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相关概念视频

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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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.
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相关实验视频

Updated: Jul 7, 2025

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
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对人类基因组学应用的基因组序列对齐工具的基准测试.

Jonathan LoTempio1,2, Emmanuele Delot3,4, Eric Vilain1,2

  • 1Institute for Clinical and Translational Science, University of California, Irvine, CA, United States of America.

PeerJ
|December 22, 2023
PubMed
概括

对人类基因组学进行长期阅读的测序对齐工具的基准测试显示,没有单一的工具是足够的. 建议使用多种对齐工具的综合方法,例如Minimap2和Winnowmap2,用于全面的基因组变异检测.

关键词:
一个基准的基准.基因组对齐是如何实现的基因组医学是一种基因组医学.长时间读取序列的序列.简读序列的短读序列.

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科学领域:

  • 基因组学就是基因组学.
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 长读基因组测序 (LRS) 在各种领域提供了实用性,但其在基因组医学的参考引导人类基因组学中的应用仍然不太了解.
  • 评估LRS对人类基因组学的适用性对于推进基因组医学至关重要.

研究的目的:

  • 通过使用LRS数据对平台不可知对齐工具进行基准测试,以确定它们在参考引导的人类基因组学中的适用性.
  • 评估不同对齐工具在产生准确的人类基因组表示的性能.

主要方法:

  • 利用来自NA12878 (牛津纳米孔) 和NA24385 (太平洋生物科学) 的公开可用的LRS数据集.
  • 使用的和基准的最先进的序列对齐工具:GraphMap2,LRA,Minimap2,NGMLR和Winnowmap2.
  • 根据计算效率,资源需求以及调整读取和检测结构变异的能力来评估工具.

主要成果:

  • Minimap2和Winnowmap2在计算上是高效的;NGMLR是资源密集的,但是一致的;LRA是快速的,但特定于平台 (PacBio).
  • 关于非对齐读数的工具之间存在重大分歧,影响了基因组覆盖和断点检测.
  • 没有单一的工具能够独立识别测试样本中的所有大型结构变异 (1,001-100,000 bp).

结论:

  • 为了全面的人类基因组学,需要采用利用多个LRS对齐工具的综合方法.
  • 建议使用至少三种工具的对齐,优先考虑像Minimap2和Winnowmap2这样的轻量级选项,以获得完整的基因组变异性图像.
  • 根据具体的研究问题,数据可用性和时间限制,NGMLR和LRA可以作为有价值的第三工具,而Graphmap2对于使用LRS数据进行全人类基因组探索并不理想.