Developmental profiles of the murine palatal methylome
Article first published online: 3 APR 2013
Copyright © 2013 Wiley Periodicals, Inc.
Birth Defects Research Part A: Clinical and Molecular Teratology
Volume 97, Issue 4, pages 171–186, April 2013
How to Cite
Seelan, R. S., Appana, S. N., Mukhopadhyay, P., Warner, D. R., Brock, G. N., Pisano, M. M. and Greene, R. M. (2013), Developmental profiles of the murine palatal methylome. Birth Defects Research Part A: Clinical and Molecular Teratology, 97: 171–186. doi: 10.1002/bdra.23126
- Issue published online: 17 APR 2013
- Article first published online: 3 APR 2013
- Manuscript Accepted: 21 FEB 2013
- Manuscript Revised: 11 FEB 2013
- Manuscript Received: 4 DEC 2012
- Supported in part by grant from NIH (DE018215, HD053509, DE021460) and NIH (P20 RR017702) from the COBRE program of the NIGMS.
Additional Supporting Information may be found in the online version of this article.
|bdra23126-sup-0001-suppinfo.tif||103K||Figure S1. A schematic outline of the Selective Enrichment of Methylated DNA (SEMD) protocol used for microarray analysis. Genomic DNA was isolated from GD 12–14 secondary palates and sonicated to generate fragments in the 300 bp – 1 kbp range. Sonicated DNA was treated with MBD2b, a methyl-CpG binding protein (Active Motif, Inc., CA) and the bound DNA fragments were released and amplified. Sonicated DNA not subjected to SEMD was similarly amplified (input DNA). Input DNA, labeled with Cy3, and SEMD DNA, labeled with Cy5, were hybridized to NimbleGen 2.1M mouse promoter microarrays (Roche NimbleGen, WI). Nine microarrays representing 3 biological replicates from each of GDs 12, 13 and 14, were probed. Data accruing from such hybridization were analyzed as detailed in Methods.|
|bdra23126-sup-0002-suppinfo.tif||110K||Figure S2. Boxplots. Figure S1 presents boxplots of all nine arrays for each channel and for the log2 red/green intensity ratios, after T-quantile normalization. Each box corresponds to a single array. The arrays are well-aligned in each channel, as expected from T-quantile normalization.|
|bdra23126-sup-0003-suppinfo.tif||435K||Figure S3. MA plots. Figure S2 shows the ‘MA’ plot for each array, after T-quantile. Here, M and A are defined as: M = log2(I1) - log2(I2); A = 1/2 (log2(I1)+log2(I2)), where I1 is the log2 red/green intensity ratio of the array studied and I2 is the log2 red/green intensity ratio of a “pseudo”-array, which consists of the median values of all the arrays. The mass of the distribution is expected to be concentrated along the M = 0 axis, and there should be no trend in the mean of M as a function of A. Outlier detection was performed by computing Hoeffding's statistic Da, which tests for the independence of the A and M distributions for each array. Shown are the 4 arrays with the highest value of Da (top row), and the 4 arrays with the lowest value (bottom row). The value of Da is shown in the panel headings. None of the arrays had Da values larger than the threshold for outlier detection (0.15).|
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