Cited by 285

MicroRNA, mRNA, and protein expression link development and aging in human and macaque brain

Somel, Mehmet, Guo, Song, Fu, Ning, Yan, Zheng, Hu, Hai Yang, Xu, Ying, Yuan, Yuan, Ning, Zhibin +7 more·2010·Genome Research

Abstract

Changes in gene expression levels determine differentiation of tissues involved in development and are associated with functional decline in aging. Although development is tightly regulated, the transition between development and aging, as well as regulation of post-developmental changes, are not well understood. Here, we measured messenger RNA (mRNA), microRNA (miRNA), and protein expression in the prefrontal cortex of humans and rhesus macaques over the species' life spans. We find that few gene expression changes are unique to aging. Instead, the vast majority of miRNA and gene expression changes that occur in aging represent reversals or extensions of developmental patterns. Surprisingly, many gene expression changes previously attributed to aging, such as down-regulation of neural genes, initiate in early childhood. Our results indicate that miRNA and transcription factors regulate not only developmental but also post-developmental expression changes, with a number of regulatory processes continuing throughout the entire life span. Differential evolutionary conservation of the corresponding genomic regions implies that these regulatory processes, although beneficial in development, might be detrimental in aging. These results suggest a direct link between developmental regulation and expression changes taking place in aging.

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  • Aberrant expression of small ncRNAs is associated with cancer, autoimmune disease, and several neurodegenerative disorders.

    “Aberrant expression of small ncRNAs, in turn, has been associated with diseases such as cancer, autoimmune disease, and several neurodegenerative disorders (9, 10).”

    From A mouse tissue atlas of small noncoding RNA (2020) · cites this paper as [10]

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  1. Courchesne E, Chisum HJ, Townsend J, Cowles A, Covington J, Egaas B, Harwood M, Hinds S, Press GA. 2000. Normal brain development and aging: Quantitative analysis at in vivo MR imaging in healthy volunteers. Radiology 216: 672-682.
  2. Fu X, Fu N, Guo S, Yan Z, Xu Y, Hu H, Menzel C, Chen W, Li Y, Zeng R, et al. 2009. Estimating accuracy of RNA-Seq and microarrays with proteomics. BMC Genomics 10: 161. doi: 10.1186/1471-2164-10-161. · DOI
  3. Hu H, Yan Z, Xu Y, Hu H, Menzel C, Zhou YH, Chen W, Khaitovich P. 2009. Sequence features associated with microRNA strand selection in humans and flies. BMC Genomics 10: 413. doi: 10.1186/1471-2164-10-413. · DOI
  4. Loerch PM, Lu T, Dakin KA, Vann JM, Isaacs A, Geula C, Wang J, Pan Y, Gabuzda DH, Li C, et al. 2008. Evolution of the aging brain transcriptome and synaptic regulation. PLoS ONE 3: e3329. doi: 10.1371/journal.pone.0003329. · DOI · Paper page
  5. Rose MR. 1991. Evolutionary biology of aging. Oxford University Press, New York.
  6. Xue H, Xian B, Dong D, Xia K, Zhu S, Zhang Z, Hou L, Zhang Q, Zhang Y, Han JJ. 2007. A modular network model of aging. Mol Syst Biol 3: 147. doi: 10.1038/msb4100189. · DOI

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Authors
Somel, M., Guo, S., Fu, N., Yan, Z., Hu, H. Y., Xu, Y., Yuan, Y., Ning, Z., Hu, Y., Menzel, C., Hu, H., Lachmann, M., Zeng, R., Chen, W., & Khaitovich, P.
Venue
Genome Research
Published
2010-07-20
Volume
20
Issue
9
Pages
1207-1218
ISSN
1088-9051
Cited by
285
References
11
Language
en

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