Metabolite Profiles of Sugarcane Culm Reveal the Relationship Among Metabolism and Axillary Bud Outgrowth in Genetically Related Sugarcane Commercial Cultivars

Metabolic composition is known to exert influence on several important agronomic traits, and metabolomics, which represents the chemical composition in a cell, has long been recognized as a powerful tool for bridging phenotype–genotype interactions. In this work, sixteen truly representative sugarcane Brazilian varieties were selected to explore the metabolic networks in buds and culms, the tissues involved in the vegetative propagation of this species. Due to the fact that bud sprouting is a key trait determining crop establishment in the field, the sprouting potential among the genotypes was evaluated. The use of partial least square discriminant analysis indicated only mild differences on bud outgrowth potential under controlled environmental conditions. However, primary metabolite profiling provided information on the variability of metabolic features even under a narrow genetic background, typical for modern sugarcane cultivars. Metabolite–metabolite correlations within and between tissues revealed more complex patterns for culms in relation to buds, and enabled the recognition of key metabolites (e.g., sucrose, putrescine, glutamate, serine, and myo-inositol) affecting sprouting ability. Finally, those results were associated with the genetic background of each cultivar, showing that metabolites can be potentially used as indicators for the genetic background

Sugarcane (Saccharum X officinarum): A Reference Study for the Regulation of Genetically Modified Cultivars in Brazil

Global interest in sugarcane has increased significantly in recent years due to its economic impact on sustainable energy production. Sugarcane breeding and better agronomic practices have contributed to a huge increase in sugarcane yield in the last 30 years. Additional increases in sugarcane yield are expected to result from the use of biotechnology tools in the near future. Genetically modified (GM) sugarcane that incorporates genes to increase resistance to biotic and abiotic stresses could play a major role in achieving this goal. However, to bring GM sugarcane to the market, it is necessary to follow a regulatory process that will evaluate the environmental and health impacts of this crop. The regulatory review process is usually accomplished through a comparison of the biology and composition of the GM cultivar and a non-GM counterpart. This review intends to provide information on non-GM sugarcane biology, genetics, breeding, agronomic management, processing, products and byproducts, as well as the current technologies used to develop GM sugarcane, with the aim of assisting regulators in the decision-making process regarding the commercial release of GM sugarcane cultivars

Development of causal models with QTL information to the study of relationship among traits associated with phosphorus uptake in maize

Metodologias de mapeamento de QTLs modernas empregam abordagem multivariada e se beneficiam da matriz de covariâncias fenotípicas para melhorar as estimativas de localização e efeitos de QTLs. No entanto, a correlação fenotípica pode ser em parte atribuída às relações de causalidade entre os fenótipos e mesmo as abordagens de mapeamento de QTLs multivariadas atuais têm desconsiderado tais relacionamentos. Dentre as metodologias científicas desenvolvidas para o estudo da causalidade em dados observacionais, destacam-se os modelos de equações estruturais e os modelos gráficos. Neste trabalho, foi estudado um conjunto de caracteres fenotípicos relacionados à morfologia de raízes, absorção de fósforo e acúmulo de biomassa em uma população composta de 145 linhagens endogâmicas recombinantes (RILs) do programa de melhoramento de milho da EMBRAPA Milho e Sorgo. O mapeamento de QTLs para os caracteres fenotípicos foi realizado utilizando mapeamento de múltiplos intervalos univariado (MIM) e multivariado (MT-MIM). A análise MIM revelou QTLs afetando diâmetro de raízes, área de superfície de raízes finas, peso seco da parte aérea e concentração de fósforo na parte aérea e nas raízes. A análise MT-MIM revelou 12 QTLs, com diferentes padrões de pleiotropia, com efeitos marginais para as sete variáveis analisadas. Um modelo de relacionamento causal entre os caracteres fenotípicos foi desenvolvido utilizando conhecimento prévio e modelagem de equações estruturais. O modelo de equações estruturais apresentou fluxo unidirecional de causalidade entre as variáveis, com as variáveis de morfologia de raízes exercendo efeito sobre as variáveis de acúmulo de biomassa, que por sua vez, têm efeito sobre as variáveis de absorção de fósforo. A aplicação do algoritmo PC para a descoberta de causalidade automatizada baseada nos padrões de independências condicionais não foi capaz de orientar todas as relações de causalidade descobertas, porém revelou um relacionamento mais complexo que o modelo de equações estruturais, com potenciais ciclos de retroalimentação causais. O emprego de algoritmos de descoberta de causalidade baseados em informações de QTLs, chamados QDG e QPSO, permitiu a orientação de todos os relacionamentos de causalidade encontrados pelo algoritmo PC e confirmou a existência de dois ciclos vizinhos de relacionamento causais entre as variáveis estudadas. Como regra geral, os QTLs pleiotrópicos detectados pela metodologia MT-MIM apresentaram efeitos sobre caracteres fenotípicos alinhados causalmente nos modelos propostos pelos algoritmos PC e QDG, sugerindo que alguns dos QTLs detectados são na realidade efeitos indiretos de QTLs situados em posição mais elevada no modelo causal. O emprego da abordagem MT-MIM aliada à análise de causalidade permitiu melhor compreensão da arquitetura genética dos caracteres de morfologia de raiz, acumulação de biomassa e aquisição de fósforo em milho.Modern QTL mapping approaches are multivariate and take advantage of the phenotypic covariance matrix to improve estimates of QTL positions and effects. However, phenotypic correlation can also be assigned to the causal relationship among phenotypes, and even modern multivariate QTL analysis does not take these relationships into account. Structural equation models and graphical models are the main methodologies to study causality from observational data. We studied a set of phenotypes related to root morphology, biomass accumulation and phosphorus acquisition in maize. These phenotypes were measured in a maize population from the EMBRAPA breeding program composed of 145 recombinant inbred lines (RILs) derived from the crossing of two divergent lines for phosphorus acquisition efficiency. QTL mapping for the traits was performed using univariate (MIM) and multivariate (MT-MIM) multiple interval mapping. MIM analysis revealed QTL affecting root diameter, fine root surface area, shoot dry weight and root dry weight. MT-MIM analysis revealed 12 QTL with different pleiotropy patterns and QTL with marginal effects affecting all seven studied characters. A causal model for phenotype characters was developed using a priori knowledge and structural equation model techniques. The structural equation model presented an unidirectional causal flow among the variables, with root morphological traits exerting causal effects over biomass traits, which in turn cause phosphorus acquisition traits. Using PC algorithm for an automatic search of causal models based on conditional independence was not able to orient all discovered causal relationships among traits but revealed a more intricated relationship than the structural equation model, with potential causal feedback loops among the traits. Employing causal search algorithms based on QTL information (named QDG and QPSO) allowed the orientation of all causal relationships detected by PC algorithm and it has also confirmed the presence of two neighbor causal cycles among the studied traits. As a general rule, pleiotropic QTL detected by MT-MIM approach exerted effects over traits according to the causal model discovered by PC and QDG algorithms, suggesting that some of the QTL detected effects were indirect effects of QTL located upstream at the proposed causal model. Employing MT-MIM approach and causal analysis has allowed a better comprehension of genetic architecture underlying root morphology, biomass accumulation and phosphorus acquisition traits in maize

Lack of Detection of Bt Sugarcane Cry1Ab and NptII DNA and Proteins in Sugarcane Processing Products Including Raw Sugar

Brazil is the largest sugarcane producer and the main sugar exporter in the world. The industrial processes applied by Brazilian mills are very efficient in producing highly purified sugar and ethanol. Literature presents evidence of lack of DNA/protein in these products, regardless of the nature of sugarcane used as raw material. Recently CTNBio, the Brazilian biosafety authority, has approved the first biotechnology-derived sugarcane variety for cultivation, event CTC175-A, which expresses the Cry1Ab protein to control the sugarcane borer (Diatraea saccharalis). The event also expresses neomycin-phosphotransferase type II (NptII) protein used as selectable marker during the transformation process. Because of the high purity of sugar and ethanol produced from genetically modified sugarcane, these end-products should potentially be classified as “pure substances, chemically defined,” by Brazilian Biosafety Law No. 11.105. If this classification is to be adopted, these substances are not considered as “GMO derivatives” and fall out of the scope of Law No. 11.105. In order to assess sugar composition and quality, we evaluate Cry1Ab and NptII expression in several sugarcane tissues and in several fractions from laboratory-scale processing of event CTC175-A for the presence of these heterologous proteins as well as for the presence of traces of recombinant DNA. The results of these studies show that CTC175-A presents high expression of Cry1Ab in leaves and barely detectable expression of heterologous proteins in stalks. We also evaluated the presence of ribulose-1,5-bisphosphate carboxylase/oxygenase protein and DNA in the fractions of the industrial processing of conventional Brazilian sugarcane cultivars. Results from both laboratory and industrial processing were concordant, demonstrating that DNA and protein are not detected in the clarified juice and downstream processed fractions, including ethanol and raw sugar, indicating that protein and DNA are removed and/or degraded during processing. In conclusion, the processing of conventional sugarcane and CTC175-A Bt event results in downstream products with no detectable concentrations of heterologous DNA or new protein. These results help in the classification of sugar and ethanol derived from CTC175-A event as pure, chemically defined substances in Brazil and may relieve regulatory burdens in countries that import Brazilian sugar

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<p>Brazil is the largest sugarcane producer and the main sugar exporter in the world. The industrial processes applied by Brazilian mills are very efficient in producing highly purified sugar and ethanol. Literature presents evidence of lack of DNA/protein in these products, regardless of the nature of sugarcane used as raw material. Recently CTNBio, the Brazilian biosafety authority, has approved the first biotechnology-derived sugarcane variety for cultivation, event CTC175-A, which expresses the Cry1Ab protein to control the sugarcane borer (Diatraea saccharalis). The event also expresses neomycin-phosphotransferase type II (NptII) protein used as selectable marker during the transformation process. Because of the high purity of sugar and ethanol produced from genetically modified sugarcane, these end-products should potentially be classified as “pure substances, chemically defined,” by Brazilian Biosafety Law No. 11.105. If this classification is to be adopted, these substances are not considered as “GMO derivatives” and fall out of the scope of Law No. 11.105. In order to assess sugar composition and quality, we evaluate Cry1Ab and NptII expression in several sugarcane tissues and in several fractions from laboratory-scale processing of event CTC175-A for the presence of these heterologous proteins as well as for the presence of traces of recombinant DNA. The results of these studies show that CTC175-A presents high expression of Cry1Ab in leaves and barely detectable expression of heterologous proteins in stalks. We also evaluated the presence of ribulose-1,5-bisphosphate carboxylase/oxygenase protein and DNA in the fractions of the industrial processing of conventional Brazilian sugarcane cultivars. Results from both laboratory and industrial processing were concordant, demonstrating that DNA and protein are not detected in the clarified juice and downstream processed fractions, including ethanol and raw sugar, indicating that protein and DNA are removed and/or degraded during processing. In conclusion, the processing of conventional sugarcane and CTC175-A Bt event results in downstream products with no detectable concentrations of heterologous DNA or new protein. These results help in the classification of sugar and ethanol derived from CTC175-A event as pure, chemically defined substances in Brazil and may relieve regulatory burdens in countries that import Brazilian sugar.</p

Image_2_Metabolite Profiles of Sugarcane Culm Reveal the Relationship Among Metabolism and Axillary Bud Outgrowth in Genetically Related Sugarcane Commercial Cultivars.JPEG

<p>Metabolic composition is known to exert influence on several important agronomic traits, and metabolomics, which represents the chemical composition in a cell, has long been recognized as a powerful tool for bridging phenotype–genotype interactions. In this work, sixteen truly representative sugarcane Brazilian varieties were selected to explore the metabolic networks in buds and culms, the tissues involved in the vegetative propagation of this species. Due to the fact that bud sprouting is a key trait determining crop establishment in the field, the sprouting potential among the genotypes was evaluated. The use of partial least square discriminant analysis indicated only mild differences on bud outgrowth potential under controlled environmental conditions. However, primary metabolite profiling provided information on the variability of metabolic features even under a narrow genetic background, typical for modern sugarcane cultivars. Metabolite–metabolite correlations within and between tissues revealed more complex patterns for culms in relation to buds, and enabled the recognition of key metabolites (e.g., sucrose, putrescine, glutamate, serine, and myo-inositol) affecting sprouting ability. Finally, those results were associated with the genetic background of each cultivar, showing that metabolites can be potentially used as indicators for the genetic background.</p

Table_3_Metabolite Profiles of Sugarcane Culm Reveal the Relationship Among Metabolism and Axillary Bud Outgrowth in Genetically Related Sugarcane Commercial Cultivars.XLSX

<p>Metabolic composition is known to exert influence on several important agronomic traits, and metabolomics, which represents the chemical composition in a cell, has long been recognized as a powerful tool for bridging phenotype–genotype interactions. In this work, sixteen truly representative sugarcane Brazilian varieties were selected to explore the metabolic networks in buds and culms, the tissues involved in the vegetative propagation of this species. Due to the fact that bud sprouting is a key trait determining crop establishment in the field, the sprouting potential among the genotypes was evaluated. The use of partial least square discriminant analysis indicated only mild differences on bud outgrowth potential under controlled environmental conditions. However, primary metabolite profiling provided information on the variability of metabolic features even under a narrow genetic background, typical for modern sugarcane cultivars. Metabolite–metabolite correlations within and between tissues revealed more complex patterns for culms in relation to buds, and enabled the recognition of key metabolites (e.g., sucrose, putrescine, glutamate, serine, and myo-inositol) affecting sprouting ability. Finally, those results were associated with the genetic background of each cultivar, showing that metabolites can be potentially used as indicators for the genetic background.</p