Single nucleotide polymorphisms and the future of genetic epidemiology

Biosensing of single-nucleotide polymorphism: Technological advances and their transformative applications on health

Single nucleotide polymorphisms (SNPs) are important genetic changes related to many diseases such as breast cancer, Alzheimer's disease, and β-thalassemia. Because of the increased interest in biosensor technologies, there has been a notable surge in the creation of new techniques to identify these changes in recent years. These new methods are highly accurate and sensitive, cost-effective and fast, making them ideal for use in clinical analysis. The non-invasive nature of biosensing techniques further enhances their integration into clinical protocols and point-of-care diagnostics. Several electrochemical, optical, and mass-based biosensors are carefully examined in this extensive review; each is distinguished by unique sensing platforms and techniques. This review presents in-depth discussions of linear dynamic ranges, detection limits, and real-world applications of contemporary research in the diagnosis of biological substrate disorders.

MicroRNA-155 rs767649 polymorphism is associated with susceptibility to peri-implantitis

OBJECTIVE

To examine how the miR-155 rs767649 polymorphism affects miR-155 expression and to investigate its association with peri-implantitis susceptibility.

DESIGN

One hundred and eighty-seven peri-implantitis patients and 196 healthy implant subjects were enrolled. The expression level of miR-155 in the subjects' serum was tested using qRT-PCR. The rs767649 polymorphism was genotyped with the TaqMan SNP genotyping assay. The genotype and allele distributions of miR-155 rs767649 polymorphism were compared between the case and control groups. Target genes of miR-155 were predicted using four online databases (ENCORI, miRDB, miRWalk and TargetScan). Functions and pathways of these target genes were annotated through GO and KEGG enrichment.

RESULTS

The qRT-PCR results revealed that miR-155 was upregulated in patients with peri-implantitis (P < 0.001) based on Student's t test analysis. Carriers of the rs767649 TT genotype had higher levels of miR-155 expression in their serum (P < 0.001) and a greater risk of peri-implantitis compared to those with the TA/AA genotype according to the chi-square test results (P = 0.016). The downstream target genes of miR-155 may be involved in pathways such as Kaposi sarcoma-associated herpesvirus infection, ubiquitin-protein hydrolysis, and cell differentiation.

CONCLUSION

The results revealed a correlation between the miR-155 rs767649 polymorphism and susceptibility to peri-implantitis. The rs767649 TT genotype upregulates miR-155 expression, which regulates downstream signaling pathways and increases the chance of peri-implantitis.

Psychiatric Genetics in Clinical Practice: Essential Knowledge for Mental Health Professionals

OBJECTIVE

The authors provide recommendations on incorporating recent advances in psychiatric genetics into clinical practice for mental health clinicians.

METHOD

The International Society for Psychiatric Genetics Education Committee met monthly to come to a consensus on priority topics in psychiatric genetics. Topics were then assigned to small teams of subspecialty experts to summarize the current knowledge base and create an illustrative clinical case. Topics included, familial aggregation, common and rare genetic variants, epigenetics, gene-environment interactions, pharmacogenomics, genetic counseling, and ethical and social implications. Each section was reviewed and revised by all committee members and then finalized by the Committee Chair.

RESULTS

Key findings highlight the importance of understanding the genetic architecture of psychiatric disorders, the potential applications of genetic information in risk assessment, diagnosis, treatment selection, and patient education, as well as the ethical and social considerations surrounding the use of genetic data. The committee emphasizes the need for a nuanced approach that integrates genetic factors with environmental and experiential factors in a holistic model of care.

CONCLUSION

As psychiatric genetics continues to evolve rapidly, mental health clinicians must stay informed about the latest findings and their clinical implications. Ongoing education, collaboration with genetics professionals, and effective communication strategies are crucial to harness the power of genetics while avoiding potential pitfalls such as genetic determinism and stigma. The committee recommends a balanced perspective that recognizes the complex interplay of genetic and non-genetic factors in shaping mental health outcomes.

Detection of a genetically related carbapenemase-producing Escherichia coli ST167 in clinical and environmental isolates: Evidence for clonal spread of carbapenemase-producing Enterobacteriaceae in humans and the environment in Iowa, United States

BACKGROUND

Carbapenemase-producing Enterobacteriaceae (CPE) are listed by the World Health Organization as one of the critical priority pathogens needing urgent attention to address global resistance to antimicrobials. Thus, the transmission and epidemiology of CPEs need to be studied via One Health perspectives.

METHODS

An environmental CPE, referred to as BO1, was isolated from a creek in Northwest Iowa using a Colilert system (IDEXX, Westbrook, ME, USA). The presence of carbapenemase was examined using the modified carbapenem inactivation test, and then phenotypic resistance was determined using a Sensititre Complete Automated AST System (Thermo Fisher Scientific, Roskilde, Denmark). Whole-genome sequencing was performed and analysed to compare with clinical CPEs.

RESULTS

BO1, carrying blaNDM-5, was isolated from a creek in Northwest Iowa. BO1 exhibited resistance to 15 antimicrobials and was defined as an extensively drug-resistant organism. BO1 was also identified as ST167, which is well known as an emerging high-risk clone, and IncFIA- and IncQ1-type conjugatable plasmids were identified within the BO1 genome. The genetic environment of blaNDM-5 was highly conserved as blaNDM-bleMBL-trpF-dsbD in all strains studied. Interestingly, single-nucleotide polymorphism analysis revealed that BO1 shared only 1, 4 and 12 single-nucleotide polymorphisms with three different clinical strains from patients at Iowa health care facilities.

CONCLUSIONS

The occurrence of BO1 was temporally and spatially close to that of one clinical strain, IA0018, implying the clonal spread of CPEs among humans and the environment, although the source and directionality of this spread remains unknown. This report illustrates the need for the strict control of CPEs in health care facilities and continuous surveillance within clinical and environmental settings to trace and prevent CPE transmission.

Nanopore toward Genuine Single-Molecule Sensing: Molecular Ping-Pong Technology

Nanopore sensing is a so-called label-free, single-molecule technology; however, multiple events of different molecules are recorded to obtain statistically robust data, which can limit both efficiency and sample use. To overcome these challenges, nanopore molecular ping-pong technology enables precise single-molecule manipulation, reducing systematic and stochastic errors by repeatedly measuring the same molecule. This review introduces the fundamentals and advancements of ping-pong technology, highlighting a recent breakthrough achieving over 10,000 recaptures of a single dsDNA molecule within minutes. This innovation not only minimizes sample requirements, which is critical for nonamplifiable samples, but also significantly enhances experimental precision. While current applications focus on dsDNA, extending this technology to protein and glycan analysis could transform nanopore research. Just as nanopore technology revolutionized DNA sequencing, it holds the potential to drive the development of nanopore-based protein and glycan sequencers, paving the way for groundbreaking advancements in molecular biology and biomedicine.

Computational Analysis of S1PR1 SNPs Reveals Drug Binding Modes Relevant to Multiple Sclerosis Treatment

Background/Objectives: Multiple sclerosis (MS) is an autoimmune disorder of the central nervous system (CNS) characterized by myelin and axonal damage with a globally rising incidence. While there is no known cure for MS, various disease-modifying treatments (DMTs) exist, including those targeting Sphingosine-1-Phosphate Receptors (S1PRs), which play important roles in immune response, CNS function, and cardiovascular regulation. This study focuses on understanding how nonsynonymous single nucleotide polymorphisms (rs1299231517, rs1323297044, rs1223284736, rs1202284551, rs1209378712, rs201200746, and rs1461490142) in the S1PR1's active site affect the binding of endogenous ligands, as well as different drugs used in MS management. Methods: Extensive molecular dynamics simulations and linear interaction energy (LIE) calculations were employed to predict binding affinities and potentially guide future personalized medicinal therapies. The empirical parameters of the LIE method were optimized using the binding free energies calculated from experimentally determined IC50 values. These optimized parameters were then applied to calculate the binding free energies of S1P to mutated S1PR1, which correlated well with experimental values, confirming their validity for assessing the impact of SNPs on S1PR1 binding affinities. Results: The binding free energies varied from the least favorable -8.2 kcal/mol for the wild type with ozanimod to the most favorable -16.7 kcal/mol for the combination of siponimod with the receptor carrying the F2055.42L mutation. Conclusions: We successfully demonstrated the differences in the binding modes, interactions, and affinities of investigated MS drugs in connection with SNPs in the S1PR1 binding site, resulting in several viable options for personalized therapies depending on the present mutations.

Epi-SSA: A novel epistasis detection method based on a multi-objective sparrow search algorithm

Genome-wide association studies typically considers epistatic interactions as a crucial factor in exploring complex diseases. However, the current methods primarily concentrate on the detection of two-order epistatic interactions, with flaws in accuracy. In this work, we introduce a novel method called Epi-SSA, which can be better utilized to detect high-order epistatic interactions. Epi-SSA draws inspiration from the sparrow search algorithm and optimizes the population based on multiple objective functions in each iteration, in order to be able to more precisely identify epistatic interactions. To evaluate its performance, we conducted a comprehensive comparison between Epi-SSA and seven other methods using five simulation datasets: DME 100, DNME 100, DME 1000, DNME 1000 and DNME3 100. The DME 100 dataset encompasses eight second-order epistasis disease models with marginal effects, each comprising 100 simulated data instances, featuring 100 SNPs per instance, alongside 800 case and 800 control samples. The DNME 100 encompasses eight second-order epistasis disease models without marginal effects and retains other properties consistent with DME 100. Experiments on the DME 100 and DNME 100 datasets were designed to evaluate the algorithms' capacity to detect epistasis across varying disease models. The DME 1000 and DNME 1000 datasets extend the complexity with 1000 SNPs per simulated data instance, while retaining other properties consistent with DME 100 and DNME 100. These experiments aimed to gauge the algorithms' adaptability in detecting epistasis as the number of SNPs in the data increases. The DNME3 100 dataset introduces a higher level of complexity with six third-order epistasis disease models, otherwise paralleling the structure of DNME 100, serving to test the algorithms' proficiency in identifying higher-order epistasis. The highest average F-measures achieved by the seven other existing methods on the five datasets are 0.86, 0.86, 0.41, 0.56, and 0.79 respectively, while the average F-measures of Epi-SSA on the five datasets are 0.92, 0.97, 0.79, 0.86, and 0.97 respectively. The experimental results demonstrate that the Epi-SSA algorithm outperforms other methods in a variety of epistasis detection tasks. As the number of SNPs in the data set increases and the order of epistasis rises, the advantages of the Epi-SSA algorithm become increasingly pronounced. In addition, we applied Epi-SSA to the analysis of the WTCCC dataset, uncovering numerous genes and gene pairs that might play a significant role in the pathogenesis of seven complex diseases. It is worthy of note that some of these genes have been relatedly reported in the Comparative Toxicogenomics Database (CTD). Epi-SSA is a potent tool for detecting epistatic interactions, which aids us in further comprehending the pathogenesis of common and complex diseases. The source code of Epi-SSA can be obtained at https://osf.io/6sqwj/.

Genetic marker: a genome mapping tool to decode genetic diversity of livestock animals

Genotyping is the process of determining the genetic makeup of an organism by examining its DNA sequences using various genetic markers. It has been widely used in various fields, such as agriculture, biomedical and conservation research, to study genetic diversity, inheritance, the genetic basis of disease-associated traits, evolution, adaptation, etc., Genotyping markers have evolved immensely and are broadly classified as random markers (RFLP, RAPD, AFLP, etc.) and functional markers (SCoT, CDDP, SRAP, etc.). However, functional markers are very limited in genotype studies, especially in animal science, despite their advantages in overcoming the limitations of random markers, which are directly linked with phenotypic traits, high specificity, and similar logistic requirements. The current review surveyed the available random and functional markers for genotyping applications, focusing on livestock including plant and microbe domains. This review article summarises the application, advantages, and limitations of developed markers and methods for genotyping applications. This review aims to make the reader aware of all available markers, their design principles, and methods, and we discuss the marker inheritance patterns of RLFP and AFLP. The review further outlines the marker selection for particular applications and endorses the application of functional markers in genotyping research.

mTOR gene variant rs2295080 might be a risk factor for atherosclerosis in Iranian women with type 2 diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus, one of the most prevalent metabolic disorders worldwide, is closely linked with an enhanced risk of atherosclerosis. However, the molecular mechanism of this linkage is not still clear. Genetic variations in the mTOR gene may increase the susceptibility of individuals to these diseases.

METHODS

One hundred nine diabetic patients and 375 healthy subjects participated in this study. mTOR Single Nucleotide Polymorphism (SNP) rs2295080 was determined using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP).

RESULTS

Comparison of genotypic, allelic, and genotypic combination frequencies between cases and controls revealed no significant result. Nevertheless, the frequency of rs2295080 GT + TT genotype was significantly more in diabetic women with atherosclerosis compared with those without atherosclerosis (p = 0.047). Besides, the rs2295080 G allele was more frequently detected in diabetic women without atherosclerosis compared to those with atherosclerosis (p = 0.046).

CONCLUSION

The rs2295080 GT + TT genotype predisposes Iranian diabetic women to atherosclerosis, while the rs2295080 G allele protects them against atherosclerosis. However, additional experiments using larger sample sizes are needed to verify this result.

Postharvest Management of Fruits and Vegetables-Series II

Fruits and vegetables are crucial nutritional sources of carbohydrates, protein, minerals, vitamins, and dietary fiber, offering significant benefits to human health [...].

A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools

Polygenetic Risk Scores are used to evaluate an individual's vulnerability to developing specific diseases or conditions based on their genetic composition, by taking into account numerous genetic variations. This article provides an overview of the concept of Polygenic Risk Scores (PRS). We elucidate the historical advancements of PRS, their advantages and shortcomings in comparison with other predictive methods, and discuss their conceptual limitations in light of the complexity of biological systems. Furthermore, we provide a survey of published tools for computing PRS and associated resources. The various tools and software packages are categorized based on their technical utility for users or prospective developers. Understanding the array of available tools and their limitations is crucial for accurately assessing and predicting disease risks, facilitating early interventions, and guiding personalized healthcare decisions. Additionally, we also identify potential new avenues for future bioinformatic analyzes and advancements related to PRS.

VariantDetective: an accurate all-in-one pipeline for detecting consensus bacterial SNPs and SVs

MOTIVATION

Genomic variations comprise a spectrum of alterations, ranging from single nucleotide polymorphisms (SNPs) to large-scale structural variants (SVs), which play crucial roles in bacterial evolution and species diversification. Accurately identifying SNPs and SVs is beneficial for subsequent evolutionary and epidemiological studies. This study presents VariantDetective (VD), a novel, user-friendly, and all-in-one pipeline combining SNP and SV calling to generate consensus genomic variants using multiple tools.

RESULTS

The VD pipeline accepts various file types as input to initiate SNP and/or SV calling, and benchmarking results demonstrate VD's robustness and high accuracy across multiple tested datasets when compared to existing variant calling approaches.

AVAILABILITY AND IMPLEMENTATION

The source code, test data, and relevant information for VD are freely accessible at https://github.com/OLF-Bioinformatics/VariantDetective under the MIT License.

A flash signal amplification approach for ultrasensitive and rapid detection of single nucleotide polymorphisms in tuberculosis

In recent years, the demand for rapid, sensitive, and simple methods for diagnosing deoxyribonucleic acid (DNA) has grown due to the increase in the variation of infectious diseases. This work aimed to develop a flash signal amplification method coupled with electrochemical detection for polymerase chain reaction (PCR)-free tuberculosis (TB) molecular diagnosis. We exploited the slightly miscible properties of butanol and water to instantly concentrate a capture probe DNA, a single-stranded mismatch DNA, and gold nanoparticles (AuNPs) to a small volume to reduce the diffusion and reaction time in the solution. In addition, the electrochemical signal was enhanced once two strands of DNA were hybridized and bound to the surface of the gold nanoparticle at an ultra-high density. To eliminate non-specific adsorption and identify mismatched DNA, the self-assembled monolayers (SAMs) and Muts proteins were sequentially modified on the working electrode. This sensitive and specific approach can detect as low as attomolar levels of DNA targets (18 aM) and is successfully applied to detecting tuberculosis-associated single nucleotide polymorphisms (SNPs) in synovial fluid. More importantly, as this biosensing strategy can amplify the signal in only a few seconds, it possesses a great potential for point-of-care and molecular diagnosis applications.

Influence of MTHFR polymorphism, alone or in combination with smoking and alcohol consumption, on cancer susceptibility

5,10-methylenetetrahydrofolate reductase (MTHFR) mutations play a significant role in various types of cancers, serving as crucial regulators of folate levels in this process. Several studies have examined the effects of smoking and drinking on MTHFR-related cancers, yielding inconsistent results. Therefore, the objective of this study was to evaluate the magnitude of the effects of gene-smoking or gene-drinking interactions on cancer development. We conducted a comprehensive literature search in PubMed, Web of Science, CNKI, and Wan Fang databases up until May 10th, 2022, to identify relevant articles that met our inclusion criteria. The extracted data from these studies were used to calculate the overall odds ratio (OR) and corresponding 95% confidence interval (95% CI) using either a fixed-effect or random-effect model in Stata version 11.2. Stratified analyses were performed based on ethnicity, control group origin, and cancer classification to assess the risk of cancers associated with gene-smoking or gene-drinking interactions. Sensitivity analyses were conducted to investigate potential sources of heterogeneity, and publication bias was assessed using the Begg's test and Egger's test. Additionally, regression analysis was employed to explore the influence of relevant variables on heterogeneity. To evaluate the statistical correlations, analytical methods such as the false-positive report probability and the Bayesian false discovery probability were applied to assess the reliability of the findings. In our meta-analysis, a total of 47 articles were included, comprising 13,701 cases and 21,995 controls for the C677T polymorphism and 5,149 cases and 8,450 controls for the A1298C polymorphism. The results indicated a significant association between C677T polymorphism and cancer risks when combined with smoking (CT + TT vs CC, OR [95% CI] = 1.225 [1.009-1.487], p = 0.041). Stratified analysis further revealed a significant increase in liver cancer risk for individuals with the C677T when combined with smoking (liver cancer: CT + TT vs CC, OR [95% CI] = 1.564 [1.014-2.413], p = 0.043), particularly among Asian smokers (CT + TT vs CC, OR [95% CI] = 1.292 [1.007-1.658], p = 0.044). Regarding the A1298C polymorphism, an elevated risk of cancer was observed in mixed populations alone (CC + AC vs AA, OR [95% CI] = 1.609 [1.087-2.381], p = 0.018), as well as when combined with smoking (CC + AC vs AA, OR [95% CI] = 1.531 [1.127-2.080], p = 0.006). In non-drinkers, C677T polymorphism was found to be associated with esophageal cancer risk (C677T: CT + TT vs CC, OR [95% CI] = 1.544 [1.011-2.359], p = 0.044) and colon cancer risk (CC + AC vs AA, OR [95% CI] = 1.877 [1.166-3.054], p = 0.010), but there was no clear link between this polymorphism and cancer risk among drinkers. The association between the C677T polymorphism and cancer risk among smokers was found to be significant, suggesting that the combination of tobacco and the C677T polymorphism may enhance the carcinogenic process, particularly in liver cancer. However, no similar relationship was observed for the A1298C polymorphism. Interestingly, significantly increased cancer risk was observed in individuals with C677T genetic variants who were nondrinkers, but not among drinkers. These findings highlight the potential role of the C677T polymorphism in modifying cancer risk in specific contexts, such as smoking and alcohol consumption.

Perspective of artificial intelligence in healthcare data management: A journey towards precision medicine

Mounting evidence has highlighted the implementation of big data handling and management in the healthcare industry to improve the clinical services. Various private and public companies have generated, stored, and analyzed different types of big healthcare data, such as omics data, clinical data, electronic health records, personal health records, and sensing data with the aim to move in the direction of precision medicine. Additionally, with the advancement in technologies, researchers are curious to extract the potential involvement of artificial intelligence and machine learning on big healthcare data to enhance the quality of patient's lives. However, seeking solutions from big healthcare data requires proper management, storage, and analysis, which imposes hinderances associated with big data handling. Herein, we briefly discuss the implication of big data handling and the role of artificial intelligence in precision medicine. Further, we also highlighted the potential of artificial intelligence in integrating and analyzing the big data that offer personalized treatment. In addition, we briefly discuss the applications of artificial intelligence in personalized treatment, especially in neurological diseases. Lastly, we discuss the challenges and limitations imposed by artificial intelligence in big data management and analysis to hinder precision medicine.

From Eberthella typhi to Salmonella Typhi: The Fascinating Journey of the Virulence and Pathogenicity of Salmonella Typhi

Salmonella Typhi (S. Typhi), the invasive typhoidal serovar of Salmonella enterica that causes typhoid fever in humans, is a severe threat to global health. It is one of the major causes of high morbidity and mortality in developing countries. According to recent WHO estimates, approximately 11-21 million typhoid fever illnesses occur annually worldwide, accounting for 0.12-0.16 million deaths. Salmonella infection can spread to healthy individuals by the consumption of contaminated food and water. Typhoid fever in humans sometimes is accompanied by several other critical extraintestinal complications related to the central nervous system, cardiovascular system, pulmonary system, and hepatobiliary system. Salmonella Pathogenicity Island-1 and Salmonella Pathogenicity Island-2 are the two genomic segments containing genes encoding virulent factors that regulate its invasion and systemic pathogenesis. This Review aims to shed light on a comparative analysis of the virulence and pathogenesis of the typhoidal and nontyphoidal serovars of S. enterica.

Genetic Diversity and Pathogenicity of Fusarium fujikuroi Species Complex (FFSC) Causing Sugarcane Pokkah Boeng Disease (PBD) in China

Pokkah boeng disease (PBD), a sugarcane foliar disease, is caused by various Fusarium spp. within the Fusarium fujikuroi species complex (FFSC). In the current study, we investigated the diversity of Fusarium spp. associated with PBD in China. In total, 320 leaf samples displaying PBD symptoms were collected over 10 consecutive years (2012 to 2021), during winter and summer, from six various sugarcane-growing regions (Guangxi, Yunnan, Guangdong, Zhejiang, Hainan, and Fujian) in China. Phylogenetic analysis of Fusarium spp. was reconstructed using translation elongation factor 1-α, and DNA-directed RNA polymerase II largest subunit and second-largest subunit multigene sequences. Evolutionary studies of these regions categorized the isolates into four FFSC species (F. sacchari, F. proliferatum, F. verticillioides, and F. andiyazi). The identified isolates, which developed irregular necrotic patches and rotting symptoms on the sugarcane plant after approximately 30 days were tested for their pathogenicity. Symptoms that appeared during pathogenicity testing were consistent with those observed under field conditions. Each strain of the pathogenic Fusarium spp. belonged to different vegetative compatibility groups (VCGs), and there was no affinity between VCGs. Our results contribute to understanding FFSC and accurately identifying Fusarium spp. associated with the sugarcane crop.

Pathogenesis of allergic diseases and implications for therapeutic interventions

Allergic diseases such as allergic rhinitis (AR), allergic asthma (AAS), atopic dermatitis (AD), food allergy (FA), and eczema are systemic diseases caused by an impaired immune system. Accompanied by high recurrence rates, the steadily rising incidence rates of these diseases are attracting increasing attention. The pathogenesis of allergic diseases is complex and involves many factors, including maternal-fetal environment, living environment, genetics, epigenetics, and the body's immune status. The pathogenesis of allergic diseases exhibits a marked heterogeneity, with phenotype and endotype defining visible features and associated molecular mechanisms, respectively. With the rapid development of immunology, molecular biology, and biotechnology, many new biological drugs have been designed for the treatment of allergic diseases, including anti-immunoglobulin E (IgE), anti-interleukin (IL)-5, and anti-thymic stromal lymphopoietin (TSLP)/IL-4, to control symptoms. For doctors and scientists, it is becoming more and more important to understand the influencing factors, pathogenesis, and treatment progress of allergic diseases. This review aimed to assess the epidemiology, pathogenesis, and therapeutic interventions of allergic diseases, including AR, AAS, AD, and FA. We hope to help doctors and scientists understand allergic diseases systematically.

Functional gene polymorphisms and expression alteration of selected microRNAs and the risk of various gastric lesions in Helicobacter pylori-related gastric diseases

Background: Helicobacter pylori (Hp) persistent infection is an important pathogenic factor for a series of chronic gastric diseases from chronic gastritis to gastric cancer. Genetic and epigenetic abnormalities of microRNAs may play a vital role in the pathological evolution of gastric mucosa in Helicobacter pylori-related gastric diseases (HPGD). This study aimed to investigate the relationship between miR-146a, miR-196a2, miR-149, miR-499 and miR-27a gene single nucleotide polymorphisms (SNPs) and their expressions with pathological changes in gastric mucosa, and to further analyze the interactions between SNPs and Hp. Methods: Subjects in this study included patients diagnosed with HPGD and healthy controls. MiR-146a rs2910164, miR-196a2 rs11614913, miR-149 rs2292832, miR-499 rs3746444 and miR-27a rs895819 were genotyped by direct sequencing. Fluorescence quantitative PCR was used to detect microRNA expressions. Gene-gene and gene-environment interactions were evaluated by multifactor dimensionality reduction (MDR) method. Results: we found that frequency distribution of miR-196a2 rs11614913 CT genotype in gastric precancerous lesion (GPL) group and gastric cancer (GC) group was significantly higher than normal control (NOR) group [adjusted OR = 6.16, 95%CI (1.46-26.03); adjusted OR = 11.83, 95%CI (1.65-84.72), respectively]. CT genotype and C allele of miR-27a rs895819 were associated with increased risk of GC [adjusted OR = 10.14, 95%CI (2.25-45.77); adjusted OR = 3.71, 95%CI(1.46-9.44), respectively]. The MDR analysis results showed that the interaction between miR-196a2 rs11614913 and Hp was associated with the risk of GPL (p = 0.004). Meanwhile, the expression level of miR-196a2 in GC group was significantly higher than NOR, chronic inflammation (CI) and early precancerous lesion (EPL) groups among Hp-positive subjects. And expressions of miR-499 and miR-27a in GC group were both higher than EPL group. Also, miR-27a expression in GC group was higher than CI and gastric atrophy (GA) groups. Conclusion: miR-196a2 rs11614913 and miR-27a rs895819 may affect the genetic susceptibility to GPL or GC. MiR-196a2 rs11614913 and Hp have a synergistic effect in the occurrence and development of GPL. The up-regulation of miR-499, miR-196a2 and miR-27a expression caused by Hp infection may be an important mechanism of gastric carcinogenesis.

Pharmacogenetics of Anticancer Drugs: Clinical Response and Toxicity

Cancer is the most challenging disease for medical professionals to treat. The factors underlying the complicated situation include anticancer drug-associated toxicity, non-specific response, low therapeutic window, variable treatment outcomes, development of drug resistance, treatment complications, and cancer recurrence. The remarkable advancement in biomedical sciences and genetics, over the past few decades, however, is changing the dire situation. The discovery of gene polymorphism, gene expression, biomarkers, particular molecular targets and pathways, and drug-metabolizing enzymes have paved the way for the development and provision of targeted and individualized anticancer treatment. Pharmacogenetics is the study of genetic factors having the potential to affect clinical responses and pharmacokinetic and pharmacodynamic behaviors of drugs. This chapter emphasizes pharmacogenetics of anticancer drugs and its applications in improving treatment outcomes, selectivity, toxicity of the drugs, and discovering and developing personalized anticancer drugs and genetic methods for prediction of drug response and toxicity.

Whole-genome single nucleotide polymorphism analysis for typing the pandemic pathogen Fusarium graminearum sensu stricto

Recent improvements in microbiology and molecular epidemiology were largely stimulated by whole- genome sequencing (WGS), which provides an unprecedented resolution in discriminating highly related genetic backgrounds. WGS is becoming the method of choice in epidemiology of fungal diseases, but its application is still in a pioneer stage, mainly due to the limited number of available genomes. Fungal pathogens often belong to complexes composed of numerous cryptic species. Detecting cryptic diversity is fundamental to understand the dynamics and the evolutionary relationships underlying disease outbreaks. In this study, we explore the value of whole-genome SNP analyses in identification of the pandemic pathogen Fusarium graminearum sensu stricto (F.g.). This species is responsible for cereal diseases and negatively impacts grain production worldwide. The fungus belongs to the monophyletic fungal complex referred to as F. graminearum species complex including at least sixteen cryptic species, a few among them may be involved in cereal diseases in certain agricultural areas. We analyzed WGS data from a collection of 99 F.g. strains and 33 strains representing all known cryptic species belonging to the FGSC complex. As a first step, we performed a phylogenomic analysis to reveal species-specific clustering. A RAxML maximum likelihood tree grouped all analyzed strains of F.g. into a single clade, supporting the clustering-based identification approach. Although, phylogenetic reconstructions are essential in detecting cryptic species, a phylogenomic tree does not fulfill the criteria for rapid and cost-effective approach for identification of fungi, due to the time-consuming nature of the analysis. As an alternative, analysis of WGS information by mapping sequence data from individual strains against reference genomes may provide useful markers for the rapid identification of fungi. We provide a robust framework for typing F.g. through the web-based PhaME workflow available at EDGE bioinformatics. The method was validated through multiple comparisons of assembly genomes to F.g. reference strain PH-1. We showed that the difference between intra- and interspecies variability was at least two times higher than intraspecific variation facilitating successful typing of F.g. This is the first study which employs WGS data for typing plant pathogenic fusaria.

Using unique ORFan genes as strain-specific identifiers for Escherichia coli

BACKGROUND

Bacterial identification at the strain level is a much-needed, but arduous and challenging task. This study aimed to develop a method for identifying and differentiating individual strains among multiple strains of the same bacterial species. The set used for testing the method consisted of 17 Escherichia coli strains picked from a collection of strains isolated in Germany, Spain, the United Kingdom and Vietnam from humans, cattle, swine, wild boars, and chickens. We targeted unique or rare ORFan genes to address the problem of selective and specific strain identification. These ORFan genes, exclusive to each strain, served as templates for developing strain-specific primers.

RESULTS

Most of the experimental strains (14 out of 17) possessed unique ORFan genes that were used to develop strain-specific primers. The remaining three strains were identified by combining a PCR for a rare gene with a selection step for isolating the experimental strains. Multiplex PCR allowed the successful identification of the strains both in vitro in spiked faecal material in addition to in vivo after experimental infections of pigs and recovery of bacteria from faecal material. In addition, primers for qPCR were also developed and quantitative readout from faecal samples after experimental infection was also possible.

CONCLUSIONS

The method described in this manuscript using strain-specific unique genes to identify single strains in a mixture of strains proved itself efficient and reliable in detecting and following individual strains both in vitro and in vivo, representing a fast and inexpensive alternative to more costly methods.

Association and functional analysis of angiotensin-converting enzyme 2 genetic variants with the pathogenesis of pre-eclampsia

OBJECTIVE

The aim of this study was to investigate the relationship between potential functional single-nucleotide polymorphisms (SNPs) of the angiotensin-converting enzyme 2 (ACE2) gene and the pathogenesis of pre-eclampsia (PE) in Guangxi, China.

MATERIALS AND METHODS

A case-control study was conducted involving 327 PE cases and 591 age-matched, normal, singleton pregnant women. Potential functional ACE2 gene variants (rs2106809 A>G, rs6632677 G>C, and rs2074192 C>T) were selected and genotyped using kompetitive allele-specific PCR. The strength of the associations between the studied genetic variants and the risk of PE were evaluated using odds ratios (ORs) and corresponding 95% confidence intervals (CIs).

RESULT

After adjusting for age and body mass index (BMI), unconditional logistic regression analysis showed that rs2106809 A>G was significantly associated with PE risk (AG vs. AA, OR = 1.43, 95% CI = 1.03-1.99, p = 0.034; AG/GG vs. AA, OR = 1.45, 95% CI = 1.06-1.99, p = 0.019), especially with severe PE (AG vs. AA, adjusted OR = 1.70, 95% CI = 1.10-2.61; AG/GG vs. AA, adjusted OR = 1.71, 95% CI = 1.14-2.57). Further stratified analysis showed that rs2106809 was even more pronounced in subjects in the pre-pregnancy BMI (pre-BMI) >23 kg/m² (adjusted OR = 2.14, 95% CI = 1.32-3.45) and triglyceride (TG) >2.84 mmol/L subgroups (adjusted OR = 1.81, 95% CI = 1.09-3.01) under the dominant genetic model. We also found that rs2106809 interacted with pre-BMI (p _interaction = 0.040), thereby affecting an individual's genetic susceptibility to PE. Multiple dimension reduction analysis demonstrated that rs2106809 made the best one-locus model, and the three-locus model was the best interaction model for predicting PE risk. Functional analysis suggested that rs2106809 A>G causes a change in the reliability of classifications of two putative splice sites in the ACE2 gene, potentially regulating the expression of functional genes (PIR, ACE2, and CLTRN) in multiple tissues and cell lines (p< 0.05).

CONCLUSION

The ACE2 gene rs2106809 A>G variant is significantly associated with the risk of PE via individual locus effects and/or complex gene-gene and gene-environment interactions. Regulating the expression of functional genes such as PIR, ACE2, and CLTRN may be the molecular mechanism by which rs2106809 increases an individual's susceptibility to PE.

AURKA gene polymorphisms and central nervous system tumor susceptibility in Chinese children

INTRODUCTION

Central nervous system (CNS) tumors comprise 15-20% of all malignancies occurring in childhood and adolescence. Previous researches have shown that overexpression and amplification of the AURKA gene could induce multiple human malignancies, with which the connection of CNS tumor susceptibility has not been extensively studied.

MATERIAL AND METHODS

In this study, we assessed whether and to what extent AURKA gene single nucleotide polymorphisms (SNPs) (rs1047972 C > T, rs2273535 T > A, rs8173 G > C) were associated with CNS tumor susceptibility, based on a case-control analysis in 191 CNS tumor patients and 248 controls. We determined this correlation using odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

AURKA gene rs8173 G > C exhibited a crucial function to CNS tumor susceptibility fall-off (GC/CC vs. GG: adjusted OR = 0.68, 95% CI = 0.46-0.998, P = 0.049). In addition, the combined effect of lowering the risk of developing CNS tumors was more pronounced in carriers with 3 protective genotypes than others (adjusted OR = 0.55, 95% CI = 0.31-0.98, P = 0.044). Further stratification analysis illustrated that the existence of rs8173 GC/CC and three protective genotypes lowered CNS tumor risk in some subgroups.

CONCLUSIONS

Our research suggested that the AURKA gene rs8173 G > C could significantly reduce CNS tumor susceptibility in Chinese children. More functional experiments are needed to explore the role of the AURKA gene rs8173 G > C.

Clinical Spectrum and Resistance Profile of Staphylococcus Infections in a Peri Urban Tertiary Care Hospital

Staphylococcus may be evaluated to be a serious microorganism to colonizes and contaminate both the healthy and immuno-competent people in the community along with the hospitalized patients with decreased immunity. This bacterium has been commonly present on the skin and in the nasal cavity of the human body. In the particular sites the organisms may give rise to local diseases of the nose, urethra, vagina and gastrointestinal tract, skin however most of them are minor and not associated with any mortality. S. aureus as well as coagulase-negative staphylococcus which are gram-positive bacteria that lives on the upper respiratory, mouth and skin structure creation, are the possible element for nosocomial and opportunistic disease in humans as well as in animals. Major complications involved with staphylococcus involved SSI, bullous impetigo, skin & soft tissues infection, bacteremia, pulmonary infections etc. The situation is further complicated by methicillin resistance in staphylococcus. MRSA/MRCoNS are considered as the emerging cause of hospital-acquired infections. it is very necessary to quantify the load of infections in order to achieve good hospital infection control policies. Furthermore, the morbidity and mortality rate may also be reduced in the same manner.

PAI-1 Polymorphisms Have Significant Associations With Cancer Risk, Especially Feminine Cancer

BACKGROUND

The plasminogen activator inhibitor-1 (PAI-1) was found in many types of tumor cells, which involved in tumorigenesis. Some studies investigated the associations between PAI-1 polymorphisms and various cancers, but the results were inconsistent. So this study did a meta-analysis to assess the strength of relationship between PAI-1 and cancer.

METHODS

Articles that meet the requirements were searched from PubMed, EMBASE, MEDLINE, Scopus, CNKI, Wanfang and SinoMed electronic databases before June 17th 2021. Stata version 11.2 was performed to merge the odds ratios (ORs) values and calculate 95% confidence intervals (CIs). Stratified analyses were assessed on the basis of types of cancer, ethnicity and source of the control group. Heterogeneity and sensitivity analysis were tested, and publication bias was also estimated. A meta-regression analysis was applied to explore sources of heterogeneity. The false-positive report probabilities (FPRP) and the Bayesian False Discovery Probability (BFDP) test were used to assess the credibility of statistically significant associations.

RESULTS

Ultimately, in this study, 33 eligible reports were included with 9550 cases and 10431 controls for the rs1799889 polymorphism, 5 reports with 2705 cases and 3168 controls for the rs2227631 polymorphism, and 4 reports with 2799 cases and 4011 controls for the rs2227667 polymorphism. The ORs and 95% CIs showed a statistically significant relationship between rs1799889 4G>5G polymorphism and cancer risk, especially in feminine cancer. The term refers to cancers that occur in the female reproductive system, such as ovarian, breast, endometrial and cervical cancer. Moreover, there was no association observed for the PAI-1 promoter A>G polymorphism (rs2227631 and rs2227667). In further subgroup analyses of 4G>5G polymorphism (rs1799889), an increased susceptibility to cancer was observed in Caucasians group and some types of cancer groups.

CONCLUSIONS

This article comes to a conclusion that the rs1799889 polymorphism might help to increase the risk of cancer; moreover, the susceptibility to feminine cancer is more evident.

Evolutionary and functional lessons from human-specific amino acid substitution matrices

Human genetic variation in coding regions is fundamental to the study of protein structure and function. Most methods for interpreting missense variants consider substitution measures derived from homologous proteins across different species. In this study, we introduce human-specific amino acid (AA) substitution matrices that are based on genetic variations in the modern human population. We analyzed the frequencies of >4.8M single nucleotide variants (SNVs) at codon and AA resolution and compiled human-centric substitution matrices that are fundamentally different from classic cross-species matrices (e.g. BLOSUM, PAM). Our matrices are asymmetric, with some AA replacements showing significant directional preference. Moreover, these AA matrices are only partly predicted by nucleotide substitution rates. We further test the utility of our matrices in exposing functional signals of experimentally-validated protein annotations. A significant reduction in AA transition frequencies was observed across nine post-translational modification (PTM) types and four ion-binding sites. Our results propose a purifying selection signal in the human proteome across a diverse set of functional protein annotations and provide an empirical baseline for interpreting human genetic variation in coding regions.

The Relevance of Genomic Epidemiology for Control of Tuberculosis in West Africa

Tuberculosis (TB), an airborne infectious disease caused by Mycobacterium tuberculosis complex (MTBC), remains a global health problem. West Africa has a unique epidemiology of TB that is characterized by medium- to high-prevalence. Moreover, the geographical restriction of M. africanum to the sub-region makes West Africa have an extra burden to deal with a two-in-one pathogen. The region is also burdened with low case detection, late reporting, poor treatment adherence leading to development of drug resistance and relapse. Sporadic studies conducted within the subregion report higher burden of drug resistant TB (DRTB) than previously thought. The need for more sensitive and robust tools for routine surveillance as well as to understand the mechanisms of DRTB and transmission dynamics for the design of effective control tools, cannot be overemphasized. The advancement in molecular biology tools including traditional fingerprinting and next generation sequencing (NGS) technologies offer reliable tools for genomic epidemiology. Genomic epidemiology provides in-depth insight of the nature of pathogens, circulating strains and their spread as well as prompt detection of the emergence of new strains. It also offers the opportunity to monitor treatment and evaluate interventions. Furthermore, genomic epidemiology can be used to understand potential emergence and spread of drug resistant strains and resistance mechanisms allowing the design of simple but rapid tools. In this review, we will describe the local epidemiology of MTBC, highlight past and current investigations toward understanding their biology and spread as well as discuss the relevance of genomic epidemiology studies to TB control in West Africa.

Bioinformatics Approach to Mitigate Mislabeling in EU Seafood Market and Protect Consumer Health

Fisheries products are some of the most traded commodities world-wide and the potential for fraud is a serious concern. Fish fraud represents a threat to human health and poses serious concerns due to the consumption of toxins, highly allergenic species, contaminates or zoonotic parasites, which may be present in substituted fish. The substitution of more expensive fish by cheaper species, with similar morphological characteristics but different origins, reflects the need for greater transparency and traceability upon which which the security of the entire seafood value-chain depends. Even though EU regulations have made significant progress in consumer information by stringent labelling requirements, fraud is still widespread. Many molecular techniques such as DNA barcoding provide valuable support to enhance the Common Fisheries Policy (CFP) in the protection of consumer interests by unequivocally detecting any kind of fraud. This paper aims to highlight both the engagement of EU fishery policy and the opportunity offered by new biotechnology instruments to mitigate the growing fraud in the globalized fish market and to enforce the food security system to protect consumers' health. In this paper, after a presentation of EU rules on fish labeling and a general overview on the current state of the global fish market, we discuss the public health implications and the opportunities offered by several techniques based on genetics, reporting a case study to show the efficacy of the DNA barcoding methodology in assessing fish traceability and identification, comparing different species of the Epinephelus genus, Mottled Grouper (Mycteroperca rubra) and Wreckfish (Polyprion americanus), often improperly sold with the commercial name of "grouper".

Selection of a Noninvasive Source of Human DNA Envisaging Genotyping Assays in Epidemiological Studies: Urine or Saliva?

Genetic epidemiology requires an appropriate approach to measure genetic variation within the population. The aim of this study was to evaluate the characteristics and genotyping results of DNA extracted from 2 human DNA sources, selected for their rapid and noninvasive sampling, and the use of simple and standardized protocols that are essential for large-scale epidemiologic studies. Saliva and urine samples were collected at the same day from 20 subjects aged 9-10 yr. Genomic DNA was extracted using commercial kits. Quantitative and qualitative evaluation was done by assessing the yield, the purity, and integrity of the extracted DNA. As a proof-of-concept, genotyping was performed targeting CC16 A38G and uteroglobin-related protein 1 (UGRP1)-112G/A. Saliva was found to provide the highest yield and concentration of total DNA extracted. Salivary DNA showed higher purity and a significantly less degraded state compared to urinary DNA. Consequently, the salivary DNA gave better genotyping results than urinary DNA. Therefore, if the choice exists, saliva is the preferred noninvasive matrix for genotyping purposes in large-scale genetic epidemiologic studies. Only in particular cases using urine could nevertheless be considered useful, although specific limitations need to be taken into account.

The influence of nutrigenetics on biomarkers of selenium nutritional status

Selenium (Se) is an essential micronutrient for human biology that executes its functions as the amino acid selenocysteine via selenoproteins, which have important functions in, for example, antioxidation, immunomodulation, thyroid metabolism, and human fertility. Se nutritional status is assessed using the quantification of blood Se biomarkers, which are influenced by several factors, including diet, age, gender, smoking status, alcohol consumption, health condition, and the genetic characteristics of individuals. Nutrigenetic studies have identified single nucleotide polymorphisms in selenoproteins that might clarify the high variability in values reported for biomarkers of Se nutritional status in different populations, and the response of these biomarkers to Se supplementation with either organic or inorganic forms of Se. This review aims to (1) define the basic aspects of Se biology, (2) describe the current most commonly used biomarkers of Se nutritional status, and (3) provide a summary of associations between functional single nucleotide polymorphisms in selenoproteins and biomarkers of Se status in healthy populations.

Effects of Single-Nucleotide Polymorphisms in Calmodulin-Dependent Protein Kinase Kinase 2 (CAMKK2): A Comprehensive Study

Calmodulin-dependent protein kinase kinase 2 (CAMKK2) is a protein kinase that belongs to the serine/threonine kinase family. It phosphorylates kinases like CAMK1, CAMK2, and AMP, and this signaling cascade is involved in various biological processes including cell proliferation, apoptosis, and proliferation. Also, the CAMKK2 signaling activity is required for the healthy activity of the brain which otherwise can cause diseases like bipolar disorders and anxiety. The current study is based on in silico bioinformatics analysis that combines sequence- and structure-based predictions to mark a SNP as damaging or neutral. The combined results from sequence-based, evolutionary conservation-based, and consensus-based tools have predicted a total of 18 nsSNPs as deleterious, and these nsSNPs were further subjected to structure-based analysis. The six mutant models of V195A, V249M, R311C, F366Y, P389T, and W445C showed a higher deviation from the wildtype protein model and hence were further taken for docking studies. The molecular docking analysis has predicted that these mutations will also be disruptive to the protein-protein interactions between CAMKK2 and PRKAG1 which will create an evident reduction in the kinase activity. The current study has enlightened us that a few of the significant mutations are prime candidates in CAMKK2 which could be the fundamental cause of various bipolar and psychiatric disorders. This is the first detailed study that predicts the deleterious nsSNPs in CAMKK2 and contributes positively in providing a better understanding of disease mechanisms.

Detecting DNA and RNA and Differentiating Single-Nucleotide Variations via Field-Effect Transistors

We detect short oligonucleotides and distinguish between sequences that differ by a single base, using label-free, electronic field-effect transistors (FETs). Our sensing platform utilizes ultrathin-film indium oxide FETs chemically functionalized with single-stranded DNA (ssDNA). The ssDNA-functionalized semiconducting channels in FETs detect fully complementary DNA sequences and differentiate these sequences from those having different types and locations of single base-pair mismatches. Changes in charge associated with surface-bound ssDNA vs double-stranded DNA (dsDNA) alter FET channel conductance to enable detection due to differences in DNA duplex stability. We illustrate the capability of ssDNA-FETs to detect complementary RNA sequences and to distinguish from RNA sequences with single nucleotide variations. The development and implementation of electronic biosensors that rapidly and sensitively detect and differentiate oligonucleotides present new opportunities in the fields of disease diagnostics and precision medicine.

Mutational analysis on predicting the impact of high-risk SNPs in human secretary phospholipase A2 receptor (PLA2R1)

PLA2R1 is a transmembrane glycoprotein that acts as an endogenous ligand which stimulates the processes including cell proliferation and cell migration. The SNPs in PLA2R1 is associated with idiopathic membranous nephropathy which is an autoimmune kidney disorder. The present study aimed to explore the structure-function analysis of high risk SNPs in PLA2R1 by using 12 different computational tools. First the functional annotation of SNPs were carried out by sequence based tools which were further subjected to evolutionary conservation analysis. Those SNPs which were predicted as deleterious in both categories were further considered for structure based analysis. The resultant SNPs were C1096S, C545S, C664S, F1257L, F734S, I1174T, I1114T, P177S, P384S, W1198G, W1328G, W692C, W692L, W962R, Y499H. One functional domain of PLA2R1 is already modelled in PDB (6JLI), the full 3D structure of the protein was predicted using I-TASSER homology modelling tool. The stability analysis, structure superimposition, RMSD calculation and docking studies were carried out. The structural analysis predicted four mutations F734S, F1246L, I1174T, W1198G as damaging to the structure of the protein. All these mutations are occurring at the conserved region of CTL domain hence are more likely to abolish the function of the protein. Up to the best of our knowledge, this is the first study that provides in-depth and in-silico analysis of deleterious mutations on structure and function of PLA2R1.

Single-Step Genomic Evaluations from Theory to Practice: Using SNP Chips and Sequence Data in BLUPF90

Single-step genomic evaluation became a standard procedure in livestock breeding, and the main reason is the ability to combine all pedigree, phenotypes, and genotypes available into one single evaluation, without the need of post-analysis processing. Therefore, the incorporation of data on genotyped and non-genotyped animals in this method is straightforward. Since 2009, two main implementations of single-step were proposed. One is called single-step genomic best linear unbiased prediction (ssGBLUP) and uses single nucleotide polymorphism (SNP) to construct the genomic relationship matrix; the other is the single-step Bayesian regression (ssBR), which is a marker effect model. Under the same assumptions, both models are equivalent. In this review, we focus solely on ssGBLUP. The implementation of ssGBLUP into the BLUPF90 software suite was done in 2009, and since then, several changes were made to make ssGBLUP flexible to any model, number of traits, number of phenotypes, and number of genotyped animals. Single-step GBLUP from the BLUPF90 software suite has been used for genomic evaluations worldwide. In this review, we will show theoretical developments and numerical examples of ssGBLUP using SNP data from regular chips to sequence data.

SNP Scanning in mecA Gene for Methicillin-Resistant Staphylococcus aureus

Background:

Staphylococcus aureus (SA) is known as an important human pathogen, which is responsible for many cases of both hospital and community-acquired infections all over the world. Studying on drug resistance is regarded as an important prevention strategy regarding these types of infections.

Objectives:

The current study is aimed to assess the association between the single-nucleotide polymorphism (SNP) and resistance to antibiotics in the methicillin-resistant Staphylococcus aureus (MRSA) strains as well as the molecular typing of isolates, collected from the clinical samples.

Materials and Methods:

We used the disc-diffusion method to test the isolates antibiotic resistance. In addition, the genotypes of staphylococcal cassette chromosome mec (SCCmec) in the Methicillin-resistant Staphylococcus aureus isolates were determined by multiplex -polymerase chain reaction (PCR). SNP was identified in the mecA gene using sequencing and amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) method.

Results:

The highest resistance was shown against oxacillin, and erythromycin and cephalexin. The most sensitive antibiotic was vancomycin (97%) and resistance to at least three antibiotic classes were identified in all isolates. Eighty six percent of isolates were positive for mecA gene and more than 50% of which were healthcare-acquired methicillin-resistant Staphylococcus aureus (HA-MRSA). Moreover, SCCmec type 3, 1were the predominant strains of the identified MRSA. Also, 23 isolates (23%) were non-typable. By using the ARMS-PCR method, it was found that 10% of the clinical specimens had SNP in the mecA gene.

Conclusion:

According to the Chi-square test (χ2), it reveals that the association between SNP in the mecA gene and oxacillin, cefoxitin, and erythromycin resistance was confirmed among clinical MRSA. Furthermore, there is a 95%probability of association between SNP and resistance to more than three antibiotics in MRSA strains.

ncRNA-eQTL: a database to systematically evaluate the effects of SNPs on non-coding RNA expression across cancer types

Numerous studies indicate that non-coding RNAs (ncRNAs) have critical functions across biological processes, and single-nucleotide polymorphisms (SNPs) could contribute to diseases or traits through influencing ncRNA expression. However, the associations between SNPs and ncRNA expression are largely unknown. Therefore, genome-wide expression quantitative trait loci (eQTL) analysis to assess the effects of SNPs on ncRNA expression, especially in multiple cancer types, will help to understand how risk alleles contribute toward tumorigenesis and cancer development. Using genotype data and expression profiles of ncRNAs of >8700 samples from The Cancer Genome Atlas (TCGA), we developed a computational pipeline to systematically identify ncRNA-related eQTLs (ncRNA-eQTLs) across 33 cancer types. We identified a total of 6 133 278 and 721 122 eQTL-ncRNA pairs in cis-eQTL and trans-eQTL analyses, respectively. Further survival analyses identified 8312 eQTLs associated with patient survival times. Furthermore, we linked ncRNA-eQTLs to genome-wide association study (GWAS) data and found 262 332 ncRNA-eQTLs overlapping with known disease- and trait-associated loci. Finally, a user-friendly database, ncRNA-eQTL (http://ibi.hzau.edu.cn/ncRNA-eQTL), was developed for free searching, browsing and downloading of all ncRNA-eQTLs. We anticipate that such an integrative and comprehensive resource will improve our understanding of the mechanistic basis of human complex phenotypic variation, especially for ncRNA- and cancer-related studies.

Genetic Association and Expression Correlation between Colony-Stimulating Factor 1 Gene Encoding M-CSF and Adult-Onset Still's Disease

Adult-onset Still's disease (AOSD) is a rare and inflammatory disorder characterized by spiking fever, rash, arthritis, and multisystemic involvement. HLA has been shown to be associated with AOSD; however, it could not explain the innate immunity and autoinflammatory characteristics of AOSD. To assess the genetic susceptibility of AOSD, we conducted a genome-wide association study (GWAS) on a cohort of 70 AOSD cases and 688 controls following a replication study of 36 cases and 200 controls and meta-analysis. The plasma concentrations of associated gene product were determined. The GWAS, replication, and combined sample analysis confirmed that SNP rs11102024 on 5'-upstream of CSF1 encoding macrophage colony-stimulating factor (M-CSF) was associated with AOSD (P = 1.20 × 10^-8, OR (95% CI): 3.28 (2.25~4.79)). Plasma levels of M-CSF increased in AOSD patients (n = 82, median: 9.31 pg/mL), particularly in the cases with activity score ≥ 6 (n = 42, 10.94 pg/mL), compared to the healthy donors (n = 68, 5.31 pg/mL) (P < 0.0001). Patients carrying rs11102024TT genotype had higher M-CSF levels (median: 20.28 pg/mL) than those with AA genotype (6.82 pg/mL) (P < 0.0001) or AT genotype (11.61 pg/mL) (P = 0.027). Patients with systemic pattern outcome were associated with elevated M-CSF and frequently observed in TT carriers. Our data suggest that genetic variants near CSF1 are associated with AOSD and the rs11102024 T allele links to higher M-CSF levels and systemic outcome. These results provide a promising initiative for the early intervention and therapeutic target of AOSD. Further investigation is needed to have better understandings and the clinical implementation of genetic variants nearby CSF1 in AOSD.

Standardized phylogenetic and molecular evolutionary analysis applied to species across the microbial tree of life

There is growing interest in reconstructing phylogenies from the copious amounts of genome sequencing projects that target related viral, bacterial or eukaryotic organisms. To facilitate the construction of standardized and robust phylogenies for disparate types of projects, we have developed a complete bioinformatic workflow, with a web-based component to perform phylogenetic and molecular evolutionary (PhaME) analysis from sequencing reads, draft assemblies or completed genomes of closely related organisms. Furthermore, the ability to incorporate raw data, including some metagenomic samples containing a target organism (e.g. from clinical samples with suspected infectious agents), shows promise for the rapid phylogenetic characterization of organisms within complex samples without the need for prior assembly.

HS-MMGKG: A Fast Multi-objective Harmony Search Algorithm for Two-locus Model Detection in GWAS

Background::

Genome-Wide Association Study (GWAS) plays a very important role in identifying the causes of a disease. Because most of the existing methods for genetic-interaction detection in GWAS are designed for a single-correlation model, their performances vary considerably for different disease models. These methods usually have high computation cost and low accuracy.

Method::

We present a new multi-objective heuristic optimization methodology named HSMMGKG for detecting genetic interactions. In HS-MMGKG, we use harmony search with five objective functions to improve the efficiency and accuracy. A new strategy based on p-value and MDR is adopted to generate more reasonable results. The Boolean representation in BOOST is modified to calculate the five functions rapidly. These strategies take less time complexity and have higher accuracy while detecting the potential models.

Results::

We compared HS-MMGKG with CSE, MACOED and FHSA-SED using 26 simulated datasets. The experimental results demonstrate that our method outperforms others in accuracy and computation time. Our method has identified many two-locus SNP combinations that are associated with seven diseases in WTCCC dataset. Some of the SNPs have direct evidence in CTD database. The results may be helpful to further explain the pathogenesis.

Conclusion::

It is anticipated that our proposed algorithm could be used in GWAS which is helpful in understanding disease mechanism, diagnosis and prognosis.

Strong Linkage of the Single Nucleotide Polymorphism rs77308790 with an α0-Thalassemia (- -SEA deletion) Allele and Application for Double-Check Diagnosis of Hb Bart's Hydrops Fetalis Syndrome in Thailand

The α⁰-thalassemia (α⁰-thal) [- -^SEA (Southeast Asian) deletion] is highly prevalent in Southeast Asia and South China. The linkage between the single nucleotide polymorphism (SNP) rs77308790 and the - -^SEA deletion was reported in the Chinese population. This study reported the genotype of SNP rs77308790 using the high resolution melting (HRM) curve analysis in the Thai population and the application for double-checking diagnosis of Hb Bart's (γ4) hydrops fetalis syndrome. A total of 202 samples, including α⁰-thal carriers (- -^SEA/αα) (n = 99) and wild-type (n = 103), was recruited. Minor allele frequency (MAF) of SNP rs77308790 (T allele) represented a significant difference (p<0.001) between carrier (- -^SEA deletion) (MAF 0.455) and wild-type (MAF 0.039). The T allele of SNP rs77308790 showed a strong linkage with the - -^SEA deletion allele [correlation coefficient between pairs of loci (D' = 1)] based on constructed random samples (CRSs) in Thais. Moreover, worldwide populations, based on the 1000Genomes database, also found the T allele to be less than 1.0%. For providing a double-checked diagnosis, two SNP (rs3760053, rs77308790) genotypes showed 100.0% concordance with a conventional gap-polymerase chain reaction (gap-PCR) method in nine families at-risk for Hb Bart's hydrops fetalis. The double-checked diagnosis based on the two SNPs (rs3760053, rs77308790) is suitable for implementation in routine diagnosis of Hb Bart's hydrops fetalis syndrome. Furthermore, our HRM analysis system can be amplified with a small amount of fetal DNA and could avoid allele dropouts.

Genetic Polymorphisms of Pharmacogenomic VIP Variants in the Circassian Subpopulation from Jordan

BACKGROUND

It has been suggested that genetic variation within candidate pharmacogenes contributes to the differences in drug safety and efficacy as well as risk of adverse drug reactions among different ethnic groups. Illustrating the polymorphic distribution of Very Important Pharmacogenes (VIPs) in various ethnic groups will contribute to the development of personalized medicine for those populations.

OBJECTIVE

The present study aimed to identify the polymorphic distribution of VIPs in the Circassian subpopulation of Jordan and compare their allele frequencies with those of other populations.

METHODS

A total of 130 healthy and unrelated Circassian adults from Jordan were randomly recruited and genotyped for eleven VIP variants within the thiopurine S-methyltransferase (TPMT), ATP-binding cassette, sub-family B, member 1 (ABCB1), and vitamin D receptor (VDR) genes via Sequenom's MassARRAY® genotyping platform (iPLEX GOLD).

RESULTS

Our data on the allelic frequencies of the investigated VIP variants were compared to those of 18 other populations, comprising 11 HapMap populations, 6 Exome Aggregation Consortium populations, and the Chechen- Jordanian population from Jordan. Circassian-Jordanians were found to most resemble the African, Chechen- Jordanian, European (Finnish), European (non-Finnish), and South-Asian populations.

CONCLUSION

Circassians from Jordan significantly differ from other populations in terms of the allelic frequencies of selected VIP variants. The present findings constitute the first set of pharmacogenetic data for Circassian population from Jordan, providing a basis for safe drug administration that may be useful in diagnosing and treating diseases in this ethnic group.

PancanQTL: systematic identification of cis-eQTLs and trans-eQTLs in 33 cancer types

Expression quantitative trait locus (eQTL) analysis, which links variations in gene expression to genotypes, is essential to understanding gene regulation and to interpreting disease-associated loci. Currently identified eQTLs are mainly in samples of blood and other normal tissues. However, no database comprehensively provides eQTLs in large number of cancer samples. Using the genotype and expression data of 9196 tumor samples in 33 cancer types from The Cancer Genome Atlas (TCGA), we identified 5 606 570 eQTL-gene pairs in the cis-eQTL analysis and 231 210 eQTL-gene pairs in the trans-eQTL analysis. We further performed survival analysis and identified 22 212 eQTLs associated with patient overall survival. Furthermore, we linked the eQTLs to genome-wide association studies (GWAS) data and identified 337 131 eQTLs that overlap with existing GWAS loci. We developed PancanQTL, a user-friendly database (http://bioinfo.life.hust.edu.cn/PancanQTL/), to store cis-eQTLs, trans-eQTLs, survival-associated eQTLs and GWAS-related eQTLs to enable searching, browsing and downloading. PancanQTL could help the research community understand the effects of inherited variants in tumorigenesis and development.

Association of Fc gamma-receptor genes polymorphisms with chronic periodontitis and Peri-Implantitis

This study was conducted on 87 patients with chronic periodontitis (CP), 50 patients with peri-implantitis and 90 periodontally healthy individuals referring to the Department of Periodontics for evaluating the association between Fc gamma-receptor genes polymorphisms with CP and peri-implantitis. After obtaining consent, venous blood samples (5cc) were obtained from patients and DNA was extracted using Miller's salting-out method. Polymerase chain reaction (PCR)-restriction fragment length polymorphism and tetra-primer amplification refractory mutation system-PCR methods were used to assess the polymorphisms of FcγRs IIa, IIIa, and IIIb genes. Analyzing showed a significant association between specific genotypes with increasing CP and peri-implantitis risks in codominant and dominant models. For FcγR IIIa, analyzing revealed a significant association between specific genotypes with increasing CP and peri-implantitis risks in codominant, dominant, and recessive models. For FcγR IIIb, we also detected a significant association between specific genotypes with increasing CP and peri-implantitis risks in codominant, dominant, and recessive models ( P < 0.05). According to the results of this study, the FCGRIIa (rs1801274), FCGRIIIa (rs396991), and FCGRIIIb (rs1050501) polymorphisms were significantly associated with CP and peri-implantitis and may have a role in the pathogenesis of these diseases.

A new Multi Locus Variable Number of Tandem Repeat Analysis Scheme for epidemiological surveillance of Xanthomonas vasicola pv. musacearum, the plant pathogen causing bacterial wilt on banana and enset

Xanthomonas vasicola pv. musacearum (Xvm) which causes Xanthomonas wilt (XW) on banana (Musa accuminata x balbisiana) and enset (Ensete ventricosum), is closely related to the species Xanthomonas vasicola that contains the pathovars vasculorum (Xvv) and holcicola (Xvh), respectively pathogenic to sugarcane and sorghum. Xvm is considered a monomorphic bacterium whose intra-pathovar diversity remains poorly understood. With the sudden emergence of Xvm within east and central Africa coupled with the unknown origin of one of the two sublineages suggested for Xvm, attention has shifted to adapting technologies that focus on identifying the origin and distribution of the genetic diversity within this pathogen. Although microbiological and conventional molecular diagnostics have been useful in pathogen identification. Recent advances have ushered in an era of genomic epidemiology that aids in characterizing monomorphic pathogens. To unravel the origin and pathways of the recent emergence of XW in Eastern and Central Africa, there was a need for a genotyping tool adapted for molecular epidemiology. Multi-Locus Variable Number of Tandem Repeat Analysis (MLVA) is able to resolve the evolutionary patterns and invasion routes of a pathogen. In this study, we identified microsatellite loci from nine published Xvm genome sequences. Of the 36 detected microsatellite loci, 21 were selected for primer design and 19 determined to be highly typeable, specific, reproducible and polymorphic with two- to four- alleles per locus on a sub-collection. The 19 markers were multiplexed and applied to genotype 335 Xvm strains isolated from seven countries over several years. The microsatellite markers grouped the Xvm collection into three clusters; with two similar to the SNP-based sublineages 1 and 2 and a new cluster 3, revealing an unknown diversity in Ethiopia. Five of the 19 markers had alleles present in both Xvm and Xanthomonas vasicola pathovars holcicola and vasculorum, supporting the phylogenetic closeliness of these three pathovars. Thank to the public availability of the haplotypes on the MLVABank database, this highly reliable and polymorphic genotyping tool can be further used in a transnational surveillance network to monitor the spread and evolution of XW throughout Africa.. It will inform and guide management of Xvm both in banana-based and enset-based cropping systems. Due to the suitability of MLVA-19 markers for population genetic analyses, this genotyping tool will also be used in future microevolution studies.

Persistent Infection and Long-Term Carriage of Typhoidal and Nontyphoidal Salmonellae

The ability of pathogenic bacteria to affect higher organisms and cause disease is one of the most dramatic properties of microorganisms. Some pathogens can establish transient colonization only, but others are capable of infecting their host for many years or even for a lifetime. Long-term infection is called persistence, and this phenotype is fundamental for the biology of important human pathogens, including Helicobacter pylori, Mycobacterium tuberculosis, and Salmonella enterica Both typhoidal and nontyphoidal serovars of the species Salmonella enterica can cause persistent infection in humans; however, as these two Salmonella groups cause clinically distinct diseases, the characteristics of their persistent infections in humans differ significantly. Here, following a general summary of Salmonella pathogenicity, host specificity, epidemiology, and laboratory diagnosis, I review the current knowledge about Salmonella persistence and discuss the relevant epidemiology of persistence (including carrier rate, duration of shedding, and host and pathogen risk factors), the host response to Salmonella persistence, Salmonella genes involved in this lifestyle, as well as genetic and phenotypic changes acquired during prolonged infection within the host. Additionally, I highlight differences between the persistence of typhoidal and nontyphoidal Salmonella strains in humans and summarize the current gaps and limitations in our understanding, diagnosis, and curing of persistent Salmonella infections.