Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

FourSig: A Method for Determining Chromosomal Interactions in 4C-Seq Data

ABSTRACT: The ability to correlate chromosome conformation and gene expression gives a great deal of information regarding the strategies used by a cell to properly regulate gene activity. 4C-seq is a relatively new and increasingly popular technology where the set of genomic interactions generated by a single point in the genome can be determined. 4C-seq experiments generate large, complicated datasets and it is imperative that signal is properly distinguished from noise. Currently there are a limited number of methods for analyzing 4C-seq data. Here, we present a new method, fourSig, which, in addition to being simple to use and as precise as current methods, also includes a new feature to prioritize significantly enriched interactions and predict their reproducibility among experimental replicates. Here, we demonstrate the efficacy of fourSig with previously published and novel 4C-seq datasets and show that our significance prioritization correlates with the ability to reproducibly detect interactions amongst replicates. The datasets provided include those generated from allele-specific 4C-Seq with a viewpoint of the TSS for the gene Ibtk on mouse Chromosome 9. FASTQ files, text files containing genomic coordiantes and read counts, and bedGraph formats for UCSC Genome Browser tracks are provided. All sequences were mapped relative to mouse genome build mm9. Sequencing of circular chromosome conformation capture (4C-Seq) was performed at the transcription start site (TSS) for the gene Ibtk for three replicates in F1 hybrid mouse trophoblast stem (TS) cells. Experiment was designed to detect allele specific patterns using SNP differences between the inbred lines mated to produce the TS cells (C57Bl/6 and CAST/EiJ)

ORGANISM(S): Mus musculus

SUBMITTER: Rex Williams

PROVIDER: E-GEOD-50907 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

fourSig: a method for determining chromosomal interactions in 4C-Seq data.

Williams Rex L RL Starmer Joshua J Mugford Joshua W JW Calabrese J Mauro JM Mieczkowski Piotr P Yee Della D Magnuson Terry T

Nucleic acids research 20140220 8

The ability to correlate chromosome conformation and gene expression gives a great deal of information regarding the strategies used by a cell to properly regulate gene activity. 4C-Seq is a relatively new and increasingly popular technology where the set of genomic interactions generated by a single point in the genome can be determined. 4C-Seq experiments generate large, complicated data sets and it is imperative that signal is properly distinguished from noise. Currently, there are a limited ...[more]

PMID: 24561615

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Project description:While it has been clearly established that well positioned H2A.Z-containing nucleosomes flank the nucleosome depleted region (NDR) at the transcriptional start site (TSS) of active mammalian genes 1,2, how this chromatin-based information is transmitted through the cell cycle is unknown. We show here that in trophoblast stem (TS) cells, the level of H2A.Z at promoters decreases during S phase coinciding with homotypic (H2A.Z/H2A.Z) nucleosomes flanking the TSS becoming heterotypic (H2A.Z/H2A). Surprisingly, these nucleosomes remain heterotypic at M phase. At the TSS, we identify an unstable heterotypic H2A.Z-containing nucleosome in G1 which, strikingly, is lost following DNA replication. These dynamic changes in H2A.Z at the TSS mirror a global expansion of the NDR at S and M which, unexpectedly, is unrelated to transcriptional activity. Coincident with the loss of H2A.Z at promoters, it is targeted to the centromere when mitosis begins. We surveyed whole genome expression using microarrays, in combination with H2A.Z ChIP-Seq (Illumina) data, to study the H2A.Z distribution on promoters of coding genes in different stages of the cell cycle in Trophoblast Stem (TS) cells. These data are published in Nekrasov et al., H2AZ inheritance during the cell cycle and it's impact on promoter organization and dynamics, Nature Structural and Molecular Biology (in press: accepted for publication on 24 Sep 2012). Mouse Trophoblast stem (TS) cells were grown in cell culture medium. By adding specific drugs cells were arrested at particular stages of the cell cycle: G1; S and M. Total RNA was extracted from TS cells arrested at G1; S and M stages of cell cycle using TRizol (Invitrogen) extraction protocol and purified further the by RNAeasy Extraction Kit (Qiagen). RNA quality was assesed on Bioanalyzer total RNA chip. RNA samples were reverse transcribed and resulted cDNA samples were subjected to DNA microarray analysis (in triplicate) using the GeneChip Mouse Gene 1.0 ST Array (Affymetrix). Robust Multichip Average (RMA) correction and probe set summaries were obtained using Affymetrix Power Tools software annotation (Affymetrix) based on the mm9 mouse genome. Unless otherwise stated, all subsequent expression analyses (see Supplementary Methods) were performed in the R statistical computing environment (version 2.11.1).

Project description:For potato crops, host resistance is currently the most effective and sustainable tool to manage potato root and tuber diseases caused by the plasmodiophorid, Spongospora subterranea. Arguably, zoospore root attachment is the most critical phase of the pathogen infection, however, the mechanisms underlying zoospore root attachment remains unknown. This study investigated the potential role of root cell wall surface polysaccharides and proteins in zoospore root attachment in resistant and susceptible potato cultivars. We first compared the effects of enzymatic removal of root cell wall proteins, N-linked glycans or polysaccharides on S. subterranea attachment to root tissue of resistant and susceptible potato cultivars. Subsequently, mass spectrometry analysis of peptides released by trypsin shaving (TS) of root segments identified 1235 proteins, of which 262 were differentially abundant between the resistant and susceptible cultivars. In particular, proteins associated with glutathione metabolism and lignin biosynthesis were more abundant in the resistant cultivar. Comparison with whole-root proteomic analysis of the same resistant and susceptible cultivars led to identification of 226 proteins unique to the TS dataset, of which 188 were significantly different between cultivars. Among these, the pathogen defence-related cell wall protein stem 28 kDa glycoprotein and two major latex proteins were significantly less abundant in the resistant cultivar compared to the susceptible cultivar. A further major latex protein was detected at reduced levels in the resistant cultivar in both TS and whole-root proteomic datasets. In contrast, in the TS-specific dataset, three glutathione S-transferase proteins were more abundant in the resistant cultivar, while the protein glucan endo-1,3-beta-glucosidase was significantly increased in both the TS and whole-root datasets. These results imply a particular role of major latex proteins and glucan endo-1,3-beta-glucosidase in the regulation of host susceptibility to S. subterranea.

Project description:4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait") that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes. 4C-Seq experiments from Igh and Cd83 bait in activated B cells and Tcrb (Eb) bait in double negative T cells and immature B cells. RNA-Seq and ATAC-Seq experiments in DN and Immature B cells.

Dataset Information

FourSig: A Method for Determining Chromosomal Interactions in 4C-Seq Data

Publications

fourSig: a method for determining chromosomal interactions in 4C-Seq data.

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