription. Transcriptome fine-mapping identifies more disease-related genes and provide additional insight into the development of novel targeted therapeutics to treat OP.

scholarly journals Post-GWAS era in genetics of schizophrenia

2019 ◽  
pp. 6-7
Author(s):  
V. E. Golimbet ◽  
A. K. Golov ◽  
N. V. Kondratyev
Keyword(s):  
Genetic Variants ◽  
Target Genes ◽  
Disease Risk ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Biological Mechanisms ◽  
Master Regulators ◽  
Genome Wide

Genome-wide association studies (GWASs) discovered multiple genetic variants associated with schizophrenia. Te next step (post-GWAS analysis) is aimed at identifying the causal genetic variants and biological mechanisms underlying the associations with disease risk. Te following strategies are considered: the study of transcriptional regulation in neuronal human cells and the use of epigenomic information for searching for regulatory elements involved in the pathogenesis of schizophrenia. Te frst strategy includes identifcation of neuronal enhancers, mapping of potential target genes and functional confrmation of enhancer-promoter interactions. Te second approach is focused on the identifcation of transcriptional factors, which appear to be master regulators of expression.

scholarly journals Genome-wide association study identifies common genetic risk factors for alcohol, heroin and methamphetamine dependence

2018 ◽  
Author(s):  
Yan Sun ◽  
Suhua Chang ◽  
Zhen Liu ◽  
Libo Zhang ◽  
Fan Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
White Matter ◽  
Genetic Variants ◽  
Genome Wide Association Study ◽  
Significant Snps ◽  
Genome Wide Association ◽  
Self Administration ◽  
Rat Models ◽  
Methamphetamine Dependence ◽  
Genome Wide

AbstractBackgroundCommon molecular and cellular foundations underlie different types of substance dependence (SD). However direct evidence for common genetic factors of SD is lacking. Here we aimed to identify specific genetic variants that are shared between alcoholism, heroin and methamphetamine dependence.MethodsWe first conducted a combined case-control genome-wide association analysis (GWAS) of 521 alcoholic, 1,026 heroin and 1,749 methamphetamine patients and 2,859 healthy controls. We then replicated the significant loci using an independent cohort (146 alcoholic, 1,045 heroin, 763 methamphetamine and 1,904 controls). Second, we examined the genetic effects of these identified SNPs on gene expression, addiction characteristics and brain images (gray and white matter). Furthermore, we investigated the effects of these genetic variants on addiction behaviors using self-administration rat models.ResultsWe identified and validated four genome-wide significant loci in the combined cohorts in the discovery stage: ADH1B rs1229984 (P=6.45×10−10), ANKS1B rs2133896 (P=4.09×10−8), AGBL4 rs147247472 (P=4.30×10−8) and CTNNA2 rs10196867 (P=4.67×10−8). Association results for each dependence group showed that ADH1B rs1229984 was only associated with alcoholism, while the other three loci were associated with heroin, methamphetamine addiction and alcoholism respectively. Variants that were strongly linked to rs2133896 affected ANKS1B gene expression, heroin use frequency and interacted with heroin dependence to affect gray matter of the left calcarine and white matter of the right superior longitudinal fasciculus. In addition, the reduced anks1b expression in the ventral tegmental area increased addiction vulnerability for heroin and methamphetamine in self-administration rat models.ConclusionOur findings revealed several novel genome-wide significant SNPs and genes that synchronously affected the vulnerability and phenotypes for alcoholism, heroin and MA dependence. These findings could shed light on the root cause and the generalized vulnerability for SD.

scholarly journals Genome-wide association analysis identified both RNA-seq and DNA variants associated to paratuberculosis in Canadian Holstein cattle ‘in vitro’ experimentally infected macrophages

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Olivier Ariel ◽  
Jean-Simon Brouard ◽  
Andrew Marete ◽  
Filippo Miglior ◽  
Eveline Ibeagha-Awemu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variants ◽  
Genome Wide Association Study ◽  
Genetic Selection ◽  
Dna Chip ◽  
Genome Wide Association ◽  
Functional Markers ◽  
Rna Seq ◽  
Regulatory Pathways ◽  
Genome Wide

Abstract Background Mycobacterium avium ssp. paratuberculosis (MAP) is the causative agent of paratuberculosis, or Johne’s disease (JD), an incurable bovine disease. The evidence for susceptibility to MAP disease points to multiple interacting factors, including the genetic predisposition to a dysregulation of the immune system. The endemic situation in cattle populations can be in part explained by a genetic susceptibility to MAP infection. In order to identify the best genetic improvement strategy that will lead to a significant reduction of JD in the population, we need to understand the link between genetic variability and the biological systems that MAP targets in its assault to dominate macrophages. MAP survives in macrophages where it disseminates. We used next-generation RNA (RNA-Seq) sequencing to study of the transcriptome in response to MAP infection of the macrophages from cows that have been naturally infected and identified as positive for JD (JD (+); n = 22) or negative for JD (healthy/resistant, JD (−); n = 28). In addition to identifying genetic variants from RNA-seq data, SNP variants were also identified using the Bovine SNP50 DNA chip. Results The complementary strategy allowed the identification of 1,356,248 genetic variants, including 814,168 RNA-seq and 591,220 DNA chip variants. Annotation using SnpEff predicted that the 2435 RNA-seq genetic variants would produce high functional effect on known genes in comparison to the 33 DNA chip variants. Significant variants from JD(+/−) macrophages were identified by genome-wide association study and revealed two quantitative traits loci: BTA4 and 11 at (P < 5 × 10− 7). Using BovineMine, gene expression levels together with significant genomic variants revealed pathways that potentially influence JD susceptibility, notably the energy-dependent regulation of mTOR by LKB1-AMPK and the metabolism of lipids. Conclusion In the present study, we succeeded in identifying genetic variants in regulatory pathways of the macrophages that may affect the susceptibility of cows that are healthy/resistant to MAP infection. RNA-seq provides an unprecedented opportunity to investigate gene expression and to link the genetic variations to biological pathways that MAP normally manipulate during the process of killing macrophages. A strategy incorporating functional markers into genetic selection may have a considerable impact in improving resistance to an incurable disease. Integrating the findings of this research into the conventional genetic selection program may allow faster and more lasting improvement in resistance to bovine paratuberculosis in dairy cattle.

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