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Improving fibroblast characterization using single-cell RNA sequencing: an optimized tissue disaggregation and data processing pipeline

ABSTRACT: Improving fibroblast characterization using single-cell RNA sequencing: an optimized tissue disaggregation and data processing pipeline

PROVIDER: PRJNA521040 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR8532670.fastq.gz	Fastqsanger.gz
	SRR8532661.fastq.gz	Fastqsanger.gz
	SRR8532671.fastq.gz	Fastqsanger.gz
	SRR8532662.fastq.gz	Fastqsanger.gz
	SRR8532672.fastq.gz	Fastqsanger.gz

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Improving fibroblast characterization using single-cell RNA sequencing: an optimized tissue disaggregation and data processing pipeline

Project description:Single-cell RNA sequencing (scRNA-Seq) provides a valuable platform for characterising multicellular ecosystems. Fibroblasts are a heterogeneous cell type involved in many physiological and pathological processes, but remain poorly-characterised. Analysis of fibroblasts is challenging: these cells are difficult to isolate from tissues, and are therefore commonly under-represented in scRNA-seq datasets. Here, we describe an optimised approach for fibroblast isolation from human lung tissues. We demonstrate the potential for this procedure in characterising stromal cell phenotypes using scRNA-Seq, analyse the effect of tissue disaggregation on gene expression, and optimise data processing to improve clustering quality. We also assess the impact of in vitro culture conditions on stromal cell gene expression and proliferation, showing that altering these conditions can skew phenotypes.

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Project description:HiCUP is a pipeline for processing sequence data generated by Hi-C, a technique used to investigate the three-dimensional organisation of a genome. The pipeline maps data to a specified reference genome and removes artefacts that would otherwise hinder subsequent analysis. HiCUP also provides an easy-to-interpret yet detailed quality control report that may be used by researchers to refine their experimental protocol for future studies. The software is freely available and has already been used for processing Hi-C data in several recently published peer-reviewed research articles. This experiment investigates the impact of using HiCUP to remove putative PCR amplification products in heavily duplicated Capture Hi-C libraries. Examination of three Capture Hi-C libraries

2015-10-29 | E-GEOD-73204 | biostudies-arrayexpress

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An optimized microRNA scaffold increases shRNA processing and target knockdown

Project description:Two shRNAs were placed into expression vectors harboring mir30 microRNA scaffold and an optimized scaffold where the artificial restriction sights in mir30 have been removed. After infection and selection shRNA processing was assessed by small-RNA cloning. For both shRNAs, placement into the optimized scaffold resulted in a ~two-fold increase in processing (based on smallRNA levels). Purpose: Others have reported that the EcoRI site that was introduced to the mir30 scaffold results in decreased smallRNA processing and hence reduced target knockdown. We've developed an alternative scaffold (termed ultramir) where this site is removed. smallRNA cloning was used to determine if the movement of this sight resulted in an increase in shRNA processing. Method: Two shRNAs (one targeting Renilla Luciferase and one targeting Human RPA3) were cloned into the original mir30 cassette the ultramir cassette. Each of the 4 constructs were infected in duplicate at single copy into cells and the cells seltected unitil infection percentages reached >90% (the shRenilla hairpin was infected into HEK293T cells and the shRPA3 construts into the Gallus gallus cell line ERC. After selection smallRNA cloning was perfromed and the amount of smallRNAs corrresponding to the two shRNAs compared to the endogenous microRNA populatlon. Results: smallRNA levels of the two shRNAs doubled relative to the microRNA population when they were placed into the ultramir scaffold.

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