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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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Sanger Sequencing01:57

Sanger Sequencing

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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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Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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Single Nucleotide Polymorphisms-SNPs01:05

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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相关实验视频

Updated: Jul 19, 2025

Detection of Copy Number Alterations Using Single Cell Sequencing
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单核酸变异调用单细胞测序数据与单基因.

Jinzhuang Dou1, Yukun Tan1, Kian Hong Kock2

  • 1Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Nature biotechnology
|August 17, 2023
PubMed
概括

单基因是一种新的工具,可以识别单细胞中的遗传变异. 它有助于了解遗传背景如何影响细胞行为,并使血统追踪用于各种应用.

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科学领域:

  • 基因组学和生物信息学
  • 一个单细胞的奥米克.
  • 人口遗传学 人口遗传学

背景情况:

  • 单细胞奥米克技术为细胞多样性提供了深刻的分子洞察力.
  • 一个细胞的遗传背景对其转录和表观遗传特征的影响尚未得到充分理解.
  • 从单细胞数据中准确检测基因变异对于全面分析至关重要.

研究的目的:

  • 在单细胞测序数据中检测单核酸变异 (SNVs) 的计算工具 Monopogen.
  • 为了使研究基因决定因素的基础细胞过程和变异.
  • 整合种群遗传学和细胞谱系追踪与单细胞奥米学.

主要方法:

  • 单基因利用外部参考面板的链接不平衡来识别生殖线SNVs.
  • 它通过分析细胞群体水平的等位基因共分离模式来检测假定的体质SNV.
  • 该工具将单细胞测序数据处理为基因型变异.

主要成果:

  • 单基因识别了10万到300万个生殖系SNV,具有95%的基因型准确性.
  • 检测到数百个假定的体性SNV,促进了克隆系谱的追踪.
  • 单基因衍生的基因型使得祖先推断和混合样本的识别,并揭示与心肌细胞代谢和表观遗传学程序相关的变异.

结论:

  • 从单细胞测序数据中,Monopogen有效地检测出生殖线和体质单核酸变异.
  • 该工具通过整合遗传背景信息来增强单细胞奥米克的能力.
  • 单基因为发现细胞表型的遗传影响和追踪细胞系提供了一个强大的平台.