Mutations observed in somatic evolution reveal underlying gene mechanisms.
Mutations observed in somatic evolution reveal underlying gene mechanisms.
复制标题
DOI：
10.1038/s42003-023-05136-y
复制
发表时间：
2023-07-19
影响因子：
5.9
通讯作者：
Hall, Benjamin A.
中科院分区：
文献类型：
--
作者：
Hall, Michael W. J.;Shorthouse, David;Alcraft, Rachel;Jones, Philip H.;Hall, Benjamin A.
高灵敏度的DNA测序技术已经允许在正常组织中发现大量的体细胞突变。一些突变赋予了相对于野生型细胞的竞争优势，产生了在组织中扩散的扩增克隆。突变克隆之间的竞争导致选择。该过程可以被认为是大规模的体内筛选增加细胞适应性的突变。因此，体细胞错义突变可能为蛋白质结构，功能和细胞适应性之间的关系提供新的见解。我们提出了一个灵活的统计方法，探索体细胞突变体数据集的结构特征的选择。我们展示了这种方法如何证明老年组织中关键驱动因素的特定结构特征的选择。最后，我们展示了如何通过不同的突变富集模式将驱动程序分类为健身增强和健身抑制。该方法提供了通过体内突变体选择了解蛋白质功能机制的途径。一种统计方法鉴定正常和癌症组织中体细胞突变的选定特征。
Highly sensitive DNA sequencing techniques have allowed the discovery of large numbers of somatic mutations in normal tissues. Some mutations confer a competitive advantage over wild-type cells, generating expanding clones that spread through the tissue. Competition between mutant clones leads to selection. This process can be considered a large scale, in vivo screen for mutations increasing cell fitness. It follows that somatic missense mutations may offer new insights into the relationship between protein structure, function and cell fitness. We present a flexible statistical method for exploring the selection of structural features in data sets of somatic mutants. We show how this approach can evidence selection of specific structural features in key drivers in aged tissues. Finally, we show how drivers may be classified as fitness-enhancing and fitness-suppressing through different patterns of mutation enrichment. This method offers a route to understanding the mechanism of protein function through in vivo mutant selection. A statistical method identifies selected features in somatic mutations in normal and cancer tissue.
登录
查看更多内容
影响因子：
30.8
作者：
Abby, Emilie;Dentro, Stefan C. C.;Hall, Michael W. J.;Fowler, Joanna C. C.;Ong, Swee Hoe;Sood, Roshan;Herms, Albert;Piedrafita, Gabriel;Abnizova, Irina;Siebel, Christian W. W.;Gerstung, Moritz;Hall, Benjamin A. A.;Jones, Philip H. H.
通讯作者：
Jones, Philip H. H.
影响因子：
48
作者：
Fowler, Douglas M.;Fields, Stanley
通讯作者：
Fields, Stanley
影响因子：
16
作者：
Hao, Bing;Oehlmann, Stephanie;Pavletich, Nikola P.
通讯作者：
Pavletich, Nikola P.
影响因子：
64.8
作者：
Lee-Six, Henry;Olafsson, Sigurgeir;Stratton, Michael R.
通讯作者：
Stratton, Michael R.
影响因子：
5.6
作者：
David A;Sternberg MJ
通讯作者：
Sternberg MJ