Codonopsis genus is comprised of species that are perennial plants primarily distributed across all east, southeast, and Central Asia. The most famous species of Codonopsis are C. tangshen, C. lanceolate, and C. pilosula. The records showed that they have a long story usage as traditional Chinese medicines, as they were alleged to be able to intensify the spleen and the lung as well as enriching blood and engendering liquid. Certain species have a culinary value in southern China and Southeast Asia, where they are considered as tea, wine, soup, plaster, and porridge. Codonopsis species were shown to be of great importance in medicine, due to their broad biological activity. Therefore, a clear understanding of their genetic diversity is needed. Adequate distinctions and descriptions of those species are necessary to preserve plant reservoir, investigations of genes associated with desirable traits, and understanding of evolutionary relationships.Subsequently, various molecular marker techniques such as Random Amplified Polymorphic DNA (RAPD), Amplified Fragment Length Polymorphism (AFLP), Simple Sequence Repeats (SSR), and Inter Simple Sequence Repeat (ISSR), Single Nucleotide Polymorphism (SNP), internal transcribed spacer (ITS), and Sequence-Characterized Amplified Region (SCAR) have been improved to provide detailed informations about genomes, that historically were not possible to obtain based on only phenotypic methods. This review represents the usage of DNA molecular markers for molecular diversity analysis of medically important species belonging to the genus Codonopsis.
Hyperparathyroidism-Jaw Tumor (HPT-JT) is an autosomal dominant disorder with variable expression, with an estimated prevalence of 6.7 per 1,000 population. Genetic testing for predisposing CDC73 (HRPT2) mutations has been an important clinical advance, aimed at early detection and/or treatment to prevent advanced disease. The aim of this study is to assess the most deleterious SNPs mutations on CDC73 gene and to predict their influence on the functional and structural levels using different bioinformatics tools. Method: Computational analysis using twelve different in-silico tools including SIFT, PROVEAN, PolyPhen-2, SNAP2, PhD-SNP, SNPs&GO, P-Mut, I-Mutant ,Project Hope, Chimera, COSMIC and dbSNP Short Genetic Variations were used to identify the impact of mutations in CDC73 gene that might be causing jaw tumor. Results: From (733) SNPs identified in the CDC73 gene we found that only Eleven SNPs (G49C, L63P, L64P, D90H, R222G, W231R, P360S, R441C, R441H, R504S and R504H) has deleterious effect on the function and structure of protein and expected to cause the syndrome. Conclusion: Eleven substantial genetic/molecular aberrations in CDC73 gene identified that could serve as diagnostic markers for hyperparathyroidism-jaw tumor (HPT-JT).
Back ground: hyperparathyroidism-jaw tumor (HPT-JT) is an autosomal dominant disorder with variable expression, with an estimated prevalence of 6.7 per 1,000 population. Genetic testing for predisposing CDC73 (HRPT2) mutations has been an important clinical advance, aimed at early detection and/or treatment to prevent advanced disease. The aim of this study is to assess the effect of SNPs on CDC73 structure and function using different bioinformatics tools. Method: Computational analysis using eight different in-silico tools including SIFT, PROVEAN, PolyPhen-2, SNAP2, PhD-SNP, SNPs&GO, PMut and Imutant were used to identify the impact on the structure and/or function of CDC73 gene that might be causing jaw tumour. Results: From (733) SNPs identified in the CDC73 gene we found that only Eleven were deleterious to the function and structure of protein and expected to cause syndrome.Conclusion: Eleven substantial genetic/molecular aberrations in CDC73 gene were identified that could serve as actionable targets for chemotherapeutic intervention in patients whose disease is no longer surgically curable.
Background: Woodhouse-Sakati Syndrome refers to a group of inherited disorders characterized by alopecia, hypogonadism, diabetes mellitus, hypothyroidism and progressive extrapyramidal signs. The aim of this study is to identify the pathogenic SNPs in the DCAF17 gene with their related mciroRNAs and their effect on the structure and function of the protein. Material and Methods:We used different bioinformatics tools to predict the effect of each SNP on the structure and function of the protein. After that we defined the miRNAs founded in the 3'-UTR region on the DCAF17 gene and studied the annotations relative to it. Results: Ten deleterious SNPs out of 339 were found to have a damaging effect on the protein structure and function, with one significant micoRNA in the 3'-UTR region . Conclusion: This was the first in silico analysis of DCAF17 gene, in which 10 novel mutations were found using different bioinformatics tools that could be used as a diagnostic markers for Woodhouse-Sakati syndrome, with one relevant microRNA that can regulate the function of the protein.
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