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| Registros recuperados : 137 | |
| 7. |  | OTENIO, M. H.; LEITAO, R. C.; GAMBETTA, R.; KUNZ, A. ODS 7 como ferramenta para aprimorar o alcance da população aos serviços de energia. In: KUNZ, A.; OTENIO, M. H.; LEITAO, R. C.; GAMBETTA, R. (ed.). Energia limpa e acessível: contribuições da Embrapa. Brasília, DF: Embrapa, 2018. E-book. (Objetivos de Desenvolvimento Sustentável, 7). p. 76-79.| Biblioteca(s): Embrapa Agroenergia; Embrapa Agroindústria Tropical; Embrapa Gado de Leite. |
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| 8. | | OTENIO, M. H.; LEITAO, R. C.; GAMBETTA, R.; KUNZ, A. ODS 7 como ferramenta para aprimorar o alcance da população aos serviços de energia. In: KUNZ, A.; OTENIO, M. H.; LEITAO, R. C.; GAMBETTA, R. (Ed.). Energia limpa e acessível: contribuições da Embrapa. Brasília, DF: Embrapa, 2018 E-book. (Objetivos de Desenvolvimento Sustentável, 7). p. 76-79.| Biblioteca(s): Embrapa Suínos e Aves. |
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| 14. | | GAMBETTA, R.; LEITÃO, R. C.; OTENIO, M. H.; KUNZ, A. Compromissos nacionalmente assumidos e a participação da Embrapa. In: KUNZ, A.; OTENIO, M. H.; LEITAO, R. C.; GAMBETTA, R. (Ed.). Energia limpa e acessível: contribuições da Embrapa. Brasília, DF: Embrapa, 2018 E-book. (Objetivos de Desenvolvimento Sustentável, 7). p. 11-16.| Biblioteca(s): Embrapa Agroenergia; Embrapa Agroindústria Tropical; Embrapa Gado de Leite. |
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| 15. | | GAMBETTA, R.; LEITAO, R. C.; OTENIO, M. H.; KUNZ, A. Compromissos nacionalmente assumidos e a participação da Embrapa. In: KUNZ, A.; OTENIO, M. H.; LEITAO, R. C.; GAMBETTA, R. (Ed.). Energia limpa e acessível: contribuições da Embrapa. Brasília, DF: Embrapa, 2018 E-book. (Objetivos de Desenvolvimento Sustentável, 7). p. 14-23.| Biblioteca(s): Embrapa Suínos e Aves. |
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| 17. | | GAMBETTA, R.; LEITAO, R. C.; OTENIO, M. H.; KUNZ, A. National commitments and participation of Embrapa. In: KUNZ, A.; OTENIO, M. H.; LEITAO, R. C.; GAMBETTA, R. (Ed.). Affordable and clean energy: contributions of Embrapa. Brasília, DF: Embrapa, 2020. p. 11-32 PDF: il. color. (Sustainable development goal, 7).| Biblioteca(s): Embrapa Agroenergia; Embrapa Agroindústria Tropical; Embrapa Gado de Leite; Embrapa Suínos e Aves. |
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| 19. | | GAMBETTA, R.; LEITÃO, R. C.; OTENIO, M. H.; KUNZ, A. Quais os entraves à universalização do acesso às fontes de energia no Brasil? In: KUNZ, A.; OTENIO, M. H.; LEITAO, R. C.; GAMBETTA, R. (Ed.). Energia limpa e acessível: contribuições da Embrapa. Brasília, DF: Embrapa, 2018 E-book. (Objetivos de Desenvolvimento Sustentável, 7). p. 17-21.| Biblioteca(s): Embrapa Agroenergia; Embrapa Agroindústria Tropical; Embrapa Gado de Leite. |
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| 20. | | GAMBETTA, R.; LEITAO, R. C.; OTENIO, M. H.; KUNZ, A. Quais os entraves à universalização do acesso às fontes de energia no Brasil? In: KUNZ, A.; OTENIO, M. H.; LEITAO, R. C.; GAMBETTA, R. (Ed.). Energia limpa e acessível: contribuições da Embrapa. Brasília, DF: Embrapa, 2018 E-book. (Objetivos de Desenvolvimento Sustentável, 7). p. 24-31.| Biblioteca(s): Embrapa Suínos e Aves. |
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| Registros recuperados : 137 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Roraima. Para informações adicionais entre em contato com cpafrr.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Roraima. |
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Data corrente: |
15/09/2021 |
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Data da última atualização: |
15/09/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
McMANUS, C.; PAIVA, S. R.; CAETANO, A. R.; HERMUCHE, P.; GUIMARÃES, R. F.; CARVALHO JUNIOR, O. A.; BRAGA, R. M.; CARNEIRO, P. L. S.; MORAES, J. C. F.; SOUZA, C. J. H. de; FACO, O.; SANTOS, S. A.; AZEVEDO, H. C.; ARAUJO, A. M. de; FAÇANHA, D. A. E.; IANELLA, P. |
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Afiliação: |
CONCEPTA MCMANUS, Universidade de Brasília (UnB) - Brasília, DF, Brazil; SAMUEL REZENDE PAIVA, Cenargen; ALEXANDRE RODRIGUES CAETANO, Cenargen; POTIRA HERMUCHE, Universidade de Brasília (UnB) - Brasília, DF, Brazil; RENATO FONTES GUIMARÃES, Universidade de Brasília (UnB) - Brasília, DF, Brazil; OSMAR ABILIO CARVALHO JUNIOR, Universidade de Brasília (UnB) - Brasília, DF, Brazil; RAMAYANA MENEZES BRAGA, CPAF-RR; PAULO LUIZ SOUZA CARNEIRO, Universidade Estadual Do Sudoeste da Bahia (UESB) - Vitória da Conquista - BA, Brazil; JOSE CARLOS FERRUGEM MORAES, CPPSUL; CARLOS JOSE HOFF DE SOUZA; OLIVARDO FACO, CNPC; SANDRA APARECIDA SANTOS; HYMERSON COSTA AZEVEDO, CPATC; ADRIANA MELLO DE ARAUJO, CPAMN; DEBORA ANDRÉA E. FAÇANHA, Federal Rural University of the Semi-arid Region (UFERSA) - Mossoró, RN, Brazil; PATRICIA IANELLA, Cenargen. |
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Título: |
Landscape genetics of sheep in Brazil using SNP markers. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Small Ruminant Research, v. 192, e106239, 2020. |
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DOI: |
https://doi.org/10.1016/j.smallrumres.2020.106239 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: The aim of this study was to explore spatial patterns of genetic structure in sheep breeds sampled in Brazil using Single Nucleotide Polymorphisms (SNPs) in order to evaluate whether or not the genetic and geographic dis-tances are interrelated in this species. Samples genotyped using the 50KSheepSNPChip (Illumina) included 215 animals from eight different sheep breeds. All collection sites were georeferenced and data analyzed to determine geographic patterns from genetic data. To evaluate the correlation between genetic and geographic distances Mantel tests, Allelic Aggregation Index Analyses (AAIA), and spatial autocorrelation were performed. Genetic Landscape Shape procedure and Monmonier?s Algorithm were used to generate graphical visualization of the genetic distances across the landscape. The observed correlation observed between genetic and geographical distances was 0.552 (P <0.00099). Observed AAIA results (Rave =0.16, P <0.001) indicated a non-random distribution of genotypes across the landscape. High genetic differentiation was observed in the Southern re-gions of Brazil, separating wool and hair sheep. Low genetic distances were observed between flocks and breeds from north and center-west regions, and may be the result of unrecorded introgressions resulting from past unknown crossbreeding events. Observed Spatial Autocorrelation Analyses results indicate a minimum distance of 400 km should be used between collection sites to maximize genetic variability in future germplasm samplings for conservation of genetic resources. MenosAbstract: The aim of this study was to explore spatial patterns of genetic structure in sheep breeds sampled in Brazil using Single Nucleotide Polymorphisms (SNPs) in order to evaluate whether or not the genetic and geographic dis-tances are interrelated in this species. Samples genotyped using the 50KSheepSNPChip (Illumina) included 215 animals from eight different sheep breeds. All collection sites were georeferenced and data analyzed to determine geographic patterns from genetic data. To evaluate the correlation between genetic and geographic distances Mantel tests, Allelic Aggregation Index Analyses (AAIA), and spatial autocorrelation were performed. Genetic Landscape Shape procedure and Monmonier?s Algorithm were used to generate graphical visualization of the genetic distances across the landscape. The observed correlation observed between genetic and geographical distances was 0.552 (P <0.00099). Observed AAIA results (Rave =0.16, P <0.001) indicated a non-random distribution of genotypes across the landscape. High genetic differentiation was observed in the Southern re-gions of Brazil, separating wool and hair sheep. Low genetic distances were observed between flocks and breeds from north and center-west regions, and may be the result of unrecorded introgressions resulting from past unknown crossbreeding events. Observed Spatial Autocorrelation Analyses results indicate a minimum distance of 400 km should be used between collection sites to maximize genetic variabili... Mostrar Tudo |
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Palavras-Chave: |
Delaunay triangulation; Genetic landscape shape; Mantel. |
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Thesaurus NAL: |
Brazil; Genetic polymorphism; Germplasm conservation; Sampling; Sheep; Sheep breeds; Single nucleotide polymorphism. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 02793naa a2200433 a 4500
001 2134431
005 2021-09-15
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.smallrumres.2020.106239$2DOI
100 1 $aMcMANUS, C.
245 $aLandscape genetics of sheep in Brazil using SNP markers.$h[electronic resource]
260 $c2020
520 $aAbstract: The aim of this study was to explore spatial patterns of genetic structure in sheep breeds sampled in Brazil using Single Nucleotide Polymorphisms (SNPs) in order to evaluate whether or not the genetic and geographic dis-tances are interrelated in this species. Samples genotyped using the 50KSheepSNPChip (Illumina) included 215 animals from eight different sheep breeds. All collection sites were georeferenced and data analyzed to determine geographic patterns from genetic data. To evaluate the correlation between genetic and geographic distances Mantel tests, Allelic Aggregation Index Analyses (AAIA), and spatial autocorrelation were performed. Genetic Landscape Shape procedure and Monmonier?s Algorithm were used to generate graphical visualization of the genetic distances across the landscape. The observed correlation observed between genetic and geographical distances was 0.552 (P <0.00099). Observed AAIA results (Rave =0.16, P <0.001) indicated a non-random distribution of genotypes across the landscape. High genetic differentiation was observed in the Southern re-gions of Brazil, separating wool and hair sheep. Low genetic distances were observed between flocks and breeds from north and center-west regions, and may be the result of unrecorded introgressions resulting from past unknown crossbreeding events. Observed Spatial Autocorrelation Analyses results indicate a minimum distance of 400 km should be used between collection sites to maximize genetic variability in future germplasm samplings for conservation of genetic resources.
650 $aBrazil
650 $aGenetic polymorphism
650 $aGermplasm conservation
650 $aSampling
650 $aSheep
650 $aSheep breeds
650 $aSingle nucleotide polymorphism
653 $aDelaunay triangulation
653 $aGenetic landscape shape
653 $aMantel
700 1 $aPAIVA, S. R.
700 1 $aCAETANO, A. R.
700 1 $aHERMUCHE, P.
700 1 $aGUIMARÃES, R. F.
700 1 $aCARVALHO JUNIOR, O. A.
700 1 $aBRAGA, R. M.
700 1 $aCARNEIRO, P. L. S.
700 1 $aMORAES, J. C. F.
700 1 $aSOUZA, C. J. H. de
700 1 $aFACO, O.
700 1 $aSANTOS, S. A.
700 1 $aAZEVEDO, H. C.
700 1 $aARAUJO, A. M. de
700 1 $aFAÇANHA, D. A. E.
700 1 $aIANELLA, P.
773 $tSmall Ruminant Research$gv. 192, e106239, 2020.
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