In silico analysis of CDC73 gene revealing 11 novel SNPs with possible association to Hyperparathyroidism-Jaw Tumor syndrome
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 p...
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| Format: | Article |
| Language: | English |
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Sciendo
2020-04-01
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| Series: | The EuroBiotech Journal |
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| Online Access: | https://doi.org/10.2478/ebtj-2020-0008 |
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| author | Abdelmoneim Abdelrahman H. Mohammed Alaa I. Gadim Esraa O. Mohammed Mayada Alhibir Hamza Sara H. Mirghani Sara A. Mahmoud Thwayba A. Hassan Mohamed A. |
| author_facet | Abdelmoneim Abdelrahman H. Mohammed Alaa I. Gadim Esraa O. Mohammed Mayada Alhibir Hamza Sara H. Mirghani Sara A. Mahmoud Thwayba A. Hassan Mohamed A. |
| author_sort | Abdelmoneim Abdelrahman H. |
| collection | DOAJ |
| description | 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). |
| first_indexed | 2024-12-17T21:41:52Z |
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| institution | Directory Open Access Journal |
| issn | 2564-615X |
| language | English |
| last_indexed | 2024-12-17T21:41:52Z |
| publishDate | 2020-04-01 |
| publisher | Sciendo |
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| series | The EuroBiotech Journal |
| spelling | doaj.art-fcf6cf895d6a4644801d6931762e2a2e2022-12-21T21:31:35ZengSciendoThe EuroBiotech Journal2564-615X2020-04-0142678110.2478/ebtj-2020-0008ebtj-2020-0008In silico analysis of CDC73 gene revealing 11 novel SNPs with possible association to Hyperparathyroidism-Jaw Tumor syndromeAbdelmoneim Abdelrahman H.0Mohammed Alaa I.1Gadim Esraa O.2Mohammed Mayada Alhibir3Hamza Sara H.4Mirghani Sara A.5Mahmoud Thwayba A.6Hassan Mohamed A.7Bioinformatic Department, Africa City of Technology, KhartoumSudanDepartment of Haematology, University of Khartoum, KhartoumSudanBioinformatic Department, Africa City of Technology, KhartoumSudanBioinformatic Department, Africa City of Technology, KhartoumSudanBioinformatic Department, Africa City of Technology, KhartoumSudanBioinformatic Department, Africa City of Technology, KhartoumSudanBioinformatic Department, Africa City of Technology, KhartoumSudanBioinformatic Department, Africa City of Technology, KhartoumSudanHyperparathyroidism-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).https://doi.org/10.2478/ebtj-2020-0008snpsphptcdc73 genehpt-jtin silico analysis |
| spellingShingle | Abdelmoneim Abdelrahman H. Mohammed Alaa I. Gadim Esraa O. Mohammed Mayada Alhibir Hamza Sara H. Mirghani Sara A. Mahmoud Thwayba A. Hassan Mohamed A. In silico analysis of CDC73 gene revealing 11 novel SNPs with possible association to Hyperparathyroidism-Jaw Tumor syndrome The EuroBiotech Journal snps phpt cdc73 gene hpt-jt in silico analysis |
| title | In silico analysis of CDC73 gene revealing 11 novel SNPs with possible association to Hyperparathyroidism-Jaw Tumor syndrome |
| title_full | In silico analysis of CDC73 gene revealing 11 novel SNPs with possible association to Hyperparathyroidism-Jaw Tumor syndrome |
| title_fullStr | In silico analysis of CDC73 gene revealing 11 novel SNPs with possible association to Hyperparathyroidism-Jaw Tumor syndrome |
| title_full_unstemmed | In silico analysis of CDC73 gene revealing 11 novel SNPs with possible association to Hyperparathyroidism-Jaw Tumor syndrome |
| title_short | In silico analysis of CDC73 gene revealing 11 novel SNPs with possible association to Hyperparathyroidism-Jaw Tumor syndrome |
| title_sort | in silico analysis of cdc73 gene revealing 11 novel snps with possible association to hyperparathyroidism jaw tumor syndrome |
| topic | snps phpt cdc73 gene hpt-jt in silico analysis |
| url | https://doi.org/10.2478/ebtj-2020-0008 |
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