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Registro Completo |
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
08/12/2023 |
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Data da última atualização: |
08/12/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
OLIVEIRA, G. F.; NASCIMENTO, A. C. C.; AZEVEDO, C. F.; CELERI, M. de O.; BARROSO, L. M. A.; SANT’ANNA, I. de C.; VIANA, J. M. S.; RESENDE, M. D. V. de; NASCIMENTO, M. |
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Afiliação: |
GABRIELA FRANÇA OLIVEIRA, UNIVERSIDADE FEDERAL DE VIÇOSA; ANA CAROLINA CAMPANA NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA; CAMILA FERREIRA AZEVEDO, UNIVERSIDADE FEDERAL DE VIÇOSA; MAURÍCIO DE OLIVEIRA CELERI, UNIVERSIDADE FEDERAL DE VIÇOSA; LAÍS MAYARA AZEVEDO BARROSO, INSTITUTO FEDERAL DE EDUCAÇÃO, CIÊNCIA E TECNOLOGIA DE MATO GROSSO; ISABELA DE CASTRO SANT’ANNA, INSTITUTO AGRONÔMICO DE CAMPINAS; JOSÉ MARCELO SORIANO VIANA, UNIVERSIDADE FEDERAL DE VIÇOSA; MARCOS DEON VILELA DE RESENDE, CNPCa; MOYSÉS NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA. |
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Título: |
Population size in QTL detection using quantile regression in genome‑wide association studies. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Scientific Reports, v. 13, Article 9585, 2023. |
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Páginas: |
10 p. |
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DOI: |
https://doi.org/10.1038/s41598-023-36730-z |
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Idioma: |
Português |
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Conteúdo: |
The aim of this study was to evaluate the performance of Quantile Regression (QR) in Genome-Wide Association Studies (GWAS) regarding the ability to detect QTLs (Quantitative Trait Locus) associated with phenotypic traits of interest, considering different population sizes. For this, simulated data was used, with traits of different levels of heritability (0.30 and 0.50), and controlled by 3 and 100 QTLs. Populations of 1,000 to 200 individuals were defined, with a random reduction of 100 individuals for each population. The power of detection of QTLs and the false positive rate were obtained by means of QR considering three different quantiles (0.10, 0.50 and 0.90) and also by means of the General Linear Model (GLM). In general, it was observed that the QR models showed greater power of detection of QTLs in all scenarios evaluated and a relatively low false positive rate in scenarios with a greater number of individuals. The models with the highest detection power of true QTLs at the extreme quantils (0.10 and 0.90) were the ones with the highest detection power of true QTLs. In contrast, the analysis based on the GLM detected few (scenarios with larger population size) or no QTLs in the evaluated scenarios. In the scenarios with low heritability, QR obtained a high detection power. Thus, it was verified that the use of QR in GWAS is effective, allowing the detection of QTLs associated with traits of interest even in scenarios with few genotyped and phenotyped individuals. |
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Thesaurus Nal: |
Genome-wide association study; Phenotypic variation; Regression analysis. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1159390/1/Population-size-in-QTL-detection.pdf
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Marc: |
LEADER 02367naa a2200277 a 4500
001 2159390
005 2023-12-08
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1038/s41598-023-36730-z$2DOI
100 1 $aOLIVEIRA, G. F.
245 $aPopulation size in QTL detection using quantile regression in genome‑wide association studies.$h[electronic resource]
260 $c2023
300 $a10 p.
520 $aThe aim of this study was to evaluate the performance of Quantile Regression (QR) in Genome-Wide Association Studies (GWAS) regarding the ability to detect QTLs (Quantitative Trait Locus) associated with phenotypic traits of interest, considering different population sizes. For this, simulated data was used, with traits of different levels of heritability (0.30 and 0.50), and controlled by 3 and 100 QTLs. Populations of 1,000 to 200 individuals were defined, with a random reduction of 100 individuals for each population. The power of detection of QTLs and the false positive rate were obtained by means of QR considering three different quantiles (0.10, 0.50 and 0.90) and also by means of the General Linear Model (GLM). In general, it was observed that the QR models showed greater power of detection of QTLs in all scenarios evaluated and a relatively low false positive rate in scenarios with a greater number of individuals. The models with the highest detection power of true QTLs at the extreme quantils (0.10 and 0.90) were the ones with the highest detection power of true QTLs. In contrast, the analysis based on the GLM detected few (scenarios with larger population size) or no QTLs in the evaluated scenarios. In the scenarios with low heritability, QR obtained a high detection power. Thus, it was verified that the use of QR in GWAS is effective, allowing the detection of QTLs associated with traits of interest even in scenarios with few genotyped and phenotyped individuals.
650 $aGenome-wide association study
650 $aPhenotypic variation
650 $aRegression analysis
700 1 $aNASCIMENTO, A. C. C.
700 1 $aAZEVEDO, C. F.
700 1 $aCELERI, M. de O.
700 1 $aBARROSO, L. M. A.
700 1 $aSANT’ANNA, I. de C.
700 1 $aVIANA, J. M. S.
700 1 $aRESENDE, M. D. V. de
700 1 $aNASCIMENTO, M.
773 $tScientific Reports$gv. 13, Article 9585, 2023.
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Registro original: |
Embrapa Café (CNPCa) |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Meio Ambiente; Embrapa Meio-Norte. |
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Data corrente: |
08/01/2024 |
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Data da última atualização: |
26/01/2024 |
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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: |
COLMANETTI, M. A. A.; CUADRA, S. V.; LAMPARELLI, R. A. C.; CABRAL, O. M. R.; VICTORIA, D. de C.; MONTEIRO, J. E. B. de A.; FREITAS, H. C. de; GALDOS, M. V.; MARAFON, A. C.; ANDRADE JUNIOR, A. S. de; SILVA, S. D. dos A. e; BUFON, V. B.; HERNANDES, T. A. D.; MAIRE, G. LE. |
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Afiliação: |
MICHEL ANDERSON ALMEIDA COLMANETTI, UNIVERSITY OF CAMPINAS, SP; SANTIAGO VIANNA CUADRA, CNPTIA; RUBENS AUGUSTO CAMARGO LAMPARELLI, UNIVERSITY OF CAMPINAS, SP; OSVALDO MACHADO RODRIGUES CABRAL, CNPMA; DANIEL DE CASTRO VICTORIA, CNPTIA; JOSÉ EDUARDO BOFFINO DE ALMEIDA MONTEIRO, CNPTIA; HELBER CUSTODIO DE FREITAS, SÃO PAULO STATE UNIVERSITY, BAURU, SP; MARCELO VALADARES GALDOS, Sustainable Soils and Crops, Rothamsted Research, Harpenden AL5 2JQ, United Kingdom; ANDERSON CARLOS MARAFON, CPATC; ADERSON SOARES DE ANDRADE JUNIOR, CPAMN; SERGIO DELMAR DOS ANJOS E SILVA, CPACT; VINICIUS BOF BUFON, CPAC; THAYSE APARECIDA DOURADO HERNANDES, Brazilian Center for Research in Energy and Materials (CNPEM); GUERRIC LE MAIRE, CIRAD, UMR Eco&Sols, F-34398 Montpellier, France. |
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Título: |
Modeling sugarcane development and growth within ECOSMOS .biophysical model. |
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Ano de publicação: |
2024 |
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Fonte/Imprenta: |
European Journal of Agronomy, v. 154, 127061, 2024. |
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Idioma: |
Inglês |
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Conteúdo: |
Sugarcane plays an important role in electricity and sugar production and is a viable biofuel. Developing and optimizing a mechanism that can predict crop growth and yield at different spatiotemporal scales can promote the understanding of the effects of cultivation on the ecosystem, while providing options for optimizing management measures and improving the operational procedures of sugarcane growers. The main objective of this study is to integrate the sugarcane module into the ECOSystem MOdel Simulator (ECOSMOS) model and calibrate a parameter set for sugarcane genotypes groups (using different datasets); the model supports datasets that vary in complexity (from flux tower experiments to operational plots), while accounting for high genotype-byenvironment-by-management (GxExM) variability. |
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Palavras-Chave: |
ECOSMOS; ECOSystem MOdel Simulator; Modelagem baseada em processos; Process-based modeling. |
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Thesagro: |
Cana de Açúcar; Modelo de Simulação. |
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Thesaurus NAL: |
Sugarcane. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1160511/1/ModelingSugarcane.pdf
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Marc: |
LEADER 01878naa a2200361 a 4500
001 2160511
005 2024-01-26
008 2024 bl uuuu u00u1 u #d
100 1 $aCOLMANETTI, M. A. A.
245 $aModeling sugarcane development and growth within ECOSMOS .biophysical model.$h[electronic resource]
260 $c2024
520 $aSugarcane plays an important role in electricity and sugar production and is a viable biofuel. Developing and optimizing a mechanism that can predict crop growth and yield at different spatiotemporal scales can promote the understanding of the effects of cultivation on the ecosystem, while providing options for optimizing management measures and improving the operational procedures of sugarcane growers. The main objective of this study is to integrate the sugarcane module into the ECOSystem MOdel Simulator (ECOSMOS) model and calibrate a parameter set for sugarcane genotypes groups (using different datasets); the model supports datasets that vary in complexity (from flux tower experiments to operational plots), while accounting for high genotype-byenvironment-by-management (GxExM) variability.
650 $aSugarcane
650 $aCana de Açúcar
650 $aModelo de Simulação
653 $aECOSMOS
653 $aECOSystem MOdel Simulator
653 $aModelagem baseada em processos
653 $aProcess-based modeling
700 1 $aCUADRA, S. V.
700 1 $aLAMPARELLI, R. A. C.
700 1 $aCABRAL, O. M. R.
700 1 $aVICTORIA, D. de C.
700 1 $aMONTEIRO, J. E. B. de A.
700 1 $aFREITAS, H. C. de
700 1 $aGALDOS, M. V.
700 1 $aMARAFON, A. C.
700 1 $aANDRADE JUNIOR, A. S. de
700 1 $aSILVA, S. D. dos A. e
700 1 $aBUFON, V. B.
700 1 $aHERNANDES, T. A. D.
700 1 $aMAIRE, G. LE
773 $tEuropean Journal of Agronomy$gv. 154, 127061, 2024.
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Registro original: |
Embrapa Meio-Norte (CPAMN) |
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