Université du Luxembourg

Supplementary Information toTREM2 triggers microglial density and age-related neuronal lossRunning title: TREM2 contributes to the aging processBettina Linnartz-Gerlach1, Liviu-Gabriel Bodea1,2, Christine Klaus1, Aurélien Ginolhac3, Rashi Halder4, Lasse Sinkkonen3, Jochen Walter5, Marco Colonna6, and Harald Neumann11Neural Regeneration, Institute of Reconstructive Neurobiology, University Hospital of Bonn, University of Bonn, 53127 Bonn, Germany2Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, St Lucia QLD 4072, Australia, Australia3Life Sciences Research Unit, University of Luxembourg, L-4367 Belvaux, Luxembourg4Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4365 Esch-sur-Alzette, Luxembourg5Department of Neurology, University Bonn, 53127 Bonn, Germany6Washington University School of Medicine, Department of Pathology & Immunology, St. Louis, MO 63110, USAMethodsRNA sequencing. Twelve samples were prepared: 6 TREM2 wt and 6 TREM2 KOs. Sequencing library preparation was done with 1??g of total RNA using the TruSeq mRNA Stranded Library Prep Kit (Illumina, USA) according to manufacturer’s protocol. Briefly, the mRNA pull down was done using the magnetic beads with oligo-dT primer. Fragmented RNA was reverse transcribed, and second strand synthesis was done with incorporation of dUTP so that during PCR amplification only first strand was amplified. The libraries were quantified using Qubit dsDNA HS assay kit (Thermo Fisher Scientific, USA) and the quality was determined using 2100 Bioanalyzer (Agilent, USA). Pooled libraries were sequenced on NextSeq500 using manufacturer’s instructions. After sequencing, reads were processed on the High Performance Computer of the University of Luxembourg ADDIN EN.CITE <EndNote><Cite><Author>Varrette</Author><Year>2014</Year><RecNum>2423</RecNum><DisplayText>(Varrette, Bouvry, Cartiaux, & Georgatos, 2014)</DisplayText><record><rec-number>2423</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1511172335">2423</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Varrette, S.</author><author>Bouvry, P.</author><author>Cartiaux, H.</author><author>Georgatos, F.</author></authors></contributors><titles><title>Management of an academic HPC cluster: The UL experience</title><secondary-title>2014 International Conference on High Performance Computing & Simulation (HPCS)</secondary-title></titles><periodical><full-title>2014 International Conference on High Performance Computing & Simulation (HPCS)</full-title></periodical><pages>959-967</pages><dates><year>2014</year></dates><accession-num>107</accession-num><urls></urls><electronic-resource-num>10.1109/HPCSim.2014.6903792</electronic-resource-num></record></Cite></EndNote>(Varrette, Bouvry, Cartiaux, & Georgatos, 2014). Reads quality was assessed using FastQC (v0.11 ). Due to a slight loss of base qualities observed at the read ends, reads were trimmed using AdapterRemoval [v2.2 ADDIN EN.CITE <EndNote><Cite><Author>Schubert</Author><Year>2016</Year><RecNum>2424</RecNum><DisplayText>(Schubert, Lindgreen, & Orlando, 2016)</DisplayText><record><rec-number>2424</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1511174516">2424</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Schubert, M.</author><author>Lindgreen, S.</author><author>Orlando, L.</author></authors></contributors><auth-address>Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350, Copenhagen, Denmark. MikkelSch@.Department of Biology, Section for Computational and RNA Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200, Copenhagen, Denmark. stinus.lindgreen@.Carlsberg Research Laboratory, Gamle Carlsberg Vej 4-10, 1799, Copenhagen, Denmark. stinus.lindgreen@.Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350, Copenhagen, Denmark. Lorlando@snm.ku.dk.Laboratoire AMIS, Universite de Toulouse, University Paul Sabatier (UPS), CNRS UMR 5288, 37 Allees Jules Guesde, 31000, Toulouse, France. Lorlando@snm.ku.dk.</auth-address><titles><title>AdapterRemoval v2: rapid adapter trimming, identification, and read merging</title><secondary-title>BMC Res Notes</secondary-title></titles><periodical><full-title>BMC Res Notes</full-title></periodical><pages>88</pages><volume>9</volume><keywords><keyword>*Algorithms</keyword><keyword>Base Sequence</keyword><keyword>High-Throughput Nucleotide Sequencing/*methods</keyword></keywords><dates><year>2016</year><pub-dates><date>Feb 12</date></pub-dates></dates><isbn>1756-0500 (Electronic)1756-0500 (Linking)</isbn><accession-num>116</accession-num><urls><related-urls><url>;(Schubert, Lindgreen, & Orlando, 2016)]. Genome indexing was done with the mouse reference mm10 (GRCm38.p3) with the ensembl gene annotation version 79 for the STAR aligner [v2.5.2b ADDIN EN.CITE <EndNote><Cite><Author>Dobin</Author><Year>2013</Year><RecNum>2425</RecNum><DisplayText>(Dobin et al., 2013)</DisplayText><record><rec-number>2425</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1511174747">2425</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Dobin, A.</author><author>Davis, C. A.</author><author>Schlesinger, F.</author><author>Drenkow, J.</author><author>Zaleski, C.</author><author>Jha, S.</author><author>Batut, P.</author><author>Chaisson, M.</author><author>Gingeras, T. R.</author></authors></contributors><auth-address>Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. dobin@cshl.edu</auth-address><titles><title>STAR: ultrafast universal RNA-seq aligner</title><secondary-title>Bioinformatics</secondary-title></titles><periodical><full-title>Bioinformatics</full-title></periodical><pages>15-21</pages><volume>29</volume><number>1</number><keywords><keyword>Algorithms</keyword><keyword>Cluster Analysis</keyword><keyword>Gene Expression Profiling</keyword><keyword>Genome, Human</keyword><keyword>Humans</keyword><keyword>RNA Splicing</keyword><keyword>Sequence Alignment/*methods</keyword><keyword>Sequence Analysis, RNA/methods</keyword><keyword>*Software</keyword></keywords><dates><year>2013</year><pub-dates><date>Jan 01</date></pub-dates></dates><isbn>1367-4811 (Electronic)1367-4803 (Linking)</isbn><accession-num>117</accession-num><urls><related-urls><url>;(Dobin et al., 2013)], setting the option --sjdbOverhang to 78. Mapping was then performed with the following command, using tweaked options suggested by Barruzo et al. ADDIN EN.CITE <EndNote><Cite><Author>Baruzzo</Author><Year>2017</Year><RecNum>2433</RecNum><DisplayText>(Baruzzo et al., 2017)</DisplayText><record><rec-number>2433</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1513086723">2433</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Baruzzo, G.</author><author>Hayer, K. E.</author><author>Kim, E. J.</author><author>Di Camillo, B.</author><author>FitzGerald, G. A.</author><author>Grant, G. R.</author></authors></contributors><titles><title>Simulation-based comprehensive benchmarking of RNA-seq aligners</title><secondary-title>Nat Methods</secondary-title></titles><periodical><full-title>Nat Methods</full-title></periodical><pages>135-139</pages><volume>14</volume><number>2</number><edition>2016 Dec 12</edition><dates><year>2017</year></dates><accession-num>136</accession-num><urls><related-urls><url>pdf</url></related-urls></urls><electronic-resource-num>doi: 10.1038/nmeth.4106</electronic-resource-num></record></Cite></EndNote>(Baruzzo et al., 2017): STAR --twopassMode Basic --outSAMunmapped Within --limitOutSJcollapsed 1000000 --limitSjdbInsertNsj 1000000 --outFilterMultimapNmax 100 --outFilterMismatchNmax 33 --outFilterMismatchNoverLmax 0.3 --seedSearchStartLmax 12 --alignSJoverhangMin 15 --alignEndsType Local --outFilterMatchNminOverLread 0 --outFilterScoreMinOverLread 0.3 --winAnchorMultimapNmax 50 --alignSJDBoverhangMin 3 --outFilterType BySJout --outSAMtype BAM SortedByCoordinate (mapping statistics provided by the STAR log files see supplementary table 1).Transcript counts were obtained from the BAM files by the R package?Rsubread [v1.26 ADDIN EN.CITE <EndNote><Cite><Author>Liao</Author><Year>2013</Year><RecNum>2426</RecNum><DisplayText>(Liao, Smyth, & Shi, 2013)</DisplayText><record><rec-number>2426</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1511175997">2426</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Liao, Y.</author><author>Smyth, G. K.</author><author>Shi, W.</author></authors></contributors><auth-address>Division of Bioinformatics, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia.</auth-address><titles><title>The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote</title><secondary-title>Nucleic Acids Res</secondary-title></titles><periodical><full-title>Nucleic Acids Res</full-title><abbr-1>Nucleic acids research</abbr-1></periodical><pages>e108</pages><volume>41</volume><number>10</number><keywords><keyword>Exons</keyword><keyword>Genomics</keyword><keyword>*High-Throughput Nucleotide Sequencing</keyword><keyword>INDEL Mutation</keyword><keyword>Sequence Alignment/*methods</keyword><keyword>*Software</keyword></keywords><dates><year>2013</year><pub-dates><date>May 01</date></pub-dates></dates><isbn>1362-4962 (Electronic)0305-1048 (Linking)</isbn><accession-num>125</accession-num><urls><related-urls><url>;(Liao, Smyth, & Shi, 2013)] using R [v3.3 ADDIN EN.CITE <EndNote><Cite><Author>Team</Author><Year>2017</Year><RecNum>2427</RecNum><DisplayText>(R Core Team, 2017)</DisplayText><record><rec-number>2427</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1511176308">2427</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>R Core Team,</author></authors></contributors><titles><title>R: A language and environment for statistical computing</title><secondary-title>R Foundation for Statistical Computing, Vienna, Austria</secondary-title></titles><periodical><full-title>R Foundation for Statistical Computing, Vienna, Austria</full-title></periodical><volume>URL: ;(R Core Team, 2017)]. Next, computation and plotting were done with R and Rstudio ADDIN EN.CITE <EndNote><Cite><Author>RStudio Team</Author><Year>2016</Year><RecNum>2428</RecNum><DisplayText>(RStudio Team, 2016)</DisplayText><record><rec-number>2428</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1511176592">2428</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>RStudio Team,</author></authors></contributors><titles><title>RStudio: Integrated Development for R</title><secondary-title>RStudio, Inc, Boston, MA</secondary-title></titles><periodical><full-title>RStudio, Inc, Boston, MA</full-title></periodical><volume>URL: ;(RStudio Team, 2016). The differential expression analysis was performed by the R package DESeq2 [v1.15 ADDIN EN.CITE <EndNote><Cite><Author>Love</Author><Year>2014</Year><RecNum>2429</RecNum><DisplayText>(Love, Huber, & Anders, 2014)</DisplayText><record><rec-number>2429</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1511176712">2429</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Love, M. I.</author><author>Huber, W.</author><author>Anders, S.</author></authors></contributors><titles><title>Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2</title><secondary-title>Genome Biol</secondary-title></titles><periodical><full-title>Genome Biol</full-title></periodical><pages>550</pages><volume>15</volume><number>12</number><keywords><keyword>Algorithms</keyword><keyword>Computational Biology/*methods</keyword><keyword>High-Throughput Nucleotide Sequencing</keyword><keyword>Models, Genetic</keyword><keyword>RNA/*analysis</keyword><keyword>Sequence Analysis, RNA</keyword><keyword>*Software</keyword></keywords><dates><year>2014</year></dates><isbn>1474-760X (Electronic)1474-7596 (Linking)</isbn><accession-num>132</accession-num><urls><related-urls><url>;(Love, Huber, & Anders, 2014)] with the contrast wt versus TREM2 KO. Transcript annotations were retrieved from ensembl (archive from March 2015) with the R bioconductor package biomaRt [v2.34 ADDIN EN.CITE <EndNote><Cite><Author>Durinck</Author><Year>2009</Year><RecNum>2430</RecNum><DisplayText>(Durinck, Spellman, Birney, & Huber, 2009)</DisplayText><record><rec-number>2430</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1511176840">2430</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Durinck, S.</author><author>Spellman, P. T.</author><author>Birney, E.</author><author>Huber, W.</author></authors></contributors><auth-address>Lawrence Berkeley National Laboratory, Berkeley, CA, USA. steffen@stat.berkeley.edu</auth-address><titles><title>Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt</title><secondary-title>Nat Protoc</secondary-title></titles><periodical><full-title>Nat Protoc</full-title></periodical><pages>1184-91</pages><volume>4</volume><number>8</number><keywords><keyword>Cell Line</keyword><keyword>*Chromosome Mapping</keyword><keyword>Cluster Analysis</keyword><keyword>Databases, Genetic</keyword><keyword>Genomics/*methods</keyword><keyword>Humans</keyword><keyword>RNA, Messenger/metabolism</keyword><keyword>*Software</keyword></keywords><dates><year>2009</year></dates><isbn>1750-2799 (Electronic)1750-2799 (Linking)</isbn><accession-num>133</accession-num><urls><related-urls><url>;(Durinck, Spellman, Birney, & Huber, 2009)].Plots were done using the R package?ggplot2?[v2.1 ADDIN EN.CITE <EndNote><Cite><Author>Wickham</Author><Year>2009</Year><RecNum>2431</RecNum><DisplayText>(Wickham, 2009)</DisplayText><record><rec-number>2431</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1511177021">2431</key></foreign-keys><ref-type name="Book">6</ref-type><contributors><authors><author>Wickham, H.</author></authors></contributors><titles><title><style face="italic" font="default" size="100%">ggplot2</style><style face="normal" font="default" size="100%">: Elegant Graphics for Data Analysis</style></title></titles><dates><year>2009</year></dates><publisher>Spinger-Verlag New York</publisher><accession-num>134</accession-num><urls></urls></record></Cite></EndNote>(Wickham, 2009)] and the collection of R packages?tidyverse?[v1.1 ADDIN EN.CITE <EndNote><Cite><Author>Wickham</Author><Year>2017</Year><RecNum>2432</RecNum><DisplayText>(Wickham, 2017)</DisplayText><record><rec-number>2432</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1511177568">2432</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Wickham, H.</author></authors></contributors><titles><title>tidyverse: Easily Install and Load ?Tidyverse` Packages.</title><secondary-title>R package version 1.1.1</secondary-title></titles><periodical><full-title>R package version 1.1.1</full-title></periodical><volume>URL: ;(Wickham, 2017)]. Raw FASTQ and BAM files have been deposited in the European Nucleotide Archive (ENA accession number: PRJEB23660).Pathway enrichment analysis. For Ingenuity Pathway Analysis (IPA), list of differentially expressed genes (log2FC>0.5, FDR<0.05) in TREM2 KO mice compared to the wt mice were uploaded in the IPA tool (Ingenuity Systems, ). The significance of the association between each list and function or canonical pathway was measured by Fisher’s exact test.Oligonucleotides for sqRT PCR. 18S forward (for) – CTCAACACGGGAAACCTCAC; 18S reverse (rev) – CGCTCCACCAACTAAGAACG ADDIN EN.CITE <EndNote><Cite><Author>Lin</Author><Year>2013</Year><RecNum>2453</RecNum><DisplayText>(Lin et al., 2013)</DisplayText><record><rec-number>2453</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1534248816">2453</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Lin, P.</author><author>Lan, X.</author><author>Chen, F.</author><author>Yang, Y.</author><author>Jin, Y.</author><author>Wang, A.</author></authors></contributors><auth-address>Key Laboratory of Animal Biotechnology of the Ministry of Agriculture, Northwest A&F University, Yangling, Shaanxi, China. pflin2001n@</auth-address><titles><title>Reference gene selection for real-time quantitative PCR analysis of the mouse uterus in the peri-implantation period</title><secondary-title>PLoS One</secondary-title></titles><periodical><full-title>PLoS One</full-title></periodical><pages>e62462</pages><volume>8</volume><number>4</number><keywords><keyword>Animals</keyword><keyword>Computational Biology/methods</keyword><keyword>Embryo Implantation/*genetics</keyword><keyword>Female</keyword><keyword>*Gene Expression Profiling</keyword><keyword>*Gene Expression Regulation</keyword><keyword>Male</keyword><keyword>Mice</keyword><keyword>Pregnancy</keyword><keyword>Uterus/*metabolism</keyword></keywords><dates><year>2013</year></dates><isbn>1932-6203 (Electronic)1932-6203 (Linking)</isbn><accession-num>875</accession-num><urls><related-urls><url>pdf</url><url>;(Lin et al., 2013); Aif1 for – GAAGCGAATGCTGGAGAAAC; Aif1 rev – AAGATGGCAGATCTCTTGCC; beta-Actin for – GGCTGTATTCCCCTCCATCG; beta-Actin rev – CCAGTTGGTAACAATGCCATGT ADDIN EN.CITE <EndNote><Cite><Author>Ruiz-Villalba</Author><Year>2017</Year><RecNum>2454</RecNum><DisplayText>(Ruiz-Villalba et al., 2017)</DisplayText><record><rec-number>2454</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="1534249100">2454</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Ruiz-Villalba, A.</author><author>Mattiotti, A.</author><author>Gunst, Q. D.</author><author>Cano-Ballesteros, S.</author><author>van den Hoff, M. J.</author><author>Ruijter, J. M.</author></authors></contributors><auth-address>Department of Anatomy, Embryology and Physiology, Academic Medical Center, Amsterdam, The Netherlands.Cell Therapy, Foundation of Applied Medical Research (FIMA), University of Navarra, Pamplona, Spain.Department of Animal Biology, University of Malaga, Malaga, Spain.Department of Anatomy, Embryology and Physiology, Academic Medical Center, Amsterdam, The Netherlands. j.m.ruijter@amc.uva.nl.</auth-address><titles><title>Reference genes for gene expression studies in the mouse heart</title><secondary-title>Sci Rep</secondary-title></titles><periodical><full-title>Sci Rep</full-title><abbr-1>Scientific reports</abbr-1></periodical><pages>24</pages><volume>7</volume><number>1</number><dates><year>2017</year><pub-dates><date>Feb 2</date></pub-dates></dates><isbn>2045-2322 (Electronic)2045-2322 (Linking)</isbn><accession-num>881</accession-num><urls><related-urls><url>pdf</url><url>;(Ruiz-Villalba et al., 2017); C1qa for – AGAGGGGAGCCAGGAGC; C1qa rev – CTTTCACGCCCTTCAGTCCT; C1qb for – GACTTCCGCTTTCTGAGGACA; C1qb rev – CAGGGGCTTCCTGTGTATGGA; C1qc for - GCCTGAAGTCCCTTACACCC; C1qc rev – GGGATTCCTGGCTCTCCCTT; C3 for – TAGTGCTACTGCTGCTGTTGGC; C3 rev – GCTGGAATCTTGATGGAGACGCTT ADDIN EN.CITE <EndNote><Cite><Author>Linnartz</Author><Year>2012</Year><RecNum>2003</RecNum><DisplayText>(Linnartz, Kopatz, Tenner, & Neumann, 2012)</DisplayText><record><rec-number>2003</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="0">2003</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Linnartz, B.</author><author>Kopatz, J.</author><author>Tenner, A.J.</author><author>Neumann, H.</author></authors></contributors><titles><title>Sialic acid on the neuronal glycocalyx prevents complement C1 binding and complement receptor-3 mediated removal by microglia</title><secondary-title>J Neurosci</secondary-title></titles><periodical><full-title>J Neurosci</full-title></periodical><pages>946-952</pages><volume>32</volume><number>3</number><dates><year>2012</year><pub-dates><date>18th January 2012</date></pub-dates></dates><accession-num>1993</accession-num><urls></urls></record></Cite></EndNote>(Linnartz, Kopatz, Tenner, & Neumann, 2012); C4b for – TGGAGGACAAGGACGGCTA; C4b rev – GGCCCTAACCCTGAGCTGA ADDIN EN.CITE <EndNote><Cite><Author>Haga</Author><Year>1996</Year><RecNum>1793</RecNum><DisplayText>(Haga, Aizawa, Ishii, & Ikeda, 1996)</DisplayText><record><rec-number>1793</rec-number><foreign-keys><key app="EN" db-id="t0trvda9p2txalers5wp9xsttwavsxzrdxdw" timestamp="0">1793</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Haga, S.</author><author>Aizawa, T.</author><author>Ishii, T.</author><author>Ikeda, K.</author></authors></contributors><auth-address>Department of Ultrastructure and Histochemistry, Tokyo Institute of Psychiatry, Japan.</auth-address><titles><title>Complement gene expression in mouse microglia and astrocytes in culture: comparisons with mouse peritoneal macrophages</title><secondary-title>Neurosci Lett</secondary-title></titles><periodical><full-title>Neurosci Lett</full-title></periodical><pages>191-4</pages><volume>216</volume><number>3</number><keywords><keyword>Animals</keyword><keyword>Astrocytes/*physiology</keyword><keyword>Base Sequence</keyword><keyword>Complement System Proteins/*genetics</keyword><keyword>Interferon-gamma/pharmacology</keyword><keyword>Macrophages, Peritoneal/*physiology</keyword><keyword>Mice</keyword><keyword>Microglia/*physiology</keyword><keyword>Molecular Sequence Data</keyword><keyword>RNA, Messenger/drug effects/*metabolism</keyword></keywords><dates><year>1996</year><pub-dates><date>Oct 4</date></pub-dates></dates><accession-num>1795</accession-num><urls><related-urls><url>pdf</url><url> </url></related-urls></urls></record></Cite></EndNote>(Haga, Aizawa, Ishii, & Ikeda, 1996); Cd68 for – CAGGGAGGTTGTGACGGTAC; Cd68 rev – GAAACATGGCCCGAAGTATC; Cyba for – CCTCCACTTCCTGTTGTCGG; Cyba rev – TCACTCGGCTTCTTTCGGAC; Cybb for – GGGAACTGGGCTGTGAATGA; Cybb rev – CAGTGCTGACCCAAGGAGTT; Dap12 for – ATGGGGGCTCTGGAGCCCT; Dap12 rev – TCATCTGTAATATTGCCTCTGTGT; Fcer1g for – CTGTCTACACGGGCCTGAAC; Fcer1g rev – AAAGAATGCAGCCAAGCACG; Gapdh for – AACTTTGGCATTGTGGAAGG; Gapdh rev – GGATGCAGGGATGATGTTCT; Il-1β for – CTTCCTTGTGCAAGTGTCTG; Il-1β rev – CAGGTCATTCTCATCACTGTC; Inos for – AAGCCCCGCTACTACTCCAT; Inos rev – GCTTCAGGTTCCTGATCCAA; Itgam for – CATCAAGGGCAGCCAGATTG; Itgam rev – GAGGCAAGGGACACACTGAC; Itgb2 for – GTCCCAGGAATGCACCAAGT; Itgb2 rev – CCGTTGGTCGAACTCAGGAT; Rpl13a for – TGGTCCCTGCTGCTCTCA; Rpl13a rev – CCCCAGGTAAGCAAACTTTCT PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Cb3V2eS1MaWl2cmFuZDwvQXV0aG9yPjxZZWFyPjIwMTQ8

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ADDIN EN.CITE.DATA (Bennett et al., 2016); Tnfα for – GGTGCCTATGTCTCAGCCTC; Tnfα rev – TGAGGGTCTGGGCCATAGAA.References ADDIN EN.REFLIST Baruzzo, G., Hayer, K. E., Kim, E. J., Di Camillo, B., FitzGerald, G. A., & Grant, G. R. (2017). Simulation-based comprehensive benchmarking of RNA-seq aligners. Nat Methods, 14(2), 135-139. doi:doi: 10.1038/nmeth.4106Bennett, M. L., Bennett, F. C., Liddelow, S. A., Ajami, B., Zamanian, J. L., Fernhoff, N. B., . . . Barres, B. A. (2016). New tools for studying microglia in the mouse and human CNS. Proc Natl Acad Sci U S A, 113(12), E1738-1746. doi:10.1073/pnas.1525528113Bouvy-Liivrand, M., Heinaniemi, M., John, E., Schneider, J. G., Sauter, T., & Sinkkonen, L. (2014). Combinatorial regulation of lipoprotein lipase by microRNAs during mouse adipogenesis. RNA Biol, 11(1), 76-91. doi:10.4161/rna.27655Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., . . . Gingeras, T. R. (2013). STAR: ultrafast universal RNA-seq aligner. Bioinformatics, 29(1), 15-21. doi:10.1093/bioinformatics/bts635Durinck, S., Spellman, P. T., Birney, E., & Huber, W. (2009). Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nat Protoc, 4(8), 1184-1191. doi:10.1038/nprot.2009.97Haga, S., Aizawa, T., Ishii, T., & Ikeda, K. (1996). Complement gene expression in mouse microglia and astrocytes in culture: comparisons with mouse peritoneal macrophages. Neurosci Lett, 216(3), 191-194. Liao, Y., Smyth, G. K., & Shi, W. (2013). The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote. Nucleic Acids Res, 41(10), e108. doi:10.1093/nar/gkt214Lin, P., Lan, X., Chen, F., Yang, Y., Jin, Y., & Wang, A. (2013). Reference gene selection for real-time quantitative PCR analysis of the mouse uterus in the peri-implantation period. PLoS One, 8(4), e62462. doi:10.1371/journal.pone.0062462Linnartz, B., Kopatz, J., Tenner, A. J., & Neumann, H. (2012). Sialic acid on the neuronal glycocalyx prevents complement C1 binding and complement receptor-3 mediated removal by microglia. J Neurosci, 32(3), 946-952. Love, M. I., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol, 15(12), 550. doi:10.1186/s13059-014-0550-8R Core Team. (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, URL: . RStudio Team. (2016). RStudio: Integrated Development for R. RStudio, Inc, Boston, MA, URL: . Ruiz-Villalba, A., Mattiotti, A., Gunst, Q. D., Cano-Ballesteros, S., van den Hoff, M. J., & Ruijter, J. M. (2017). Reference genes for gene expression studies in the mouse heart. Sci Rep, 7(1), 24. doi:10.1038/s41598-017-00043-9Schubert, M., Lindgreen, S., & Orlando, L. (2016). AdapterRemoval v2: rapid adapter trimming, identification, and read merging. BMC Res Notes, 9, 88. doi:10.1186/s13104-016-1900-2Varrette, S., Bouvry, P., Cartiaux, H., & Georgatos, F. (2014). Management of an academic HPC cluster: The UL experience. 2014 International Conference on High Performance Computing & Simulation (HPCS), 959-967. doi:10.1109/HPCSim.2014.6903792Wickham, H. (2009). ggplot2: Elegant Graphics for Data Analysis: Spinger-Verlag New York.Wickham, H. (2017). tidyverse: Easily Install and Load ?Tidyverse` Packages. R package version 1.1.1, URL: . Supplementary tableSupplementary table 1: Mapping statistics using the STAR aligner (according to STAR statistics)sample# input reads# uniquely mapped readsuniquely mapped reads (%)average length (bp)KO0139,300,66036,954,17194.0377.85KO0240,106,76437,800,64794.2577.63KO0343,838,95041,176,16593.9377.38KO0437,475,81735,234,85394.0277.79KO0540,037,05437,717,59894.2177.96KO0638,943,35736,666,64094.1577.79WT0138,993,18736,707,25894.1478.04WT0238,378,21736,030,25293.8877.94WT0334,722,07932,635,36893.9977.26WT0438,172,96135,963,93694.2178WT0540,225,27337,903,71394.2377.79WT0642,881,49640,336,77994.0778Total473,075,815445,127,380NANASupplementary FiguresFigure S1: Comparison of housekeeping gene transcripts between TREM2 KO mice and littermate controls. A Vulcano plot showing all genes (each dot respresents a transcript; (log2FoldChange (FC) versus –log10[adjusted p-value])) as identified by RNA-seq analysis in half brain samples of TREM2 KO mice. Genes with abs(log2FC)≥0.5 and adjusted p-value (padj)<0.05 are highlighted in orange. Moreover, the three housekeeping genes Gapdh, beta-Actin (Actb) and Rpl13a are labelled in red, showing that they are very stable between the two conditions (Gapdh: padj=0.87; Actb: padj=0.73; Rpl13a: padj=0.99). n=6 mice per group. B Semi-quantitative real-time (sqRT) PCR of the housekeeping genes Gapdh, beta-Actin, 18S and Rpl13a in half brains of 24?months old TREM2 wt and KO mice. None of the investigated housekeeping genes shows differences in the cycle threshold in-between TREM2 wt and KO mice. Data are presented as mean+s.e.m. n=5-6 mice per group. n.s. not significant.Figure S2: Less age-related neuronal loss in TREM2 KO mice. Quantification of the width of hippocampal dentate gyrus (DG, left) and CA3 (right) of 3, 12 and 24?months old TREM2 wildtype (wt) versus knock-out (KO) mice showed an increased DG and CA3 width in 24?months old TREM2 KO mice. n=6-12 mice per group. Data are presented as mean±s.e.m. Values were normalized to 3?months old wt animals. Multiple linear regression model with post hoc LSD; *?p≤0.05; ***?p≤0.001; n.s. not significant.Figure S3: Genes, molecules and pathways differentially regulated in aged TREM2 KO mice. A Plot demonstrates the 211 differentially expressed (DE) genes (log2FC>0.5, FDR<0.05) identified by RNA-seq analysis in half brain samples of TREM2 KO mice that were used for Ingenuity Pathway Analysis (IPA) in panels B-D. The genes are listed according to their fold change in TREM2 KO mice. Genes of particular interest are highlighted. The bars indicate the fold change in log2-scale and circles are color-coded according to statistical significance of the expression change (adjusted p-value, Benjamini-Hochberg correction). n=6 mice per group. B The top six canonical pathways with highest enrichment for the DE genes in TREM2 KO include the complement system and the production of nitric oxide and reactive oxygen species in macrophages. C Among the top five molecular and cellular functions as revealed by IPA are cell-to-cell signaling and interaction, and cellular function and maintenance. D The top six upstream regulators predicted by IPA to control DE genes in TREM2 KO are ifnγ, tnfα, il4, il-1?, il6 and ifnα. The predicted mode of regulation is inhibition. The significance of the enrichments was derived using Fisher?s exact test and are shown as -log(p-value). ................
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