Resilience, plasticity and robustness in gene expression during aging in the brain of outbred deer mice
Tóm tắt
Tài liệu tham khảo
RoyS, Bhattacharyya DK, Kalita JK. Reconstruction of gene co-expression networkfrom microarray data using local expression patterns. BMC Bioinformatics.2014;15 (Suppl 7):S10. doi:10.1186/1471-2105-15-S7-S10 https://doi.org/10.1186/1471-2105-15-S7-S10
Luo J, Xu P, Cao P, Wan H, Lv X, Xu S, Wang G, Cook MN, Jones BC, Lu L, Wang X. Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses. Front Mol Neurosci. 2018;11:102. doi: https://doi.org/10.3389/fnmol.2018.00102. PMID: 29674951; PMCID: PMC5895640.
van Dam S, Võsa U, van der Graaf A, Franke L, de Magalhães JP. Gene co-expression analysis for functional classification and gene-disease predictions. Brief Bioinform. 2018;19(4):575–592. doi: https://doi.org/10.1093/bib/bbw139. PMID: 28077403; PMCID: PMC6054162.
Amar D, Safer H, Shamir R. Dissection of regulatory networks that are altered in disease via differential co-expression. PLoS Comput Biol. 2013;9(3):e1002955. doi: https://doi.org/10.1371/journal.pcbi.1002955. Epub 2013 Mar 7. PMID: 23505361; PMCID: PMC3591264.
Kostka D, Spang R. Finding disease specific alterations in the co-expression of genes. Bioinformatics. 2004;20 Suppl 1:i194-9. doi: https://doi.org/10.1093/bioinformatics/bth909. PMID: 15262799.
Kakati T, Bhattacharyya DK, Barah P, Kalita JK. Comparison of Methods for Differential Co-expression Analysis for Disease Biomarker Prediction. Comput Biol Med. 2019;113:103380. https://doi.org/10.1016/j.compbiomed.2019.103380 Epub 2019 Aug 10. PMID: 31415946.
Macneil LT, Walhout AJ. Gene regulatory networks and the role of robustness and stochasticity in the control of gene expression. Genome Res. 2011;21(5):645–657. doi:https://doi.org/10.1101/gr.097378.109
McDermaid A, Monier B, Zhao J, Liu B, Ma Q. Interpretation of differential gene expression results of RNA-seq data: review and integration. Brief Bioinform. 2019;20(6):2044–2054. doi: https://doi.org/10.1093/bib/bby067. PMID: 30099484; PMCID: PMC6954399.
Crow M, Lim N, Ballouz S, Pavlidis P, Gillis J, S A. Predictability of human differential gene expression. Proc Natl Acad Sci USA. 2019;26(13):6491–500. https://doi.org/10.1073/pnas.1802973116 Epub 2019 Mar 7. PMID: 30846554; PMCID: PMC6442595.
Sabunciyan, S. Gene Expression Profiles Associated with Brain Aging are Altered in Schizophrenia. Sci Rep 9, 5896 (2019). https://doi.org/10.1038/s41598-019-42308-5
Shavlakadze T, Morris M, Fang J, Wang SX, Zhu J, Zhou W, Tse HW, Mondragon-Gonzalez R, Roma G, Glass DJ. Age-Related Gene Expression Signature in Rats Demonstrate Early, Late, and Linear Transcriptional Changes from Multiple Tissues. Cell Rep. 2019;28(12):3263–3273.e3. doi: https://doi.org/10.1016/j.celrep.2019.08.043. PMID: 31533046.
Zeng L, Yang J, Peng S, Zhu J, Zhang B, Suh Y, Tu Z. Transcriptome analysis reveals the difference between “healthy” and “common” aging and their connection with age-related diseases. Aging Cell. 2020;19(3):e13121. https://doi.org/10.1111/acel.13121 Epub 2020 Feb 19. PMID: 32077223; PMCID: PMC7059150.
Havighorst A, Zhang Y, Farmaki E, Kaza V, Chatzistamou I, Kiaris H. Differential regulation of the unfolded protein response in outbred deer mice and susceptibility to metabolic disease. Dis Model Mech. 2019;12(2):dmm037242. doi: https://doi.org/10.1242/dmm.037242. PMID: 30733237; PMCID: PMC6398494.
Zhang Y, Lucius MD, Altomare D, Havighorst A, Farmaki E, Chatzistamou I, Shtutman M, Kiaris H. Coordination Analysis of Gene Expression Points to the Relative Impact of Different Regulators During Endoplasmic Reticulum Stress. DNA Cell Biol. 2019;38(9):969–81. https://doi.org/10.1089/dna.2019.4910 Epub 2019 Aug 6. PMID: 31355672; PMCID: PMC7061302.
Zhang Y, Chatzistamou I, Kiaris H. Identification of frailty-associated genes by coordination analysis of gene expression. Aging (Albany NY). 2020;12(5):4222–4229. doi: https://doi.org/10.18632/aging.102875. Epub 2020 Feb 29. PMID: 32112643; PMCID: PMC7093164.
Munshi-South J, Richardson JL. Peromyscus transcriptomics: Understanding adaptation and gene expression plasticity within and between species of deer mice. Semin Cell Dev Biol. 2017;61:131–139. doi:https://doi.org/10.1016/j.semcdb.2016.08.011
Vrana PB, Shorter KR, Szalai G, Felder MR, Crossland JP, Veres M, Allen JE, Wiley CD, Duselis AR, Dewey MJ, Dawson WD. Peromyscus (deer mice) as developmental models. Wiley Interdiscip Rev Dev Biol. 2014;3(3):211 – 30. doi: https://doi.org/10.1002/wdev.132. Epub 2013 Dec 3. PMID: 24896658.
Hindupur SK, Colombi M, Fuhs SR, et al. The protein histidine phosphatase LHPP is a tumour suppressor. Nature. 2018;555(7698):678–682. doi:https://doi.org/10.1038/nature26140
Wo, J. et al. The Role of Gamma-Delta T Cells in Diseases of the Central Nervous System. Front Immunol 11, 580304, doi:https://doi.org/10.3389/fimmu.2020.580304 (2020).
Southworth LK, Owen AB, Kim SK. Aging mice show a decreasing correlation of gene expression within genetic modules. PLoS Genet. 2009;5(12):e1000776. https://doi.org/10.1371/journal.pgen.1000776 Epub 2009 Dec 18. PMID: 20019809; PMCID: PMC2788246.
Boyce JM, Shone GR. Effects of ageing on smell and taste. Postgrad Med J. 2006;82(966):239–241. doi:https://doi.org/10.1136/pgmj.2005.039453
Attems J, Walker L, Jellinger KA. Olfaction and Aging: A Mini-Review. Gerontology. 2015;61(6):485–90. doi: 10.1159/000381619. Epub 2015 May 9. PMID: 25968962.
Gan KJ, Südhof TC. Specific factors in blood from young but not old mice directly promote synapse formation and NMDA-receptor recruitment. Proc Natl Acad Sci U S A. 2019;116(25):12524–12533. doi: https://doi.org/10.1073/pnas.1902672116. Epub 2019 Jun 3. PMID: 31160442; PMCID: PMC6589664.
Chavez B, Farmaki E, Zhang Y, Altomare D, Hao J, Soltnamohammadi E, Shtutman M, Chatzistamou I, Kiaris H. A strategy for the identification of paracrine regulators of cancer cell migration. Clin Exp Pharmacol Physiol. 2020;47(10):1758–1763. doi: https://doi.org/10.1111/1440-1681.13366. PMID: 32585033.