title: Microarray and comparative genomics-based identification of genes and gene regulatory regions of the mouse immune system.
abstract: BACKGROUND
  In this study we have built and mined a gene expression database composed of 65 diverse mouse tissues for genes preferentially expressed in immune tissues and cell types. Using expression pattern criteria, we identified 360 genes with preferential expression in thymus, spleen, peripheral blood mononuclear cells, lymph nodes (unstimulated or stimulated), or in vitro activated T-cells.
  
  
  RESULTS
  Gene clusters, formed based on similarity of expression-pattern across either all tissues or the immune tissues only, had highly significant associations both with immunological processes such as chemokine-mediated response, antigen processing, receptor-related signal transduction, and transcriptional regulation, and also with more general processes such as replication and cell cycle control. Within-cluster gene correlations implicated known associations of known genes, as well as immune process-related roles for poorly described genes. To characterize regulatory mechanisms and cis-elements of genes with similar patterns of expression, we used a new version of a comparative genomics-based cis-element analysis tool to identify clusters of cis-elements with compositional similarity among multiple genes. Several clusters contained genes that shared 5-6 cis-elements that included ETS and zinc-finger binding sites. cis-Elements AP2 EGRF ETSF MAZF SP1F ZF5F and AREB ETSF MZF1 PAX5 STAT were shared in a thymus-expressed set; AP4R E2FF EBOX ETSF MAZF SP1F ZF5F and CREB E2FF MAZF PCAT SP1F STAT cis-clusters occurred in activated T-cells; CEBP CREB NFKB SORY and GATA NKXH OCT1 RBIT occurred in stimulated lymph nodes.
  
  
  CONCLUSIONS
  This study demonstrates a series of analytic approaches that have allowed the implication of genes and regulatory elements that participate in the differentiation, maintenance, and function of the immune system. Polymorphism or mutation of these could adversely impact immune system functions.
authors.affiliation: Department of Pediatrics and Biomedical Informatics, University of Cincinnati and Cincinnati Children's Hospital Research Foundation, Cincinnati, Ohio 45229, USA. john.hutton@cchmc.org <john.hutton@cchmc.org>
authors.forename: John J
authors.initials: JJ
authors.lastname: Hutton
authors.forename: Anil G
authors.initials: AG
authors.lastname: Jegga
authors.forename: Sue
authors.initials: S
authors.lastname: Kong
authors.forename: Ashima
authors.initials: A
authors.lastname: Gupta
authors.forename: Catherine
authors.initials: C
authors.lastname: Ebert
authors.forename: Sarah
authors.initials: S
authors.lastname: Williams
authors.forename: Jonathan D
authors.initials: JD
authors.lastname: Katz
authors.forename: Bruce J
authors.initials: BJ
authors.lastname: Aronow
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D020869:Gene Expression Profiling / Q000379:methods* / Q000706:statistics & numerical data; D005786:Gene Expression Regulation / Q000235:genetics*; D005796:Genes / Q000235:genetics* / Q000502:physiology; D005805:Genes, MHC Class I / Q000502:physiology; D023281:Genomics / Q000379:methods*; D007107:Immune System / Q000737:chemistry* / Q000378:metabolism* / Q000502:physiology; D051379:Mice; D008810:Mice, Inbred C57BL; D046228:Microarray Analysis / Q000379:methods* / Q000706:statistics & numerical data