Combined SNPs sequencing and allele specific proteomics capture reveal functional causality underpinning the 2p25 prostate cancer susceptibility locus
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PROVIDER: PRJNA1212024 | ENA |
REPOSITORIES: ENA
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Project description:Genome wide association studies (GWASs) have identified numerous risk loci associated with prostate cancer, yet unraveling their functional significance remains elusive. Leveraging our high-throughput SNPs-seq method, we pinpointed rs4519489 within the multi-ancestry GWAS-discovered 2p25 locus as a potential functional SNP due to its significant allelic differences in protein binding. Here, we conduct a comprehensive analysis of rs4519489 and its associated gene, NOL10, employing diverse cohort data and experimental models. Clinical findings reveal a synergistic effect between rs4519489 genotype and NOL10 expression on prostate cancer prognosis and severity. Through unbiased proteomics screening, we reveal that the risk allele A of rs4519489 exhibits enhanced binding to USF1, a novel oncogenic transcription factor (TF) implicated in prostate cancer progression and prognosis, resulting in elevated NOL10 expression. Furthermore, we elucidate that NOL10 regulates cell cycle pathways, fostering prostate cancer progression. The concurrent expression of NOL10 and USF1 correlates with aggressive prostate cancer characteristics and poorer prognosis. Collectively, our study offers a robust strategy for functional SNP screening and TF identification through high-throughput SNPs-seq and unbiased proteomics, highlighting the rs4519489-USF1- NOL10 regulatory axis as a promising biomarker or therapeutic target for clinical diagnosis and treatment of prostate cancer.
2025-01-21 | GSE287279 | GEO
Project description:Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift (EMSA) and luciferase reporter assays. To identify binding of transcription factors and/or other nuclear proteins in an allele-determined manner, we employed pulldown using nuclear extract from Daudi cells and silver staining in SNPs that had exhibited allele-specific differential binding by EMSA. Each pulldown product for each allele of the five high-probability SNPs (rs2297550 C/G, rs13213604 C/G, rs276461 T/C, rs9907955 C/T, rs7302634 T/C) was evaluated by mass spectrometry (MS) to identify binding nuclear proteins, yielding a set of candidate proteins for each.
2024-08-02 | PXD048367 | Pride
Project description:Introduction Genome-wide association studies along with expression quantitative trait loci (eQTL) have identified hundreds of single nucleotide polymorphisms (SNPs) and their target genes in prostate cancer (PrCa). Although these genetic associations to PrCa have been widely reported, functional characterization of these risk loci remains challenging. Methods To screen for regulatory SNPs, we designed a library containing 9133 guide RNAs (gRNAs) to target 2,166 candidate SNP sites implicated in PrCa. We performed negative screening in dCas9-KRAB stable prostate cell lines and applied the RIGOR program to identify the essential SNPs for cell proliferation. We further characterized the regulatory role of a selected single nucleotide polymorphim (SNP, rs60464856) using luciferase reporter assay, ChIP-qPCR, and xCas9 base editing in prostate cells. Finally, we investigated the biological impact of the SNP-regulated gene RUVBL1 on cell proliferation and tumor growth via gene knockdown using in vitro and in vivo assays. Results From interference of 2,166 candidate SNPs via CRISPR interference screening, the RIGOR program identified 117 SNPs that could regulate genes to promote growth advantage in prostate cancer cell lines. Compared to unselected SNPs, the 117 candidates tended to reside near 5 kb flanking the transcription start sites (p = 0.01). To characterize the regulatory role of these SNPs, we selected one SNP (rs60464856) for detailed analysis. This SNP was covered by multiple gRNAs significantly depleted in the screening (FDR<0.05). Pooled SNP association analysis in the PRACTICAL cohort showed significantly higher PrCa risk for the G allele (pvalue=1.2E-16). eQTL analysis showed that the G allele is associated with an increased expression of RUVBL1 in multiple datasets. To further validate the CRISPR interference effect, we transfected a gRNA targeting the rs60464856 site in the dCas9 stable cell lines and observed significant inhibition of the RUVBL1 expression. We also applied the xCas9 adenine base editor to convert the rs60464856 A into G allele and observed an increased RUVBL1 expression in subclones carrying the rs60464856 G allele in prostate cell lines. To test if any protein showed allele-specific binding at rs60464856, we used SILAC-based DNA pull-down proteomics and observed that cohesin subunits (including SMC3) preferred the A allele. ChIP qPCR assays showed significant enrichment of CTCF and SMC3 signals at the rs60464856 site with preferential binding to the A allele. To evaluate the potential role of this locus in maintaining long-range chromatin structure, we analyzed a HiC dataset and found that the rs60464856 locus enriched consistent chromatin interactions in prostate cell lines. To determine the potential role of the rs60464856 target gene, we knocked down the RUVBL1 via shRNA and observed significant proliferation inhibition in prostate cell lines. We also tested PC3 cells with RUVBL1 knockdown in nude mice xenografts and observed reduced tumorigenesis. Gene set enrichment analysis showed that RUVBL1 expression was associated with the enrichment of cell cycle related pathways in both cell line and TCGA prostate cancer cohorts. Lastly, we showed that an increased RUVBL1 expression and its relevant pathway activation were associated with poor survival. Conclusion We applied the CRISPR interference screening at selected prostate cancer risk loci and identified over a hundred regulatory SNPs essential for prostate cell proliferation. Further analysis confirmed the important role of rs60464856 and its target gene RUVBL1 in prostate cell growth and tumorigenesis. To validate one of our candidate, we knocked down RUVBL1 gene in BPH1 and PC3 cell lines and observed the transcriptome alterations with RNA-seq
2023-07-05 | GSE224646 | GEO
Project description:Introduction Genome-wide association studies along with expression quantitative trait loci (eQTL) have identified hundreds of single nucleotide polymorphisms (SNPs) and their target genes in prostate cancer (PrCa). Although these genetic associations to PrCa have been widely reported, functional characterization of these risk loci remains challenging. Methods To screen for regulatory SNPs, we designed a library containing 9133 guide RNAs (gRNAs) to target 2,166 candidate SNP sites implicated in PrCa. We performed negative screening in dCas9-KRAB stable prostate cell lines and applied the RIGOR program to identify the essential SNPs for cell proliferation. We further characterized the regulatory role of a selected single nucleotide polymorphim (SNP, rs60464856) using luciferase reporter assay, ChIP-qPCR, and xCas9 base editing in prostate cells. Finally, we investigated the biological impact of the SNP-regulated gene RUVBL1 on cell proliferation and tumor growth via gene knockdown using in vitro and in vivo assays. Results From interference of 2,166 candidate SNPs via CRISPR interference screening, the RIGOR program identified 117 SNPs that could regulate genes to promote growth advantage in prostate cancer cell lines. Compared to unselected SNPs, the 117 candidates tended to reside near 5 kb flanking the transcription start sites (p = 0.01). To characterize the regulatory role of these SNPs, we selected one SNP (rs60464856) for detailed analysis. This SNP was covered by multiple gRNAs significantly depleted in the screening (FDR<0.05). Pooled SNP association analysis in the PRACTICAL cohort showed significantly higher PrCa risk for the G allele (pvalue=1.2E-16). eQTL analysis showed that the G allele is associated with an increased expression of RUVBL1 in multiple datasets. To further validate the CRISPR interference effect, we transfected a gRNA targeting the rs60464856 site in the dCas9 stable cell lines and observed significant inhibition of the RUVBL1 expression. We also applied the xCas9 adenine base editor to convert the rs60464856 A into G allele and observed an increased RUVBL1 expression in subclones carrying the rs60464856 G allele in prostate cell lines. To test if any protein showed allele-specific binding at rs60464856, we used SILAC-based DNA pull-down proteomics and observed that cohesin subunits (including SMC3) preferred the A allele. ChIP qPCR assays showed significant enrichment of CTCF and SMC3 signals at the rs60464856 site with preferential binding to the A allele. To evaluate the potential role of this locus in maintaining long-range chromatin structure, we analyzed a HiC dataset and found that the rs60464856 locus enriched consistent chromatin interactions in prostate cell lines. To determine the potential role of the rs60464856 target gene, we knocked down the RUVBL1 via shRNA and observed significant proliferation inhibition in prostate cell lines. We also tested PC3 cells with RUVBL1 knockdown in nude mice xenografts and observed reduced tumorigenesis. Gene set enrichment analysis showed that RUVBL1 expression was associated with the enrichment of cell cycle related pathways in both cell line and TCGA prostate cancer cohorts. Lastly, we showed that an increased RUVBL1 expression and its relevant pathway activation were associated with poor survival. Conclusion We applied the CRISPR interference screening at selected prostate cancer risk loci and identified over a hundred regulatory SNPs essential for prostate cell proliferation. Further analysis confirmed the important role of rs60464856 and its target gene RUVBL1 in prostate cell growth and tumorigenesis. To discover proliferative essential SNP loci, we used CRISPRi screening technology and DNA-seq to determine those functional candidate from previously published eQTL variants
2023-07-05 | GSE224653 | GEO
Project description:Causality of gut bacteria Klebsiella pneumoniae to hypertension development
| PRJNA765306 | ENA
Project description:Background: Expression quantitative trait loci (eQTL) studies are a valuable approach for identifying genetic variants correlated with gene expression. However, identifying the causal variants is challenging due to linkage disequilibrium amongst variants in the same haplotype block. In this study, we aim to identify functional SNPs in key regulatory regions that alter transcriptional regulation and thus, potentially impact cellular function. The majority of disease-associated single-nucleotide polymorphisms (SNPs) are located in regulatory regions, which can result in allele-specific binding (ASB) of transcription factors and differential expression of the target gene alleles. Here, we present regSNPs-ASB, a generalized linear model-based approach to accurately identify regulatory SNPs that are located in transcription factor binding sites from ATAC-seq data. Results: Using regSNPs-ASB, we identified 53 regulatory SNPs in human MCF-7 breast cancer cells and 125 regulatory SNPs in human mesenchymal stem cells (MSC). By integrating the regSNPs-ASB output with RNA-seq experimental data and publicly available chromatin interaction data from MCF-7 cells, we found that these 53 regulatory SNPs were associated with 74 potential target genes and that 32 (43%) of these genes showed significant allele-specific expression (ASE). By comparing all of the MCF-7 and MSC regulatory SNPs to the eQTLs in the Genome-Tissue Expression (GTEx) Project database, we found that 30% (16/53) of the regulatory SNPs in MCF-7 and 43% (52/122) of the regulatory SNPs in MSC were also eQTLs. The enrichment of regulatory SNPs in eQTLs indicated that many of them are likely responsible for allelic differences in gene expression (chi-square test, p-value < 0.01). In sum, we conclude that regSNPs-ASB is a useful tool for identifying causal variants from ATAC-seq data. This new computational tool will enable efficient prioritization of genetic variants identified as eQTL for further studies to validate their causal regulatory function. Ultimately, identifying causal genetic variants will further our understanding of the underlying molecular mechanisms of disease and the eventual development of potential therapeutic targets.
2020-02-14 | GSE145245 | GEO
Project description:Most of the millions of single-nucleotide polymorphisms (SNPs) in the human genome are non-coding, and many overlap with putative regulatory elements. Genome-wide association studies have linked many of these SNPs to human traits or to gene expression levels, but rarely with sufficient resolution to identify the causal SNPs. Functional screens based on reporter assays have previously been of insufficient throughput to test the vast space of SNPs for possible effects on enhancer and promoter activity. Here, we have leveraged the throughput of the SuRE reporter technology to survey a total of 5.9 million SNPs, including 57% of the known common SNPs world-wide. We identified more than 30 thousand SNPs that alter the activity of putative regulatory elements, often in a cell-type specific manner. These data indicate that a large proportion of human non-coding SNPs may affect gene regulation. Integration of these SuRE data with genome-wide association studies may help to identify causal SNPs.
2019-04-05 | GSE128325 | GEO
Project description:ApoC-III is a proatherogenic protein associated with elevated triglycerides; its deficiency is associated with reduced atherosclerosis. Mixed dyslipidemia, characterized by elevated triglyceride and apoC-III levels and low HDL cholesterol level, with or without elevated LDL cholesterol, increases cardiovascular disease risk and is commonly treated with combined statin and fibrate therapy. We sought to identify single nucleotide polymorphisms (SNPs) associated with apoC-III level response to combination therapy with statins and fenofibric acid (FA) in individuals with mixed dyslipidemia. Participants in a multicenter, randomized, double-blind, active-controlled study examining response to FA alone and in combination with statin were genotyped for candidate SNPs. Association between genotyed SNPs and APOC3 response to therapy was conducted We sought to identify single nucleotide polymorphisms (SNPs) associated with apoC-III level response to combination therapy with statins and fenofibric acid (FA) in individuals with mixed dyslipidemia. Participants in a multicenter, randomized, double-blind, active-controlled study examining response to FA alone and in combination with statin were genotyped for candidate SNPs. Genomic DNA extracted from peripheral blood was genotyped using a custom GoldenGate bead array encompassing 384 SNPs (Illumina). Multivariate linear regression and 2-way ANOVA for percent change in apoC-III level were performed between the groups receiving FA alone compared with FA+statin compared with statin alone.
2012-01-11 | E-GEOD-34945 | biostudies-arrayexpress
Project description:ApoC-III is a proatherogenic protein associated with elevated triglycerides; its deficiency is associated with reduced atherosclerosis. Mixed dyslipidemia, characterized by elevated triglyceride and apoC-III levels and low HDL cholesterol level, with or without elevated LDL cholesterol, increases cardiovascular disease risk and is commonly treated with combined statin and fibrate therapy. We sought to identify single nucleotide polymorphisms (SNPs) associated with apoC-III level response to combination therapy with statins and fenofibric acid (FA) in individuals with mixed dyslipidemia. Participants in a multicenter, randomized, double-blind, active-controlled study examining response to FA alone and in combination with statin were genotyped for candidate SNPs. Association between genotyed SNPs and APOC3 response to therapy was conducted
2012-01-11 | GSE34945 | GEO
Project description:We identified 9325 reliable single nucleotide polymorphisms (SNPs) distributed throughout the genome, of which nearly 68% were represented in R9308 versus Xieqingzao B by CT and GA SNPs. This may indicate that DNA methylation, a heritable epigenetic mark, exists in the parents and their F1 hybrid. Of 2793 identified transcripts with consistent allelic biases, only 480 (17%) showed significant allelic biases during at least one stage, suggesting that trans effects may mediate most transcriptional differences in hybrid offspring. Approximately 67% and 62% of the 480 transcripts showed allelic expression biases towards the R9308 allele at tillering and heading stages, respectively. Transcripts with higher levels of gene expression in R9308 also exhibited R9308 allelic biases in the hybrid. In addition, 125 transcripts were identified with significant allelic expression biases at both stages, of which 74% showed allele expression biases towards the R9308 allele. R9308 alleles may tend to preserve their characteristic states of activity in the hybrid and may play an important role in hybrid vigor at both stages. The allelic expression of 355 transcripts was highly stage-specific, with divergent allelic expression patterns observed at different developmental stages. Many transcripts associated with stress resistance were differently regulated in the F1 hybrid. The results of this study would provide valuable information for further understanding molecular mechanisms of heterosis.
2014-05-16 | GSE43727 | GEO