Neonatal Maternal Deprivation Response and Developmental Changes in Gene Expression Revealed by Hypothalamic Gene Expression Profiling in Mice
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BMC Medical Genomics Biomed Central
BMC Medical Genomics BioMed Central Research article Open Access Data integration from two microarray platforms identifies bi-allelic genetic inactivation of RIC8A in a breast cancer cell line Aslaug Aamodt Muggerud†1,2, Henrik Edgren†3,4, Maija Wolf3,4, Kristine Kleivi1,4, Emelyne Dejeux5, Jörg Tost5, Therese Sørlie*†1,6 and Olli Kallioniemi*†3,4 Address: 1Department of Genetics, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, 0310 Oslo, Norway, 2Faculty of Medicine, Division The Norwegian Radium Hospital, University of Oslo, 0316 Oslo, Norway, 3Institute for Molecular Medicine (FIMM), University of Helsinki, Biomedicum Helsinki 2 U, Tukholmankatu 8, FIN-00290 Helsinki, Finland, 4Medical Biotechnology, VTT Technical Research Centre of Finland and Centre for Biotechnology, University of Turku, FIN-20520 Turku, Finland, 5CEA-Institut de Génomique, Centre National de Génotypage, Laboratory for Epigenetics, 2 rue Gaston Crèmieux, 91000 Evry, France and 6Department of Informatics, University of Oslo, Oslo, Norway Email: Aslaug Aamodt Muggerud - [email protected]; Henrik Edgren - [email protected]; Maija Wolf - [email protected]; Kristine Kleivi - [email protected]; Emelyne Dejeux - [email protected]; Jörg Tost - [email protected]; Therese Sørlie* - Therese.Sorlie@rr- research.no; Olli Kallioniemi* - [email protected] * Corresponding authors †Equal contributors Published: 11 May 2009 Received: 3 December 2008 Accepted: 11 May 2009 BMC Medical Genomics 2009, 2:26 doi:10.1186/1755-8794-2-26 This article is available from: http://www.biomedcentral.com/1755-8794/2/26 © 2009 Muggerud et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. -
A High Throughput, Functional Screen of Human Body Mass Index GWAS Loci Using Tissue-Specific Rnai Drosophila Melanogaster Crosses Thomas J
Washington University School of Medicine Digital Commons@Becker Open Access Publications 2018 A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses Thomas J. Baranski Washington University School of Medicine in St. Louis Aldi T. Kraja Washington University School of Medicine in St. Louis Jill L. Fink Washington University School of Medicine in St. Louis Mary Feitosa Washington University School of Medicine in St. Louis Petra A. Lenzini Washington University School of Medicine in St. Louis See next page for additional authors Follow this and additional works at: https://digitalcommons.wustl.edu/open_access_pubs Recommended Citation Baranski, Thomas J.; Kraja, Aldi T.; Fink, Jill L.; Feitosa, Mary; Lenzini, Petra A.; Borecki, Ingrid B.; Liu, Ching-Ti; Cupples, L. Adrienne; North, Kari E.; and Province, Michael A., ,"A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses." PLoS Genetics.14,4. e1007222. (2018). https://digitalcommons.wustl.edu/open_access_pubs/6820 This Open Access Publication is brought to you for free and open access by Digital Commons@Becker. It has been accepted for inclusion in Open Access Publications by an authorized administrator of Digital Commons@Becker. For more information, please contact [email protected]. Authors Thomas J. Baranski, Aldi T. Kraja, Jill L. Fink, Mary Feitosa, Petra A. Lenzini, Ingrid B. Borecki, Ching-Ti Liu, L. Adrienne Cupples, Kari E. North, and Michael A. Province This open access publication is available at Digital Commons@Becker: https://digitalcommons.wustl.edu/open_access_pubs/6820 RESEARCH ARTICLE A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses Thomas J. -
A High Throughput, Functional Screen of Human Body Mass Index GWAS Loci Using Tissue-Specific Rnai Drosophila Melanogaster Crosses
RESEARCH ARTICLE A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses Thomas J. Baranski1*, Aldi T. Kraja2, Jill L. Fink1, Mary Feitosa2, Petra A. Lenzini2, Ingrid B. Borecki3, Ching-Ti Liu4, L. Adrienne Cupples4, Kari E. North5, Michael A. Province2* a1111111111 1 Department of Internal Medicine, Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine, St. Louis, Missouri, United States of America, 2 Department of Genetics and a1111111111 Center for Genome Sciences and Systems Biology, Division of Statistical Genomics, Washington University a1111111111 School of Medicine, St. Louis, Missouri, United States of America, 3 Department of Biostatistics, University of a1111111111 Washington, Seattle, Washington, United States of America, 4 Department of Biostatistics, Boston University a1111111111 School of Public Health, Boston, Massachusetts, United States of America, 5 Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America * [email protected] (TJB); [email protected] (MAP) OPEN ACCESS Citation: Baranski TJ, Kraja AT, Fink JL, Feitosa M, Abstract Lenzini PA, Borecki IB, et al. (2018) A high Human GWAS of obesity have been successful in identifying loci associated with adiposity, throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi but for the most part, these are non-coding SNPs whose function, or even whose gene of Drosophila melanogaster crosses. PLoS Genet 14 action, is unknown. To help identify the genes on which these human BMI loci may be oper- (4): e1007222. https://doi.org/10.1371/journal. ating, we conducted a high throughput screen in Drosophila melanogaster. -
Agricultural University of Athens
ΓΕΩΠΟΝΙΚΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΑΘΗΝΩΝ ΣΧΟΛΗ ΕΠΙΣΤΗΜΩΝ ΤΩΝ ΖΩΩΝ ΤΜΗΜΑ ΕΠΙΣΤΗΜΗΣ ΖΩΙΚΗΣ ΠΑΡΑΓΩΓΗΣ ΕΡΓΑΣΤΗΡΙΟ ΓΕΝΙΚΗΣ ΚΑΙ ΕΙΔΙΚΗΣ ΖΩΟΤΕΧΝΙΑΣ ΔΙΔΑΚΤΟΡΙΚΗ ΔΙΑΤΡΙΒΗ Εντοπισμός γονιδιωματικών περιοχών και δικτύων γονιδίων που επηρεάζουν παραγωγικές και αναπαραγωγικές ιδιότητες σε πληθυσμούς κρεοπαραγωγικών ορνιθίων ΕΙΡΗΝΗ Κ. ΤΑΡΣΑΝΗ ΕΠΙΒΛΕΠΩΝ ΚΑΘΗΓΗΤΗΣ: ΑΝΤΩΝΙΟΣ ΚΟΜΙΝΑΚΗΣ ΑΘΗΝΑ 2020 ΔΙΔΑΚΤΟΡΙΚΗ ΔΙΑΤΡΙΒΗ Εντοπισμός γονιδιωματικών περιοχών και δικτύων γονιδίων που επηρεάζουν παραγωγικές και αναπαραγωγικές ιδιότητες σε πληθυσμούς κρεοπαραγωγικών ορνιθίων Genome-wide association analysis and gene network analysis for (re)production traits in commercial broilers ΕΙΡΗΝΗ Κ. ΤΑΡΣΑΝΗ ΕΠΙΒΛΕΠΩΝ ΚΑΘΗΓΗΤΗΣ: ΑΝΤΩΝΙΟΣ ΚΟΜΙΝΑΚΗΣ Τριμελής Επιτροπή: Aντώνιος Κομινάκης (Αν. Καθ. ΓΠΑ) Ανδρέας Κράνης (Eρευν. B, Παν. Εδιμβούργου) Αριάδνη Χάγερ (Επ. Καθ. ΓΠΑ) Επταμελής εξεταστική επιτροπή: Aντώνιος Κομινάκης (Αν. Καθ. ΓΠΑ) Ανδρέας Κράνης (Eρευν. B, Παν. Εδιμβούργου) Αριάδνη Χάγερ (Επ. Καθ. ΓΠΑ) Πηνελόπη Μπεμπέλη (Καθ. ΓΠΑ) Δημήτριος Βλαχάκης (Επ. Καθ. ΓΠΑ) Ευάγγελος Ζωίδης (Επ.Καθ. ΓΠΑ) Γεώργιος Θεοδώρου (Επ.Καθ. ΓΠΑ) 2 Εντοπισμός γονιδιωματικών περιοχών και δικτύων γονιδίων που επηρεάζουν παραγωγικές και αναπαραγωγικές ιδιότητες σε πληθυσμούς κρεοπαραγωγικών ορνιθίων Περίληψη Σκοπός της παρούσας διδακτορικής διατριβής ήταν ο εντοπισμός γενετικών δεικτών και υποψηφίων γονιδίων που εμπλέκονται στο γενετικό έλεγχο δύο τυπικών πολυγονιδιακών ιδιοτήτων σε κρεοπαραγωγικά ορνίθια. Μία ιδιότητα σχετίζεται με την ανάπτυξη (σωματικό βάρος στις 35 ημέρες, ΣΒ) και η άλλη με την αναπαραγωγική -
Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ...................................................... -
Aminopeptidase Expression in Multiple Myeloma Associates with Disease Progression and Sensitivity to Melflufen
cancers Article Aminopeptidase Expression in Multiple Myeloma Associates with Disease Progression and Sensitivity to Melflufen Juho J. Miettinen 1,† , Romika Kumari 1,†, Gunnhildur Asta Traustadottir 2 , Maiju-Emilia Huppunen 1, Philipp Sergeev 1, Muntasir M. Majumder 1, Alexander Schepsky 2 , Thorarinn Gudjonsson 2 , Juha Lievonen 3, Despina Bazou 4, Paul Dowling 5, Peter O‘Gorman 4, Ana Slipicevic 6, Pekka Anttila 3, Raija Silvennoinen 3 , Nina N. Nupponen 6, Fredrik Lehmann 6 and Caroline A. Heckman 1,* 1 Institute for Molecular Medicine Finland-FIMM, HiLIFE–Helsinki Institute of Life Science, iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, 00290 Helsinki, Finland; juho.miettinen@helsinki.fi (J.J.M.); romika.kumari@helsinki.fi (R.K.); maiju-emilia.huppunen@helsinki.fi (M.-E.H.); philipp.sergeev@helsinki.fi (P.S.); muntasir.mamun@helsinki.fi (M.M.M.) 2 Stem Cell Research Unit, Biomedical Center, University of Iceland, 101 Reykjavik, Iceland; [email protected] (G.A.T.); [email protected] (A.S.); [email protected] (T.G.) 3 Department of Hematology, Helsinki University Hospital Comprehensive Cancer Center, 00290 Helsinki, Finland; juha.lievonen@hus.fi (J.L.); pekka.anttila@hus.fi (P.A.); raija.silvennoinen@helsinki.fi (R.S.) 4 Department of Hematology, Mater Misericordiae University Hospital, D07 Dublin, Ireland; [email protected] (D.B.); [email protected] (P.O.) 5 Department of Biology, Maynooth University, National University of Ireland, Citation: Miettinen, J.J.; Kumari, R.; W23 F2H6 Maynooth, Co. Kildare, Ireland; [email protected] Traustadottir, G.A.; Huppunen, M.-E.; 6 Oncopeptides AB, 111 53 Stockholm, Sweden; [email protected] (A.S.); Sergeev, P.; Majumder, M.M.; [email protected] (N.N.N.); [email protected] (F.L.) Schepsky, A.; Gudjonsson, T.; * Correspondence: caroline.heckman@helsinki.fi; Tel.: +358-50-415-6769 † These authors equally contributed to this work. -
1 Supplementary Information ADCK2 Haploinsufficiency Reduces
Supplementary information ADCK2 haploinsufficiency reduces mitochondrial lipid oxidation and causes myopathy associated with CoQ deficiency.. Luis Vázquez-Fonseca1,8,§, Jochen Schäfer2,§, Ignacio Navas-Enamorado1,7, Carlos Santos-Ocaña1,10, Juan D. Hernández-Camacho1,10, Ignacio Guerra1, María V. Cascajo1,10, Ana Sánchez-Cuesta1,10, Zoltan Horvath2#, Emilio Siendones1, Cristina Jou3,10, Mercedes Casado3,10, Purificación Gutiérrez1, Gloria Brea-Calvo1,10, Guillermo López-Lluch1,10, Daniel M. Fernández-Ayala1,10, Ana B. Cortés- Rodríguez1,10, Juan C. Rodríguez-Aguilera1,10, Cristiane Matté4, Antonia Ribes5,10, Sandra Y. Prieto- Soler6, Eduardo Dominguez-del-Toro6, Andrea di Francesco8, Miguel A. Aon8, Michel Bernier8, Leonardo Salviati9, Rafael Artuch3,10, Rafael de Cabo8, Sandra Jackson2 and Plácido Navas1,10 1 Supplementary Results Case report The male index patient (subject II-3, Fig. S1A) presented to our clinic at 45 years of age with a 15-year history of slowly progressive muscle weakness and myalgia, which occurred at rest but worsened with exercise. Past medical history was unremarkable except for renal disease of unknown cause in childhood, which spontaneously improved. Family history was negative for neurological disease. On examination, moderate proximal symmetrical myopathy, more pronounced in the arms, was noted and the patient was unable to lift his arms above the horizontal position. The patient had a hyperlordotic, waddling gait and was only able to walk 100 meters without the aid of crutches. Bilateral scapular winging was present, and bilateral atrophy of the biceps, triceps, and quadriceps was noted, whilst the deltoid muscles were well preserved. Calf hypertrophy was present. The Trendelenburg sign was positive, and the patient was unable to rise from squatting. -
A Meta-Analysis of Genome-Wide Association Studies of Growth Differentiation Factor-15 Concentration in Blood
fgene-09-00097 March 21, 2018 Time: 17:25 # 1 ORIGINAL RESEARCH published: 23 March 2018 doi: 10.3389/fgene.2018.00097 A Meta-Analysis of Genome-Wide Association Studies of Growth Differentiation Factor-15 Concentration in Blood Jiyang Jiang1†, Anbupalam Thalamuthu1†, Jennifer E. Ho2,3, Anubha Mahajan4, Weronica E. Ek5, David A. Brown6,7, Samuel N. Breit6, Thomas J. Wang8, Ulf Gyllensten5, Edited by: 9,10 5 3 11 William Scott Bush, Ming-Huei Chen , Stefan Enroth , James L. Januzzi Jr. , Lars Lind , 1,12 13,14 13,14 1,15 Case Western Reserve University, Nicola J. Armstrong , John B. Kwok , Peter R. Schofield , Wei Wen , 1,16 5 4,17 18,19 United States Julian N. Trollor , Åsa Johansson , Andrew P. Morris , Ramachandran S. Vasan , Perminder S. Sachdev1,15* and Karen A. Mather1* Reviewed by: Jing Hua Zhao, 1 Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia, University of Cambridge, 2 Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, United States, 3 Cardiology Division, United Kingdom Department of Medicine, Massachusetts General Hospital, Boston, MA, United States, 4 Wellcome Trust Centre for Human Geetha Chittoor, Genetics, University of Oxford, Oxford, United Kingdom, 5 Science for Life Laboratory, Department of Immunology, Genetics Geisinger Health System, and Pathology, Uppsala University, Uppsala, Sweden, 6 St. Vincent’s Centre for Applied Medical Research, St. Vincent’s United States Hospital, Darlinghurst, NSW, Australia, 7 Westmead Institute for Medical Research, The Institute for Clinical Pathology and Brandon Pierce, Medical Research and Westmead Hospital, Westmead, NSW, Australia, 8 Division of Cardiology, Department of Medicine, University of Chicago, United States Vanderbilt University, Nashville, TN, United States, 9 Population Sciences Branch, National Heart, Lung, and Blood Institute, *Correspondence: National Institutes of Health, Framingham, MA, United States, 10 The Framingham Heart Study, Framingham, MA, Karen A. -
Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations Fall 2010 Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Renuka Nayak University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Computational Biology Commons, and the Genomics Commons Recommended Citation Nayak, Renuka, "Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress" (2010). Publicly Accessible Penn Dissertations. 1559. https://repository.upenn.edu/edissertations/1559 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/1559 For more information, please contact [email protected]. Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Abstract Genes interact in networks to orchestrate cellular processes. Here, we used coexpression networks based on natural variation in gene expression to study the functions and interactions of human genes. We asked how these networks change in response to stress. First, we studied human coexpression networks at baseline. We constructed networks by identifying correlations in expression levels of 8.9 million gene pairs in immortalized B cells from 295 individuals comprising three independent samples. The resulting networks allowed us to infer interactions between biological processes. We used the network to predict the functions of poorly-characterized human genes, and provided some experimental support. Examining genes implicated in disease, we found that IFIH1, a diabetes susceptibility gene, interacts with YES1, which affects glucose transport. Genes predisposing to the same diseases are clustered non-randomly in the network, suggesting that the network may be used to identify candidate genes that influence disease susceptibility. -
Winners Sorted by Institute-Center
FARE2020WINNERS Sorted By Institute Ji Chen Postdoctoral Fellow CC Neuroscience - General Toward a Wearable Pediatric Robotic Knee Exoskeleton for Real World Overground Gait Rehabilitation in Ambulatory Individuals Crouch gait, or excessive knee flexion, is a debilitating gait pathology in children with cerebral palsy (CP). Surgery, bracing and therapy provide only short term correction of crouch and more sustainable solutions remain a significant challenge in children with CP. One major hurdle is achieving the required dosage and intensity of gait training necessary to produce meaningful long term improvements in walking ability. Rather than replace lost or absent function, gait training in CP population aims to improve the participant’s baseline walking pattern by encouraging longer bouts of training and exercise, which is different than in those with paralysis. Wearable robotic exoskeletons, as a potential strategy, can assist individuals with CP to gradually regain knee extension over time and help maintain it for longer periods through intense task-specific gait training. We previously tested our initial prototype which produced significant improvement in knee extension comparable in magnitude to reported results from orthopedic surgery. Children continued to exert voluntary knee extensor muscle when walking with the exoskeleton which indicated the device was assisting but not controlling their gait. These positive initial results motivated us to design second prototype to expand the user population, and to enable its effective use outside of the laboratory environment. The current version has individualized control capability and device portability for home use as it implemented a multi-layered closed loop control system and a microcontroller based data acquisition system. -
Deciphering the Mode of Action and Position of Genetic Variants
Tarsani et al. BMC Genomics (2020) 21:512 https://doi.org/10.1186/s12864-020-06915-1 RESEARCH ARTICLE Open Access Deciphering the mode of action and position of genetic variants impacting on egg number in broiler breeders Eirini Tarsani1* , Andreas Kranis2,3, Gerasimos Maniatis2, Santiago Avendano2, Ariadne L. Hager-Theodorides1 and Antonios Kominakis1 Abstract Background: Aim of the present study was first to identify genetic variants associated with egg number (EN) in female broilers, second to describe the mode of their gene action (additive and/or dominant) and third to provide a list with implicated candidate genes for the trait. A number of 2586 female broilers genotyped with the high density (~ 600 k) SNP array and with records on EN (mean = 132.4 eggs, SD = 29.8 eggs) were used. Data were analyzed with application of additive and dominant multi-locus mixed models. Results: A number of 7 additive, 4 dominant and 6 additive plus dominant marker-trait significant associations were detected. A total number of 57 positional candidate genes were detected within 50 kb downstream and upstream flanking regions of the 17 significant markers. Functional enrichment analysis pinpointed two genes (BHLHE40 and CRTC1) to be involved in the ‘entrainment of circadian clock by photoperiod’ biological process. Gene prioritization analysis of the positional candidate genes identified 10 top ranked genes (GDF15, BHLHE40, JUND, GDF3, COMP, ITPR1, ELF3, ELL, CRLF1 and IFI30). Seven prioritized genes (GDF15, BHLHE40, JUND, GDF3, COMP, ELF3, CRTC1) have documented functional relevance to reproduction, while two more prioritized genes (ITPR1 and ELL) are reported to be related to egg quality in chickens. -
Aminopeptidase Expression in Multiple Myeloma Associates with Disease Progression and Sensitivity to Melflufen
Supplementary Materials Aminopeptidase Expression in Multiple Myeloma Associates with Disease Progression and Sensitivity to Melflufen Juho J. Miettinen, Romika Kumari, Gunnhildur Asta Traustadottir, Maiju-Emilia Huppunen, Philipp Sergeev, Muntasir M. Majumder, Alexander SChepsky, Thorarinn Gudjonsson, Juha Lievonen, Despina Bazou, Paul Dowling, Peter O`Gorman, Ana SlipiCeviC, Pekka Anttila, Raija Silvennoinen, Nina N. Nupponen, Fredrik Lehmann, and Caroline A. HeCkman TABLE OF CONTENTS Supplementary figures Figure S1. Drug plate layout and drug concentrations used in the flow cytometry-based drug sensitivity testing. Figure S2. Flow cytometry gating strategy used in drug sensitivity testing. Figure S3. Aminopeptidase gene family genes showed similar expression in both the CoMMpass and FIMM datasets. Figure S4. Correlation of aminopeptidase genes LAP3, ERAP2, METAP2, TPP2, DPP7, ERAP1, LTA4H, LNPEP (Group I) expression with myeloma patient cytogenetics and age in the FIMM dataset. Figure S5. Aminopeptidase gene expression positively correlates with aminopeptidase protein expression, especially for LAP3, BLMH, DPP3, DPP7, RNPEP, and ERAP2 aminopeptidases. Figure S6. CoMMpass dataset confirms that aminopeptidase genes are differentially expressed in NDMM vs. RRMM. Figure S7. Correlation of aminopeptidase genes differentially expressed between RRMM and NDMM with myeloma patient cytogenetics and ISS stage in the FIMM dataset. Figure S8. Prognostic significance of three aminopeptidase genes XPNPEP1, RNPEP, and DPP3 expression in NDMM and RRMM samples separately in the FIMM dataset. Figure S9. Prognostic significance of aminopeptidase gene expression in the CoMMpass dataset. Figure S10. Somatic mutation predictions for aminopeptidase genes in the FIMM dataset samples (n = 169). Figure S11. Somatic mutation predictions for aminopeptidase genes in CoMMpass dataset (n = 1164). Figure S12. Aminopeptidase gene CNVs in FIMM dataset MM samples (n = 169).