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Gene Regulatory Factors in the Evolutionary History of Humans

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Gene regulatory factors in the evolutionary history of humans Von der Fakultät für Mathematik und Informatik der Universität Leipzig angenommene Dissertation zur Erlangung des akademischen Grades DOCTOR RERUM NATURALIUM (Dr. rer. nat.) im Fachgebiet Informatik vorgelegt von MSc. Alvaro Perdomo-Sabogal geboren am 08. Januar 1979 in Armenia, Quindio (Kolumbien) Die Annahme der Dissertation wurde empfohlen von: 1. Prof. Dr. Peter F. Stadler, Institut für Informatik, Leipzig 2. Prof. Dr. Andrew Torda, Zentrum für Bioinformatik, Hamburg Die Verleihung des akademischen Grades erfolgt mit Bestehen der Verteidigung am 24. August 2016 mit dem Gesamtprädikat “magna cum laude" Abstract Changes in cis‐ and trans‐regulatory elements are among the prime sources of genetic and phenotypical variation at species level. The introduction of cis‐ and trans regulatory variation, as evolutionary processes, has played important roles in driving evolution, diversity and phenotypical differentiation in humans. Therefore, exploring and identifying variation that occurs on cis‐ and trans‐ regulatory elements becomes imperative to better understanding of human evolution and its genetic diversity. In this research, around 3360 gene regulatory factors in the human genome were catalogued. This catalog includes genes that code for proteins that perform gene regulatory activities such DNA‐depending transcription, RNA polymerase II transcription cofactor and co‐repressor activity, chromatin binding, and remodeling, among other 218 gene ontology terms. Using the classification of DNA‐ binding GRFs (Wingender et al. 2015), we were able to group 1521 GRF genes (~46%) into 41 different GRF classes. This GRF catalog allowed us to initially explore and discuss how some GRF genes have evolved in humans, archaic humans (Neandertal and Denisovan) and non‐human primates species. It is also discussed which are the likely phenotypical and medical effects that evolutionary changes in GRF genes may have introduced into the human genome are; for instance, speech and language capabilities, recombination hotspots, and metabolic pathways and diseases. In addition, by exploring genome‐wide scan data for detecting selection, we built a list of GRF candidate genes that may have undergone positive selection in three human populations: Utah Residents with Northern and Western Ancestry (CEU), Han Chinese in Beijing (CHB), and Yoruba in Ibadan (YRI). We think this set gathers genes that may have contributed in shaping the phenotypical diversity currently observed in these three human populations, for example by introducing regulatory diversity at population‐specific level. Out of the 41 DNA‐binding GRF classes, six i groups evidenced enrichment for genes located on regions that may have been target of positive selection: C2H2 zinc finger, KRAB‐ZNF zinc finger, Homeo domain, Tryptophan cluster, Fork head/winged helix and, and High‐mobility HMG domain. We additionally identified three KRAB‐ZNF gene clusters, in the chromosomes one, three, and 16, of the Asian population that exhibit regions with extended haplotype homozygosity EHH (larger than 100 kb). The presence of this EHH suggests that these three regions have undergone positive selection in CHB population. Out of the 22 GRF genes located within these three KRAB‐ZNF clusters, seven C2H2‐ZNF GRF genes (ZNF695, ZNF646, ZNF668, ZNF167, ZNF35, ZNF502, and ZNF501) carry nonsynonymous SNPs that code nonsynonymous SNPs that change the amino acid sequence in their protein domains (linkers and cystine‐2 histidine‐2 amino‐acid sequence motifs). Six GRF genes located on the EHH region on the chromosome 16 of CHB have been associated with obesity (KAT8, ZNF646, ZNF668, FBXL19) and blood coagulation (STX1B and VKORC1) in humans. In addition, we also detected genetic changes at GRF sequence level that may have resulted in subtle regulatory changes in metabolic pathways associated with glucose and insulin metabolism at population‐specific level. Finally, acknowledging that a representative fraction of the phenotypic diversity we observed between humans and its closely related species are likely explained by changes in cis‐regulatory elements (CREs), putative binding sites of the transcription factor GABPa were identified and investigated. GABPa is GRF protein member of the E‐twenty six DNA‐binding proteins class. GABPs control gene expression of many genes that play key roles at cellular level, for instance, in cell migration and differentiation, cell cycle control and fate, hormonal regulation and apoptosis. Using ChIP‐Seq data generated from a human cell line (HEK293T), we found 11,619 putative GABPa CREs were found, of which 224 are putative human‐ specific. To experimentally validate the transcriptional activity of these human‐ specific GABPa CREs, reporter gene essays and knock‐down experiments were performed. Our results supported the functionality of these human‐specific GABPa CREs and suggest that at least 1,215 genes are primary targets of GABPa. Finally, further analyses of the data gathered depict scenarios that bring together transcriptional regulation by GABPa with the evolution of particular human ii speciation and traits for instance, cognitive abilities, breast morphology, and lipids and glucose metabolic pathways and the regulation of human‐specific genes. By studying genetic changes in cis‐ and trans‐ regulatory elements in humans in two different evolutionary time frames, species evolution and population genetics, we were able to show how genome regulatory innovations and genetic variation may have contributed to the evolution of human‐ and population specific traits. Here, we conclude that human‐specific changes in regulatory elements are likely introducing subtle regulatory variation in key pathways at physiological level, for instance, in glucose/insulin, lipids metabolism and cognitive abilities. Some of these changes may have resulted in adaptive responses that left signatures of positive selection at human population specific level. iii Acknowledgment I would like to thank those who significantly helped me to keep myself together, motivated and combative when the difficult times arrived. This mainly refers to my sister Ericka, family, and best friends. Special memorable thanks go to the one who already left, my dad, who before leaving put incredible effort in making of this, a feasible trip into this scientific career. I would also like to thank to Katja, for her commitment with the supervising process, for her valuable time and massive patience during the academic discussions. Many thanks to Lydia and Daniel, who apart from being devotedly committed with the Friday’s friendly catching up sessions, also had the time to provide help and feedback when the times were cloudy and the codes were messy. Many thanks to Peter for generating a space with the facilities, the people and the environment to do proper scientific research. Many thanks to Jens and Petra who were always available for sorting out logistic issues. Many thanks to the folks from the Bioinformatics institute who always provided me with a friendly and enjoyable environment. iv Contents Introduction ............................................................................................................................ 5 1.1. Emergence of modern humans .......................................................................................... 6 1.2. Evolutionary changes after human lineage split from non‐human‐primates 10 Chapter 1 ................................................................................................................................ 15 Gene Regulatory Factors, key genes in the evolutionary history of modern humans ............................................................................................................................................. 15 2.1. Introduction ............................................................................................................................ 15 2.2. Results ...................................................................................................................................... 17 2.2.1. An updated comprehensive catalog of GRFs for studying regulatory evolution in human ..................................................................................................................................................... 17 2.2.2. Evolutionary changes in GRFs after humans split from chimpanzees .................. 19 2.2.3. Evolution of GRFs in AMH population ................................................................................ 22 2.3. Discussion ................................................................................................................................ 24 2.3.1. Newly evolved GRF in humans .............................................................................................. 25 2.3.2. Human‐specific GRFs and disease........................................................................................ 25 2.3.3. A first glance of evolutionary changes in GRF within AMHs populations ........... 26 2.4. Conclusion ............................................................................................................................... 28 2.5. Materials and Methods ....................................................................................................... 28 2.5.1. Building the GRF gene catalog ............................................................................................... 28 Chapter 2 ...............................................................................................................................
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    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 ......................................................
  • Gene Expression Profiling of Peripheral Blood in Patients With

    Gene Expression Profiling of Peripheral Blood in Patients With

    FLORE Repository istituzionale dell'Università degli Studi di Firenze Gene expression profiling of peripheral blood in patients with abdominal aortic aneurysm Questa è la Versione finale referata (Post print/Accepted manuscript) della seguente pubblicazione: Original Citation: Gene expression profiling of peripheral blood in patients with abdominal aortic aneurysm / Giusti B; Rossi L; Lapini I; Magi A; Pratesi G; Lavitrano M; Blasi GM; Pulli R; Pratesi C; Abbate R. - In: EUROPEAN JOURNAL OF VASCULAR AND ENDOVASCULAR SURGERY. - ISSN 1078-5884. - STAMPA. - 38(2009), pp. 104-112. [10.1016/j.ejvs.2009.01.020] Availability: This version is available at: 2158/369023 since: 2018-03-01T22:38:47Z Published version: DOI: 10.1016/j.ejvs.2009.01.020 Terms of use: Open Access La pubblicazione è resa disponibile sotto le norme e i termini della licenza di deposito, secondo quanto stabilito dalla Policy per l'accesso aperto dell'Università degli Studi di Firenze (https://www.sba.unifi.it/upload/policy-oa-2016-1.pdf) Publisher copyright claim: (Article begins on next page) 24 September 2021 Eur J Vasc Endovasc Surg (2009) 38, 104e112 Gene Expression Profiling of Peripheral Blood in Patients with Abdominal Aortic Aneurysm B. Giusti a,*, L. Rossi a, I. Lapini a, A. Magi a, G. Pratesi b, M. Lavitrano c, G.M. Biasi c, R. Pulli d, C. Pratesi d, R. Abbate a a Department of Medical and Surgical Critical Care and DENOTHE Center, University of Florence, Viale Morgagni 85, 50134 Florence, Italy b Vascular Surgery Unit, Department of Surgery, University of Rome ‘‘Tor Vergata’’, Rome, Italy c Department of Surgical Sciences, University of Milano-Bicocca, Italy d Department of Vascular Surgery, University of Florence, Italy Submitted 17 September 2008; accepted 15 January 2009 Available online 23 February 2009 KEYWORDS Abstract Object: Abdominal aortic aneurysm (AAA) pathogenesis remains poorly understood.