Computational protocol: Genome-Wide DNA Methylation Patterns of Bovine Blastocysts Developed In Vivo from Embryos Completed Different Stages of Development In Vitro

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Protocol publication

[…] The array data and downstream analyses methods used for the study have been described in EmbryoGENE Microarray (EDMA) platform []. Briefly, the intensity cutoff (Mean + 4*SD) of the negative controls was used to identify probes that displayed a signal intensity above the background. Loess normalization followed by quantile inter-array scale normalization was performed to obtain Bayesian statistics of differential methylation. Differentially methylated probes were then identified from the full set of probes using linear models for microarray data (limma) []. Since in EDMA platform, the measured fold changes are not quantitative but merely indicative of higher or lower odds of differentially methylation, probes which showed significant (p < 0.05) differences with absolute log2(fold-change) ≥1.5 between the treatment and the reference sample were considered as differentially methylated regions (DMRs). Therefore, probes which showed a significant increase in signal intensity by 1.5 folds and higher in ZY, 4C, 16C or IVP compared to the VO group were considered as hypermethylated probes while probes which displayed a reduced signal intensity by 1.5 folds and higher in ZY, 4C, 16C or IVP compared to the VO group were considered as hypomethylated probes. Enrichment analysis for genome-scale DNA methylation data was performed using string of integrated scripts that sorts the genome data into CpG island density, CpG island length, CpG island distance, genomic location and types of repetitive elements. Moreover, the gene ontology enrichment analysis was performed for genes that were associated with differentially methylated regions. Probes were associated with the GO terms of a gene provided the probe fragment falls within the introns, exons or promoter of a particular gene. Following this, Go enrichment was assessed using the topGO bioconductor package (http://www.bioconductor.org/packages/release/bioc/html/topGO.html) and the weight01 algorithm defined by Alexa et al []. For comparative analysis of methylation profile and gene expression data, the genes absolute log2(fold-change) ≥1.5, p value < 0.05 and false discovery rate (FDR) < 0.3 were selected from our previous data []. The heatmaps showing the relationship between differentially methylated regions and differentially expressed genes were constructed using PermutMatrix []. [...] Twelve differentially methylated regions (DMRs) were selected to validate the array data independently using bisulfite sequencing. For this, primers () were designed using MethPrimer (http://www.urogene.org/cgi-bin/methprimer/methprimer.cgi), an online tool for designing primers for amplification of bisulfite converted DNA. The genomic DNA in ZY, 4C, 16C, IVP and VO blastocyst groups was bisulfite converted using EZ DNA methylation direct kit (ZymoResearch) according to the manufacturer’s instruction. PCR amplification was performed in 25 μl volume containing 2 μl of bisulfite-converted DNA, 0.4 μl forward and reverses primers (10μm), 0.4 μ1 dNTP mixes (25mM), 0.2 μl Zymo Taq™ DNA polymerase (5u/μl) (ZymoResearch). The presence of PCR product was confirmed by loading 5 μl of the PCR product onto electrophoresis run on 2% w/v agarose gel stained with ethidium bromide at 120 V for 20 min. The PCR product was then purified using QIAquick PCR Purification (Qiagen) and cloned to pGEM®-T Easy Vector Systems (Promega, WI, USA) and transformed to E. coli competent cells. The bacterial culture was plated onto LB agar/ampicillin/IPTG/X-gal plate and incubated overnight at 37°C. Following this, 10–20 independent white colonies were selected and sequenced in GenomeLab™ GeXP Genetic Analysis System (Beckman Coulter). The bisulfite sequencing DNA methylation analysis software (BISMA) [] was used to analyze the sequencing data. The average of methylation percentage at each CpG site in each experimental group was used for analysis. […]

Pipeline specifications

Software tools methPrimer, BISMA
Application BS-seq analysis
Organisms Bos taurus
Diseases Neoplasms, Germ Cell and Embryonal
Chemicals Adenosine Triphosphate