scholarly journals Genome-Wide Association Studies for the Detection of Genetic Variants Associated With Daptomycin and Ceftaroline Resistance in Staphylococcus aureus

2021 ◽  
Vol 12 ◽  
Author(s):  
Robert E. Weber ◽  
Stephan Fuchs ◽  
Franziska Layer ◽  
Anna Sommer ◽  
Jennifer K. Bender ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Genetic Variants ◽  
Association Studies ◽  
Rapid Development ◽  
Genome Wide Association ◽  
Resistant Isolate ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Resistance Traits

BackgroundAs next generation sequencing (NGS) technologies have experienced a rapid development over the last decade, the investigation of the bacterial genetic architecture reveals a high potential to dissect causal loci of antibiotic resistance phenotypes. Although genome-wide association studies (GWAS) have been successfully applied for investigating the basis of resistance traits, complex resistance phenotypes have been omitted so far. For S. aureus this especially refers to antibiotics of last resort like daptomycin and ceftaroline. Therefore, we aimed to perform GWAS for the identification of genetic variants associated with DAP and CPT resistance in clinical S. aureus isolates.Materials/methodsTo conduct microbial GWAS, we selected cases and controls according to their clonal background, date of isolation, and geographical origin. Association testing was performed with PLINK and SEER analysis. By using in silico analysis, we also searched for rare genetic variants in candidate loci that have previously been described to be involved in the development of corresponding resistance phenotypes.ResultsGWAS revealed MprF P314L and L826F to be significantly associated with DAP resistance. These mutations were found to be homogenously distributed among clonal lineages suggesting convergent evolution. Additionally, rare and yet undescribed single nucleotide polymorphisms could be identified within mprF and putative candidate genes. Finally, we could show that each DAP resistant isolate exhibited at least one amino acid substitution within the open reading frame of mprF. Due to the presence of strong population stratification, no genetic variants could be associated with CPT resistance. However, the investigation of the staphylococcal cassette chromosome mec (SCCmec) revealed various mecA SNPs to be putatively linked with CPT resistance. Additionally, some CPT resistant isolates revealed no mecA mutations, supporting the hypothesis that further and still unknown resistance determinants are crucial for the development of CPT resistance in S. aureus.ConclusionWe hereby confirmed the potential of GWAS to identify genetic variants that are associated with antibiotic resistance traits in S. aureus. However, precautions need to be taken to prevent the detection of spurious associations. In addition, the implementation of different approaches is still essential to detect multiple forms of variations and mutations that occur with a low frequency.

scholarly journals A Genome-Wide Association Study of Novel Genetic Variants Associated With Anthropometric Traits in Koreans

2021 ◽  
Vol 12 ◽  
Author(s):  
Hye-Won Cho ◽  
Hyun-Seok Jin ◽  
Yong-Bin Eom
Keyword(s):  
Genetic Variants ◽  
Genetic Factors ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Fat Distribution ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
A Genome

Most previous genome-wide association studies (GWAS) have identified genetic variants associated with anthropometric traits. However, most of the evidence were reported in European populations. Anthropometric traits such as height and body fat distribution are significantly affected by gender and genetic factors. Here we performed GWAS involving 64,193 Koreans to identify the genetic factors associated with anthropometric phenotypes including height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip ratio. We found nine novel single-nucleotide polymorphisms (SNPs) and 59 independent genetic signals in genomic regions that were reported previously. Of the 19 SNPs reported previously, eight genetic variants at RP11-513I15.6 and one genetic variant at the RP11-977G19.10 region and six Asian-specific genetic variants were newly found. We compared our findings with those of previous studies in other populations. Five overlapping genetic regions (PAN2, ANKRD52, RNF41, HGMA1, and C6orf106) had been reported previously but none of the SNPs were independently identified in the current study. Seven of the nine newly found novel loci associated with height in women revealed a statistically significant skeletal expression of quantitative trait loci. Our study provides additional insight into the genetic effects of anthropometric phenotypes in East Asians.

scholarly journals A fast and agnostic method for bacterial genome-wide association studies: bridging the gap between kmers and genetic events

2018 ◽  
Author(s):  
Magali Jaillard ◽  
Leandro Lima ◽  
Maud Tournoud ◽  
Pierre Mahé ◽  
Alex van Belkum ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Genetic Variants ◽  
Association Studies ◽  
Bacterial Species ◽  
Bacterial Genome ◽  
Genome Wide Association ◽  
Compact Set ◽  
Genome Wide Association Studies ◽  
Alignment Free ◽  
Genome Wide

AbstractMotivationGenome-wide association study (GWAS) methods applied to bacterial genomes have shown promising results for genetic marker discovery or fine-assessment of marker effect. Recently, alignment-free methods based on kmer composition have proven their ability to explore the accessory genome. However, they lead to redundant descriptions and results which are hard to interpret.MethodsHere, we introduce DBGWAS, an extended kmer-based GWAS method producing interpretable genetic variants associated with pheno-types. Relying on compacted De Bruijn graphs (cDBG), our method gathers cDBG nodes identified by the association model into subgraphs defined from their neighbourhood in the initial cDBG. DBGWAS is fast, alignment-free and only requires a set of contigs and phenotypes. It produces annotated subgraphs representing local polymorphisms as well as mobile genetic elements (MGE) and offers a graphical framework to interpret GWAS results.ResultsWe validated our method using antibiotic resistance phenotypes for three bacterial species. DBGWAS recovered known resistance determinants such as mutations in core genes in Mycobacterium tuberculosis and genes acquired by horizontal transfer in Staphylococcus aureus and Pseudomonas aeruginosa – along with their MGE context. It also enabled us to formulate new hypotheses involving genetic variants not yet described in the antibiotic resistance literature.ConclusionOur novel method proved its efficiency to retrieve any type of phenotype-associated genetic variant without prior knowledge. All experiments were computed in less than two hours and produced a compact set of meaningful subgraphs, thereby outperforming other GWAS approaches and facilitating the interpretation of the results.AvailabilityOpen-source tool available at https://gitlab.com/leoisl/dbgwas

scholarly journals Editing GWAS: experimental approaches to dissect and exploit disease-associated genetic variation

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Shuquan Rao ◽  
Yao Yao ◽  
Daniel E. Bauer
Keyword(s):  
Genome Editing ◽  
Genetic Variants ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Functional Studies ◽  
Functional Genetics ◽  
Genome Wide ◽  
Causal Variants ◽  
Experimental Approaches

AbstractGenome-wide association studies (GWAS) have uncovered thousands of genetic variants that influence risk for human diseases and traits. Yet understanding the mechanisms by which these genetic variants, mainly noncoding, have an impact on associated diseases and traits remains a significant hurdle. In this review, we discuss emerging experimental approaches that are being applied for functional studies of causal variants and translational advances from GWAS findings to disease prevention and treatment. We highlight the use of genome editing technologies in GWAS functional studies to modify genomic sequences, with proof-of-principle examples. We discuss the challenges in interrogating causal variants, points for consideration in experimental design and interpretation of GWAS locus mechanisms, and the potential for novel therapeutic opportunities. With the accumulation of knowledge of functional genetics, therapeutic genome editing based on GWAS discoveries will become increasingly feasible.

scholarly journals CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies

2019 ◽  
Author(s):  
Jianhua Wang ◽  
Dandan Huang ◽  
Yao Zhou ◽  
Hongcheng Yao ◽  
Huanhuan Liu ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Genetic Variants ◽  
Association Studies ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Genome Wide ◽  
Credible Sets ◽  
Causal Variants

Abstract Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.

scholarly journals The Mediation Effects of Aluminum in Plasma and Dipeptidyl Peptidase Like Protein 6 (DPP6) Polymorphism on Renal Function via Genome-Wide Typing Association

2021 ◽  
Vol 18 (19) ◽  
pp. 10484
Author(s):  
Ting-Hao Chen ◽  
Chen-Cheng Yang ◽  
Kuei-Hau Luo ◽  
Chia-Yen Dai ◽  
Yao-Chung Chuang ◽  
...  
Keyword(s):  
Renal Function ◽  
Mediation Analysis ◽  
Association Studies ◽  
Dipeptidyl Peptidase ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Mediation Effects ◽  
Genome Wide ◽  
Estimated Glomerular Filtration Rates

Aluminum (Al) toxicity is related to renal failure and the failure of other systems. Although there were some genome-wide association studies (GWAS) in Australia and England, there were no GWAS about Han Chinese to our knowledge. Thus, this research focused on using whole genomic genotypes from the Taiwan Biobank for exploring the association between Al concentrations in plasma and renal function. Participants, who underwent questionnaire interviews, biomarkers, and genotyping, were from the Taiwan Biobank database. Then, we measured their plasma Al concentrations with ICP-MS in the laboratory at Kaohsiung Medical University. We used this data to link genome-wide association (GWA) tests while looking for candidate genes and associated plasma Al concentration to renal function. Furthermore, we examined the path relationship between Single Nucleotide Polymorphisms (SNPs), Al concentrations, and estimated glomerular filtration rates (eGFR) through the mediation analysis with 3000 replication bootstraps. Following the principles of GWAS, we focused on three SNPs within the dipeptidyl peptidase-like protein 6 (DPP6) gene in chromosome 7, rs10224371, rs2316242, and rs10268004, respectively. The results of the mediation analysis showed that all of the selected SNPs have indirectly affected eGFR through a mediation of Al concentrations. Our analysis revealed the association between DPP6 SNPs, plasma Al concentrations, and eGFR. However, further longitudinal studies and research on mechanism are in need. Our analysis was still be the first study that explored the association between the DPP6, SNPs, and Al in plasma affecting eGFR.

scholarly journals Genome-wide association studies of yield-related traits in high-latitude japonica rice

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Guomin Zhang ◽  
Rongsheng Wang ◽  
Juntao Ma ◽  
Hongru Gao ◽  
Lingwei Deng ◽  
...  
Keyword(s):  
Linear Model ◽  
High Latitude ◽  
Association Studies ◽  
Genome Wide Association ◽  
Japonica Rice ◽  
Genome Wide Association Studies ◽  
Heilongjiang Province ◽  
Nucleotide Polymorphisms ◽  
Coding Region ◽  
Genome Wide

Abstract Background Heilongjiang Province is a high-quality japonica rice cultivation area in China. One in ten bowls of Chinese rice is produced here. Increasing yield is one of the main aims of rice production in this area. However, yield is a complex quantitative trait composed of many factors. The purpose of this study was to determine how many genetic loci are associated with yield-related traits. Genome-wide association studies (GWAS) were performed on 450 accessions collected from northeast Asia, including Russia, Korea, Japan and Heilongjiang Province of China. These accessions consist of elite varieties and landraces introduced into Heilongjiang Province decade ago. Results After resequencing of the 450 accessions, 189,019 single nucleotide polymorphisms (SNPs) were used for association studies by two different models, a general linear model (GLM) and a mixed linear model (MLM), examining four traits: days to heading (DH), plant height (PH), panicle weight (PW) and tiller number (TI). Over 25 SNPs were found to be associated with each trait. Among them, 22 SNPs were selected to identify candidate genes, and 2, 8, 1 and 11 SNPs were found to be located in 3′ UTR region, intron region, coding region and intergenic region, respectively. Conclusions All SNPs detected in this research may become candidates for further fine mapping and may be used in the molecular breeding of high-latitude rice.

scholarly journals GWASdb: a database for human genetic variants identified by genome-wide association studies

2011 ◽  
Vol 40 (D1) ◽  
pp. D1047-D1054 ◽  
Author(s):  
Mulin Jun Li ◽  
Panwen Wang ◽  
Xiaorong Liu ◽  
Ee Lyn Lim ◽  
Zhangyong Wang ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals GWASdb v2: an update database for human genetic variants identified by genome-wide association studies

2015 ◽  
Vol 44 (D1) ◽  
pp. D869-D876 ◽  
Author(s):  
Mulin Jun Li ◽  
Zipeng Liu ◽  
Panwen Wang ◽  
Maria P. Wong ◽  
Matthew R. Nelson ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Modeling gene-covariate interactions in sparse regression with group structure for genome-wide association studies

2015 ◽  
Vol 14 (3) ◽  
Author(s):  
Yun Li ◽  
George T. O’Connor ◽  
Josée Dupuis ◽  
Eric Kolaczyk
Keyword(s):  
Genetic Variants ◽  
Immunoglobulin E ◽  
Group Structure ◽  
Association Studies ◽  
Genome Wide Association ◽  
Estimation Methods ◽  
Biological Knowledge ◽  
Genome Wide Association Studies ◽  
Sparse Regression ◽  
Genome Wide

AbstractIn genome-wide association studies (GWAS), it is of interest to identify genetic variants associated with phenotypes. For a given phenotype, the associated genetic variants are usually a sparse subset of all possible variants. Traditional Lasso-type estimation methods can therefore be used to detect important genes. But the relationship between genotypes at one variant and a phenotype may be influenced by other variables, such as sex and life style. Hence it is important to be able to incorporate gene-covariate interactions into the sparse regression model. In addition, because there is biological knowledge on the manner in which genes work together in structured groups, it is desirable to incorporate this information as well. In this paper, we present a novel sparse regression methodology for gene-covariate models in association studies that not only allows such interactions but also considers biological group structure. Simulation results show that our method substantially outperforms another method, in which interaction is considered, but group structure is ignored. Application to data on total plasma immunoglobulin E (IgE) concentrations in the Framingham Heart Study (FHS), using sex and smoking status as covariates, yields several potentially interesting gene-covariate interactions.

scholarly journals Secure large-scale genome-wide association studies using homomorphic encryption

2020 ◽  
Vol 117 (21) ◽  
pp. 11608-11613 ◽  
Author(s):  
Marcelo Blatt ◽  
Alexander Gusev ◽  
Yuriy Polyakov ◽  
Shafi Goldwasser
Keyword(s):  
Large Scale ◽  
Homomorphic Encryption ◽  
Association Studies ◽  
Genome Wide Association ◽  
Single Server ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
User Interactions ◽  
Individual Level ◽  
Genome Wide

Genome-wide association studies (GWASs) seek to identify genetic variants associated with a trait, and have been a powerful approach for understanding complex diseases. A critical challenge for GWASs has been the dependence on individual-level data that typically have strict privacy requirements, creating an urgent need for methods that preserve the individual-level privacy of participants. Here, we present a privacy-preserving framework based on several advances in homomorphic encryption and demonstrate that it can perform an accurate GWAS analysis for a real dataset of more than 25,000 individuals, keeping all individual data encrypted and requiring no user interactions. Our extrapolations show that it can evaluate GWASs of 100,000 individuals and 500,000 single-nucleotide polymorphisms (SNPs) in 5.6 h on a single server node (or in 11 min on 31 server nodes running in parallel). Our performance results are more than one order of magnitude faster than prior state-of-the-art results using secure multiparty computation, which requires continuous user interactions, with the accuracy of both solutions being similar. Our homomorphic encryption advances can also be applied to other domains where large-scale statistical analyses over encrypted data are needed.

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