Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irati 122

Detalhes bibliográficos
Autor(a) principal: Ramos, Mariana Rodrigues Feitosa
Data de Publicação: 2019
Tipo de documento: Tese
Idioma: por
Título da fonte: Repositório Institucional da UFG
dARK ID: ark:/38995/0013000008zxm
Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/10297
Resumo: A relevant aspect of all rice breeding programs is the extensive genetic variability available and stored in germplasm banks. A major challenge is precisely how to select the most appropriate genotypes to meet the objectives of these programs. An interesting alternative is the assembly of core collections. Besides the characterization per se, the accessions that stood out for their genetic variability or productive performance were crossed in a diallel scheme. The resulting hybrids were self-fertilized to obtain generation F2, which was advanced by Bulk and SSD until F7. Among the most productive crosses, one in particular was interesting due to the genetic distance between the parents (RW = 0.91), and the high value of specific combining ability - Epagri 108 (Oryza sativa spp. Indica) x Irat 122 (Oryza sativa spp. Japonica). This study aimed to perform QTL analysis for plant yield and height using two populations of Epagri 108 x Irat 122 cross, advanced by SSD (generation F8) and Bulk (generation F7:8) methods. The 158 recombinant inbred lines of each method (SSD and Bulk) were evaluated for two years (2016/2017 and 2017/2018 seasons), in a 18x18 double lattice design with two replications, consisting of four-line plots of three meters in Palmital Farm (Goianira, GO). The RILs were genotyped by the DArTseq® methodology, which generated about 6,000 SNPs. The statistical model adopted for the grain yield data analysis was mixed linear model (MLM) through the R program. For the first and second year evaluations (2016/2017 and 2017/2018 seasons) and joint analysis (two years/seasons), the RILs-Bulk group presented higher grain yield averages when compared to the RILs-SSD and testers group. However, regarding the genetic variance component, the SSD group presented the highest estimate followed by Bulk and testers. Bulk-RIL yields ranged from 4,010.75 kg ha-1 to 5,815.42 kg ha-1, while SSD-RILs ranged from 3,321.76 kg ha-1 to 8,096.27 kg ha-1, both exceeding the testers group, which ranged from 2,754.30 kg ha-1 to 3,643.73 kg ha-1.For the plant height trait (ALT), in the first year, the plants ranged from 116 cm to 165 cm for RILs-Bulk. On the other hand, RILsSSD ranged from 91 cm to 177 cm, while the testers ranged from 100 cm to 104 cm. In the second year, RILs-Bulk ranged from 101 cm to 130 cm, while RILs-SSD ranged from 81 cm to 132 cm, while the testers presented heights from 96 cm to 117 cm. In the joint analysis, the testers presented the lowest heights. For QTL analysis, multiple interval mapping was used, with a total of 2,115 SNPs, and 3 QTLs were identified in the SSIL-RILs for the grain yield (PG) traitr, of which 2 QTLs were located on chromosome 6 (qGYLD6.1 and qGYLD6.2), one for the second year of experiment, with a phenotypic variation of 23.56%, and the other for the joint analysis, explaining 9.45% of the phenotypic variation. The other QTL was identified on chromosome 9 (qGYLD9) for the second year, with a phenotypic variation of 7.45%. For the trait height (ALT) a QTL on chromosome 1 (qPTHT1) was identified, with a phenotypic variation of 14.01%. For RILs-Bulk, with a total of 2,354 markers, 3 QTLs were identified for the PG character, two QTLs mapped on chromosomes 6 and 9 (qGYLD6 and qGYLD9), referring to the second year of evaluation, presenting a phenotypic variation of 21.65. % and 3.71%, respectively. In the joint analysis a QTL was mapped on chromosome 7 (qGYLD7), with phenotypic variation of 12.9%. For ALT no QTL was found in the RILs-Bulk. From the identification of these QTLs in haplotypic blocks, the next step will be the validation of markers in Embrapa germplasm bank accesses before being incorporated into the assisted selection routine, in order to identify materials with higher grain yield potential. For the Epagri 108 x Irat 122 cross, the SSD method was the most efficient in the generation of superior rice lines for grain yield, but at a higher operating cost than the Bulk method. RILs derived from both Bulk and SSD identified QTLs for the PG character; however, SSD identified a higher number of QTLs with greater effect on trait variation.
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spelling Brondani, Claudiohttp://lattes.cnpq.br/4775600104554147Brondani, ClaudioVianello, Rosana PereiraBorba, Tereza Cristina de OliveiraCoelho, Gesimária Ribeiro CostaRamalho, Ivanildohttp://lattes.cnpq.br/5095095609338794Ramos, Mariana Rodrigues Feitosa2020-01-14T11:51:54Z2019-11-12RAMOS, M. R. F. Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irat 122. 2019. 145 f. Tese (Doutorado em Genética e Melhoramento de Plantas) - Universidade Federal de Goiás, Goiânia, 2019.http://repositorio.bc.ufg.br/tede/handle/tede/10297ark:/38995/0013000008zxmA relevant aspect of all rice breeding programs is the extensive genetic variability available and stored in germplasm banks. A major challenge is precisely how to select the most appropriate genotypes to meet the objectives of these programs. An interesting alternative is the assembly of core collections. Besides the characterization per se, the accessions that stood out for their genetic variability or productive performance were crossed in a diallel scheme. The resulting hybrids were self-fertilized to obtain generation F2, which was advanced by Bulk and SSD until F7. Among the most productive crosses, one in particular was interesting due to the genetic distance between the parents (RW = 0.91), and the high value of specific combining ability - Epagri 108 (Oryza sativa spp. Indica) x Irat 122 (Oryza sativa spp. Japonica). This study aimed to perform QTL analysis for plant yield and height using two populations of Epagri 108 x Irat 122 cross, advanced by SSD (generation F8) and Bulk (generation F7:8) methods. The 158 recombinant inbred lines of each method (SSD and Bulk) were evaluated for two years (2016/2017 and 2017/2018 seasons), in a 18x18 double lattice design with two replications, consisting of four-line plots of three meters in Palmital Farm (Goianira, GO). The RILs were genotyped by the DArTseq® methodology, which generated about 6,000 SNPs. The statistical model adopted for the grain yield data analysis was mixed linear model (MLM) through the R program. For the first and second year evaluations (2016/2017 and 2017/2018 seasons) and joint analysis (two years/seasons), the RILs-Bulk group presented higher grain yield averages when compared to the RILs-SSD and testers group. However, regarding the genetic variance component, the SSD group presented the highest estimate followed by Bulk and testers. Bulk-RIL yields ranged from 4,010.75 kg ha-1 to 5,815.42 kg ha-1, while SSD-RILs ranged from 3,321.76 kg ha-1 to 8,096.27 kg ha-1, both exceeding the testers group, which ranged from 2,754.30 kg ha-1 to 3,643.73 kg ha-1.For the plant height trait (ALT), in the first year, the plants ranged from 116 cm to 165 cm for RILs-Bulk. On the other hand, RILsSSD ranged from 91 cm to 177 cm, while the testers ranged from 100 cm to 104 cm. In the second year, RILs-Bulk ranged from 101 cm to 130 cm, while RILs-SSD ranged from 81 cm to 132 cm, while the testers presented heights from 96 cm to 117 cm. In the joint analysis, the testers presented the lowest heights. For QTL analysis, multiple interval mapping was used, with a total of 2,115 SNPs, and 3 QTLs were identified in the SSIL-RILs for the grain yield (PG) traitr, of which 2 QTLs were located on chromosome 6 (qGYLD6.1 and qGYLD6.2), one for the second year of experiment, with a phenotypic variation of 23.56%, and the other for the joint analysis, explaining 9.45% of the phenotypic variation. The other QTL was identified on chromosome 9 (qGYLD9) for the second year, with a phenotypic variation of 7.45%. For the trait height (ALT) a QTL on chromosome 1 (qPTHT1) was identified, with a phenotypic variation of 14.01%. For RILs-Bulk, with a total of 2,354 markers, 3 QTLs were identified for the PG character, two QTLs mapped on chromosomes 6 and 9 (qGYLD6 and qGYLD9), referring to the second year of evaluation, presenting a phenotypic variation of 21.65. % and 3.71%, respectively. In the joint analysis a QTL was mapped on chromosome 7 (qGYLD7), with phenotypic variation of 12.9%. For ALT no QTL was found in the RILs-Bulk. From the identification of these QTLs in haplotypic blocks, the next step will be the validation of markers in Embrapa germplasm bank accesses before being incorporated into the assisted selection routine, in order to identify materials with higher grain yield potential. For the Epagri 108 x Irat 122 cross, the SSD method was the most efficient in the generation of superior rice lines for grain yield, but at a higher operating cost than the Bulk method. RILs derived from both Bulk and SSD identified QTLs for the PG character; however, SSD identified a higher number of QTLs with greater effect on trait variation.Um aspecto relevante de todos os programas de melhoramento genético de arroz é a extensa variabilidade genética disponível e armazenada em bancos de germoplasma. Um grande desafio é justamente o modo de como selecionar os genótipos mais adequados para atender os objetivos desses programas. Uma alternativa interessante é a montagem de coleções nucleares. Além da caracterização per se, os acessos que se destacaram por sua variabilidade genética ou desempenho produtivo foram cruzados entre si em esquema de dialelo. Os híbridos resultantes foram autofecundados para obtenção da geração F2, que foi avançada por Bulk e SSD até F7. Dentre os cruzamentos mais produtivos, um em particular chamou a atenção, inicialmente pela distância genética entre os genitores (RW= 0,91), e posteriormente, pelo alto valor de capacidade específica de combinação - o Epagri 108 (Oryza sativa spp. indica) x Irat 122 (Oryza sativa spp. japonica). Esse trabalho objetivou realizar análise de QTLs para produtividade e altura de plantas utilizando duas populações do cruzamento Epagri 108 x Irat 122, avançadas pelos métodos de SSD (geração F8) e Bulk (geração F7:8). As 158 linhagens (RILs) de cada método (SSD e Bulk) foram avaliadas por dois anos (safras 2016/2017 e 2017/2018), no delineamento látice duplo 18x18 com duas repetições, compostas por parcelas de quatro linhas de três metros, na Fazenda Palmital (Goianira, GO). As RILs foram genotipadas pela metodologia DArTseq®, que gerou cerca de 6 mil SNPs. O modelo estatístico adotado para a análise dos dados de produtividade foi modelo linear misto (MLM) por meio do programa R. Para as avaliações do primeiro e segundo ano (safras 2016/2017 e 2017/2018) e análise conjunta (dois anos/safras), o grupo de RILs-Bulk apresentou maiores médias de produtividade quando comparado ao grupo RILs-SSD e Testemunhas. Porém, quanto ao componente de variância genética, o grupo SSD apresentou a maior estimativa seguido por Bulk e Testemunhas. As produtividades das RILs-Bulk variaram de 4.010,75 kg ha-1 a 5.815,42 kg ha-1 , enquanto que as RILs-SSD variaram de 3.321,76 kg ha-1 a 8.096.27 kg ha-1 , ambas superando o grupo das Testemunhas, que variaram de 2.754,30 kg ha-1 a 3.643,73 kg ha-1 . Para o caráter altura de plantas (ALT), no primeiro ano, as plantas variaram de 116 cm a 165 cm para as RILs- Bulk. Já as RILs-SSD apresentaram variação de 91 cm a 177 cm, enquanto que as Testemunhas variaram de 100 cm a 104 cm. No segundo ano, as RILs-Bulk tiveram variação de 101 cm a 130 cm, enquanto as RILs-SSD variaram de 81 cm a 132 cm, já as Testemunhas apresentaram alturas de 96 cm a 117 cm. Na análise conjunta, as Testemunhas apresentaram as menores alturas. Para a análise de QTLs foi utilizado o mapeamento por intervalo múltiplo, com um total de 2.115 SNPs, e foram identificados 3 QTLs nas RILs-SSD para o caráter produtividade de grãos (PG), dos quais 2 QTLs foram localizados no cromossomo 6 (qGYLD6.1 e qGYLD6.2), um para o segundo ano de avaliação, com variação fenotípica de 23,56%, e o outro para a análise conjunta, explicando 9,45% da variação fenotípica. O outro QTL foi identificado no cromossomo 9 (qGYLD9), para o segundo ano,com variação fenotípica de 7,45%. Para o caráter altura (ALT) foi identificado um QTL no cromossomo 1 (qPTHT1), com a variação fenotípica de 14,01%. Para as RILs- Bulk, com total de 2.354 marcadores, 3 QTLs foram identificados para o caráter PG, sendo dois QTLs mapeados nos cromossomos 6 e 9 (qGYLD6 e qGYLD9), referentes ao segundo ano de avaliação, apresentando variação fenotípica de 21,65% e 3,71%, respectivamente. Na análise conjunta um QTL foi mapeado no cromossomo 7 (qGYLD7), com variação fenotípica de 12,9%. Para ALT nenhum QTL foi encontrado nas RILs-Bulk. A partir da identificação desses QTLs nos blocos haplotípicos, a próxima etapa será a validação dos marcadores em acessos do banco de germoplasma da Embrapa antes de serem incorporados a rotina de seleção assistida, com a finalidade de identificar materiais com maior potencial produtivo. Para o cruzamento Epagri 108 x Irat 122 o método SSD foi o mais eficiente na geração de linhagens superiores de arroz para produtividade de grãos, porém a um custo operacional maior em relação ao método Bulk. RILs derivadas tanto de Bulk quanto SSD identificaram QTLs para o caráter PG, entretanto, SSD identificou maior número de QTLs com maior efeito na variação do caráter.Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2020-01-13T14:59:57Z No. of bitstreams: 2 Tese - Mariana Rodrigues Feitosa Ramos - 2019.pdf: 5272141 bytes, checksum: 0cfe0d8ad2a34814d1c728c6cc1ec00f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2020-01-14T11:51:54Z (GMT) No. of bitstreams: 2 Tese - Mariana Rodrigues Feitosa Ramos - 2019.pdf: 5272141 bytes, checksum: 0cfe0d8ad2a34814d1c728c6cc1ec00f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Made available in DSpace on 2020-01-14T11:51:54Z (GMT). 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dc.title.eng.fl_str_mv Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irati 122
dc.title.alternative.eng.fl_str_mv Comparative analysis of Bulk and SSD generation advancement methods in the identification of QTLs for rice grain yield at crossbreeding Epagri 108 X Irat 122
title Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irati 122
spellingShingle Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irati 122
Ramos, Mariana Rodrigues Feitosa
Dialelo
RILs
Marcadores SNPs
Mapeamento por Intervalo
Produtividade de grãos
RILs
SNP Markers
Interval Mapping
Grain yield
Diallel
GENETICA::GENETICA VEGETAL
title_short Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irati 122
title_full Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irati 122
title_fullStr Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irati 122
title_full_unstemmed Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irati 122
title_sort Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irati 122
author Ramos, Mariana Rodrigues Feitosa
author_facet Ramos, Mariana Rodrigues Feitosa
author_role author
dc.contributor.advisor1.fl_str_mv Brondani, Claudio
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/4775600104554147
dc.contributor.referee1.fl_str_mv Brondani, Claudio
dc.contributor.referee2.fl_str_mv Vianello, Rosana Pereira
dc.contributor.referee3.fl_str_mv Borba, Tereza Cristina de Oliveira
dc.contributor.referee4.fl_str_mv Coelho, Gesimária Ribeiro Costa
dc.contributor.referee5.fl_str_mv Ramalho, Ivanildo
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/5095095609338794
dc.contributor.author.fl_str_mv Ramos, Mariana Rodrigues Feitosa
contributor_str_mv Brondani, Claudio
Brondani, Claudio
Vianello, Rosana Pereira
Borba, Tereza Cristina de Oliveira
Coelho, Gesimária Ribeiro Costa
Ramalho, Ivanildo
dc.subject.por.fl_str_mv Dialelo
RILs
Marcadores SNPs
Mapeamento por Intervalo
Produtividade de grãos
RILs
SNP Markers
Interval Mapping
Grain yield
topic Dialelo
RILs
Marcadores SNPs
Mapeamento por Intervalo
Produtividade de grãos
RILs
SNP Markers
Interval Mapping
Grain yield
Diallel
GENETICA::GENETICA VEGETAL
dc.subject.eng.fl_str_mv Diallel
dc.subject.cnpq.fl_str_mv GENETICA::GENETICA VEGETAL
description A relevant aspect of all rice breeding programs is the extensive genetic variability available and stored in germplasm banks. A major challenge is precisely how to select the most appropriate genotypes to meet the objectives of these programs. An interesting alternative is the assembly of core collections. Besides the characterization per se, the accessions that stood out for their genetic variability or productive performance were crossed in a diallel scheme. The resulting hybrids were self-fertilized to obtain generation F2, which was advanced by Bulk and SSD until F7. Among the most productive crosses, one in particular was interesting due to the genetic distance between the parents (RW = 0.91), and the high value of specific combining ability - Epagri 108 (Oryza sativa spp. Indica) x Irat 122 (Oryza sativa spp. Japonica). This study aimed to perform QTL analysis for plant yield and height using two populations of Epagri 108 x Irat 122 cross, advanced by SSD (generation F8) and Bulk (generation F7:8) methods. The 158 recombinant inbred lines of each method (SSD and Bulk) were evaluated for two years (2016/2017 and 2017/2018 seasons), in a 18x18 double lattice design with two replications, consisting of four-line plots of three meters in Palmital Farm (Goianira, GO). The RILs were genotyped by the DArTseq® methodology, which generated about 6,000 SNPs. The statistical model adopted for the grain yield data analysis was mixed linear model (MLM) through the R program. For the first and second year evaluations (2016/2017 and 2017/2018 seasons) and joint analysis (two years/seasons), the RILs-Bulk group presented higher grain yield averages when compared to the RILs-SSD and testers group. However, regarding the genetic variance component, the SSD group presented the highest estimate followed by Bulk and testers. Bulk-RIL yields ranged from 4,010.75 kg ha-1 to 5,815.42 kg ha-1, while SSD-RILs ranged from 3,321.76 kg ha-1 to 8,096.27 kg ha-1, both exceeding the testers group, which ranged from 2,754.30 kg ha-1 to 3,643.73 kg ha-1.For the plant height trait (ALT), in the first year, the plants ranged from 116 cm to 165 cm for RILs-Bulk. On the other hand, RILsSSD ranged from 91 cm to 177 cm, while the testers ranged from 100 cm to 104 cm. In the second year, RILs-Bulk ranged from 101 cm to 130 cm, while RILs-SSD ranged from 81 cm to 132 cm, while the testers presented heights from 96 cm to 117 cm. In the joint analysis, the testers presented the lowest heights. For QTL analysis, multiple interval mapping was used, with a total of 2,115 SNPs, and 3 QTLs were identified in the SSIL-RILs for the grain yield (PG) traitr, of which 2 QTLs were located on chromosome 6 (qGYLD6.1 and qGYLD6.2), one for the second year of experiment, with a phenotypic variation of 23.56%, and the other for the joint analysis, explaining 9.45% of the phenotypic variation. The other QTL was identified on chromosome 9 (qGYLD9) for the second year, with a phenotypic variation of 7.45%. For the trait height (ALT) a QTL on chromosome 1 (qPTHT1) was identified, with a phenotypic variation of 14.01%. For RILs-Bulk, with a total of 2,354 markers, 3 QTLs were identified for the PG character, two QTLs mapped on chromosomes 6 and 9 (qGYLD6 and qGYLD9), referring to the second year of evaluation, presenting a phenotypic variation of 21.65. % and 3.71%, respectively. In the joint analysis a QTL was mapped on chromosome 7 (qGYLD7), with phenotypic variation of 12.9%. For ALT no QTL was found in the RILs-Bulk. From the identification of these QTLs in haplotypic blocks, the next step will be the validation of markers in Embrapa germplasm bank accesses before being incorporated into the assisted selection routine, in order to identify materials with higher grain yield potential. For the Epagri 108 x Irat 122 cross, the SSD method was the most efficient in the generation of superior rice lines for grain yield, but at a higher operating cost than the Bulk method. RILs derived from both Bulk and SSD identified QTLs for the PG character; however, SSD identified a higher number of QTLs with greater effect on trait variation.
publishDate 2019
dc.date.issued.fl_str_mv 2019-11-12
dc.date.accessioned.fl_str_mv 2020-01-14T11:51:54Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv RAMOS, M. R. F. Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irat 122. 2019. 145 f. Tese (Doutorado em Genética e Melhoramento de Plantas) - Universidade Federal de Goiás, Goiânia, 2019.
dc.identifier.uri.fl_str_mv http://repositorio.bc.ufg.br/tede/handle/tede/10297
dc.identifier.dark.fl_str_mv ark:/38995/0013000008zxm
identifier_str_mv RAMOS, M. R. F. Análise comparativa dos métodos de avanço por Bulk e SSD na identificação de QTLs para produtividade de grão de arroz no cruzamento Epagri 108 X Irat 122. 2019. 145 f. Tese (Doutorado em Genética e Melhoramento de Plantas) - Universidade Federal de Goiás, Goiânia, 2019.
ark:/38995/0013000008zxm
url http://repositorio.bc.ufg.br/tede/handle/tede/10297
dc.language.iso.fl_str_mv por
language por
dc.relation.program.fl_str_mv -6265679607231828330
dc.relation.confidence.fl_str_mv 600
600
600
dc.relation.department.fl_str_mv -6046953723502374070
dc.relation.cnpq.fl_str_mv -7397920248419280716
dc.rights.driver.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Goiás
dc.publisher.program.fl_str_mv Programa de Pós-graduação em Genética e Melhoramento de Plantas (EA)
dc.publisher.initials.fl_str_mv UFG
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Escola de Agronomia - EA (RG)
publisher.none.fl_str_mv Universidade Federal de Goiás
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFG
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reponame_str Repositório Institucional da UFG
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