Dataset Information

ABSTRACT: Multi-omics data and stochastic simulations support a cancer heterogeneity framework unifying genetic, epigenetic, and stochastic variabilities [Bulk-WXS-seq] (human)

PROVIDER: PRJNA632351 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	SRR11746966_1.fastq.gz	Fastqsanger.gz
	SRR11746966_2.fastq.gz	Fastqsanger.gz
	SRR11746967_1.fastq.gz	Fastqsanger.gz
	SRR11746967_2.fastq.gz	Fastqsanger.gz
	SRR11746968_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 16

Similar Datasets

Project description:Rare cells exert substantial impact on tissue physiology and pathology across a spectrum of biological realms. The elucidation of their physiological functions through multi-omics analysis is pivotal. Nonetheless, advancements in trace-level cell multi-omics technology are impeded by cellular loss during experimental procedures. Mitochondrial DNA (mtDNA) editing facilitates disease modeling of mitochondrial genetic disorders in cell lines and animals, with potential for future therapeutic applications. However, the absence of technology capable of simultaneously assessing the efficiency of mitochondrial gene editors and molecular phenotypes limits the development of mitochondrial gene editors and their in vivo therapeutic applications. Here, to address these challenges, we devised a novel omics carrier microparticle, abbreviated as OmicsCam for driving low-input cells multi-omics. OmicsCam consists of three key components: miniaturized open microparticles for multi-step biochemistry, an enlarged cell chamber boundary for streamline manipulation and minimize cell loss, and tunable permeability to ensure compatibility with key steps of magnetic separation in automated systems. By refining OmicsCam's manufacturing process, optimizing cell permeation conditions, and fine-tuning multi-omics library biochemistry, we demonstrated simultaneous assessment of mtDNA editing efficiency (mtDNA sequencing), post-editing cellular transcriptome, and chromatin accessibility in minute cell samples containing as few as 25,000 cells. Moreover, we can concurrently analyze off-target effects of gene editing. The OmicsCam platform offers a powerful way for microscale cell multi-omics analysis, enabling interrogation mitochondrial gene editing efficiency and molecular phenotypes in a unified framework. This offers a holistic perspective on the consequences of genetic manipulation within the mitochondrial genome, thereby advancing our understanding of mitochondrial biology and facilitating the development of precision therapeutics for mitochondrial disorders.

Dataset Information

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets