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相关概念视频

Evolutionary Relationships through Genome Comparisons02:54

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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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Synteny and Evolution02:31

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John H. Renwick first coined the term “synteny” in 1971, which refers to the genes present on the same chromosomes, even if they are not genetically linked. The species with common ancestry tend to show conserved syntenic regions. Therefore, the concept of synteny is nowadays used to describe the evolutionary relationship between species.
Around 80 million years ago, the human and mice lineages diverged from the common ancestor. During the course of evolution, the ancestral...
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Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
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Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.
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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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Mapping Mammalian 3D Genome Interactions with Micro-C-XL
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基于序列的机器学习揭示了黑猩猩和黑猩猩之间的3D基因组差异.

Colin M Brand1,2, Shuzhen Kuang3, Erin N Gilbertson1,4

  • 1Bakar Computational Health Sciences Institute, University of California, San Francisco, CA.

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概括
此摘要是机器生成的。

黑猩猩和黑猩猩的基因组折叠差异导致了表型分歧. 机器学习揭示了人口层面的3D基因组变异,确定了影响基因调节和特征的关键区域和变异.

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科学领域:

  • 基因组学就是基因组学.
  • 进化生物学 进化生物学
  • 计算生物学 计算生物学

背景情况:

  • 像黑猩猩和黑猩猩 (属*Pan*) 等密切相关物种之间的表型分歧受到基因调节变异的显著影响.
  • 三维 (3D) 基因组结构在调解基因表达方面发挥着至关重要的作用,但Pan* 属内的折叠差异仍然不太了解.

研究的目的:

  • 通过机器学习预测和分析来自红和黑猩猩的DNA序列的全基因组3D基因组接触图.
  • 量化和表征3D基因组分歧在群体层面的 * Pan * 属内.
  • 为了确定特定的基因组区域和变异,有助于3D基因组折叠差异和潜在的表型分歧.

主要方法:

  • 应用机器学习从DNA序列预测56个个体的3D基因组接触地图,跨越所有五个现存的*Pan*血统.
  • 采用双向方法,在4420个1Mb的基因组窗口中估计3D差异.
  • 进行 *in silico* 突变发生,以识别不同基因组窗口中的 3D 修改变体,重点关注 CTCF 结合动机破坏.

主要成果:

  • 在约17%的单个对对比中预测了相当大的3D基因组折叠差异.
  • 确定了89个基因组窗口,其中存在大量的博黑猩猩接触地图分歧,包括与表型差异相关的基因区域.
  • 在不同的窗口中发现了51个3D修改变异,其中66.67% (34个变异) 通过CTCF结合动机破坏影响基因组折叠.

结论:

  • 揭示了 *Pan* 属内的 3D 基因组结构在人口水平上的显著变化.
  • 确定了特定的基因组区域和变异,其中改变的3D折叠可能是黑猩猩和黑猩猩之间的表型差异的基础.
  • 突出了CTCF结合动机破坏在驱动3D基因组折叠变化的作用,这有助于产生特定物种的特征.