Exploring the Role of Non-synonymous and Deleterious Variants Identified in Colorectal Cancer: A Multi-dimensional Computational Scrutiny of Exomes.

Introduction: Colorectal cancers are the world's third most commonly diagnosed type of cancer. Currently, there are several diagnostic and treatment options to combat it. However, a delay in detection of the disease is life-threatening. Additionally, a thorough analysis of the exomes of cancers reveals potential variation data that can be used for early disease prognosis. Methods: By utilizing a comprehensive computational investigation, the present study aimed to reveal mutations that could potentially predispose to colorectal cancer. Ten colorectal cancer exomes were retrieved. Quality control assessments were performed using FastQC and MultiQC, gapped alignment to the human reference genome (hg19) using Bowtie2 and calling the germline variants using Haplotype caller in the GATK pipeline. The variants were filtered and annotated using SIFT and PolyPhen2 successfully categorized the mutations into synonymous, non-synonymous, start loss and stop gain mutations as well as marked them as possibly damaging, probably damaging and benign. This mutational profile helped in shortlisting frequently occurring mutations and associated genes, for which the downstream multi-dimensional expression analyses were carried out. Results: Our work involved prioritizing the non-synonymous, deleterious SNPs since these polymorphisms bring about a functional alteration to the phenotype. The top variations associated with their genes with the highest frequency of occurrence included LGALS8, CTSB, RAD17, CPNE1, OPRM1, SEMA4D, MUC4, PDE4DIP, ELN and ADRA1A. An in-depth multi-dimensional downstream analysis of all these genes in terms of gene expression profiling and analysis and differential gene expression with regard to various cancer types revealed CTSB and CPNE1 as highly expressed and overregulated genes in colorectal cancer. Conclusion: Our work provides insights into the various alterations that might possibly lead to colorectal cancer and suggests the possibility of utilizing the most important genes identified for wet-lab experimentation.

Spruce giga-genomes: structurally similar yet distinctive with differentially expanding gene families and rapidly evolving genes.

Spruces (Picea spp.) are coniferous trees widespread in boreal and mountainous forests of the northern hemisphere, with large economic significance and enormous contributions to global carbon sequestration. Spruces harbor very large genomes with high repetitiveness, hampering their comparative analysis. Here, we present and compare the genomes of four different North American spruces: the genome assemblies for Engelmann spruce (Picea engelmannii) and Sitka spruce (Picea sitchensis) together with improved and more contiguous genome assemblies for white spruce (Picea glauca) and for a naturally occurring introgress of these three species known as interior spruce (P. engelmannii × glauca × sitchensis). The genomes were structurally similar, and a large part of scaffolds could be anchored to a genetic map. The composition of the interior spruce genome indicated asymmetric contributions from the three ancestral genomes. Phylogenetic analysis of the nuclear and organelle genomes revealed a topology indicative of ancient reticulation. Different patterns of expansion of gene families among genomes were observed and related with presumed diversifying ecological adaptations. We identified rapidly evolving genes that harbored high rates of non-synonymous polymorphisms relative to synonymous ones, indicative of positive selection and its hitchhiking effects. These gene sets were mostly distinct between the genomes of ecologically contrasted species, and signatures of convergent balancing selection were detected. Stress and stimulus response was identified as the most frequent function assigned to expanding gene families and rapidly evolving genes. These two aspects of genomic evolution were complementary in their contribution to divergent evolution of presumed adaptive nature. These more contiguous spruce giga-genome sequences should strengthen our understanding of conifer genome structure and evolution, as their comparison offers clues into the genetic basis of adaptation and ecology of conifers at the genomic level. They will also provide tools to better monitor natural genetic diversity and improve the management of conifer forests. The genomes of four closely related North American spruces indicate that their high similarity at the morphological level is paralleled by the high conservation of their physical genome structure. Yet, the evidence of divergent evolution is apparent in their rapidly evolving genomes, supported by differential expansion of key gene families and large sets of genes under positive selection, largely in relation to stimulus and environmental stress response.

Non-random Codon Usage of Synonymous and Non-synonymous Mutations in the Human HLA-A Gene.

The structure and function of human leucocyte antigen (HLA-A) is well known and is an extremely variable protein. From the public HLA-A database, we chose 26 high frequency HLA-A alleles (45% of sequenced alleles). Using five arbitrary references from these alleles, we analyzed synonymous mutations at the third codon position (sSNP3) and non-synonymous mutations (NSM). Both mutation types showed non-random locations of 29 sSNP3 codons and 71 NSM codons in the five reference lists. Most sSNP3 codons show identical mutation types with many mutations resulting from cytosine deamination. We proposed 23 ancestral parents of sSNP3 in five reference sequences using conserved parents in five unidirectional codons and 18 majority parents in reciprocal codons. These 23 proposed ancestral parents show exclusive codon usage of G3 or C3 parents located on both DNA strands that mutate to A3 or T3 variants mostly (76%) by cytosine deamination The sSNP3 and NSM show clear separation of the two variant types with most sSNP3 located in conserved areas in exons 2, 3 and 4, compared to most NSM appearing in two Variable Areas with no sSNP3 in the latter parts of exons 2 (α1) and 3 (α2). The Variable Areas contain NSM (polymorphic) residues at the center of the groove that bind the foreign peptide. We find distinctly different mutation patterns in NSM codons from those of sSNP3. Namely, G-C to A-T mutation frequency was much smaller, suggesting that evolutional pressures of deamination and other mechanisms applied to the two areas are significantly different.

Non-synonymous SNPs variants of PRKCG and its association with oncogenes predispose to hepatocellular carcinoma.

BACKGROUND: PRKCG encodes PKC γ, which is categorized under the classical protein kinase C family. No studies have specifically established the relationship between PRKCG nsSNPs with structural and functional variations in PKC γ in the context of hepatocellular carcinoma (HCC). The present study aims to uncover this link through in-silico and experimental studies. METHODS: The 3D structure of PKC γ was predicted. Molecular Dynamic (MD) Simulations were run and estimates were made for interactions, stability, conservation and post-translational alterations between wild and mutant structures. The association of PRKCG levels with HCC survival rate was determined. Genotyping analyses were conducted to investigate the deleterious PRKCG nsSNP association with HCC. mRNA expression of PKC γ, HIF-1 alpha, AKT, SOCS3 and VEGF in the blood of controls and HCC patients was analyzed and a genetic cascade was constructed depicting these interactions. RESULTS: The expression level of studied oncogenes was compared to tumour suppressor genes. Through Alphafold, the 3D structure of PKC γ was explored. Fifteen SNPs were narrowed down for in-silico analyses that were identified in exons 5, 10 and 18 and the regulatory and kinase domain of PKC γ. Root mean square deviation and fluctuation along with the radius of gyration unveiled potential changes between the wild and mutated variant structures. Mutant genotype AA (homozygous) corresponding to nsSNP, rs386134171 had more frequency in patients with OR (2.446), RR (1.564) and P-values (< 0.0029) that highlights its significant association with HCC compared to controls in which the wild genotype GG was found more prevalent. CONCLUSION: nsSNP rs386134171 can be a genetic marker for HCC diagnosis and therapeutic studies. This study has laid down a road map for future studies to be conducted on HCC.

Characterisation of SARS-CoV-2 clades based on signature SNPs unveils continuous evolution.

Since the emergence of SARS-CoV-2 in Wuhan, China more than a year ago, it has spread across the world in a very short span of time. Although, different forms of vaccines are being rolled out for vaccination programs around the globe, the mutation of the virus is still a cause of concern among the research communities. Hence, it is important to study the constantly evolving virus and its strains in order to provide a much more stable form of cure. This fact motivated us to conduct this research where we have initially carried out multiple sequence alignment of 15359 and 3033 global dataset without Indian and the dataset of exclusive Indian SARS-CoV-2 genomes respectively, using MAFFT. Subsequently, phylogenetic analyses are performed using Nextstrain to identify virus clades. Consequently, the virus strains are found to be distributed among 5 major clades or clusters viz. 19A, 19B, 20A, 20B and 20C. Thereafter, mutation points as SNPs are identified in each clade. Henceforth, from each clade top 10 signature SNPs are identified based on their frequency i.e. number of occurrences in the virus genome. As a result, 50 such signature SNPs are individually identified for global dataset without Indian and dataset of exclusive Indian SARS-CoV-2 genomes respectively. Out of each 50 signature SNPs, 39 and 41 unique SNPs are identified among which 25 non-synonymous signature SNPs (out of 39) resulted in 30 amino acid changes in protein while 27 changes in amino acid are identified from 22 non-synonymous signature SNPs (out of 41). These 30 and 27 amino acid changes for the non-synonymous signature SNPs are visualised in their respective protein structure as well. Finally, in order to judge the characteristics of the identified clades, the non-synonymous signature SNPs are considered to evaluate the changes in proteins as biological functions with the sequences using PROVEAN and PolyPhen-2 while I-Mutant 2.0 is used to evaluate their structural stability. As a consequence, for global dataset without Indian sequences, G251V in ORF3a in clade 19A, F308Y and G196V in NSP4 and ORF3a in 19B are the unique amino acid changes which are responsible for defining each clade as they are all deleterious and unstable. Such changes which are common for both global dataset without Indian and dataset of exclusive Indian sequences are R203M in Nucleocapsid for 20B, T85I and Q57H in NSP2 and ORF3a respectively for 20C while for exclusive Indian sequences such unique changes are A97V in RdRp, G339S and G339C in NSP2 in 19A and Q57H in ORF3a in 20A.

Structural Consequences of IRS-2 nsSNPs and Implication for Insulin Receptor Substrate-2 Protein Stability.

Single-Nucleotide Polymorphisms (SNPs) are common genetic variations implicated in human diseases. The non-synonymous SNPs (nsSNPs) affect the proteins' structures and their molecular interactions with other interacting proteins during the accomplishment of biochemical processes. This ultimately causes proteins functional perturbation and disease phenotypes. The Insulin receptor substrate-2 (IRS-2) protein promotes glucose absorption and participates in the biological regulation of glucose metabolism and energy production. Several IRS-2 SNPs are reported in association with type 2 diabetes and obesity in human populations. However, there are no comprehensive reports about the protein structural consequences of these nsSNPs. Keeping in view the pathophysiological consequences of the IRS-2 nsSNPs, we designed the current study to understand their possible structural impact on coding protein. The prioritized list of the deleterious IRS-2 nsSNPs was acquired from multiple bioinformatics resources, including VEP (SIFT, PolyPhen, and Condel), PROVEAN, SNPs&GO, PMut, and SNAP2. The protein structure stability assessment of these nsSNPs was performed by MuPro and I-Mutant-3.0 servers via structural modeling approaches. The atomic-level structural and molecular dynamics (MD) impact of these nsSNPs were examined using GROMACS 2019.2 software package. The analyses initially predicted 8 high-risk nsSNPs located in the highly conserved regions of IRS-2. The MD simulation analysis eventually prioritized the N232Y, R218C, and R104H nsSNPs that predicted to significantly compromise the structure stability and may affect the biological function of IRS-2. These nsSNPs are predicted as high-risk candidates for diabetes and obesity. The validation of protein structural impact of these shortlisted nsSNPs may provide biochemical insight into the IRS-2-mediated type-2 diabetes.

An Integrated Computational Analysis of High-Risk SNPs in Angiopoietin-like Proteins (ANGPTL3 and ANGPTL8) Reveals Perturbed Protein Dynamics Associated with Cancer.

Angiopoietin-like proteins (ANGPTL) constitute a family of eight proteins (1-8) which play a pivotal role in the regulation of various pathophysiological processes. The current study sought to identify high-risk, "non-synonymous, single-nucleotide polymorphisms" (nsSNPs) in both ANGPTL3 and ANGPTL8 to evaluate the role that these nsSNPs play in various types of cancer. We retrieved a total of 301 nsSNPs from various databases; 79 of these candidates constitute high-risk nsSNPs. Moreover, we identified eleven high-risk nsSNPs that cause various types of cancer: seven candidates for ANGPTL3 (L57H, F295L, L309F, K329M, R332L, S348C, and G409R) and four candidates for ANGPTL8 (P23L, R85W, R138S, and E148D). Protein-protein interaction analysis revealed a strong association of ANGPTL proteins with several tumor-suppressor proteins such as ITGB3, ITGAV, and RASSF5. 'Gene-expression profiling interactive analysis' (GEPIA) showed that expression of ANGPTL3 is significantly downregulated in five cancers: sarcoma (SARC); cholangio carcinoma (CHOL); kidney chromophobe carcinoma (KICH); kidney renal clear cell carcinoma (KIRC); and kidney renal papillary cell carcinoma (KIRP). GEPIA also showed that expression of ANGPTL8 remains downregulated in three cancers: CHOL; glioblastoma (GBM); and breast invasive carcinoma (BRCA). Survival rate analysis indicated that both upregulation and downregulation of ANGPTL3 and ANGPTL8 leads to low survival rates in various types of cancer. Overall, the current study revealed that both ANGPTL3 and ANGPTL8 constitute potential prognostic biomarkers for cancer; moreover, nsSNPs in these proteins might lead to the progression of cancer. However, further in vivo investigation will be helpful to validate the role of these proteins in the biology of cancer.

Membrane Anchorage-Induced (MAGIC) Knockdown of Non-synonymous Point Mutations.

The promise of personalized medicine for monogenic and complex polygenic diseases depends on the availability of strategies for targeted inhibition of disease-associated polymorphic protein variants. Loss of function variants, including non-synonymous single nucleotide variants (nsSNVs) and insertion/deletion producing a frameshift, account for the vast majority of disease-related genetic changes. Because it is challenging to interpret the functional consequences of nsSNVs, they are considered a big barrier for personalized medicine. A method for inhibiting the specific expression of nsSNVs without editing the human genome will facilitate the elucidation of the biology of nsSNVs, but such a method is currently lacking. Here, I describe the phenomenon of membrane anchorage-induced (MAGIC) knockdown of allele-specific inhibition of protein and mRNA expression upon inner membrane tethering of point mutation-specific monoclonal antibodies (mAb). This phenomenon is likely mediated by a mechanism distinct from the protein degradation pathways, as the epitope-specific knockdown is replicated upon intracellular expression of a membrane-anchored single domain intrabody that lacks the Fc domain of the mAb. By harnessing the MAGIC knockdown of epitope-containing protein targets, I report a novel approach for inhibiting the expression of amino-acid-altering germline and somatic nsSNVs. As a proof-of-concept, I show the inhibition of human disease-associated variants namely, FGFR4 p.G388R, KRAS p.G12D and BRAF p.V600E protein variants. This method opens up a new avenue for not just therapeutic suppression of undruggable protein variants, but also for functional interrogation of the nsSNVs of unknown significance.

Elucidation of molecular mechanism for colistin resistance among Gram-negative isolates from tertiary care hospitals.

Antimicrobial resistance is a growing concern of global public health. The emergence of colistin-resistance among carbapenem-resistant (CPR) Gram-negative bacteria causing fear of pan-resistance, treatment failure, and high mortality across the globe. AIM: To determine the genotypic colistin-resistance mechanisms among colistin-resistant (CR)Gram-negative clinical isolates along with genomic insight into hypermucoviscous(hv)-CR-Klebsiella pneumoniae. METHODS: Phenotypic colistin-resistance via broth-microdilution method. PCR-based detection of plasmid-mediated colistin resistance genes(mcr-1,2,3). Characterization of selected hvCR-K. pneumoniae via Whole-genome sequencing. RESULTS: Phenotypic colistin-resistance was 28% among CPR-Gram-negative isolates of which 90% of CR-isolates displayed MDR profile with overall low plasmid-mediated colistin resistance (mcr-2 = 9.4%;mcr-3 = 6%). Although K. pneumoniae isolates showed the highest phenotypic colistin-resistance (51%) however, relatively low plasmid-mediated gene-carriage (mcr-2 = 11.5%;mcr-3 = 3.4%) pointed toward other mechanisms of colistin-resistance. mcr-negative CR-K. pneumoniae displaying hv-phenotype were subjected to WGS. In-silico analysis detected 7-novel mutations in lipid-A modification genes includes eptA(I38V; V50L; A135P), opgE(M53L; T486A; G236S), and arnD(S164P) in addition to several non-synonymous mutations in lipid-A modification genes conferring resistance to colistin. Insertion of 6.6-kb region harboring putative-PEA-encoding gene(yjgX) was detected for the first time in K. pneumoniae (hvCRKP4771). In-silico analysis further confirmed the acquisition of not only MDR determinants but several hypervirulent-determinants displaying a convergent phenotype. CONCLUSION: overall high prevalence of phenotypic colistin resistance but low mcr-gene carriage suggested complex chromosomal mediated resistance mechanism especially in K. pneumoniae isolates. The presence of novel mutations in lipid-A modification genes and the acquisition of putative-PEA-encoding gene by hvCR-K. pneumoniae points toward the role of chromosomal determinants conferring resistance to colistin in the absence of mcr-genes.

In silico analysis of non-synonymous missense SNPs (nsSNPs) in CPE, GNAS genes and experimental validation in type II diabetes mellitus through Next Generation Sequencing.

Non-synonymous missense SNPs (nsSNPs) in CPE and GNAS genes were investigated computationally. In silico identified nsSNPs were experimentally validated in type II diabetes mellitus (T2DM) in Pakistani Pathan population using next generation sequencing (NGS). Sixty two high-risk nsSNPs in CPE and 44 in GNAS were identified. Only 12 in GNAS were clinically significant. Thirty six high-risk nsSNPs in CPE and 08 clinically significant nsSNPs in GNAS lies in the most conserved regions. I-mutant predicted that nsSNPs decrease the proteins stability and ModPred predicted 20 and 12 post-translational modification sites in CPE and GNAS proteins respectively. Ramachandran plot showed 88.7% residues are in the most favored region of protein models. By experimentation, none of the nsSNPs were found to be associated with T2DM. In conclusion, this study differentiates the deleterious nsSNPs from the neutral ones. Although nsSNPs are not associated with T2DM, they can be targeted in other CPE and GNAS genes related disorders.

Vaccine design based on 16 epitopes of SARS-CoV-2 spike protein.

The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) urgently requires an effective vaccine for prevention. In this study, 66 epitopes containing pentapeptides of SARS-CoV-2 spike protein in the IEDB database were compared with the amino acid sequence of SARS-CoV-2 spike protein, and 66 potentially immune-related peptides of SARS-CoV-2 spike protein were obtained. Based on the single-nucleotide polymorphisms analysis of spike protein of 1218 SARS-CoV-2 isolates, 52 easily mutated sites were identified and used for vaccine epitope screening. The best vaccine candidate epitopes in the 66 peptides of SARS-CoV-2 spike protein were screened out through mutation and immunoinformatics analysis. The best candidate epitopes were connected by different linkers in silico to obtain vaccine candidate sequences. The results showed that 16 epitopes were relatively conservative, immunological, nontoxic, and nonallergenic, could induce the secretion of cytokines, and were more likely to be exposed on the surface of the spike protein. They were both B- and T-cell epitopes, and could recognize a certain number of HLA molecules and had high coverage rates in different populations. Moreover, epitopes 897-913 were predicted to have possible cross-immunoprotection for SARS-CoV and SARS-CoV-2. The results of vaccine candidate sequences screening suggested that sequences (without linker, with linker GGGSGGG, EAAAK, GPGPG, and KK, respectively) were the best. The proteins translated by these sequences were relatively stable, with a high antigenic index and good biological activity. Our study provided vaccine candidate epitopes and sequences for the research of the SARS-CoV-2 vaccine.

Deleterious missense variants in the aflatoxin biosynthesis genes explain the low toxicity of Aspergillus flavus from infected rice.

Aspergillus flavus is one of the most natural contaminants of the improperly stored rice grains. It produces several secondary metabolites, like aflatoxins, which are well known hepatotoxic, hepatocarcinogenic and mutagenic agents. This study describes the in silico consequences of the missense mutations identified in several genes of aflatoxins biosynthesis in rice-contaminating A. flavus isolates. In the in vitro portion of the study, aflatoxins production profile was measured, and PCR-single strand-conformation polymorphism (SSCP)-sequencing method was used to genotype the studied genetic loci: aflP, aflM, aflR, PEP, and cob. Results showed aflatoxigenic potential in 79 out of 109 A. flavus isolates. Twenty-two missense and fifty-five synonymous mutations were found to be distributed variably on the studied loci. In the in silico portion of this study, several computations were utilized to predict the effect of each observed missense mutation on proteins structure, function, and stability. Seven mutations (O-methyl transferase: p.G256C; ver-1 dehydrogenase: p.K179 N and p.V183L; aspergillopepsin-1: p.P137L, p.S138F, p.G154C, and p.S158C) were found to be highly deleterious among the missense variants with damaging effects on their proteins' structure and function. In contrast to these detected variations in the aflatoxigenic loci, all missense mutations in the control non-aflatoxigenic cob gene were found to be neutral. These findings indicated that the observed mutations may reduce the concomitant biohazard of their biosynthesized aflatoxins. The current findings suggest that the naturally available variants may reduce or eliminates the dangerous consequences of aflatoxins upon ingesting the rice infected with A. flavus. To the best of our knowledge, this study is the first comprehensive report to analyze the missense mutations on the aflatoxin biosynthesis genes using in vitro and the state-of-art bio-computational tools.

SARS-CoV2 envelope protein: non-synonymous mutations and its consequences.

In the NCBI database, as on June 6, 2020, total number of available complete genome sequences of SARS-CoV2 across the world is 3617. The envelope (E) protein of SARS-CoV2 possesses several non-synonymous mutations over the transmembrane and C-terminus domains in 15 (0.414%) genomes among 3617 SARS-CoV2 genomes, analyzed. More precisely, 10(0.386%) out of 2588 genomes from the USA, 3(0.806%) from Asia, 1 (0.348%) from Europe and 1 (0.274%) from Oceania contained the missense mutations over the E-protein of SARS-CoV2 genomes. The C-terminus motif DLLV has been to DFLV and YLLV in the proteins from QJR88103 (Australia: Victoria) and QKI36831 (China: Guangzhou) respectively, which might affect the binding of this motif with the host protein PALS1.

Identification and characterization of trait-specific SNPs using ddRAD sequencing in water buffalo.

Single Nucleotide Polymorphism (SNP) is one of the important molecular markers widely used in animal breeding program for improvement of any desirable genetic traits. Considering this, the present study was carried out to identify, annotate and analyze the SNPs related to four important traits of buffalo viz. milk volume, age at first calving, post-partum cyclicity and feed conversion efficiency. We identified 246,495, 168,202, 74,136 and 194,747 genome-wide SNPs related to mentioned traits, respectively using ddRAD sequencing technique based on 85 samples of Murrah Buffaloes. Distribution of these SNPs were highest (61.69%) and lowest (1.78%) in intron and exon regions, respectively. Under coding regions, the SNPs for the four traits were further classified as synonymous (4697) and non-synonymous (3827). Moreover, Gene Ontology (GO) terms of identified genes assigned to various traits. These characterized SNPs will enhance the knowledge of cellular mechanism for enhancing productivity of water buffalo through molecular breeding.

Variant effect predictions capture some aspects of deep mutational scanning experiments.

BACKGROUND: Deep mutational scanning (DMS) studies exploit the mutational landscape of sequence variation by systematically and comprehensively assaying the effect of single amino acid variants (SAVs; also referred to as missense mutations, or non-synonymous Single Nucleotide Variants - missense SNVs or nsSNVs) for particular proteins. We assembled SAV annotations from 22 different DMS experiments and normalized the effect scores to evaluate variant effect prediction methods. Three trained on traditional variant effect data (PolyPhen-2, SIFT, SNAP2), a regression method optimized on DMS data (Envision), and a naïve prediction using conservation information from homologs. RESULTS: On a set of 32,981 SAVs, all methods captured some aspects of the experimental effect scores, albeit not the same. Traditional methods such as SNAP2 correlated slightly more with measurements and better classified binary states (effect or neutral). Envision appeared to better estimate the precise degree of effect. Most surprising was that the simple naïve conservation approach using PSI-BLAST in many cases outperformed other methods. All methods captured beneficial effects (gain-of-function) significantly worse than deleterious (loss-of-function). For the few proteins with multiple independent experimental measurements, experiments differed substantially, but agreed more with each other than with predictions. CONCLUSIONS: DMS provides a new powerful experimental means of understanding the dynamics of the protein sequence space. As always, promising new beginnings have to overcome challenges. While our results demonstrated that DMS will be crucial to improve variant effect prediction methods, data diversity hindered simplification and generalization.

Solution structure and functional investigation of human guanylate kinase reveals allosteric networking and a crucial role for the enzyme in cancer.

Human guanylate kinase (hGMPK) is the only known enzyme responsible for cellular GDP production, making it essential for cellular viability and proliferation. Moreover, hGMPK has been assigned a critical role in metabolic activation of antiviral and antineoplastic nucleoside-analog prodrugs. Given that hGMPK is indispensable for producing the nucleotide building blocks of DNA, RNA, and cGMP and that cancer cells possess elevated GTP levels, it is surprising that a detailed structural and functional characterization of hGMPK is lacking. Here, we present the first high-resolution structure of hGMPK in the apo form, determined with NMR spectroscopy. The structure revealed that hGMPK consists of three distinct regions designated as the LID, GMP-binding (GMP-BD), and CORE domains and is in an open configuration that is nucleotide binding-competent. We also demonstrate that nonsynonymous single-nucleotide variants (nsSNVs) of the hGMPK CORE domain distant from the nucleotide-binding site of this domain modulate enzymatic activity without significantly affecting hGMPK's structure. Finally, we show that knocking down the hGMPK gene in lung adenocarcinoma cell lines decreases cellular viability, proliferation, and clonogenic potential while not altering the proliferation of immortalized, noncancerous human peripheral airway cells. Taken together, our results provide an important step toward establishing hGMPK as a potential biomolecular target, from both an orthosteric (ligand-binding sites) and allosteric (location of CORE domain-located nsSNVs) standpoint.

A-to-I mRNA editing in fungi: occurrence, function, and evolution.

A-to-I RNA editing is an important post-transcriptional modification that converts adenosine (A) to inosine (I) in RNA molecules via hydrolytic deamination. Although editing of mRNAs catalyzed by adenosine deaminases acting on RNA (ADARs) is an evolutionarily conserved mechanism in metazoans, organisms outside the animal kingdom lacking ADAR orthologs were thought to lack A-to-I mRNA editing. However, recent discoveries of genome-wide A-to-I mRNA editing during the sexual stage of the wheat scab fungus Fusarium graminearum, model filamentous fungus Neurospora crassa, Sordaria macrospora, and an early diverging filamentous ascomycete Pyronema confluens indicated that A-to-I mRNA editing is likely an evolutionarily conserved feature in filamentous ascomycetes. More importantly, A-to-I mRNA editing has been demonstrated to play crucial roles in different sexual developmental processes and display distinct tissue- or development-specific regulation. Contrary to that in animals, the majority of fungal RNA editing events are non-synonymous editing, which were shown to be generally advantageous and favored by positive selection. Many non-synonymous editing sites are conserved among different fungi and have potential functional and evolutionary importance. Here, we review the recent findings about the occurrence, regulation, function, and evolution of A-to-I mRNA editing in fungi.

The impracticalities of multiplicatively-closed codon models: a retreat to linear alternatives.

A matrix Lie algebra is a linear space of matrices closed under the operation [Formula: see text]. The "Lie closure" of a set of matrices is the smallest matrix Lie algebra which contains the set. In the context of Markov chain theory, if a set of rate matrices form a Lie algebra, their corresponding Markov matrices are closed under matrix multiplication; this has been found to be a useful property in phylogenetics. Inspired by previous research involving Lie closures of DNA models, it was hypothesised that finding the Lie closure of a codon model could help to solve the problem of mis-estimation of the non-synonymous/synonymous rate ratio, [Formula: see text]. We propose two different methods of finding a linear space from a model: the first is the linear closure which is the smallest linear space which contains the model, and the second is the linear version which changes multiplicative constraints in the model to additive ones. For each of these linear spaces we then find the Lie closures of them. Under both methods, it was found that closed codon models would require thousands of parameters, and that any partial solution to this problem that was of a reasonable size violated stochasticity. Investigation of toy models indicated that finding the Lie closure of matrix linear spaces which deviated only slightly from a simple model resulted in a Lie closure that was close to having the maximum number of parameters possible. Given that Lie closures are not practical, we propose further consideration of the two variants of linearly closed models.

Evaluation of computational techniques for predicting non-synonymous single nucleotide variants pathogenicity.

The human genetic diseases associated with many factors, one of these factors is the non-synonymous Single Nucleotide Variants (nsSNVs) cause single amino acid change with another resulting in protein function change leading to disease. Many computational techniques have been released to expect the impacts of amino acid alteration on protein function and classify mutations as pathogenic or neutral. Here in this article, we assessed the performance of eight techniques; FATHMM, SIFT, Provean, iFish, Mutation Assessor, PANTHER, SNAP2, and PON- P2 using a VaribenchSelectedPure dataset of 2144 pathogenic variants and 3777 neutral variants extracted from the free standard database "Varibench." The first five techniques achieve (45.60-83.75) % specificity, (52.64-94.13) % sensitivity, (51.00-88.90) % AUC, and (49.76-88.24) % ACC on whole dataset, while all eight techniques achieve (36.54-77.88) % specificity, (50.00-75.00) % sensitivity, (51.00-76.40) % AUC, and (25.00-77.78) % ACC on random sample dataset. We also created a Meta classifier (CSTJ48) that combines FATHMM, iFish, and Mutation Assessor. It registers 96.33% specificity, 86.07% sensitivity, 91.20% AUC, and 91.89 ACC. By comparing the results, it's clear that FATHMM gives the highest performance over the seven individual techniques, where it achieves 83.75% and 77.88% specificity, 94.13%, and 75.00% sensitivity, 88.90% and 76.40% AUC, and 88.24% and 77.78% ACC on whole and random sample dataset, respectively. Also, the launched Meta classifier (CSTJ48) is outperforming over all the eight individual tools that compared here.

Chloroplast genome of an extremely endangered conifer Thuja sutchuenensis Franch.: gene organization, comparative and phylogenetic analysis.

Thuja sutchuenensis is a critically endangered tertiary relict species of Cupressaceae from southwestern China. We sequenced the complete chloroplast (cp) genome of T. sutchuenensis, showing the genome content of 129,776 bp, 118 unique genes including 82 unique protein-coding genes, 32 tRNA genes, and 4 rRNA genes. The genome structures, gene order, and GC content are similar to other typical gymnosperm cp genomes. Thirty-eight simple sequence repeats were identified in the T. sutchuenensis cp genome. We also found an apparent inversion between trnT and psbK between genera Thuja and Thujopsis. In addition, positive selection signals were detected in seven genes with high Ka/Ks ratios. The reconstructed phylogeny based on locally collinear blocks of cp genomes among 21 gymnosperms species is similar to previous inferences. We also inferred a Late-Miocene divergence between T. sutchuenensis and T. standishii, according to the dating of ~ 11.05 Mya by cp genomes. These results will be helpful for future studies of Cupressaceae phylogeny as well as studies in population genetics, systematics, and cp genetic engineering.