• Title/Summary/Keyword: ChIP

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ChIP-seq Analysis of Histone H3K27ac and H3K27me3 Showing Different Distribution Patterns in Chromatin

  • Kang, Jin;Kim, AeRi
    • Biomedical Science Letters
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    • v.28 no.2
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    • pp.109-119
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    • 2022
  • Histone proteins can be modified by the addition of acetyl group or methyl group to specific amino acids. The modifications have different distribution patterns in chromatin. Recently, histone modifications are studied based on ChIP-seq data, which requires reasonable analysis of sequencing data depending on their distribution patterns. Here we have analyzed histone H3K27ac and H3K27me3 ChIP-seq data and it showed that the H3K27ac is enriched at narrow regions while H3K27me3 distributes broadly. To properly analyze the ChIP-seq data, we called peaks for H3K27ac and H3K27me3 using MACS2 (narrow option and broad option) and SICER methods, and compared propriety of the peaks using signal-to-background ratio. As results, H3K27ac-enriched regions were well identified by both methods while H3K27me3 peaks were properly identified by SICER, which indicates that peak calling method is more critical for histone modifications distributed broadly. When ChIP-seq data were compared in different sequencing depth (15, 30, 60, 120 M), high sequencing depth caused high false-positive rate in H3K27ac peak calling, but it reflected more properly the broad distribution pattern of H3K27me3. These results suggest that sequencing depth affects peak calling from ChIP-seq data and high sequencing depth is required for H3K27me3. Taken together, peak calling tool and sequencing depth should be chosen depending on the distribution pattern of histone modification in ChIP-seq analysis.

ChIP-seq Library Preparation and NGS Data Analysis Using the Galaxy Platform (ChIP-seq 라이브러리 제작 및 Galaxy 플랫폼을 이용한 NGS 데이터 분석)

  • Kang, Yujin;Kang, Jin;Kim, Yea Woon;Kim, AeRi
    • Journal of Life Science
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    • v.31 no.4
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    • pp.410-417
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    • 2021
  • Next-generation sequencing (NGS) is a high-throughput technique for sequencing large numbers of DNA fragments that are prepared from a genome. This sequencing technique has been used to elucidate whole genome sequences of living organisms and to analyze complementary DNA (cDNA) or chromatin immunoprecipitated DNA (ChIPed DNA) at the genome level. After NGS, the use of proper tools is important for processing and analyzing data with reasonable parameters. However, handling large-scale sequencing data and programing for data analysis can be difficult. The Galaxy platform, a public web service system, provides many different tools for NGS data analysis, and it allows researchers to analyze their data on a web browser with no deep knowledge about bioinformatics and/or programing. In this study, we explain the procedure for preparing chromatin immunoprecipitation-sequencing (ChIP-seq) libraries and steps for analyzing ChIP-seq data using the Galaxy platform. The data analysis steps include the NGS data upload to Galaxy, quality check of the NGS data, premapping processes, read mapping, the post-mapping process, peak-calling and visualization by window view, heatmaps, average profile, and correlation analysis. Analysis of our histone H3K4me1 ChIP-seq data in K562 cells shows that it correlates with public data. Thus, NGS data analysis using the Galaxy platform can provide an easy approach to bioinformatics.

Protective Effect of Physostigmine and Neostigmine against Acute Toxicity of Parathion in Rats

  • Jun, Jung-Won;Kim, Young-Chul
    • Archives of Pharmacal Research
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    • v.14 no.4
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    • pp.330-335
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    • 1991
  • The effects of physostigmine and neostigmine on the parathin induced toxicity were examined in adult female rats. Physostigmine $(100\;{\mu}g/kg,\;ip)$ or neostigmine $(200\;{\mu}g/kg,\;ip)$ inhibited acetylcholinesterase (AChE) and cholinesterase (ChE) activities in blood, brain and lung when the enzyme activity was measured 30 min after the treatment. At the doses of two carbamates equipotent on brain AChE, neostigmine showed greater inhibition on peripheral AChE/ChE. The enzyme activity returned to normal in 120 min following the carbamates except in the lung of rats treated with neostigmine. Carbamates administered 30 min prior to parathion (2 mg/kg) antagonized the inhibition of AChE/ChE by parathion when the enzyme activity was measured 2 hr following parathion. Neostigmine showed greater protective effect on peripheral AChE/ChE. The effect of either carbamate on AChE/ChE was not significant 2 hr beyond the parathion treatment. Carbamates decreased the mortality of rats challenged with a lethal dose of parathion (4 mg/kg, ip) either when treated alone or in combination with atropine (10 mg/kg, ip). Lethal action of paraoxon (1.5 mg/ks ip), the active metabolite of parathion was also decreased by the carbamate treatment indicating that the protection was not mediated by competitive inhibition of metabolic conversion of parathion to paraoxon. The results suggest that carbamylation of the active sites may not be the sole underlying mechanism of protection provided by the carbamates.

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Inference of Genetic Regulatory Modules Using ChIP-on-chip and mRNA Expression Data

  • Cho, Hye-Young;Lee, Do-Heon
    • Bioinformatics and Biosystems
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    • v.2 no.2
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    • pp.62-65
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    • 2007
  • We present here the strategy of data integration for inference of genetic regulatory modules. First, we construct all possible combinations of regulators of genes using chromatin-immunoprecipitation(ChIP)-chip data. Second, hierarchical clustering method is employed to analyze mRNA expression profiles. Third, integration method is applied to both of the data. Finally, we construct a genetic regulatory module which is involved in the function of ribosomal protein synthesis.

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A Review of Three Different Studies on Hidden Markov Models for Epigenetic Problems: A Computational Perspective

  • Lee, Kyung-Eun;Park, Hyun-Seok
    • Genomics & Informatics
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    • v.12 no.4
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    • pp.145-150
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    • 2014
  • Recent technical advances, such as chromatin immunoprecipitation combined with DNA microarrays (ChIp-chip) and chromatin immunoprecipitation-sequencing (ChIP-seq), have generated large quantities of high-throughput data. Considering that epigenomic datasets are arranged over chromosomes, their analysis must account for spatial or temporal characteristics. In that sense, simple clustering or classification methodologies are inadequate for the analysis of multi-track ChIP-chip or ChIP-seq data. Approaches that are based on hidden Markov models (HMMs) can integrate dependencies between directly adjacent measurements in the genome. Here, we review three HMM-based studies that have contributed to epigenetic research, from a computational perspective. We also give a brief tutorial on HMM modelling-targeted at bioinformaticians who are new to the field.

A ChIP-Seq Data Analysis Pipeline Based on Bioconductor Packages

  • Park, Seung-Jin;Kim, Jong-Hwan;Yoon, Byung-Ha;Kim, Seon-Young
    • Genomics & Informatics
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    • v.15 no.1
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    • pp.11-18
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    • 2017
  • Nowadays, huge volumes of chromatin immunoprecipitation-sequencing (ChIP-Seq) data are generated to increase the knowledge on DNA-protein interactions in the cell, and accordingly, many tools have been developed for ChIP-Seq analysis. Here, we provide an example of a streamlined workflow for ChIP-Seq data analysis composed of only four packages in Bioconductor: dada2, QuasR, mosaics, and ChIPseeker. 'dada2' performs trimming of the high-throughput sequencing data. 'QuasR' and 'mosaics' perform quality control and mapping of the input reads to the reference genome and peak calling, respectively. Finally, 'ChIPseeker' performs annotation and visualization of the called peaks. This workflow runs well independently of operating systems (e.g., Windows, Mac, or Linux) and processes the input fastq files into various results in one run. R code is available at github: https://github.com/ddhb/Workflow_of_Chipseq.git.

A demonstration of the H3 trimethylation ChIP-seq analysis of galline follicular mesenchymal cells and male germ cells

  • Chokeshaiusaha, Kaj;Puthier, Denis;Nguyen, Catherine;Sananmuang, Thanida
    • Asian-Australasian Journal of Animal Sciences
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    • v.31 no.6
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    • pp.791-797
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    • 2018
  • Objective: Trimethylation of histone 3 (H3) at 4th lysine N-termini (H3K4me3) in gene promoter region was the universal marker of active genes specific to cell lineage. On the contrary, coexistence of trimethylation at 27th lysine (H3K27me3) in the same loci-the bivalent H3K4m3/H3K27me3 was known to suspend the gene transcription in germ cells, and could also be inherited to the developed stem cell. In galline species, throughout example of H3K4m3 and H3K27me3 ChIP-seq analysis was still not provided. We therefore designed and demonstrated such procedures using ChIP-seq and mRNA-seq data of chicken follicular mesenchymal cells and male germ cells. Methods: Analytical workflow was designed and provided in this study. ChIP-seq and RNA-seq datasets of follicular mesenchymal cells and male germ cells were acquired and properly preprocessed. Peak calling by Model-based analysis of ChIP-seq 2 was performed to identify H3K4m3 or H3K27me3 enriched regions ($Fold-change{\geq}2$, $FDR{\leq}0.01$) in gene promoter regions. Integrative genomics viewer was utilized for cellular retinoic acid binding protein 1 (CRABP1), growth differentiation factor 10 (GDF10), and gremlin 1 (GREM1) gene explorations. Results: The acquired results indicated that follicular mesenchymal cells and germ cells shared several unique gene promoter regions enriched with H3K4me3 (5,704 peaks) and also unique regions of bivalent H3K4m3/H3K27me3 shared between all cell types and germ cells (1,909 peaks). Subsequent observation of follicular mesenchyme-specific genes-CRABP1, GDF10, and GREM1 correctly revealed vigorous transcriptions of these genes in follicular mesenchymal cells. As expected, bivalent H3K4m3/H3K27me3 pattern was manifested in gene promoter regions of germ cells, and thus suspended their transcriptions. Conclusion: According the results, an example of chicken H3K4m3/H3K27me3 ChIP-seq data analysis was successfully demonstrated in this study. Hopefully, the provided methodology should hereby be useful for galline ChIP-seq data analysis in the future.

Isolation of Putative in vivo Hoxc8 Downstream Target Genes Using ChIP-Cloning Method

  • Chung, Hyun-Joo;Kang, Myeng-Mo;Kim, Myoung-Hee
    • Biomedical Science Letters
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    • v.14 no.1
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    • pp.47-53
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    • 2008
  • Hox genes are known to be transcription factors controlling vertebrate pattern formation along the anteroposterior body axis by regulating many target gene expressions during vertebrate embryogenesis. In order to isolate in vivo Hox responsive target genes, ChIP-cloning technique has been applied using Hoxc8 antibody. Here murine embryo of day 11.5 post coitum (E11.5) highly expressing Hoxc8 gene was used after removing head and tail portions where Hoxc8 is rarely expressing. After fixation with formaldehyde, the chromatin DNAs harboring bound proteins were isolated. After sonication, about 0.5- to 1 Kb chromatin DNAs were immunoprecipitated with anti Hoxc8 antibody. After removing the bound proteins with proteinase K, DNAs were isolated, cloned into the pBluescsript II SK vector, and then sequenced. Total 33 random clones sequenced were anlalyzed to be located at 12 different genomic regions. Among these, 8 turned out to be introns and 4 were intergenic regions localized in random chromosomes. The base composition of total cloned genomic sequences (6608 bp) were AT-rich, i.e., 40% GC. When the Hoxc8 core binding sites, such as TAAT, ATTA, TTAT, and ATAA were analyzed total number of 55, 45, 54, and 55 were found, respectively, which are than twice as many as expected number of 26. Although this in silico analysis does not mean that the ChIP-cloned sequence is real Hoxc8 regulatory element in vivo, these results strongly imply that the DNA fragments cloned through chromatin immunoprecipitation could be very much likely the putative Hoxc8 downstream target genes.

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Comparative analysis of commonly used peak calling programs for ChIP-Seq analysis

  • Jeon, Hyeongrin;Lee, Hyunji;Kang, Byunghee;Jang, Insoon;Roh, Tae-Young
    • Genomics & Informatics
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    • v.18 no.4
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    • pp.42.1-42.9
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    • 2020
  • Chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-Seq) is a powerful technology to profile the location of proteins of interest on a whole-genome scale. To identify the enrichment location of proteins, many programs and algorithms have been proposed. However, none of the commonly used peak calling programs could accurately explain the binding features of target proteins detected by ChIP-Seq. Here, publicly available data on 12 histone modifications, including H3K4ac/me1/me2/me3, H3K9ac/me3, H3K27ac/me3, H3K36me3, H3K56ac, and H3K79me1/me2, generated from a human embryonic stem cell line (H1), were profiled with five peak callers (CisGenome, MACS1, MACS2, PeakSeq, and SISSRs). The performance of the peak calling programs was compared in terms of reproducibility between replicates, examination of enriched regions to variable sequencing depths, the specificity-to-noise signal, and sensitivity of peak prediction. There were no major differences among peak callers when analyzing point source histone modifications. The peak calling results from histone modifications with low fidelity, such as H3K4ac, H3K56ac, and H3K79me1/me2, showed low performance in all parameters, which indicates that their peak positions might not be located accurately. Our comparative results could provide a helpful guide to choose a suitable peak calling program for specific histone modifications.

Analysis of H3K4me3-ChIP-Seq and RNA-Seq data to understand the putative role of miRNAs and their target genes in breast cancer cell lines

  • Kotipalli, Aneesh;Banerjee, Ruma;Kasibhatla, Sunitha Manjari;Joshi, Rajendra
    • Genomics & Informatics
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    • v.19 no.2
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    • pp.17.1-17.13
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    • 2021
  • Breast cancer is one of the leading causes of cancer in women all over the world and accounts for ~25% of newly observed cancers in women. Epigenetic modifications influence differential expression of genes through non-coding RNA and play a crucial role in cancer regulation. In the present study, epigenetic regulation of gene expression by in-silico analysis of histone modifications using chromatin immunoprecipitation sequencing (ChIP-Seq) has been carried out. Histone modification data of H3K4me3 from one normal-like and four breast cancer cell lines were used to predict miRNA expression at the promoter level. Predicted miRNA promoters (based on ChIP-Seq) were used as a probe to identify gene targets. Five triple-negative breast cancer (TNBC)-specific miRNAs (miR153-1, miR4767, miR4487, miR6720, and miR-LET7I) were identified and corresponding 13 gene targets were predicted. Eight miRNA promoter peaks were predicted to be differentially expressed in at least three breast cancer cell lines (miR4512, miR6791, miR330, miR3180-3, miR6080, miR5787, miR6733, and miR3613). A total of 44 gene targets were identified based on the 3'-untranslated regions of downregulated mRNA genes that contain putative binding targets to these eight miRNAs. These include 17 and 15 genes in luminal-A type and TNBC respectively, that have been reported to be associated with breast cancer regulation. Of the remaining 12 genes, seven (A4GALT, C2ORF74, HRCT1, ZC4H2, ZNF512, ZNF655, and ZNF608) show similar relative expression profiles in large patient samples and other breast cancer cell lines thereby giving insight into predicted role of H3K4me3 mediated gene regulation via the miRNA-mRNA axis.