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https://doi.org/10.18054/pb.v121-122i1-2.10737

Evolutionary age of genes can assist in genome mining

Ivan Mijakovic   ORCID icon orcid.org/0000-0002-8860-6853

Puni tekst: engleski, pdf (675 KB) str. 3-6 preuzimanja: 42* citiraj
APA 6th Edition
Mijakovic, I. (2020). Evolutionary age of genes can assist in genome mining. Periodicum biologorum, 121-122 (1-2), 3-6. https://doi.org/10.18054/pb.v121-122i1-2.10737
MLA 8th Edition
Mijakovic, Ivan. "Evolutionary age of genes can assist in genome mining." Periodicum biologorum, vol. 121-122, br. 1-2, 2020, str. 3-6. https://doi.org/10.18054/pb.v121-122i1-2.10737. Citirano 07.05.2021.
Chicago 17th Edition
Mijakovic, Ivan. "Evolutionary age of genes can assist in genome mining." Periodicum biologorum 121-122, br. 1-2 (2020): 3-6. https://doi.org/10.18054/pb.v121-122i1-2.10737
Harvard
Mijakovic, I. (2020). 'Evolutionary age of genes can assist in genome mining', Periodicum biologorum, 121-122(1-2), str. 3-6. https://doi.org/10.18054/pb.v121-122i1-2.10737
Vancouver
Mijakovic I. Evolutionary age of genes can assist in genome mining. Periodicum biologorum [Internet]. 2020 [pristupljeno 07.05.2021.];121-122(1-2):3-6. https://doi.org/10.18054/pb.v121-122i1-2.10737
IEEE
I. Mijakovic, "Evolutionary age of genes can assist in genome mining", Periodicum biologorum, vol.121-122, br. 1-2, str. 3-6, 2020. [Online]. https://doi.org/10.18054/pb.v121-122i1-2.10737

Sažetak

The rate of sequencing microbial genomes is accelerating, with the hope of discovering new antibiotics, cures for various diseases or new industrial enzymes. However, about 25-30% of the genes in the sequenced microbial genomes do not have an assigned function. Predicting the functions of these “unknown” genes could unlock a considerable biological potential for biomedical and biotechnology applications, as well as further our understanding of the molecular tenets of life. Current methods for gene mining rely basically on comparison of primary sequences or 3D-structures to those of already characterized genes. The problem with such approaches is that unknown genes with no homology to the already characterized genes remain completely out of reach. Herein, I argue that evolutionary approaches, such as the genomic phylostratigraphy, can make a substantial contribution to genome mining – especially regarding genes with no homology to the characterized ones. My group has recently used genomic phylostratigraphy to discover new genes involved in sporulation of the bacterial model organism Bacillus subtilis. These new sporulation genes exhibited no sequence homology with the known sporulation genes and were missed by all other genome mining approaches. They have been discovered solely based on their evolutionary age. Along these lines, I argue that phylostratigraphy should be integrated into genome mining pipelines and develop a brief example of how this could be done.

Hrčak ID: 254643

URI
https://hrcak.srce.hr/254643

Posjeta: 66 *