Integração de mapas genéticos

Detalhes bibliográficos
Ano de defesa: 2008
Autor(a) principal: Salgado, Caio Césio
Orientador(a): Cruz, Cosme Damião lattes
Banca de defesa: Barros, Willian Silva lattes, Caixeta, Eveline Teixeira lattes
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Viçosa
Programa de Pós-Graduação: Mestrado em Genética e Melhoramento
Departamento: Genética animal; Genética molecular e de microrganismos; Genética quantitativa; Genética vegetal; Me
País: BR
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: http://locus.ufv.br/handle/123456789/4686
Resumo: The genetic mapping facilitates the breeding work once one or more marks of the genotype can be associated to controlling genes of qualitative and quantitative characteristics (QTL). Genetic maps for several species have been built by different groups of researchers with different molecular markers and populations. A way to generate maps more saturated for those species would be the integration of the existent maps. The key to integrate different maps is the presence of common marks among them. Only when there are a minimum number of common marks among the different maps, these can be integrated. This way, the objective of this work was to develop a process of integration of genetic maps and to test the efficiency of this process. Data from the simulation of genome and populations were generated and analyzed. A important factor to obtain solid data in a mapping work is the sample or population size. Based in these simulated data it was evaluated the optimum population size to study the integration of genetic maps. To obtain and study the consensus maps, parental genomes and samples of co- dominant F2, dominant F2 and backcrosses populations were simulated. The generated samples had 100, 200, 400 individuals with 3 linkage groups each and 11 dominant and co-dominant molecular marks spaced by 5, 10 and 15 centiMorgans. 10 repetitions were accomplished by sample, five used to construct the consensus maps with analysis multilocus and other five without analysis multilocus. It was concluded that the obtention of the consensus maps becomes more efficient with the increase of the population size. A population size of 200 individuals would be enough to rescue the original information. To study the obtention of the effective integrated map samples of co-dominant F2 and backcrosses populations were simulated. The generated samples had 100, 200 and 400 individuals, 21 marks for linkage group and markers equidistant by 5 cM, in a total of four simulations for co-dominant F2 and four for backcrosses. Each simulated genome was fragmented in four new maps which three maps had eight markers and one had nine markers, each one of these maps containing four markers that are anchors among the four maps. These new maps were aligned, orderly and integrated and then compared with the original map. It was concluded that the process of ordainment and integration are efficient to obtain the integrated map. The population size exercises influence on the map and the distances measures among the marks.
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spelling Salgado, Caio Césiohttp://lattes.cnpq.br/3824742152089733Viana, José Marcelo Sorianohttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4786170D5Carneiro, Pedro Crescêncio Souzahttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4728227T6Cruz, Cosme Damiãohttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4788274A6Barros, Willian Silvahttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4737461Z0Caixeta, Eveline Teixeirahttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4728636Z72015-03-26T13:42:06Z2009-06-232015-03-26T13:42:06Z2008-07-28SALGADO, Caio Césio. Integrated genetic maps. 2008. 142 f. Dissertação (Mestrado em Genética animal; Genética molecular e de microrganismos; Genética quantitativa; Genética vegetal; Me) - Universidade Federal de Viçosa, Viçosa, 2008.http://locus.ufv.br/handle/123456789/4686The genetic mapping facilitates the breeding work once one or more marks of the genotype can be associated to controlling genes of qualitative and quantitative characteristics (QTL). Genetic maps for several species have been built by different groups of researchers with different molecular markers and populations. A way to generate maps more saturated for those species would be the integration of the existent maps. The key to integrate different maps is the presence of common marks among them. Only when there are a minimum number of common marks among the different maps, these can be integrated. This way, the objective of this work was to develop a process of integration of genetic maps and to test the efficiency of this process. Data from the simulation of genome and populations were generated and analyzed. A important factor to obtain solid data in a mapping work is the sample or population size. Based in these simulated data it was evaluated the optimum population size to study the integration of genetic maps. To obtain and study the consensus maps, parental genomes and samples of co- dominant F2, dominant F2 and backcrosses populations were simulated. The generated samples had 100, 200, 400 individuals with 3 linkage groups each and 11 dominant and co-dominant molecular marks spaced by 5, 10 and 15 centiMorgans. 10 repetitions were accomplished by sample, five used to construct the consensus maps with analysis multilocus and other five without analysis multilocus. It was concluded that the obtention of the consensus maps becomes more efficient with the increase of the population size. A population size of 200 individuals would be enough to rescue the original information. To study the obtention of the effective integrated map samples of co-dominant F2 and backcrosses populations were simulated. The generated samples had 100, 200 and 400 individuals, 21 marks for linkage group and markers equidistant by 5 cM, in a total of four simulations for co-dominant F2 and four for backcrosses. Each simulated genome was fragmented in four new maps which three maps had eight markers and one had nine markers, each one of these maps containing four markers that are anchors among the four maps. These new maps were aligned, orderly and integrated and then compared with the original map. It was concluded that the process of ordainment and integration are efficient to obtain the integrated map. The population size exercises influence on the map and the distances measures among the marks.O mapeamento genético facilita o trabalho de melhoramento uma vez que uma ou mais marcas do genótipo podem ser associadas a genes controladores de características qualitativas e quantitativas (QTL). Mapas genéticos para diversas espécies tem sido construídos por diferentes grupos de pesquisadores com diferentes tipos de marcadores e diferentes tipos de populações. Uma maneira de gerar mapas mais saturados para as diversas culturas seria a integração dos mapas genéticos já existentes. A chave para integração de mapas distintos é a presença de marcas comuns entre os mapas. Somente quando há um número mínimo de marcas comuns entre os diferentes mapas, estes podem ser integrados. Deste modo, o objetivo deste trabalho foi desenvolver um processo de integração de mapas genéticos e testar a eficiência do processo de integração. Para isso foram gerados e analisados dados a partir da simulação de genoma e de populações. Um dos fatores de fundamental importância para se obter dados consistentes em um trabalho de mapeamento é o tamanho da amostra ou população a ser trabalhada. Com base nestes dados simulados, avaliou-se o tamanho ótimo de populações para estudo de integração de mapas genéticos. Para estudo e obtenção dos mapas consenso foram simulados genomas parentais e amostras de populações F2 codominantes, F2 dominantes e de retrocruzamentos. As amostras geradas foram de tamanho 100, 200 e 400 indivíduos com três grupos de ligação cada e 11 marcas moleculares co-dominantes e dominantes espaçadas a 5, 10 e 15 centimorgans por grupo de ligação. Foram realizadas 10 repetições por amostra, sendo que destas, cinco foram utilizadas para construção de mapas consenso com análise multiloco e outras cinco sem análise multiloco. Concluiu-se que a obtenção dos mapas consenso se torna mais eficiente com aumento do tamanho da população. Um tamanho populacional de 200 indivíduos seria o suficiente para resgatar as informações originais. Para estudo da obtenção do mapa integrado efetivo foram simuladas F2 co-dominante e retrocruzamento com tamanhos de 100, 200 e 400 indivíduos, com 21 marcas por grupo de ligação e marcadores eqüidistantes a 5 cM, em um total de quatro simulações para F2 codominante e quatro para retrocruzamentos. Cada genoma simulado foi fragmentado em quatro novos mapas de modo que, foram obtidos três mapas com oito marcadores e um com nove marcadores, sendo que cada um deles constando quatro marcadores que são âncoras entre os quatro mapas. Estes novos mapas foram alinhados, ordenados, integrados e em seguida comparados com o mapa de origem. Concluiu-se que os processos de ordenamento e integração são eficientes para obtenção do mapa integrado e, também, que o tamanho da população exerce influência sobre o mapa e as medidas de distâncias entre as marcas.Conselho Nacional de Desenvolvimento Científico e Tecnológicoapplication/pdfporUniversidade Federal de ViçosaMestrado em Genética e MelhoramentoUFVBRGenética animal; Genética molecular e de microrganismos; Genética quantitativa; Genética vegetal; MeMapa genéticoMarcadores âncorasMapa consensoGenetic mapAnchors markersConsensus mapsCNPQ::CIENCIAS BIOLOGICAS::GENETICA::GENETICA QUANTITATIVAIntegração de mapas genéticosIntegrated genetic mapsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALtexto completo.pdfapplication/pdf1107978https://locus.ufv.br//bitstream/123456789/4686/1/texto%20completo.pdf5a845c5ae4a67c50d70037eeeeb7eed9MD51TEXTtexto completo.pdf.txttexto completo.pdf.txtExtracted texttext/plain241487https://locus.ufv.br//bitstream/123456789/4686/2/texto%20completo.pdf.txt9da51decdde2812657d116087d363d86MD52THUMBNAILtexto completo.pdf.jpgtexto completo.pdf.jpgIM Thumbnailimage/jpeg3509https://locus.ufv.br//bitstream/123456789/4686/3/texto%20completo.pdf.jpg3a346afdb10df11e897ad49ac51de65dMD53123456789/46862016-04-10 23:12:32.596oai:locus.ufv.br:123456789/4686Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452016-04-11T02:12:32LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false
dc.title.por.fl_str_mv Integração de mapas genéticos
dc.title.alternative.eng.fl_str_mv Integrated genetic maps
title Integração de mapas genéticos
spellingShingle Integração de mapas genéticos
Salgado, Caio Césio
Mapa genético
Marcadores âncoras
Mapa consenso
Genetic map
Anchors markers
Consensus maps
CNPQ::CIENCIAS BIOLOGICAS::GENETICA::GENETICA QUANTITATIVA
title_short Integração de mapas genéticos
title_full Integração de mapas genéticos
title_fullStr Integração de mapas genéticos
title_full_unstemmed Integração de mapas genéticos
title_sort Integração de mapas genéticos
author Salgado, Caio Césio
author_facet Salgado, Caio Césio
author_role author
dc.contributor.authorLattes.por.fl_str_mv http://lattes.cnpq.br/3824742152089733
dc.contributor.author.fl_str_mv Salgado, Caio Césio
dc.contributor.advisor-co1.fl_str_mv Viana, José Marcelo Soriano
dc.contributor.advisor-co1Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4786170D5
dc.contributor.advisor-co2.fl_str_mv Carneiro, Pedro Crescêncio Souza
dc.contributor.advisor-co2Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4728227T6
dc.contributor.advisor1.fl_str_mv Cruz, Cosme Damião
dc.contributor.advisor1Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4788274A6
dc.contributor.referee1.fl_str_mv Barros, Willian Silva
dc.contributor.referee1Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4737461Z0
dc.contributor.referee2.fl_str_mv Caixeta, Eveline Teixeira
dc.contributor.referee2Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4728636Z7
contributor_str_mv Viana, José Marcelo Soriano
Carneiro, Pedro Crescêncio Souza
Cruz, Cosme Damião
Barros, Willian Silva
Caixeta, Eveline Teixeira
dc.subject.por.fl_str_mv Mapa genético
Marcadores âncoras
Mapa consenso
topic Mapa genético
Marcadores âncoras
Mapa consenso
Genetic map
Anchors markers
Consensus maps
CNPQ::CIENCIAS BIOLOGICAS::GENETICA::GENETICA QUANTITATIVA
dc.subject.eng.fl_str_mv Genetic map
Anchors markers
Consensus maps
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS BIOLOGICAS::GENETICA::GENETICA QUANTITATIVA
description The genetic mapping facilitates the breeding work once one or more marks of the genotype can be associated to controlling genes of qualitative and quantitative characteristics (QTL). Genetic maps for several species have been built by different groups of researchers with different molecular markers and populations. A way to generate maps more saturated for those species would be the integration of the existent maps. The key to integrate different maps is the presence of common marks among them. Only when there are a minimum number of common marks among the different maps, these can be integrated. This way, the objective of this work was to develop a process of integration of genetic maps and to test the efficiency of this process. Data from the simulation of genome and populations were generated and analyzed. A important factor to obtain solid data in a mapping work is the sample or population size. Based in these simulated data it was evaluated the optimum population size to study the integration of genetic maps. To obtain and study the consensus maps, parental genomes and samples of co- dominant F2, dominant F2 and backcrosses populations were simulated. The generated samples had 100, 200, 400 individuals with 3 linkage groups each and 11 dominant and co-dominant molecular marks spaced by 5, 10 and 15 centiMorgans. 10 repetitions were accomplished by sample, five used to construct the consensus maps with analysis multilocus and other five without analysis multilocus. It was concluded that the obtention of the consensus maps becomes more efficient with the increase of the population size. A population size of 200 individuals would be enough to rescue the original information. To study the obtention of the effective integrated map samples of co-dominant F2 and backcrosses populations were simulated. The generated samples had 100, 200 and 400 individuals, 21 marks for linkage group and markers equidistant by 5 cM, in a total of four simulations for co-dominant F2 and four for backcrosses. Each simulated genome was fragmented in four new maps which three maps had eight markers and one had nine markers, each one of these maps containing four markers that are anchors among the four maps. These new maps were aligned, orderly and integrated and then compared with the original map. It was concluded that the process of ordainment and integration are efficient to obtain the integrated map. The population size exercises influence on the map and the distances measures among the marks.
publishDate 2008
dc.date.issued.fl_str_mv 2008-07-28
dc.date.available.fl_str_mv 2009-06-23
2015-03-26T13:42:06Z
dc.date.accessioned.fl_str_mv 2015-03-26T13:42:06Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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dc.identifier.citation.fl_str_mv SALGADO, Caio Césio. Integrated genetic maps. 2008. 142 f. Dissertação (Mestrado em Genética animal; Genética molecular e de microrganismos; Genética quantitativa; Genética vegetal; Me) - Universidade Federal de Viçosa, Viçosa, 2008.
dc.identifier.uri.fl_str_mv http://locus.ufv.br/handle/123456789/4686
identifier_str_mv SALGADO, Caio Césio. Integrated genetic maps. 2008. 142 f. Dissertação (Mestrado em Genética animal; Genética molecular e de microrganismos; Genética quantitativa; Genética vegetal; Me) - Universidade Federal de Viçosa, Viçosa, 2008.
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dc.publisher.department.fl_str_mv Genética animal; Genética molecular e de microrganismos; Genética quantitativa; Genética vegetal; Me
publisher.none.fl_str_mv Universidade Federal de Viçosa
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