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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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Sanger Sequencing01:57

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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Next-generation Sequencing03:00

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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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Maxam-Gilbert Sequencing01:05

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In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
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Since the discovery of the two BER pathways, there has been a debate about how a cell chooses one pathway over the other and the factors determining this selection. Numerous in vitro experiments have pointed out multiple determinants for the sub-pathway selection. These are:
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Related Experiment Video

Updated: Jul 7, 2025

Sequencing of mRNA from Whole Blood using Nanopore Sequencing
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Patch-seq: Advances and Biological Applications.

Mingting Shao1, Wei Zhang1, Ye Li1

  • 1State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China.

Cellular and Molecular Neurobiology
|December 20, 2023
PubMed
Summary
This summary is machine-generated.

Patch-sequencing (Patch-seq) integrates gene expression, cell shape, and electrical activity for neurons. This multimodal approach advances neuroscience by creating detailed cell atlases and answering complex brain questions.

Keywords:
ElectrophysiologyMorphologyMultimodalPatch-clampPatch-seqSc/snRNA-seqTranscriptomics

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Area of Science:

  • Neuroscience
  • Genomics
  • Cell Biology

Background:

  • Analyzing neuronal complexity requires integrating gene expression, electrophysiology, and morphology.
  • Previous methods faced challenges due to neuronal diversity.

Purpose of the Study:

  • To review the development and applications of Patch-sequencing (Patch-seq).
  • To highlight how Patch-seq advances neuroscience research by linking multimodal data.

Main Methods:

  • Patch-sequencing (Patch-seq) directly couples transcriptomics with electrophysiological and morphological data.
  • Analysis spans across cortex, hippocampus, and other neural systems.

Main Results:

  • Patch-seq enables the creation of multimodal cell type atlases.
  • It allows for targeted cell population studies and correlation of transcriptomic data with phenotypes.
  • New insights into fundamental neuroscience questions have been generated.

Conclusions:

  • Patch-seq has ushered in a multimodal era in neuroscience.
  • The technique offers significant opportunities for future brain research, despite existing challenges.