Within genera polymorphic sites identified for <i>rbcL</i> and <i>matK</i>.

<p>(*) indicating other polymorphic sites not shown in both markers. (1) indicating 111-6bp deletion, (2) indicating 117-6bp deletion.</p

Genetic distances in barcode loci at three taxonomic levels.

<p>Genetic distances in barcode loci at three taxonomic levels.</p

Pairwise intraspecific and interspecific distances in the barcode loci of all 161 plant species.

<p>Pairwise intraspecific and interspecific distances in the barcode loci of all 161 plant species.</p

Identification success of Egyptian horticultural crops based on Blast1 method.

<p>Identification success of Egyptian horticultural crops based on Blast1 method.</p

Comparison of two loci tested on several genera.

<p>No.: Number, Sp.: Species, Seq.: Sequence, Len.: Length, Hap.: Haplotype, Nuc. Div.: Diversity, Segre.: Segregation.</p

Table_1_In silico characterization of differentially expressed short-read nucleotide sequences identified in dieback stress-induced transcriptomic analysis reveals their role as antimicrobial peptides.docx

We investigated the in silico characterization of short-length nucleotide sequences that were differentially expressed in dieback stress-induced transcriptomic analysis. They displayed homology with C-terminal flanking peptides and defensins-like proteins, revealing their antimicrobial activity. Their predicted fingerprints displayed protein signatures related to antimicrobial peptides. These short-length RGAs have been shown to possess structural motifs such as APLT P-type ATPase, casein kinase II (CK2), protein kinase 3, protein kinase C (PKC), and N-glycosylation site that are the attributes of disease resistance genes. The prediction of arginine and lysine residues in active binding sites in ligand docking analysis prophesied them as antimicrobial peptides due to their strong relation with antimicrobial activity. The in silico structural–functional characterization has predicted their role in resistance against microbial pathogens. Moreover, the predicted antimicrobial peptide regions showed their homology with the signature domain of PR-5-like protein and AMP family Thaumatin</p

DataSheet1_Identification of resistance gene analogs of the NBS-LRR family through transcriptome probing and in silico prediction of the expressome of Dalbergia sissoo under dieback disease stress.docx

Dalbergia sissoo is an important timber tree, and dieback disease poses a dire threat to it toward extinction. The genomic record of D. sissoo is not available yet on any database; that is why it is challenging to probe the genetic elements involved in stress resistance. Hence, we attempted to unlock the genetics involved in dieback resistance through probing the NBS-LRR family, linked with mostly disease resistance in plants. We analyzed the transcriptome of D. sissoo under dieback challenge through DOP-rtPCR analysis using degenerate primers from conserved regions of NBS domain-encoded gene sequences. The differentially expressed gene sequences were sequenced and in silico characterized for predicting the expressome that contributes resistance to D. sissoo against dieback. The molecular and bioinformatic analyses predicted the presence of motifs including ATP/GTP-binding site motif A (P-loop NTPase domain), GLPL domain, casein kinase II phosphorylation site, and N-myristoylation site that are the attributes of proteins encoded by disease resistance genes. The physicochemical characteristics of identified resistance gene analogs, subcellular localization, predicted protein fingerprints, in silico functional annotation, and predicted protein structure proved their role in disease and stress resistance.</p

Additional file 1 of Exploring the benefits of wild plants in dietary nutrition: investigating perspectives, choices, health impacts and sustainable practices

Additional file 1

Table_1_Precision drug design against Acidovorax oryzae: leveraging bioinformatics to combat rice brown stripe disease.docx

Bacterial brown stripe disease caused by Acidovorax oryzae is a major threat to crop yields, and the current reliance on pesticides for control is unsustainable due to environmental pollution and resistance. To address this, bacterial-based ligands have been explored as a potential treatment solution. In this study, we developed a protein–protein interaction (PPI) network for A. oryzae by utilizing shared differentially expressed genes (DEGs) and the STRING database. Using a maximal clique centrality (MCC) approach through CytoHubba and Network Analyzer, we identified hub genes within the PPI network. We then analyzed the genomic data of the top 10 proteins, and further narrowed them down to 2 proteins by utilizing betweenness, closeness, degree, and eigenvector studies. Finally, we used molecular docking to screen 100 compounds against the final two proteins (guaA and metG), and Enfumafungin was selected as a potential treatment for bacterial resistance caused by A. oryzae based on their binding affinity and interaction energy. Our approach demonstrates the potential of utilizing bioinformatics and molecular docking to identify novel drug candidates for precision treatment of bacterial brown stripe disease caused by A. oryzae, paving the way for more targeted and sustainable control strategies. The efficacy of Enfumafungin in inhibiting the growth of A. oryzae strain RS-1 was investigated through both computational and wet lab methods. The models of the protein were built using the Swiss model, and their accuracy was confirmed via a Ramachandran plot. Additionally, Enfumafungin demonstrated potent inhibitory action against the bacterial strain, with an MIC of 100 µg/mL, reducing OD600 values by up to 91%. The effectiveness of Enfumafungin was further evidenced through agar well diffusion assays, which exhibited the highest zone of inhibition at 1.42 cm when the concentration of Enfumafungin was at 100 µg/mL. Moreover, Enfumafungin was also able to effectively reduce the biofilm of A. oryzae RS-1 in a concentration-dependent manner. The swarming motility of A. oryzae RS-1 was also found to be significantly inhibited by Enfumafungin. Further validation through TEM observation revealed that bacterial cells exposed to Enfumafungin displayed mostly red fluorescence, indicating destruction of the bacterial cell membrane.</p

Table_2_Determination of morpho-physiological and yield traits of maize inbred lines (Zea mays L.) under optimal and drought stress conditions.XLSX

Globally, climate change could hinder future food security that concurrently implies the importance of investigating drought stress and genotype screening under stressed environments. Hence, the current study was performed to screen 45 diverse maize inbred lines for 18 studied traits comprising phenological, physiological, morphological, and yield characters under optimum and water stress conditions for two successive growing seasons (2018 and 2019). The results showed that growing seasons and water regimes significantly influenced (p < 0.01) most of the studied traits, while inbred lines had a significant effect (p < 0.01) on all of the studied traits. The findings also showed a significant increase in all studied characters under normal conditions compared to drought conditions, except chlorophyll content, transpiration rate, and proline content which exhibited higher levels under water stress conditions. Furthermore, the results of the principal component analysis indicated a notable distinction between the performance of the 45 maize inbred lines under normal and drought conditions. In terms of grain yield, the drought tolerance index (DTI) showed that Nub60 (1.56), followed by Nub32 (1.46), Nub66 (1.45), and GZ603 (1.44) were the highest drought-tolerant inbred lines, whereas Nub46 (0.38) was the lowest drought-tolerant inbred line. These drought-tolerant inbred lines were able to maintain a relatively high grain yield under normal and stress conditions, whereas those drought-sensitive inbred lines showed a decline in grain yield when exposed to drought conditions. The hierarchical clustering analysis based on DTI classified the forty-five maize inbred lines and eighteen measured traits into three column- and row-clusters, as inbred lines in cluster-3 followed by those in cluster-2 exhibited greater drought tolerance in most of the studied traits. Utilizing the multi-trait stability index (MTSI) criterion in this study identified nine inbred lines, including GZ603, as stable genotypes in terms of the eighteen studied traits across four environments. The findings of the current investigation motivate plant breeders to explore the genetic potential of the current maize germplasm, especially in water-stressed environments.</p