Біоінформаційний підхід до ідентифікації причинних місенс-поліморфізмів у геномах тварин
Recent trends in the development of genetic markers for animal breeding increasingly focus on identifying causative polymorphisms, as their use as markers enhances the accuracy of linking genotype to phenotype. Bioinformatic analyses offer a valuable tool for assessing the impact of missense polymorphisms on the functional characteristics of the encoded proteins, allowing for the identification of those with the most substantial effects on protein structure and function. These polymorphisms hold promise as the most likely candidates for causative roles.
New bioinformatic approach is proposed to identifying causative polymorphisms in animal genomes. The influence of both known causative and candidate missense polymorphisms in key genes of pigs (MC4R, NR6A1, PRKAG3, RYR1, SYNGR2) and cows (ABCG2, DGAT1, GHR, MSTN) was assesed. Our study included an evaluation of the impact of these polymorphisms on protein function, considering the evolutionary and physicochemical properties of amino acids at polymorphic sites. Additionally, the influence of such polymorphisms on the stability of tertiary protein structures was assessed.
The comprehensive bioinformatic analysis used in this study enables the differentiation of polymorphisms into neutral, where both amino acids at the polymorphic site do not significantly affect the structure and function of the protein, and causative, where one of the amino acids significantly alters protein properties.
The project was supported by the National Academy of Agrarian Sciences of Ukraine (Grant registration number: 0123U102862).
All protein structures with alternative amino acid variants at polymorphic sites, modeled in silico as part of this study, are presented below.
Pig Polymorphisms
Cattle Polymorphisms
All protein structure models with causative polymorphisms are available for download at the following link
During the study, a search for homologous sequences was conducted for each of the studied proteins (MC4R, NR6A1, PRKAG3, RYR1, SYNGR2 for pigs and ABCG2, GHR, DGAT1, MSTN for cows) in the UniRef90 and UniRef50 databases, retrieving up to 1000 sequences for each protein. Files containing the homologous sequences in FASTA format for each protein can be downloaded from the following link.
These sequences are suitable for phylogenetic analysis or for examining the impact of causative polymorphisms on protein function (for example, using the SIFT tool, as was applied in our study). In each file, the porcine or bovine protein sequence is listed first, with the specific polymorphic variant present in the studied pig and cow proteins indicated in the file name.
If you use data of this project, please cite this web-page. Publication based on the results of the study is under evaluation in the journal.
Публікації
Peka, M., & Balatsky, V. (2024). Bioinformatic approach to identifying causative missense polymorphisms in animal genomes. BMC genomics, 25(1), 1226. CrossRef
Balatsky, V. M., Saienko, A. M., & Peka, M. Yu. (2024). Modern animal breeding technologies and molecular genetic markers. In Prospects for the development and implementation of innovative technologies in veterinary medicine and animal husbandry (pp. 496-517). Baltija Publishing. CrossRef
Balatsky, V. N., Peka, M. Yu., Saienko, A. M., & Buslyk, T. V. (2024, September 23-26). Bioinformatic analysis for identifying causative polymorphism in livestock species genomes. XІX International Scientific Conference “Factors in Experimental Evolution of Organisms”, Ternopil, Ukraine. CrossRef