Volume 41 Issue 5
Sep.  2020
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Chao-Chao Yan, Xin-Shang Zhang, Liang Zhou, Qiao Yang, Min Zhou, Lin-Wan Zhang, Jin-Chuan Xing, Zhi-Feng Yan, Megan Price, Jing Li, Bi-Song Yue, Zhen-Xin Fan. Effects of aging on gene expression in blood of captive Tibetan macaques (Macaca thibetana) and comparisons with expression in humans. Zoological Research, 2020, 41(5): 557-563. doi: 10.24272/j.issn.2095-8137.2020.092
Citation: Chao-Chao Yan, Xin-Shang Zhang, Liang Zhou, Qiao Yang, Min Zhou, Lin-Wan Zhang, Jin-Chuan Xing, Zhi-Feng Yan, Megan Price, Jing Li, Bi-Song Yue, Zhen-Xin Fan. Effects of aging on gene expression in blood of captive Tibetan macaques (Macaca thibetana) and comparisons with expression in humans. Zoological Research, 2020, 41(5): 557-563. doi: 10.24272/j.issn.2095-8137.2020.092

Effects of aging on gene expression in blood of captive Tibetan macaques (Macaca thibetana) and comparisons with expression in humans

doi: 10.24272/j.issn.2095-8137.2020.092
#Authors contributed equally to this work
Funds:  This work was supported by the National Natural Science Foundation of China 31501871 (Z.X.F.), Department of Science and Technology of Sichuan Province 2019JDZH0029 (X.Z.), Department of Science and Technology of Sichuan Province 2020JDZH0026 (X.Z.), and Academy of Medical Sciences & Sichuan Provincial People’s Hospital 2017QN06 (X.Z.)
More Information
  • Corresponding author: E-mail: zxfan@scu.edu.cn
  • Received Date: 2020-04-23
  • Accepted Date: 2020-06-18
  • Available Online: 2020-06-24
  • Publish Date: 2020-09-18
  • Changes in gene expression occur as animals, including primates, age. Macaques have long been used as a model species for primate evolution and biomedical studies. Here, to study gene expression in Tibetan macaques (Macaca thibetana, TMs) and its differences to humans, we applied RNA-Seq to obtain the blood transcriptomes of 24 TMs. In total, 2 523 age-associated differentially expressed genes (DEGs) were identified. Several pathways and processes that regulate aging, including the FoxO signaling pathway, autophagy, and platelet activation, were significantly enriched in the up-regulated DEGs. Two significantly age-related modules were identified by weighted gene co-expression network analysis (WGCNA). The TMs and humans shared 279 common DEGs, including 111 up-regulated and 141 down-regulated genes with advancing age in the same expression direction. However, 27 age-related DEGs presented the opposite expression direction in TMs as that in humans. For example, INPPL1, with inhibitory effects on the B cell receptor signaling pathway, was up-regulated in humans but down-regulated in TMs. In general, our study suggests that aging is a critical factor affecting gene expression in the captive TM population. The similarities and differences in gene expression patterns between TMs and humans could provide new insights into primate evolution and benefit TM model development.
  • #Authors contributed equally to this work
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  • [1]
    Anders S, Pyl PT, Huber W. 2015. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics, 31(2): 166−169. doi: 10.1093/bioinformatics/btu638
    Aziz H, Zaas A, Ginsburg GS. 2007. Peripheral blood gene expression profiling for cardiovascular disease assessment. Genomic Medicine, 1(3-4): 105−112. doi: 10.1007/s11568-008-9017-x
    Charruau P, Johnston RA, Stahler DR, Lea A, Snyder-Mackler N, Smith DW, et al. 2016. Pervasive effects of aging on gene expression in wild wolves. Molecular Biology and Evolution, 33(8): 1967−1978. doi: 10.1093/molbev/msw072
    Dannemann M, Kelso J. 2017. The contribution of Neanderthals to phenotypic variation in modern humans. The American Journal of Human Genetics, 101(4): 578−589. doi: 10.1016/j.ajhg.2017.09.010
    de Magalhães JP, Passos JF. 2018. Stress, cell senescence and organismal ageing. Mechanisms of Ageing and Development, 170: 2−9. doi: 10.1016/j.mad.2017.07.001
    Eghlidi DH, Luna SL, Brown DI, Garyfallou VT, Kohama SG, Urbanski HF. 2018. Gene expression profiling of the SCN in young and old rhesus macaques. Journal of Molecular Endocrinology, 61(2): 57−67. doi: 10.1530/JME-18-0062
    Fan ZX, Zhao G, Li P, Osada N, Xing JC, Yi Y, et al. 2014. Whole-genome sequencing of Tibetan macaque (Macaca thibetana) provides new insight into the macaque evolutionary history. Molecular Biology and Evolution, 31(6): 1475−1489. doi: 10.1093/molbev/msu104
    Favaloro EJ, Franchini M, Lippi G. 2014. Aging hemostasis: changes to laboratory markers of hemostasis as we age-a narrative review. Seminars in Thrombosis and Hemostasis, 40(6): 621−633. doi: 10.1055/s-0034-1384631
    Frehlick LJ, Eirín-López JM, Ausió J. 2007. New insights into the nucleophosmin/nucleoplasmin family of nuclear chaperones. BioEssays, 29(1): 49−59. doi: 10.1002/bies.20512
    Gibbons A. 2017. Neandertal genome reveals greater legacy in the living. Science, 358(6359): 21. doi: 10.1126/science.358.6359.21
    Göring HHH, Curran JE, Johnson MP, Dyer TD, Charlesworth J, Cole SA, et al. 2007. Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes. Nature Genetics, 39(10): 1208−1216. doi: 10.1038/ng2119
    Granneman S, Tollervey D. 2007. Building ribosomes: even more expensive than expected?. Current Biology, 17(11): R415−R417. doi: 10.1016/j.cub.2007.04.011
    Hong MG, Myers AJ, Magnusson PKE, Prince JA. 2008. Transcriptome-wide assessment of human brain and lymphocyte senescence. PLoS One, 3(8): e3024. doi: 10.1371/journal.pone.0003024
    Hoopes BC, Rimbault M, Liebers D, Ostrander EA, Sutter NB. 2012. The insulin-like growth factor 1 receptor (IGF1R) contributes to reduced size in dogs. Mammalian Genome, 23(11-12): 780−790. doi: 10.1007/s00335-012-9417-z
    Horvath S, Zhang YF, Langfelder P, Kahn RS, Boks MPM, van Eijk K, et al. 2012. Aging effects on DNA methylation modules in human brain and blood tissue. Genome Biology, 13(10): R97. doi: 10.1186/gb-2012-13-10-r97
    Kenyon CJ. 2010. The genetics of ageing. Nature, 467(7315): 622.
    Kim D, Langmead B, Salzberg SL. 2015. HISAT: a fast spliced aligner with low memory requirements. Nature Methods, 12(4): 357−360. doi: 10.1038/nmeth.3317
    Lan Y, Wang J, Yang Q, Tang RX, Zhou M, Lei GL, et al. 2020. Blood transcriptome analysis reveals gene expression features of breast-feeding rhesus macaque (Macaca mulatta) infants. Zoological Research, 41(4): 431−436. doi: 10.24272/j.issn.2095-8137.2020.044
    Lapointe J, Li CD, Higgins JP, van de Rijn M, Bair E, Montgomery K, et al. 2004. Gene expression profiling identifies clinically relevant subtypes of prostate cancer. Proceedings of the National Academy of Sciences of the United States of America, 101(3): 811−816. doi: 10.1073/pnas.0304146101
    Lindqvist LM, Tandoc K, Topisirovic I, Furic L. 2018. Cross-talk between protein synthesis, energy metabolism and autophagy in cancer. Current Opinion in Genetics & Development, 48: 104−111.
    López-Otín C, Blasco MA, Partridge L, Serrano M, Kroemer G. 2013. The hallmarks of aging. Cell, 153(6): 1194−1217. doi: 10.1016/j.cell.2013.05.039
    Love MI, Huber W, Anders S. 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15(12): 550. doi: 10.1186/s13059-014-0550-8
    Lyman GH, Culakova E, Poniewierski MS, Kuderer NM. 2018. Morbidity, mortality and costs associated with venous thromboembolism in hospitalized patients with cancer. Thrombosis Research, 164: S112−S118. doi: 10.1016/j.thromres.2018.01.028
    Mari D, Coppola R, Provenzano R. 2008. Hemostasis factors and aging. Experimental Gerontology, 43(2): 66−73. doi: 10.1016/j.exger.2007.06.014
    Mesko B, Poliska S, Nagy L. 2011. Gene expression profiles in peripheral blood for the diagnosis of autoimmune diseases. Trends in Molecular Medicine, 17(4): 223−33. doi: 10.1016/j.molmed.2010.12.004
    Peters MJ, Joehanes R, Pilling LC, Schurmann C, Conneely KN, Powell J, et al. 2015. The transcriptional landscape of age in human peripheral blood. Nature Communications, 6: 8570. doi: 10.1038/ncomms9570
    Reynolds LM, Ding JZ, Taylor JR, Lohman K, Soranzo N, de la Fuente A, et al. 2015. Transcriptomic profiles of aging in purified human immune cells. BMC Genomics, 16(1): 333. doi: 10.1186/s12864-015-1522-4
    Sheffield WD, Squire RA, Strandberg JD. 1981. Cerebral venous thrombosis in the rhesus monkey. Veterinary Pathology, 18(3): 326−334. doi: 10.1177/030098588101800305
    Shu TJ, Zhang YZ. 2007. Nucleoplasmin, an important nuclear chaperone. Chinese Journal of Biochemistry and Molecular Biology, 23(9): 718−723. (in Chinese)
    Simon AK, Hollander GA, McMichael A. 2015. Evolution of the immune system in humans from infancy to old age. Proceedings Biological Sciences, 282(1821): 20143085.
    Stute P, Sielker S, Wood CE, Register TC, Lees CJ, Dewi FN, Williams JK, Wagner JD, Stefenelli U, Cline JM. 2012. Life stage differences in mammary gland gene expression profile in non-human primates. Breast Cancer Research and Treatment, 133(2): 617−634.
    Tung J, Zhou X, Alberts SC, Stephens M, Gilad Y. 2015. The genetic architecture of gene expression levels in wild baboons. eLife, 4: e04729. doi: 10.7554/eLife.04729
    van der Horst A, Burgering BMT. 2007. Stressing the role of foxo proteins in lifespan and disease. Nature Reviews Molecular Cell Biology, 8(6): 440−450. doi: 10.1038/nrm2190
    van den Akker EB, Passtoors WM, Jansen R, van Zwet EW, Goeman JJ, Hulsman M, et al. 2014. Meta-analysis on blood transcriptomic studies identifies consistently coexpressed protein- protein interaction modules as robust markers of human aging. Aging Cell, 13(2): 216−225. doi: 10.1111/acel.12160
    Wei K, Liang X, Zou FD, Yin HL, Yue BS. 2006. Molecular cloning and sequence analysis of interferon-gamma and interleukin-6 from Tibetan macaque (Macaca thibetana). Veterinary Immunology and Immunopathology, 114(3−4): 346−354. doi: 10.1016/j.vetimm.2006.08.014
    Wu D, Yi Y, Sun F, Zhou L, Yang F, Wang H, et al. 2014. Effects of age and sex on the hematology and blood chemistry of Tibetan macaques (Macaca thibetana). Journal of the American Association for Laboratory Animal Science, 53(1): 12−17.
    Wu D, Yue F, Zou CL, Chan P, Zhang YA. 2012. Analysis of glucose metabolism in cynomolgus monkeys during aging. Biogerontology, 13(2): 147−155. doi: 10.1007/s10522-011-9364-1
    Xie C, Mao XZ, Huang JJ, Ding Y, Wu JM, Dong S, et al. 2011. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Research, 39(S2): W316−W322.
    Yao YF, Zhao JJ, Dai QX, Li JY, Zhou L, Wang YT, et al. 2013. Identification and characterization of the major histocompatibility complex class II DQB (MhcMath-DQB1) alleles in Tibetan macaques (Macaca thibetana). Tissue Antigens, 82(2): 113−121. doi: 10.1111/tan.12145
    Yin JA, Gao G, Liu XJ, Hao ZQ, Li K, Kang XL, et al. 2017. Genetic variation in glia-neuron signalling modulates ageing rate. Nature, 551(7679): 198−203. doi: 10.1038/nature24463
    Zheng HR, Liu T, Lei TT, Girani L, Wang Y, Deng SP. 2019. Promising potentials of Tibetan macaques in xenotransplantation. Xenotransplantation, 26(1): e12489. doi: 10.1111/xen.12489
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