An evaluation of the expression and predictive significance of the MDM2 gene in brain lower-grade glioma (LGG) cancer was carried out using onco-informatics pipelines. Several transcriptome servers were used to measure the differential expression of the targeted MDM2 gene and search mutations and copy number variations. GENT2, Gene Expression Profiling Interactive Analysis, Onco-Lnc, and PrognoScan were used to figure out the survival rate of LGG cancer patients. The protein–protein interaction networks between MDM2 gene and its co-expressed genes were constructed by Gene-MANIA tool. Identified bioactive phytochemicals were evaluated through molecular docking using Schrödinger Suite Software, with the MDM2 (PDB ID: 1RV1) target. Protein–ligand interactions were observed with key residues of the macromolecular target. A molecular dynamics simulation of the novel bioactive compounds with the targeted protein was performed. Phytochemicals targeting MDM2 protein, such as Taxifolin and (-)-Epicatechin, have been shown with more highly stable results as compared to the control drug, and hence, concluded that phytochemicals with bioactive potential might be alternative therapeutic options for the management of LGG patients. Our once informatics-based designed pipeline has indicated that the MDM2 gene may have been a predictive biomarker for LGG cancer and selected phytochemicals possessed outstanding interaction results within the macromolecular target’s active site after utilizing in silico approaches. In vitro and in vivo experiments are recommended to confirm these outcomes.

Guava (Psidium guajava L.) is an open-pollinated crop having 25-40% dissimilarity index which promotes heterozygosity and adds new cultivars. Morpho-genetic characterization of 37 guava accessions was carried out for genetic variability and structure of guava germplasm located in Punjab province, Pakistan. Principal Component analysis (PCA) was subjected to analyze the morphological diversity and for genetic analysis we applied cluster analysis, using the PyElph software. PCA distributed thirty one traits into six components and first two components accounted 39.5% of total variation. A dendrogram constructed on the basis of morphological traits which showed 34% dissimilarity index among thirty seven guava accessions and divided them into 6 groups. For genetic characterization 18 microsatellites were used, the size of reproducible and scorable bands ranged from 150 to 320 bp. The 18 primer pairs amplified 85 alleles with an average number of 4.7 alleles per locus and no more than two displayed bands (nuclear SSR loci). The phylogenetic tree based on molecular analysis showed 50% dissimilarity index among selected guava accessions and separated them into 4 groups.

Molecular germplasm characterization is essential for gathering information on favorable attributes and varietal improvement. The current study evaluated the genetic divergence and population structure of 80 potato genotypes collected from Punjab, Pakistan, using polymorphic retrotransposon-DNA-based markers (iPBS). A total of 11 iPBS primers generated 787 alleles with a mean value of 8.9 alleles per primer, of which ~95% were polymorphic across the 80 genotypes. Different variation attributes, such as mean expected heterozygosity (H = 0.21), mean unbiased expected heterozygosity (µHe = 0.22), and mean Shannon’s information index (I = 0.32), showed the existence of sufficient genetic diversity in the studied potato genotypes. Analysis of molecular variance (AMOVA) showed that genetic variation within the population was higher (84%) than between populations (16%). A neighbor-joining tree was constructed based on the distance matrices that arranged the 80 genotypes into five distinct groups, and the genotypes FD61-3 and potato 2 had the highest genetic distance. A STRUCTURE analysis corroborated the dendrogram results and distributed the 80 genotypes also into five clusters. Our results determined that retrotransposon-based markers are highly polymorphic and could be used to evaluate genetic diversity between local and exotic potato genotypes. The genotypic data and population structure dissection analysis reported in this study will enhance potato varietal improvement and development.

The cytoplasmic dynein light chain 1 (DYNLL1) is an important constituent of motor proteins complex. In human it is encoded by DYNLL1 gene. It is involved in cargo transport functions and interacts with many viral proteins with the help of short linear consensus motif sequence (K/R) XTQT. Viral proteins bind to DYNLL1 through its consensus short linear motif (SLiM) sequence to reach the target site in the cell and cause different infections in the host. It is still unknown if bacterial proteins also contain the same conserved SLiMs sequence through which they bind to this motor protein and cause infections. So, it is important to investigate the role of DYNLL1 in human bacterial infections. The interaction partner proteins of DYNLL1 against conserved viral motif sequences were predicted through PDBSum. Pairwise sequence alignment, between viral motif sequence and that of predicted proteins, was performed to identify conserved region in predicted interaction partners. Docking between the DYNLL1 and new pathogenic interaction partners was performed, by using PatchDock, to explore the protein-protein binding quality. Interactions of docked complexes were visualized by DimPlot. Three pathogenic bacterial proteins i.e., enterochelin esterase (3MGA), protective antigen (3J9C) and putative lipoprotein (4KT3) were selected as candidate interaction partners of DYNLL1. The putative lipoprotein (4KT3) showed low quality binding with DYNLL1. So, enterochelin esterase (3MGA) and protective antigen (3J9C) were speculated to be involved in human bacterial infections by using DYNLL1 to reach their target sites.

Both morphological and molecular markers have been extensively used to evaluate genetic diversity; however, molecular markers are considered more reliable and can lead to improved reproductive efficiency. This study utilized inter-primer binding site (iPBS) markers to examine the genetic diversity and population structure of thirty mulberry accessions from the districts of Sahiwal and Faisalabad, Pakistan. These mulberry accessions belonged to three species: Morus nigra (n = 13), Morus alba (n = 12), and Morus rubra (n = 5). The use of nine iPBS primers in this study provided a comprehensive understanding of genetic diversity among the selected mulberry accessions. Nine iPBS primers were used in the study and generated 431 bands with allelic frequencies ranging from 21 to 75 and band sizes from 200 to 1500 base pairs. The primer 2230 showed the highest polymorphic information content (PIC) value of 0.47 and the highest Shannon’s information index (I = 0.53). The Morus nigra accessions had the highest levels of expected heterozygosity (He = 0.30), unbiased expected heterozygosity (µHe = 0.33), and Shannon’s information index (I = 0.45). The molecular variance analysis (AMOVA) revealed a high degree of genetic variation, as estimated by the pairwise PhiPT value of 0.21, which was significant at the p < 0.001 *** level. The neighbor joining tree, principal coordinate analysis, and structure analysis grouped the 30 mulberry accessions into four main clusters. The distinct grouping of accessions SWLS14, SWLS6, FSDS30, and SWLS7 validated their notable genetic distinctiveness. Overall, these findings contribute valuable insights into the genetic landscape of mulberry accessions, which are essential for conservation and breeding strategies.