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Registro Completo |
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Biblioteca(s): |
Embrapa Mandioca e Fruticultura. |
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Data corrente: |
11/11/2015 |
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Data da última atualização: |
18/05/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
OLIVEIRA, G. A. F.; DANTAS, J. L. L.; OLIVEIRA, E. J. de. |
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Afiliação: |
G. A. F. OLIVEIRA, UFRB; JORGE LUIZ LOYOLA DANTAS, CNPMF; EDER JORGE DE OLIVEIRA, CNPMF. |
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Título: |
Development and validation of minisatellite markers for Carica papaya. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
Biologia Plantarum, v. 59, n.4, p 686-694, 2015. |
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DOI: |
10.1007/s10535-015-0551-9686 |
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Idioma: |
Inglês |
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Conteúdo: |
Whereas microsatellite markers are well described, there are few studies investigating minisatellites. Therefore, this study aimed to identify, characterize, and validate minisatellite loci for papaya (Carica papaya L.). The entire papaya genome, which covers 330 Mb, was used to mine minisatellites with motifs ranging from 6 to 500 bp, and at least six replicates and 82 loci were validated in a set of 24 accessions. A total of 1 730 minisatellite loci were identified, located in 695 sequences, with an average of one minisatellite every 156 kb. Variation in GC content ranged from 0.00 to 83.84 % with an average of 28.84 % indicating that these papaya minisatellites are AT rich. Motifs of up to 20 bases represented 71.45 % of the markers. In addition, the observed variation in the number of motif repeats was from 6 to 186 with an average of 9.27 per minisatellite. Independent of the classification, the frequency of minisatellites decreased with an increase in the number of repeating units. Among the validated loci, 48.78 % were found to be polymorphic, and the number of alleles (NA) ranged from two to seven with a mean of 3.10. The average polymorphic information content (PIC), expected heterozygosity (He), and observed heterozygosity (Ho) were 0.38, 0.43, and 0.11, respectively. According to genetic diversity parameters, such as NA, He, and PIC, no significant correlations were found among the size of motifs, the number of repeats, and the GC content of these minisatellites. This study clearly demonstrates the polymorphism of minisatellites and their potential use in detection of intraspecific genetic variations in C. papaya. The results will be useful when managing genetic resources and plant breeding. MenosWhereas microsatellite markers are well described, there are few studies investigating minisatellites. Therefore, this study aimed to identify, characterize, and validate minisatellite loci for papaya (Carica papaya L.). The entire papaya genome, which covers 330 Mb, was used to mine minisatellites with motifs ranging from 6 to 500 bp, and at least six replicates and 82 loci were validated in a set of 24 accessions. A total of 1 730 minisatellite loci were identified, located in 695 sequences, with an average of one minisatellite every 156 kb. Variation in GC content ranged from 0.00 to 83.84 % with an average of 28.84 % indicating that these papaya minisatellites are AT rich. Motifs of up to 20 bases represented 71.45 % of the markers. In addition, the observed variation in the number of motif repeats was from 6 to 186 with an average of 9.27 per minisatellite. Independent of the classification, the frequency of minisatellites decreased with an increase in the number of repeating units. Among the validated loci, 48.78 % were found to be polymorphic, and the number of alleles (NA) ranged from two to seven with a mean of 3.10. The average polymorphic information content (PIC), expected heterozygosity (He), and observed heterozygosity (Ho) were 0.38, 0.43, and 0.11, respectively. According to genetic diversity parameters, such as NA, He, and PIC, no significant correlations were found among the size of motifs, the number of repeats, and the GC content of these minisatellites. ... Mostrar Tudo |
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Thesagro: |
Carica Papaya; Mamão; Variação genética. |
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Thesaurus Nal: |
Genetic variation. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 02343naa a2200205 a 4500
001 2028333
005 2023-05-18
008 2015 bl uuuu u00u1 u #d
024 7 $a10.1007/s10535-015-0551-9686$2DOI
100 1 $aOLIVEIRA, G. A. F.
245 $aDevelopment and validation of minisatellite markers for Carica papaya.$h[electronic resource]
260 $c2015
520 $aWhereas microsatellite markers are well described, there are few studies investigating minisatellites. Therefore, this study aimed to identify, characterize, and validate minisatellite loci for papaya (Carica papaya L.). The entire papaya genome, which covers 330 Mb, was used to mine minisatellites with motifs ranging from 6 to 500 bp, and at least six replicates and 82 loci were validated in a set of 24 accessions. A total of 1 730 minisatellite loci were identified, located in 695 sequences, with an average of one minisatellite every 156 kb. Variation in GC content ranged from 0.00 to 83.84 % with an average of 28.84 % indicating that these papaya minisatellites are AT rich. Motifs of up to 20 bases represented 71.45 % of the markers. In addition, the observed variation in the number of motif repeats was from 6 to 186 with an average of 9.27 per minisatellite. Independent of the classification, the frequency of minisatellites decreased with an increase in the number of repeating units. Among the validated loci, 48.78 % were found to be polymorphic, and the number of alleles (NA) ranged from two to seven with a mean of 3.10. The average polymorphic information content (PIC), expected heterozygosity (He), and observed heterozygosity (Ho) were 0.38, 0.43, and 0.11, respectively. According to genetic diversity parameters, such as NA, He, and PIC, no significant correlations were found among the size of motifs, the number of repeats, and the GC content of these minisatellites. This study clearly demonstrates the polymorphism of minisatellites and their potential use in detection of intraspecific genetic variations in C. papaya. The results will be useful when managing genetic resources and plant breeding.
650 $aGenetic variation
650 $aCarica Papaya
650 $aMamão
650 $aVariação genética
700 1 $aDANTAS, J. L. L.
700 1 $aOLIVEIRA, E. J. de
773 $tBiologia Plantarum$gv. 59, n.4, p 686-694, 2015.
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Registro original: |
Embrapa Mandioca e Fruticultura (CNPMF) |
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
10/02/2010 |
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Data da última atualização: |
09/07/2010 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
Internacional - A |
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Autoria: |
GOMES, E. G.; MELLO, J. C. C. B. S. de; MEZA, L. A. |
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Afiliação: |
Eliane Gonçalves Gomes, Embrapa-SGE; João Carlos Correia Baptista Soares de Mello, Universidade Federal Fluminense; Lidia Angulo Meza, Universidade Federal Fluminense. |
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Título: |
Large discreet resource allocation: a hybrid approach based on DEA efficiency measurement. |
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Ano de publicação: |
2008 |
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Fonte/Imprenta: |
Pesquisa Operacional, v.28, n.3, p. 597-608, set./dez. 2008. |
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Idioma: |
Inglês |
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Conteúdo: |
Resource allocation is one of the traditional Operations Research problems. In this paper we propose a hybrid model for resource allocation that uses Data Envelopment Analysis efficiency measures. We use Zero Sum Gains DEA models as the starting point to decrease the computational work for the step-bystep algorithm to allocate integer resources in a DEA context. Our approach is illustrated by a numerical example. |
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Palavras-Chave: |
Step-by-step allocation; Zero sum gains. |
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Thesaurus NAL: |
resource allocation. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/17468/1/Large-discreet-resources-allocation.pdf
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Marc: |
LEADER 00988naa a2200181 a 4500
001 1657623
005 2010-07-09
008 2008 bl uuuu u00u1 u #d
100 1 $aGOMES, E. G.
245 $aLarge discreet resource allocation$ba hybrid approach based on DEA efficiency measurement.$h[electronic resource]
260 $c2008
520 $aResource allocation is one of the traditional Operations Research problems. In this paper we propose a hybrid model for resource allocation that uses Data Envelopment Analysis efficiency measures. We use Zero Sum Gains DEA models as the starting point to decrease the computational work for the step-bystep algorithm to allocate integer resources in a DEA context. Our approach is illustrated by a numerical example.
650 $aresource allocation
653 $aStep-by-step allocation
653 $aZero sum gains
700 1 $aMELLO, J. C. C. B. S. de
700 1 $aMEZA, L. A.
773 $tPesquisa Operacional$gv.28, n.3, p. 597-608, set./dez. 2008.
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