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Cytogenomic SNP Microarray - Fetal ARUP Test Code 2002366 Maternal Contamination Study Fetal Spec Fetal Cells
Patient Report |FINAL Client: Example Client ABC123 Patient: Patient, Example 123 Test Drive Salt Lake City, UT 84108 DOB 2/13/1987 UNITED STATES Gender: Female Patient Identifiers: 01234567890ABCD, 012345 Physician: Doctor, Example Visit Number (FIN): 01234567890ABCD Collection Date: 00/00/0000 00:00 Cytogenomic SNP Microarray - Fetal ARUP test code 2002366 Maternal Contamination Study Fetal Spec Fetal Cells Single fetal genotype present; no maternal cells present. Fetal and maternal samples were tested using STR markers to rule out maternal cell contamination. This result has been reviewed and approved by Maternal Specimen Yes Cytogenomic SNP Microarray - Fetal Abnormal * (Ref Interval: Normal) Test Performed: Cytogenomic SNP Microarray- Fetal (ARRAY FE) Specimen Type: Direct (uncultured) villi Indication for Testing: Patient with 46,XX,t(4;13)(p16.3;q12) (Quest: EN935475D) ----------------------------------------------------------------- ----- RESULT SUMMARY Abnormal Microarray Result (Male) Unbalanced Translocation Involving Chromosomes 4 and 13 Classification: Pathogenic 4p Terminal Deletion (Wolf-Hirschhorn syndrome) Copy number change: 4p16.3p16.2 loss Size: 5.1 Mb 13q Proximal Region Deletion Copy number change: 13q11q12.12 loss Size: 6.1 Mb ----------------------------------------------------------------- ----- RESULT DESCRIPTION This analysis showed a terminal deletion (1 copy present) involving chromosome 4 within 4p16.3p16.2 and a proximal interstitial deletion (1 copy present) involving chromosome 13 within 13q11q12.12. This -
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. -
De Novo EIF2AK1 and EIF2AK2 Variants Are Associated with Developmental Delay, Leukoencephalopathy, and Neurologic Decompensation
bioRxiv preprint doi: https://doi.org/10.1101/757039; this version posted September 16, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. De novo EIF2AK1 and EIF2AK2 variants are associated with developmental delay, leukoencephalopathy, and neurologic decompensation Dongxue Mao1,2, Chloe M. Reuter3,4, Maura R.Z. Ruzhnikov5,6, Anita E. Beck7, Emily G. Farrow8,9,10, Lisa T. Emrick1,11,12,13, Jill A. Rosenfeld12, Katherine M. Mackenzie5, Laurie Robak2,12,13, Matthew T. Wheeler3,14, Lindsay C. Burrage12,13, Mahim Jain15, Pengfei Liu12, Daniel Calame11,13, Sebastien Küry17,18, Martin Sillesen19, Klaus Schmitz-Abe20, Davide Tonduti21, Luigina Spaccini22, Maria Iascone23, Casie A. Genetti20, Madeline Graf16, Alyssa Tran12, Mercedes Alejandro12, Undiagnosed Diseases Network, Brendan H. Lee12,13, Isabelle Thiffault8,9,24, Pankaj B. Agrawal#,20, Jonathan A. Bernstein#,3,25, Hugo J. Bellen#,2,12,26,27,28, Hsiao- Tuan Chao#,1,2,11,12,13,28,27,29 #Correspondence should be addressed: [email protected] (P.A.), [email protected] (J.A.B.), [email protected] (H.J.B.), [email protected] (H.T.C.) 1Department of Pediatrics, Baylor College of Medicine (BCM), Houston, TX 2Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX 3Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA 4Stanford Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, -
Targeting PH Domain Proteins for Cancer Therapy
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 12-2018 Targeting PH domain proteins for cancer therapy Zhi Tan Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Bioinformatics Commons, Medicinal Chemistry and Pharmaceutics Commons, Neoplasms Commons, and the Pharmacology Commons Recommended Citation Tan, Zhi, "Targeting PH domain proteins for cancer therapy" (2018). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 910. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/910 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]. TARGETING PH DOMAIN PROTEINS FOR CANCER THERAPY by Zhi Tan Approval page APPROVED: _____________________________________________ Advisory Professor, Shuxing Zhang, Ph.D. _____________________________________________ -
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Table S1. Putative miR-322 target transcripts which is highly expressed in MGCs ________________________________________________________________________________ 0610037L13Rik, 1700037H04Rik, 2310061I04Rik, 2810006K23Rik, Abcc5, Abhd16a, Acbd3, Acox1, Acsbg1, Acsl4, Actr1a, Actr2, Adck5, Adh5, Adrbk1, Aff4, Agk, Ahcyl1, Akap11, Akap7, Akirin1, Alg3, Amfr, Ammecr1, Amotl2, Ankfy1, Ankhd1, Ankrd52, Ap2a1, Ap2b1, Ap3b1, Ap3d1, App, Arcn1, Arf3, Arfgap2, Arhgap12, Arhgap5, Arhgdia, Arhgef11, Arih1, Arl2, Arl3, Arl8b, Armcx6, Asap1, Asnsd1, Atf6, Atg13, Atg4b, Atp13a3, Atp5g1, Atp6v1a, Atxn2, Atxn7l3, Atxn7l3b, AW549877, B4galt1, B4galt7, Bace1, Bag5, Baiap2, Baz2a, BC037034, Bcl2l1, Bcl2l2, Bfar, Bmpr1a, Bptf, Brd2, Brd4, Brpf3, Btbd3, Btg2, Cab39, Cacna2d1, Calm1, Capns1, Caprin1, Capza2, Carm1, Caskin1, Cbfa2t3, Cbx5, Cbx6, Cc2d1b, Ccdc127, Ccdc6, Ccnd2, Ccnt2, Ccnyl1, Cd164, Cd2ap, Cdc25a, Cdc27, Cdc37l1, Cdc42se2, Cdca4, Cdipt, Cdk5rap3, Cdk8, Cdk9, Cdv3, Celf1, Cfl2, Chchd3, Chd6, Chmp1a, Chmp7, Chordc1, Chpf, Chpt1, Chst8, Chtf8, Cisd2, Clasrp, Clcn3, Clstn1, Cmpk1, Cnih2, Cnot1, Cnot2, Col4a3bp, Cope, Cops2, Cops7a, Cops7b, Copz1, Coq6, Cpd, Crebzf, Crim1, Crk, Crkl, Csde1, Cse1l, Ctnnb1, Cul4a, Cul4b, Cxx1a, Cxx1b, Cxx1c, D15Ertd621e, D2hgdh, Dcaf7, Dcbld2, Dcp1a, Dctn5, Ddost, Ddr1, Ddx39, Ddx3x, Ddx6, Dedd, Dhdds, Dhx16, Diap1, Dido1, Dlst, Dmtf1, Dnaja2, Dnajb14, Dnajb2, Dnajc1, Dnajc16, Dnajc25, Dph3, Dpm1, Dpp9, Dpy19l4, Dsel, Dtl, Dvl1, Dync1li2, Dynll2, Dynlt3, Dyrk1a, Dyrk1b, Ebna1bp2, Edc4, Eftud2, Egln2, Eif1a, Eif2b2, Eif2s1, -
Mapping the Spatial Proteome of Metastatic Cells in Colorectal Cancer
Mapping the spatial proteome of metastatic cells in colorectal cancer Marta Mendes‡¶, Alberto Peláez-García‡¥, María López-Lucendo‡, Ruben A. Bartolomé‡, Eva Calviño‡, Rodrigo Barderas‡§**, J. Ignacio Casal‡** ‡Department of Cellular and Molecular Medicine, Centro de Investigaciones Biológicas (CIB-CSIC), Madrid, Spain §Instituto de Salud Carlos III. Majadahonda. Spain ¶Present address: Technische Universität Berlin, Germany ¥Present address: Department of Pathology, Hospital Universitario La Paz, IdiPAZ, Madrid, Spain Running title: Mapping the metastatic proteome Keywords: Spatial proteome, cell fractionation, SILAC, metastasis, colorectal cancer ** To whom correspondence should be addressed: Department of Cellular and Molecular Medicine, Centro de Investigaciones Biológicas (CIB-CSIC), Ramiro de Maeztu, 9, 28040 Madrid, Spain. Tel.: +34 918373112; E-mail: [email protected]. Instituto de Salud Carlos III, Majadahonda, Spain Carretera de Majadahonda - Pozuelo, Km. 2.200, 28220 Majadahonda, Madrid, Spain. Tel.: +34 913944155; E-mail: [email protected] 1 ABSTRACT Colorectal cancer (CRC) is the second deadliest cancer worldwide. Here, we aimed to study metastasis mechanisms using spatial proteomics in the KM12 cell model. Cells were SILAC-labeled and fractionated into five subcellular fractions corresponding to: cytoplasm, plasma, mitochondria and ER/golgi membranes, nuclear, chromatin-bound and cytoskeletal proteins and analyzed with high resolution mass spectrometry. We provide localization data of 4863 quantified proteins in the different subcellular fractions. A total of 1318 proteins with at least 1.5-fold change were deregulated in highly metastatic KM12SM cells respect to KM12C cells. The protein network organization, protein complexes and functional pathways associated to CRC metastasis was revealed with spatial resolution. Although 92% of the differentially expressed proteins showed the same deregulation in all subcellular compartments, a subset of 117 proteins (8%) showed opposite changes in different subcellular localizations. -
EIF2B2 Gene Eukaryotic Translation Initiation Factor 2B Subunit Beta
EIF2B2 gene eukaryotic translation initiation factor 2B subunit beta Normal Function The EIF2B2 gene provides instructions for making one of five parts of a protein called eIF2B, specifically the beta subunit of this protein. The eIF2B protein helps regulate overall protein production (synthesis) in the cell by interacting with another protein, eIF2. The eIF2 protein is called an initiation factor because it is involved in starting (initiating) protein synthesis. Under some conditions, eIF2B increases protein synthesis by helping to recycle molecules called GTP, which carry energy to the initiation factor. Under other conditions, it slows protein synthesis by binding tightly to the initiation factor, which converts the eIF2B protein into an inactive form and prevents recycling of GTP. Proper regulation of protein synthesis is vital for ensuring that the correct levels of protein are available for the cell to cope with changing conditions. For example, cells must synthesize protein much faster if they are multiplying than if they are in a resting state. Health Conditions Related to Genetic Changes Leukoencephalopathy with vanishing white matter Mutations in the EIF2B2 gene have been identified in a few people with leukoencephalopathy with vanishing white matter, including some affected females with a variant of the disorder in which the neurological features are accompanied by ovarian failure (ovarioleukodystrophy). These mutations cause partial loss of eIF2B function. Impairment of eIF2B function makes it more difficult for the body's cells to regulate protein synthesis and deal with changing conditions and stress. Researchers believe that cells in the white matter (nerve fibers covered by a fatty substance called myelin that insulates and protects nerves) may be particularly affected by an abnormal response to stress, resulting in the signs and symptoms of leukoencephalopathy with vanishing white matter. -
Rna-Sequencing Applications: Gene Expression Quantification and Methylator Phenotype Identification
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 8-2013 RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION Guoshuai Cai Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Bioinformatics Commons, Computational Biology Commons, and the Medicine and Health Sciences Commons Recommended Citation Cai, Guoshuai, "RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION" (2013). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 386. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/386 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]. RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION -
Mechanisms of Action of Coxiella Burnetii Effectors Inferred from Host-Pathogen Protein Interactions
RESEARCH ARTICLE Mechanisms of action of Coxiella burnetii effectors inferred from host-pathogen protein interactions Anders Wallqvist1, Hao Wang1, Nela Zavaljevski1, Vesna MemisÏević1, Keehwan Kwon2, Rembert Pieper2, Seesandra V. Rajagopala2, Jaques Reifman1* 1 Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America, 2 J. Craig Venter Institute, Rockville, Maryland, United States of America a1111111111 a1111111111 * [email protected] a1111111111 a1111111111 a1111111111 Abstract Coxiella burnetii is an obligate Gram-negative intracellular pathogen and the etiological agent of Q fever. Successful infection requires a functional Type IV secretion system, which OPEN ACCESS translocates more than 100 effector proteins into the host cytosol to establish the infection, Citation: Wallqvist A, Wang H, Zavaljevski N, restructure the intracellular host environment, and create a parasitophorous vacuole where MemisÏević V, Kwon K, Pieper R, et al. (2017) the replicating bacteria reside. We used yeast two-hybrid (Y2H) screening of 33 selected C. Mechanisms of action of Coxiella burnetii effectors burnetii effectors against whole genome human and murine proteome libraries to generate inferred from host-pathogen protein interactions. a map of potential host-pathogen protein-protein interactions (PPIs). We detected 273 PLoS ONE 12(11): e0188071. https://doi.org/ 10.1371/journal.pone.0188071 unique interactions between 20 pathogen and 247 human proteins, and 157 between 17 pathogen and 137 murine proteins. We used orthology to combine the data and create a sin- Editor: Zhao-Qing Luo, Purdue University, UNITED STATES gle host-pathogen interaction network containing 415 unique interactions between 25 C. -
UNIVERSITY of CALIFORNIA Los Angeles Molecular and Genetic
UNIVERSITY OF CALIFORNIA Los Angeles Molecular and Genetic Study of Human Liposarcoma A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Molecular and Medical Pharmacology by Kathleen Barzan Smith 2012 ABSTRACT OF THE DISSERTATION Molecular and Genetic Study of Human Liposarcoma by Kathleen Barzan Smith Doctor of Philosophy in Molecular and Medical Pharmacology University of California, Los Angeles, 2012 Professor Frederick C. Eilber, Co-chair Professor Hong Wu, Co-chair Sarcomas are cancers of connective tissue, such as bone, nerves, and muscle. Liposarcoma, a neoplasm arising within adipose tissue, is the most common soft tissue sarcoma. Although most commonly found in the retroperitoneum or thighs, liposarcomas can arise throughout the body and are often large when found. Current treatment is limited to surgery and radiation, with chemotherapy doing little to improve prognosis in advanced cases. D ue to the large size of tumors and t heir proximity to organs and healthy tissue, complete surgical removal is difficult and recurrence rates remain high. Liposarcoma can be divided into three histological subtypes: pleomorphic, myxoid/round cell, and /well- dedifferentiated. Here we demonstrate the generation of three novel dedifferentiated liposarcoma xenograft models from freshly resected patient tissue. These xenograft models and their derived cultured cells successfully recapitulate the morphological and gene expression profiles of their patient tumors throughout serial passage in mice. Interestingly, the patients whose tumors could engraft and be serially passaged had significantly shorter survival than patients whose tumors did not engraft. These ii tumors carried gene expression signatures with more aggressive and less differentiated features. -
Research2007herschkowitzetvolume Al
Open Access Research2007HerschkowitzetVolume al. 8, Issue 5, Article R76 Identification of conserved gene expression features between comment murine mammary carcinoma models and human breast tumors Jason I Herschkowitz¤*†, Karl Simin¤‡, Victor J Weigman§, Igor Mikaelian¶, Jerry Usary*¥, Zhiyuan Hu*¥, Karen E Rasmussen*¥, Laundette P Jones#, Shahin Assefnia#, Subhashini Chandrasekharan¥, Michael G Backlund†, Yuzhi Yin#, Andrey I Khramtsov**, Roy Bastein††, John Quackenbush††, Robert I Glazer#, Powel H Brown‡‡, Jeffrey E Green§§, Levy Kopelovich, reviews Priscilla A Furth#, Juan P Palazzo, Olufunmilayo I Olopade, Philip S Bernard††, Gary A Churchill¶, Terry Van Dyke*¥ and Charles M Perou*¥ Addresses: *Lineberger Comprehensive Cancer Center. †Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. ‡Department of Cancer Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA. reports §Department of Biology and Program in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. ¶The Jackson Laboratory, Bar Harbor, ME 04609, USA. ¥Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. #Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, USA. **Department of Pathology, University of Chicago, Chicago, IL 60637, USA. ††Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA. ‡‡Baylor College of Medicine, Houston, TX 77030, USA. §§Transgenic Oncogenesis Group, Laboratory of Cancer Biology and Genetics. Chemoprevention Agent Development Research Group, National Cancer Institute, Bethesda, MD 20892, USA. Department of Pathology, Thomas Jefferson University, Philadelphia, PA 19107, USA. Section of Hematology/Oncology, Department of Medicine, Committees on Genetics and Cancer Biology, University of Chicago, Chicago, IL 60637, USA. -
Supplementary Table 1. Mutated Genes That Contain Protein Domains Identified Through Mutation Enrichment Analysis
Supplementary Table 1. Mutated genes that contain protein domains identified through mutation enrichment analysis A. Breast cancers InterPro ID Mutated genes (number of mutations) IPR000219 ARHGEF4(2), ECT2(1), FARP1(1), FLJ20184(1), MCF2L2(1), NET1(1), OBSCN(5), RASGRF2(2), TRAD(1), VAV3(1) IPR000225 APC2(2), JUP(1), KPNA5(2), SPAG6(1) IPR000357 ARFGEF2(2), CMYA4(1), DRIM(2), JUP(1), KPNA5(2), PIK3R4(1), SPAG6(1) IPR000533 AKAP9(2), C10orf39(1), C20orf23(1), CUTL1(1), HOOK1(1), HOOK3(1), KTN1(2), LRRFIP1(3), MYH1(3), MYH9(2), NEF3(1), NF2(1), RSN(1), TAX1BP1(1), TPM4(1) IPR000694 ADAM12(3), ADAMTS19(1), APC2(2), APXL(1), ARID1B(1), BAT2(2), BAT3(1), BCAR1(1), BCL11A(2), BCORL1(1), C14orf155(3), C1orf2(1), C1QB(1), C6orf31(1), C7orf11(1), CD2(1), CENTD3(3), CHD5(3), CIC(3), CMYA1(2), COL11A1(3), COL19A1(2), COL7A1(3), DAZAP1(1), DBN1(3), DVL3(1), EIF5(1), FAM44A(1), FAM47B(1), FHOD1(1), FLJ20584(1), G3BP2(2), GAB1(2), GGA3(1), GLI1(3), GPNMB(2), GRIN2D(3), HCN3(1), HOXA3(2), HOXA4(1), IRS4(1), KCNA5(1), KCNC2(1), LIP8(1), LOC374955(1), MAGEE1(2), MICAL1(2), MICAL‐L1(1), MLLT2(1), MMP15(1), N4BP2(1), NCOA6(2), NHS(1), NUP214(3), ODZ1(3), PER1(2), PER2(1), PHC1(1), PLXNB1(1), PPM1E(2), RAI17(2), RAPH1(2), RBAF600(2), SCARF2(1), SEMA4G(1), SLC16A2(1), SORBS1(1), SPEN(2), SPG4(1), TBX1(1), TCF1(2), TCF7L1(1), TESK1(1), THG‐1(1), TP53(18), TRIF(1), ZBTB3(2), ZNF318(2) IPR000909 CENTB1(2), PLCB1(1), PLCG1(1) IPR000998 AEGP(3), EGFL6(2), PRSS7(1) IPR001140 ABCB10(2), ABCB6(1), ABCB8(2) IPR001164 ARFGAP3(1), CENTB1(2), CENTD3(3), CENTG1(2) IPR001589