Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico
| Ano de defesa: | 2023 |
|---|---|
| Autor(a) principal: | |
| Orientador(a): | |
| Banca de defesa: | |
| Tipo de documento: | Dissertação |
| Tipo de acesso: | Acesso aberto |
| Idioma: | por |
| Instituição de defesa: |
Não Informado pela instituição
|
| Programa de Pós-Graduação: |
Não Informado pela instituição
|
| Departamento: |
Não Informado pela instituição
|
| País: |
Não Informado pela instituição
|
| Área do conhecimento CNPq: | |
| Link de acesso: | http://repositorio.ufc.br/handle/riufc/74678 |
Resumo: | Abiotic stresses cause a huge negative impact on agricultural production, mainly the water deficit. An efficient way to understand the effects of stress on genotypes is through reaction norms. Reaction norm is a regression that shows the possible phenotypes that a given genotype can express under different environmental conditions. As it is a regression, the reaction norm can be decomposed into linear (intercept) and angular (slope) coefficients. These components, obtained as a function of an environmental gradient, provide information on the average performance over the planned environments and the responsibility for environmental improvement. Therefore, average performance is associated with the predictability/stability of a genotype against an environmental gradient and, thus, related to tolerance, while responsiveness is linked to phenotypic plasticity, that is, responsiveness to environmental increments. Thus, the use of this information (components of the reaction norms) instead of the use of raw phenotypic data in the performance of genetic association studies (GWAS), should make it possible to know genomic regions that are more influenced by environmental variables in terms of average performance and responsiveness to water stress. To test this hypothesis, a public genetic diversity panel consisting of 360 tropical maize lines was used, evaluated in eight environments, four under conditions of ideal water supply (WW) and four under conditions of water stress (WS). The root systems of the lines were phenotyped via image capture and processing using the RhizoVision Explorer® software, as well as shoot characters such as plant height, stem diameter, SPAD index and dry mass. At first, analyzes of phenotypic data were performed to extract adjusted means (BLUEs) via mixed linear model adjustment. Subsequently, reaction norms were obtained by genotype-by-genotype regression, considering the BLUEs of each strain in each environment as a response variable and the gradient with information on the environmental variable water supply as a predictor variable. The values of each strain referring to the components of reaction norms, intercept and slope were extracted. Thus, with this information, association analyzes (GWAS) were performed for each character. Afterwards, the candidate genes were annotated, with their potential effects and physiological relationships with water deficit tolerance via the MaizeGDB database. Significant SNPs were identified in practically all maize karyotypes, with the exception of chromosomes 6 and 7 in slope analysis and in chromosome 2 for intercept and slope. The SNPs that appeared in both conditions for more than one trait suggest the occurrence of a pleiotropic effect, as is the case of the Zm00001d048702 gene. A total of 25 significant SNPs were identified, these being for all characters evaluated in WW and WS. Of these, 15 SNPs for average performance, 15 for responsiveness and 5 common to both components (intercept and slope). The genes and/or genomic regions identified here reveal physiological responses and direct or indirect molecular mechanisms related to water deficit tolerance. This information will make it possible to carry out more assertive selections and subsidize breeding programs that aim to implement genomic selection, genomic editing (such as CRISPR) or genotyping technologies such as KASPTM (Kompetitive allele specific PCR) that aim to obtain cultivars intended for water stress conditions with cost reduction in the evaluation process |
| id |
UFC-7_487a61a4d67cdc0129aba50b2bea9c97 |
|---|---|
| oai_identifier_str |
oai:repositorio.ufc.br:riufc/74678 |
| network_acronym_str |
UFC-7 |
| network_name_str |
Repositório Institucional da Universidade Federal do Ceará (UFC) |
| repository_id_str |
|
| spelling |
Lobo, Antonio Lucas AguiarFritsche-Neto, RobertoSilva, Júlio César do Vale2023-10-17T17:15:28Z2023-10-17T17:15:28Z2023LOBO, Antonio Lucas Aguiar. Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico. 51 f. Dissertação (Mestrado em Agronomia/Fitotecnia) - Universidade Federal do Ceará, Fortaleza, 2023.http://repositorio.ufc.br/handle/riufc/74678Abiotic stresses cause a huge negative impact on agricultural production, mainly the water deficit. An efficient way to understand the effects of stress on genotypes is through reaction norms. Reaction norm is a regression that shows the possible phenotypes that a given genotype can express under different environmental conditions. As it is a regression, the reaction norm can be decomposed into linear (intercept) and angular (slope) coefficients. These components, obtained as a function of an environmental gradient, provide information on the average performance over the planned environments and the responsibility for environmental improvement. Therefore, average performance is associated with the predictability/stability of a genotype against an environmental gradient and, thus, related to tolerance, while responsiveness is linked to phenotypic plasticity, that is, responsiveness to environmental increments. Thus, the use of this information (components of the reaction norms) instead of the use of raw phenotypic data in the performance of genetic association studies (GWAS), should make it possible to know genomic regions that are more influenced by environmental variables in terms of average performance and responsiveness to water stress. To test this hypothesis, a public genetic diversity panel consisting of 360 tropical maize lines was used, evaluated in eight environments, four under conditions of ideal water supply (WW) and four under conditions of water stress (WS). The root systems of the lines were phenotyped via image capture and processing using the RhizoVision Explorer® software, as well as shoot characters such as plant height, stem diameter, SPAD index and dry mass. At first, analyzes of phenotypic data were performed to extract adjusted means (BLUEs) via mixed linear model adjustment. Subsequently, reaction norms were obtained by genotype-by-genotype regression, considering the BLUEs of each strain in each environment as a response variable and the gradient with information on the environmental variable water supply as a predictor variable. The values of each strain referring to the components of reaction norms, intercept and slope were extracted. Thus, with this information, association analyzes (GWAS) were performed for each character. Afterwards, the candidate genes were annotated, with their potential effects and physiological relationships with water deficit tolerance via the MaizeGDB database. Significant SNPs were identified in practically all maize karyotypes, with the exception of chromosomes 6 and 7 in slope analysis and in chromosome 2 for intercept and slope. The SNPs that appeared in both conditions for more than one trait suggest the occurrence of a pleiotropic effect, as is the case of the Zm00001d048702 gene. A total of 25 significant SNPs were identified, these being for all characters evaluated in WW and WS. Of these, 15 SNPs for average performance, 15 for responsiveness and 5 common to both components (intercept and slope). The genes and/or genomic regions identified here reveal physiological responses and direct or indirect molecular mechanisms related to water deficit tolerance. This information will make it possible to carry out more assertive selections and subsidize breeding programs that aim to implement genomic selection, genomic editing (such as CRISPR) or genotyping technologies such as KASPTM (Kompetitive allele specific PCR) that aim to obtain cultivars intended for water stress conditions with cost reduction in the evaluation processOs estresses abióticos causam enorme impacto negativo sobre a produção agrícola, principalmente o déficit hídrico. Uma forma eficiente de se entender os efeitos do estresse nos genótipos é por meio de norma de reação. Norma de reação é uma regressão que mostra os possíveis fenótipos que um dado genótipo pode expressar em diferentes condições ambientais. Por ser uma regressão, a norma de reação pode ser decomposta em coeficientes linear (intercepto) e angular (slope). Esses componentes obtidos em função de um gradiente ambiental, dá informação acerca do desempenho base ao longo dos ambientes estudados e a responsividade frente a melhoria ambiental. Portanto, o desempenho base está associado à previsibilidade/estabilidade de um genótipo perante um gradiente ambiental e, dessa forma, relacionado a tolerância, enquanto que a responsividade está ligada à plasticidade fenotípica, isto é, capacidade de resposta frente aos incrementos ambientais. Assim, o uso dessas informações (componentes das normas de reação) ao invés do emprego de dados fenotípicos brutos na realização de estudos de genética associação (GWAS), deve possibilitar conhecer regiões genômicas que são mais influenciadas por variáveis ambientais quanto ao desempenho base e responsividade ao estresse hídrico. Para testar essa hipótese, foi usado um painel público de diversidade genética constituído por 360 linhagens de milho tropical, avaliado em oito ambientes, sendo quatro em condições de suprimento ideal de água (WW) e quatro em condições de estresse hídrico (WS). Foram fenotipados os sistemas radiculares das linhagens via captura e processamento de imagens usando o software RhizoVision Explorer® bem como caracteres da parte aérea como altura de planta, diâmetro do colmo, índice SPAD e massa seca. A princípio, foram realizadas análises dos dados fenotípicos para extração de médias ajustadas (BLUEs) via ajuste de modelo linear misto. Posteriormente, obtidas normas de reação por regressões genótipo a genótipo, considerando os BLUEs de cada linhagem em cada ambiente como variável resposta e o gradiente com as informações da variável ambiental suprimento de água como variável preditora. Foram extraídos os valores de cada linhagem referente aos componentes de normas de reação, intercepto e slope. Assim, com essas informações foram realizadas análises de associação (GWAS) para cada caráter. Depois foi feita a anotação dos genes candidatos, com seus potenciais efeitos e relações fisiológicas com a tolerância ao déficit hídrico via banco de dados MaizeGDB. Foram identificados SNPs significativos em praticamente todo o cariótipo do milho, com exceção dos cromossomos 6 e 7 nas análises de slope e no cromossomo 2 para intercepto e slope. Os SNPs que apareceram em ambas as condições para mais de um caráter, sugerem a ocorrência de efeito pleiotrópico, como é o caso do gene Zm00001d048702. Ao total foam identificados 25 SNPs significativos, sendo estes, para todos os caracteres avaliados em WW e WS. Destes, 15 SNPs para o desempenho base, 15 para responsividade e 5 comuns a ambas os componentes (intercepto e slope). Além disso, eles explicam no intercepto para cada caráter 40% (PH), 57% (SD), 67% (SPAD), 40% (LRL), 44% (LRA) e para slope explicam 62% (PH), 67% (SD), 30% (SPAD), 61% (LRL), 43% (LRA). Os genes e/ou regiões genômicas identificadas aqui revelam respostas fisiológicas e mecanismos moleculares diretos ou indiretos relacionados à tolerância ao déficit hídrico. Essas informações possibilitarão realizar seleções mais assertivas e subsidiar programas de melhoramento que visam implementar seleção genômica, edição genômica (como CRISPR) ou tecnologias de genotipagem como é o caso da KASPTM (Kompetitive allele specific PCR) que visam obtenção de cultivares destinados a condição de estresse hídrico com redução de custos ao processo de avaliação.Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídricoAssociation mapping for components of reaction norms to environmental covariates in a public panel of tropical maize under water deficitinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisEstresse abióticoGWASTolerância à secaResponsividadeEficiência no uso da águaResponsivenessDrought stressAbiotic stressGWASDrought toleranceEfficiency in the use of waterCNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIAinfo:eu-repo/semantics/openAccessporreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFChttps://orcid.org/0000-0001-5629-5221http://lattes.cnpq.br/7974539442320599https://orcid.org/0000-0002-3497-9793http://lattes.cnpq.br/7549117961923408https://orcid.org/0000-0003-4310-0047http://lattes.cnpq.br/58304814803289102023-10-17LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.ufc.br/bitstream/riufc/74678/6/license.txt8a4605be74aa9ea9d79846c1fba20a33MD56ORIGINAL2023_dis_alalobo.pdf2023_dis_alalobo.pdfapplication/pdf2280132http://repositorio.ufc.br/bitstream/riufc/74678/7/2023_dis_alalobo.pdf7d8f1e8149cfa31ee672951e619f97e9MD57riufc/746782023-10-17 14:17:35.723oai:repositorio.ufc.br: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Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2023-10-17T17:17:35Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false |
| dc.title.pt_BR.fl_str_mv |
Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico |
| dc.title.en.pt_BR.fl_str_mv |
Association mapping for components of reaction norms to environmental covariates in a public panel of tropical maize under water deficit |
| title |
Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico |
| spellingShingle |
Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico Lobo, Antonio Lucas Aguiar CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIA Estresse abiótico GWAS Tolerância à seca Responsividade Eficiência no uso da água Responsiveness Drought stress Abiotic stress GWAS Drought tolerance Efficiency in the use of water |
| title_short |
Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico |
| title_full |
Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico |
| title_fullStr |
Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico |
| title_full_unstemmed |
Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico |
| title_sort |
Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico |
| author |
Lobo, Antonio Lucas Aguiar |
| author_facet |
Lobo, Antonio Lucas Aguiar |
| author_role |
author |
| dc.contributor.co-advisor.none.fl_str_mv |
Fritsche-Neto, Roberto |
| dc.contributor.author.fl_str_mv |
Lobo, Antonio Lucas Aguiar |
| dc.contributor.advisor1.fl_str_mv |
Silva, Júlio César do Vale |
| contributor_str_mv |
Silva, Júlio César do Vale |
| dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIA |
| topic |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIA Estresse abiótico GWAS Tolerância à seca Responsividade Eficiência no uso da água Responsiveness Drought stress Abiotic stress GWAS Drought tolerance Efficiency in the use of water |
| dc.subject.ptbr.pt_BR.fl_str_mv |
Estresse abiótico GWAS Tolerância à seca Responsividade Eficiência no uso da água Responsiveness |
| dc.subject.en.pt_BR.fl_str_mv |
Drought stress Abiotic stress GWAS Drought tolerance Efficiency in the use of water |
| description |
Abiotic stresses cause a huge negative impact on agricultural production, mainly the water deficit. An efficient way to understand the effects of stress on genotypes is through reaction norms. Reaction norm is a regression that shows the possible phenotypes that a given genotype can express under different environmental conditions. As it is a regression, the reaction norm can be decomposed into linear (intercept) and angular (slope) coefficients. These components, obtained as a function of an environmental gradient, provide information on the average performance over the planned environments and the responsibility for environmental improvement. Therefore, average performance is associated with the predictability/stability of a genotype against an environmental gradient and, thus, related to tolerance, while responsiveness is linked to phenotypic plasticity, that is, responsiveness to environmental increments. Thus, the use of this information (components of the reaction norms) instead of the use of raw phenotypic data in the performance of genetic association studies (GWAS), should make it possible to know genomic regions that are more influenced by environmental variables in terms of average performance and responsiveness to water stress. To test this hypothesis, a public genetic diversity panel consisting of 360 tropical maize lines was used, evaluated in eight environments, four under conditions of ideal water supply (WW) and four under conditions of water stress (WS). The root systems of the lines were phenotyped via image capture and processing using the RhizoVision Explorer® software, as well as shoot characters such as plant height, stem diameter, SPAD index and dry mass. At first, analyzes of phenotypic data were performed to extract adjusted means (BLUEs) via mixed linear model adjustment. Subsequently, reaction norms were obtained by genotype-by-genotype regression, considering the BLUEs of each strain in each environment as a response variable and the gradient with information on the environmental variable water supply as a predictor variable. The values of each strain referring to the components of reaction norms, intercept and slope were extracted. Thus, with this information, association analyzes (GWAS) were performed for each character. Afterwards, the candidate genes were annotated, with their potential effects and physiological relationships with water deficit tolerance via the MaizeGDB database. Significant SNPs were identified in practically all maize karyotypes, with the exception of chromosomes 6 and 7 in slope analysis and in chromosome 2 for intercept and slope. The SNPs that appeared in both conditions for more than one trait suggest the occurrence of a pleiotropic effect, as is the case of the Zm00001d048702 gene. A total of 25 significant SNPs were identified, these being for all characters evaluated in WW and WS. Of these, 15 SNPs for average performance, 15 for responsiveness and 5 common to both components (intercept and slope). The genes and/or genomic regions identified here reveal physiological responses and direct or indirect molecular mechanisms related to water deficit tolerance. This information will make it possible to carry out more assertive selections and subsidize breeding programs that aim to implement genomic selection, genomic editing (such as CRISPR) or genotyping technologies such as KASPTM (Kompetitive allele specific PCR) that aim to obtain cultivars intended for water stress conditions with cost reduction in the evaluation process |
| publishDate |
2023 |
| dc.date.accessioned.fl_str_mv |
2023-10-17T17:15:28Z |
| dc.date.available.fl_str_mv |
2023-10-17T17:15:28Z |
| dc.date.issued.fl_str_mv |
2023 |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| format |
masterThesis |
| status_str |
publishedVersion |
| dc.identifier.citation.fl_str_mv |
LOBO, Antonio Lucas Aguiar. Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico. 51 f. Dissertação (Mestrado em Agronomia/Fitotecnia) - Universidade Federal do Ceará, Fortaleza, 2023. |
| dc.identifier.uri.fl_str_mv |
http://repositorio.ufc.br/handle/riufc/74678 |
| identifier_str_mv |
LOBO, Antonio Lucas Aguiar. Mapeamento de associação para componentes de normas de reação à covariáveis ambientais em painel público de milho tropical sob déficit hídrico. 51 f. Dissertação (Mestrado em Agronomia/Fitotecnia) - Universidade Federal do Ceará, Fortaleza, 2023. |
| url |
http://repositorio.ufc.br/handle/riufc/74678 |
| dc.language.iso.fl_str_mv |
por |
| language |
por |
| dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.source.none.fl_str_mv |
reponame:Repositório Institucional da Universidade Federal do Ceará (UFC) instname:Universidade Federal do Ceará (UFC) instacron:UFC |
| instname_str |
Universidade Federal do Ceará (UFC) |
| instacron_str |
UFC |
| institution |
UFC |
| reponame_str |
Repositório Institucional da Universidade Federal do Ceará (UFC) |
| collection |
Repositório Institucional da Universidade Federal do Ceará (UFC) |
| bitstream.url.fl_str_mv |
http://repositorio.ufc.br/bitstream/riufc/74678/6/license.txt http://repositorio.ufc.br/bitstream/riufc/74678/7/2023_dis_alalobo.pdf |
| bitstream.checksum.fl_str_mv |
8a4605be74aa9ea9d79846c1fba20a33 7d8f1e8149cfa31ee672951e619f97e9 |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
| repository.name.fl_str_mv |
Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC) |
| repository.mail.fl_str_mv |
bu@ufc.br || repositorio@ufc.br |
| _version_ |
1847793350699122688 |