Motivation: DNA enrichment followed by sequencing is a versatile tool in molecular biology, with a wide variety of applications including genome-wide analysis of epigenetic marks and mechanisms. A common requirement of these diverse applications is a comparison of read coverage between experimental conditions. The amount of samples generated for such comparisons ranges from few replicates to hundreds of samples per condition for epigenome-wide association studies. Consequently, there is an urgent need for software that allows for fast and simple processing and comparison of sequencing data derived from enriched DNA.Results: Here, we present a major update of the R/Bioconductor package MEDIPS, which allows for an arbitrary number of replicates per group and integrates sophisticated statistical methods for the detection of differential coverage between experimental conditions. Our approach can be applied to a diversity of quantitative sequencing data. In addition, our update adds novel functionality to MEDIPS, including correlation analysis between samples, and takes advantage of Bioconductor’s annotation databases to facilitate annotation of specific genomic regions.Availability and implementation: The latest version of MEDIPS is available as version 1.12.0 and part of Bioconductor 2.13. The package comes with a manual containing detailed description of its functionality and is available at http://www.bioconductor.org.Contact: lienhard@molgen.mpg.deSupplementary information: Supplementary data are available at Bioinformatics online.

Chromatin remodeling and histone modifications facilitate access of transcription factors to DNA by promoting the unwinding and destabilization of histone-DNA interactions. We present DPF3, a new epigenetic key factor for heart and muscle development characterized by a double PHD finger. DPF3 is associated with the BAF chromatin remodeling complex and binds methylated and acetylated lysine residues of histone 3 and 4. Thus, DPF3 may represent the first plant homeodomains that bind acetylated lysines, a feature previously only shown for the bromodomain. During development Dpf3 is expressed in the heart and somites of mouse, chicken, and zebrafish. Morpholino knockdown of dpf3 in zebrafish leads to incomplete cardiac looping and severely reduced ventricular contractility, with disassembled muscular fibers caused by transcriptional deregulation of structural and regulatory proteins. Promoter analysis identified Dpf3 as a novel downstream target of Mef2a. Taken together, DPF3 adds a further layer of complexity to the BAF complex by representing a tissue-specific anchor between histone acetylations as well as methylations and chromatin remodeling. Furthermore, this shows that plant homeodomain proteins play a yet unexplored role in recruiting chromatin remodeling complexes to acetylated histones.[Keywords: Heart and skeletal muscle development and function; PHD finger; BAF chromatin remodeling complex; SMARCD3-BAF60; acetylated and methylated histones; Mef2] Supplemental material is available at http://www.genesdev.org.

MicroRNAs are short single-stranded RNAs that are associated with gene regulation at the transcriptional and translational level. Changes in their expression were found in a variety of human cancers. Only few data are available on microRNAs in clear cell renal cell carcinoma (ccRCC). We performed genome-wide expression profiling of microRNAs using microarray analysis and quantification of specific microRNAs by TaqMan real-time RT-PCR. Matched malignant and non-malignant tissue samples from two independent sets of 12 and 72 ccRCC were profiled. The microarray-based experiments identified 13 over-expressed and 20 down-regulated microRNAs in malignant samples. Expression in ccRCC tissue samples compared with matched non-malignant samples measured by RT-PCR was increased on average by 2.7- to 23-fold for the hsa-miR-16, −452*, −224, −155 and −210, but decreased by 4.8- to 138-fold for hsa-miR-200b, −363, −429, −200c, −514 and −141. No significant associations between these differentially expressed microRNAs and the clinico-pathological factors tumour stage, tumour grade and survival rate were found. Nevertheless, malignant and non-malignant tissue could clearly be differentiated by their microRNA profile. A combination of miR-141 and miR-155 resulted in a 97% overall correct classification of samples. The presented differential microRNA pattern provides a solid basis for further validation, including functional studies.

The generation of genome-wide data derived from methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq) has become a major tool for epigenetic studies in health and disease. The computational analysis of such data, however, still falls short on accuracy, sensitivity, and speed. We propose a time-efficient statistical method that is able to cope with the inherent complexity of MeDIP-seq data with similar performance compared with existing methods. In order to demonstrate the computational approach, we have analyzed alterations in DNA methylation during the differentiation of human embryonic stem cells (hESCs) to definitive endoderm. We show improved correlation of normalized MeDIP-seq data in comparison to available whole-genome bisulfite sequencing data, and investigated the effect of differential methylation on gene expression. Furthermore, we analyzed the interplay between DNA methylation, histone modifications, and transcription factor binding and show that in contrast to de novo methylation, demethylation is mainly associated with regions of low CpG densities.[Supplemental material is available at http://www.genome.org. The MeDIP-seq data from this study have been submitted to NCBI Sequence Read Archive (http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi) under accession no. SRA012665. The bead array gene expression data from this study have been submitted to the NCBI Gene Expression Omnibus (http:// www.ncbi.nlm.nih.gov/geo) under accession no. GSE21715. The MEDIPS software package, manual, data, and example data are available online at http://medips.molgen.mpg. et al. 2005), which can be detected either by tiling arrays (MeDIPChip) or by next-generation sequencing (MeDIP-seq). Methylation profiles obtained by the MeDIP approach are not base pair-specific but reflect methylation levels on a resolution restricted by the size of the sonicated DNA fragments after amplification and size selection. In contrast, bisulfite sequencing detects cytosine methylation on a base-pair level. Although whole-genome single-base resolution maps have been generated (Lister et al. 2008(Lister et al. , 2009, such techniques cannot yet be cost-effectively applied to screen large sets of sequences or samples. Reduced representation bisulfite sequencing (RRBS) was introduced in order to address this issue by selecting only some regions of the genome for sequencing. Here, reduced representation is achieved by the size-fractionation of DNA fragments after restriction enzyme digestion (Meissner et al. 2008;Laird 2010). In contrast to bisulfite sequencing, MeDIP-seq-derived methylation data are of far lower resolution, and therefore, it remains difficult to discriminate between CpG and non-CpG methylation when single-end short reads are considered. However, MeDIP-seq covers nearly as many CpGs per sample genome as does the more expensive whole-genome shotgun bisulfite sequencing (WGSBS) approach (Laird 2010). An advantage of the MeDIP approach is the generation of unbiased, cost-effective, and fullgenome methylation levels w...