Relevant bibliographies by topics / Eukaryotic gene

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Eukaryotic gene'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Eukaryotic gene"

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Hofstatter, Paulo G., Alexander K. Tice, Seungho Kang, Matthew W. Brown, and Daniel J. G. Lahr. "Evolution of bacterial recombinase A ( recA ) in eukaryotes explained by addition of genomic data of key microbial lineages." Proceedings of the Royal Society B: Biological Sciences 283, no. 1840 (October 12, 2016): 20161453. http://dx.doi.org/10.1098/rspb.2016.1453.

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Recombinase enzymes promote DNA repair by homologous recombination. The genes that encode them are ancestral to life, occurring in all known dominions: viruses, Eubacteria, Archaea and Eukaryota. Bacterial recombinases are also present in viruses and eukaryotic groups (supergroups), presumably via ancestral events of lateral gene transfer. The eukaryotic recA genes have two distinct origins (mitochondrial and plastidial), whose acquisition by eukaryotes was possible via primary (bacteria–eukaryote) and/or secondary (eukaryote–eukaryote) endosymbiotic gene transfers (EGTs). Here we present a comprehensive phylogenetic analysis of the recA genealogy, with substantially increased taxonomic sampling in the bacteria, viruses, eukaryotes and a special focus on the key eukaryotic supergroup Amoebozoa, earlier represented only by Dictyostelium . We demonstrate that several major eukaryotic lineages have lost the bacterial recombinases (including Opisthokonta and Excavata), whereas others have retained them (Amoebozoa, Archaeplastida and the SAR-supergroups). When absent, the bacterial recA homologues may have been lost entirely (secondary loss of canonical mitochondria) or replaced by other eukaryotic recombinases. RecA proteins have a transit peptide for organellar import, where they act. The reconstruction of the RecA phylogeny with its EGT events presented here retells the intertwined evolutionary history of eukaryotes and bacteria, while further illuminating the events of endosymbiosis in eukaryotes by expanding the collection of widespread genes that provide insight to this deep history.
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Ku, Chuan, Shijulal Nelson-Sathi, Mayo Roettger, Sriram Garg, Einat Hazkani-Covo, and William F. Martin. "Endosymbiotic gene transfer from prokaryotic pangenomes: Inherited chimerism in eukaryotes." Proceedings of the National Academy of Sciences 112, no. 33 (March 2, 2015): 10139–46. http://dx.doi.org/10.1073/pnas.1421385112.

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Endosymbiotic theory in eukaryotic-cell evolution rests upon a foundation of three cornerstone partners—the plastid (a cyanobacterium), the mitochondrion (a proteobacterium), and its host (an archaeon)—and carries a corollary that, over time, the majority of genes once present in the organelle genomes were relinquished to the chromosomes of the host (endosymbiotic gene transfer). However, notwithstanding eukaryote-specific gene inventions, single-gene phylogenies have never traced eukaryotic genes to three single prokaryotic sources, an issue that hinges crucially upon factors influencing phylogenetic inference. In the age of genomes, single-gene trees, once used to test the predictions of endosymbiotic theory, now spawn new theories that stand to eventually replace endosymbiotic theory with descriptive, gene tree-based variants featuring supernumerary symbionts: prokaryotic partners distinct from the cornerstone trio and whose existence is inferred solely from single-gene trees. We reason that the endosymbiotic ancestors of mitochondria and chloroplasts brought into the eukaryotic—and plant and algal—lineage a genome-sized sample of genes from the proteobacterial and cyanobacterial pangenomes of their respective day and that, even if molecular phylogeny were artifact-free, sampling prokaryotic pangenomes through endosymbiotic gene transfer would lead to inherited chimerism. Recombination in prokaryotes (transduction, conjugation, transformation) differs from recombination in eukaryotes (sex). Prokaryotic recombination leads to pangenomes, and eukaryotic recombination leads to vertical inheritance. Viewed from the perspective of endosymbiotic theory, the critical transition at the eukaryote origin that allowed escape from Muller’s ratchet—the origin of eukaryotic recombination, or sex—might have required surprisingly little evolutionary innovation.
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Hunter, Gary J. "Eukaryotic gene transcription." Biochemical Education 25, no. 3 (July 1997): 182. http://dx.doi.org/10.1016/s0307-4412(97)84456-1.

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Chin, Jason W. "Eukaryotic gene regulation." Chemistry & Biology 7, no. 1 (January 2000): R26. http://dx.doi.org/10.1016/s1074-5521(00)00071-5.

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Garrard, William T. "Eukaryotic gene expression." Trends in Biochemical Sciences 10, no. 2 (February 1985): 86–87. http://dx.doi.org/10.1016/0968-0004(85)90247-6.

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Ku, Chuan, and Arnau Sebé-Pedrós. "Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1786 (October 7, 2019): 20190098. http://dx.doi.org/10.1098/rstb.2019.0098.

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Understanding the diversity and evolution of eukaryotic microorganisms remains one of the major challenges of modern biology. In recent years, we have advanced in the discovery and phylogenetic placement of new eukaryotic species and lineages, which in turn completely transformed our view on the eukaryotic tree of life. But we remain ignorant of the life cycles, physiology and cellular states of most of these microbial eukaryotes, as well as of their interactions with other organisms. Here, we discuss how high-throughput genome-wide gene expression analysis of eukaryotic single cells can shed light on protist biology. First, we review different single-cell transcriptomics methodologies with particular focus on microbial eukaryote applications. Then, we discuss single-cell gene expression analysis of protists in culture and what can be learnt from these approaches. Finally, we envision the application of single-cell transcriptomics to protist communities to interrogate not only community components, but also the gene expression signatures of distinct cellular and physiological states, as well as the transcriptional dynamics of interspecific interactions. Overall, we argue that single-cell transcriptomics can significantly contribute to our understanding of the biology of microbial eukaryotes. This article is part of a discussion meeting issue ‘Single cell ecology’.
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Brueckner, Julia, and William F. Martin. "Bacterial Genes Outnumber Archaeal Genes in Eukaryotic Genomes." Genome Biology and Evolution 12, no. 4 (March 6, 2020): 282–92. http://dx.doi.org/10.1093/gbe/evaa047.

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Abstract Eukaryotes are typically depicted as descendants of archaea, but their genomes are evolutionary chimeras with genes stemming from archaea and bacteria. Which prokaryotic heritage predominates? Here, we have clustered 19,050,992 protein sequences from 5,443 bacteria and 212 archaea with 3,420,731 protein sequences from 150 eukaryotes spanning six eukaryotic supergroups. By downsampling, we obtain estimates for the bacterial and archaeal proportions. Eukaryotic genomes possess a bacterial majority of genes. On average, the majority of bacterial genes is 56% overall, 53% in eukaryotes that never possessed plastids, and 61% in photosynthetic eukaryotic lineages, where the cyanobacterial ancestor of plastids contributed additional genes to the eukaryotic lineage. Intracellular parasites, which undergo reductive evolution in adaptation to the nutrient rich environment of the cells that they infect, relinquish bacterial genes for metabolic processes. Such adaptive gene loss is most pronounced in the human parasite Encephalitozoon intestinalis with 86% archaeal and 14% bacterial derived genes. The most bacterial eukaryote genome sampled is rice, with 67% bacterial and 33% archaeal genes. The functional dichotomy, initially described for yeast, of archaeal genes being involved in genetic information processing and bacterial genes being involved in metabolic processes is conserved across all eukaryotic supergroups.
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Liapounova, Natalia A., Vladimir Hampl, Paul M. K. Gordon, Christoph W. Sensen, Lashitew Gedamu, and Joel B. Dacks. "Reconstructing the Mosaic Glycolytic Pathway of the Anaerobic Eukaryote Monocercomonoides." Eukaryotic Cell 5, no. 12 (October 27, 2006): 2138–46. http://dx.doi.org/10.1128/ec.00258-06.

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ABSTRACT All eukaryotes carry out glycolysis, interestingly, not all using the same enzymes. Anaerobic eukaryotes face the challenge of fewer molecules of ATP extracted per molecule of glucose due to their lack of a complete tricarboxylic acid cycle. This may have pressured anaerobic eukaryotes to acquire the more ATP-efficient alternative glycolytic enzymes, such as pyrophosphate-fructose 6-phosphate phosphotransferase and pyruvate orthophosphate dikinase, through lateral gene transfers from bacteria and other eukaryotes. Most studies of these enzymes in eukaryotes involve pathogenic anaerobes; Monocercomonoides, an oxymonad belonging to the eukaryotic supergroup Excavata, is a nonpathogenic anaerobe representing an evolutionarily and ecologically distinct sampling of an anaerobic glycolytic pathway. We sequenced cDNA encoding glycolytic enzymes from a previously established cDNA library of Monocercomonoides and analyzed the relationships of these enzymes to those from other organisms spanning the major groups of Eukaryota, Bacteria, and Archaea. We established that, firstly, Monocercomonoides possesses alternative versions of glycolytic enzymes: fructose-6-phosphate phosphotransferase, both pyruvate kinase and pyruvate orthophosphate dikinase, cofactor-independent phosphoglycerate mutase, and fructose-bisphosphate aldolase (class II, type B). Secondly, we found evidence for the monophyly of oxymonads, kinetoplastids, diplomonads, and parabasalids, the major representatives of the Excavata. We also found several prokaryote-to-eukaryote as well as eukaryote-to-eukaryote lateral gene transfers involving glycolytic enzymes from anaerobic eukaryotes, further suggesting that lateral gene transfer was an important factor in the evolution of this pathway for denizens of this environment.
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Whitaker, John W., Glenn A. McConkey, and David R. Westhead. "Prediction of horizontal gene transfers in eukaryotes: approaches and challenges." Biochemical Society Transactions 37, no. 4 (July 22, 2009): 792–95. http://dx.doi.org/10.1042/bst0370792.

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HGT (horizontal gene transfer) is recognized as an important force in bacterial evolution. Now that many eukaryotic genomes have been sequenced, it has become possible to carry out studies of HGT in eukaryotes. The present review compares the different approaches that exist for identifying HGT genes and assess them in the context of studying eukaryotic evolution. The metabolic evolution resource metaTIGER is then described, with discussion of its application in identification of HGT in eukaryotes.
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Johnson, Kristina M., Katherine Mitsouras, and Michael Carey. "Eukaryotic transcription: The core of eukaryotic gene activation." Current Biology 11, no. 13 (July 2001): R510—R513. http://dx.doi.org/10.1016/s0960-9822(01)00306-2.

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Dissertations / Theses on the topic "Eukaryotic gene"

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Kielbasa, Szymon M. "Bioinformatics of eukaryotic gene regulation." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=982693192.

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Marciniak, Jennifer Yuko. "Variability in eukaryotic gene expression /." Diss., Connect to a 24 p. preview or request complete full text in PDF formate. Access restricted to UC campuses, 2005. http://wwwlib.umi.com/cr/ucsd/fullcit?p3208639.

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Kiełbasa, Szymon M. "Bioinformatics of eukaryotic gene regulation." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2006. http://dx.doi.org/10.18452/15562.

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Die Aufklärung der Mechanismen zur Kontrolle der Genexpression ist eines der wichtigsten Probleme der modernen Molekularbiologie. Detaillierte experimentelle Untersuchungen sind enorm aufwändig aufgrund der komplexen und kombinatorischen Wechselbeziehungen der beteiligten Moleküle. Infolgedessen sind bioinformatische Methoden unverzichtbar. Diese Dissertation stellt drei Methoden vor, die die Vorhersage der regulatorischen Elementen der Gentranskription verbessern. Der erste Ansatz findet Bindungsstellen, die von den Transkriptionsfaktoren erkannt werden. Dieser sucht statistisch überrepräsentierte kurze Motive in einer Menge von Promotersequenzen und wird erfolgreich auf das Genom der Bäckerhefe angewandt. Die Analyse der Genregulation in höheren Eukaryoten benötigt jedoch fortgeschrittenere Techniken. In verschiedenen Datenbanken liegen Hunderte von Profilen vor, die von den Transkriptionsfaktoren erkannt werden. Die Ähnlichkeit zwischen ihnen resultiert in mehrfachen Vorhersagen einer einzigen Bindestelle, was im nachhinein korrigiert werden muss. Es wird eine Methode vorgestellt, die eine Möglichkeit zur Reduktion der Anzahl von Profilen bietet, indem sie die Ähnlichkeiten zwischen ihnen identifiziert. Die komplexe Natur der Wechselbeziehung zwischen den Transkriptionsfaktoren macht jedoch die Vorhersage von Bindestellen schwierig. Auch mit einer Verringerung der zu suchenden Profile sind die Resultate der Vorhersagen noch immer stark fehlerbehafted. Die Zuhilfenahme der unabhängigen Informationsressourcen reduziert die Häufigkeit der Falschprognosen. Die dritte beschriebene Methode schlägt einen neuen Ansatz vor, die die Gen-Anotation mit der Regulierung von multiplen Transkriptionsfaktoren und den von ihnen erkannten Bindestellen assoziiert. Der Nutzen dieser Methode wird anhand von verschiedenen wohlbekannten Sätzen von Transkriptionsfaktoren demonstriert.
Understanding the mechanisms which control gene expression is one of the fundamental problems of molecular biology. Detailed experimental studies of regulation are laborious due to the complex and combinatorial nature of interactions among involved molecules. Therefore, computational techniques are used to suggest candidate mechanisms for further investigation. This thesis presents three methods improving the predictions of regulation of gene transcription. The first approach finds binding sites recognized by a transcription factor based on statistical over-representation of short motifs in a set of promoter sequences. A succesful application of this method to several gene families of yeast is shown. More advanced techniques are needed for the analysis of gene regulation in higher eukaryotes. Hundreds of profiles recognized by transcription factors are provided by libraries. Dependencies between them result in multiple predictions of the same binding sites which need later to be filtered out. The second method presented here offers a way to reduce the number of profiles by identifying similarities between them. Still, the complex nature of interaction between transcription factors makes reliable predictions of binding sites difficult. Exploiting independent sources of information reduces the false predictions rate. The third method proposes a novel approach associating gene annotations with regulation of multiple transcription factors and binding sites recognized by them. The utility of the method is demonstrated on several well-known sets of transcription factors. RNA interference provides a way of efficient down-regulation of gene expression. Difficulties in predicting efficient siRNA sequences motivated the development of a library containing siRNA sequences and related experimental details described in the literature. This library, presented in the last chapter, is publicly available at http://www.human-sirna-database.net
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Tang, Terry, and University of Lethbridge Faculty of Arts and Science. "Mathematical modeling of eukaryotic gene expression." Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Chemistry and Biochemistry, 2010, 2010. http://hdl.handle.net/10133/2567.

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Using the Gillespie algorithm, the export of the mRNA molecules from their transcription site to the nuclear pore complex is simulated. The effect of various structures in the nu- cleus on the efficiency of export is discussed. The results show that having some of the space filled by chromatin near the mRNA synthesis site shortens the transport time. Next, the complete eukaryotic gene expression including transcription, splicing, mRNA export, translation, and mRNA degradation is modeled using delay stochastic simulation. This allows for the study of stochastic effects during the process and on the protein production rate patterns. Various protein production patterns can be produced by adjusting the poly-A tail length of the mRNA and the promoter efficiency of the gene. After that, the opposing effects of the chromatin density on the seeking time of the transcription factors for the promoter and the exit time of the mRNA product are discussed.
xi, 102 leaves ; 28 cm
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Benovoy, David. "Ectopic gene conversions in eukaryotic genomes." Thesis, University of Ottawa (Canada), 2006. http://hdl.handle.net/10393/27111.

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We studied ectopic gene conversions, i.e., gene conversions between duplicated genes located at different chromosomal positions, in eukaryotic genomes. In the first part we examined the factors affecting ectopic gene conversions in the human genome and compared their characteristics to those observed in other eukaryotic and prokaryotic species. In the second part, we examined the effect that ectopic conversions have on the GC-content of the duplicated genes found in yeast and Arabidopsis genomes. Using Stanley Sawyer's method implemented in his GENCONV program, we identified and characterized the ectopic gene conversions of the human genome. The human gene families containing 3 or more members contained 483 pairs of converted genes. The average length of conversions is 371+/-752 (+/- standard deviation) nucleotides long with the smallest conversions being 10 nucleotides long and the largest 6011 nucleotides long. Larger gene conversions are found between sequences that are more similar and the frequency of intra-chromosomal gene conversion increases as the distance between genes decreases. Pairs of intra-chromosomal genes sharing the same transcriptional orientation convert more often than intra-chromosomal genes in opposite transcriptional orientation. The excess of conversions in the 3'-end suggest incomplete cDNA molecules are often involved in gene conversions with chromosomal gene copies. Allelic recombination has previously been shown to increase the GC-content of the sequences of a wide variety of eukaryotic species. Ectopic recombination between clustered tandemly repeated genes has also been shown to increase their GC-content. Here we show that gene conversions between the dispersed genes found in the duplicated regions of the yeast and Arabidopsis genomes also increases their GC-content when these genes are more than 88% similar.
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Sturm, Richard Alan. "Control mechanisms of higher eukaryotic gene transcription--divergent histone genes /." Title page, contents and abstract only, 1985. http://web4.library.adelaide.edu.au/theses/09PH/09phs936.pdf.

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Abril, Ferrando Josep Francesc. "Comparative analysis of eukaryotic gene sequence features." Doctoral thesis, Universitat Pompeu Fabra, 2005. http://hdl.handle.net/10803/7108.

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L'incessant augment del nombre de seqüències genòmiques, juntament amb
l'increment del nombre de tècniques experimentals de les que es disposa,
permetrà obtenir el catàleg complet de les funcions cel.lulars de
diferents organismes, incloent-hi la nostra espècie. Aquest catàleg
definirà els fonaments sobre els que es podrà entendre millor com els
organismes funcionen a nivell molecular. Al mateix temps es tindran més
pistes sobre els canvis que estan associats amb les malalties. Per tant,
la seqüència en brut, tal i com s'obté dels projectes de seqüenciació de
genomes, no té cap valor sense les anàlisis i la subsegüent anotació de
les característiques que defineixen aquestes funcions. Aquesta tesi
presenta la nostra contribució en tres aspectes relacionats de
l'anotació dels gens en genomes eucariotes.

Primer, la comparació a nivell de seqüència entre els genomes humà i de
ratolí es va dur a terme mitjançant un protocol semi-automàtic. El
programa de predicció de gens SGP2 es va desenvolupar a partir
d'elements d'aquest protocol. El concepte al darrera de l'SGP2 és que
les regions de similaritat obtingudes amb el programa TBLASTX, es fan
servir per augmentar la puntuació dels exons predits pel programa
geneid, amb el que s obtenen conjunts d'anotacions més acurats
d'estructures gèniques. SGP2 té una especificitat que és prou gran com
per que es puguin validar experimentalment via RT-PCR. La validació de
llocs d'splicing emprant la tècnica de la RT-PCR és un bon exemple de
com la combinació d'aproximacions computacionals i experimentals
produeix millors resultats que per separat.

S'ha dut a terme l'anàlisi descriptiva a nivell de seqüència dels llocs
d'splicing obtinguts sobre un conjunt fiable de gens ortòlegs per humà,
ratolí, rata i pollastre. S'han explorat les diferències a nivell de
nucleòtid entre llocs U2 i U12, pel conjunt d'introns ortòlegs que se'n
deriva d'aquests gens. S'ha trobat que els senyals d'splicing ortòlegs
entre humà i rossegadors, així com entre rossegadors, estan més
conservats que els llocs no relacionats. Aquesta conservació addicional
pot ser explicada però a nivell de conservació basal dels introns.
D'altra banda, s'ha detectat més conservació de l'esperada entre llocs
d'splicing ortòlegs entre mamífers i pollastre. Els resultats obtinguts
també indiquen que les classes intròniques U2 i U12 han evolucionat
independentment des de l'ancestre comú dels mamífers i les aus. Tampoc
s'ha trobat cap cas convincent d'interconversió entre aquestes dues
classes en el conjunt d'introns ortòlegs generat, ni cap cas de
substitució entre els subtipus AT-AC i GT-AG d'introns U12. Al contrari,
el pas de GT-AG a GC-AG, i viceversa, en introns U2 no sembla ser inusual.

Finalment, s'han implementat una sèrie d'eines de visualització per
integrar anotacions obtingudes pels programes de predicció de gens i per
les anàlisis comparatives sobre genomes. Una d'aquestes eines, el
gff2ps, s'ha emprat en la cartografia dels genomes humà, de la mosca del
vinagre i del mosquit de la malària, entre d'altres. El programa
gff2aplot i els filtres associats, han facilitat la tasca d'integrar
anotacions de seqüència amb els resultats d'eines per la cerca
d'homologia, com ara el BLAST. S'ha adaptat també el concepte de
pictograma a l'anàlisi comparativa de llocs d splicing ortòlegs, amb el
desenvolupament del programa compi.
El aumento incesante del número de secuencias genómicas, junto con el
incremento del número de técnicas experimentales de las que se dispone,
permitirá la obtención del catálogo completo de las funciones celulares
de los diferentes organismos, incluida nuestra especie. Este catálogo
definirá las bases sobre las que se pueda entender mejor el
funcionamiento de los organismos a nivel molecular. Al mismo tiempo, se
obtendrán más pistas sobre los cambios asociados a enfermedades. Por
tanto, la secuencia en bruto, tal y como se obtiene en los proyectos de
secuenciación masiva, no tiene ningún valor sin los análisis y la
posterior anotación de las características que definen estas funciones.
Esta tesis presenta nuestra contribución a tres aspectos relacionados de
la anotación de los genes en genomas eucariotas.

Primero, la comparación a nivel de secuencia entre el genoma humano y el
de ratón se llevó a cabo mediante un protocolo semi-automático. El
programa de predicción de genes SGP2 se desarrolló a partir de elementos
de dicho protocolo. El concepto sobre el que se fundamenta el SGP2 es
que las regiones de similaridad obtenidas con el programa TBLASTX, se
utilizan para aumentar la puntuación de los exones predichos por el
programa geneid, con lo que se obtienen conjuntos más precisos de
anotaciones de estructuras génicas. SGP2 tiene una especificidad
suficiente como para validar esas anotaciones experimentalmente vía
RT-PCR. La validación de los sitios de splicing mediante el uso de la
técnica de la RT-PCR es un buen ejemplo de cómo la combinación de
aproximaciones computacionales y experimentales produce mejores
resultados que por separado.

Se ha llevado a cabo el análisis descriptivo a nivel de secuencia de los
sitios de splicing obtenidos sobre un conjunto fiable de genes ortólogos
para humano, ratón, rata y pollo. Se han explorado las diferencias a
nivel de nucleótido entre sitios U2 y U12 para el conjunto de intrones
ortólogos derivado de esos genes. Se ha visto que las señales de
splicing ortólogas entre humanos y roedores, así como entre roedores,
están más conservadas que las no ortólogas. Esta conservación puede ser
explicada en parte a nivel de conservación basal de los intrones. Por
otro lado, se ha detectado mayor conservación de la esperada entre
sitios de splicing ortólogos entre mamíferos y pollo. Los resultados
obtenidos indican también que las clases intrónicas U2 y U12 han
evolucionado independientemente desde el ancestro común de mamíferos y
aves. Tampoco se ha hallado ningún caso convincente de interconversión
entre estas dos clases en el conjunto de intrones ortólogos generado, ni
ningún caso de substitución entre los subtipos AT-AC y GT-AG en intrones
U12. Por el contrario, el paso de GT-AG a GC-AG, y viceversa, en
intrones U2 no parece ser inusual.

Finalmente, se han implementado una serie de herramientas de
visualización para integrar anotaciones obtenidas por los programas de
predicción de genes y por los análisis comparativos sobre genomas. Una
de estas herramientas, gff2ps, se ha utilizado para cartografiar los
genomas humano, de la mosca del vinagre y del mosquito de la malaria. El
programa gff2aplot y los filtros asociados, han facilitado la tarea de
integrar anotaciones a nivel de secuencia con los resultados obtenidos
por herramientas de búsqueda de homología, como BLAST. Se ha adaptado
también el concepto de pictograma al análisis comparativo de los sitios
de splicing ortólogos, con el desarrollo del programa compi.
The constantly increasing amount of available genome sequences, along
with an increasing number of experimental techniques, will help to
produce the complete catalog of cellular functions for different
organisms, including humans. Such a catalog will define the base from
which we will better understand how organisms work at the molecular
level. At the same time it will shed light on which changes are
associated with disease. Therefore, the raw sequence from genome
sequencing projects is worthless without the complete analysis and
further annotation of the genomic features that define those functions.
This dissertation presents our contribution to three related aspects of
gene annotation on eukaryotic genomes.

First, a comparison at sequence level of human and mouse genomes was
performed by developing a semi-automatic analysis pipeline. The SGP2
gene-finding tool was developed from procedures used in this pipeline.
The concept behind SGP2 is that similarity regions obtained by TBLASTX
are used to increase the score of exons predicted by geneid, in order to
produce a more accurate set of gene structures. SGP2 provides a
specificity that is high enough for its predictions to be experimentally
verified by RT-PCR. The RT-PCR validation of predicted splice junctions
also serves as example of how combined computational and experimental
approaches will yield the best results.

Then, we performed a descriptive analysis at sequence level of the
splice site signals from a reliable set of orthologous genes for human,
mouse, rat and chicken. We have explored the differences at nucleotide
sequence level between U2 and U12 for the set of orthologous introns
derived from those genes. We found that orthologous splice signals
between human and rodents and within rodents are more conserved than
unrelated splice sites. However, additional conservation can be
explained mostly by background intron conservation. Additional
conservation over background is detectable in orthologous mammalian and
chicken splice sites. Our results also indicate that the U2 and U12
intron classes have evolved independently since the split of mammals and
birds. We found neither convincing case of interconversion between these
two classes in our sets of orthologous introns, nor any single case of
switching between AT-AC and GT-AG subtypes within U12 introns. In
contrast, switching between GT-AG and GC-AG U2 subtypes does not appear
to be unusual.

Finally, we implemented visualization tools to integrate annotation
features for gene- finding and comparative analyses. One of those tools,
gff2ps, was used to draw the whole genome maps for human, fruitfly and
mosquito. gff2aplot and the accompanying parsers facilitate the task of
integrating sequence annotations with the output of homologybased tools,
like BLAST.We have also adapted the concept of pictograms to the
comparative analysis of orthologous splice sites, by developing compi.
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Dickinson, P. "Fibronectin gene expression in higher eukaryotic cells." Thesis, University of Manchester, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.378322.

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Ouma, Zachary Wilberforce. "Topological Properties of Eukaryotic Gene Regulatory Networks." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1512041623395438.

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Clark, Francis. "A computational study of gene structure and splicing in model eukaryote organisms /." St. Lucia, Qld, 2003. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe17395.pdf.

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Books on the topic "Eukaryotic gene"

1

Gene regulation: A eukaryotic perspective. 2nd ed. London: Chapman & Hall, 1995.

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Gene regulation: A eukaryotic perspective. 5th ed. New York: Taylor & Francis, 2006.

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Latchman, David S. Gene regulation: A eukaryotic perspective. London: Unwin Hyman, 1990.

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Gene regulation: A eukaryotic perspective. 4th ed. Cheltenham: Nelson Thornes, 2002.

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Privalsky, Martin L., ed. Transcriptional Corepressors: Mediators of Eukaryotic Gene Repression. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-10595-5.

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Wingender, Edgar. Gene regulation in eukaryotes. Weinheim: VCH, 1993.

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Wajapeyee, Narendra, and Romi Gupta, eds. Eukaryotic Transcriptional and Post-Transcriptional Gene Expression Regulation. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-6518-2.

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Barrett, Lucy W. Untranslated gene regions and other non-coding elements: Regulation of eukaryotic gene expression. Basel: Springer, 2013.

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J, Kingsman A., ed. Genetic engineering: An introduction to gene analysis and exploitation in eukaryotes. Oxford, England: Blackwell Scientific Publications, 1988.

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A, Broda P. M., Oliver S. G. 1949-, and Sims P, eds. The eukaryotic genome: Organisation and regulation. Cambridge: Cambridge University Press, 1993.

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Book chapters on the topic "Eukaryotic gene"

1

Gromek, Jennifer H., and Arik Dvir. "Eukaryotic Gene Transcription." In Signal Transduction: Pathways, Mechanisms and Diseases, 257–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02112-1_14.

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Kriegler, Michael. "Eukaryotic Control Elements." In Gene Transfer and Expression, 3–22. London: Palgrave Macmillan UK, 1990. http://dx.doi.org/10.1007/978-1-349-11891-5_1.

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Weber, Martin. "Gene Transfer into Eukaryotic Cells." In Manufacturing of Gene Therapeutics, 135–53. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1353-7_7.

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Gupta, Naba K., Mir F. Ahmad, Debopam Chakrabarti, and Nargis Nasrin. "Roles of Eukaryotic Initiation Factor 2 and Eukaryotic Initiation Factor 2 Ancillary Protein Factors in Eukaryotic Protein Synthesis Initiation." In Translational Regulation of Gene Expression, 287–334. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4684-5365-2_14.

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Gehrke, Lee. "Differential Translation of Eukaryotic Messenger RNAs." In Translational Regulation of Gene Expression, 367–78. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4684-5365-2_16.

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Solovyev, V. "Statistical Approaches in Eukaryotic Gene Prediction." In Handbook of Statistical Genetics, 97–159. Chichester, UK: John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch4.

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Stanke, Mario. "Computational Gene Prediction in Eukaryotic Genomes." In Cellular Origin, Life in Extreme Habitats and Astrobiology, 291–306. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-3795-4_16.

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Wasylyk, B. "Promoter Elements of Eukaryotic Protein-Coding Genes." In Chromosomal Proteins and Gene Expression, 103–19. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4684-7615-6_7.

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Durairaj, Geetha, Shivani Malik, and Sukesh R. Bhaumik. "Eukaryotic Gene Expression by RNA Polymerase II." In Gene Regulation, Epigenetics and Hormone Signaling, 1–28. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2017. http://dx.doi.org/10.1002/9783527697274.ch1.

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Walthers, Don, Alvin Go, and Linda J. Kenney. "Regulation of Porin Gene Expression by the Two-Component Regulatory System EnvZ/OmpR." In Bacterial and Eukaryotic Porins, 1–24. Weinheim, FRG: Wiley-VCH Verlag GmbH & Co. KGaA, 2005. http://dx.doi.org/10.1002/3527603875.ch1.

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Conference papers on the topic "Eukaryotic gene"

1

Hasty, Jeff. "Origins of extrinsic variability in eukaryotic gene expression." In 2006 Bio Micro and Nanosystems Conference. IEEE, 2006. http://dx.doi.org/10.1109/bmn.2006.330878.

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Akhtar, Mahmood, Eliathamby Ambikairajah, and Julien Epps. "Optimizing period-3 methods for eukaryotic gene prediction." In ICASSP 2008 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/icassp.2008.4517686.

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Wu, Shinq-Jen, Cheng-Tao Wu, and Tsu-Tian Lee. "Computation Intelligent for Eukaryotic Cell-Cycle Gene Network." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.260339.

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Wu, Shinq-Jen, Cheng-Tao Wu, and Tsu-Tian Lee. "Computation Intelligent for Eukaryotic Cell-Cycle Gene Network." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.4397830.

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Eftestol, T., T. Ryen, S. O. Aase, C. Strassle, M. Boos, G. Schuster, and P. Ruoff. "Eukaryotic Gene Prediction by Spectral Analysis and Pattern Recognition Techniques." In Proceedings of the 7th Nordic Signal Processing Symposium - NORSIG 2006. IEEE, 2006. http://dx.doi.org/10.1109/norsig.2006.275214.

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Gao, Meijun, and Kevin J. Liu. "Statistical analysis of GC-biased gene conversion and recombination hotspots in eukaryotic genomes." In BCB '21: 12th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3459930.3469509.

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Tinghong Zhang, Zhenjie Zhang, Xie Zhao, and Weishan Chang. "Eukaryotic expression of Porcine BST-2 gene and identification of biological activity of BST-2." In 2011 International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE). IEEE, 2011. http://dx.doi.org/10.1109/rsete.2011.5966124.

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Pannekok, H., A. J. Van Zonneveid, C. J. M. de vries, M. E. MacDonald, H. Veerman, and F. Blasi. "FUNCTIONAL PROPERTIES OF DELETION-MUTANTS OF TISSUE-TYPE PLASMINOGEN ACTIVATOR." In XIth International Congress on Thrombosis and Haemostasis. Schattauer GmbH, 1987. http://dx.doi.org/10.1055/s-0038-1643724.

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Over the past twenty-five years, genetic methods have generated a wealth of information on the regulation and the structure-function relationship of bacterial genes.These methods are based on the introduction of random mutations in a gene to alter its function. Subsequently, genetic techniques cure applied to localize the mutation, while the nature of the impairedfunction could be determined using biochemical methods. Classic examples of this approach is now considered to be the elucidation of the structure and function of genes, constituting the Escherichia coli lactose (lac) and tryptophan (trp) operons,and the detailed establishment of the structure and function of the repressor (lacl) of the lac operon. Recombinant DNA techniques and the development of appropriate expression systems have provided the means both to study structure and functionof eukaryotic (glyco-) proteins and to create defined mutations with a predestinedposition. The rationale for the construction of mutant genes should preferentiallyrely on detailed knowledge of the three-dimensional structure of the gene product.Elegant examples are the application of in vitro mutagenesis techniques to substitute amino-acid residues near the catalytic centre of subtilisin, a serine proteasefrom Bacillus species and to substituteanamino acid in the reactive site (i.e. Pi residue; methionine) of α-antitrypsin, a serine protease inhibitor. Such substitutions have resulted into mutant proteins which are less susceptible to oxidation and, in some cases, into mutant proteins with a higher specific activity than the wild-type protein.If no data are available on the ternary structure of a protein, other strategies have to be developed to construct intelligent mutants to study the relation between the structure and the function of a eukaryotic protein. At least for a number of gene families, the gene structure is thought to be created by "exon shuffling", an evolutionary recombinational process to insert an exon or a set of exons which specify an additional structural and/or functional domain into a pre-existing gene. Both the structure of the tissue-type plasminogen activator protein(t-PA) and the t-PA gene suggest that this gene has evolved as a result of exon shuffling. As put forward by Gilbert (Science 228 (1985) 823), the "acid test"to prove the validity of the exon shuffling theory is either to delete, insert or to substitute exon(s) (i.e. in the corresponding cDNA) and toassay the properties of the mutant proteins to demonstrate that an exon or a set of adjacent exons encode (s) an autonomousfunction. Indeed, by the construction of specific deletions in full-length t-PA cDNA and expression of mutant proteins intissue-culture cells, we have shown by this approach that exon 2 of thet-PA gene encodes the function required forsecretion, exon 4 encodes the "finger" domain involved in fibrin binding(presumably on undegraded fibrin) and the set of exons 8 and 9 specifies kringle 2, containing a lysine-binding sit(LBS) which interacts with carboxy-terminal lysines, generated in fibrin after plasmic digestion. Exons 10 through 14 encode the carboxy-ter-minal light chain of t-PA and harbor the catalytic centre of the molecule and represents the predominant "target site" for the fast-acting endothelial plasminogen activator inhibitor (PAI-1).As a follow-up of this genetic approach to construct deletion mutants of t-PA, we also created substitution mutants of t-PA. Different mutants were constructed to substitute cDNA encoding thelight chain of t-PA by cDNA encoding the B-chain of urokinase (u-PA), in order to demonstrate that autonomous structural and functional domains of eitherone of the separate molecules are able toexert their intrinsic properties in a different context (C.J.M. de Vries et al., this volume). The possibilities and the limitations of this approach to study the structure and the function of t-PA and of other components of the fibrinolytic process will be outlined.
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Mochalova, E. N. "Rational Design of Nanoparticle-Based Agents for Effective Targeted Drug and Gene Delivery to Eukaryotic Cells." In 2020 International Conference Laser Optics (ICLO). IEEE, 2020. http://dx.doi.org/10.1109/iclo48556.2020.9285548.

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Hassan, H. J., L. Cianetti, P. M. Mannucci, V. Vicente, R. Cortese, and C. Peschle. "HEREDITARY THROMBOPHILIA CAUSED BY MISSENSE MUTATION IN PROTEIN C GENE." In XIth International Congress on Thrombosis and Haemostasis. Schattauer GmbH, 1987. http://dx.doi.org/10.1055/s-0038-1642944.

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The structure of the gene for protein C was analyzed in 13 protein C deficient unrelated patients (11 heterozygous, 2 homozygous), who showed an equivalent reduction of this serine protease at both enzymatic and antigen level. No deletion(s) or rearrangement(s) was demonstrated by Southern blot after hybridization to a cDNA probe. One patient showed a variant restriction pattern after Bam HI digestion, characterized by an abnormal 9.6 kb band in addition to the 8.3 and 1.3 normal ones. Extensive family studies, including 7 heterozygotes with the same clinical phenotype, showed the same abnormal pattern in all and only these heterozygotes. Protein C gene from the propositus was cloned in EMBL3 lambda vector. A 411 bp PstI - SacI fragment from exon 9 encompassing the mutation in the Bam HI site was subcloned in M13mpl8. Its sequence showed a single transversion in the Bam HI palyndrome (GGATCC -> GCATCC) : this causes a substitution of the 402 thryptophan residue with a cystein. The 402 thryptophan residue is constantly conserved in a biochemical domain present in all eukaryotic serine proteases: substitution of the large thryptophan aromatic ring with the small cysteine hydrophilic side-chain conceivably leads to destabilization of the tertiary structure of protein C in these heterozygotes. Thus, the point mutation reported here is sufficient to explain the protein C deficiency in these subjects, and is apparently responsible for their clinical phenotype.
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Reports on the topic "Eukaryotic gene"

1

Lee, Andrew Loyd. Structural and dynamic characterization of eukaryotic gene regulatory protein domains in solution. Office of Scientific and Technical Information (OSTI), May 1996. http://dx.doi.org/10.2172/373861.

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