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相关概念视频

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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RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

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Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific...
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Next-generation Sequencing03:00

Next-generation Sequencing

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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
Although all next-generation methods use different technologies, they all share a set of standard features....
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相关实验视频

Updated: Jun 2, 2025

Transcriptome Analysis of Single Cells
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Transcriptome Analysis of Single Cells

Published on: April 25, 2011

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通过使用插入的 oligonucleotide 序列来增强单细胞转录组学.

Jianfeng Sun1, Martin Philpott1, Danson Loi1

  • 1Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, National Institute of Health Research Oxford Biomedical Research Unit (BRU), University of Oxford, Oxford, UK.

Communications biology
|January 17, 2025
PubMed
概括
此摘要是机器生成的。

寡核酸合成错误阻碍了单细胞转录组学. 一个新的增强设计通过减少基于滴滴测序的读取丢弃来改善基因表达特征.

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相关实验视频

Last Updated: Jun 2, 2025

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Transcriptome Analysis of Single Cells

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Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells
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科学领域:

  • 分子生物学分子生物学
  • 基因组学就是基因组学.
  • 生物技术是生物技术.

背景情况:

  • 单细胞转录学依赖于条形码和独特的分子标识符 (UMI) 来捕获mRNA.
  • 寡核酸合成错误可能会损害单细胞RNA测序数据的准确性.
  • 由于这些不准确性,现有的方法通常需要丢弃大量的读数.

研究的目的:

  • 开发一种改进的寡核酸捕获设计,以减轻单细胞转录组学中的错误.
  • 为了提高基因表达的可靠性和准确性,在基于滴滴的单细胞测序中进行基因表达分析.

主要方法:

  • 修改了寡核酸捕获探头设计.
  • 在条形码和UMI之间集成一个插入的接序列.
  • 评估基于滴滴的单细胞测序中的读取丢弃率和基因表达特征.

主要成果:

  • 增强的寡核酸设计显著减少了由于合成错误而丢弃的读数数量.
  • 在使用修改捕获设计的分析中观察到改善的基因表达特征.
  • 在单细胞水平上量化基因表达的提高准确性.

结论:

  • 开发的增强型寡核酸设计有效地解决了单细胞转录学中的寡核酸合成错误.
  • 这种方法为基于滴滴的单细胞测序提供了实质性的改进,导致更可靠的基因表达数据.
  • 修改后的设计提高了单细胞转录组分析的整体实用性和准确性.