Single-Cell Analysis of Human Pancreas Reveals Transcriptional Signatures of Aging and Somatic Mutation Patterns.
Single-Cell Analysis of Human Pancreas Reveals Transcriptional Signatures of Aging and Somatic Mutation Patterns.
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DOI：
10.1016/j.cell.2017.09.004
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发表时间：
2017-10-05
期刊：
影响因子：
64.5
通讯作者：
Quake SR
中科院分区：
文献类型：
--
作者：
Enge M;Arda HE;Mignardi M;Beausang J;Bottino R;Kim SK;Quake SR
随着生物的年龄，细胞会积累遗传和表观遗传误差，最终导致器官功能或灾难性转化（例如癌症）。由于衰老反映了疾病增加的随机过程，因此器官中的细胞将以不同的方式单独影响，从而对有丝分裂后成人细胞的大量分析难以解释。在这里，我们通过对跨越六十年生命的八个供体进行2,544个人胰腺细胞的单细胞转录组分析来直接测量人体组织中衰老的影响。我们发现，来自老年供体的胰岛内分泌细胞显示出提高的转录噪声和潜在命运漂移水平。通过确定单个细胞的突变史，我们发现了健康衰老内分泌细胞中的新型突变特征。我们的结果表明，使用单细胞RNA测序（RNA-SEQ）数据从原代细胞中进行了可行性，以洞悉对人类组织衰老的遗传和转录过程。
衰老与单细胞水平上的转录失调和身份丧失有关
As organisms age, cells accumulate genetic and epigenetic errors that eventually lead to impaired organ function or catastrophic transformation such as cancer. Because aging reflects a stochastic process of increasing disorder, cells in an organ will be individually affected in different ways, thus rendering bulk analyses of postmitotic adult cells difficult to interpret. Here, we directly measure the effects of aging in human tissue by performing single-cell transcriptome analysis of 2,544 human pancreas cells from eight donors spanning six decades of life. We find that islet endocrine cells from older donors display increased levels of transcriptional noise and potential fate drift. By determining the mutational history of individual cells, we uncover a novel mutational signature in healthy aging endocrine cells. Our results demonstrate the feasibility of using single-cell RNA sequencing (RNA-seq) data from primary cells to derive insights into genetic and transcriptional processes that operate on aging human tissue. Aging is associated with increased transcriptional dysregulation and loss of identity at the single-cell level
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影响因子：
64.5
作者：
López-Otín C;Blasco MA;Partridge L;Serrano M;Kroemer G
通讯作者：
Kroemer G
影响因子：
2.1
作者：
Kasar S;Brown JR
通讯作者：
Brown JR
DOI：
10.1093/bioinformatics/btu638
发表时间：
2015-01-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Anders S;Pyl PT;Huber W
通讯作者：
Huber W
影响因子：
5.2
作者：
De Tata V
通讯作者：
De Tata V
DOI：
10.1073/pnas.1507125112
发表时间：
2015-06-09
影响因子：
11.1
作者：
Darmanis S;Sloan SA;Zhang Y;Enge M;Caneda C;Shuer LM;Hayden Gephart MG;Barres BA;Quake SR
通讯作者：
Quake SR