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• W2520696572 abstract "•RNA-seq of 124 unfractionated tissue samples from 32 different organs was analyzed•Human pan-endothelial enriched transcripts across vascular beds were identified•Relative expression profile was maintained in early passage cultured cells•Analysis method is applicable to profile other body-wide expressed cell types Endothelial cells line blood vessels and regulate hemostasis, inflammation, and blood pressure. Proteins critical for these specialized functions tend to be predominantly expressed in endothelial cells across vascular beds. Here, we present a systems approach to identify a panel of human endothelial-enriched genes using global, body-wide transcriptomics data from 124 tissue samples from 32 organs. We identified known and unknown endothelial-enriched gene transcripts and used antibody-based profiling to confirm expression across vascular beds. The majority of identified transcripts could be detected in cultured endothelial cells from various vascular beds, and we observed maintenance of relative expression in early passage cells. In summary, we describe a widely applicable method to determine cell-type-specific transcriptome profiles in a whole-organism context, based on differential abundance across tissues. We identify potential vascular drug targets or endothelial biomarkers and highlight candidates for functional studies to increase understanding of the endothelium in health and disease. Endothelial cells line blood vessels and regulate hemostasis, inflammation, and blood pressure. Proteins critical for these specialized functions tend to be predominantly expressed in endothelial cells across vascular beds. Here, we present a systems approach to identify a panel of human endothelial-enriched genes using global, body-wide transcriptomics data from 124 tissue samples from 32 organs. We identified known and unknown endothelial-enriched gene transcripts and used antibody-based profiling to confirm expression across vascular beds. The majority of identified transcripts could be detected in cultured endothelial cells from various vascular beds, and we observed maintenance of relative expression in early passage cells. In summary, we describe a widely applicable method to determine cell-type-specific transcriptome profiles in a whole-organism context, based on differential abundance across tissues. We identify potential vascular drug targets or endothelial biomarkers and highlight candidates for functional studies to increase understanding of the endothelium in health and disease. Endothelial cells (ECs) line the inside of all vessels and have a critical role in the regulation of hemostasis, inflammation, defense against blood borne pathogens, vascular tone, angiogenesis, and the transport of molecules and nutrients to and from the blood stream (Pober and Sessa, 2007Pober J.S. Sessa W.C. Evolving functions of endothelial cells in inflammation.Nat. Rev. Immunol. 2007; 7: 803-815Crossref PubMed Scopus (954) Google Scholar, Vita, 2011Vita J.A. Endothelial function.Circulation. 2011; 124: e906-e912Crossref PubMed Scopus (149) Google Scholar). The involvement of ECs in multiple disease states, such as coronary artery disease, venous thromboembolism, edema, and vasculitis is well recognized (Ganz and Hsue, 2013Ganz P. Hsue P.Y. Endothelial dysfunction in coronary heart disease is more than a systemic process.Eur. Heart J. 2013; 34: 2025-2027Crossref PubMed Scopus (15) Google Scholar, Mackman, 2012Mackman N. New insights into the mechanisms of venous thrombosis.J. Clin. Invest. 2012; 122: 2331-2336Crossref PubMed Scopus (186) Google Scholar, Steyers and Miller, 2014Steyers 3rd, C.M. Miller Jr., F.J. Endothelial dysfunction in chronic inflammatory diseases.Int. J. Mol. Sci. 2014; 15: 11324-11349Crossref PubMed Scopus (241) Google Scholar, Tabas et al., 2015Tabas I. García-Cardeña G. Owens G.K. Recent insights into the cellular biology of atherosclerosis.J. Cell Biol. 2015; 209: 13-22Crossref PubMed Scopus (487) Google Scholar). ECs from different vascular beds can vary in their gene expression profile, reflecting organ-specific functions and even morphologically similar ECs can show differences in gene expression (Aird, 2012Aird W.C. Endothelial cell heterogeneity.Cold Spring Harb Perspect Med. 2012; 2: a006429Crossref Scopus (360) Google Scholar, Civelek et al., 2011Civelek M. Manduchi E. Riley R.J. Stoeckert Jr., C.J. Davies P.F. Coronary artery endothelial transcriptome in vivo: Identification of endoplasmic reticulum stress and enhanced reactive oxygen species by gene connectivity network analysis.Circ Cardiovasc Genet. 2011; 4: 243-252Crossref PubMed Scopus (44) Google Scholar, Nolan et al., 2013Nolan D.J. Ginsberg M. Israely E. Palikuqi B. Poulos M.G. James D. Ding B.S. Schachterle W. Liu Y. Rosenwaks Z. et al.Molecular signatures of tissue-specific microvascular endothelial cell heterogeneity in organ maintenance and regeneration.Dev. Cell. 2013; 26: 204-219Abstract Full Text Full Text PDF PubMed Scopus (349) Google Scholar, Seaman et al., 2007Seaman S. Stevens J. Yang M.Y. Logsdon D. Graff-Cherry C. St Croix B. Genes that distinguish physiological and pathological angiogenesis.Cancer Cell. 2007; 11: 539-554Abstract Full Text Full Text PDF PubMed Scopus (304) Google Scholar). Known genes with largely EC-restricted expression across tissue beds are important for vascular stability (Du Toit, 2015Du Toit A. Mechanotransduction: VE-cadherin lets it flow.Nat. Rev. Mol. Cell Biol. 2015; 16 (268–268)Google Scholar) or cell-specific functions, for example, in inflammatory processes (Ley, 2003Ley K. The role of selectins in inflammation and disease.Trends Mol. Med. 2003; 9: 263-268Abstract Full Text Full Text PDF PubMed Scopus (492) Google Scholar) or hemostasis (Lenting et al., 2015Lenting P.J. Christophe O.D. Denis C.V. von Willebrand factor biosynthesis, secretion, and clearance: Connecting the far ends.Blood. 2015; 125: 2019-2028Crossref PubMed Scopus (166) Google Scholar). Recently there have been significant technological advancements in large-scale analysis of cellular gene expression profiles (Spies and Ciaudo, 2015Spies D. Ciaudo C. Dynamics in transcriptomics: Advancements in RNA-seq time course and downstream analysis.Comput. Struct. Biotechnol. J. 2015; 13: 469-477Crossref PubMed Scopus (49) Google Scholar). As ECs are a minority cell type in a given organ it is challenging to determine EC gene expression profiles from averaged transcriptome analysis of whole-tissue samples. Methodological advances, such as laser cell capture (Cheng et al., 2013Cheng L. Zhang S. MacLennan G.T. Williamson S.R. Davidson D.D. Wang M. Jones T.D. Lopez-Beltran A. Montironi R. Laser-assisted microdissection in translational research: Theory, technical considerations, and future applications.Appl. Immunohistochem. Mol. Morphol. 2013; 21: 31-47PubMed Google Scholar), enzymatic, or manual dissection and cell sorting (Berger et al., 2012Berger C. Harzer H. Burkard T.R. Steinmann J. van der Horst S. Laurenson A.S. Novatchkova M. Reichert H. Knoblich J.A. FACS purification and transcriptome analysis of Drosophila neural stem cells reveals a role for Klumpfuss in self-renewal.Cell Rep. 2012; 2: 407-418Abstract Full Text Full Text PDF PubMed Scopus (83) Google Scholar, Nolan et al., 2013Nolan D.J. Ginsberg M. Israely E. Palikuqi B. Poulos M.G. James D. Ding B.S. Schachterle W. Liu Y. Rosenwaks Z. et al.Molecular signatures of tissue-specific microvascular endothelial cell heterogeneity in organ maintenance and regeneration.Dev. Cell. 2013; 26: 204-219Abstract Full Text Full Text PDF PubMed Scopus (349) Google Scholar) and immuno-purification (Wang and Navin, 2015Wang Y. Navin N.E. Advances and applications of single-cell sequencing technologies.Mol. Cell. 2015; 58: 598-609Abstract Full Text Full Text PDF PubMed Scopus (285) Google Scholar) have allowed the isolation of ECs from tissue prior to analysis. However, such processing and/or subsequent in vitro culture can trigger changes in gene expression, due to the loss of the organ-specific microenvironment (Amaya et al., 2015Amaya R. Pierides A. Tarbell J.M. The interaction between fluid wall shear stress and solid circumferential strain affects endothelial gene expression.PLoS ONE. 2015; 10: e0129952Google Scholar, Balda and Matter, 2009Balda M.S. Matter K. Tight junctions and the regulation of gene expression.Biochim. Biophys. Acta. 2009; 1788: 761-767Crossref PubMed Scopus (188) Google Scholar, Durr et al., 2004Durr E. Yu J. Krasinska K.M. Carver L.A. Yates J.R. Testa J.E. Oh P. Schnitzer J.E. Direct proteomic mapping of the lung microvascular endothelial cell surface in vivo and in cell culture.Nat. Biotechnol. 2004; 22: 985-992Crossref PubMed Scopus (367) Google Scholar). Here, as an illustrative application of the Human Protein Atlas resource (Uhlén et al., 2015Uhlén M. Fagerberg L. Hallström B.M. Lindskog C. Oksvold P. Mardinoglu A. Sivertsson Å. Kampf C. Sjöstedt E. Asplund A. et al.Proteomics. Tissue-based map of the human proteome.Science. 2015; 347: 1260419Crossref PubMed Scopus (4833) Google Scholar), we used a systems-based approach to define the physiological human in vivo pan endothelial-enriched gene expression profile using whole-transcriptome analysis of unfractionated tissue samples. We identify a panel of human pan EC-enriched transcripts and replicate our findings using the same analysis protocol on Genotype-Tissue Expression (GTEx) datasets. 118 of the identified transcripts encode for novel or uncharacterized EC proteins. We also provide a searchable resource that can be used to determine the extent of pan endothelial specificity of any gene. The identification of previously unknown EC-enriched genes provides new vascular drug targets or biomarker candidates and presents candidates for future studies to further increase our understanding of EC function in health and disease. We performed RNA sequencing (RNA-seq) tissue transcript profiling of 124 samples collected from 32 human organs (n = 2–7 samples/organ) as part of the Human Protein Atlas Project (HPA; http://www.proteinatlas.org/) (Uhlén et al., 2015Uhlén M. Fagerberg L. Hallström B.M. Lindskog C. Oksvold P. Mardinoglu A. Sivertsson Å. Kampf C. Sjöstedt E. Asplund A. et al.Proteomics. Tissue-based map of the human proteome.Science. 2015; 347: 1260419Crossref PubMed Scopus (4833) Google Scholar). Tissue cryosections from selected organs (bone marrow, pancreas, ovary, tonsil, salivary gland, appendix, spleen, thyroid gland, gall bladder, urinary bladder, heart muscle, and lung) were H&E stained to morphologically determine the percentage of ECs, prior to RNA processing and sequencing from identical samples (see Table S1 and Experimental Procedures for further details). Fragments per kilobase of exon model per million mapped reads (FPKMs) values were calculated for 20,073 mapped protein-coding genes in all 124 samples. We selected three transcripts that encode for proteins that are predominantly expressed in ECs across different vascular beds; c-type lectin domain family 14, member A (CLEC14A) (Rho et al., 2011Rho S.S. Choi H.J. Min J.K. Lee H.W. Park H. Park H. Kim Y.M. Kwon Y.G. Clec14a is specifically expressed in endothelial cells and mediates cell to cell adhesion.Biochem. Biophys. Res. Commun. 2011; 404: 103-108Crossref PubMed Scopus (36) Google Scholar), von Willebrand factor (vWF) (Zanetta et al., 2000Zanetta L. Marcus S.G. Vasile J. Dobryansky M. Cohen H. Eng K. Shamamian P. Mignatti P. Expression of Von Willebrand factor, an endothelial cell marker, is up-regulated by angiogenesis factors: A potential method for objective assessment of tumor angiogenesis.Int. J. Cancer. 2000; 85: 281-288Crossref PubMed Scopus (140) Google Scholar), and CD34 (CD34) (Müller et al., 2002Müller A.M. Hermanns M.I. Skrzynski C. Nesslinger M. Müller K.M. Kirkpatrick C.J. Expression of the endothelial markers PECAM-1, vWf, and CD34 in vivo and in vitro.Exp. Mol. Pathol. 2002; 72: 221-229Crossref PubMed Scopus (153) Google Scholar, Pusztaszeri et al., 2006Pusztaszeri M.P. Seelentag W. Bosman F.T. Immunohistochemical expression of endothelial markers CD31, CD34, von Willebrand factor, and Fli-1 in normal human tissues.J. Histochem. Cytochem. 2006; 54: 385-395Crossref PubMed Scopus (525) Google Scholar). VWF has long been acknowledged as an EC marker in vivo (Zanetta et al., 2000Zanetta L. Marcus S.G. Vasile J. Dobryansky M. Cohen H. Eng K. Shamamian P. Mignatti P. Expression of Von Willebrand factor, an endothelial cell marker, is up-regulated by angiogenesis factors: A potential method for objective assessment of tumor angiogenesis.Int. J. Cancer. 2000; 85: 281-288Crossref PubMed Scopus (140) Google Scholar), as has CD34, although both reportedly show some variation between tissue beds and vessel types (Müller et al., 2002Müller A.M. Hermanns M.I. Skrzynski C. Nesslinger M. Müller K.M. Kirkpatrick C.J. Expression of the endothelial markers PECAM-1, vWf, and CD34 in vivo and in vitro.Exp. Mol. Pathol. 2002; 72: 221-229Crossref PubMed Scopus (153) Google Scholar, Pusztaszeri et al., 2006Pusztaszeri M.P. Seelentag W. Bosman F.T. Immunohistochemical expression of endothelial markers CD31, CD34, von Willebrand factor, and Fli-1 in normal human tissues.J. Histochem. Cytochem. 2006; 54: 385-395Crossref PubMed Scopus (525) Google Scholar). CLEC14A was originally described as an EC protein in murine models (Rho et al., 2011Rho S.S. Choi H.J. Min J.K. Lee H.W. Park H. Park H. Kim Y.M. Kwon Y.G. Clec14a is specifically expressed in endothelial cells and mediates cell to cell adhesion.Biochem. Biophys. Res. Commun. 2011; 404: 103-108Crossref PubMed Scopus (36) Google Scholar), and it was later described as a tumor angiogenesis marker with limited expression in selected normal human tissues (Mura et al., 2012Mura M. Swain R.K. Zhuang X. Vorschmitt H. Reynolds G. Durant S. Beesley J.F. Herbert J.M. Sheldon H. Andre M. et al.Identification and angiogenic role of the novel tumor endothelial marker CLEC14A.Oncogene. 2012; 31: 293-305Crossref PubMed Scopus (72) Google Scholar, Noy et al., 2015Noy P.J. Lodhia P. Khan K. Zhuang X. Ward D.G. Verissimo A.R. Bacon A. Bicknell R. Blocking CLEC14A-MMRN2 binding inhibits sprouting angiogenesis and tumour growth.Oncogene. 2015; 34: 5821-5831Crossref PubMed Scopus (34) Google Scholar). However, immunohistochemistry (IHC) confirmed enriched EC expression of all three across vascular beds (examples shown in Figure 1A). Mean FPKM values of CLEC14A, vWF, and CD34 varied from <1–56, <1–110, and 4–166, respectively, across the 32 organs (Figure 1A). Although absolute FPKM values differed, the relative expression of the EC reference transcripts were strikingly similar, with highest levels detected in highly vascularized organs, such as the heart, lung, placenta, and adipose tissue and lowest in less vascularized organs, such as pancreas and ovary (organs with accompanying percentage EC data in Figure 1A, those without in Figure S1A.i). CLEC14A, vWF, and CD34 FPKM values were strongly correlated with each other across individual samples (correlation >0.74, p values <0.001) (Figure S1A.ii), supporting the concept that combined CLEC14A, vWF, and CD34 expression provides a surrogate measurement for the relative degree of tissue vascularization in vivo. Consistent with the expression data, IHC revealed a high vascular content in tissues with high CLEC14A, vWF, and CD34 FPKM values (Figure 1A). CLEC14A, vWF, and CD34 expression correlated with percentage of EC in the corresponding sequenced tissue samples (correlation 0.82, p value 0.001; correlation 0.90, p value <0.0001 and correlation 0.80 p value 0.002, respectively) (Figure 1B). We performed a bioinformatics analysis of the RNA-seq tissue transcript profiling data across the 32 organ types to produce correlation coefficient values between CLEC14A, vWF, and CD34 FKPM values and those of the other 20,073 mapped protein-coding genes. A high correlation value with all three EC reference genes should indicate EC-enriched expression of the gene(s) in question across tissue types. To test this method for identification of EC-enriched transcripts, we generated a list of 26 genes widely considered as EC enriched, based on published data (Ballabio et al., 2004Ballabio E. Mariotti M. De Benedictis L. Maier J.A.M. The dual role of endothelial differentiation-related factor-1 in the cytosol and nucleus: Modulation by protein kinase A.Cell. Mol. Life Sci. 2004; 61: 1069-1074Crossref PubMed Scopus (23) Google Scholar, Bernat et al., 2006Bernat J.A. Crawford G.E. Ogurtsov A.Y. Collins F.S. Ginsburg D. Kondrashov A.S. Distant conserved sequences flanking endothelial-specific promoters contain tissue-specific DNase-hypersensitive sites and over-represented motifs.Hum. Mol. Genet. 2006; 15: 2098-2105Crossref PubMed Scopus (17) Google Scholar, Ho et al., 2003Ho M. Yang E. Matcuk G. Deng D. Sampas N. Tsalenko A. Tabibiazar R. Zhang Y. Chen M. Talbi S. et al.Identification of endothelial cell genes by combined database mining and microarray analysis.Physiol. Genomics. 2003; 13: 249-262Crossref PubMed Scopus (95) Google Scholar, Huminiecki and Bicknell, 2000Huminiecki L. Bicknell R. In silico cloning of novel endothelial-specific genes.Genome Res. 2000; 10: 1796-1806Crossref PubMed Scopus (131) Google Scholar, Jaye et al., 1999Jaye M. Lynch K.J. Krawiec J. Marchadier D. Maugeais C. Doan K. South V. Amin D. Perrone M. Rader D.J. A novel endothelial-derived lipase that modulates HDL metabolism.Nat. Genet. 1999; 21: 424-428Crossref PubMed Scopus (395) Google Scholar, Korhonen et al., 1995Korhonen J. Lahtinen I. Halmekytö M. Alhonen L. Jänne J. Dumont D. Alitalo K. Endothelial-specific gene expression directed by the tie gene promoter in vivo.Blood. 1995; 86: 1828-1835Crossref PubMed Google Scholar, Steagall et al., 2006Steagall R.J. Rusiñol A.E. Truong Q.A. Han Z. HSPA12B is predominantly expressed in endothelial cells and required for angiogenesis.Arterioscler. Thromb. Vasc. Biol. 2006; 26: 2012-2018Crossref PubMed Scopus (37) Google Scholar) and analyzed the correlation between the FPKM values for these transcripts and CLEC14A, vWF, and CD34 (Figure 2A). 20/26 selected genes had a high mean correlation coefficient with CLEC14A, vWF, and CD34 >0.5 (15/25 correlation >0.6). However, FPKM values for endothelial-specific molecule (ESM1), endothelial lipase (LIPG), and endothelial differentiation-related factor 1 (EDF1) failed to correlate with CLEC14A, vWF, or CD34 FPKM values (correlation 0.04, −0.02, and −0.09, respectively), suggesting misclassification of these genes as pan EC enriched. Consistent with this hypothesis, IHC for transcripts with high-correlation coefficients, e.g., HSPA12B, PECAM1, and ENG (mean correlation 0.73, p value <0.001, 0.67 p value <0.001 and 0.59, p value <0.001, respectively) confirmed EC-enriched expression, while IHC for ESM1, LIPG, and EDF1 did not (selected organs representing low [salivary gland], medium [gallbladder], and high [lung] EC percentage by histology are shown as representative examples in Figure 2B). Furthermore, mean FPKM values for HSPA12B, PECAM1, and ENG showed a correlation with the estimated mean percentage of ECs in bone marrow, pancreas, ovary, tonsil, salivary gland, appendix, spleen, thyroid gland, gall bladder, urinary bladder, heart muscle, and lung (correlation 0.60, p value 0.04, 0.53 p value 0.07, 0.75, p value 0.005, respectively), while such correlation was absent for ESM1, LIPG, and EDF1 (correlation 0.43, p value 0.16; correlation 0.23, p value 0.47 and 0.05, p value 0.86, respectively) (Figure 2B, right). Based on this correlation data, we defined “EC-enriched genes” as those that had significant mean correlation coefficients with the EC reference transcripts CLEC14A, vWF, and CD34 >0.5. The EC reference transcripts CD34 and vWF are also expressed in hematopoietic stem cells (Satterthwaite et al., 1992Satterthwaite A.B. Burn T.C. Le Beau M.M. Tenen D.G. Structure of the gene encoding CD34, a human hematopoietic stem cell antigen.Genomics. 1992; 12: 788-794Crossref PubMed Scopus (70) Google Scholar) and platelets (Kanaji et al., 2012Kanaji S. Fahs S.A. Shi Q. Haberichter S.L. Montgomery R.R. Contribution of platelet vs. endothelial VWF to platelet adhesion and hemostasis.J. Thromb. Haemost. 2012; 10: 1646-1652Crossref PubMed Scopus (77) Google Scholar, Schick et al., 1997Schick P.K. Walker J. Profeta B. Denisova L. Bennett V. Synthesis and secretion of von Willebrand factor and fibronectin in megakaryocytes at different phases of maturation.Arterioscler. Thromb. Vasc. Biol. 1997; 17: 797-801Crossref PubMed Scopus (14) Google Scholar), respectively, raising the concern that transcripts from vasculature associated hematopoietic cells could be incorrectly classified as EC enriched. Protein tyrosine phosphatase, receptor type, C (PTPRC) (commonly known as CD45), a differentiated hematopoietic cell marker, was predominantly expressed in the lymph node, tonsil, appendix, spleen, and bone marrow (Figure S1B.i) and the platelet protein integrin, alpha 2b (platelet glycoprotein IIb of IIb/IIIa complex, antigen CD41) (ITGA2B) was expressed mainly in bone marrow (Figure S1C.i). PTPRC and ITGA2B showed no significant correlation with the EC reference seeds (correlation with CLEC14A, vWF, and CD34: 0.01, 0.11, −0.11 and 0.11, 0.19, 0.25, respectively) (Figures S2A and S2B), arguing against potential misclassification of transcripts expressed by circulating blood cells as EC enriched. As vascular smooth muscle cells (SMCs) surround vessels, we assessed whether transcripts from this cell type could be incorrectly classified as EC enriched. The SMC marker protein myosin, heavy chain 11, smooth muscle (MYH11) was most highly expressed in smooth muscle tissue and esophagus (Figure S1D.i). MYH11 expression did show a significant, albeit weak, correlation with the three EC reference transcripts (correlation CLEC14A, vWF, and CD34: 0.41, 0.36, 0.41, respectively) (Figure S2C), indicating further analysis was required to determine whether any SMC transcripts were falsely annotated as EC-enriched transcripts. We found no association between the mean percentage of ECs in bone marrow, pancreas, ovary, tonsil, salivary gland, appendix, spleen, thyroid gland, gall bladder, urinary bladder, heart muscle, and lung and the mean FPKM value for PTPRC, ITGA2B, or MYH11 (correlation −0.30, −0.29, and −0.05, respectively; Figures S1B.ii, S1C.ii, and S1D.ii). To test the sensitivity and specificity of our method for identification of EC-enriched transcripts and to determine optimal analysis criteria, we compared correlation coefficients between the EC reference genes, CLEC14A, vWF, and CD34, and four sets of transcripts categorized as: (1) “previously known EC enriched” (Ballabio et al., 2004Ballabio E. Mariotti M. De Benedictis L. Maier J.A.M. The dual role of endothelial differentiation-related factor-1 in the cytosol and nucleus: Modulation by protein kinase A.Cell. Mol. Life Sci. 2004; 61: 1069-1074Crossref PubMed Scopus (23) Google Scholar, Bernat et al., 2006Bernat J.A. Crawford G.E. Ogurtsov A.Y. Collins F.S. Ginsburg D. Kondrashov A.S. Distant conserved sequences flanking endothelial-specific promoters contain tissue-specific DNase-hypersensitive sites and over-represented motifs.Hum. Mol. Genet. 2006; 15: 2098-2105Crossref PubMed Scopus (17) Google Scholar, Ho et al., 2003Ho M. Yang E. Matcuk G. Deng D. Sampas N. Tsalenko A. Tabibiazar R. Zhang Y. Chen M. Talbi S. et al.Identification of endothelial cell genes by combined database mining and microarray analysis.Physiol. Genomics. 2003; 13: 249-262Crossref PubMed Scopus (95) Google Scholar, Huminiecki and Bicknell, 2000Huminiecki L. Bicknell R. In silico cloning of novel endothelial-specific genes.Genome Res. 2000; 10: 1796-1806Crossref PubMed Scopus (131) Google Scholar, Jaye et al., 1999Jaye M. Lynch K.J. Krawiec J. Marchadier D. Maugeais C. Doan K. South V. Amin D. Perrone M. Rader D.J. A novel endothelial-derived lipase that modulates HDL metabolism.Nat. Genet. 1999; 21: 424-428Crossref PubMed Scopus (395) Google Scholar, Korhonen et al., 1995Korhonen J. Lahtinen I. Halmekytö M. Alhonen L. Jänne J. Dumont D. Alitalo K. Endothelial-specific gene expression directed by the tie gene promoter in vivo.Blood. 1995; 86: 1828-1835Crossref PubMed Google Scholar) (as featured in Figure 2A, with the exclusion of ESM1, LIPG, and EDF1 due to lack of evidence of EC expression) (2) “non-EC expressed” (no expression in cultured EC, no evidence of EC staining in vivo by IHC and expression in at least 20 of the 32 organs sequenced, see Table S2, tab 2 for details) (3) “smooth muscle cell (SMC) enriched” (Conley, 2001Conley C.A. Leiomodin and tropomodulin in smooth muscle.Am. J. Physiol. Cell Physiol. 2001; 280: C1645-C1656PubMed Google Scholar, Dreiza et al., 2010Dreiza C.M. Komalavilas P. Furnish E.J. Flynn C.R. Sheller M.R. Smoke C.C. Lopes L.B. Brophy C.M. The small heat shock protein, HSPB6, in muscle function and disease.Cell Stress Chaperones. 2010; 15: 1-11Crossref PubMed Scopus (67) Google Scholar, Long et al., 2009Long X. Tharp D.L. Georger M.A. Slivano O.J. Lee M.Y. Wamhoff B.R. Bowles D.K. Miano J.M. The smooth muscle cell-restricted KCNMB1 ion channel subunit is a direct transcriptional target of serum response factor and myocardin.J. Biol. Chem. 2009; 284: 33671-33682Crossref PubMed Scopus (49) Google Scholar, Miwa et al., 1991Miwa T. Manabe Y. Kurokawa K. Kamada S. Kanda N. Bruns G. Ueyama H. Kakunaga T. Structure, chromosome location, and expression of the human smooth muscle (enteric type) gamma-actin gene: Evolution of six human actin genes.Mol. Cell. Biol. 1991; 11: 3296-3306Crossref PubMed Google Scholar, Rensen et al., 2007Rensen S.S. Doevendans P.A. van Eys G.J. Regulation and characteristics of vascular smooth muscle cell phenotypic diversity.Neth. Heart J. 2007; 15: 100-108Crossref PubMed Scopus (532) Google Scholar, Wang et al., 2003Wang Z. Wang D.Z. Pipes G.C. Olson E.N. Myocardin is a master regulator of smooth muscle gene expression.Proc. Natl. Acad. Sci. USA. 2003; 100: 7129-7134Crossref PubMed Scopus (392) Google Scholar, Yamawaki et al., 2001Yamawaki K. Ito M. Machida H. Moriki N. Okamoto R. Isaka N. Shimpo H. Kohda A. Okumura K. Hartshorne D.J. Nakano T. Identification of human CPI-17, an inhibitory phosphoprotein for myosin phosphatase.Biochem. Biophys. Res. Commun. 2001; 285: 1040-1045Crossref PubMed Scopus (23) Google Scholar), or (4) “macrophage enriched” (East and Isacke, 2002East L. Isacke C.M. The mannose receptor family.Biochim. Biophys. Acta. 2002; 1572: 364-386Crossref PubMed Scopus (448) Google Scholar, Fabriek et al., 2009Fabriek B.O. van Bruggen R. Deng D.M. Ligtenberg A.J. Nazmi K. Schornagel K. Vloet R.P. Dijkstra C.D. van den Berg T.K. The macrophage scavenger receptor CD163 functions as an innate immune sensor for bacteria.Blood. 2009; 113: 887-892Crossref PubMed Scopus (255) Google Scholar, Kaufmann et al., 2001Kaufmann A. Salentin R. Gemsa D. Sprenger H. Increase of CCR1 and CCR5 expression and enhanced functional response to MIP-1 alpha during differentiation of human monocytes to macrophages.J. Leukoc. Biol. 2001; 69: 248-252PubMed Google Scholar, Kunjathoor et al., 2002Kunjathoor V.V. Febbraio M. Podrez E.A. Moore K.J. Andersson L. Koehn S. Rhee J.S. Silverstein R. Hoff H.F. Freeman M.W. Scavenger receptors class A-I/II and CD36 are the principal receptors responsible for the uptake of modified low density lipoprotein leading to lipid loading in macrophages.J. Biol. Chem. 2002; 277: 49982-49988Crossref PubMed Scopus (695) Google Scholar, Liang and Tedder, 2001Liang Y. Tedder T.F. Identification of a CD20-, FcepsilonRIbeta-, and HTm4-related gene family: Sixteen new MS4A family members expressed in human and mouse.Genomics. 2001; 72: 119-127Crossref PubMed Scopus (97) Google Scholar, Murray and Wynn, 2011Murray P.J. Wynn T.A. Protective and pathogenic functions of macrophage subsets.Nat. Rev. Immunol. 2011; 11: 723-737Crossref PubMed Scopus (2749) Google Scholar, Varchetta et al., 2012Varchetta S. Brunetta E. Roberto A. Mikulak J. Hudspeth K.L. Mondelli M.U. Mavilio D. Engagement of Siglec-7 receptor induces a pro-inflammatory response selectively in monocytes.PLoS ONE. 2012; 7: e45821Crossref PubMed Scopus (26) Google Scholar) (Table S2, tabs 1–4: column A). 15/23 (65%) of the previously known EC-enriched transcripts had mean correlation values >0.6 with our EC reference transcripts, which increased to 20/23 (87%) when the cutoff point was lowered to ≥0.5 (Table S2, tab 1, section A; Figure S3A.i). In contrast, all 50 “non-EC transcripts” had mean correlation values <0.3 with the EC reference transcripts (mean −0.01, SD 0.19) (Table S2, tab 2, section A; Figure S3A.ii). 9/12 (75%) “SMC-enriched” transcripts had correlation values <0.5 with the EC reference transcripts (mean 0.40, SD 0.06), but 3/12 (25%) had correlation values >0.5 (mean 0.52, SD 0.01), indicating a 25% rate of false classification of SMC genes as EC enriched (Table S2, tab 3, section A; Figure S3A.iii). All “macrophage-enriched” transcripts had correlation values <0.38 with the EC reference transcripts (mean 0.22, SD 0.11) (Table S2, tab 4, section A; Figure S3A.iv). Overall 67/70 (96%) of the non EC-enriched transcripts had a correlation coefficient with the EC reference transcripts of <0.5, and the three others were all from the SMC-enriched category. To determine whether such false positives could be identified, we performed an additional analysis to measure mean correlation coefficient values between three selected SMC reference transcripts Myosin, Heavy Chain 11, Smooth Muscle (MYH11), Myosin Light Chain Kinase (MYLK), and Actin, Alpha 2, Smooth Muscle, Aorta (ACTA2) and those in the “previously known EC-enriched” and the SMC-enriched test set (Table S2, tabs 1 and 3, section C). The prev" @default.
• W2520696572 created "2016-09-23" @default.
• W2520696572 creator A5005639182 @default.
• W2520696572 creator A5011635059 @default.
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• W2520696572 creator A5041800520 @default.
• W2520696572 creator A5055072095 @default.
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• W2520696572 date "2016-09-01" @default.
• W2520696572 modified "2023-10-15" @default.
• W2520696572 title "Analysis of Body-wide Unfractionated Tissue Data to Identify a Core Human Endothelial Transcriptome" @default.
• W2520696572 cites W1489226586 @default.
• W2520696572 cites W1533942137 @default.
• W2520696572 cites W1605004657 @default.
• W2520696572 cites W1658877244 @default.
• W2520696572 cites W1757181695 @default.
• W2520696572 cites W1821834469 @default.
• W2520696572 cites W1939640254 @default.
• W2520696572 cites W1947739337 @default.
• W2520696572 cites W1949072443 @default.
• W2520696572 cites W1963669837 @default.
• W2520696572 cites W1965917470 @default.
• W2520696572 cites W1971677443 @default.
• W2520696572 cites W1973268693 @default.
• W2520696572 cites W1975817566 @default.
• W2520696572 cites W1975905715 @default.
• W2520696572 cites W1977818394 @default.
• W2520696572 cites W1979404773 @default.
• W2520696572 cites W1981885216 @default.
• W2520696572 cites W1985330418 @default.
• W2520696572 cites W1985859986 @default.
• W2520696572 cites W1986553481 @default.
• W2520696572 cites W1990173431 @default.
• W2520696572 cites W1992814996 @default.
• W2520696572 cites W1995882349 @default.
• W2520696572 cites W1996242613 @default.
• W2520696572 cites W1997023449 @default.
• W2520696572 cites W2004553952 @default.
• W2520696572 cites W2005055996 @default.
• W2520696572 cites W2010567193 @default.
• W2520696572 cites W2012034410 @default.
• W2520696572 cites W2017805529 @default.
• W2520696572 cites W2020565041 @default.
• W2520696572 cites W2020594884 @default.
• W2520696572 cites W2025706879 @default.
• W2520696572 cites W2034125855 @default.
• W2520696572 cites W2039068212 @default.
• W2520696572 cites W2041291777 @default.
• W2520696572 cites W2043485993 @default.
• W2520696572 cites W2045147732 @default.
• W2520696572 cites W2045220907 @default.
• W2520696572 cites W2046895286 @default.
• W2520696572 cites W2049190480 @default.
• W2520696572 cites W2050183466 @default.
• W2520696572 cites W2050370340 @default.
• W2520696572 cites W2053183528 @default.
• W2520696572 cites W2053938092 @default.
• W2520696572 cites W2055279538 @default.
• W2520696572 cites W2063703948 @default.
• W2520696572 cites W2065460237 @default.
• W2520696572 cites W2065468032 @default.
• W2520696572 cites W2065617511 @default.
• W2520696572 cites W2066847273 @default.
• W2520696572 cites W2068757005 @default.
• W2520696572 cites W2073290778 @default.
• W2520696572 cites W2073973669 @default.
• W2520696572 cites W2091040995 @default.
• W2520696572 cites W2091574626 @default.
• W2520696572 cites W2093280246 @default.
• W2520696572 cites W2095002343 @default.
• W2520696572 cites W2097177355 @default.
• W2520696572 cites W2103017472 @default.
• W2520696572 cites W2103680698 @default.
• W2520696572 cites W2103802452 @default.
• W2520696572 cites W2104839879 @default.
• W2520696572 cites W2110926368 @default.
• W2520696572 cites W2111154266 @default.
• W2520696572 cites W2117119768 @default.
• W2520696572 cites W2118709967 @default.
• W2520696572 cites W2119327344 @default.
• W2520696572 cites W2120004578 @default.
• W2520696572 cites W2120972647 @default.
• W2520696572 cites W2122438081 @default.
• W2520696572 cites W2124296544 @default.
• W2520696572 cites W2126700250 @default.
• W2520696572 cites W2128551987 @default.
• W2520696572 cites W2129752592 @default.
• W2520696572 cites W2133469704 @default.
• W2520696572 cites W2133811295 @default.
• W2520696572 cites W2139319526 @default.
• W2520696572 cites W2140729960 @default.
• W2520696572 cites W2140733306 @default.
• W2520696572 cites W2141458291 @default.
• W2520696572 cites W2141461285 @default.
• W2520696572 cites W2146524990 @default.
• W2520696572 cites W2147176626 @default.
• W2520696572 cites W2149805661 @default.

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