Chrom-Lasso：A lasso regression-based model to detect functional chromatin interactions using Hi-C data
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ABSTRACT:
PROVIDER: PRJNA665037 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12693617_1.fastq.gz | Fastqsanger.gz | |||
| SRR12693617_2.fastq.gz | Fastqsanger.gz | |||
| SRR12693618_1.fastq.gz | Fastqsanger.gz | |||
| SRR12693618_2.fastq.gz | Fastqsanger.gz | |||
| SRR12693619_1.fastq.gz | Fastqsanger.gz |
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Project description:We present Chrom-Lasso, an algorithm to identify chromatin interactions from Hi-C data, which performs better in identifying functional chromatin interactions that regulates gene expression when comparing with other methods. To futher assess its performance in investigating biological questions and its ability to deal with noisy data, we use an in vitro mouse CD8+ T cell activation model to generate Hi-C data and RNA-seq data at 4 status(Tn, Teff1, Teff2, Tex) during the process of activation, and we sort T cells at different status by gating criteria as follows: Tn(CD8+, CD44-, CD62L+, at day0), Teff1(CD8+, PD-1+, TIM-3-, at day2), Teff2(CD8+, PD-1+, TIM-3-, at day5), and Tex(CD8+, PD-1+, TIM-3+, at day5), for each status, we prepare 1 Hi-C library following the in situ Hi-C prorocol, and we also prepare 3 RNA-seq libraries from 3 times of parallel experiments. Since functional interactions influence the downstream gene expression level, so the relevance between interactions detected by Chrom-Lasso and gene expression would be powerful evidence proving the capability of Chrom-Lasso in detecting functional interactions.
2020-11-30 | GSE158375 | GEO
Project description:Hi-C is a genome-wide assay based on Chromosome Conformation Capture and high-throughput sequencing to decipher 3D chromatin organization in the nucleus. However, computational methods to detect functional interactions utilizing Hi-C data face challenges including the correction for various sources of biases and the identification of functional interactions with low counts of interacting fragments. We present Chrom-Lasso, a lasso linear regression model that removes complex biases assumption-free and identifies functional interacting loci with increased power by combining information of local reads distribution surrounding the area of interest. We showed that interacting regions identified by Chrom-Lasso are more enriched for 5C validated interactions and functional GWAS hits than that of GOTHiC and Fit-Hi-C. To further demonstrate the ability of Chrom-Lasso to detect interactions of functional importance, we performed time-series Hi-C and RNA-seq during T cell activation and exhaustion. We showed that the dynamic changes in gene expression and chromatin interactions identified by Chrom-Lasso were largely concordant with each other. Finally, we experimentally confirmed Chrom-Lasso's finding that Erbb3 was co-regulated with distinct neighboring genes at different states during T cell activation. Our results highlight Chrom-Lasso's utility in detecting weak functional interaction between cis-regulatory elements, such as promoters and enhancers.
| S-EPMC8574949 | biostudies-literature
Project description:Chromatin marks are associated with transcriptional regulatory activities. Here, We developed a method termed Chrom-seq to efficiently capture RNAs associated with various chromatin marks in living cells. Chrom-seq jointly applies highly specific chromatin-mark reader with APEX2 which catalyzes the oxidation of biotin-aniline to label the adjacent RNAs for isolation by streptavidin-coated beads. Using the readers of mCBX7/dPC, mCBX1 and mTAF3, we detected RNA species significantly associated with H3K27me3, H3K9me3 and H3K4me3, respectively. Chrom-seq provides an antibody-free approach to systematically map RNAs at chromatin marks with potential regulatory roles in different epigenetic events.
2024-07-31 | GSE244454 | GEO
Project description:Chrom-seq Identifies RNAs at Chromatin Marks [Chrom-seq]
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Project description:Chromatin marks are associated with transcriptional regulatory activities. Here, We developed a method termed Chrom-seq to efficiently capture RNAs associated with various chromatin marks in living cells. Chrom-seq jointly applies highly specific chromatin-mark reader with APEX2 which catalyzes the oxidation of biotin-aniline to label the adjacent RNAs for isolation by streptavidin-coated beads. Using the readers of mCBX7/dPC, mCBX1 and mTAF3, we detected RNA species significantly associated with H3K27me3, H3K9me3 and H3K4me3, respectively. Chrom-seq provides an antibody-free approach to systematically map RNAs at chromatin marks with potential regulatory roles in different epigenetic events.
2024-07-31 | GSE252807 | GEO
Project description:Chromatin marks are associated with transcriptional regulatory activities. Here, We developed a method termed Chrom-seq to efficiently capture RNAs associated with various chromatin marks in living cells. Chrom-seq jointly applies highly specific chromatin-mark reader with APEX2 which catalyzes the oxidation of biotin-aniline to label the adjacent RNAs for isolation by streptavidin-coated beads. Using the readers of mCBX7/dPC, mCBX1 and mTAF3, we detected RNA species significantly associated with H3K27me3, H3K9me3 and H3K4me3, respectively. Chrom-seq provides an antibody-free approach to systematically map RNAs at chromatin marks with potential regulatory roles in different epigenetic events.
2024-07-31 | GSE252808 | GEO
Project description:The genome-wide chromosome conformation capture method, Hi-C, has greatly advanced our understanding of genome organization. However, its quantitative properties, including sensitivity, bias, and linearity, remain challenging to assess. Measuring these properties in vivo is difficult due to the heterogenous and dynamic nature of chromosomal interactions. Here, using Chemically Induced Chromosomal Interaction (CICI) method, we create stable intra- and inter-chromosomal interactions in G1-phase budding yeast across a broad range of contact frequencies. Hi-C analysis of these engineered cell populations demonstrates that static intra-chromosomal loops do not generate Topologically Associated Domains (TADs) and only promote 3D proximity within ~50kb flanking regions. At moderate sequencing depth, Hi-C is sensitive enough to detect interactions occurring in a few percent of cells. It also shows no inherent bias toward intra- versus inter-chromosomal interactions. Furthermore, we observe a linear relationship between Hi-C signal intensity and contact frequency. These findings illuminate the intrinsic properties of the Hi-C assay and provide a robust framework for its calibration.
2024-12-11 | GSE283767 | GEO
Project description:Chrom-seq Identifies RNAs at Chromatin Marks
| PRJNA1062744 | ENA
Project description:First we developed a new, simple, and robust assay called CoP (Column Purified chromatin) for profiling of accessible regions by directly purifying fragmentized crosslinked chromatin with DNA purification column. The CoP chromatin regions by CoP-seq are consistent with the accessible regions detected by ATAC-seq and FARIE-seq. Then we integrated CoP-seq and Hi-C technique (Hi-CoP) for interactions of accessible chromatin regions which represent active cis-regulatory elements in cells. Our data showed that Hi-CoP assay can robustly detect interactions of regulatory regions.
2020-01-29 | GSE144412 | GEO
Project description:Chromatin organisation of trophoblast stem cells (TSC) were compared with that of embryonic stem cells (ESC). The method enriches Hi-C libraries, to detect promoter interactions at restriction fragment level. We prepared Hi-C libraries from TSC and ESC (serum grown) samples and enriched them with a promoter capture bait system that captures ~22.000 promoters. Promoter interactions were then analysed using the GOTHiC pipeline.
2018-09-05 | E-MTAB-6585 | biostudies-arrayexpress