Quantitative proteomics for dcas9 captured proteins
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ABSTRACT: Quantitative proteomics analysis for dcas9 captured locus specific binding proteins with K562 cell line. The locus includes "HBB, HBG, HBD and the enhancer regions" .
Project description:K562 cell line treated with 1,6-HD and proteins were captured via cross-linking. We quantified chromatin structure changes and chromatin binding proteins in K562 cell before and after 1,6-hexanediol treatment by Hi-C and Hi-MS, respectively.
Project description:K562 cell line treated with 2,5-HD and proteins were captured via cross-linking. We quantified chromatin structure changes and chromatin binding proteins in K562 cell before and after 2,5-hexanediol treatment by Hi-C and Hi-MS, respectively.
Project description:The CDKN2A/B locus at 9p21.3 contains crucial tumor suppressors (P16, P14, and P15) and oncogenic lncRNA ANRIL genes. This locus is most frequently inactivated in cancer genomes by deletion and DNA methylation. However, the mechanisms coordinately regulating their expression level are far from clear. In the present study, a novel lncRNA, P14AS, was characterized in the antisense strand of the fragment near CDKN2A in human cell lines using CDKN2A-specific probe captured RNA-sequencing (RNACap-Seq).
Project description:we performed lentiviral CRISPR interference (CRISPRi) by recruiting dCas9 fused with the KRAB domain to the CSMD1 enhancer (fam3) in the neuronal precursor cell line – Lund human mesencephalic (LUHMES). Given that the expression of CSMD1 was not detectable in LUHMES cells we differentiated these cells into neurons. Differentiated neurons with CRISPRi of CSMD1 enhancer showed significantly higher expression of CSMD1 than control.
Project description:Transcriptional enhancers orchestrate cell-type specific gene expression programs critical to eukaryotic development, physiology, and disease. However, despite the large number of enhancers now identified, only a small number have been functionally assessed. Here, we develop MOsaic Single-cell Analysis by Indexed CRISPR Sequencing (Mosaic-seq), a method that measures one direct phenotype of enhancer repression: change of the transcriptome, at the single cell level. Using dCas9-KRAB to suppress enhancer function, we first implement a multiplexed system to allow the simultaneous measurement of the transcriptome and detection of sgRNAs by single cell RNA sequencing. We validate this approach by targeting the HS2 enhancer in the well-studied beta-globin locus. Next, through computational simulation, we demonstrate strategies to robustly detect changes in gene expression in these single cell measurements. Finally, we use Mosaic-seq to target 71 hypersensitive regions belonging to 15 super-enhancers in K562 cells by utilizing a lentiviral library containing 241 unique-barcoded sgRNAs. Our results demonstrate that Mosaic-seq is a reliable approach to study enhancer function in single cells in a high-throughput manner.
Project description:Transcriptional enhancers orchestrate cell-type specific gene expression programs critical to eukaryotic development, physiology, and disease. However, despite the large number of enhancers now identified, only a small number have been functionally assessed. Here, we develop MOsaic Single-cell Analysis by Indexed CRISPR Sequencing (Mosaic-seq), a method that measures one direct phenotype of enhancer repression: change of the transcriptome, at the single cell level. Using dCas9-KRAB to suppress enhancer function, we first implement a multiplexed system to allow the simultaneous measurement of the transcriptome and detection of sgRNAs by single cell RNA sequencing. We validate this approach by targeting the HS2 enhancer in the well-studied beta-globin locus. Next, through computational simulation, we demonstrate strategies to robustly detect changes in gene expression in these single cell measurements. Finally, we use Mosaic-seq to target 71 hypersensitive regions belonging to 15 super-enhancers in K562 cells by utilizing a lentiviral library containing 241 unique-barcoded sgRNAs. Our results demonstrate that Mosaic-seq is a reliable approach to study enhancer function in single cells in a high-throughput manner.
Project description:Transcriptional enhancers orchestrate cell-type specific gene expression programs critical to eukaryotic development, physiology, and disease. However, despite the large number of enhancers now identified, only a small number have been functionally assessed. Here, we develop MOsaic Single-cell Analysis by Indexed CRISPR Sequencing (Mosaic-seq), a method that measures one direct phenotype of enhancer repression: change of the transcriptome, at the single cell level. Using dCas9-KRAB to suppress enhancer function, we first implement a multiplexed system to allow the simultaneous measurement of the transcriptome and detection of sgRNAs by single cell RNA sequencing. We validate this approach by targeting the HS2 enhancer in the well-studied beta-globin locus. Next, through computational simulation, we demonstrate strategies to robustly detect changes in gene expression in these single cell measurements. Finally, we use Mosaic-seq to target 71 hypersensitive regions belonging to 15 super-enhancers in K562 cells by utilizing a lentiviral library containing 241 unique-barcoded sgRNAs. Our results demonstrate that Mosaic-seq is a reliable approach to study enhancer function in single cells in a high-throughput manner.
Project description:Transcriptional enhancers orchestrate cell-type specific gene expression programs critical to eukaryotic development, physiology, and disease. However, despite the large number of enhancers now identified, only a small number have been functionally assessed. Here, we develop MOsaic Single-cell Analysis by Indexed CRISPR Sequencing (Mosaic-seq), a method that measures one direct phenotype of enhancer repression: change of the transcriptome, at the single cell level. Using dCas9-KRAB to suppress enhancer function, we first implement a multiplexed system to allow the simultaneous measurement of the transcriptome and detection of sgRNAs by single cell RNA sequencing. We validate this approach by targeting the HS2 enhancer in the well-studied beta-globin locus. Next, through computational simulation, we demonstrate strategies to robustly detect changes in gene expression in these single cell measurements. Finally, we use Mosaic-seq to target 71 hypersensitive regions belonging to 15 super-enhancers in K562 cells by utilizing a lentiviral library containing 241 unique-barcoded sgRNAs. Our results demonstrate that Mosaic-seq is a reliable approach to study enhancer function in single cells in a high-throughput manner.