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EQTL Colocalization Analyses Identify NTN4 as a Candidate Breast Cancer Risk Gene.

ABSTRACT: Breast cancer genome-wide association studies (GWASs) have identified 150 genomic risk regions containing more than 13,000 credible causal variants (CCVs). The CCVs are predominantly noncoding and enriched in regulatory elements. However, the genes underlying breast cancer risk associations are largely unknown. Here, we used genetic colocalization analysis to identify loci at which gene expression could potentially explain breast cancer risk phenotypes. Using data from the Breast Cancer Association Consortium (BCAC) and quantitative trait loci (QTL) from the Genotype-Tissue Expression (GTEx) project and The Cancer Genome Project (TCGA), we identify shared genetic relationships and reveal novel associations between cancer phenotypes and effector genes. Seventeen genes, including NTN4, were identified as potential mediators of breast cancer risk. For NTN4, we showed the rs61938093 CCV at this region was located within an enhancer element that physically interacts with the NTN4 promoter, and the risk allele reduced NTN4 promoter activity. Furthermore, knockdown of NTN4 in breast cells increased cell proliferation in vitro and tumor growth in vivo. These data provide evidence linking risk-associated variation to genes that may contribute to breast cancer predisposition.

SUBMITTER: Beesley J

PROVIDER: S-EPMC7536644 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:We previously identified a locus at 21q22.3, tagged by the single nucleotide polymorphism (SNP) rs35418111, being associated with breast cancer risk at a genome-wide significance level; however, the underlying causal functional variants and gene(s) responsible for this association are unknown. We performed functional genomic analyses to identify potential functional variants and target genes that may mediate this association. Functional annotation for SNPs in high linkage disequilibrium (LD, r2 > 0.8) with rs35418111 in Asians showed evidence of promoter and/or enhancer activities, including rs35418111, rs2078203, rs8134832, rs57385578, and rs8126917. These five variants were assessed for interactions with nuclear proteins by electrophoretic mobility shift assays. Our results showed that the risk alleles for rs2078203 and rs35418111 altered DNA-protein interaction patterns. Cis-expression quantitative loci (cis-eQTL) analysis, using data from the Genotype-Tissue Expression database (GTEx) European-ancestry female normal breast tissue, indicated that the risk allele of rs35418111 was associated with a decreased expression of the YBEY gene, a relatively uncharacterized endoribonuclease in humans. We investigated the biological effects of YBEY on breast cancer cell lines by transient knock-down of YBEY expression in MCF-7, T47D, and MDA-MB-231 cell lines. Knockdown of YBEY mRNA in breast cancer cell lines consistently decreased cell proliferation, colony formation, and migration/invasion, regardless of estrogen receptor status. We performed RNA sequencing in MDA-MB-231 cells transfected with siRNA targeting YBEY and subsequent gene set enrichment analysis to identify gene networks associated with YBEY knockdown. These data indicated YBEY was involved in networks associated with inflammation and metabolism. Finally, we showed trends in YBEY expression patterns in breast tissues from The Cancer Genome Atlas (TCGA); early-stage breast cancers had elevated YBEY expression compared with normal tissue, but significantly decreased expression in late-stage disease. Our study provides evidence of a significant role for the human YBEY gene in breast cancer pathogenesis and the association between the rs35418111/21q22.3 locus and breast cancer risk, which may be mediated through functional SNPs, rs35418111 and rs2078203, that regulate expression of YBEY.

Project description:BackgroundA detailed understanding of genetic variants that affect beef merit helps maximize the efficiency of breeding for improved production merit in beef cattle. To prioritize the putative variants and genes, we ran a comprehensive genome-wide association studies (GWAS) analysis for 21 agronomic traits using imputed whole-genome variants in Simmental beef cattle. Then, we applied expression quantitative trait loci (eQTL) mapping between the genotype variants and transcriptome of three tissues (longissimus dorsi muscle, backfat, and liver) in 120 cattle.ResultsWe identified 1,580 association signals for 21 beef agronomic traits using GWAS. We then illuminated 854,498 cis-eQTLs for 6,017 genes and 46,970 trans-eQTLs for 1,903 genes in three tissues and built a synergistic network by integrating transcriptomics with agronomic traits. These cis-eQTLs were preferentially close to the transcription start site and enriched in functional regulatory regions. We observed an average of 43.5% improvement in cis-eQTL discovery using multi-tissue eQTL mapping. Fine-mapping analysis revealed that 111, 192, and 194 variants were most likely to be causative to regulate gene expression in backfat, liver, and muscle, respectively. The transcriptome-wide association studies identified 722 genes significantly associated with 11 agronomic traits. Via the colocalization and Mendelian randomization analyses, we found that eQTLs of several genes were associated with the GWAS signals of agronomic traits in three tissues, which included genes, such as NADSYN1, NDUFS3, LTF and KIFC2 in liver, GRAMD1C, TMTC2 and ZNF613 in backfat, as well as TIGAR, NDUFS3 and L3HYPDH in muscle that could serve as the candidate genes for economic traits.ConclusionsThe extensive atlas of GWAS, eQTL, fine-mapping, and transcriptome-wide association studies aid in the suggestion of potentially functional variants and genes in cattle agronomic traits and will be an invaluable source for genomics and breeding in beef cattle.

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EQTL Colocalization Analyses Identify NTN4 as a Candidate Breast Cancer Risk Gene.

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