Genomewide Copy Number Analysis of Müllerian Adenosarcoma Identified
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THE ROLE of HOMEODOMAIN TRANSCRIPTION FACTOR IRX5 in CARDIAC CONTRACTILITY and HYPERTROPHIC RESPONSE by © COPYRIGHT by KYOUNG H
THE ROLE OF HOMEODOMAIN TRANSCRIPTION FACTOR IRX5 IN CARDIAC CONTRACTILITY AND HYPERTROPHIC RESPONSE By KYOUNG HAN KIM A THESIS SUBMITTED IN CONFORMITY WITH THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY GRADUATE DEPARTMENT OF PHYSIOLOGY UNIVERSITY OF TORONTO © COPYRIGHT BY KYOUNG HAN KIM (2011) THE ROLE OF HOMEODOMAIN TRANSCRIPTION FACTOR IRX5 IN CARDIAC CONTRACTILITY AND HYPERTROPHIC RESPONSE KYOUNG HAN KIM DOCTOR OF PHILOSOPHY GRADUATE DEPARTMENT OF PHYSIOLOGY UNIVERSITY OF TORONTO 2011 ABSTRACT Irx5 is a homeodomain transcription factor that negatively regulates cardiac fast transient + outward K currents (Ito,f) via the KV4.2 gene and is thereby a major determinant of the transmural repolarization gradient. While Ito,f is invariably reduced in heart disease and changes in Ito,f can modulate both cardiac contractility and hypertrophy, less is known about a functional role of Irx5, and its relationship with Ito,f, in the normal and diseased heart. Here I show that Irx5 plays crucial roles in the regulation of cardiac contractility and proper adaptive hypertrophy. Specifically, Irx5-deficient (Irx5-/-) hearts had reduced cardiac contractility and lacked the normal regional difference in excitation-contraction with decreased action potential duration, Ca2+ transients and myocyte shortening in sub-endocardial, but not sub-epicardial, myocytes. In addition, Irx5-/- mice showed less cardiac hypertrophy, but increased interstitial fibrosis and greater contractility impairment following pressure overload. A defect in hypertrophic responses in Irx5-/- myocardium was confirmed in cultured neonatal mouse ventricular myocytes, exposed to norepinephrine while being restored with Irx5 replacement. Interestingly, studies using mice ii -/- virtually lacking Ito,f (i.e. KV4.2-deficient) showed that reduced contractility in Irx5 mice was completely restored by loss of KV4.2, whereas hypertrophic responses to pressure-overload in hearts remained impaired when both Irx5 and Ito,f were absent. -
Genetic Mutation Analysis of High and Low Igy Chickens by Capture Sequencing
animals Article Genetic Mutation Analysis of High and Low IgY Chickens by Capture Sequencing 1,2, 1,2, 1,3 1,2 1,2 1,2 Qiao Wang y , Fei Wang y, Lu Liu , Qinghe Li , Ranran Liu , Maiqing Zheng , Huanxian Cui 1,2, Jie Wen 1,2 and Guiping Zhao 1,2,4,* 1 Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; [email protected] (Q.W.); [email protected] (F.W.); [email protected] (L.L.); [email protected] (Q.L.); [email protected] (R.L.); [email protected] (M.Z.); [email protected] (H.C.); [email protected] (J.W.) 2 State Key Laboratory of Animal Nutrition, Beijing 100193, China 3 College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China 4 School of Life Science and Engineering, Foshan University, Foshan 528225, China * Correspondence: [email protected] These authors contributed equally to this work. y Received: 6 March 2019; Accepted: 20 May 2019; Published: 23 May 2019 Simple Summary: Immunoglobulin Y (IgY) is the major antibody produced by hens and it endows their offspring with effective humoral immunity against the pathogens. In previous research, we identified 13 genomic regions that were significantly associated with the serum IgY level or antibody responses to sheep red-blood-cells, but the specific mutations in these regions have not been reported. Therefore, we screened for variations in these regions in White Leghorn and Beijing-You chickens with high and low IgY. Our study identified 35,154 mutations and 829 Indels which were associated with IgY levels in both lines. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Podocyte Specific Knockdown of Klf15 in Podocin-Cre Klf15flox/Flox Mice Was Confirmed
SUPPLEMENTARY FIGURE LEGENDS Supplementary Figure 1: Podocyte specific knockdown of Klf15 in Podocin-Cre Klf15flox/flox mice was confirmed. (A) Primary glomerular epithelial cells (PGECs) were isolated from 12-week old Podocin-Cre Klf15flox/flox and Podocin-Cre Klf15+/+ mice and cultured at 37°C for 1 week. Real-time PCR was performed for Nephrin, Podocin, Synaptopodin, and Wt1 mRNA expression (n=6, ***p<0.001, Mann-Whitney test). (B) Real- time PCR was performed for Klf15 mRNA expression (n=6, *p<0.05, Mann-Whitney test). (C) Protein was also extracted and western blot analysis for Klf15 was performed. The representative blot of three independent experiments is shown in the top panel. The bottom panel shows the quantification of Klf15 by densitometry (n=3, *p<0.05, Mann-Whitney test). (D) Immunofluorescence staining for Klf15 and Wt1 was performed in 12-week old Podocin-Cre Klf15flox/flox and Podocin-Cre Klf15+/+ mice. Representative images from four mice in each group are shown in the left panel (X 20). Arrows show colocalization of Klf15 and Wt1. Arrowheads show a lack of colocalization. Asterisk demonstrates nonspecific Wt1 staining. “R” represents autofluorescence from RBCs. In the right panel, a total of 30 glomeruli were selected in each mouse and quantification of Klf15 staining in the podocytes was determined by the ratio of Klf15+ and Wt1+ cells to Wt1+ cells (n=6 mice, **p<0.01, unpaired t test). Supplementary Figure 2: LPS treated Podocin-Cre Klf15flox/flox mice exhibit a lack of recovery in proteinaceous casts and tubular dilatation after DEX administration. -
CCT2 Antibody A
Revision 5 C 0 2 - t CCT2 Antibody a e r o t S Orders: 877-616-CELL (2355) [email protected] Support: 877-678-TECH (8324) 1 6 Web: [email protected] 5 www.cellsignal.com 3 # 3 Trask Lane Danvers Massachusetts 01923 USA For Research Use Only. Not For Use In Diagnostic Procedures. Applications: Reactivity: Sensitivity: MW (kDa): Source: UniProt ID: Entrez-Gene Id: WB, IP H M R Mk Endogenous 54 Rabbit P78371 10576 Product Usage Information 6. McCormack, E.A. et al. (2001) J Struct Biol 135, 198-204. Application Dilution Western Blotting 1:1000 Immunoprecipitation 1:100 Storage Supplied in 10 mM sodium HEPES (pH 7.5), 150 mM NaCl, 100 µg/ml BSA and 50% glycerol. Store at –20°C. Do not aliquot the antibody. Specificity / Sensitivity CCT2 Antibody detects endogenous levels of total CCT2 protein. Species Reactivity: Human, Mouse, Rat, Monkey Source / Purification Polyclonal antibodies are produced by immunizing animals with a synthetic peptide corresponding to human CCT2. Antibodies are purified by protein A and peptide affinity chromatography. Background CCT2 is one of eight largely unrelated subunit proteins found in a protein chaperone complex known as the chaperonin-containing TCP-1 (CCT) or TRiC complex. The CCT complex is an abundanct cytoslic component that is credited with helping newly synthesized polypeptides adopt the correct conformation (1). Proteins that fold and assemble with the help of CCT include the cytoskeletal proteins actin and tubulin as well as up to 15% of newly synthesized eukaryotic proteins (2). CCT2 is the β-subunit of the chaperone complex and is one of several CCT proteins that exhibit increased expression in response to stress. -
Table S1 the Four Gene Sets Derived from Gene Expression Profiles of Escs and Differentiated Cells
Table S1 The four gene sets derived from gene expression profiles of ESCs and differentiated cells Uniform High Uniform Low ES Up ES Down EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol 269261 Rpl12 11354 Abpa 68239 Krt42 15132 Hbb-bh1 67891 Rpl4 11537 Cfd 26380 Esrrb 15126 Hba-x 55949 Eef1b2 11698 Ambn 73703 Dppa2 15111 Hand2 18148 Npm1 11730 Ang3 67374 Jam2 65255 Asb4 67427 Rps20 11731 Ang2 22702 Zfp42 17292 Mesp1 15481 Hspa8 11807 Apoa2 58865 Tdh 19737 Rgs5 100041686 LOC100041686 11814 Apoc3 26388 Ifi202b 225518 Prdm6 11983 Atpif1 11945 Atp4b 11614 Nr0b1 20378 Frzb 19241 Tmsb4x 12007 Azgp1 76815 Calcoco2 12767 Cxcr4 20116 Rps8 12044 Bcl2a1a 219132 D14Ertd668e 103889 Hoxb2 20103 Rps5 12047 Bcl2a1d 381411 Gm1967 17701 Msx1 14694 Gnb2l1 12049 Bcl2l10 20899 Stra8 23796 Aplnr 19941 Rpl26 12096 Bglap1 78625 1700061G19Rik 12627 Cfc1 12070 Ngfrap1 12097 Bglap2 21816 Tgm1 12622 Cer1 19989 Rpl7 12267 C3ar1 67405 Nts 21385 Tbx2 19896 Rpl10a 12279 C9 435337 EG435337 56720 Tdo2 20044 Rps14 12391 Cav3 545913 Zscan4d 16869 Lhx1 19175 Psmb6 12409 Cbr2 244448 Triml1 22253 Unc5c 22627 Ywhae 12477 Ctla4 69134 2200001I15Rik 14174 Fgf3 19951 Rpl32 12523 Cd84 66065 Hsd17b14 16542 Kdr 66152 1110020P15Rik 12524 Cd86 81879 Tcfcp2l1 15122 Hba-a1 66489 Rpl35 12640 Cga 17907 Mylpf 15414 Hoxb6 15519 Hsp90aa1 12642 Ch25h 26424 Nr5a2 210530 Leprel1 66483 Rpl36al 12655 Chi3l3 83560 Tex14 12338 Capn6 27370 Rps26 12796 Camp 17450 Morc1 20671 Sox17 66576 Uqcrh 12869 Cox8b 79455 Pdcl2 20613 Snai1 22154 Tubb5 12959 Cryba4 231821 Centa1 17897 -
Loss-Of-Function Mutation in the Dioxygenase-Encoding FTO Gene
Loss-of-Function Mutation in the Dioxygenase-Encoding FTO Gene Causes Severe Growth Retardation and Multiple Malformations Sarah Boissel, Orit Reish, Karine Proulx, Hiroko Kawagoe-Takaki, Barbara Sedgwick, Giles Yeo, David Meyre, Christelle Golzio, Florence Molinari, Noman Kadhom, et al. To cite this version: Sarah Boissel, Orit Reish, Karine Proulx, Hiroko Kawagoe-Takaki, Barbara Sedgwick, et al.. Loss-of- Function Mutation in the Dioxygenase-Encoding FTO Gene Causes Severe Growth Retardation and Multiple Malformations. American Journal of Human Genetics, Elsevier (Cell Press), 2009, 85 (1), pp.106-111. 10.1016/j.ajhg.2009.06.002. hal-02044723 HAL Id: hal-02044723 https://hal.archives-ouvertes.fr/hal-02044723 Submitted on 21 Feb 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. REPORT Loss-of-Function Mutation in the Dioxygenase-Encoding FTO Gene Causes Severe Growth Retardation and Multiple Malformations Sarah Boissel,1,7 Orit Reish,2,7 Karine Proulx,3,7 Hiroko Kawagoe-Takaki,4 Barbara Sedgwick,4 Giles S.H. Yeo,3 David Meyre,5 Christelle Golzio,1 Florence Molinari,1 Noman Kadhom,1 Heather C. Etchevers,1 Vladimir Saudek,3 I. Sadaf Farooqi,3 Philippe Froguel,5,6 Tomas Lindahl,4 Stephen O’Rahilly,3 Arnold Munnich,1 and Laurence Colleaux1,* FTO is a nuclear protein belonging to the AlkB-related non-haem iron- and 2-oxoglutarate-dependent dioxygenase family. -
High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model
Purdue University Purdue e-Pubs Department of Animal Sciences Faculty Department of Animal Sciences Publications 2016 High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model Chiao-Ling Lo Indiana University School of Medicine Amy C. Lossie Indiana University School of Medicine Tiebing Liang Indiana University School of Medicine Yunlong Liu Indiana University School of Medicine Xiaoling Xuei Indiana University School of Medicine See next page for additional authors Follow this and additional works at: http://docs.lib.purdue.edu/anscpubs Recommended Citation Lo C-L, Lossie AC, Liang T, Liu Y, Xuei X, Lumeng L, et al. (2016) High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model. PLoS Genet 12(8): e1006178. https://doi.org/10.1371/ journal.pgen.1006178 This document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact [email protected] for additional information. Authors Chiao-Ling Lo, Amy C. Lossie, Tiebing Liang, Yunlong Liu, Xiaoling Xuei, Lawrence Lumeng, Feng C. Zhou, and William M. Muir This article is available at Purdue e-Pubs: http://docs.lib.purdue.edu/anscpubs/19 RESEARCH ARTICLE High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model Chiao-Ling Lo1,2, Amy C. Lossie1,3¤, Tiebing Liang1,4, Yunlong Liu1,5, Xiaoling Xuei1,6, Lawrence Lumeng1,4, Feng C. Zhou1,2,7*, William -
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. -
Evidence for Differential Alternative Splicing in Blood of Young Boys With
Stamova et al. Molecular Autism 2013, 4:30 http://www.molecularautism.com/content/4/1/30 RESEARCH Open Access Evidence for differential alternative splicing in blood of young boys with autism spectrum disorders Boryana S Stamova1,2,5*, Yingfang Tian1,2,4, Christine W Nordahl1,3, Mark D Shen1,3, Sally Rogers1,3, David G Amaral1,3 and Frank R Sharp1,2 Abstract Background: Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. Methods: RNA from blood was processed on whole genome exon arrays for 2-4–year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). Results: A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. -
Profiling Data
Compound Name DiscoveRx Gene Symbol Entrez Gene Percent Compound Symbol Control Concentration (nM) JNK-IN-8 AAK1 AAK1 69 1000 JNK-IN-8 ABL1(E255K)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317I)-nonphosphorylated ABL1 87 1000 JNK-IN-8 ABL1(F317I)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317L)-nonphosphorylated ABL1 65 1000 JNK-IN-8 ABL1(F317L)-phosphorylated ABL1 61 1000 JNK-IN-8 ABL1(H396P)-nonphosphorylated ABL1 42 1000 JNK-IN-8 ABL1(H396P)-phosphorylated ABL1 60 1000 JNK-IN-8 ABL1(M351T)-phosphorylated ABL1 81 1000 JNK-IN-8 ABL1(Q252H)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(Q252H)-phosphorylated ABL1 56 1000 JNK-IN-8 ABL1(T315I)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(T315I)-phosphorylated ABL1 92 1000 JNK-IN-8 ABL1(Y253F)-phosphorylated ABL1 71 1000 JNK-IN-8 ABL1-nonphosphorylated ABL1 97 1000 JNK-IN-8 ABL1-phosphorylated ABL1 100 1000 JNK-IN-8 ABL2 ABL2 97 1000 JNK-IN-8 ACVR1 ACVR1 100 1000 JNK-IN-8 ACVR1B ACVR1B 88 1000 JNK-IN-8 ACVR2A ACVR2A 100 1000 JNK-IN-8 ACVR2B ACVR2B 100 1000 JNK-IN-8 ACVRL1 ACVRL1 96 1000 JNK-IN-8 ADCK3 CABC1 100 1000 JNK-IN-8 ADCK4 ADCK4 93 1000 JNK-IN-8 AKT1 AKT1 100 1000 JNK-IN-8 AKT2 AKT2 100 1000 JNK-IN-8 AKT3 AKT3 100 1000 JNK-IN-8 ALK ALK 85 1000 JNK-IN-8 AMPK-alpha1 PRKAA1 100 1000 JNK-IN-8 AMPK-alpha2 PRKAA2 84 1000 JNK-IN-8 ANKK1 ANKK1 75 1000 JNK-IN-8 ARK5 NUAK1 100 1000 JNK-IN-8 ASK1 MAP3K5 100 1000 JNK-IN-8 ASK2 MAP3K6 93 1000 JNK-IN-8 AURKA AURKA 100 1000 JNK-IN-8 AURKA AURKA 84 1000 JNK-IN-8 AURKB AURKB 83 1000 JNK-IN-8 AURKB AURKB 96 1000 JNK-IN-8 AURKC AURKC 95 1000 JNK-IN-8 -
22 Ultra-Conserved Elements in Vertebrate and Fly Genomes Mathias Drton Nicholas Eriksson Garmay Leung
22 Ultra-Conserved Elements in Vertebrate and Fly Genomes Mathias Drton Nicholas Eriksson Garmay Leung Ultra-conserved elements in an alignment of multiple genomes are consecutive nucleotides that are in perfect agreement across all the genomes. For aligned vertebrate and fly genomes, we give descriptive statistics of ultra-conserved elements, explain their biological relevance, and show that the existence of ultra-conserved elements is highly improbable in neutrally evolving regions. 22.1 The data Our analyses of ultra-conserved elements are based on multiple sequence align- ments produced by MAVID [Bray and Pachter, 2004]. Prior to the alignment of multiple genomes, homology mappings (from Mercator [Dewey, 2005]) group into bins genomic regions that are anchored together by neighboring homolo- gous exons. A multiple sequence alignment is then produced for each of these alignment bins. MAVID is a global multiple alignment program, and therefore homologous regions with more than one homologous hit to another genome may not be found aligned together. Table 22.1 shows an example of Merca- tor’s output for a single region along with the beginning of the resulting MAVID multiple sequence alignment. Species Chrom. Start End Alignment Dog chrX 752057 864487 + A----AACCAAA--------- Chicken chr1 122119382 122708162 − TGCTGAGCTAAAGATCAGGCT Zebrafish chr9 19018916 19198136 + ------ATGCAACATGCTTCT Pufferfish chr2 7428614 7525502 + ---TAGATGGCAGACGATGCT Fugufish asm1287 21187 82482 + ---TCAAGGG----------- Table 22.1. Mercator output for a single bin, giving the position and orientation on the chromosome. Notice that the Fugu fish genome has not been fully assembled into chromosomes (cf. Section 4.2). The vertebrate dataset consists of 10,279 bins over 9 genomes (Table 22.2).