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| 12. |  | CHOUGULE, K, M.; OLSON, A.; MAGALHAES, J. V. de; VAN BUREN, P.; WANG, L.; WARE, D. Assessing new tools and best practices for RNA seq data analysis and visualization with iPlant cyberinfrastructure. In: MEETING ON GENOMIC INFORMATICS, 2015, New York. Abstracts of papers. New York: Cold Spring Harbor Laboratory, 2015. p. 64.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 13. | | WANG, L. H.; GALEHOUSE, D.; MELLON, P.; DUESBERG, P.; MASON, W. S.; VOGT, P. K. Mapping oligonucleotides of Rous sarcoma virus RNA that segregate with polymerase and group-specific antigen markers in recombinants. Proceedings National Academy Science, USA, v.73, n.11, p.3952-3956, Nov. 1976.| Biblioteca(s): Embrapa Pantanal. |
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| 15. | | DONG, F. M.; WANG, L. L.; WANG, C. M.; CHENG, J. P.; HE, Z. Q.; SHENG, Z. J.; SHEN, R. Q. Molecular cloning and mapping of phenol degradation genes from Bacillus stearothermophilus FDTP-3 and their expression in Escherichia coli. Appl. Environ. Microbiol., v.58, n.8, p.2531-2535, 1992.| Biblioteca(s): Embrapa Agrobiologia. |
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| 16. | | WANG, L. Z.; YIN, G. C.; LUO, J. F.; LEI, B. J.; WANG, J. A.; YAO, Z. C.; LI, X. L.; SHAO, Q. Q.; JIANG, X. C.; ZHOU, Z. Q. T-DNA transfer in soybean. In: SYMPOSIUM [ON] SOYBEAN IN TROPICAL AND SUBTROPICAL CROPPING SYSTEMS, 1983, Tsukuba. Proceedings... Shanhua: AVRDC, 1985. p.165-168. Editado por S. Shanmugasundaram, E.W. Sulzberger.| Biblioteca(s): Embrapa Soja. |
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| 17. | | LOPES, F. R.; JJINGO, D.; SILVA C. R. M. da; ANDRADE, A. C.; MARRACCINI, P.; TEIXEIRA, J. B.; CARAZZOLLE, M. F.; PEREIRA, G. A. G.; PEREIRA, L. F. P.; VANZELA, A. L. L.; WANG, L.; JORDAN, I. K.; CARARETO, C. M. A. Transcriptional activity, chromosomal distribution and expression effects of transposable elements in Coffea genomes. Plos One, v, 8, n. 11, e78931, 2013.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 18. | | KRASILNIKOV, P.; FONTANA, A.; LANDI, A.; MERMUT, A. R.; LABAZ, B.; SMRECZAK, B.; PINHEIRO, C. R.; VAN HUYSSTEEN, C. W.; MONGER, C.; OLIVEIRA, F. P. de; MORRAS, H. J. M.; HUSEIN, H. H.; IVELIC-SÁEZ, J.; PERALTA, K.; WANG, L.; ANJOS, L. H. C. dos; SANTOS, L. A. C. dos; PFEIFFER, M.; PEREIRA, M. G.; BOLANOS-BENAVIDES, M. M.; TABOADA, M. A.; CAMPOS, M. C. C.; DALMOLIN, R. S. D.; OROZAKUNOVA, R.; USTINOV, S.; RADIC, S.; VALLE, S.; KUYPER, T. W.; CHERLINKA, V.; DEMETRIO, W.; CARDONA, W. A.; ZHANG, Y.; DMYTRUK, Y.; TAKATA, Y. Status and challenges of black soils. In: FAO. Global status of black soils. Rome, 2022. cap. 3, p. 71-105.| Biblioteca(s): Embrapa Solos. |
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| 19. | | MAES, P.; AMARASINGHE, G. K.; AYLLÓN, M. A.; BASLER, C. F.; SINA, B.; BLASDELL, K. R.; BRIESE, T.; BROWN, P. A.; BUKREYEV, A.; BALKEMA-BUSCHMANN, A.; BUCHHOLZ, U. J.; CHANDRAN, K.; CROZIER, I.; SWART, R. de; DIETZGEN, R. G.; DOLNIK, O.; DOMIER, L. L.; DREXLER, J. F.; DÜRRWALD, R.; DUNDON, W. G.; DUPREX, W. P.; DYE, J. M.; EASTON, A. J.; FOOKS, A. R.; FORMENTY, P. B. H.; FOUCHIER, R. A. M.; ASTUA, J. de F.; GHEDIN, E.; GRIFFITHS, A.; HEWSON, R.; HORIE, M.; HURWITZ, J. L.; HYNDMAN, T. H.; JIANG, D.; KOBINGER, G. P.; KONDO, H.; KURATH, G.; KUZMIN, I. V.; LAMB, R. T A.; LEE, B.; LEROY, E. M.; LI, J.; MARZANO, S. L.; MUHLBERGER, E.; NETESOV, S.; NETESOV, S. V.; PALACIOS, G.; PÁLYI, B.; PAWESKA, J. T.; PAYNE, S. L.; RIMA, B. K.; ROTA, P.; RUBBENSTROTH, D.; SIMMONDS, P.; SMITHER, S. J.; SONG, Q.; SONG, T.; SPANN, K.; STENGLEIN, M. D.; STONE, D. M.; TAKADA, A.; TESH, R. T B.; TOMONAGA, K.; TORDO, N.; TOWNER, J. S.; VAN DEN HOOGEN, B.; VASILAKIS, N.; WAHL, V.; WALKER, P. J.; WANG, D.; WANG, L.-F.; WHITFIELD, A. E.; WILLIAMS, J. V.; YE, G.; ZERBINI, F. M.; ZHANG, Y.-Z.; KUHN, J. H. Taxonomy of the order Mononegavirales: second update 2018. Archives of Virology, p.1-12, 2019.| Biblioteca(s): Embrapa Mandioca e Fruticultura. |
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| 20. | | AMARASINGHE, G. K.; AYLLÓN, M. A.; BÀO, Y.; BASLER, C. F.; BAVARI, S.; BLASDELL, K. R.; BRIESE, T.; BROWN, P. A.; BUKREYEV, A.; BUSCHMANN, A. B.; BUCHHOLZ, U. J.; JESUS, C. C.; CHANDRAN, K.; CHIAPPONI, C.; CROZIER, I.; SWART, R. L. de; DIETZGEN, R. G.; DOLNIK, O.; DREXLER, J. F.; DÜRRWALD, R.; DUNDON, W. G.; DUPREX, W. P.; DYE, J. M.; EASTON, A. J.; FOOKS, A. R.; FORMENTY, P. B. H; FOUCHIER, R. A. M; ASTUA, J. de F.; GRIFFITHS, A.; HEWSON, R.; HORIE, M.; HYNDMAN, T. H.; JIÃNG, D.; KITAJIMA, E. W.; KOBINGER. G. P.; KONDÕ, H.; KURATH, G.; KUZMIN, I. V.; LAMB, R. A.; LAVAZZA, A.; LEE, B.; LELLI, D.; LEROY, E. M.; LI, J.; MAES, P.; MARZANO, S. L.; MORENO, A.; MÜHLBERGER, E.; NETESOV, S. V.; NOWOTNY, N.; NYLUND, A.; ØKLAND, A. L.; PALACIOS, G.; Pályi, B.; PAW?SKA, J. T.; PAYNE, S. L.; PROSPERI, A.; GONZALEZ, P. L. R.; RIMA, B. K.; ROTA, P.; RUBBENSTROTH, D.; SH?, M.; SIMMONDS, P.; SMITHER, S. J.; SOZZI, E.; SPANN, K.; STENGLEIN, M. D.; STONE, D. M.; TAKADA, A.; TESH, R. B.; TOMONAGA, K.; TORDO, N.; TOWNER, J. S.; HOOGEN, B. V. D.; VASILAKIS, N.; WAHL, V.; WALKER, P. J.; WANG, L.; WHITFIELD, A. E.; WILLIAMS, J. V.; ZERBINI, F. M.; ZH?NG, T.; ZHANG, Y. Z.; KUHN, J. H. Taxonomy of the order Mononegavirales: update 2019. Archives of Virology, v.164, p.1967-1980, 2019.| Biblioteca(s): Embrapa Mandioca e Fruticultura. |
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| Registros recuperados : 22 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
14/07/2017 |
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Data da última atualização: |
03/01/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
GOIS, I. B.; BORÉM, A.; CRISTOFANI-YALY, M.; RESENDE, M. D. V. de; AZEVEDO, C. F.; BASTIANEL, M.; NOVELLI, V. M.; MACHADO, M. A. |
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Afiliação: |
I. B. Gois, Departamento de Fitotecnia, Universidade Federal de Viçosa; A. Borém, Departamento de Fitotecnia, Universidade Federal de Viçosa; M. Cristofani-Yaly, Instituto Agronômico de Campinas, Centro APTA Citros Sylvio Moreira; MARCOS DEON VILELA DE RESENDE, CNPF; C. F. Azevedo, Departamento de Estatística, Universidade Federal de Viçosa; M. Bastianel, Instituto Agronômico de Campinas, Centro APTA Citros Sylvio Moreira; V. M. Novelli, Instituto Agronômico de Campinas, Centro APTA Citros Sylvio Moreira; M. A. Machado, Instituto Agronômico de Campinas, Centro APTA Citros Sylvio Moreira. |
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Título: |
Genome wide selection in citrus breeding. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Genetics and Molecular Research, v. 15, n. 4, gmr15048863, Oct. 2016. |
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DOI: |
http://dx.doi.org/10.4238/gmr15048863 |
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Idioma: |
Inglês |
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Conteúdo: |
Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seqTM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus. MenosGenome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seqTM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citr... Mostrar Tudo |
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Palavras-Chave: |
DarT_seq; Molecular markers; Seleção precoce; Selective accuracy. |
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Thesagro: |
Fruta cítrica; Marcador Molecular; Melhoramento vegetal. |
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Thesaurus NAL: |
Citrus; early selection; linkage disequilibrium; Plant breeding. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/161818/1/2016-M.Deon-GMR-Genome.pdf
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Marc: |
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008 2016 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.4238/gmr15048863$2DOI
100 1 $aGOIS, I. B.
245 $aGenome wide selection in citrus breeding.$h[electronic resource]
260 $c2016
520 $aGenome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seqTM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.
650 $aCitrus
650 $aearly selection
650 $alinkage disequilibrium
650 $aPlant breeding
650 $aFruta cítrica
650 $aMarcador Molecular
650 $aMelhoramento vegetal
653 $aDarT_seq
653 $aMolecular markers
653 $aSeleção precoce
653 $aSelective accuracy
700 1 $aBORÉM, A.
700 1 $aCRISTOFANI-YALY, M.
700 1 $aRESENDE, M. D. V. de
700 1 $aAZEVEDO, C. F.
700 1 $aBASTIANEL, M.
700 1 $aNOVELLI, V. M.
700 1 $aMACHADO, M. A.
773 $tGenetics and Molecular Research$gv. 15, n. 4, gmr15048863, Oct. 2016.
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