Comprehensive in silico analysis of prolactin receptor (PRLR) gene nonsynonymous single nucleotide polymorphisms (nsSNPs) reveals multifaceted impact on protein structure, function, and interactions.

This study delves into the functional and structural implications of non-synonymous single nucleotide polymorphisms (nsSNPs) within the Prolactin Receptor (PRLR) gene. Thirteen deleterious nsSNPs were identified through bioinformatics tools, with SIFT predicting 168 out of 395 nsSNPs as detrimental, exhibiting tolerance index (TI) scores ranging from 0 to 0.05. Polyphen2 assigned likelihood scores >0.99 to all 13 nsSNPs, indicating high probability of harm, while Panther scores classified most nsSNPs as 'probably damaging', with specific mutations like W218R scoring 0.74, suggesting a higher impact. Stability analysis using DDG I-Mutant and DDG Mupro consistently predicted decreased stability for all mutations, with CUPSAT indicating mutations like V125G and W218R significantly decreasing stability. Structural analysis through DynaMut predicted destabilization for all mutations except L196I and L292H. MutPred2 highlighted structural alterations for all nsSNPs except L196I, L293V, R315W, and S353N. Domain analysis revealed key mutations within essential functional domains, with five nsSNPs located within Fibronectin type-III domains. Bayesian analysis through ConSurf identified 9 critical residues, with 11 nsSNPs exhibiting notably high conservation. STRING analysis unveiled a complex interaction network, indicating involvement in vital biological processes like lactation. Molecular dynamics (MD) simulations, spanning 100 nanoseconds, elucidated structural dynamics induced by detrimental missense SNPs. Post-translational modification (PTM) analysis identified specific mutations, such as R351, involved in methylation, while S353 was implicated in phosphorylation and glycosylation. These findings offer comprehensive insights into the molecular and phenotypic effects of deleterious nsSNPs in the PRLR gene, crucial for selective breeding.Communicated by Ramaswamy H. Sarma.

Computational analysis of non-synonymous single nucleotide polymorphism in the bovine PKLR gene.

Pyruvate kinase (PKLR) is a potential candidate gene for milk production traits in cows. The main aim of this work is to investigate the potentially deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in the PKLR gene by using several computational tools. In silico tools including SIFT, Polyphen-2, SNAP2 and Panther indicated only 18 nsSNPs out of 170 were considered deleterious. The analysis of proteins' stability change due to amino acid substitution performed by the use of the I-mutant, MUpro, CUPSTAT, SDM and Dynamut confirmed that 9 nsSNPs decreased protein stability. ConSurf analysis predicted that all 18 nsSNPs were evolutionary moderately or highly conserved. Two different domains of PKLR protein were revealed by the InterPro tool with 12 nsSNPs positioned in the Pyruvate Kinase barrel domain and 6 nsSNP present in the Pyruvate Kinase C Terminal. The PKLR 3D model was predicted by MODELLER software and validated via Ramachandran plot and Prosa which indicated a good quality model. The analysis of energy minimizations for the native and mutated structures was performed by SWISS PDB viewer with GROMOS 96 program and showed that 3 structural and 4 functional residues had total energy higher than the native model. These findings indicate that these mutant structures (rs441424814, rs449326723, rs476805413, rs472263384, rs474320860, rs475521477, rs441633284) were less stable than the native model. Molecular Dynamics simulations were performed to confirm the impact of nsSNPs on the protein structure and function. The present study provides useful information about functional SNPs that have an impact on PKLR protein in cattle.Communicated by Ramaswamy H. Sarma.

Identification of deleterious nsSNPs in human HGF gene: in silico approach.

HGF is a protein that binds to the hepatocyte growth factor receptor to regulate cell growth, cell motility and morphogenesis in different cells and tissues. Several bioinformatics tools and in silico methods were used to identify most deleterious nsSNPs that might change the structure and function of HGF protein. The in silico tools such as SIFT, SNP&GO and PolyPhen2 were used to distinguish deleterious nsSNPs from neutral ones. Protein stability is analysed by I-Mutant, MUpro and iStable. The functional and structural effects are predicted by other tools like MutPred2, Maestro, DUET etc. Analysis of structure was performed by HOPE and Mutation3D. SWISS-MODEL. server, was used for wild type and mutant proteins 3-D Modelling. Gene-gene and protein-protein interaction were predicted by GeneMANIA and STRING, respectively. The wildtype HGF protein and these three variants were independently docked with their close interactor protein MET by the use of ClusPro. Our study suggested that out of 392 missense nsSNPs of the HGF gene, five nsSNPs (D358G, G648R, I550N, N175S and R220Q), are the most deleterious in HGF gene. Gene-gene interactions showed relation of HGF with other genes depicting its importance in several pathways and co-expressions. The protein-protein interacting network is composed of 11 nodes. Analysis of protein stability by different tools indicated that the five nsSNPS decreased the stability of the protein. Anyway these nsSNPs need a confirmation analysis by experimental investigation and GWAS studiesCommunicated by Ramaswamy H. Sarma.

In silico Structural, Functional and Phylogenetic Analyses of cellulase from Ruminococcus albus.

BACKGROUND: Cellulose is the primary component of the plant cell wall and an important source of energy for the ruminant and microbial protein synthesis in the rumen. Cell wall content is digested by anaerobic fermentation activity mainly of bacteria belonging to species Fibrobacter succinogenes, Ruminicoccus albus, Ruminococcus flavefaciens, and Butyrivibrio fibrisolvens. Bacteria belonging to the species Ruminococcus albus contain cellulosomes that enable it to adhere to and digest cellulose, and its genome encodes cellulases and hemicellulases. This study aimed to perform an in silico comparative characterization and functional analysis of cellulase from Ruminococcus albus to explore physicochemical properties and to estimate primary, secondary, and tertiary structure using various bio-computational tools. The protein sequences of cellulases belonging to 6 different Ruminococcus albus strains were retrieved using UniProt. In in silico composition of amino acids, basic physicochemical characteristics were analyzed using ProtParam and Protscale. Multiple sequence alignment of retrieved sequences was performed using Clustal Omega and the phylogenetic tree was constructed using Mega X software. Bioinformatics tools are used to better understand and determine the 3D structure of cellulase. The predicted model was refined by ModRefiner. Structure alignment between the best-predicted model and the template is applied to evaluate the similarity between structures. RESULTS: In this study are demonstrated several physicochemical characteristics of the cellulase enzyme. The instability index values indicate that the proteins are highly stable. Proteins are dominated by random coils and alpha helixes. The aliphatic index was higher than 71 providing information that the proteins are highly thermostable. No transmembrane domain was found in the protein, and the enzyme is extracellular and moderately acidic. The best tertiary structure model of the enzyme was obtained by the use of Raptor X, which was refined by ModRefiner. Raptor X suggested the 6Q1I_A as one of the best homologous templates for the predicted 3D protein structure. Ramachandran plot analysis showed that 90.1% of amino acid residues are within the most favored regions. CONCLUSIONS: This study provides for the first time insights about the physicochemical properties, structure, and function of cellulase, from Ruminococcus albus, that will help for detection and identification of such enzyme in vivo or in silico.

On the origin of European sheep as revealed by the diversity of the Balkan breeds and by optimizing population-genetic analysis tools.

BACKGROUND: In the Neolithic, domestic sheep migrated into Europe and subsequently spread in westerly and northwesterly directions. Reconstruction of these migrations and subsequent genetic events requires a more detailed characterization of the current phylogeographic differentiation. RESULTS: We collected 50 K single nucleotide polymorphism (SNP) profiles of Balkan sheep that are currently found near the major Neolithic point of entry into Europe, and combined these data with published genotypes from southwest-Asian, Mediterranean, central-European and north-European sheep and from Asian and European mouflons. We detected clines, ancestral components and admixture by using variants of common analysis tools: geography-informative supervised principal component analysis (PCA), breed-specific admixture analysis, across-breed [Formula: see text] profiles and phylogenetic analysis of regional pools of breeds. The regional Balkan sheep populations exhibit considerable genetic overlap, but are clearly distinct from the breeds in surrounding regions. The Asian mouflon did not influence the differentiation of the European domestic sheep and is only distantly related to present-day sheep, including those from Iran where the mouflons were sampled. We demonstrate the occurrence, from southeast to northwest Europe, of a continuously increasing ancestral component of up to 20% contributed by the European mouflon, which is assumed to descend from the original Neolithic domesticates. The overall patterns indicate that the Balkan region and Italy served as post-domestication migration hubs, from which wool sheep reached Spain and north Italy with subsequent migrations northwards. The documented dispersal of Tarentine wool sheep during the Roman period may have been part of this process. Our results also reproduce the documented 18th century admixture of Spanish Merino sheep into several central-European breeds. CONCLUSIONS: Our results contribute to a better understanding of the events that have created the present diversity pattern, which is relevant for the management of the genetic resources represented by the European sheep population.

Genetic diversity of Albanian goat breeds revealed by mtDNA sequence variation.

Albanian farmers have a long tradition in goat farming. Recently, several studies were carried out to determine genetic diversity of local goat populations, using molecular markers such as SNP (Single Nucleotide Polymorphisms), microsatellites and AFLP (Amplified Fragment Length Polymorphism). In the present study 77 mtDNA D-loop sequences from six different goat breeds were analysed. The results revealed 67 different haplotypes, with haplotype diversity ranging from 0.864 to 1 and nucleotide diversity values ranging from 0.016 to 0.106. The results showed that the studied breed grouped only in lineage A. The FST analysis indicated that 98.7% of the variation was found within the goat breeds and only 1.3% among them.