Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Epigenetic Regulation01:37

Epigenetic Regulation

3.0K
Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
X-chromosome...
3.0K
Mutations01:35

Mutations

33.6K
Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
Chromosomal Alterations Are Large-Scale Mutations
While point mutations are changes in a single nucleotide in...
33.6K
Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

11.5K
Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
11.5K
Somatic to iPS Cell Reprogramming01:29

Somatic to iPS Cell Reprogramming

2.2K
Reprogramming alters the gene expression in somatic cells, transforming them into induced pluripotent stem (iPS) cells over several generations. Scientists can reprogram cells by introducing genes for four transcription factors—Oct4, Sox2, Klf4, and c-Myc (OSKM) by viral or non-viral methods. These factors are also known as Yamanaka factors after Shinya Yamanaka, who first generated iPS cells using mouse skin cells. Yamanaka was awarded the Nobel Prize in Physiology or Medicine in 2012...
2.2K
Nucleotide Excision Repair01:38

Nucleotide Excision Repair

3.4K
DNA Distortion and Damage
Cells are regularly exposed to mutagens—factors in the environment that can damage DNA and generate mutations. UV radiation is one of the most common mutagens and is estimated to introduce a significant number of changes in DNA. These include bends or kinks in the structure, which can block DNA replication or transcription. If these errors are not fixed, the damage can cause mutations, which in turn can result in cancer or disease depending on which sequences are...
3.4K
Loss of Tumor Suppressor Gene Functions01:12

Loss of Tumor Suppressor Gene Functions

4.7K
Tumor suppressor genes are normal genes that can slow down cell division, repair DNA mistakes, or program the cells for apoptosis in case of irreparable damage. Hence, they play an essential role in preventing the proliferation of damaged cells.
When the tumor suppressor genes develop mutations or are lost, cells start growing out of control, leading to cancer. However, a single functional copy of the tumor suppressor gene is enough for the cells to maintain their normal functions and cell...
4.7K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A genome-scale CRISPRi perturbation atlas of human induced pluripotent stem cells.

Nature biotechnology·2026
Same author

Poorer Physical Function Is Associated With Elevated Spatial Entropy in the Aging Brain Network Landscape.

Aging cell·2026
Same author

DREAM repressive activity links somatic mutation, lifespan and disease.

Nature aging·2026
Same author

A foundation model of cancer genotype enables precise predictions of therapeutic response.

Cancer discovery·2026
Same author

Evaluation of a Pediatric Surgical Risk Calculator for Postoperative Outcomes in Spinal Deformity.

Global spine journal·2026
Same author

Transcriptomic Profiling in Skeletal Muscle Identifies Associations With Knee Osteoarthritis: the Study of Muscle, Mobility and Aging (SOMMA).

medRxiv : the preprint server for health sciences·2026

相关实验视频

Updated: Jun 2, 2025

Studying Age-dependent Genomic Instability using the S. cerevisiae Chronological Lifespan Model
08:46

Studying Age-dependent Genomic Instability using the S. cerevisiae Chronological Lifespan Model

Published on: September 29, 2011

15.6K

身体突变作为表观遗传衰老的解释.

Zane Koch1, Adam Li1, Daniel S Evans2,3

  • 1Program in Bioinformatics and Systems Biology, University of California, San Diego, La Jolla, CA, USA.

Nature aging
|January 13, 2025
PubMed
概括

身体突变和DNA甲基化变化与生物衰老相关. 这项研究表明,突变积累可以类似于表观遗传钟来预测年龄,揭示了突变和甲基组重塑之间的联系.

更多相关视频

Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae
11:08

Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae

Published on: October 16, 2014

12.5K
Evaluation of Injury-induced Senescence and In Vivo Reprogramming in the Skeletal Muscle
09:14

Evaluation of Injury-induced Senescence and In Vivo Reprogramming in the Skeletal Muscle

Published on: October 26, 2017

9.5K

相关实验视频

Last Updated: Jun 2, 2025

Studying Age-dependent Genomic Instability using the S. cerevisiae Chronological Lifespan Model
08:46

Studying Age-dependent Genomic Instability using the S. cerevisiae Chronological Lifespan Model

Published on: September 29, 2011

15.6K
Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae
11:08

Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae

Published on: October 16, 2014

12.5K
Evaluation of Injury-induced Senescence and In Vivo Reprogramming in the Skeletal Muscle
09:14

Evaluation of Injury-induced Senescence and In Vivo Reprogramming in the Skeletal Muscle

Published on: October 26, 2017

9.5K

科学领域:

  • 基因组学就是基因组学.
  • 表观遗传学 在表观遗传学中,表观遗传学是指表观遗传学.
  • 衰老研究研究 衰老研究

背景情况:

  • 基于DNA甲基化的表观遗传钟,可以预测生物年龄.
  • 细胞酸甲基化可以导致C-to-T突变,这表明甲基化变化和体质突变积累之间存在联系.

研究的目的:

  • 为了调查与年龄相关的DNA甲基化变化反映体质突变积累的假设.
  • 为了确定突变积累是否可以产生类似于表观遗传钟的衰老估计.
  • 探索突变热点与预测年龄的甲基化模式之间的关系.

主要方法:

  • 分析了来自9331名人类个体的多式联运数据.
  • 检查CpG突变与甲基化变化的巧合.
  • 开发基于突变的年龄预测模型.
  • 将基于突变的年龄预测与已建立的表观遗传钟进行比较.

主要成果:

  • 发现CpG突变与甲基化变化相吻合,影响甲基化模式,距离突变部位可达±10千基.
  • 基于突变的年龄预测与表观遗传钟估计结果一致.
  • 使用突变数据,可以识别比预期更快或更慢老化的个体.
  • 具有年龄累积突变的基因组位点表现出高度预测年龄的甲基化模式.

结论:

  • 随机体突变的积累和与年龄相关的广泛甲基化变化之间存在密切的联系.
  • 身体突变为估计衰老提供了一个新的基础,补充了表观遗传钟.
  • 了解这种联系,可以了解衰老的分子机制.