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Predicting drivers of proximal tubule cell state through regularized regression analysis of single cell multiomic sequencing

ABSTRACT: Predicting drivers of proximal tubule cell state through regularized regression analysis of single cell multiomic sequencing

PROVIDER: PRJNA909264 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR22549035_1.fastq.gz	Fastqsanger.gz
	SRR22549035_2.fastq.gz	Fastqsanger.gz
	SRR22549036_1.fastq.gz	Fastqsanger.gz
	SRR22549036_2.fastq.gz	Fastqsanger.gz
	SRR22549037_1.fastq.gz	Fastqsanger.gz

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Project description:In this study, we generated a single nucleus multiomic (snRNA-seq and snATAC-seq) dataset of adult human kidney. We developed a bioinformatic tool to analyze this dataset by identifying key cis-regulatory elements and transcription factors associated with specific cell types and states. We applied this tool to identify transcription factors implicated in proximal tubule cell injury and failed repair states. We demonstrate this tool can be applied to single cell multiomic datasets to derive insight into cell type- and state-specific gene regulatory networks.

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Predicting proximal tubule failed repair drivers through regularized regression analysis of single cell multiomic sequencing

Project description:This SuperSeries is composed of the SubSeries listed below.

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Profiling of Transcripts in Rat Proximal Tubule

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Transcriptomes of Major Proximal-Tubule Cell-Culture Models

Project description:Purpose:Cultured cell lines are widely used for research in the physiology, pathophysiology, toxicology and pharmacology of the renal proximal tubule. The lines that are most appropriate for a given use depend on the genes expressed.We have used modern RNA-sequencing techniques to identify the gene expression profile of 14 different cell lines plus primary cultures of mouse proximal tubule and compare them to transcriptomes of native kidney proximal tubules. Methods: 14 different proximal tubule cell lines were grown on permeable supports under conditions specific for the respective lines. RNA-Seq followed standard procedures. Results and conclusion: Transcripts expressed in cell lines showed variable match to transcripts selectively expressed in native proximal tubule. Opossum kidney (OK) cells displayed the highest percentage match (45%) with pig kidney cells (LLC-PK1) close behind (39%). Much lower percentage matches were seen for various human lines including HK-2 cells (26%) and lines from rodent kidneys (18-23%).An online resource (https://esbl.nhlbi.nih.gov/JBrowse/KCT/) has been created for interrogation of the data.No cell line closely matched the transcriptome of native proximal tubule cells. However, some of the lines tested are suitable for the study of particular metabolic and transport processes seen in the proximal tubule.

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