Targeting EZH2 Increases Therapeutic Efficacy of PD-1 Check-Point Blockade in Models of Prostate Cancer Supplement Figures and T
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse
Welcome to More Choice CD Marker Handbook For more information, please visit: Human bdbiosciences.com/eu/go/humancdmarkers Mouse bdbiosciences.com/eu/go/mousecdmarkers Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse CD3 CD3 CD (cluster of differentiation) molecules are cell surface markers T Cell CD4 CD4 useful for the identification and characterization of leukocytes. The CD CD8 CD8 nomenclature was developed and is maintained through the HLDA (Human Leukocyte Differentiation Antigens) workshop started in 1982. CD45R/B220 CD19 CD19 The goal is to provide standardization of monoclonal antibodies to B Cell CD20 CD22 (B cell activation marker) human antigens across laboratories. To characterize or “workshop” the antibodies, multiple laboratories carry out blind analyses of antibodies. These results independently validate antibody specificity. CD11c CD11c Dendritic Cell CD123 CD123 While the CD nomenclature has been developed for use with human antigens, it is applied to corresponding mouse antigens as well as antigens from other species. However, the mouse and other species NK Cell CD56 CD335 (NKp46) antibodies are not tested by HLDA. Human CD markers were reviewed by the HLDA. New CD markers Stem Cell/ CD34 CD34 were established at the HLDA9 meeting held in Barcelona in 2010. For Precursor hematopoetic stem cell only hematopoetic stem cell only additional information and CD markers please visit www.hcdm.org. Macrophage/ CD14 CD11b/ Mac-1 Monocyte CD33 Ly-71 (F4/80) CD66b Granulocyte CD66b Gr-1/Ly6G Ly6C CD41 CD41 CD61 (Integrin b3) CD61 Platelet CD9 CD62 CD62P (activated platelets) CD235a CD235a Erythrocyte Ter-119 CD146 MECA-32 CD106 CD146 Endothelial Cell CD31 CD62E (activated endothelial cells) Epithelial Cell CD236 CD326 (EPCAM1) For Research Use Only. -
14-3-3Sigma Negatively Regulates the Stability and Subcellular Localization of Cop1
The Texas Medical Center Library DigitalCommons@TMC The University of Texas MD Anderson Cancer Center UTHealth Graduate School of The University of Texas MD Anderson Cancer Biomedical Sciences Dissertations and Theses Center UTHealth Graduate School of (Open Access) Biomedical Sciences 12-2010 14-3-3SIGMA NEGATIVELY REGULATES THE STABILITY AND SUBCELLULAR LOCALIZATION OF COP1 Chun-Hui Su Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Biology Commons Recommended Citation Su, Chun-Hui, "14-3-3SIGMA NEGATIVELY REGULATES THE STABILITY AND SUBCELLULAR LOCALIZATION OF COP1" (2010). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 101. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/101 This Dissertation (PhD) is brought to you for free and open access by the The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences at DigitalCommons@TMC. It has been accepted for inclusion in The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access) by an authorized administrator of DigitalCommons@TMC. For more information, please contact [email protected]. 14-3-3SIGMA NEGATIVELY REGULATES THE STABILITY AND SUBCELLULAR LOCALIZATION OF COP1 By Chun-Hui Su, M.S. APPROVED: ______________________________ Mong-Hong Lee, Supervisory Professor ______________________________ Randy -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Cd1b Tetramers Bind T Cell Receptors to Identify a Mycobacterial
Published August 1, 2011 Brief Definitive Report CD1b tetramers bind T cell receptors to identify a mycobacterial glycolipid- reactive T cell repertoire in humans Anne G. Kasmar,1 Ildiko van Rhijn,1,2 Tan-Yun Cheng,1 Marie Turner,3 Chetan Seshadri,1 Andre Schiefner,4 Ravi C. Kalathur,4 John W. Annand,1 Annemieke de Jong,1 John Shires,5 Luis Leon,1 Michael Brenner,1 Ian A. Wilson,4 John D. Altman,5 and D. Branch Moody1 1Division of Rheumatology, Immunology and Allergy, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 2Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, 3508 TD Utrecht, Netherlands 3Tuberculosis Treatment Unit, Lemuel Shattuck Hospital, Jamaica Plain, MA 02130 4Department of Molecular Biology and Skaggs Institute for Chemical Biology, the Scripps Research Institute, La Jolla, CA 92037 Downloaded from 5Emory Vaccine Center, Atlanta, GA 30329 Microbial lipids activate T cells by binding directly to CD1 and T cell receptors (TCRs) or by indirect effects on antigen-presenting cells involving induction of lipid autoantigens, CD1 transcription, or cytokine release. To distinguish among direct and indirect mechanisms, we developed fluorescent human CD1b tetramers and measured T cell staining. CD1b tetramer staining of T cells requires glucose monomycolate (GMM) antigens, is specific for TCR jem.rupress.org structure, and is blocked by a recombinant clonotypic TCR comprised of TRAV17 and TRBV4-1, proving that CD1b–glycolipid complexes bind the TCR. GMM-loaded tetramers brightly stain a small subpopulation of blood-derived cells from humans infected with Mycobacterium tuberculosis, providing direct detection of a CD1b-reactive T cell reper- toire. -
Flow Reagents Single Color Antibodies CD Chart
CD CHART CD N° Alternative Name CD N° Alternative Name CD N° Alternative Name Beckman Coulter Clone Beckman Coulter Clone Beckman Coulter Clone T Cells B Cells Granulocytes NK Cells Macrophages/Monocytes Platelets Erythrocytes Stem Cells Dendritic Cells Endothelial Cells Epithelial Cells T Cells B Cells Granulocytes NK Cells Macrophages/Monocytes Platelets Erythrocytes Stem Cells Dendritic Cells Endothelial Cells Epithelial Cells T Cells B Cells Granulocytes NK Cells Macrophages/Monocytes Platelets Erythrocytes Stem Cells Dendritic Cells Endothelial Cells Epithelial Cells CD1a T6, R4, HTA1 Act p n n p n n S l CD99 MIC2 gene product, E2 p p p CD223 LAG-3 (Lymphocyte activation gene 3) Act n Act p n CD1b R1 Act p n n p n n S CD99R restricted CD99 p p CD224 GGT (γ-glutamyl transferase) p p p p p p CD1c R7, M241 Act S n n p n n S l CD100 SEMA4D (semaphorin 4D) p Low p p p n n CD225 Leu13, interferon induced transmembrane protein 1 (IFITM1). p p p p p CD1d R3 Act S n n Low n n S Intest CD101 V7, P126 Act n p n p n n p CD226 DNAM-1, PTA-1 Act n Act Act Act n p n CD1e R2 n n n n S CD102 ICAM-2 (intercellular adhesion molecule-2) p p n p Folli p CD227 MUC1, mucin 1, episialin, PUM, PEM, EMA, DF3, H23 Act p CD2 T11; Tp50; sheep red blood cell (SRBC) receptor; LFA-2 p S n p n n l CD103 HML-1 (human mucosal lymphocytes antigen 1), integrin aE chain S n n n n n n n l CD228 Melanotransferrin (MT), p97 p p CD3 T3, CD3 complex p n n n n n n n n n l CD104 integrin b4 chain; TSP-1180 n n n n n n n p p CD229 Ly9, T-lymphocyte surface antigen p p n p n -
1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor
xO GENE PANEL 1714 gene comprehensive cancer panel enriched for clinically actionable genes with additional biologically relevant genes 400-500x average coverage on tumor Genes A-C Genes D-F Genes G-I Genes J-L AATK ATAD2B BTG1 CDH7 CREM DACH1 EPHA1 FES G6PC3 HGF IL18RAP JADE1 LMO1 ABCA1 ATF1 BTG2 CDK1 CRHR1 DACH2 EPHA2 FEV G6PD HIF1A IL1R1 JAK1 LMO2 ABCB1 ATM BTG3 CDK10 CRK DAXX EPHA3 FGF1 GAB1 HIF1AN IL1R2 JAK2 LMO7 ABCB11 ATR BTK CDK11A CRKL DBH EPHA4 FGF10 GAB2 HIST1H1E IL1RAP JAK3 LMTK2 ABCB4 ATRX BTRC CDK11B CRLF2 DCC EPHA5 FGF11 GABPA HIST1H3B IL20RA JARID2 LMTK3 ABCC1 AURKA BUB1 CDK12 CRTC1 DCUN1D1 EPHA6 FGF12 GALNT12 HIST1H4E IL20RB JAZF1 LPHN2 ABCC2 AURKB BUB1B CDK13 CRTC2 DCUN1D2 EPHA7 FGF13 GATA1 HLA-A IL21R JMJD1C LPHN3 ABCG1 AURKC BUB3 CDK14 CRTC3 DDB2 EPHA8 FGF14 GATA2 HLA-B IL22RA1 JMJD4 LPP ABCG2 AXIN1 C11orf30 CDK15 CSF1 DDIT3 EPHB1 FGF16 GATA3 HLF IL22RA2 JMJD6 LRP1B ABI1 AXIN2 CACNA1C CDK16 CSF1R DDR1 EPHB2 FGF17 GATA5 HLTF IL23R JMJD7 LRP5 ABL1 AXL CACNA1S CDK17 CSF2RA DDR2 EPHB3 FGF18 GATA6 HMGA1 IL2RA JMJD8 LRP6 ABL2 B2M CACNB2 CDK18 CSF2RB DDX3X EPHB4 FGF19 GDNF HMGA2 IL2RB JUN LRRK2 ACE BABAM1 CADM2 CDK19 CSF3R DDX5 EPHB6 FGF2 GFI1 HMGCR IL2RG JUNB LSM1 ACSL6 BACH1 CALR CDK2 CSK DDX6 EPOR FGF20 GFI1B HNF1A IL3 JUND LTK ACTA2 BACH2 CAMTA1 CDK20 CSNK1D DEK ERBB2 FGF21 GFRA4 HNF1B IL3RA JUP LYL1 ACTC1 BAG4 CAPRIN2 CDK3 CSNK1E DHFR ERBB3 FGF22 GGCX HNRNPA3 IL4R KAT2A LYN ACVR1 BAI3 CARD10 CDK4 CTCF DHH ERBB4 FGF23 GHR HOXA10 IL5RA KAT2B LZTR1 ACVR1B BAP1 CARD11 CDK5 CTCFL DIAPH1 ERCC1 FGF3 GID4 HOXA11 IL6R KAT5 ACVR2A -
Supplementary Material DNA Methylation in Inflammatory Pathways Modifies the Association Between BMI and Adult-Onset Non- Atopic
Supplementary Material DNA Methylation in Inflammatory Pathways Modifies the Association between BMI and Adult-Onset Non- Atopic Asthma Ayoung Jeong 1,2, Medea Imboden 1,2, Akram Ghantous 3, Alexei Novoloaca 3, Anne-Elie Carsin 4,5,6, Manolis Kogevinas 4,5,6, Christian Schindler 1,2, Gianfranco Lovison 7, Zdenko Herceg 3, Cyrille Cuenin 3, Roel Vermeulen 8, Deborah Jarvis 9, André F. S. Amaral 9, Florian Kronenberg 10, Paolo Vineis 11,12 and Nicole Probst-Hensch 1,2,* 1 Swiss Tropical and Public Health Institute, 4051 Basel, Switzerland; [email protected] (A.J.); [email protected] (M.I.); [email protected] (C.S.) 2 Department of Public Health, University of Basel, 4001 Basel, Switzerland 3 International Agency for Research on Cancer, 69372 Lyon, France; [email protected] (A.G.); [email protected] (A.N.); [email protected] (Z.H.); [email protected] (C.C.) 4 ISGlobal, Barcelona Institute for Global Health, 08003 Barcelona, Spain; [email protected] (A.-E.C.); [email protected] (M.K.) 5 Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain 6 CIBER Epidemiología y Salud Pública (CIBERESP), 08005 Barcelona, Spain 7 Department of Economics, Business and Statistics, University of Palermo, 90128 Palermo, Italy; [email protected] 8 Environmental Epidemiology Division, Utrecht University, Institute for Risk Assessment Sciences, 3584CM Utrecht, Netherlands; [email protected] 9 Population Health and Occupational Disease, National Heart and Lung Institute, Imperial College, SW3 6LR London, UK; [email protected] (D.J.); [email protected] (A.F.S.A.) 10 Division of Genetic Epidemiology, Medical University of Innsbruck, 6020 Innsbruck, Austria; [email protected] 11 MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, W2 1PG London, UK; [email protected] 12 Italian Institute for Genomic Medicine (IIGM), 10126 Turin, Italy * Correspondence: [email protected]; Tel.: +41-61-284-8378 Int. -
TET2 Repression by Androgen Hormone Regulates Global Hydroxymethylation Status and Prostate Cancer Progression
ARTICLE Received 5 Oct 2014 | Accepted 30 Jul 2015 | Published 25 Sep 2015 DOI: 10.1038/ncomms9219 TET2 repression by androgen hormone regulates global hydroxymethylation status and prostate cancer progression Ken-ichi Takayama1,2,*, Aya Misawa1,*, Takashi Suzuki3, Kiyoshi Takagi3, Yoshihide Hayashizaki4,5, Tetsuya Fujimura6, Yukio Homma6, Satoru Takahashi7, Tomohiko Urano1,2 & Satoshi Inoue1,2,8 Modulation of epigenetic patterns has promising efficacy for treating cancer. 5-Hydro- xymethylated cytosine (5-hmC) is an epigenetic mark potentially important in cancer. Here we report that 5-hmC is an epigenetic hallmark of prostate cancer (PCa) progression. A member of the ten–eleven translocation (TET) proteins, which catalyse the oxidation of methylated cytosine (5-mC) to 5-hmC, TET2, is repressed by androgens in PCa. Androgen receptor (AR)-mediated induction of the miR-29 family, which targets TET2, are markedly enhanced in hormone refractory PCa (HRPC) and its high expression predicts poor outcome of PCa patients. Furthermore, decreased expression of miR-29b results in reduced tumour growth and increased TET2 expression in an animal model of HRPC. Interestingly, global 5-hmC modification regulated by miR-29b represses FOXA1 activity. A reduction in 5-hmC activates PCa-related key pathways such as mTOR and AR. Thus, DNA modification directly links the TET2-dependent epigenetic pathway regulated by AR to 5-hmC-mediated tumour progression. 1 Department of Anti-Aging Medicine, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo 113-8655, Japan. 2 Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo 113-8655, Japan. -
Supplementary Table 1: Differentially Methylated Genes and Functions of the Genes Before/After Treatment with A) Doxorubicin and B) FUMI and in C) Responders Vs
Supplementary Table 1: Differentially methylated genes and functions of the genes before/after treatment with a) doxorubicin and b) FUMI and in c) responders vs. non- responders for doxorubicin and d) FUMI Differentially methylated genes before/after treatment a. Doxo GENE FUNCTION CCL5, CCL8, CCL15, CCL21, CCR1, CD33, IL5, immunoregulatory and inflammatory processes IL8, IL24, IL26, TNFSF11 CCNA1, CCND2, CDKN2A cell cycle regulators ESR1, FGF2, FGF14, FGF18 growth factors WT1, RASSF5, RASSF6 tumor suppressor b. FUMI GENE FUNCTION CCL7, CCL15, CD28, CD33, CD40, CD69, TNFSF18 immunoregulatory and inflammatory processes CCND2, CDKN2A cell cycle regulators IGF2BP1, IGFBP3 growth factors HOXB4, HOXB6, HOXC8 regulation of cell transcription WT1, RASSF6 tumor suppressor Differentially methylated genes in responders vs. non-responders c. Doxo GENE FUNCTION CBR1, CCL4, CCL8, CCR1, CCR7, CD1A, CD1B, immunoregulatory and inflammatory processes CD1D, CD1E, CD33, CD40, IL5, IL8, IL20, IL22, TLR4 CCNA1, CCND2, CDKN2A cell cycle regulators ESR2, ERBB3, FGF11, FGF12, FGF14, FGF17 growth factors WNT4, WNT16, WNT10A implicated in oncogenesis TNFSF12, TNFSF15 apoptosis FOXL1, FOXL2, FOSL1,HOXA2, HOXA7, HOXA11, HOXA13, HOXB4, HOXB6, HOXB8, HOXB9, HOXC8, regulation of cell transcription HOXD8, HOXD9, HOXD11 GSTP1, MGMT DNA repair APC, WT1 tumor suppressor d. FUMI GENE FUNCTION CCL1, CCL3, CCL5,CCL14, CD1B, CD33, CD40, CD69, immunoregulatory and inflammatory IL20, IL32 processes CCNA1, CCND2, CDKN2A cell cycle regulators IGF2BP1, IGFBP3, IGFBP7, EGFR, ESR2,RARB2 -
Discovery of Deoxyceramides and Diacylglycerols As Cd1b Scaffold Lipids Among Diverse Groove-Blocking Lipids of the Human CD1 System
Discovery of deoxyceramides and diacylglycerols as CD1b scaffold lipids among diverse groove-blocking lipids of the human CD1 system Shouxiong Huanga, Tan-Yun Chenga, David C. Younga, Emilie Layrea, Cressida A. Madigana, John Shiresb, Vincenzo Cerundoloc, John D. Altmanb, and D. Branch Moodya,1 aDepartment of Medicine, Division of Rheumatology, Immunology and Allergy, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115; bEmory Vaccine Center, Emory School of Medicine, Atlanta, GA 30322; and cMedical Research Council Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom Edited* by Peter Cresswell, Yale University School of Medicine, New Haven, CT, and approved October 17, 2011 (received for review August 10, 2011) Unlike the dominant role of one class II invariant chain peptide (CLIP) environment (7, 8). The differing pH requirements for antigen in blocking MHC class II, comparative lipidomics analysis shows that loading, combined with enrichment of endogenous lipids in the human cluster of differentiation (CD) proteins CD1a, CD1b, CD1c, secretory pathway and exogenous lipids endosomes, are coalescing and CD1d bind lipids corresponding to hundreds of diverse accurate into a two-step model of lipid antigen presentation. First, newly mass retention time values. Although most ions were observed in translated CD1 proteins, aided by the microsomal triglyceride association with several CD1 proteins, ligands binding selectively to transport protein (MTP) (9), -
Detection of Differentially Expressed Candidate Genes for a Fatty Liver QTL
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Springer - Publisher Connector Kobayashi et al. BMC Genetics (2016) 17:73 DOI 10.1186/s12863-016-0385-2 RESEARCH ARTICLE Open Access Detection of differentially expressed candidate genes for a fatty liver QTL on mouse chromosome 12 Misato Kobayashi1, Miyako Suzuki1, Tamio Ohno2, Kana Tsuzuki1, Chie Taguchi1, Soushi Tateishi1, Teruo Kawada3, Young-il Kim3, Atsushi Murai1 and Fumihiko Horio1,4* Abstract Background: The SMXA-5 mouse is an animal model of high-fat diet-induced fatty liver. The major QTL for fatty liver, Fl1sa on chromosome 12, was identified in a SM/J × SMXA-5 intercross. The SMXA-5 genome consists of the SM/J and A/J genomes, and the A/J allele of Fl1sa is a fatty liver-susceptibility allele. The existence of the responsible genes for fatty liver within Fl1sa was confirmed in A/J-12SM consomic mice. The aim of this study was to identify candidate genes for Fl1sa, and to investigate whether the identified genes affect the lipid metabolism. Results: A/J-12SM mice showed a significantly lower liver triglyceride content compared to A/J mice when fed the high-fat diet for 7 weeks. We detected differences in the accumulation of liver lipids in response to the high-fat diet between A/J and A/J-12SM consomic mice. To identify candidate genes for Fl1sa, we performed DNA microarray analysis using the livers of A/J-12SM and A/J mice fed the high-fat diet. The mRNA levels of three genes (Iah1, Rrm2, Prkd1) in the chromosomal region of Fl1sa were significantly different between the strains.