Research Article
Microarray Analysis Reveals Altered Genes Involved in Apoptosis, Inflammation and Bone Metabolism in Knee Osteoarthritis
Vishal Chandra,
Mohd Tashfeen Ashraf,
Pramod Yadav,
Vikas Raghuvanshi
Issue:
Volume 11, Issue 2, December 2023
Pages:
12-19
Received:
20 September 2023
Accepted:
10 October 2023
Published:
31 October 2023
Abstract: Background: Osteoarthritis (OA) is a common rheumatic disorder that affects multiple joint tissues and has complex genetic and environmental etiologies. This study explores the genetic basis of OA in the Kanpur District, India. Methods: It is examined genes related to metabolism, apoptosis, cytokine signaling, and bone metabolism. Microarray-based gene expression analysis revealed significant differences between OA patients and healthy controls. Results: The results indicated the potential involvement of apoptosis and inflammatory pathways, as evidenced by the upregulated expression of caspases, TNF receptors, and ligands. The results also suggested a proinflammatory environment that contributes to cartilage degradation, as shown by the elevated expression of cytokines such as IL-1β, IL-17D, and IL-18. Moreover, the results demonstrated extracellular matrix remodelling and immune activation in OA pathogenesis, as indicated by the increased expression of matrix metalloproteinase (MMP) and complement component genes. Interestingly, bone metabolism-related genes displayed varied expression patterns, with decreased expression of TGFβ isoforms and increased expression of S100 proteins. Conclusion: These findings underscore the dysregulation of apoptosis, inflammation, and extracellular matrix homeostasis in OA, offering insights into potential therapeutic targets for disease management. However, the study limitations, such as small sample size and regional specificity, warrant further investigation to confirm and extend these findings. Future research should utilize larger cohorts and diverse methodologies to enhance the understanding of OA’s molecular mechanisms and facilitate the development of targeted interventions.
Abstract: Background: Osteoarthritis (OA) is a common rheumatic disorder that affects multiple joint tissues and has complex genetic and environmental etiologies. This study explores the genetic basis of OA in the Kanpur District, India. Methods: It is examined genes related to metabolism, apoptosis, cytokine signaling, and bone metabolism. Microarray-based ...
Show More
Research Article
Genetic Variation of Recombinant Inbred Lines Soybean (Glycine max L. Merrill) from USA at Jimma, Ethiopia
Gada Gudina*,
Abush Tesfaye,
Amsalu Nebiyu,
Getachew Bekele
Issue:
Volume 11, Issue 2, December 2023
Pages:
20-29
Received:
6 November 2023
Accepted:
21 November 2023
Published:
22 December 2023
Abstract: In this study the genetic variability of soybean lines generated from segregating populations introduced from USA was evaluated. A total of 97 soybean genotypes that were introduced from USA along with three checks were grown in 10×10 simple lattice design with two replications at Jimma, Ethiopia. The ANOVA results showed significant (p≤0.05) variations in days to flowering, days to maturity, plant height, number of branches per plant, number of pods per plant, pod length, number of seeds per pod, number of seeds per plant, 100 seed weight, above ground biomass, harvest index, and grain yield indicating a considerable variability among the tested genotypes for the characters. Characters viz., plant height, number of branches per plant, above ground biomass and grain yield had high heritability and high genetic advance. Grain yield had positive and high significant (p≤0.01) genotypic correlations with harvest index (0.746) and 100 seed weight (0.267). Similarly, grain yield showed positive and significant (p≤0.05) genotypic associations with number of seeds per plant (0.225) and above ground biomass (0.205). This implies that higher mean values for these traits tend to improve grain yield in soybean. Cluster analysis grouped the genotypes into three clusters with the maximum squared distance found between cluster II and III. The principal component analysis revealed that the first four principal components (PCs) accounted for more than 71.25% of the total variation. The variability amongst the tested genotypes, heritability and genetic advance, as well as the associations in the tested traits provide information for an increased soybean productivity using this lines.
Abstract: In this study the genetic variability of soybean lines generated from segregating populations introduced from USA was evaluated. A total of 97 soybean genotypes that were introduced from USA along with three checks were grown in 10×10 simple lattice design with two replications at Jimma, Ethiopia. The ANOVA results showed significant (p≤0.05) varia...
Show More
