Integrated RNA-seq and DNase-seq analyses identify phenotype-specific BMP4 signaling in breast cancer

Abstract Background Bone morphogenetic protein 4 (BMP4) plays an important role in cancer pathogenesis. In breast cancer, it reduces proliferation and increases migration in a cell line-dependent manner. To characterize the transcriptional mediators of these phenotypes, we performed RNA-seq and DNase-seq analyses after BMP4 treatment in MDA-MB-231 and T-47D breast cancer cells that respond to BMP4 with enhanced migration and decreased cell growth, respectively. Results The RNA-seq data revealed gene expression changes that were consistent with the in vitro phenotypes of the cell lines, particularly in MDA-MB-231, where migration-related processes were enriched. These results were confirmed when enrichment of BMP4-induced open chromatin regions was analyzed. Interestingly, the chromatin in transcription start sites of differentially expressed genes was already open in unstimulated cells, thus enabling rapid recruitment of transcription factors to the promoters as a response to stimulation. Further analysis and functional validation identified MBD2, CBFB, and HIF1A as downstream regulators of BMP4 signaling. Silencing of these transcription factors revealed that MBD2 was a consistent activator of target genes in both cell lines, CBFB an activator in cells with reduced proliferation phenotype, and HIF1A a repressor in cells with induced migration phenotype. Conclusions Integrating RNA-seq and DNase-seq data showed that the phenotypic responses to BMP4 in breast cancer cell lines are reflected in transcriptomic and chromatin levels. We identified and experimentally validated downstream regulators of BMP4 signaling that relate to the different in vitro phenotypes and thus demonstrate that the downstream BMP4 response is regulated in a cell type-specific manner

Additional file 3: Table S2. of Integrated RNA-seq and DNase-seq analyses identify phenotype-specific BMP4 signaling in breast cancer

Differentially expressed genes after BMP4 treatment in T-47D cell line. Ensembl IDs, read counts, fold changes and Log2 ratios are shown. The genes are arranged in order from the largest to smallest Log2 ratio, first upregulated genes and then downregulated genes. (XLSX 34 kb

Additional file 8: Figure S3. of Integrated RNA-seq and DNase-seq analyses identify phenotype-specific BMP4 signaling in breast cancer

Transcription factor validation. The chosen TFs were silenced and then treated with BMP4 before measuring target gene expression using qRT-PCR. The transcription factor and cell line in question is stated at the beginning of each page. DLL, which is downregulated in T-47D upon BMP4 treatment, is circled with red. (PDF 256 kb

Additional file 9: Table S8. of Integrated RNA-seq and DNase-seq analyses identify phenotype-specific BMP4 signaling in breast cancer

Primers used for DNase-seq. Table S9. Primer sequences for qRT-PCR based expression analyses of BMP4 target genes and transcription factors. (DOCX 19 kb

Additional file 2: Table S1. of Integrated RNA-seq and DNase-seq analyses identify phenotype-specific BMP4 signaling in breast cancer

Differentially expressed genes after BMP4 treatment in MDA-MB-231 cell line. Ensembl IDs, read counts, fold changes and Log2 ratios are shown. The genes are arranged in order from the largest to smallest Log2 ratio, first upregulated genes and then downregulated genes. (XLSX 20 kb

Additional file 1: Figure S1. of Integrated RNA-seq and DNase-seq analyses identify phenotype-specific BMP4 signaling in breast cancer

Relationship between chromatin status of TSS and gene expression. The boxplots illustrate the distribution of DNase-seq read coverage at TSS for protein-coding genes at five different levels of gene expression, which were determined by division of expressions into quintiles. Panel A shows the results obtained from untreated MDA-MB-231 cells and panel B the corresponding results for untreated T-47D cells. Panels C and D illustrate the difference between non-expressed and differentially expressed (protein - coding) genes in terms of the chromatin status at TSS in vehicle-treated samples of MDA-MB-231 and T-47D cells, respectively. In both cell lines, chromatin is clearly open at the TSS of differentially expressed genes before the stimulation with BMP4. (PDF 2463 kb

Additional file 4: Table S3. of Integrated RNA-seq and DNase-seq analyses identify phenotype-specific BMP4 signaling in breast cancer

Survival analysis of DEGs in MDA-MB-231. Table S4. Survival analysis of DEGs in T-47D. Each differentially expressed protein - coding gene was tested for possible association with the survival of breast cancer patients based on the gene expression data obtained from The Cancer Genome Atlas (TCGA). Blue background indicates DEGs shared by both cell lines. Benjamini-Hochberg corrected P-values are shown. No diff. = no association with survival. Not available = not found in TCGA data. (XLSX 16 kb

Additional file 5: Table S5. of Integrated RNA-seq and DNase-seq analyses identify phenotype-specific BMP4 signaling in breast cancer

Comparison between our T-47D DNase-seq data and analogous data from ENCODE. DNase-seq peaks from promoter regions in BMP4-treated and vehicle-treated T-47D cells were compared to DNase-seq data of T-47D promoters from ENCODE (ENCSR000ELT replicates 1 and 2; ENCSR000EQB replicates 1 and 2). The table shows the percentage of shared peaks between pairs of samples. A high percentage of the peaks identified in our data are also present in ENCODE samples (cells B6-E7). (XLSX 8 kb

Genome-wide association studies highlight novel risk loci for septal defects and left-sided congenital heart defects

Abstract Background Congenital heart defects (CHD) are structural defects of the heart affecting approximately 1% of newborns. They exhibit low penetrance and non-Mendelian patterns of inheritance as varied and complex traits. While genetic factors are known to play an important role in the development of CHD, the specific genetics remain unknown for the majority of patients. To elucidate the underlying genetic risk, we performed a genome wide association study (GWAS) of CHDs in general and specific CHD subgroups using the FinnGen Release 10 (R10) (N > 393,000), followed by functional fine-mapping through eQTL and co-localization analyses using the GTEx database. Results We discovered three genome-wide significant loci associated with general CHD. Two of them were located in chromosome 17: 17q21.32 (rs2316327, intronic: LRRC37A2, Odds ratio (OR) [95% Confidence Interval (CI)] = 1.17[1.12–1.23], p = 1.5 × 10–9) and 17q25.3 (rs1293973611, nearest: BAHCC1, OR[95%CI] = 4.48[2.80–7.17], p = 7.0 × 10–10), respectively, and in addition to general CHD, the rs1293973611 locus was associated with the septal defect subtype. The third locus was in band 1p21.2 (rs35046143, nearest: PALMD, OR[95%CI] = 1.15[1.09–1.21], p = 7.1 × 10–9), and it was associated with general CHD and left-sided lesions. In the subgroup analysis, two additional loci were associated with septal defects (rs75230966 and rs6824295), and one with left-sided lesions (rs1305393195). In the eQTL analysis the variants rs2316327 (general CHD), and rs75230966 (septal defects) both located in 17q21.32 (with a LD r2 of 0.41) were both predicted to significantly associate with the expression of WNT9B in the atrial appendage tissue category. This effect was further confirmed by co-localization analysis, which also implicated WNT3 expression in the atrial appendage. A meta-analysis of general CHD together with the UK Biobank (combined N = 881,678) provided a different genome-wide significant locus in LRRC37A2; rs16941382 (OR[95%CI] = 1.15[1.11–1.20], p = 1.5 × 10–9) which is in significant LD with rs2316327. Conclusions Our results of general CHD and different CHD subcategories identified a complex risk locus on chromosome 17 near BAHCC1 and LRRC37A2, interacting with the genes WNT9B, WNT3 and MYL4, may constitute potential novel CHD risk associated loci, warranting future experimental tests to determine their role

Genome-wide association studies highlight novel risk loci for septal defects and left-sided congenital heart defects

Background Congenital heart defects (CHD) are structural defects of the heart affecting approximately 1% of newborns. They exhibit low penetrance and non-Mendelian patterns of inheritance as varied and complex traits. While genetic factors are known to play an important role in the development of CHD, the specific genetics remain unknown for the majority of patients. To elucidate the underlying genetic risk, we performed a genome wide association study (GWAS) of CHDs in general and specific CHD subgroups using the FinnGen Release 10 (R10) (N > 393,000), followed by functional fine-mapping through eQTL and co-localization analyses using the GTEx database. Results We discovered three genome-wide significant loci associated with general CHD. Two of them were located in chromosome 17: 17q21.32 (rs2316327, intronic: LRRC37A2, Odds ratio (OR) [95% Confidence Interval (CI)] = 1.17[1.12–1.23], p = 1.5 × 10–9) and 17q25.3 (rs1293973611, nearest: BAHCC1, OR[95%CI] = 4.48[2.80–7.17], p = 7.0 × 10–10), respectively, and in addition to general CHD, the rs1293973611 locus was associated with the septal defect subtype. The third locus was in band 1p21.2 (rs35046143, nearest: PALMD, OR[95%CI] = 1.15[1.09–1.21], p = 7.1 × 10–9), and it was associated with general CHD and left-sided lesions. In the subgroup analysis, two additional loci were associated with septal defects (rs75230966 and rs6824295), and one with left-sided lesions (rs1305393195). In the eQTL analysis the variants rs2316327 (general CHD), and rs75230966 (septal defects) both located in 17q21.32 (with a LD r2 of 0.41) were both predicted to significantly associate with the expression of WNT9B in the atrial appendage tissue category. This effect was further confirmed by co-localization analysis, which also implicated WNT3 expression in the atrial appendage. A meta-analysis of general CHD together with the UK Biobank (combined N = 881,678) provided a different genome-wide significant locus in LRRC37A2; rs16941382 (OR[95%CI] = 1.15[1.11–1.20], p = 1.5 × 10–9) which is in significant LD with rs2316327. Conclusions Our results of general CHD and different CHD subcategories identified a complex risk locus on chromosome 17 near BAHCC1 and LRRC37A2, interacting with the genes WNT9B, WNT3 and MYL4, may constitute potential novel CHD risk associated loci, warranting future experimental tests to determine their role.peerReviewe