DOCSLIB.ORG

Nerodia Fasciata/Clarkii</Em>

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Nerodia Fasciata/Clarkii</Em> Clemson University TigerPrints All Theses Theses December 2019 Testing the Waters: Diversification and Selection in the Nerodia fasciata/clarkii Species Complex Mark Alexander DiMeo Clemson University, [email protected] Follow this and additional works at: https://tigerprints.clemson.edu/all_theses Recommended Citation DiMeo, Mark Alexander, "Testing the Waters: Diversification and Selection in the Nerodia fasciata/clarkii Species Complex" (2019). All Theses. 3202. https://tigerprints.clemson.edu/all_theses/3202 This Thesis is brought to you for free and open access by the Theses at TigerPrints. It has been accepted for inclusion in All Theses by an authorized administrator of TigerPrints. For more information, please contact [email protected]. TESTING THE WATERS: DIVERSIFICATION AND SELECTION IN THE NERODIA FASCIATA/CLARKII SPECIES COMPLEX A Thesis Presented to the Graduate School of Clemson University In Partial Fulfillment of the Requirements for the Degree Master of Science Biological Sciences by Mark Alexander DiMeo December 2019 Accepted by: Dr. Christopher Parkinson, Committee Chair Dr. J. Antonio Baeza Dr. Vincent Richards ABSTRACT Understanding evolution is a key component in trying to decipher the processes generating global species diversity. The strength, direction, and interaction of gene flow and selection often determine diversification patterns and the process of speciation. The Nerodia fasciata/clarkii species complex, a lineage of water snakes, is thought to have high levels of both gene flow and selective pressures due to ecological constraint. Nerodia clarkii resides in salt marsh and estuarine habitats while Nerodia fasciata is typically found in fresh water. Salinity is a strong selective pressure and is thought to play a role in the diversification process. Currently, there are five described subspecies within the complex but their validity is in question, causing concerns about the conservation status of the federally threatened Atlantic Salt Marsh Snake (N. c. taeniata). To understand the diversification of the Nerodia fasciata/clarkii complex and to resolve the noted taxonomic issues, I generated the first population genomic dataset for this group using double digest restriction site-associated DNA sequencing (ddRADseq). I first used a Discriminate Analysis of Principal Components (DAPC) to identify population structure and SVDQuartets to generate a coalescent based phylogeny. With these data, I identified 4-6 populations that approximate subspecies designations although only one assigned subspecies, N. c. clarkii, was monophyletic. Second, I estimated migration among the best supported population clustering (k=5) using Estimated Effective Migration Surfaces (EEMS). EEMS revealed a migration corridor between the mostly N. fasciata populations and a reduction in gene flow at the coasts. Third, I used two selection scan analyses and one environmental association analysis to identify genes that ii are putatively under selection with an emphasis on local adaptation to saline water. I found 10 candidate genes that may be involved in osmoregulation and multiple correlations to temperature and precipitation. My results indicate that the two species are valid, and that four subspecies are also evolutionary lineages. Although gene flow and population assignment tests provided evidence that N. c. taeniata was isolated from other populations I could not unambiguously determine its validity. Both the candidate gene frequencies and EEMS indicate that majority N. fasciata populations mostly share a selection regime and gene flow patterns separate them from N. clarkii. This may demonstrate how a reduction in gene flow and a change in selection pressures can generate species diversity. iii To my family, Even if I’m in Japan I know you’re with me iv ACKNOWLEDGEMENTS Finishing this thesis was a longer and harder process than I ever expected and I could never have done it without help. First, I want to thank my advisor and committee members. Dr. Parkinson, thank you for taking a chance on me when I had next to no research experience and sticking with me as I struggled to become a scientist. I’m sure it wasn’t easy to do so. Additionally, without your grant from USFW I’m not sure I could have funded all the work. I want to thank my committee members Dr. Baeza and Dr. Richards for their patience with me for all the delays to my thesis. I hope I was able to live up to all your expectations. Second, I want to thank all the members of the Parkinson Lab, past and present, who have provided support to me, without which I could never have finished. In the three years I was a part of the lab I have seen multiple lab mates come and go and all of them have played a part in my growth as a scientist and person. Notably Jason Strickland, Andrew Mason, and Rhett Rautsaw have been with me since I joined and without their guidance this wouldn’t be possible. In particular I want to thank Mark Margres who really took me under his wing in the last year and Rooksana Noorai who was always there to listen to me despite the fact that she is not an official member of the lab and was not obligated to do so. Then I have to thank the past Master’s students, Greg Territo and Jason Hickson, and the undergrads who laid out the foundation for this project through sample collection and data generation. I cannot forget all the contributions to the research and editing of this project that the Parkinson Lab gave me. v Third, during the course of my research I worked at both the University of Central Florida and Clemson University so I want to thank all the friends I made at both institutions. You may not have directly contributed to my thesis but you helped to keep me sane through the hard times with your friendship. Finally, I want to thank my family. I don’t know why but despite all my setbacks and delays your confidence in me never seemed to waver. This emotional support was worth so much to me, even more than the financial support! Despite the fact that I’m not near you now I know I’ll always have your support. vi TABLE OF CONTENTS Page TITLE PAGE .................................................................................................................... i ABSTRACT ..................................................................................................................... ii ACKNOWLEDGEMENTS ............................................................................................ iv LIST OF TABLES ......................................................................................................... vii LIST OF FIGURES ...................................................................................................... viii CHAPTER I. INTRODUCTION ......................................................................................... 1 Diversification, Gene Flow, and Selection .............................................. 1 Population Genomics ............................................................................... 2 Study Species ........................................................................................... 3 Objectives ................................................................................................ 5 Questions and Predictions ........................................................................ 6 II. EVOLUTIONARY HISTORY AND POPULATION GENETICS OF THE NERODIA FASCIATA/CLARKII SPECIES COMPLEX ........................................... 7 Introduction .............................................................................................. 7 Materials and Methods ............................................................................. 9 Results .................................................................................................... 17 Discussion .............................................................................................. 29 III. EVIDENCE OF SELECTION IN THE NERODIA FASCIATA/CLARKII SPECIES COMPLEX ......................................... 32 Introduction ............................................................................................ 32 Materials and Methods ........................................................................... 34 Results .................................................................................................... 38 Discussion .............................................................................................. 45 IV. DISCUSSION .............................................................................................. 48 vii Table of Contents (Continued) Page Taxonomy and Conservation ................................................................. 49 Future Directions ................................................................................... 50 APPENDICES: Supplementary Tables and Figures...................................................... 52 REFERENCES .............................................................................................................. 73 viii LIST OF TABLES Table Page 2.1 Locus name, annealing temperature (ᵒC) and alignment length used for Bayesian phylogenetic inference of the Nerodia fasciata/clarkii species complex ................................................................ 10 2.2 List of mitochondrial and nuclear genes with the model for each coding position. TATA, M, and E are introns and were not split by codon thus they only have one position……………………………………………………… 15 2.3 Fst, Gst, and Jost’s D pairwise measures of differentiation among
Load more

Recommended publications
  • Doctoral Thesis Genetics of Male Infertility
    DOCTORAL THESIS GENETICS OF MALE INFERTILITY: MOLECULAR STUDY OF NON-SYNDROMIC CRYPTORCHIDISM AND SPERMATOGENIC IMPAIRMENT Deborah Grazia Lo Giacco November 2013 Genetics of male infertility: molecular study of non-syndromic cryptorchidism and spermatogenic impairment Thesis presented by Deborah Grazia Lo Giacco To fulfil the PhD degree at Universitat Autònoma de Barcelona Thesis realized under the direction of Dr. Elisabet Ars Criach and Prof. Csilla Krausz at the laboratory of Molecular Biology of Fundació Puigvert, Barcelona Thesis ascribed to the Department of Cellular Biology, Physiology and Immunology, Medicine School of Universitat Autònoma de Barcelona PhD in Cellular Biology Dr. Elisabet Ars Criach Prof. Csilla Krausz Dr. Carme Nogués Sanmiquel Director of the thesis Director of the thesis Tutor of the thesis Deborah Grazia Lo Giacco Ph.D Candidate A mis padres Agradecimientos Esta tesis es un esfuerzo en el cual, directa o indirectamente, han participado varias personas, leyendo, opinando, corrigiendo, teniéndo paciencia, dando ánimo, acompañando en los momentos de crisis y en los momentos de felicidad. Antes de todo quisiera agradecer a mis directoras de tesis, la Dra Csilla Krausz y la Dra Elisabet Ars, por su dedicación costante y continua a este trabajo de investigación y por sus observaciones y siempre acertados consejos. Gracias por haber sido mentores y amigas, gracias por transmitirme vuestro entusiasmo y por todo lo que he aprendido de vosotras. Mi más profundo agradecimiento a la Sra Esperança Marti por haber creído en el valor de nuestro trabajo y haber hecho que fuera posible. Quisiera agradecer al Dr. Eduard Ruiz-Castañé por su apoyo y ayuda constante, y a todos los médicos del Servicio de Andrología: Dr.
    [Show full text]
  • A Comparative Analysis of Transcribed Genes in the Mouse Hypothalamus and Neocortex Reveals Chromosomal Clustering
    A comparative analysis of transcribed genes in the mouse hypothalamus and neocortex reveals chromosomal clustering Wee-Ming Boon*, Tim Beissbarth†, Lavinia Hyde†, Gordon Smyth†, Jenny Gunnersen*, Derek A. Denton*‡, Hamish Scott†, and Seong-Seng Tan* *Howard Florey Institute, University of Melbourne, Parkville 3052, Australia; and †Genetics and Bioinfomatics Division, Walter and Eliza Hall Institute of Medical Research, Royal Parade, Parkville 3050, Australia Contributed by Derek A. Denton, August 26, 2004 The hypothalamus and neocortex are subdivisions of the mamma- representing all of the genes that are expressed (qualitative and lian forebrain, and yet, they have vastly different evolutionary quantitative) in the hypothalamus and neocortex under standard histories, cytoarchitecture, and biological functions. In an attempt conditions. to define these attributes in terms of their genetic activity, we have In the current study, we describe the use of the Serial Analysis compared their genetic repertoires by using the Serial Analysis of of Gene Expression (SAGE) database, which allows simulta- Gene Expression database. From a comparison of 78,784 hypothal- neous detection of the expression levels of the entire genome amus tags with 125,296 neocortical tags, we demonstrate that each without a priori knowledge of gene sequences (13). SAGE takes structure possesses a different transcriptional profile in terms of advantage of the fact that a small sequence tag taken from a gene ontological characteristics and expression levels. Despite its defined position within the transcript is sufficient to identify the more recent evolutionary history, the neocortex has a more com- gene (from known cDNA or EST sequences), and up to 40 tags plex pattern of gene activity.
    [Show full text]
  • Ovarian Gene Expression in the Absence of FIGLA, an Oocyte
    BMC Developmental Biology BioMed Central Research article Open Access Ovarian gene expression in the absence of FIGLA, an oocyte-specific transcription factor Saurabh Joshi*1, Holly Davies1, Lauren Porter Sims2, Shawn E Levy2 and Jurrien Dean1 Address: 1Laboratory of Cellular and Developmental Biology, NIDDK, National Institutes of Health, Bethesda, MD 20892, USA and 2Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA Email: Saurabh Joshi* - [email protected]; Holly Davies - [email protected]; Lauren Porter Sims - [email protected]; Shawn E Levy - [email protected]; Jurrien Dean - [email protected] * Corresponding author Published: 13 June 2007 Received: 11 December 2006 Accepted: 13 June 2007 BMC Developmental Biology 2007, 7:67 doi:10.1186/1471-213X-7-67 This article is available from: http://www.biomedcentral.com/1471-213X/7/67 © 2007 Joshi 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. Abstract Background: Ovarian folliculogenesis in mammals is a complex process involving interactions between germ and somatic cells. Carefully orchestrated expression of transcription factors, cell adhesion molecules and growth factors are required for success. We have identified a germ-cell specific, basic helix-loop-helix transcription factor, FIGLA (Factor In the GermLine, Alpha) and demonstrated its involvement in two independent developmental processes: formation of the primordial follicle and coordinate expression of zona pellucida genes. Results: Taking advantage of Figla null mouse lines, we have used a combined approach of microarray and Serial Analysis of Gene Expression (SAGE) to identify potential downstream target genes.
    [Show full text]
  • Replace This with the Actual Title Using All Caps
    UNDERSTANDING THE GENETICS UNDERLYING MASTITIS USING A MULTI-PRONGED APPROACH A Dissertation Presented to the Faculty of the Graduate School of Cornell University In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy by Asha Marie Miles December 2019 © 2019 Asha Marie Miles UNDERSTANDING THE GENETICS UNDERLYING MASTITIS USING A MULTI-PRONGED APPROACH Asha Marie Miles, Ph. D. Cornell University 2019 This dissertation addresses deficiencies in the existing genetic characterization of mastitis due to granddaughter study designs and selection strategies based primarily on lactation average somatic cell score (SCS). Composite milk samples were collected across 6 sampling periods representing key lactation stages: 0-1 day in milk (DIM), 3- 5 DIM, 10-14 DIM, 50-60 DIM, 90-110 DIM, and 210-230 DIM. Cows were scored for front and rear teat length, width, end shape, and placement, fore udder attachment, udder cleft, udder depth, rear udder height, and rear udder width. Independent multivariable logistic regression models were used to generate odds ratios for elevated SCC (≥ 200,000 cells/ml) and farm-diagnosed clinical mastitis. Within our study cohort, loose fore udder attachment, flat teat ends, low rear udder height, and wide rear teats were associated with increased odds of mastitis. Principal component analysis was performed on these traits to create a single new phenotype describing mastitis susceptibility based on these high-risk phenotypes. Cows (N = 471) were genotyped on the Illumina BovineHD 777K SNP chip and considering all 14 traits of interest, a total of 56 genome-wide associations (GWA) were performed and 28 significantly associated quantitative trait loci (QTL) were identified.
    [Show full text]
  • 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.
    [Show full text]
  • Supplemental Table 1. Complete Gene Lists and GO Terms from Figure 3C
    Supplemental Table 1. Complete gene lists and GO terms from Figure 3C. Path 1 Genes: RP11-34P13.15, RP4-758J18.10, VWA1, CHD5, AZIN2, FOXO6, RP11-403I13.8, ARHGAP30, RGS4, LRRN2, RASSF5, SERTAD4, GJC2, RHOU, REEP1, FOXI3, SH3RF3, COL4A4, ZDHHC23, FGFR3, PPP2R2C, CTD-2031P19.4, RNF182, GRM4, PRR15, DGKI, CHMP4C, CALB1, SPAG1, KLF4, ENG, RET, GDF10, ADAMTS14, SPOCK2, MBL1P, ADAM8, LRP4-AS1, CARNS1, DGAT2, CRYAB, AP000783.1, OPCML, PLEKHG6, GDF3, EMP1, RASSF9, FAM101A, STON2, GREM1, ACTC1, CORO2B, FURIN, WFIKKN1, BAIAP3, TMC5, HS3ST4, ZFHX3, NLRP1, RASD1, CACNG4, EMILIN2, L3MBTL4, KLHL14, HMSD, RP11-849I19.1, SALL3, GADD45B, KANK3, CTC- 526N19.1, ZNF888, MMP9, BMP7, PIK3IP1, MCHR1, SYTL5, CAMK2N1, PINK1, ID3, PTPRU, MANEAL, MCOLN3, LRRC8C, NTNG1, KCNC4, RP11, 430C7.5, C1orf95, ID2-AS1, ID2, GDF7, KCNG3, RGPD8, PSD4, CCDC74B, BMPR2, KAT2B, LINC00693, ZNF654, FILIP1L, SH3TC1, CPEB2, NPFFR2, TRPC3, RP11-752L20.3, FAM198B, TLL1, CDH9, PDZD2, CHSY3, GALNT10, FOXQ1, ATXN1, ID4, COL11A2, CNR1, GTF2IP4, FZD1, PAX5, RP11-35N6.1, UNC5B, NKX1-2, FAM196A, EBF3, PRRG4, LRP4, SYT7, PLBD1, GRASP, ALX1, HIP1R, LPAR6, SLITRK6, C16orf89, RP11-491F9.1, MMP2, B3GNT9, NXPH3, TNRC6C-AS1, LDLRAD4, NOL4, SMAD7, HCN2, PDE4A, KANK2, SAMD1, EXOC3L2, IL11, EMILIN3, KCNB1, DOK5, EEF1A2, A4GALT, ADGRG2, ELF4, ABCD1 Term Count % PValue Genes regulation of pathway-restricted GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, SMAD protein phosphorylation 9 6.34 1.31E-08 ENG pathway-restricted SMAD protein GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, phosphorylation
    [Show full text]
  • Supplementary Table 1: Adhesion Genes Data Set
    Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like,
    [Show full text]
  • Tissue-Specific Pathways and Networks Underlying Sexual
    Kurt et al. Biology of Sex Differences (2018) 9:46 https://doi.org/10.1186/s13293-018-0205-7 RESEARCH Open Access Tissue-specific pathways and networks underlying sexual dimorphism in non- alcoholic fatty liver disease Zeyneb Kurt1, Rio Barrere-Cain1, Jonnby LaGuardia1, Margarete Mehrabian2, Calvin Pan2, Simon T Hui2, Frode Norheim2, Zhiqiang Zhou2, Yehudit Hasin2, Aldons J Lusis2* and Xia Yang1* Abstract Background: Non-alcoholic fatty liver disease (NAFLD) encompasses benign steatosis and more severe conditions such as non-alcoholic steatohepatitis (NASH), cirrhosis, and liver cancer. This chronic liver disease has a poorly understood etiology and demonstrates sexual dimorphisms. We aim to examine the molecular mechanisms underlying sexual dimorphisms in NAFLD pathogenesis through a comprehensive multi-omics study. We integrated genomics (DNA variations), transcriptomics of liver and adipose tissue, and phenotypic data of NAFLD derived from female mice of ~ 100 strains included in the hybrid mouse diversity panel (HMDP) and compared the NAFLD molecular pathways and gene networks between sexes. Results: We identified both shared and sex-specific biological processes for NAFLD. Adaptive immunity, branched chain amino acid metabolism, oxidative phosphorylation, and cell cycle/apoptosis were shared between sexes. Among the sex-specific pathways were vitamins and cofactors metabolism and ion channel transport for females, and phospholipid, lysophospholipid, and phosphatidylinositol metabolism and insulin signaling for males. Additionally, numerous lipid and insulin-related pathways and inflammatory processes in the adipose and liver tissue appeared to show more prominent association with NAFLD in male HMDP. Using data-driven network modeling, we identified plausible sex-specific and tissue-specific regulatory genes as well as those that are shared between sexes.
    [Show full text]
  • Supplementary Data
    SUPPLEMENTARY DATA A cyclin D1-dependent transcriptional program predicts clinical outcome in mantle cell lymphoma Santiago Demajo et al. 1 SUPPLEMENTARY DATA INDEX Supplementary Methods p. 3 Supplementary References p. 8 Supplementary Tables (S1 to S5) p. 9 Supplementary Figures (S1 to S15) p. 17 2 SUPPLEMENTARY METHODS Western blot, immunoprecipitation, and qRT-PCR Western blot (WB) analysis was performed as previously described (1), using cyclin D1 (Santa Cruz Biotechnology, sc-753, RRID:AB_2070433) and tubulin (Sigma-Aldrich, T5168, RRID:AB_477579) antibodies. Co-immunoprecipitation assays were performed as described before (2), using cyclin D1 antibody (Santa Cruz Biotechnology, sc-8396, RRID:AB_627344) or control IgG (Santa Cruz Biotechnology, sc-2025, RRID:AB_737182) followed by protein G- magnetic beads (Invitrogen) incubation and elution with Glycine 100mM pH=2.5. Co-IP experiments were performed within five weeks after cell thawing. Cyclin D1 (Santa Cruz Biotechnology, sc-753), E2F4 (Bethyl, A302-134A, RRID:AB_1720353), FOXM1 (Santa Cruz Biotechnology, sc-502, RRID:AB_631523), and CBP (Santa Cruz Biotechnology, sc-7300, RRID:AB_626817) antibodies were used for WB detection. In figure 1A and supplementary figure S2A, the same blot was probed with cyclin D1 and tubulin antibodies by cutting the membrane. In figure 2H, cyclin D1 and CBP blots correspond to the same membrane while E2F4 and FOXM1 blots correspond to an independent membrane. Image acquisition was performed with ImageQuant LAS 4000 mini (GE Healthcare). Image processing and quantification were performed with Multi Gauge software (Fujifilm). For qRT-PCR analysis, cDNA was generated from 1 µg RNA with qScript cDNA Synthesis kit (Quantabio). qRT–PCR reaction was performed using SYBR green (Roche).
    [Show full text]
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
    [Show full text]
  • Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?
    Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement.
    [Show full text]
  • Single-Cell RNA-Seq of Dopaminergic Neurons Informs Candidate Gene Selection for Sporadic
    bioRxiv preprint doi: https://doi.org/10.1101/148049; this version posted August 31, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Single-cell RNA-seq of dopaminergic neurons informs candidate gene selection for sporadic 2 Parkinson's disease 3 4 Paul W. Hook1, Sarah A. McClymont1, Gabrielle H. Cannon1, William D. Law1, A. Jennifer 5 Morton2, Loyal A. Goff1,3*, Andrew S. McCallion1,4,5* 6 7 1McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of 8 Medicine, Baltimore, Maryland, United States of America 9 2Department of Physiology Development and Neuroscience, University of Cambridge, 10 Cambridge, United Kingdom 11 3Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, 12 Maryland, United States of America 13 4Department of Comparative and Molecular Pathobiology, Johns Hopkins University School of 14 Medicine, Baltimore, Maryland, United States of America 15 5Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, 16 United States of America 17 *, To whom correspondence should be addressed: [email protected] and [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/148049; this version posted August 31, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
    [Show full text]