Dditional file 1: Figure S1. Comparison of all pairwise gene expression sets.
Dditional file 1: Figure S1. Comparison of all pairwise gene expression sets. Figure S2. qPCR controls. Table S1. Cell-specific gene lists from Zhang et al. Table S2. Cell-specific gene lists from Zeisel et al. Table S3. Microglial gene lists from Hickman et al. Table S4. Gene Expression Assays. Table S5. Primary and secondary antibodies. Table S6. Transcripts differentially expressed with age. Table S7. PubMed ID:http://www.ncbi.nlm.nih.gov/pubmed/25432023 Pathway, regulator and function changes with aging. Table S8. Transcripts differentially expressed between sexes. Table S9. Pathway, regulator and function differences between sexes. Table S10. Sex difference pathways, processes, and regulators. (ZIP 1133 kb)Abbreviations BHMTC: Benjamini ochberg multiple testing correction; SNK: Student?Newman euls Acknowledgements The authors thank the Genome Sciences Facility at the Penn State Hershey College of Medicine for microarray and quantitative PCR assistance, Wendy Holtry for helping execute all perfusion protocols, Dr. Benjamin Barres for graciously providing the C1q IHC antibody, the Penn State Microscopy and Cytometry Facility–University Park, PA, and Byron Bluth for assistance with the figure preparation. The authors declare no financial conflicts of interest. Funding This work was supported by the Donald W. Reynolds Foundation, the National Institute on Aging (R01AG026607, P30AG050911, F31AG038285), National Eye Institute (R01EY021716, R21EY024520, T32EY023202), and Oklahoma Center for Advancement of Science and Technology (HR14-174). Availability of data and materials All data generated or analyzed during this study are included in this published article: additional files and raw sequencing data are available from the Gene Expression Omnibus (GEO) #GSE85084. Authors’ contributions CAM designed the studies with WMF and WES and in conjunction with BW, DRM, GVB, MD, MMF, and RMB who performed the A-836339MedChemExpress A-836339 animal studies and molecular and biochemical experiments. DRS, NH, and WMF performed bioinformatic analyses. CAM and WMF wrote the manuscript with editing from all other authors. All authors read and approved the final manuscript. Ethics approval Animal studies were conducted with approval of the Penn State University Institutional Animal Use Committee. Consent for publication Not applicableReferences 1. Kennedy BK, Berger SL, Brunet A, Campisi J, Cuervo AM, Epel ES, Franceschi C, Lithgow GJ, Morimoto RI, Pessin JE, et al. Geroscience: linking aging to chronic disease. Cell. 2014;159(4):709?3. 2. Berchtold NC, Cribbs DH, Coleman PD, Rogers J, Head E, Kim R, Beach T, Miller C, Troncoso J, Trojanowski JQ, et al. Gene expression changes in the course of normal brain aging are sexually dimorphic. Proc Natl Acad Sci U S A. 2008;105(40):15605?0. 3. Blalock EM, Grondin R, Chen KC, Thibault O, Thibault V, Pandya JD, Dowling A, Zhang Z, Sullivan P, Porter NM, et al. Aging-related gene expression in hippocampus proper compared with dentate gyrus is selectively associated with metabolic syndrome variables in rhesus monkeys. J Neurosci. 2010; 30(17):6058?1. 4. Kadish I, Thibault O, Blalock EM, Chen KC, Gant JC, Porter NM, Landfield PW. Hippocampal and cognitive aging across the lifespan: a bioenergetic shift precedes and increased cholesterol trafficking parallels memory impairment. J Neurosci. 2009;29(6):1805?6. 5. Masser DR, Bixler GV, Brucklacher RM, Yan H, Giles CB, Wren JD, Sonntag WE, Freeman WM. Hippocampal subregions exhibit both distinct and shared transcriptomic responses to aging and nonneurodege.
