An Rnai Screen for Aire Cofactors Reveals a Role for Hnrnpl in Polymerase Release and Aire-Activated Ectopic Transcription
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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. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
HNRPH1 (HNRNPH1) (NM 005520) Human Tagged ORF Clone Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RC201834 HNRPH1 (HNRNPH1) (NM_005520) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: HNRPH1 (HNRNPH1) (NM_005520) Human Tagged ORF Clone Tag: Myc-DDK Symbol: HNRNPH1 Synonyms: hnRNPH; HNRPH; HNRPH1 Vector: pCMV6-Entry (PS100001) E. coli Selection: Kanamycin (25 ug/mL) Cell Selection: Neomycin This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 6 HNRPH1 (HNRNPH1) (NM_005520) Human Tagged ORF Clone – RC201834 ORF Nucleotide >RC201834 ORF sequence Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGATGTTGGGCACGGAAGGTGGAGAGGGATTCGTGGTGAAGGTCCGGGGCTTGCCCTGGTCTTGCTCGG CCGATGAAGTGCAGAGGTTTTTTTCTGACTGCAAAATTCAAAATGGGGCTCAAGGTATTCGTTTCATCTA CACCAGAGAAGGCAGACCAAGTGGCGAGGCTTTTGTTGAACTTGAATCAGAAGATGAAGTCAAATTGGCC CTGAAAAAAGACAGAGAAACTATGGGACACAGATATGTTGAAGTATTCAAGTCAAACAACGTTGAAATGG ATTGGGTGTTGAAGCATACTGGTCCAAATAGTCCTGACACGGCCAATGATGGCTTTGTACGGCTTAGAGG ACTTCCCTTTGGATGTAGCAAGGAAGAAATTGTTCAGTTCTTCTCAGGGTTGGAAATCGTGCCAAATGGG ATAACATTGCCGGTGGACTTCCAGGGGAGGAGTACGGGGGAGGCCTTCGTGCAGTTTGCTTCACAGGAAA TAGCTGAAAAGGCTCTAAAGAAACACAAGGAAAGAATAGGGCACAGGTATATTGAAATCTTTAAGAGCAG TAGAGCTGAAGTTAGAACTCATTATGATCCACCACGAAAGCTTATGGCCATGCAGCGGCCAGGTCCTTAT -
Dynamic Transcriptomic Profiles of Zebrafish Gills in Response to Zinc
Zheng et al. BMC Genomics 2010, 11:548 http://www.biomedcentral.com/1471-2164/11/548 RESEARCH ARTICLE Open Access Dynamic transcriptomic profiles of zebrafish gills in response to zinc depletion Dongling Zheng1,4, Peter Kille2, Graham P Feeney2, Phil Cunningham1, Richard D Handy3, Christer Hogstrand1* Abstract Background: Zinc deficiency is detrimental to organisms, highlighting its role as an essential micronutrient contributing to numerous biological processes. To investigate the underlying molecular events invoked by zinc depletion we performed a temporal analysis of transcriptome changes observed within the zebrafish gill. This tissue represents a model system for studying ion absorption across polarised epithelial cells as it provides a major pathway for fish to acquire zinc directly from water whilst sharing a conserved zinc transporting system with mammals. Results: Zebrafish were treated with either zinc-depleted (water = 2.61 μgL-1; diet = 26 mg kg-1) or zinc-adequate (water = 16.3 μgL-1; diet = 233 mg kg-1) conditions for two weeks. Gill samples were collected at five time points and transcriptome changes analysed in quintuplicate using a 16K oligonucleotide array. Of the genes represented the expression of a total of 333 transcripts showed differential regulation by zinc depletion (having a fold-change greater than 1.8 and an adjusted P-value less than 0.1, controlling for a 10% False Discovery Rate). Down-regulation was dominant at most time points and distinct sets of genes were regulated at different stages. Annotation enrichment analysis revealed that ‘Developmental Process’ was the most significantly overrepresented Biological Process GO term (P = 0.0006), involving 26% of all regulated genes. -
Snapshot: the Splicing Regulatory Machinery Mathieu Gabut, Sidharth Chaudhry, and Benjamin J
192 Cell SnapShot: The Splicing Regulatory Machinery Mathieu Gabut, Sidharth Chaudhry, and Benjamin J. Blencowe 133 Banting and Best Department of Medical Research, University of Toronto, Toronto, ON M5S 3E1, Canada Expression in mouse , April4, 2008©2008Elsevier Inc. Low High Name Other Names Protein Domains Binding Sites Target Genes/Mouse Phenotypes/Disease Associations Amy Ceb Hip Hyp OB Eye SC BM Bo Ht SM Epd Kd Liv Lu Pan Pla Pro Sto Spl Thy Thd Te Ut Ov E6.5 E8.5 E10.5 SRp20 Sfrs3, X16 RRM, RS GCUCCUCUUC SRp20, CT/CGRP; −/− early embryonic lethal E3.5 9G8 Sfrs7 RRM, RS, C2HC Znf (GAC)n Tau, GnRH, 9G8 ASF/SF2 Sfrs1 RRM, RS RGAAGAAC HipK3, CaMKIIδ, HIV RNAs; −/− embryonic lethal, cond. KO cardiomyopathy SC35 Sfrs2 RRM, RS UGCUGUU AChE; −/− embryonic lethal, cond. KO deficient T-cell maturation, cardiomyopathy; LS SRp30c Sfrs9 RRM, RS CUGGAUU Glucocorticoid receptor SRp38 Fusip1, Nssr RRM, RS ACAAAGACAA CREB, type II and type XI collagens SRp40 Sfrs5, HRS RRM, RS AGGAGAAGGGA HipK3, PKCβ-II, Fibronectin SRp55 Sfrs6 RRM, RS GGCAGCACCUG cTnT, CD44 DOI 10.1016/j.cell.2008.03.010 SRp75 Sfrs4 RRM, RS GAAGGA FN1, E1A, CD45; overexpression enhances chondrogenic differentiation Tra2α Tra2a RRM, RS GAAARGARR GnRH; overexpression promotes RA-induced neural differentiation SR and SR-Related Proteins Tra2β Sfrs10 RRM, RS (GAA)n HipK3, SMN, Tau SRm160 Srrm1 RS, PWI AUGAAGAGGA CD44 SWAP Sfrs8 RS, SWAP ND SWAP, CD45, Tau; possible asthma susceptibility gene hnRNP A1 Hnrnpa1 RRM, RGG UAGGGA/U HipK3, SMN2, c-H-ras; rheumatoid arthritis, systemic lupus -
GTF2A1 (TFIIA-Alpha) Rabbit Polyclonal Antibody Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for AP20422PU-N GTF2A1 (TFIIA-alpha) Rabbit Polyclonal Antibody Product data: Product Type: Primary Antibodies Applications: IHC, WB Recommended Dilution: Western blot: 1/500-1/1000. Immunohistochemistry on paraffin sections: 1/50-1/200. Reactivity: Human, Mouse, Rat Host: Rabbit Clonality: Polyclonal Specificity: This antibody detects endogenous levels of TFIIA-α protein. (region surrounding Glu311) Formulation: Phosphate buffered saline (PBS), pH 7.2 State: Aff - Purified State: Liquid purified Ig fraction Preservative: 0.05% sodium azide Concentration: 1.0 mg/ml Purification: Affinity-chromatography using epitope-specific immunogen; purity is > 95% (by SDS-PAGE) Conjugation: Unconjugated Storage: Store undiluted at 2-8°C for one month or (in aliquots) at -20°C for longer. Avoid repeated freezing and thawing. Stability: Shelf life: one year from despatch. Predicted Protein Size: ~ 42 kDa Gene Name: Homo sapiens general transcription factor IIA subunit 1 (GTF2A1), transcript variant 1 Database Link: Entrez Gene 83602 MouseEntrez Gene 83830 RatEntrez Gene 2957 Human P52655 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 GTF2A1 (TFIIA-alpha) Rabbit Polyclonal Antibody – AP20422PU-N Background: Initiation of transcription from protein-coding genes in eukaryotes is a complex process that requires RNA polymerase II, as well as families of basal transcription factors. Binding of the factor TFIID (TBP) to the TATA box is believed to be the first step in the formation of a multiprotein complex containing several additional factors, including TFIIA, TFIIB, TFIIE, TFIIF and TFIIH. -
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. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Supporting Figure 8
HUGO ID Name HUGO ID Name Nalm-6 TOM-1 Reh Karpas-422 DoHH-2 SU-DHL-5 Nama lwa DG-75 Ramos Raji BEL EHEB BONNA-12 L-428 DEL BCP-1 BC-3 BCBL-1 JSC-1 PEL -SY HBL-6 DS-1 RPMI-8226 NCI-H929 L-363 SK-MM-2 Nalm-6 TOM-1 Reh Karpas-422 DoHH-2 SU-DHL-5 Nama lwa DG-75 Ramos Raji BEL EHEB BONNA-12 L-428 DEL BCP-1 BC-3 BCBL-1 JSC-1 PEL -SY HBL-6 DS-1 RPMI-8226 NCI-H929 L-363 SK-MM-2 CDC5L Cdc5-related protein (PCDC5RP) RAD51 Replication protein A (E coli RecA homolog) HSU53209 transformer-2 alpha (htra-2 alpha) HMG2 High-mobility group (nonhistone chromosomal) protein 2 CDC10 similar to TR:G560623 G560623 HCDC10 SPS selenium donor protein (selD) NFYB CAAT-box DNA binding protein subunit B CES2 Carboxylestease 2 (liver) GTF2I Bruton's tyrosine kinase-associated protein NOE1 clone 23876 neuronal olfactomedin-related ER localized CCT4 stimulator of TAR RNA binding (SRB) ZNF22 HKR-T1 RY1 RY-1 putative nucleic acid binding protein FKBP5 54 kDa progesterone receptor-associated FKBP54 DVL2 dishevelled 2 (DVL2) FKBP5 54 kDa progesterone receptor-associated FKBP54 RPL13 60S RIBOSOMAL PROTEIN L13 CU L4 A Hs-cul-4A C14ORF3 Hydroxyacyl-Coenzyme A dehydrogenase, beta subuit CU L4 A Hs-cul-4A SM S spermine synthase CLCN6 putative chloride channel SF3A1 splicing factor SF3a120 FALZ fetal Alz-50-reactive clone 1 (FAC1) KNSL4 oriP binding protein (OBP-1) GTF2H3 General transcription factor IIH, polypeptide 3 TUBA1 alpha-tubulin TRIP hT RIP TUBA1 Alpha-tubulin (K00558) GM2A glucose transporter pseudogene TUBA1 Alpha-tubulin (K00558) RBBP6 RBQ-1 TUBA1 TUBULIN ALPHA-4 -
Evolutionary Fate of Retroposed Gene Copies in the Human Genome
Evolutionary fate of retroposed gene copies in the human genome Nicolas Vinckenbosch*, Isabelle Dupanloup*†, and Henrik Kaessmann*‡ *Center for Integrative Genomics, University of Lausanne, Ge´nopode, 1015 Lausanne, Switzerland; and †Computational and Molecular Population Genetics Laboratory, Zoological Institute, University of Bern, 3012 Bern, Switzerland Communicated by Wen-Hsiung Li, University of Chicago, Chicago, IL, December 30, 2005 (received for review December 14, 2005) Given that retroposed copies of genes are presumed to lack the and rodent genomes (7–12). In addition, three recent studies regulatory elements required for their expression, retroposition using EST data (13, 14) and tiling-microarray data from chro- has long been considered a mechanism without functional rele- mosome 22 (15) indicated that retrocopy transcription may be vance. However, through an in silico assay for transcriptional widespread, although these surveys were limited, and potential activity, we identify here >1,000 transcribed retrocopies in the functional implications were not addressed. human genome, of which at least Ϸ120 have evolved into bona To further explore the functional significance of retroposition fide genes. Among these, Ϸ50 retrogenes have evolved functions in the human genome, we systematically screened for signatures in testes, more than half of which were recruited as functional of selection related to retrocopy transcription. Our results autosomal counterparts of X-linked genes during spermatogene- suggest that retrocopy transcription is not rare and that the sis. Generally, retrogenes emerge ‘‘out of the testis,’’ because they pattern of transcription of human retrocopies has been pro- are often initially transcribed in testis and later evolve stronger and foundly shaped by natural selection, acting both for and against sometimes more diverse spatial expression patterns. -
Application of Microrna Database Mining in Biomarker Discovery and Identification of Therapeutic Targets for Complex Disease
Article Application of microRNA Database Mining in Biomarker Discovery and Identification of Therapeutic Targets for Complex Disease Jennifer L. Major, Rushita A. Bagchi * and Julie Pires da Silva * Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; [email protected] * Correspondence: [email protected] (R.A.B.); [email protected] (J.P.d.S.) Supplementary Tables Methods Protoc. 2021, 4, 5. https://doi.org/10.3390/mps4010005 www.mdpi.com/journal/mps Methods Protoc. 2021, 4, 5. https://doi.org/10.3390/mps4010005 2 of 25 Table 1. List of all hsa-miRs identified by Human microRNA Disease Database (HMDD; v3.2) analysis. hsa-miRs were identified using the term “genetics” and “circulating” as input in HMDD. Targets CAD hsa-miR-1 Targets IR injury hsa-miR-423 Targets Obesity hsa-miR-499 hsa-miR-146a Circulating Obesity Genetics CAD hsa-miR-423 hsa-miR-146a Circulating CAD hsa-miR-149 hsa-miR-499 Circulating IR Injury hsa-miR-146a Circulating Obesity hsa-miR-122 Genetics Stroke Circulating CAD hsa-miR-122 Circulating Stroke hsa-miR-122 Genetics Obesity Circulating Stroke hsa-miR-26b hsa-miR-17 hsa-miR-223 Targets CAD hsa-miR-340 hsa-miR-34a hsa-miR-92a hsa-miR-126 Circulating Obesity Targets IR injury hsa-miR-21 hsa-miR-423 hsa-miR-126 hsa-miR-143 Targets Obesity hsa-miR-21 hsa-miR-223 hsa-miR-34a hsa-miR-17 Targets CAD hsa-miR-223 hsa-miR-92a hsa-miR-126 Targets IR injury hsa-miR-155 hsa-miR-21 Circulating CAD hsa-miR-126 hsa-miR-145 hsa-miR-21 Targets Obesity hsa-mir-223 hsa-mir-499 hsa-mir-574 Targets IR injury hsa-mir-21 Circulating IR injury Targets Obesity hsa-mir-21 Targets CAD hsa-mir-22 hsa-mir-133a Targets IR injury hsa-mir-155 hsa-mir-21 Circulating Stroke hsa-mir-145 hsa-mir-146b Targets Obesity hsa-mir-21 hsa-mir-29b Methods Protoc. -
A KMT2A-AFF1 Gene Regulatory Network Highlights the Role of Core Transcription Factors and Reveals the Regulatory Logic of Key Downstream Target Genes
Downloaded from genome.cshlp.org on October 7, 2021 - Published by Cold Spring Harbor Laboratory Press Research A KMT2A-AFF1 gene regulatory network highlights the role of core transcription factors and reveals the regulatory logic of key downstream target genes Joe R. Harman,1,7 Ross Thorne,1,7 Max Jamilly,2 Marta Tapia,1,8 Nicholas T. Crump,1 Siobhan Rice,1,3 Ryan Beveridge,1,4 Edward Morrissey,5 Marella F.T.R. de Bruijn,1 Irene Roberts,3,6 Anindita Roy,3,6 Tudor A. Fulga,2,9 and Thomas A. Milne1,6 1MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, United Kingdom; 2MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, United Kingdom; 3MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Department of Paediatrics, University of Oxford, Oxford, OX3 9DS, United Kingdom; 4Virus Screening Facility, MRC Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DS, United Kingdom; 5Center for Computational Biology, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DS, United Kingdom; 6NIHR Oxford Biomedical Research Centre Haematology Theme, University of Oxford, Oxford, OX3 9DS, United Kingdom Regulatory interactions mediated by transcription factors (TFs) make up complex networks that control cellular behavior. Fully understanding these gene regulatory networks (GRNs) offers greater insight into the consequences of disease-causing perturbations than can be achieved by studying single TF binding events in isolation. Chromosomal translocations of the lysine methyltransferase 2A (KMT2A) gene produce KMT2A fusion proteins such as KMT2A-AFF1 (previously MLL-AF4), caus- ing poor prognosis acute lymphoblastic leukemias (ALLs) that sometimes relapse as acute myeloid leukemias (AMLs).