Lowmaca: Low Frequency Mutation Analysis Via Consensus Alignment
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CDX4 Regulates the Progression of Neural Maturation in the Spinal Cord
Developmental Biology 449 (2019) 132–142 Contents lists available at ScienceDirect Developmental Biology journal homepage: www.elsevier.com/locate/developmentalbiology CDX4 regulates the progression of neural maturation in the spinal cord Piyush Joshi a,b, Andrew J. Darr c, Isaac Skromne a,d,* a Department of Biology, University of Miami, 1301 Memorial Drive, Coral Gables, Florida, 33146, United States b Cancer and Blood Disorders Institute, Johns Hopkins All Children's Hospital, 600 5th St S, St. Petersburg, FL 33701, United States c Department of Health Sciences Education, University of Illinois College of Medicine, 1 Illini Drive, Peoria, IL 61605, United States d Department of Biology, University of Richmond, 138 UR Drive B322, Richmond, VA, 23173, United States ARTICLE INFO ABSTRACT Keywords: The progression of cells down different lineage pathways is a collaborative effort between networks of extra- CDX cellular signals and intracellular transcription factors. In the vertebrate spinal cord, FGF, Wnt and Retinoic Acid Neurogenesis signaling pathways regulate the progressive caudal-to-rostral maturation of neural progenitors by regulating a Spinal cord poorly understood gene regulatory network of transcription factors. We have mapped out this gene regulatory Gene regulatory network network in the chicken pre-neural tube, identifying CDX4 as a dual-function core component that simultaneously regulates gradual loss of cell potency and acquisition of differentiation states: in a caudal-to-rostral direction, CDX4 represses the early neural differentiation marker Nkx1.2 and promotes the late neural differentiation marker Pax6. Significantly, CDX4 prevents premature PAX6-dependent neural differentiation by blocking Ngn2 activation. This regulation of CDX4 over Pax6 is restricted to the rostral pre-neural tube by Retinoic Acid signaling. -
Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
Watsonjn2018.Pdf (1.780Mb)
UNIVERSITY OF CENTRAL OKLAHOMA Edmond, Oklahoma Department of Biology Investigating Differential Gene Expression in vivo of Cardiac Birth Defects in an Avian Model of Maternal Phenylketonuria A THESIS SUBMITTED TO THE GRADUATE FACULTY In partial fulfillment of the requirements For the degree of MASTER OF SCIENCE IN BIOLOGY By Jamie N. Watson Edmond, OK June 5, 2018 J. Watson/Dr. Nikki Seagraves ii J. Watson/Dr. Nikki Seagraves Acknowledgements It is difficult to articulate the amount of gratitude I have for the support and encouragement I have received throughout my master’s thesis. Many people have added value and support to my life during this time. I am thankful for the education, experience, and friendships I have gained at the University of Central Oklahoma. First, I would like to thank Dr. Nikki Seagraves for her mentorship and friendship. I lucked out when I met her. I have enjoyed working on this project and I am very thankful for her support. I would like thank Thomas Crane for his support and patience throughout my master’s degree. I would like to thank Dr. Shannon Conley for her continued mentorship and support. I would like to thank Liz Bullen and Dr. Eric Howard for their training and help on this project. I would like to thank Kristy Meyer for her friendship and help throughout graduate school. I would like to thank my committee members Dr. Robert Brennan and Dr. Lilian Chooback for their advisement on this project. Also, I would like to thank the biology faculty and staff. I would like to thank the Seagraves lab members: Jailene Canales, Kayley Pate, Mckayla Muse, Grace Thetford, Kody Harvey, Jordan Guffey, and Kayle Patatanian for their hard work and support. -
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. -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7 -
UNIVERSITY of CALIFORNIA, IRVINE Combinatorial Regulation By
UNIVERSITY OF CALIFORNIA, IRVINE Combinatorial regulation by maternal transcription factors during activation of the endoderm gene regulatory network DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Biological Sciences by Kitt D. Paraiso Dissertation Committee: Professor Ken W.Y. Cho, Chair Associate Professor Olivier Cinquin Professor Thomas Schilling 2018 Chapter 4 © 2017 Elsevier Ltd. © 2018 Kitt D. Paraiso DEDICATION To the incredibly intelligent and talented people, who in one way or another, helped complete this thesis. ii TABLE OF CONTENTS Page LIST OF FIGURES vii LIST OF TABLES ix LIST OF ABBREVIATIONS X ACKNOWLEDGEMENTS xi CURRICULUM VITAE xii ABSTRACT OF THE DISSERTATION xiv CHAPTER 1: Maternal transcription factors during early endoderm formation in 1 Xenopus Transcription factors co-regulate in a cell type-specific manner 2 Otx1 is expressed in a variety of cell lineages 4 Maternal otx1 in the endodermal conteXt 5 Establishment of enhancers by maternal transcription factors 9 Uncovering the endodermal gene regulatory network 12 Zygotic genome activation and temporal control of gene eXpression 14 The role of maternal transcription factors in early development 18 References 19 CHAPTER 2: Assembly of maternal transcription factors initiates the emergence 26 of tissue-specific zygotic cis-regulatory regions Introduction 28 Identification of maternal vegetally-localized transcription factors 31 Vegt and OtX1 combinatorially regulate the endodermal 33 transcriptome iii -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1. -
SUPPLEMENTARY MATERIAL Bone Morphogenetic Protein 4 Promotes
www.intjdevbiol.com doi: 10.1387/ijdb.160040mk SUPPLEMENTARY MATERIAL corresponding to: Bone morphogenetic protein 4 promotes craniofacial neural crest induction from human pluripotent stem cells SUMIYO MIMURA, MIKA SUGA, KAORI OKADA, MASAKI KINEHARA, HIROKI NIKAWA and MIHO K. FURUE* *Address correspondence to: Miho Kusuda Furue. Laboratory of Stem Cell Cultures, National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8, Saito-Asagi, Ibaraki, Osaka 567-0085, Japan. Tel: 81-72-641-9819. Fax: 81-72-641-9812. E-mail: [email protected] Full text for this paper is available at: http://dx.doi.org/10.1387/ijdb.160040mk TABLE S1 PRIMER LIST FOR QRT-PCR Gene forward reverse AP2α AATTTCTCAACCGACAACATT ATCTGTTTTGTAGCCAGGAGC CDX2 CTGGAGCTGGAGAAGGAGTTTC ATTTTAACCTGCCTCTCAGAGAGC DLX1 AGTTTGCAGTTGCAGGCTTT CCCTGCTTCATCAGCTTCTT FOXD3 CAGCGGTTCGGCGGGAGG TGAGTGAGAGGTTGTGGCGGATG GAPDH CAAAGTTGTCATGGATGACC CCATGGAGAAGGCTGGGG MSX1 GGATCAGACTTCGGAGAGTGAACT GCCTTCCCTTTAACCCTCACA NANOG TGAACCTCAGCTACAAACAG TGGTGGTAGGAAGAGTAAAG OCT4 GACAGGGGGAGGGGAGGAGCTAGG CTTCCCTCCAACCAGTTGCCCCAAA PAX3 TTGCAATGGCCTCTCAC AGGGGAGAGCGCGTAATC PAX6 GTCCATCTTTGCTTGGGAAA TAGCCAGGTTGCGAAGAACT p75 TCATCCCTGTCTATTGCTCCA TGTTCTGCTTGCAGCTGTTC SOX9 AATGGAGCAGCGAAATCAAC CAGAGAGATTTAGCACACTGATC SOX10 GACCAGTACCCGCACCTG CGCTTGTCACTTTCGTTCAG Suppl. Fig. S1. Comparison of the gene expression profiles of the ES cells and the cells induced by NC and NC-B condition. Scatter plots compares the normalized expression of every gene on the array (refer to Table S3). The central line -
Methylome and Transcriptome Maps of Human Visceral and Subcutaneous
www.nature.com/scientificreports OPEN Methylome and transcriptome maps of human visceral and subcutaneous adipocytes reveal Received: 9 April 2019 Accepted: 11 June 2019 key epigenetic diferences at Published: xx xx xxxx developmental genes Stephen T. Bradford1,2,3, Shalima S. Nair1,3, Aaron L. Statham1, Susan J. van Dijk2, Timothy J. Peters 1,3,4, Firoz Anwar 2, Hugh J. French 1, Julius Z. H. von Martels1, Brodie Sutclife2, Madhavi P. Maddugoda1, Michelle Peranec1, Hilal Varinli1,2,5, Rosanna Arnoldy1, Michael Buckley1,4, Jason P. Ross2, Elena Zotenko1,3, Jenny Z. Song1, Clare Stirzaker1,3, Denis C. Bauer2, Wenjia Qu1, Michael M. Swarbrick6, Helen L. Lutgers1,7, Reginald V. Lord8, Katherine Samaras9,10, Peter L. Molloy 2 & Susan J. Clark 1,3 Adipocytes support key metabolic and endocrine functions of adipose tissue. Lipid is stored in two major classes of depots, namely visceral adipose (VA) and subcutaneous adipose (SA) depots. Increased visceral adiposity is associated with adverse health outcomes, whereas the impact of SA tissue is relatively metabolically benign. The precise molecular features associated with the functional diferences between the adipose depots are still not well understood. Here, we characterised transcriptomes and methylomes of isolated adipocytes from matched SA and VA tissues of individuals with normal BMI to identify epigenetic diferences and their contribution to cell type and depot-specifc function. We found that DNA methylomes were notably distinct between diferent adipocyte depots and were associated with diferential gene expression within pathways fundamental to adipocyte function. Most striking diferential methylation was found at transcription factor and developmental genes. Our fndings highlight the importance of developmental origins in the function of diferent fat depots. -
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 -
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Supplemental Information Biological and Pharmaceutical Bulletin Promoter Methylation Profiles between Human Lung Adenocarcinoma Multidrug Resistant A549/Cisplatin (A549/DDP) Cells and Its Progenitor A549 Cells Ruiling Guo, Guoming Wu, Haidong Li, Pin Qian, Juan Han, Feng Pan, Wenbi Li, Jin Li, and Fuyun Ji © 2013 The Pharmaceutical Society of Japan Table S1. Gene categories involved in biological functions with hypomethylated promoter identified by MeDIP-ChIP analysis in lung adenocarcinoma MDR A549/DDP cells compared with its progenitor A549 cells Different biological Genes functions transcription factor MYOD1, CDX2, HMX1, THRB, ARNT2, ZNF639, HOXD13, RORA, FOXO3, HOXD10, CITED1, GATA1, activity HOXC6, ZGPAT, HOXC8, ATOH1, FLI1, GATA5, HOXC4, HOXC5, PHTF1, RARB, MYST2, RARG, SIX3, FOXN1, ZHX3, HMG20A, SIX4, NR0B1, SIX6, TRERF1, DDIT3, ASCL1, MSX1, HIF1A, BAZ1B, MLLT10, FOXG1, DPRX, SHOX, ST18, CCRN4L, TFE3, ZNF131, SOX5, TFEB, MYEF2, VENTX, MYBL2, SOX8, ARNT, VDR, DBX2, FOXQ1, MEIS3, HOXA6, LHX2, NKX2-1, TFDP3, LHX6, EWSR1, KLF5, SMAD7, MAFB, SMAD5, NEUROG1, NR4A1, NEUROG3, GSC2, EN2, ESX1, SMAD1, KLF15, ZSCAN1, VAV1, GAS7, USF2, MSL3, SHOX2, DLX2, ZNF215, HOXB2, LASS3, HOXB5, ETS2, LASS2, DLX5, TCF12, BACH2, ZNF18, TBX21, E2F8, PRRX1, ZNF154, CTCF, PAX3, PRRX2, CBFA2T2, FEV, FOS, BARX1, PCGF2, SOX15, NFIL3, RBPJL, FOSL1, ALX1, EGR3, SOX14, FOXJ1, ZNF92, OTX1, ESR1, ZNF142, FOSB, MIXL1, PURA, ZFP37, ZBTB25, ZNF135, HOXC13, KCNH8, ZNF483, IRX4, ZNF367, NFIX, NFYB, ZBTB16, TCF7L1, HIC1, TSC22D1, TSC22D2, REXO4, POU3F2, MYOG, NFATC2, ENO1, -
Cdx4 and Menin Co-Regulate Hoxa9 Expression in Hematopoietic Cells Jizhou Yan, Ya-Xiong Chen, Angela Desmond, Albert Silva, Yuqing Yang, Haoren Wang, Xianxin Hua*
Cdx4 and Menin Co-Regulate Hoxa9 Expression in Hematopoietic Cells Jizhou Yan, Ya-Xiong Chen, Angela Desmond, Albert Silva, Yuqing Yang, Haoren Wang, Xianxin Hua* Abramson Family Cancer Research Institute, Department of Cancer Biology, Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America Background. Transcription factor Cdx4 and transcriptional coregulator menin are essential for Hoxa9 expression and normal hematopoiesis. However, the precise mechanism underlying Hoxa9 regulation is not clear. Methods and Findings. Here, we show that the expression level of Hoxa9 is correlated with the location of increased trimethylated histone 3 lysine 4 (H3K4M3). The active and repressive histone modifications co-exist along the Hoxa9 regulatory region. We further demonstrate that both Cdx4 and menin bind to the same regulatory region at the Hoxa9 locus in vivo, and co-activate the reporter gene driven by the Hoxa9 cis-elements that contain Cdx4 binding sites. Ablation of menin abrogates Cdx4 access to the chromatin target and significantly reduces both active and repressive histone H3 modifications in the Hoxa9 locus. Conclusion. These results suggest a functional link among Cdx4, menin and histone modifications in Hoxa9 regulation in hematopoietic cells. Citation: Yan J, Chen Y-X, Desmond A, Silva A, Yang Y, et al. (2006) Cdx4 and Menin Co-Regulate Hoxa9 Expression in Hematopoietic Cells. PLoS ONE 1(1): e47. doi:10.1371/journal.pone.0000047 INTRODUCTION Hoxa9 overexpression is a common feature of acute myeloid Homeo-box-containing transcription factors (Hox proteins) play leukemia [19–21]. Although both menin and Cdx4 have been a pivotal role in normal differentiation and expansion of hemato- shown to participate in regulating Hoxa9 gene transcription and poietic cells [1,2].