| |
|
|
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Arroz e Feijão. |
|
Data corrente: |
29/05/2022 |
|
Data da última atualização: |
12/04/2024 |
|
Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
|
Autoria: |
CROSSA, J.; MONTESINOS-LÓPEZ, O. A.; PÉREZ-RODRÍGUEZ, P.; COSTA-NETO, G.; FRITSCHE-NETO, R.; ORTIZ, R.; MARTINI, J. W. R.; LILLEMO, M.; MONTESINOS-LÓPEZ, A.; JARQUIN, D.; BRESEGHELLO, F.; CUEVAS, J.; RINCENT, R. |
|
Afiliação: |
JOSE CROSSA, CIMMYT; OSVAL ANTONIO MONTESINOS-LOPEZ, UNIVERSIDAD DE COLIMA, México; PAULINO PEREZ-RODRIGUEZ, COLEGIO DE POSTGRADUADOS, Montecillos-Mexico; GERMANO COSTA-NETO, ESALQ; ROBERTO FRITSCHE-NETO, ESALQ; RODOMIRO ORTIZ, SWEDISH UNIVERSITY OF AGRICULTURAL SCIENCES, Alnarp-Sweden; JOHANNES W. R. MARTINI, CIMMYT; MORTEN LILLEMO, NORWEGIAN UNIVERSITY OF LIFE SCIENCES, Norway; ABELARDO MONTESINOS-LOPEZ, CENTRO DE INVESTIGACIÓN EN MATEMÁTICAS, Guanajuato-Mexico; DIEGO JARQUIN, UNIVERSITY OF NEBRASKA, Lincoln-NE; FLAVIO BRESEGHELLO, CNPAF; JAIME CUEVAS, UNIVERSIDAD DE QUINTANA ROO, Quintana Roo-Mexico; RENAUD RINCENT, INRAE, Clermont-Ferrand-France. |
|
Título: |
Genome and environment based prediction models and methods of complex traits incorporating genotype × environment interaction. |
|
Ano de publicação: |
2022 |
|
Fonte/Imprenta: |
In: AHMADI, N.; BARTHOLOME, J. (ed.). Genomic prediction of complex traits: methods and protocols. New York: Humana Press, 2022. |
|
Páginas: |
p. 245-283. |
|
Série: |
(Methods in Molecular Biology). |
|
ISBN: |
978-1-0716-2205-6 |
|
DOI: |
https://doi.org/10.1007/978-1-0716-2205-6_9 |
|
Idioma: |
Inglês |
|
Conteúdo: |
Genomic-enabled prediction models are of paramount importance for the successful implementation of genomic selection (GS) based on breeding values. As opposed to animal breeding, plant breeding includes extensive multienvironment and multiyear field trial data. Hence, genomic-enabled prediction models should include genotype × environment (G × E) interaction, which most of the time increases the prediction performance when the response of lines are different from environment to environment. In this chapter, we describe a historical timeline since 2012 related to advances of the GS models that take into account G × E interaction. We describe theoretical and practical aspects of those GS models, including the gains in prediction performance when including G × E structures for both complex continuous and categorical scale traits. Then, we detailed and explained the main G × E genomic prediction models for complex traits measured in continuous and noncontinuous (categorical) scale. Related to G × E interaction models this review also examine the analyses of the information generated with high-throughput phenotype data (phenomic) and the joint analyses of multitrait and multienvironment field trial data that is also employed in the general assessment of multitrait G × E interaction. The inclusion of nongenomic data in increasing the accuracy and biological reliability of the G × E approach is also outlined. We show the recent advances in large-scale envirotyping (enviromics), and how the use of mechanistic computational modeling can derive the crop growth and development aspects useful for predicting phenotypes and explaining G × E. MenosGenomic-enabled prediction models are of paramount importance for the successful implementation of genomic selection (GS) based on breeding values. As opposed to animal breeding, plant breeding includes extensive multienvironment and multiyear field trial data. Hence, genomic-enabled prediction models should include genotype × environment (G × E) interaction, which most of the time increases the prediction performance when the response of lines are different from environment to environment. In this chapter, we describe a historical timeline since 2012 related to advances of the GS models that take into account G × E interaction. We describe theoretical and practical aspects of those GS models, including the gains in prediction performance when including G × E structures for both complex continuous and categorical scale traits. Then, we detailed and explained the main G × E genomic prediction models for complex traits measured in continuous and noncontinuous (categorical) scale. Related to G × E interaction models this review also examine the analyses of the information generated with high-throughput phenotype data (phenomic) and the joint analyses of multitrait and multienvironment field trial data that is also employed in the general assessment of multitrait G × E interaction. The inclusion of nongenomic data in increasing the accuracy and biological reliability of the G × E approach is also outlined. We show the recent advances in large-scale envirotyping (enviromics), and... Mostrar Tudo |
|
Palavras-Chave: |
Genome-enabled prediction; Genomic selection; Models with G x E interaction. |
|
Thesagro: |
Genótipo; Interação Genética; Melhoramento Genético Vegetal. |
|
Thesaurus Nal: |
Genome; Genomics; Genotype-environment interaction; Plant breeding. |
|
Categoria do assunto: |
G Melhoramento Genético |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1143533/1/cap9-2022.pdf
|
|
Marc: |
LEADER 03084naa a2200433 a 4500
001 2143533
005 2024-04-12
008 2022 bl uuuu u00u1 u #d
020 $a978-1-0716-2205-6
024 7 $ahttps://doi.org/10.1007/978-1-0716-2205-6_9$2DOI
100 1 $aCROSSA, J.
245 $aGenome and environment based prediction models and methods of complex traits incorporating genotype × environment interaction.$h[electronic resource]
260 $c2022
300 $ap. 245-283.
490 $a(Methods in Molecular Biology).
520 $aGenomic-enabled prediction models are of paramount importance for the successful implementation of genomic selection (GS) based on breeding values. As opposed to animal breeding, plant breeding includes extensive multienvironment and multiyear field trial data. Hence, genomic-enabled prediction models should include genotype × environment (G × E) interaction, which most of the time increases the prediction performance when the response of lines are different from environment to environment. In this chapter, we describe a historical timeline since 2012 related to advances of the GS models that take into account G × E interaction. We describe theoretical and practical aspects of those GS models, including the gains in prediction performance when including G × E structures for both complex continuous and categorical scale traits. Then, we detailed and explained the main G × E genomic prediction models for complex traits measured in continuous and noncontinuous (categorical) scale. Related to G × E interaction models this review also examine the analyses of the information generated with high-throughput phenotype data (phenomic) and the joint analyses of multitrait and multienvironment field trial data that is also employed in the general assessment of multitrait G × E interaction. The inclusion of nongenomic data in increasing the accuracy and biological reliability of the G × E approach is also outlined. We show the recent advances in large-scale envirotyping (enviromics), and how the use of mechanistic computational modeling can derive the crop growth and development aspects useful for predicting phenotypes and explaining G × E.
650 $aGenome
650 $aGenomics
650 $aGenotype-environment interaction
650 $aPlant breeding
650 $aGenótipo
650 $aInteração Genética
650 $aMelhoramento Genético Vegetal
653 $aGenome-enabled prediction
653 $aGenomic selection
653 $aModels with G x E interaction
700 1 $aMONTESINOS-LÓPEZ, O. A.
700 1 $aPÉREZ-RODRÍGUEZ, P.
700 1 $aCOSTA-NETO, G.
700 1 $aFRITSCHE-NETO, R.
700 1 $aORTIZ, R.
700 1 $aMARTINI, J. W. R.
700 1 $aLILLEMO, M.
700 1 $aMONTESINOS-LÓPEZ, A.
700 1 $aJARQUIN, D.
700 1 $aBRESEGHELLO, F.
700 1 $aCUEVAS, J.
700 1 $aRINCENT, R.
773 $tIn: AHMADI, N.; BARTHOLOME, J. (ed.). Genomic prediction of complex traits: methods and protocols. New York: Humana Press, 2022.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
 | Acesso ao texto completo restrito à biblioteca da Embrapa Soja. Para informações adicionais entre em contato com valeria.cardoso@embrapa.br. |
Registro Completo
|
Biblioteca(s): |
Embrapa Soja. |
|
Data corrente: |
15/09/2014 |
|
Data da última atualização: |
05/04/2022 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Circulação/Nível: |
A - 1 |
|
Autoria: |
REIS, R. R.; CUNHA, B. A. D. B. da; MARTINS, P. K.; MARTINS, M. T. B.; ALEKCEVETCH, J. C.; CHALFUN-JÚNIOR, A.; ANDRADE, A. C.; RIBEIRO, A. P.; QIN, F.; MIZOI, J.; YAMAGUCHI-SHINOZAKI, K.; NAKASHIMA, K.; CARVALHO, J. de F. C.; SOUSA, C. A. F. de; NEPOMUCENO, A. L.; KOBAYASHI, A. K.; MOLINARI, H. B. C. |
|
Afiliação: |
RAFAELA RIBEIRO REIS, UNIVERSIDADE FEDERAL DE LAVRAS - UFLA; BARBARA ANDRADE DIAS BRITO DA CUNHA, CNPAE; POLYANA KELLY MARTINS; MARIA THEREZA BAZZO MARTINS; JEAN CARLOS ALEKCEVETCH, UNIVERSIDADE FEDERAL DE LAVRAS - UFLA; ANTÔNIO CHALFUN-JUNIOR, UNIVERSIDADE FEDERAL DE LAVRAS - UFLA; ALAN CARVALHO ANDRADE, CENARGEN; ANA PAULA RIBEIRO, UNIVERSIDADE FEDERAL DE LAVRAS - UFLA; FENG QIN, JIRCAS; JUNYA MIZOI, University of Tokyo; KAZUKO YAMAGUCHI-SHINOZAKI., University of Tokyo; KAZUO NAKASHIMA, JIRCAS; JOSIRLEY DE FÁTIMA CORRÊA CARVALHO; CARLOS ANTONIO FERREIRA DE SOUSA, CNPAE; ALEXANDRE LIMA NEPOMUCENO, SRI; ADILSON KENJI KOBAYASHI, CNPAE; HUGO BRUNO CORREA MOLINARI, CNPAE. |
|
Título: |
Induced over-expression of AtDREB2A CA improves drought tolerance in sugarcane. |
|
Ano de publicação: |
2014 |
|
Fonte/Imprenta: |
Plant Science, Limerick, v. 221-222, p. 59-68, May, 2014. |
|
Idioma: |
Português |
|
Conteúdo: |
Drought is one of the most challenging agricultural issues limiting sustainable sugarcane production and, in some cases, yield losses caused by drought are nearly 50%. DREB proteins play vital regulatory roles in abiotic stress responses in plants. The transcription factor DREB2A interacts with a cis-acting DRE sequence to activate the expression of downstream genes that are involved in drought-, salt- and heat-stress response in Arabidopsis thaliana. In the present study, we evaluated the effects of stress-inducible over-expression of AtDREB2A CA on gene expression, leaf water potential ( L), relative water content (RWC), sucrose content and gas exchanges of sugarcane plants submitted to a four-days water deficit treatment in a rhizotron-grown root system. The plants were also phenotyped by scanning the roots and measuring morphological parameters of the shoot. The stress-inducible expression of AtDREB2A CA in transgenic sugarcane led to the up-regulation of genes involved in plant response to drought stress. The transgenic plants maintained higher RWC and L over 4 days after withholding water and had higher photosynthetic rates until the 3rd day of water-deficit. Induced expression of AtDREB2A CA in sugarcane increased sucrose levels and improved bud sprouting of the transgenic plants. Our results indicate that induced expression of AtDREB2A CA in sugarcane enhanced its drought tolerance without biomass penalty. |
|
Palavras-Chave: |
AtDREB2A CA; Transcription factor. |
|
Thesaurus NAL: |
abiotic stress. |
|
Categoria do assunto: |
-- |
|
Marc: |
LEADER 02478naa a2200349 a 4500
001 1994957
005 2022-04-05
008 2014 bl uuuu u00u1 u #d
100 1 $aREIS, R. R.
245 $aInduced over-expression of AtDREB2A CA improves drought tolerance in sugarcane.$h[electronic resource]
260 $c2014
520 $aDrought is one of the most challenging agricultural issues limiting sustainable sugarcane production and, in some cases, yield losses caused by drought are nearly 50%. DREB proteins play vital regulatory roles in abiotic stress responses in plants. The transcription factor DREB2A interacts with a cis-acting DRE sequence to activate the expression of downstream genes that are involved in drought-, salt- and heat-stress response in Arabidopsis thaliana. In the present study, we evaluated the effects of stress-inducible over-expression of AtDREB2A CA on gene expression, leaf water potential ( L), relative water content (RWC), sucrose content and gas exchanges of sugarcane plants submitted to a four-days water deficit treatment in a rhizotron-grown root system. The plants were also phenotyped by scanning the roots and measuring morphological parameters of the shoot. The stress-inducible expression of AtDREB2A CA in transgenic sugarcane led to the up-regulation of genes involved in plant response to drought stress. The transgenic plants maintained higher RWC and L over 4 days after withholding water and had higher photosynthetic rates until the 3rd day of water-deficit. Induced expression of AtDREB2A CA in sugarcane increased sucrose levels and improved bud sprouting of the transgenic plants. Our results indicate that induced expression of AtDREB2A CA in sugarcane enhanced its drought tolerance without biomass penalty.
650 $aabiotic stress
653 $aAtDREB2A CA
653 $aTranscription factor
700 1 $aCUNHA, B. A. D. B. da
700 1 $aMARTINS, P. K.
700 1 $aMARTINS, M. T. B.
700 1 $aALEKCEVETCH, J. C.
700 1 $aCHALFUN-JÚNIOR, A.
700 1 $aANDRADE, A. C.
700 1 $aRIBEIRO, A. P.
700 1 $aQIN, F.
700 1 $aMIZOI, J.
700 1 $aYAMAGUCHI-SHINOZAKI, K.
700 1 $aNAKASHIMA, K.
700 1 $aCARVALHO, J. de F. C.
700 1 $aSOUSA, C. A. F. de
700 1 $aNEPOMUCENO, A. L.
700 1 $aKOBAYASHI, A. K.
700 1 $aMOLINARI, H. B. C.
773 $tPlant Science, Limerick$gv. 221-222, p. 59-68, May, 2014.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Soja (CNPSO) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
