Single-cell transcriptomics reveals gene signatures and alterations associated with aging in distinct neural stem/progenitor cell subpopulations
Zhanping Shi, Yanan Geng, Jiping Liu, Huina Zhang, Liqiang Zhou, Quan Lin, Juehua Yu, Kunshan Zhang, Jie Liu, Xinpei Gao, Chunxue Zhang, Yinan Yao, Chong Zhang, Yi E. Sun
Single-cell transcriptomics reveals gene signatures and alterations associated with aging in distinct neural stem/progenitor cell subpopulations
Aging associated cognitive decline has been linked to dampened neural stem/progenitor cells (NSC/NPCs) activities manifested by decreased proliferation, reduced propensity to produce neurons, and increased differentiation into astrocytes. While gene transcription changes objectively reveal molecular alterations of cells undergoing various biological processes, the search for molecular mechanisms underlying aging of NSC/NPCs has been confronted by the enormous heterogeneity in cellular compositions of the brain and the complex cellular microenvironment where NSC/NPCs reside. Moreover, brain NSC/NPCs themselves are not a homogenous population, making it even more difficult to uncover NSC/NPC sub-type specific aging mechanisms. Here, using both population-based and single cell transcriptome analyses of young and aged mouse forebrain ependymal and subependymal regions and comprehensive “big-data” processing, we report that NSC/NPCs reside in a rather inflammatory environment in aged brain, which likely contributes to the differentiation bias towards astrocytes versus neurons. Moreover, single cell transcriptome analyses revealed that different aged NSC/NPC subpopulations, while all have reduced cell proliferation, use different gene transcription programs to regulate age-dependent decline in cell cycle. Interestingly, changes in cell proliferation capacity are not influenced by inflammatory cytokines, but likely result from cell intrinsic mechanisms. The Erk/Mapk pathway appears to be critically involved in regulating age-dependent changes in the capacity for NSC/NPCs to undergo clonal expansion. Together this study is the first example of using population and single cell based transcriptome analyses to unveil the molecular interplay between different NSC/NPCs and their microenvironment in the context of the aging brain.
NSC/NPCs / SEZ/SVZ / single cell transcriptome / aging / cell cycle / Erk1/2
[1] |
Beckervordersandforth R
CrossRef
Google scholar
|
[2] |
Bonni A
CrossRef
Google scholar
|
[3] |
Coskun V
CrossRef
Google scholar
|
[4] |
Doetsch F
CrossRef
Google scholar
|
[5] |
Duan H
CrossRef
Google scholar
|
[6] |
Dulken BW
CrossRef
Google scholar
|
[7] |
Enwere E
CrossRef
Google scholar
|
[8] |
Kim D
CrossRef
Google scholar
|
[9] |
Kim DH
CrossRef
Google scholar
|
[10] |
Laurens VDM, Hinton G (2008) Visualizing data using t-SNE. J Mach Learn Res 9(2605):2579–2605
|
[11] |
Llorens-Bobadilla E
CrossRef
Google scholar
|
[12] |
Love MI
CrossRef
Google scholar
|
[13] |
Luo Y
CrossRef
Google scholar
|
[14] |
Maslov AY
CrossRef
Google scholar
|
[15] |
Ming GL, Song H (2011) Adult neurogenesis in the mammalian brain: significant answers and significant questions. Neuron 70:687–702
CrossRef
Google scholar
|
[16] |
Morrison SJ, Spradling AC (2008) Stem cells and niches: mechanisms that promote stem cell maintenance throughout life. Cell 132:598–611
CrossRef
Google scholar
|
[17] |
Nolan DJ
CrossRef
Google scholar
|
[18] |
Pertea M
CrossRef
Google scholar
|
[19] |
Picelli S
CrossRef
Google scholar
|
[20] |
Picelli S
CrossRef
Google scholar
|
[21] |
Satoh Y
CrossRef
Google scholar
|
[22] |
Shalek AK
CrossRef
Google scholar
|
[23] |
Shapiro E, Biezuner T, Linnarsson S (2013) Single-cell sequencingbased technologies will revolutionize whole-organism science. Nat Rev Genet 14:618–630
CrossRef
Google scholar
|
[24] |
Sun Y
CrossRef
Google scholar
|
[25] |
Vithayathil J
CrossRef
Google scholar
|
[26] |
Yang
CrossRef
Google scholar
|
[27] |
Zhang K
CrossRef
Google scholar
|
[28] |
Zhao C
CrossRef
Google scholar
|
[29] |
Zheng
CrossRef
Google scholar
|
/
〈 | 〉 |