Then the model was used to predict values for the response variable.
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To remove effects of any independent variable on the response variable, residuals function in R was applied to obtain the corrected values of the response variable. Then, we randomly sampled regions from each ERBS group and repeated the sampling for 10 times. Choosing random sites was limited by the number of ERBS with at least 3 mutations. To make sure an equal number of genes were included for each ERBS group, we randomly sampled genes for times and computed the mean expression levels of the genes sampled each time. The distributions of gene expression levels were compared across ERBS groups with different numbers of mutations.
P values were calculated using two-sided t test. Same as above, genes were randomly sampled for times to compute mean expression distributions for different ERBS groups, which avoids bias when comparing with the ChIA-PET based analysis results. Bam files for the 9 ER ChIP-seq samples with good outcome, and the 12 samples with poor or metastasis outcome were merged for mutation discovery [ 23 ]. To increase the credibility of somatic mutations identified from the ChIP-seq data, only the sites covered with at least 10 reads and encompassing both the reference and alternative alleles in BRCA-EU were selected as potential somatic mutations.
In the end, the percentage of outcome-associated ERBS that contain potential somatic mutations was calculated for samples with corresponding outcomes. Motif score ratios between mutant and reference sequences were calculated for the reliably identified motifs. Motifs with large absolute values of score ratios were presented in Figs. BEDTools utilities [ 54 ] were used to carry out operations such as extensions or overlaps in the various analyses of genomic features. All the statistical tests were performed in the R version 3.
Customized bash, R and python scripts were used to perform all the other analysis. Increasing amounts of unlabelled WT or mutant competitor oligonucleotides were used to analyze specificity of mobility shifts. Competitor probe concentration was 8 pM.
- Ligands & receptors.
- Receptor (biochemistry) - Wikipedia.
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Promega FuGene 6 cat. The same molar ratio of plasmids were used for dCas9-target and control sgRNAs. Single colonies were picked up, grown in well plates, and then transferred to well plates for expansion. For each colony, genomic DNA was isolated according to the protocol [ 37 ] and qPCR was performed using the primers that cover the point mutation site of the ZNF gene. Fragmented chromatin was diluted with ChIP-dilution buffer 0.
Next, beads were washed well on the magnetic field with each of these buffers two times: low-salt immune complex wash buffer 0.
After reverse cross-linking, proteinase K and RNase digestion, DNA was extracted with ethanol precipitation method and quantified via Qubit Fluorometer. A primer pair for a negative control genomic region was used to calculate fold enrichment. Crosslinking was quenched with ice-cold 0. Sequentially, cell and nuclear membrane lysis reactions were performed with appropriate buffers. DNAs were precipitated by using phenol-chloroform extraction method.
Normalized crosslinking frequency was calculated by using Ct value difference between target and genomic control primer pairs. Wild-type and mutant MCF-7 cells were plated at a density of 1, cells per well in well plates.
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The plate was inverted overnight and covered to dry before imaging. Evolution of the cancer genome. Nat Rev Genet. Nat Genet. International network of cancer genome projects. Landscape of somatic mutations in breast cancer whole-genome sequences. Genome-wide analysis of noncoding regulatory mutations in cancer. Synonymous mutations frequently act as driver mutations in human cancers. Nat Biotechnol. Systematic analysis of noncoding somatic mutations and gene expression alterations across 14 tumor types.
Highly recurrent TERT promoter mutations in human melanoma.
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TERT promoter mutations in familial and sporadic melanoma. Recurrent and functional regulatory mutations in breast cancer. The large-scale distribution of somatic mutations in cancer genomes. Hum Mutat. Signatures of mutational processes in human cancer. The cancer genome. Nucleotide excision repair is impaired by binding of transcription factors to DNA. Differential DNA repair underlies mutation hotspots at active promoters in cancer genomes. Supek F, Lehner B. Differential DNA mismatch repair underlies mutation rate variation across the human genome.
Cancer statistics, CA Cancer J Clin. Int J Cancer. Quantification of estrogen receptor alpha and beta expression in sporadic breast cancer. Estrogen receptors and human disease. J Clin Invest. Estrogen carcinogenesis in breast cancer. N Engl J Med.
CCR chemokine receptor binding Gene Ontology Term (GO)
Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Genome Biol. The effects of chromatin organization on variation in mutation rates in the genome. The topography of mutational processes in breast cancer genomes. Nat Commun. Cell Rep. Consortium EP. An integrated encyclopedia of DNA elements in the human genome. Chromatin interaction analysis reveals changes in small chromosome and telomere clustering between epithelial and breast cancer cells.
Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation. Cook PR.
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