Bioinformatic analysis of the effect of SNPs in the pig TERT gene on the structural and functional characteristics of the enzyme to develop new genetic markers of productivity traits.

BACKGROUND: Telomerase reverse transcriptase (TERT) plays a crucial role in synthesizing telomeric repeats that safeguard chromosomes from damage and fusion, thereby maintaining genome stability. Mutations in the TERT gene can lead to a deviation in gene expression, impaired enzyme activity, and, as a result, abnormal telomere shortening. Genetic markers of productivity traits in livestock can be developed based on the TERT gene polymorphism for use in marker-associated selection (MAS). In this study, a bioinformatic-based approach is proposed to evaluate the effect of missense single-nucleotide polymorphisms (SNPs) in the pig TERT gene on enzyme function and structure, with the prospect of developing genetic markers. RESULTS: A comparative analysis of the coding and amino acid sequences of the pig TERT was performed with corresponding sequences of other species. The distribution of polymorphisms in the pig TERT gene, with respect to the enzyme's structural-functional domains, was established. A three-dimensional model of the pig TERT structure was obtained through homological modeling. The potential impact of each of the 23 missense SNPs in the pig TERT gene on telomerase function and stability was assessed using predictive bioinformatic tools utilizing data on the amino acid sequence and structure of pig TERT. CONCLUSIONS: According to bioinformatic analysis of 23 missense SNPs of the pig TERT gene, a predictive effect of rs789641834 (TEN domain), rs706045634 (TEN domain), rs325294961 (TRBD domain) and rs705602819 (RTD domain) on the structural and functional parameters of the enzyme was established. These SNPs hold the potential to serve as genetic markers of productivity traits. Therefore, the possibility of their application in MAS should be further evaluated in associative analysis studies.

Polymorphisms of the porcine cathepsins, growth hormone-releasing hormone and leptin receptor genes and their association with meat quality traits in Ukrainian Large White breed.

Cathepsins, growth hormone-releasing hormone (GHRH) and leptin receptor (LEPR) genes have been receiving increasing attention as potential markers for meat quality and pig performance traits. This study investigated the allele variants in four cathepsin genes (CTSB, CTSK, CTSL, CTSS), GHRH and LEPR in pure-bred Ukrainian Large White pigs and evaluated effects of the allele variants on meat quality characteristics. The study was conducted on 72 pigs. Genotyping was performed using PCR-RFLP technique. Meat quality characteristics analysed were intramuscular fat content, tenderness, total water content, ultimate pH, crude protein and ashes. A medium level of heterozygosity values was established for GHRH and LEPR genes which corresponded to very high levels of informativeness indexes. Cathepsins CTSL, CTSB and CTSK had a low level of heterozygosity, and CTSS did not segregate in this breed. Association studies established that intramuscular fat content and tenderness were affected by the allele variance in GHRH and LEPR but not by CTSB and CTSL genes. The GHRH results could be particularly relevant for the production of lean prime cuts as the A allele is associated with both, a lower meat fat content and better tenderness values, which are two attributes highly regarded by consumers. Results of this study suggest that selective breeding towards GHRH/AA genotype would be particularly useful for improving meat quality characteristics in the production systems involving lean Large White lines, which typically have less than 2 % intramuscular fat content.

The impact of mutation sets in receptor-binding domain of SARS-CoV-2 variants on the stability of RBD-ACE2 complex.

Aim: Bioinformatic analysis of mutation sets in receptor-binding domain (RBD) of currently and previously circulating SARS-CoV-2 variants of concern (VOCs) and interest (VOIs) to assess their ability to bind the ACE2 receptor. Methods: In silico sequence and structure-oriented approaches were used to evaluate the impact of single and multiple mutations. Results: Mutations detected in VOCs and VOIs led to the reduction of binding free energy of the RBD-ACE2 complex, forming additional chemical bonds with ACE2, and to an increase of RBD-ACE2 complex stability. Conclusion: Mutation sets characteristic of SARS-CoV-2 variants have complex effects on the ACE2 receptor-binding affinity associated with amino acid interactions at mutation sites, as well as on the acquisition of other viral adaptive advantages.

The increase in the infectious potential of SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, Omicron, etc.) that causes COVID-19 is mainly due to virus mutations. Particularly important for the development of the disease is the interaction of the coronavirus spike protein with a receptor on the surface of human cell, as a result of which the virus penetrates the cell. Angiotensin-binding enzyme (ACE2) is such a receptor in humans, and there is a receptor-binding domain (RBD) in the coronavirus spike protein. In this study, using bioinformatic methods, an analysis of mutations in the RBD of the virus was carried out to find out their influence on the functionality and ability of the virus to interact with the ACE2 receptor with high stability, which ultimately leads to infection. A number of mutations increase the infectious potential of the virus. More recent variants of the virus have more than one mutation in the RBD, so their effects are complex. It is important that the coronavirus is constantly evolving, increasing the ability to bind to the ACE2 receptor, as well as avoiding the immune response. The Omicron variant, which has at least 15 mutations in the RBD, is the most successful in these directions.

Analysis of RBD-ACE2 interactions in livestock species as a factor in the spread of SARS-CoV-2 among animals.

The high mutation rate of SARS-CoV-2, which has led to the emergence of a number of virus variants, creates risks of transmission from humans to animal species and the emergence of new animal reservoirs of COVID-19. This study aimed to identify animal species among livestock susceptible to infection and develop an approach that would be possible to use for assessing the hazards caused by new SARS-CoV-2 variants for animals. Bioinformatic analysis was used to evaluate the ability of receptor-binding domains (RBDs) of different SARS-CoV-2 variants to interact with ACE2 receptors of livestock species. The results indicated that the stability of RBD-ACE2 complexes depends on both amino acid residues in the ACE2 sequences of animal species and on mutations in the RBDs of SARS-CoV-2 variants, with the residues in the interface of the RBD-ACE2 complex being the most important. All studied SARS-CoV-2 variants had high affinity for ferret and American mink receptors, while the affinity for horse, donkey, and bird species' receptors significantly increased in the highly mutated Omicron variant. Hazards that future SARS-CoV-2 variants may acquire specificity to new animal species remain high given the mutability of the virus. The continued use and expansion of the bioinformatic approach presented in this study may be relevant for monitoring transmission risks and preventing the emergence of new reservoirs of COVID-19 among animals.