Sequence analysis and editing for bisulphite genomic sequencing projects

Bisulphite genomic sequencing is a widely used technique for detailed analysis of the methylation status of a region of DNA. It relies upon the selective deamination of unmethylated cytosine to uracil after treatment with sodium bisulphite, usually followed by PCR amplification of the chosen target region. Since this two-step procedure replaces all unmethylated cytosine bases with thymine, PCR products derived from unmethylated templates contain only three types of nucleotide, in unequal proportions. This can create a number of technical difficulties (e.g. for some base-calling methods) and impedes manual analysis of sequencing results (since the long runs of T or A residues are difficult to align visually with the parent sequence). To facilitate the detailed analysis of bisulphite PCR products (particularly using multiple cloned templates), we have developed a visually intuitive program that identifies the methylation status of CpG dinucleotides by analysis of raw sequence data files produced by MegaBace or ABI sequencers as well as Staden SCF trace files and plain text files. The program then also collates and presents data derived from independent templates (e.g. separate clones). This results in a considerable reduction in the time required for completion of a detailed genomic methylation project

Chemotherapy induces Notch1-dependent MRP1 up-regulation, inhibition of which sensitizes breast cancer cells to chemotherapy

Background Multi-drug Resistance associated Protein-1 (MRP1) can export chemotherapeutics from cancer cells and is implicated in chemoresistance, particularly as is it known to be up-regulated by chemotherapeutics. Our aims in this study were to determine whether activation of Notch signalling is responsible for chemotherapy-induced MRP1 expression Notch in breast cancers, and whether this pathway can be manipulated with an inhibitor of Notch activity. Methods MRP1 and Notch1 were investigated in 29 patients treated with neoadjuvant chemotherapy (NAC) for breast cancer, using immunohistochemistry on matched biopsy (pre-NAC) and surgical samples (post-NAC). Breast epithelial cell cultures (T47D, HB2) were treated with doxorubicin in the presence and absence of functional Notch1, and qPCR, siRNA, Western blots, ELISAs and flow-cytometry were used to establish interactions. Results In clinical samples, Notch1 was activated by neoadjuvant chemotherapy (Wilcoxon signed-rank p < 0.0001) and this correlated with induction of MRP1 expression (rho = 0.6 p = 0.0008). In breast cell lines, doxorubicin induced MRP1 expression and function (non-linear regression p < 0.004). In the breast cancer line T47D, doxorubicin activated Notch1 and, critically, inhibition of Notch1 activation with the γ-secretase inhibitor DAPT abolished the doxorubicin-induced increase in MRP1 expression and function (t-test p < 0.05), resulting in enhanced cellular retention of doxorubicin and increased doxorubicin-induced apoptosis (t-test p = 0.0002). In HB2 cells, an immortal but non-cancer derived breast cell line, Notch1-independent MRP1 induction was noted and DAPT did not enhance doxorubicin-induced apoptosis. Conclusions Notch inhibitors may have potential in sensitizing breast cancer cells to chemotherapeutics and therefore in tackling chemoresistance

非線型Klein-Gordon方程式の大域解の存在に対する一注意(函数解析を用いた偏微分方程式の研究)

<p><b>Fig 1A: Comparison of <i>PLAGL1</i> transcription derived from three alternative promoters (P1; P2; P5) in a panel of human tissues</b>. For each tissue, three individual RT-PCR reactions were performed, using primers that specifically amplify transcripts from P1 (lane ‘1’), P2 (lane ‘2’) or P5 (lane ‘5’) (See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185678#sec009" target="_blank">Materials and methods</a>). The top two panels show <i>PLAGL1</i> in cDNA samples: Ov, ovary; Ki, kidney; Th, thymus; Co, colon; He, heart; Li, liver; Br, brain; Pr, prostate; Sp, spleen; Pl, placenta; Ad, adipose tissue; Bl, bladder; Ce, cervix; Oe, oesophagus; Lu, lung; Sk, skeletal muscle; Sm, small intestine; Te, testes; Th, thyroid; Tr, trachea; Pa, pancreas. The molecular weight marker is GeneRuler 100bp+ ladder (Invitrogen). <i>PLAGL1</i> transcripts are subject to complex alternative splicing of the 5′-UTR, and the two major bands (arrowed) result from alternative splicing of the coding exons. The third panel down shows RT-PCR of the housekeeping gene <i>RPLP0</i> as a loading control for each reaction. All non-template (water) controls were negative. <b>Fig 1B: Comparison of <i>PLAGL1</i> transcription from the three alternative promoters in primary blood cells.</b> cDNA samples: leukocytes (peripheral blood leukocytes); CD14+ cells (monocytes); activated CD4+ cells (T helper/inducer cells); CD8+ cells (T suppressor/cytotoxic cells); activated CD8+ cells; CD19+ cells (B-lymphocytes); activated CD19+; NK cells (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185678#sec009" target="_blank">Materials and methods</a>). The panel below shows <i>RPLP0</i> as loading controls for each reaction. All non-template controls were negative. <b>Fig 1C: qPCR analysis of promoter P5 transcription in a range of blood cell RNAs, compared with pancreas and placenta tissue.</b> The expression levels of P5 transcripts were normalised to that of the endogenous control gene <i>RPLP0</i> in each sample, and are expressed in arbitrary units. <b>Fig 1D: qPCR analysis of promoter P2 transcription using the same cDNA samples as in Fig. 1C, for comparison.</b> Similar to the P5 qPCR, expression levels were normalised to RPLP0 expression, and are in arbitrary units.</p

Alternative splicing of <i>PLAGL1</i> P5 transcripts isolated from A) activated CD4+ cell cDNA and B) activated CD19+ cell cDNA.

<p>The locus is shown at the top with the location of the five <i>PLAGL1</i> promoters indicated, and exon ‘3a’ and ‘3b’ (not to scale).</p

Allelic expression of <i>PLAGL1</i> transcripts derived from promoter P5, isolated from peripheral blood leukocytes from a normal individual (sample H3), heterozygous for SNP rs2092894.

<p><b>A</b>: SNP alleles represented in cloned P5 transcripts indicate biallelic transcription as both alleles are represented. Data for P1 and P2 for sample H3 have been published previously, showing monoallelic and biallelic expression respectively [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185678#pone.0185678.ref007" target="_blank">7</a>]. <b>B:</b> Representative electropherograms of two cloned P5 transcripts indicating the alternative alleles at the location of the SNP (arrows). The sequence shown is 5'-3' with respect to the <i>PLAGL1</i> sequence. A representative sequence from this amplicon (clone 11; lower panel) has been deposited in GenBank (MF361142).</p

Methylation analysis of CpG sites close to the P5 TSS in peripheral blood leukocytes and placenta tissue.

<p>A) DNA sequence of the region close to the promoter P5 exon, written in the 5′-3′ orientation with respect to <i>PLAGL1</i> (chr6: 144054338–144055350; GRCh38/hg38). The 70-bp P5 exon is shown in bold. The amplicons for methylation analysis are highlighted in grey, and the locations of PCR primers are underlined. (Note: actual primer sequences are for bisulphite-converted DNA, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185678#sec009" target="_blank">Materials and methods</a>). Amplicon 1: CpG sites 1–3, labelled from 5′ end with respect to P5, are highlighted in white. CpG site 4 was not analyzed. Amplicon 2: CpG sites 5–9 highlighted in white (note that CpGs 5 and 6 are located within a primer). A further CpG in the UCSC Genome browser reference sequence is a SNP (rs6901529). B) Methylation analysis by bisulphite sequencing for the two separate amplicons for peripheral blood leukocyte genomic DNA (individual H1 and H7, and amplicon 1 only for H2) and placenta genomic DNA. Squares represent CpG sites: black indicates a methylated CpG site; white, an unmethylated CpG site. Grey shading indicates a CpG site that was neither CG nor TG.</p

Transcriptional start sites identified for the <i>PLAGL1</i> P5 promoter in activated CD4+ and activated CD19+ cells.

<p>The complete P5 exon, as defined by 5′-RLM-RACE in these cell types, is 70-bp in length (chr6:144,055,217–144,055,286; genome assembly GRCh38/hg38). Arrows indicate the different transcriptional start sites identified in cloned 5'-RACE transcripts. The corresponding number in the Table indicates the number of clones corresponding to that TSS and their prevalence, expressed as a percentage of the number of clones sequenced.</p

Neoadjuvant Chemotherapy Induces Expression Levels of Breast Cancer Resistance Protein That Predict Disease-Free Survival in Breast Cancer

<div><p>Three main xenobiotic efflux pumps have been implicated in modulating breast cancer chemotherapy responses. These are P-glycoprotein (Pgp), Multidrug Resistance-associated Protein 1 (MRP1), and Breast Cancer Resistance Protein (BCRP). We investigated expression of these proteins in breast cancers before and after neoadjuvant chemotherapy (NAC) to determine whether their levels define response to NAC or subsequent survival. Formalin-fixed paraffin-embedded tissues were collected representing matched pairs of core biopsy (pre-NAC) and surgical specimen (post-NAC) from 45 patients with invasive ductal carcinomas. NAC regimes were anthracyclines +/− taxanes. Immunohistochemistry was performed for Pgp, MRP1 and BCRP and expression was quantified objectively using computer-aided scoring. Pgp and MRP1 were significantly up-regulated after exposure to NAC (Wilcoxon signed-rank p = 0.0024 and p<0.0001), while BCRP showed more variation in response to NAC, with frequent up- (59% of cases) and down-regulation (41%) contributing to a lack of significant difference overall. Pre-NAC expression of all markers, and post-NAC expression of Pgp and MRP1 did not correlate with NAC response or with disease-free survival (DFS). Post-NAC expression of BCRP did not correlate with NAC response, but correlated significantly with DFS (Log rank p = 0.007), with longer DFS in patients with low post-NAC BCRP expression. In multivariate Cox regression analyses, post-NAC BCRP expression levels proved to predict DFS independently of standard prognostic factors, with high expression associated with a hazard ratio of 4.04 (95% confidence interval 1.3–12.2; p = 0.013). We conclude that NAC-induced expression levels of BCRP predict survival after NAC for breast cancer, while Pgp and MRP1 expression have little predictive value.</p></div