Characterization of the superoxide dismutase gene family in seeds of two Ricinus communis L. genotypes submitted to germination under water restriction conditions

Neto, Valdir Gomes; Ribeiro, Paulo R.; Del-Bem, Luiz-Eduardo; Bernal, Daniele Takahashi; Lima, Sergio Monteiro; Ligterink, Wilco; Fernandez, Luzimar Gonzaga; Castro, Renato Delmondez de

doi:10.1016/j.envexpbot.2018.08.001

Cited by 21 publications

(11 citation statements)

References 65 publications

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“…With the selected models (Table 4), it is possible to estimate the germination times of interest to the researcher, using the formulas presented in (8), (9) and (10). The average germination time or time required for 50% of the seeds used in the germination experiments (T50) is considered to be the preferred one to describe the germination and physiological quality of the seeds submitted to different treatments or to compare different batches of seeds [7][8][9]11,14].…”

Section: Cornmentioning

confidence: 99%

“…The germination times of 10 and 90% of the seeds have also been calculated [14,37] to evaluate the physiological quality of seeds. However, the two most widespread statistics for evaluating the germination of a seed lot are the T50 and germination uniformities [7,10,37].…”

Section: Cornmentioning

confidence: 99%

“…As a result, the germination test is performed to determine the final germination percentage of the seed lots. However, the time for 50% of the seeds to germinate (T50) and the germination uniformity, which is the time difference between two percentage germinations and other defined parameters [7][8][9][10], complement the germination data and can indicate the performance of seeds in the field.…”

Section: Introductionmentioning

confidence: 99%

“…To assess which seed lot has superior physiological quality, the response variable (percentage of germinated seeds) is commonly assessed by non-linear regressions, such as the Hill function [7,10,11]. Another way used to analyze the germination data is through linearization, in which a link function is used, highlighting the Probit function as the most used [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

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The Use of the Generalized Linear Model to Assess the Speed and Uniformity of Germination of Corn and Soybean Seeds

et al. 2021

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The use of seeds with high physiological quality allows rapid growth and establishment of seedlings in the field to be obtained. Therefore, the accuracy of the information obtained during the determination of the physiological quality of seeds is of great importance. The objective was to use generalized linear models, investigating which link function (Probit, Logit and Complementary log-log) is suitable to predict T50 and uniformity during germination of soybean and corn seeds. To perform the experiments, we used seeds from five commercial hybrids and/or cultivars of corn and soybean. The germination speed was calculated by counting the germinated seeds and the results were expressed in the form of proportions. Germination uniformity was calculated by the difference in the times required for germination. The best model was selected according to the criteria of the test of Deviance, AIC and BIC. The Logit model showed accurate results for most cultivars. The evaluation of germination in the form of proportions considering the assumption of binomial response is satisfactory, and the choice of the link function is dependent on the characteristics of each lot and/or species evaluated. The use of this methodology makes it possible to estimate any germination time and uniformity.

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Section: Cornmentioning

confidence: 99%

Section: Cornmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Use of the Generalized Linear Model to Assess the Speed and Uniformity of Germination of Corn and Soybean Seeds

et al. 2021

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“…Total RNA was extracted according to the hot borate protocol modified by Wan and Wilkins (1994) and Gomes Neto et al (2018). Approximately 20 mg of ground seeds were mixed with 800 μl of extraction buffer (0.2 M Na borate decahydrate (Borax), 30 mM EGTA, 1% SDS, 1% Na deoxycholate (Na-DOC)) containing 1.6 mg DTT and 48 mg PVP40 which had been heated to 80°C.…”

Section: Rna Extractionmentioning

confidence: 99%

Transcriptome profiling of Ricinus communis L. provides new insights underlying the mechanisms towards thermotolerance during seed imbibition and germination

Ribeiro

Willems

Silva

et al. 2018

Industrial Crops and Products

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A B S T R A C TRicinus communis seeds germinate to a high percentage and faster at 35°C than at lower temperatures, but with compromised seedling establishment and survival. However, seedlings are able to cope with high temperatures at later stages of seedling establishment if germination occurred at lower temperatures. The identification of this thermo-sensitive window during seed germination suggests that temperature disturb crucial mechanisms that support seedling establishment. We studied the molecular mechanisms that could explain this thermo-sensitive window with a genomics approach using microarray analysis to determine transcriptome changes during seed germination at 20, 25 and 35°C. Although temperature had a strong effect on the R. communis transcriptome, most of these differences occurred between 6 h of imbibition and the commencement of germination, i.e. radicle protrusion, which coincided with the identified thermo-sensitive window. We identified several responsive genes that might be involved in the thermotolerance of R. communis. Temperature had a major effect on genes involved in energy generating pathways, such as the Calvin-Benson-Bassham cycle, gluconeogenesis, and starch-and triacylglycerol degradation. Transcripts of ATP binding proteins, DNA binding proteins, RNA binding proteins, DNA-directed RNA polymerases, heat shock factor proteins, multiprotein-bridging factor proteins, and zinc finger proteins were also affected by temperature suggesting that transcriptional reprogramming mechanisms were disturbed. Among the downregulated transcripts, three were shared by all three stages: one oxidationrelated zinc finger 2, one F-box and wd40 domain protein, and one DNA binding protein/ MYB-like transcription factor. Among the upregulated transcripts, nine were shared by all three stages: one BET1P/SFT1P-like protein 14BB, one low-molecular-weight cysteine-rich protein LCR78, one WD-repeat protein, one GAST1 protein, one adenylate kinase 1/P-loop containing nucleoside triphosphate hydrolases superfamily protein, and four conserved hypothetical proteins. These genes constitute good candidate genes for further characterization of temperature-responsive molecular mechanisms in R. communis, which in turn will provide necessary tools for the exploitation of R. communis by small family farmers under the typical harsh conditions of semiarid regions worldwide.

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Resilience of Ricinus communis L. to high temperatures during germination and seedling growth resulting from efficient superoxide dismutase modulation

Neto,

Ligterink,

Hilhorst

et al. 2024

Braz. J. Bot

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Characterization of the superoxide dismutase gene family in seeds of two Ricinus communis L. genotypes submitted to germination under water restriction conditions

Cited by 21 publications

References 65 publications

The Use of the Generalized Linear Model to Assess the Speed and Uniformity of Germination of Corn and Soybean Seeds

The Use of the Generalized Linear Model to Assess the Speed and Uniformity of Germination of Corn and Soybean Seeds

Transcriptome profiling of Ricinus communis L. provides new insights underlying the mechanisms towards thermotolerance during seed imbibition and germination

Resilience of Ricinus communis L. to high temperatures during germination and seedling growth resulting from efficient superoxide dismutase modulation

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