Deleterious Single Nucleotide Polymorphisms Research Articles

Variability in predicted deleterious mutations among barley accessions conserved ex situ

AbstractUnderstanding the genetic cost for long‐term conservation of more than 7 million plant germplasm accessions in 1750 genebanks worldwide requires knowledge about the extent and variation of deleterious mutations within and among conserved germplasm collections. Our recent study revealed a wide range of mutations predicted to be deleterious to gene function and averaged sample‐wise mutation burden per deleterious locus across barley, wheat, oat, soybean, maize, rapa, and sunflower germplasm collections. Here we report the extent and variation of predicted deleterious mutations among nine accessions of a barley (Hordeum vulgare L.) collection from an RNA‐Seq analysis of 16 individual samples of each accession. The assayed accessions were found to vary significantly in the number and proportion of single nucleotide polymorphisms (SNPs) predicted to be deleterious mutations (ranging from 242 to 314 with a mean of 270 and from 0.00073 to 0.00099 with a mean of 0.00086, respectively). Similarly, a significant variation was also observed in the averaged sample‐wise mutation burden estimates per deleterious locus, ranging from 0.541 to 0.747 with a mean of 0.681. Cultivar accessions had higher averages in the proportions of the predicted deleterious SNPs and in the averaged sample‐wise mutation burden estimates than landrace accessions (0.00090 vs. 0.00082 and 0.695 vs. 0.663, respectively). The estimates of deleterious base‐substitution mutations (×10−8) for the nine accessions varied from 0.313 to 0.406 with a mean of 0.349. These within‐collection findings are useful for understanding the genetic cost in conserved germplasm and have implications for long‐term germplasm management and conservation.

Graph-Based Pan-Genome Reveals the Pattern of Deleterious Mutations during the Domestication of Saccharomyces cerevisiae.

The "cost of domestication" hypothesis suggests that the domestication of wild species increases the number, frequency, and/or proportion of deleterious genetic variants, potentially reducing their fitness in the wild. While extensively studied in domesticated species, this phenomenon remains understudied in fungi. Here, we used Saccharomyces cerevisiae, the world's oldest domesticated fungus, as a model to investigate the genomic characteristics of deleterious variants arising from fungal domestication. Employing a graph-based pan-genome approach, we identified 1,297,761 single nucleotide polymorphisms (SNPs), 278,147 insertion/deletion events (indels; <30 bp), and 19,967 non-redundant structural variants (SVs; ≥30 bp) across 687 S. cerevisiae isolates. Comparing these variants with synonymous SNPs (sSNPs) as neutral controls, we found that the majority of the derived nonsynonymous SNPs (nSNPs), indels, and SVs were deleterious. Heterozygosity was positively correlated with the impact of deleterious SNPs, suggesting a role of genetic diversity in mitigating their effects. The domesticated isolates exhibited a higher additive burden of deleterious SNPs (dSNPs) than the wild isolates, but a lower burden of indels and SVs. Moreover, the domesticated S. cerevisiae showed reduced rates of adaptive evolution relative to the wild S. cerevisiae. In summary, deleterious variants tend to be heterozygous, which may mitigate their harmful effects, but they also constrain breeding potential. Addressing deleterious alleles and minimizing the genetic load are crucial considerations for future S. cerevisiae breeding efforts.

Insights into the structure–function relationship of missense mutations in the human TOP2A protein in ovarian cancer

Topoisomerase 2-alpha (TOP2A) is a nuclear protein that is responsible for the maintenance of the topological state of DNA. TOP2A is highly upregulated in ovarian cancer, and its copy number is an important prognosis factor. A large number of single-nucleotide polymorphism (SNP), insertion, and deletion mutations have been reported in TOP2A. Thus, a structural and functional study of missense SNPs was carried out to screen potentially damaging mutations. The 193 non-synonymous SNPs in the coding region of TOP2A in the dbSNP database were selected for in silico analysis. The deleterious SNPs were screened using sorting intolerant from tolerant (SIFT), PolyPhen-2, SNAP2, and SNPs&amp;amp;Go, and we obtained four possibly damaging SNPs at the end (Y481C, N7741, E922K, and R1514W). Mutants Y481C and E922K were predicted to be highly deleterious and showed decreased protein stability compared with native proteins, as predicted by I-Mutant 3. We used the SWISS-MODEL to model the structure of these two mutants, and the structural attributes of modeled mutants were studied using Hope Project, solvent accessibility-based protein–protein interface identification and recognition (SPPIDER), SRide, and HBAT, which predicted small variations from the native protein. Molecular dynamics simulation demonstrated a decrease in root mean square deviation (RMSD) and the radius of gyration of two mutants, which is relative to the native protein. The molecular docking of TOP2A with etoposide suggests that mutations may lead to resistance to TOP2A-targeted chemotherapy. In addition, the relative expression analysis performed by qRT-PCR also reveals that there is a three-fold increase in the expression levels of the TOP2A protein in ovarian adenoma cancer cell lines. Our analysis reveals that Y481C and E922K are highly damaging variants of TOP2A, which alter the protein dynamics and may be implicated in causing ovarian cancer.

Investigating the Influence of ANTXR2 Gene Mutations on Protective Antigen Binding for Heightened Anthrax Resistance.

Bacillus anthracis is the bacterium responsible for causing the zoonotic disease called anthrax. The disease presents itself in different forms like gastrointestinal, inhalation, and cutaneous. Bacterial spores are tremendously adaptable, can persist for extended periods and occasionally endanger human health. The Anthrax Toxin Receptor-2 (ANTXR2) gene acts as membrane receptor and facilitates the entry of the anthrax toxin into host cells. Additionally, mutations in the ANTXR2 gene have been linked to various autoimmune diseases, including Hyaline Fibromatosis Syndrome (HFS), Ankylosing Spondylitis (AS), Juvenile Hyaline Fibromatosis (JHF), and Infantile Systemic Hyalinosis (ISH). This study delves into the genetic landscape of ANTXR2, aiming to comprehend its associations with diverse disorders, elucidate the impacts of its mutations, and pinpoint minimal non-pathogenic mutations capable of reducing the binding affinity of the ANTXR2 gene with the protective antigen. Recognizing the pivotal role of single-nucleotide polymorphisms (SNPs) in shaping genetic diversity, we conducted computational analyses to discern highly deleterious and tolerated non-synonymous SNPs (nsSNPs) in the ANTXR2 gene. The Mutpred2 server determined that the Arg465Trp alteration in the ANTXR2 gene leads to altered DNA binding (p = 0.22) with a probability of a deleterious mutation of 0.808; notably, among the identified deleterious SNPs, rs368288611 (Arg465Trp) stands out due to its significant impact on altering the DNA-binding ability of ANTXR2. We propose these SNPs as potential candidates for hypertension linked to the ANTXR2 gene, which is implicated in blood pressure regulation. Noteworthy among the tolerated substitutions is rs200536829 (Ala33Ser), recognized as less pathogenic; this highlights its potential as a valuable biomarker, potentially reducing side effects on the host while also reducing binding with the protective antigen protein. Investigating these SNPs holds the potential to correlate with several autoimmune disorders and mitigate the impact of anthrax disease in humans.

BRCA2 Polymorphisms and Breast Cancer Susceptibility: a Multi-Tools Bioinformatics Approach.

The main focus of this investigation is to identify deleterious single nucleotide polymorphisms (SNPs) located in the BRCA2 gene through in silico approach, thereby,providing an understanding of potential consequences regarding the susceptibility to breast cancer. The GenomAD database was used to identify SNPs. To determine the potential adverse consequences, our study employed various prediction tools, including SIFT, PolyPhen, PredictSNP, SNAP2, PhD-SNP, and ClinVar. The pathogenicity associated with the deleterious snSNPs was evaluated bu MutPred and Fathmm. Additionally, I-Mutant and MuPro were used to assess the stability, followed by conservation and protein-protein interaction analysis using robust computational tools. The 3D structure of BRCA2 protein was generated by SwissModel, followed by validation using PROCHECK and Errat. The GenomAD database was used to identify a total of 7, 921 SNPs, including 1940 missense SNPs. A set of 69 SNPs predicted by consensus to be damaging across all platforms was identified. Mutpred and Fathmm identified 48 and 38 SNPs, respectively to be associated with cancer. While I- Mutant and MuPro assays suggested 22 SNPs to decrease protein stability. Additionally, these 22 SNPs reside within highly conserved regions of the BRCA2 protein. Domain analysis, utilizing InterPro, pinpointed 18 deleterious mutations within crucial DNA binding domains and one in the BRC repeat region. This study establishes a foundation for future experimental validations and the creation of breast cancer-targeted treatment approaches.

Unraveling the function and structure impact of deleterious missense SNPs in the human OX1R receptor by computational analysis

The orexin/hypocretin receptor type 1 (OX1R) plays a crucial role in regulating various physiological functions, especially feeding behavior, addiction, and reward. Genetic variations in the OX1R have been associated with several neurological disorders. In this study, we utilized a combination of sequence and structure-based computational tools to identify the most deleterious missense single nucleotide polymorphisms (SNPs) in the OX1R gene. Our findings revealed four highly conserved and structurally destabilizing missense SNPs, namely R144C, I148N, S172W, and A297D, located in the GTP-binding domain. Molecular dynamics simulations analysis demonstrated that all four most detrimental mutant proteins altered the overall structural flexibility and dynamics of OX1R protein, resulting in significant changes in the structural organization and motion of the protein. These findings provide valuable insights into the impact of missense SNPs on OX1R function loss and their potential contribution to the development of neurological disorders, thereby guiding future research in this field.

Genomic evidence for climate-linked diversity loss and increased vulnerability of wild barley spanning 28 years of climate warming

The information on how plant populations respond genetically to climate warming is scarce. Here, landscape genomic and machine learning approaches were integrated to assess genetic response of 10 wild barley (Hordeum vulgare ssp. spontaneum; WB) populations in the past and future, using whole genomic sequencing (WGS) data. The WB populations were sampled in 1980 and again in 2008. Phylogeny of accessions was roughly in conformity with sampling sites, which accompanied by admixture/introgressions. The 28-y climate warming resulted in decreased genetic diversity, increased selection pressure, and an increase in deleterious single nucleotide polymorphism (dSNP) numbers, heterozygous deleterious and total deleterious burdens for WB. Genome-environment associations identified some candidate genes belonging to peroxidase family (HORVU2Hr1G057450, HORVU4Hr1G052060 and HORVU4Hr1G057210) and heat shock protein 70 family (HORVU2Hr1G112630). The gene HORVU2Hr1G120170 identified by selective sweep analysis was under strong selection during the climate warming of the 28-y, and its derived haplotypes were fixed by WB when faced with the 28-y increasingly severe environment. Temperature variables were found to be more important than precipitation variables in influencing genomic variation, with an eco-physiological index gdd5 (growing degree-days at the baseline threshold temperature of 5 °C) being the most important determinant. Gradient forest modelling revealed higher predicted genomic vulnerability in Sede Boqer under future climate scenarios at 2041–2070 and 2071–2100. Additionally, estimates of effective population size (Ne) tracing back to 250 years indicated a forward decline in all populations over time. Our assessment about past genetic response and future vulnerability of WB under climate warming is crucial for informing conservation efforts for wild cereals and rational use strategies.

Genetic Variations in the Purinergic P2X7 Receptor Are Associated with the Immune Response to Ocular Toxoplasmosis in Colombia.

Ocular toxoplasmosis (OT) is characterized by inflammation within the eye and is the most recognized clinical manifestation of toxoplasmosis. The objective of this study was to identify new single-nucleotide polymorphisms (SNPs) in the P2RX7 gene that may have significance in the immune response to OT in Colombian patients. A case-control study was conducted to investigate the associations between SNPs (rs1718119 and rs2230912) in the P2RX7 gene and OT in 64 Colombian patients with OT and 64 controls. Capillary electrophoresis was used to analyze the amplification products, and in silico algorithms were employed to predict deleterious SNPs. Stability analysis of amino acid changes indicated that both mutations could lead to decreased protein structure stability. A nonsynonymous SNP, Gln460Arg, located in the long cytoplasmic tail of the receptor, showed a significant association with OT (Bonferroni correction (BONF) = 0.029; odds ratio OR = 3.46; confidence interval CI: 1.05 to 11.39), while no significant association between rs1718119 and OT risk was observed. Based on the 3D structure analysis of the P2RX7 protein trimer, it is hypothesized that an increase in the flexibility of the cytoplasmic domain of this receptor could alter its function. This SNP could potentially serve as a biomarker for identifying Colombian patients at risk of OT.

Unveiling the Molecular Mechanisms Behind the Devastating Impact of the ALK Protein on Pediatric Cancers: Insights into Deleterious SNPs through In Silico Predictions, Molecular Docking, and Dynamics Studies

Abstract Introduction Pediatric cancers present significant challenges in terms of diagnosis and treatment, and the anaplastic lymphoma kinase (ALK) protein has emerged as a crucial molecular target in these malignancies. ALK, a receptor tyrosine kinase, plays a vital role in normal cellular processes, but genetic alterations and aberrant activation of the ALK gene have been implicated in various pediatric cancer types. While genetic alterations have been well studied, the precise molecular mechanisms underlying the pathogenicity of the ALK protein in pediatric cancers remain poorly understood. Objective In this study, the primary objective is to uncover the molecular mechanisms associated with the effects of deleterious single-nucleotide polymorphisms (SNPs) on the structure and functionality of the ALK protein. Material and Methods Several known point mutations of the ALK protein were taken for the in silico predictions such as PolyPhen-2, SIFT, PANTHER, PredictSNP, etc., residue conservation analysis using Consurf server, molecular docking (AutoDock), and molecular dynamics simulation studies (GROMACS). Results The computation predictions found that the studied variants are deleterious in different tools. The residue conservation analysis reveals all the variants are located in highly conserved regions. The molecular docking study of wild-type and mutant structures with the crizotinib drug molecule found the variants were modulating the binding cavity and had a strong impact on the binding affinity. The binding energy of the wild-type is –5.896 kcal/mol, whereas the mutants have –9.988 kcal/mol. The specific amino acid Ala1200 of wild-type was found to interact with crizotinib, and Asp1203 residue was found to interact predominantly in the mutant structures. Conclusion The simulation study differentiates the variants in terms of structural stability and residue fluctuation. Among the studied variants, R1275Q, F1245V, and F1174L had strong deleterious effects, structural changes, and pathogenicity based on the in silico predictions. By elucidating the functional consequences of deleterious mutations within the ALK gene, this research may uncover novel therapeutic targets and personalized medicine approaches for the management of pediatric cancers. Ultimately, gaining insights into the molecular mechanisms of the ALK protein's role in driving response and resistance will contribute to improving patient outcomes and advancing our understanding of this complex disease.

Prediction of Deleterious Non-Synonymous Single Nucleotide Polymorphism of Cathelicidin

Background: Cathelicidin, a human host defense peptide, plays a salubrious role in innate host defense against human pathogens. Despite the extensive studies on the antimicrobial function of Cathelicidin, there is a lack of information on this peptide's deleterious single nucleotide polymorphisms (SNPs) that potentially alter the disease susceptibility and hence the current study. Objective: To predict Cathelicidin's structural and functional deleterious non-synonymous single nucleotide polymorphisms. Methods: The non-synonymous SNPs of Cathelicidin were investigated using computational prediction tools like SIFT, Polyphen, PROVEAN, MusiteDeep, I-Mutant, and STRING. Results: The present study predicted 23 potentially harmful nsSNP of Cathelicidin. Among these, 14 were highly conserved, 8 were average conserved, and 1 alone was variable. Phosphorylation was observed in serine and threonine residues using post-translational modification. Further mutation 3D predicted 11 clustered and 13 covered mutations in cathelicidin variants. The structural distribution of high-risk nsSNPs predicted 80 alpha helixes, 0 random coils, 19 extended strands, and 4 beta turns. Among 23 predicted deleterious SNPs, 9 nsSNPs alone showed mutation effect based on the HOPE structural and functional analysis. The direct functional interaction pattern of Cathelicidin with other proteins, FPR2, PRTN3, TLR9, IGF1R, and JUN, was observed. Conclusion: The identified deleterious nsSNPs could help understand the mutation effect of Cathelicidin in disease susceptibility and drug discovery.

Discovering Deleterious Single Nucleotide Polymorphisms of Human AKT1 Oncogene: An In Silico Study.

AKT1 is a serine/threonine kinase necessary for the mediation of apoptosis, angiogenesis, metabolism, and cell proliferation in both normal and cancerous cells. The mutations in the AKT1 gene have been associated with different types of cancer. Further, the AKT1 gene mutations are also reported to be associated with other diseases such as Proteus syndrome and Cowden syndromes. Hence, this study aims to identify the deleterious AKT1 missense SNPs and predict their effect on the function and structure of the AKT1 protein using various computational tools. Extensive in silico approaches were applied to identify deleterious SNPs of the human AKT1 gene and assessment of their impact on the function and structure of the AKT1 protein. The association of these highly deleterious missense SNPs with different forms of cancers was also analyzed. The in silico approach can help in reducing the cost and time required to identify SNPs associated with diseases. In this study, 12 highly deleterious SNPs were identified which could affect the structure and function of the AKT1 protein. Out of the 12, four SNPs-namely, G157R, G159V, G336D, and H265Y-were predicted to be located at highly conserved residues. G157R could affect the ligand binding to the AKT1 protein. Another highly deleterious SNP, R273Q, was predicted to be associated with liver cancer. This study can be useful for pharmacogenomics, molecular diagnosis of diseases, and developing inhibitors of the AKT1 oncogene.

Construction and evaluation of the functional polygenic risk score for gastric cancer in a prospective cohort of the European population.

A polygenic risk score (PRS) derived from 112 single-nucleotide polymorphisms (SNPs) for gastric cancer has been reported in Chinese populations (PRS-112). However, its performance in other populations is unknown. A functional PRS (fPRS) using functional SNPs (fSNPs) may improve the generalizability of the PRS across populations with distinct ethnicities. We performed functional annotations on SNPs in strong linkage disequilibrium (LD) with the 112 previously reported SNPs to identify fSNPs that affect protein-coding or transcriptional regulation. Subsequently, we constructed an fPRS based on the fSNPs by using the LDpred2-infinitesimal model and then analyzed the performance of the PRS-112 and fPRS in the risk prediction of gastric cancer in 457,521 European participants of the UK Biobank cohort. Finally, the performance of the fPRS in combination with lifestyle factors were evaluated in predicting the risk of gastric cancer. During 4,582,045 person-years of follow-up with a total of 623 incident gastric cancer cases, we found no significant association between the PRS-112 and gastric cancer risk in the European population (hazard ratio [HR] = 1.00 [95% confidence interval (CI) 0.93-1.09], P = 0.846). We identified 125 fSNPs, including seven deleterious protein-coding SNPs and 118 regulatory non-coding SNPs, and used them to constructed the fPRS-125. Our result showed that the fPRS-125 was significantly associated with gastric cancer risk (HR = 1.11 [95% CI, 1.03-1.20], P = 0.009). Compared to participants with a low fPRS-125 (bottom quintile), those with a high fPRS-125 (top quintile) had a higher risk of incident gastric cancer (HR = 1.43 [95% CI, 1.12-1.84], P = 0.005). Moreover, we observed that participants with both an unfavorable lifestyle and a high genetic risk had the highest risk of incident gastric cancer (HR = 4.99 [95% CI, 1.55-16.10], P = 0.007) compared to those with both a favorable lifestyle and a low genetic risk. These results indicate that the fPRS-125 derived from fSNPs may act as an indicator to measure the genetic risk of gastric cancer in the European population.

High risk genetic variants of human insulin receptor substrate 1(IRS1) infer structural instability and functional interference

Insulin receptor substrate 1(IRS1) is a signaling adapter protein encoded by the IRS1 gene. This protein delivers signals from insulin and insulin-like growth factor-1(IGF-1) receptors to the phosphatidylinositol 3-kinases (P13K)/protein kinase B (Akt) and Extracellular signal-regulated kinases (Erk) - Mitogen-activated protein (MAP) kinase pathways, which regulate particular cellular processes. Mutations in this gene have been linked to type 2 diabetes mellitus, a heightened risk of insulin resistance, and an increased likelihood of developing a number of different malignancies. The structure and function of IRS1 could be severely compromised as a result of single nucleotide polymorphism (SNP) type genetic variants. In this study, we focused on identification of the most harmful non-synonymous SNPs (nsSNPs) of the IRS1 gene as well as prediction of their structural and functional consequences. Six different algorithms made the initial prediction that 59 of the 1142 IRS1 nsSNPs would have a negative impact on the protein structure. In-depth evaluations detected 26 nsSNPs located inside the functional domains of IRS1. Following that, 16 nsSNPs were identified as more harmful based on conservation profile, hydrophobic interaction, surface accessibility, homology modelling, and inter-atomic interactions. Following an in-depth analysis of protein stability, M249T (rs373826433), I223T (rs1939785175) and V204G (rs1574667052) were identified as three most deleterious SNPs and were subjected to molecular dynamics simulation for further insights. These findings will help us understand the implications for disease susceptibility, cancer progression, and the efficacy of therapeutic development against IRS1 gene mutants. Communicated by Ramaswamy H. Sarma

Comprehensive analysis of non-synonymous SNPs related to Parkinson’s disease and molecular dynamics simulation of PRKN mutants

Parkinson’s disease (PD) is associated with a mutation in the PRKN (Parkin RBR E3 Ubiquitin Protein Ligase). PRKN functions as maintaining dopamine (DA) neuronal homeostasis and homeostasis dysfunction, which play an important role in early PD onset. The main objective behind this work is to identify PRKN deleterious single nucleotide polymorphism (SNPs) by computational analysis and implement molecular dynamic simulation (MDS) to study the structural and functional properties of native and mutant proteins. We found A46T, I23T, C212Y, D243N, E28G, G359D, P37L, Q34R, R256C, R275W, R366W, and R402C as the most delirious and disease-linked by using different bioinformatics tools such as ANNOVAR (SIFT & POLYPHEN2) annotation, SNPs & GO, PROVEAN, and I-Mutant3.0. To understand protein functionality and atomic arrangement in 3-D space, the comparative modeling of native and mutant PRKN protein (A46T, I23T, C212Y, D243N, E28G, G359D, P37L, Q34R, R256C, R275W, R366W, and R402C) was performed with standalone MODELLER 9.15 program. Finally, MDS analysis was done by using the GROMACS 5.1.5 comprehensive package to study the structural stability and dynamic perturbations in native and mutant PRKN proteins. MDS analysis shows more flexibility in native structures in comparison to mutant structures. Mutant structures show structural perturbation and result in loss of PRKN protein function. The findings of this study might assist wet-lab studies to create effective pharmacological treatments against PD targeting PRKN.

The prevalence of deleterious mutations during the domestication and improvement of soybean

Soybean (Glycine max L.) is a protein and oil crop grown worldwide. Its fitness may be reduced by deleterious mutations, whose identification and purging is desirable for crop breeding. In the published whole-genome re-sequenced data of 2214 soybean accessions, including 221 wild soybean, 1132 landrace cultivars and 861 improved soybean lines, we identified 115,275 deleterious single-nucleotide polymorphisms (SNPs). Numbers of deleterious alleles increased from wild soybeans to landraces and decreased from landraces to modern improved lines. Genes in selective-sweep regions showed fewer deleterious mutations than the remaining genes. Deleterious mutations explained 4.3%–48% more phenotypic variation than randomly selected SNPs for resistance to soybean cyst nematode race 2 (SCN2), soybean cyst nematode race 3 (SCN3) and soybean mosaic virus race 3 (SMV3). These findings illustrate how mutation load has shifted during soybean domestication, expansion and improvement and provide candidate sites for breeding out deleterious mutations in soybean by genome editing and/or conventional breeding focused on the selection of progeny with fewer deleterious alleles.

Dominant complementation of biological pathways in maize hybrid lines is associated with heterosis.

Allele-specific expressed genes (ASEGs) are widespread in maize hybrid lines and play important roles of complementation of biological pathways in heterosis. Heterosis (hybrid vigor) is an important phenomenon with both theoretical and practical value. However, our understanding of the genetic and molecular mechanisms behind heterosis is still limited. Here, we analyzed a comprehensive dataset of maize (Zea mays L.), including RNA-seq data from three hybrid-parent triplets (HPTs) and acetylated protein data from one HPT. The gene expression patterns exhibited extensive variation between the hybrids and their parents, and a substantial number of allele-specific expressed genes (ASEGs) were identified in the hybrids. Notably, ASEGs from different HPTs were significantly enriched in various conserved pathways. The parental alleles of ASEGs with fewer deleterious single-nucleotide polymorphisms were more likely to be expressed in hybrid lines than other parental alleles. ASEGs were mainly enriched in the functional gene ontology terms protein biosynthesis, photosynthesis, and metabolism. In addition, the ASEGs across the three HPTs were involved in key photosynthetic pathways and might enhance the photosynthetic efficiency of the hybrids. These findings suggest that ASEGs involved in complementary biological pathways in maize hybrids contribute to heterosis, shedding new light on the molecular mechanism of heterosis.

Role of Genetic Polymorphisms in Drug-Metabolizing Enzyme-Mediated Toxicity and Pharmacokinetic Resistance to Anti-Cancer Agents: A Review on the Pharmacogenomics Aspect.

The inter-individual differences in cancer susceptibility are somehow correlated with the genetic differences that are caused by the polymorphisms. These genetic variations in drug-metabolizing enzymes/drug-inactivating enzymes may negatively or positively affect the pharmacokinetic profile of chemotherapeutic agents that eventually lead to pharmacokinetic resistance and toxicity against anti-cancer drugs. For instance, the CYP1B1*3 allele is associated with CYP1B1 overexpression and consequent resistance to a variety of taxanes and platins, while 496T>G is associated with lower levels of dihydropyrimidine dehydrogenase, which results in severe toxicities related to 5-fluorouracil. In this context, a pharmacogenomics approach can be applied to ascertain the role of the genetic make-up in a person's response to any drug. This approach collectively utilizes pharmacology and genomics to develop effective and safe medications that are devoid of resistance problems. In addition, recently reported genomics studies revealed the impact of many single nucleotide polymorphisms in tumors. These studies emphasized the importance of single nucleotide polymorphisms in drug-metabolizing enzymes on the effect of anti-tumor drugs. In this review, we discuss the pharmacogenomics aspect of polymorphisms in detail to provide an insight into the genetic manipulations in drug-metabolizing enzymes that are responsible for pharmacokinetic resistance or toxicity against well-known anti-cancer drugs. Special emphasis is placed on different deleterious single nucleotide polymorphisms and their effect on pharmacokinetic resistance. The information provided in this report may be beneficial to researchers, especially those who are working in the field of biotechnology and human genetics, in rationally manipulating the genetic information of patients with cancer who are undergoing chemotherapy to avoid the problem of pharmacokinetic resistance/toxicity associated with drug-metabolizing enzymes.

REV1: A novel biomarker and potential therapeutic target for various cancers.

Background: REV1 is a member of the translesion synthesis DNA polymerase Y family. It is an essential player in a variety of DNA replication activities, and perform major roles in the production of both spontaneous and DNA damage-induced mutations. This study aimed to explore the role of REV1 as a prognostic biomarker and its potential function regulating the sensitivity of anti-tumor drugs in various cancers. Methods: We analyzed the impact of REV1 gene alterations on patient prognosis and the impact of different REV1 single nucleotide polymorphisms (SNP) on protein structure and function using multiple online prediction servers. REV1 expression was assessed using data from Oncomine, TCGA, and TIMER database. The correlation between REV1 expression and patient prognosis was performed using the PrognoScan and Kaplan-Meier plotter databases. The IC50 values of anti-cancer drugs were downloaded from the Genomics of Drug Sensitivity in Cancer database and the correlation analyses between REV1 expression and each drug pathway’s IC50 value in different tumor types were conducted. Results: Progression free survival was longer in REV1 gene altered group comparing to unaltered group [Median progression free survival (PFS), 107.80 vs. 60.89 months, p value = 7.062e-3]. REV1 SNP rs183737771 (F427L) was predicted to be deleterious SNP. REV1 expression differs in different tumour types. Low REV1 expression is associated with better prognosis in colorectal disease specific survival (DSS), disease-free survival (DFS), gastric overall survival (OS), post progression survival (PPS) and ovarian (OS, PPS) cancer while high REV1 expression is associated with better prognosis in lung [OS, relapse free survival (RFS), first progession (FP), PPS] and breast (DSS, RFS) cancer. In colon adenocarcinoma and rectum adenocarcinoma and lung adenocarcinoma, low expression of REV1 may suggest resistance to drugs in certain pathways. Conversely, high expression of REV1 in acute myeloid leukemia, brain lower grade glioma, small cell lung cancer and thyroid carcinoma may indicate resistance to drugs in certain pathways. Conclusion: REV1 plays different roles in different tumor types, drug susceptibility, and related biological events. REV1 expression is significantly correlated with different prognosis in colorectal, ovarian, lung, breast, and gastric cancer. REV1 expression can be used as predictive marker for various drugs of various pathways in different tumors.

Comprehensive analysis predicting effects of deleterious SNPs of human progesterone receptor gene on its structure and functions: a computational approach

Progesterone receptor plays a crucial role in the development of the mammary gland and breast cancer. Single nucleotide polymorphisms (SNPs) within its gene, PGR, are associated with the risk of miscarriages and preterm birth as well as many cancers across different populations. The main aim of this work is to investigate the most deleterious SNPs in the PGR gene to identify potential biomarkers for various disease susceptibility and treatments. Both sequence and structure-based computational approaches were adopted and in total 11 nsSNPs have been filtered out of 674 nsSNPs along with seven non-coding SNPs. R740Q, I744T and D746E belonged to a mutation cluster. R740Q, D746E along with S865L altered H-bond interactions within the receptor. The same mutations have been found to be associated with several cancers including uterine and breast cancer among others. It is, therefore, possible that the high-risk SNPs associated with cancers may exert their effect by causing changes in the protein structure, particularly in its bonding patterns, and thus affecting its function. In addition, seven non-coding SNPs that were located in the UTR region created a new miRNA site while three SNPs disrupted a conserved miRNA site. These high-risk SNPs can play an instrumental role in generating a dataset of the PGR gene’s SNPs. Thus, the present study may pave the way to design and develop novel therapeutics for overcoming the challenges associated with certain cancers and pregnancy that result from a change in the protein structure and function due to the SNP mutations in the PGR gene. Communicated by Ramaswamy H. Sarma

Functional and Structural Impact of Deleterious Missense Single Nucleotide Polymorphisms in the NR3C1, CYP3A5, and TNF-α Genes: An In Silico Analysis.

Human diseases are generally influenced by SNPs (single nucleotide polymorphisms). The mutations in amino acid residues generated by deleterious SNPs contribute to the structural and functional diversity of the encoded protein. Tumor necrosis factor-α (TNF-α), Glucocorticoid receptor gene (NR3C1), and Cytochrome P450 3A5 (CYP3A5) play a key role in glucocorticoid resistance susceptibility in humans. Possible causative mutations could be used as therapeutic targets and diagnostic markers for glucocorticoid resistance. This study evaluated the missense SNPs of TNF-α, NR3C1, and CYP3A5 to predict their impact on amino acid changes, protein interaction, and functional stability. The protein sequence of dbSNP was obtained and used online in silico method to screen deleterious mutants for the in silico analysis. In the coding regions of TNF-α, NR3C1, and CYP3A5, 14 deleterious mutations were discovered. The protein functional and stability changes in the amino acid between native and mutant energy were identified by analyzing the changes in the hydrogen bonding of these mutants from native, which were all measured using Swiss PDB and PyMOL. F446S and R439K had the highest root-mean-square deviation (RMSD) values among the 14 deleterious mutants. Additionally, the conserved region of amino acid protein interaction was analyzed. This study could aid in the discovery of new detrimental mutations in TNF-α, NR3C1, and CYP3A5, as well as the development of long-term therapy for corticosteroid resistance in several inflammatory diseases. However, more research into the deleterious mutations of the TNF-α, NR3C1, and CYP3A5 genes is needed to determine their role in corticosteroid resistance.