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Related Concept Videos

RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Genomics02:02

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
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Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
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An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
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Single-cell sequencing to multi-omics: technologies and applications.

Xiangyu Wu1, Xin Yang1, Yunhan Dai2

  • 1Department of Urology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China.

Biomarker Research
|September 28, 2024
PubMed
Summary

Single-cell multi-omics integrates various data types to reveal complex cellular information. This approach enhances understanding of cell development, disease, and treatment strategies.

Keywords:
Computational biologyMetabolomeMicrobiomeProteomicsSingle-cell multi-omicsSpatial transcriptomicsscBCR-seqscRNA-seqscTCR-seq

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Area of Science:

  • Genomics
  • Molecular Biology
  • Biomedical Science

Background:

  • Cells possess intricate multidimensional spatiotemporal information.
  • Single-cell RNA sequencing (scRNA-seq) is a key technology for analyzing cellular states and heterogeneity.
  • Advancements in sequencing enable deeper insights into cellular complexity.

Purpose of the Study:

  • To review traditional single-cell sequencing technologies.
  • To outline the latest advancements in single-cell multi-omics.
  • To summarize the current status and challenges of single-cell multi-omics applications.

Main Methods:

  • Integration of scRNA-seq with other omics data (e.g., immune repertoire, spatial, temporal, epitopes).
  • Simultaneous measurement of diverse molecular data within individual cells.
  • Analysis of multi-omics data across various spatiotemporal contexts.

Main Results:

  • Single-cell multi-omics precisely captures multidimensional cellular aspects.
  • Enables detailed cell atlas construction for normal and diseased tissues.
  • Provides a foundation for studying cell differentiation, development, and disease mechanisms.

Conclusions:

  • Single-cell multi-omics significantly expands understanding of cellular biology.
  • Applications span basic research, disease heterogeneity, drug resistance, and treatment strategies.
  • Identifies current limitations and challenges, proposing future strategies.