Welcome to ChromOS
NGS Samples
Tissues (Cells)
Registered Users
ChromOS services online access to the data resources from Chromosome Orchestration System (OS) , a research project supported by MEXT Japan.
Chromosomes play a fundamental role in many biological processes. Previous research efforts have advanced our understanding of specific chromosomal events, such as DNA transcription, replication, recombination, partitioning, and epigenetic modification. One of the major future challenges in chromosome biology will be to provide an overall framework of how these individual activities are orchestrated and coordinated to maximize their effects in a variety of biological processes that evolve over time. The main goal of this project is to describe the mechanisms that regulate the functional unity of the chromosomes (chromosome OS) by thoroughly examining the structural relationship between, and the hierarchy of, individual chromosomal functions.
| Accession | Cell | Organism | Restriction enzyme | Condition | Run ID |
|---|---|---|---|---|---|
| OLP-2-620 | RPE | human | MboI | ESCO1, 2 KD (siRNA transfection 48 h), No Sync | 1809JNHX-0004_si11-19_res |
| OLP-2-614 | RPE | human | MboI | RAD21 KD (siRNA transfection 72 h), No Sync | 1809JNHX-0003_si621_res |
| OLP-2-628 | RPE | human | MboI | PDS5B KD (siRNA transfection 48 h), No Sync | HN00102383_si91_res |
| OLP-2-621 | RPE | human | MboI | MAU2 KD (siRNA transfection 72 h), No Sync | 1809JNHX-0004_si251_res |
| OLP-2-613 | RPE | human | MboI | RAD21 KD (siRNA transfection 72 h), No Sync | 1809JNHX-0003_si7-621_res |
| OLP-2-623 | RPE | human | MboI | CTCF KD (siRNA transfection 72 h), No Sync | 1811KHX-0110_R_626_628_d3_res |
| OLP-2-624 | RPE | human | MboI | WAPL KD (siRNA transfection 48 h), No Sync | HN00102380_si31_res |
| OLP-2-625 | RPE | human | MboI | PDS5A KD (siRNA transfection 72 h), No Sync | HN00102380_si88_d3_res |
| OLP-2-619 | RPE | human | MboI | ESCO1 KD (siRNA transfection 48 h), No Sync | 1809JNHX-0004_si11_res |
| OLP-2-626 | RPE | human | MboI | JQ1 (BRD Inhibitor), No Sync | HN00102383_JQ1_plus_res |
| OLP-2-615 | RPE | human | MboI | Control, No Sync | 1807JNHX-0018_Ctrl_res |
| OLP-2-627 | RPE | human | MboI | PDS5A,B KD (siRNA transfection 48 h), No Sync | HN00102383_si88_91_res |
| OLP-2-616 | RPE | human | MboI | Control, No Sync | 1809JNHX-0003_Ctrl_res |
| OLP-2-618 | RPE | human | MboI | CTCF KD (siRNA transfection 72 h), No Sync | 1811KHX-0109_FT_WT_res |
| OLP-2-617 | RPE | human | MboI | CTCF KD (siRNA transfection 72 h), No Sync | 1809JNHX-0003_si628_res |
| OLP-2-622 | RPE | human | MboI | Control, No Sync | 1811KHX-0109_R_Ctrl_res |
| OLP-2-629 | LCL | human | MboI | WT, No Sync | 1904JNHX-0009_GIA_res |
| OLP-2-630 | LCL | human | MboI | HP1beta mutation, No Sync | 1904JNHX-0009_RIM_res |
| OLP-2-631 | HCT116/Rad21-mAD/TIR1 | human | MboI | NIPBL, exon3 frame-shift, No Sync | 1903JNHX-0034_B3_res |
| OLP-2-633 | HCT116/ESCO1-mAD/TIR1 | human | MboI | Dox 12 h -> IAA 3 h (ESCO1 depletion), No Sync | 1907JNHX-0026_E1_dox_iaa_res |
| OLP-2-632 | HCT116/ESCO1-mAD/TIR1 | human | MboI | Dox 16 h -> (control), No Sync | 1908JNHX-0025_E1_dox_res |
| OLP-2-634 | HCT116 | human | MboI | NIPBL, exon 3 single allele mutation, No sync | 1807JNHX-0018_HCT_3-3_res |
| OLP-2-635 | HCT116 | human | MboI | Wild Type, No Sync | 1807JNHX-0018_HCT_Wt_res |
| OLP-2-641 | fibroblast | human | MboI | WT, female, No Sync | 1807JNHX-0018_GM2036_res |
| OLP-2-640 | fibroblast | human | MboI | WT, female, No Sync | 1904JNHX-0009_2036_res |
| OLP-2-639 | fibroblast | human | MboI | CdLS, NIPBL:2479_2480delAG; R827GfsX2, No Sync | 1807JNHX-0018_CdLS304_res |
| OLP-2-636 | fibroblast | human | MboI | CdLS, NIPBL: 1372C>T;Q458X / Nonsense, female, No Sync | 1807JNHX-0018_CdLS510_res |
| OLP-2-642 | fibroblast | human | MboI | WT, male, No Sync | 1807JNHX-0018_GM3348_res |
| OLP-2-638 | fibroblast | human | MboI | CdLS, NIPBL:2479_2480delAG; R827GfsX2, No Sync | 1807JNHX-0018_CdLS087_res |
| OLP-2-637 | fibroblast | human | MboI | WT, male, No Sync | 1807JNHX-0018_CdLS006_res |
| OLP-2-643 | Blood Cell Stem Cell | mouse | MboI | STAG2 conditional KO | 1811KHX-0110_KO_561_res |
| OLP-2-646 | Blood Cell Stem Cell | mouse | MboI | STAG2 conditional KO | 1811KHX-0110_KO_544_res |
| OLP-2-645 | Blood Cell Stem Cell | mouse | MboI | WT | 1811KHX-0110_WT_546_res |
| OLP-2-644 | Blood Cell Stem Cell | mouse | MboI | WT | 1811KHX-0110_WT_563_res |
| OLP-2-654 | 293FT | human | MboI | WT, No Sync | 1905JNHX-0006_FT_res |
| OLP-2-648 | 293FT | human | MboI | lentiviral vector Infection, Control, No Sync | 1903JNHX-0034_FT-vi24_res |
| OLP-2-649 | 293FT | human | MboI | lentiviral vector Infection, Control, No Sync | 1903JNHX-0035_FT-Wt_res |
| OLP-2-651 | 293FT | human | MboI | lentiviral vector Infection, Control, No Sync | 1908JNHX-0026_vi24_res |
| OLP-2-652 | 293FT | human | MboI | Wild AFF4 lentiviral vector Infection, No Sync | 1908JNHX-0026_vi27_res |
| OLP-2-647 | 293FT | human | MboI | Mutant AFF4 lentiviral vector Infection, No Sync | 1903JNHX-0035_FT-vi28_res |
| OLP-2-653 | 293FT | human | MboI | Mutant AFF4 lentiviral vector Infection, No Sync | 1908JNHX-0026_vi28_res |
| OLP-2-650 | 293FT | human | MboI | NIPBL, exon 3 bi-allele mutation, No Sync | 1811KHX-0109_FT_ND1_res |
- ChromOS manages the data from the project "Chromosome OS".
- ChromOS provides the analytic pipeline for Hi-C data by collaborating with OpenLooper (OLP).
- Registration via OpenLooper is required. Thereby, users can manage the data and submit jobs to analyze. Learn more..
- Anyone can freely access the data opened by the registered users.
To reduce BAM filesize, prepare one chromosome per BAM.
"Samtools view" command will be helpful to do it.
Data Sharing (OpenLooper)
OpenLooper (OLP) collects genome-wide data on chromatin structures investigated by various high-throughput experimental assays. Simultaneously, OLP provides a platform that supports opening and sharing the data.
Hi-C Analysis
ChromOS runs a pipeline for Hi-C data analysis with user-uploaded BAM files via OpenLooper.
This pipeline is now in service (2020.06).
Example: [OLP-1-608]
HiC collection: [RPE, HCT116, LCL,...]
In Focus Articles (last modified: 2021-01-22 08:23:52)
The Nucleome Data Bank: web-based resources to simulate and analyze the three-dimensional genome.Contessoto VG, Cheng RR, Hajitaheri A, Dodero-Rojas E, Mello MF, Lieberman-Aiden E, Wolynes PG, Di Pierro M, Onuchic JN (Nucleic Acids Res. 2021 01 08;49(D1):D172-D182) We introduce the Nucleome Data Bank (NDB), a web-based platform to simulate and analyze the three-dimensional (3D) organization of genomes. The NDB enables physics-based simulation of chromosomal structural dynamics through the MEGABASE + MiChroM computational pipeline. The input of the pipeline consists of epigenetic information sourced from the Encode database; the output consists of the trajectories of chromosomal motions that accurately predict Hi-C and fluorescence insitu hybridization data, as well as multiple observations of chromosomal dynamics in vivo. As an intermediate step, users can also generate chromosomal sub-compartment annotations directly from the same epigenetic input, without the use of any DNA-DNA proximity ligation data. Additionally, the NDB freely hosts both experimental and computational structural genomics data. Besides being able to perform their own genome simulations and download the hosted data, users can also analyze and visualize the same data through custom-designed web-based tools. In particular, the one-dimensional genetic and epigenetic data can be overlaid onto accurate 3D structures of chromosomes, to study the spatial distribution of genetic...... |
| PubMed:33021634 |
The DLO Hi-C Tool for Digestion-Ligation-Only Hi-C Chromosome Conformation Capture Data Analysis.Hong P, Jiang H, Xu W, Lin D, Xu Q, Cao G, Li G (Genes (Basel). 2020 03 10;11(3):) It is becoming increasingly important to understand the mechanism of regulatory elements on target genes in long-range genomic distance. 3C (chromosome conformation capture) and its derived methods are now widely applied to investigate three-dimensional (3D) genome organizations and gene regulation. Digestion-ligation-only Hi-C (DLO Hi-C) is a new technology with high efficiency and cost-effectiveness for whole-genome chromosome conformation capture. Here, we introduce the DLO Hi-C tool, a flexible and versatile pipeline for processing DLO Hi-C data from raw sequencing reads to normalized contact maps and for providing quality controls for different steps. It includes more efficient iterative mapping and linker filtering. We applied the DLO Hi-C tool to different DLO Hi-C datasets and demonstrated its ability in processing large data with multithreading. The DLO Hi-C tool is suitable for processing DLO Hi-C and in situ DLO Hi-C datasets. It is convenient and efficient for DLO Hi-C data processing.... |
| PubMed:32164155 |
Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles.Tao H, Li H, Xu K, Hong H, Jiang S, Du G, Wang J, Sun Y, Huang X, Ding Y, Li F, Zheng X, Chen H, Bo X (Brief Bioinform. 2021 Jan 18;:) The exploration of three-dimensional chromatin interaction and organization provides insight into mechanisms underlying gene regulation, cell differentiation and disease development. Advances in chromosome conformation capture technologies, such as high-throughput chromosome conformation capture (Hi-C) and chromatin interaction analysis by paired-end tag (ChIA-PET), have enabled the exploration of chromatin interaction and organization. However, high-resolution Hi-C and ChIA-PET data are only available for a limited number of cell lines, and their acquisition is costly, time consuming, laborious and affected by theoretical limitations. Increasing evidence shows that DNA sequence and epigenomic features are informative predictors of regulatory interaction and chromatin architecture. Based on these features, numerous computational methods have been developed for the prediction of chromatin interaction and organization, whereas they are not extensively applied in biomedical study. A systematical study to summarize and evaluate such methods is still needed to facilitate their application. Here, we summarize 48 computational methods for the prediction of chromatin interaction and organi...... |
| PubMed:33454752 |
A chromosome-level genome assembly provides new insights into paternal genome elimination in the cotton mealybug Phenacoccus solenopsis.Li M, Tong H, Wang S, Ye W, Li Z, Omar MAA, Ao Y, Ding S, Li Z, Wang Y, Yin C, Zhao X, He K, Liu F, Chen X, Mei Y, Walters JR, Jiang M, Li F (Mol Ecol Resour. 2020 Nov;20(6):1733-1747) Mealybugs (Hemiptera: Pseudococcidae) are economically important agricultural pests with several compelling biological phenomena including paternal genome elimination (PGE). However, limited high-quality genome assemblies of mealybugs hinder a full understanding of this striking and unusual biological phenomenon. Here, we generated a chromosome-level genome assembly of cotton mealybug, Phenacoccus solenopsis, by combining Illumina short reads, PacBio long reads and Hi-C scaffolding. The assembled genome was 292.54 Mb with a contig N50 of 489.8 kb and a scaffold N50 of 49.0 Mb. Hi-C scaffolding assigned 84.42% of the bases to five chromosomes. A total of 110.75 Mb (37.9%) repeat sequences and 11,880 protein-coding genes were predicted. The completeness of the genome assembly was estimated to be 95.5% based on BUSCO genes. In addition, 27,086 (95.3%) full-length PacBio transcripts were uniquely mapped to the assembled scaffolds, suggesting the high quality of the genome assembly. We showed that cotton mealybugs lack differentiated sex chromosomes by analysing genome resequencing data of males and females. DAPI staining confirmed that one chromosome set in males becomes heterochro...... |
| PubMed:33460249 |
SPIN reveals genome-wide landscape of nuclear compartmentalization.Wang Y, Zhang Y, Zhang R, van Schaik T, Zhang L, Sasaki T, Peric-Hupkes D, Chen Y, Gilbert DM, van Steensel B, Belmont AS, Ma J (Genome Biol. 2021 Jan 14;22(1):36) We report SPIN, an integrative computational method to reveal genome-wide intranuclear chromosome positioning and nuclear compartmentalization relative to multiple nuclear structures, which are pivotal for modulating genome function. As a proof-of-principle, we use SPIN to integrate nuclear compartment mapping (TSA-seq and DamID) and chromatin interaction data (Hi-C) from K562 cells to identify 10 spatial compartmentalization states genome-wide relative to nuclear speckles, lamina, and putative associations with nucleoli. These SPIN states show novel patterns of genome spatial organization and their relation to other 3D genome features and genome function (transcription and replication timing). SPIN provides critical insights into nuclear spatial and functional compartmentalization.... |
| PubMed:33446254 |