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Validation of determinate (dt) gene-based DNA marker in inter-specific hybrid sesame and in-silico analysis of the predicted dt protein structures.

ABSTRACT: Determinacy is a desirable trait in sesame, an important oilseed crop. We have developed an inter-specific hybrid between basally branched indeterminate cultivated Sesamum indicum genotype and wild S. prostratum with no branching yet synchronous pods on the shoot. The hybrid and a few exotic sesame germplasms were successfully screened with a determinacy (dt) gene-based DNA marker. In-silico translation of the partial coding sequences of the dt gene from the two contrasting parent genotypes revealed an SNP (V159A) in S. prostratum. The predicted cytoplasmic dt protein showed a high resemblance with flowering protein centroradialis.

Supplementary information

The online version contains supplementary material available at 10.1007/s12298-022-01135-1.

SUBMITTER: Dutta D

PROVIDER: S-EPMC8847511 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Validation of determinate (dt) gene-based DNA marker in inter-specific hybrid sesame and in-silico analysis of the predicted dt protein structures.

Dutta Debabrata D Banerjee Saptadipa S Pal Manisha M Gangopadhyay Gaurab G

Physiology and molecular biology of plants : an international journal of functional plant biology 20220131 1

Determinacy is a desirable trait in sesame, an important oilseed crop. We have developed an inter-specific hybrid between basally branched indeterminate cultivated Sesamum indicum genotype and wild S. prostratum with no branching yet synchronous pods on the shoot. The hybrid and a few exotic sesame germplasms were successfully screened with a determinacy (dt) gene-based DNA marker. In-silico translation of the partial coding sequences of the dt gene from the tw ...[more]

PMID: 35221576

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Project description:The human gut microbiome has been extensively studied, but its diversity scaling (changes or heterogeneities) along the digestive tract (DT) as well as their inter-individual heterogeneities have not been adequately addressed to the best of our knowledge. Here we fill the gap by applying the diversity-area relationship (DAR), a recent extension to the classic species-area relationship (SAR) in biogeography, by reanalyzing a dataset of over 2000 16s-rRNA microbiome samples obtained from 10 DT sites of over 200 individuals. We sketched out the biogeography "maps" for each of the 10 DT sites by cross-individual DAR analysis, and the intra-DT distribution pattern by cross-DT-site DAR analysis. Regarding the inter-individual biogeography, it was found that all DT sites have the invariant (constant) scaling parameter-all sites possessing the same diversity change rate across individuals, but most sites have different potential diversities, which include the portions of diversity that may be absent locally but present regionally. In the case of this study, the potential diversity of each DT site covers the total diversity of the respective site from all individuals in the cohort. In terms of the genus richness, an average individual hosts approximately 20% of the population-level genus richness (total bacterial genus of a human population). In contrast, in terms of community biodiversity, the percentages of individual over population may exceed 90%. This suggests that the differences between individuals in their DT microbiomes are predominantly in the composition of bacterial species, rather than how their abundances are distributed (i.e., biodiversity). Regarding the intra-DT patterns, the scaling parameter (z) is larger-suggesting that the intra-DT biodiversity changes are larger than inter-individual changes. The higher intra-DT heterogeneity of bacteria diversity, as suggested by larger intra-DT z than the inter-individual heterogeneity, should be expected since the intra-DT heterogeneity reflects the functional differentiations of the DT tract, while the inter-individual heterogeneity (z) reflects the difference of the same DT site across individuals. On average, each DT site contains 21-36% of the genus diversity of the whole DT, and the percentages are even higher in terms of higher taxon levels.

Project description:Prediction of transcriptional regulatory mechanisms in Arabidopsis has become increasingly critical with the explosion of genomic data now available for both gene expression and gene sequence composition. We have shown in previous work 1, that a combination of correlation measurements and cis-regulatory element (CRE) detection methods are effective in predicting targets for candidate transcription factors for specific case studies which were validated. However, to date there has been no quantitative assessment as to which correlation measures or CRE detection methods used alone or in combination are most effective in predicting TF-->target relationships on a genome-wide scale.We tested several widely used methods, based on correlation (Pearson and Spearman Rank correlation) and cis-regulatory element (CRE) detection (>or=1 CRE or CRE over-representation), to determine which of these methods individually or in combination is the most effective by various measures for making regulatory predictions. To predict the regulatory targets of a transcription factor (TF) of interest, we applied these methods to microarray expression data for genes that were regulated over treatment and control conditions in wild type (WT) plants. Because the chosen data sets included identical experimental conditions used on TF over-expressor or T-DNA knockout plants, we were able to test the TF-->target predictions made using microarray data from WT plants, with microarray data from mutant/transgenic plants. For each method, or combination of methods, we computed sensitivity, specificity, positive and negative predictive value and the F-measure of balance between sensitivity and positive predictive value (precision). This analysis revealed that the >or=1 CRE and Spearman correlation (used alone or in combination) were the most balanced CRE detection and correlation methods, respectively with regard to their power to accurately predict regulatory-target interactions.These findings provide an approach and guidance for researchers interested in predicting transcriptional regulatory mechanisms using microarray data that they generate (or microarray data that is publically available) combined with CRE detection in promoter sequence data.

Dataset Information

Validation of determinate (dt) gene-based DNA marker in inter-specific hybrid sesame and in-silico analysis of the predicted dt protein structures.

Supplementary information

Publications

Validation of determinate (<i>dt</i>) gene-based DNA marker in inter-specific hybrid sesame and <i>in-silico</i> analysis of the predicted dt protein structures.

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