Genome-wide Association Study Approach Research Articles

Multivariate GWAS of Structural Dental Anomalies and Dental Caries in a Multi-Ethnic Cohort.

Odontogenesis is a complex process, where disruption can result in dental anomalies and/or increase the risk of developing dental caries. Based on previous studies, certain dental anomalies tend to co-occur in patients, suggesting that these traits may share common genetic and etiological components. The main goal of this study was to implement a multivariate genome-wide association study approach to identify genetic variants shared between correlated structural dental anomalies and dental caries. Our cohort (N = 3,579) was derived from the Pittsburgh Orofacial Clefts Study, where multiple dental traits were assessed in both the unaffected relatives of orofacial cleft (OFC) cases (n = 2,187) and unaffected controls (n = 1,392). We identified four multivariate patterns of correlated traits in this data: tooth agenesis, impaction, and rotation (AIR); enamel hypoplasia, displacement, and rotation (HDR); displacement, rotation, and mamelon (DRM); and dental caries, tooth agenesis and enamel hypoplasia (CAH). We analyzed each of these four models using genome-wide multivariate tests of association. No genome-wide statistically significant results were found, but we identified multiple suggestive association signals (P < 10-5) near genes with known biological roles during tooth development, including ADAMTS9 and PRICKLE2 associated with AIR; GLIS3, WDR72, and ROR2 associated with HDR and DRM; ROBO2 associated with DRM; BMP7 associated with HDR; and ROBO1, SMAD2, and MSX2 associated with CAH. This is the first study to investigate genetic associations for multivariate patterns of correlated dental anomalies and dental caries. Further studies are needed to replicate these results in independent cohorts.

Identification of Quantitative Trait Loci for Leaf Rust and Stem Rust Seedling Resistance in Bread Wheat Using a Genome-Wide Association Study.

In recent years, leaf rust (LR) and stem rust (SR) have become a serious threat to bread wheat production in Kazakhstan. Most local cultivars are susceptible to these rusts, which has affected their yield and quality. The development of new cultivars with high productivity and LR and SR disease resistance, including using marker-assisted selection, is becoming an important priority in local breeding projects. Therefore, the search for key genetic factors controlling resistance in all plant stages, including the seedling stage, is of great significance. In this work, we applied a genome-wide association study (GWAS) approach using 212 local bread wheat accessions that were phenotyped for resistance to specific races of Puccinia triticina Eriks. (Pt) and Puccinia graminis f. sp. tritici (Pgt) at the seedling stages. The collection was genotyped using a 20 K Illumina iSelect SNP assay, and 11,150 polymorphic SNP markers were selected for the association mapping. Using a mixed linear model, we identified 11 quantitative trait loci (QTLs) for five out of six specific races of Pt and Pgt. The comparison of the results from this GWAS with those from previously published work showed that nine out of eleven QTLs for LR and SR resistance had been previously reported in a GWAS study at the adult plant stages of wheat growth. Therefore, it was assumed that these nine common identified QTLs were effective for all-stage resistance to LR and SR, and the two other QTLs appear to be novel QTLs. In addition, five out of these nine QTLs that had been identified earlier were found to be associated with yield components, suggesting that they may directly influence the field performance of bread wheat. The identified QTLs, including novel QTLs found in this study, may play an essential role in the breeding process for improving wheat resistance to LR and SR.

Genome-Wide Association Analysis of Stable Stripe Rust Resistance Loci in a Chinese Wheat Landrace Panel Using the 660K SNP Array.

Stripe rust (caused by Puccinia striiformis f. sp. tritici) is one of the most severe diseases affecting wheat production. The disease is best controlled by developing and growing resistant cultivars. Chinese wheat (Triticum aestivum) landraces have excellent resistance to stripe rust. The objectives of this study were to identify wheat landraces with stable resistance and map quantitative trait loci (QTL) for resistance to stripe rust from 271 Chinese wheat landraces using a genome-wide association study (GWAS) approach. The landraces were phenotyped for stripe rust responses at the seedling stage with two predominant Chinese races of P. striiformis f. sp. tritici in a greenhouse and the adult-plant stage in four field environments and genotyped using the 660K wheat single-nucleotide polymorphism (SNP) array. Thirteen landraces with stable resistance were identified, and 17 QTL, including eight associated to all-stage resistance and nine to adult-plant resistance, were mapped on chromosomes 1A, 1B, 2A, 2D, 3A, 3B, 5A, 5B, 6D, and 7A. These QTL explained 6.06–16.46% of the phenotypic variation. Five of the QTL, QYrCL.sicau-3AL, QYrCL.sicau-3B.4, QYrCL.sicau-3B.5, QYrCL.sicau-5AL.1 and QYrCL.sicau-7AL, were likely new. Five Kompetitive allele specific PCR (KASP) markers for four of the QTL were converted from the significant SNP markers. The identified wheat landraces with stable resistance to stripe rust, significant QTL, and KASP markers should be useful for breeding wheat cultivars with durable resistance to stripe rust.

Unravelling Rubber Tree Growth by Integrating GWAS and Biological Network-Based Approaches.

Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs.

Systems biology analysis of human genomes points to key pathways conferring spina bifida risk

Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases versus controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation, and essential transcriptional regulation consistent with their having impact on the pathogenesis of human SB. Additionally, an interrogation of conserved noncoding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to the interrogation of coding and noncoding sequence variant contributions to rare complex genetic disorders.

Genome wide association study of plant height and tiller number in hulless barley

Hulless barley (Hordeum vulgare L. var. nudum), also called naked barley, is a unique variety of cultivated barley. The genome-wide specific length amplified fragment sequencing (SLAF-seq) method is a rapid deep sequencing technology that is used for the selection and identification of genetic loci or markers. In this study, we collected 300 hulless barley accessions and used the SLAF-seq method to identify candidate genes involved in plant height (PH) and tiller number (TN). We obtained a total of 1407 M paired-end reads, and 228,227 SLAF tags were developed. After filtering using an integrity threshold of >0.8 and a minor allele frequency of >0.05, 14,504,892 single-nucleotide polymorphisms (SNP) loci were screened out. The remaining SNPs were used for the construction of a neighbour-joining phylogenetic tree, and the three subcluster members showed no obvious differentiation among regional varieties. We used a genome wide association study approach to identify 1006 and 113 SNPs associated with TN and PH, respectively. Based on best linear unbiased predictors (BLUP), 41 and 29 SNPs associated with TN and PH, respectively. Thus, several of genes, including Hd3a and CKX5, may be useful candidates for the future genetic breeding of hulless barley. Taken together, our results provide insight into the molecular mechanisms controlling barley architecture, which is important for breeding and yield.

Dissecting four correlated growth period traits using a genome-wide association study approach in soybean

Soybean [Glycine max (L.) Merr.] is a short-day, photoperiod-sensitive crop. The vegetative growth period (V), reproductive growth period (R), whole growth period (V + R) and the ratio of growth period structure (R/V) are photoperiod traits critical to adaptability and yield in soybean. To thoroughly dissect the genetic basis of these growth period traits and their correlations, a panel of 277 soybean accessions were genotyped with a single nucleotide polymorphisms (SNPs) panel and phenotyped at three field environments over three years. A genome-wide association study found 28 SNPs on fifteen chromosomes with 33 significant marker-trait associations, eleven, eight, four and ten for V, R, V + R and R/V, respectively. Two SNPs, Map-6077 and -6502, showed pleiotropy in three and two traits, respectively. Map-6077, associated with V, R, and V + R, was a synonymous SNP of the GmMFT, a member of PEBP family that has been reported to inhibit seed germination and regulate oil content. These results provide candidate SNP markers and genes for further functional experiments to advance molecular marker-assisted breeding.

Genetic evaluation of dementia with Lewy bodies implicates distinct disease subgroups.

The APOE locus is strongly associated with risk for developing Alzheimer's disease and dementia with Lewy bodies. In particular, the role of the APOE ε4 allele as a putative driver of α-synuclein pathology is a topic of intense debate. Here, we performed a comprehensive evaluation in 2466 dementia with Lewy bodies cases versus 2928 neurologically healthy, aged controls. Using an APOE-stratified genome-wide association study approach, we found that GBA is associated with risk for dementia with Lewy bodies in patients without APOE ε4 (P = 6.58 × 10-9, OR = 3.41, 95% CI = 2.25-5.17), but not with dementia with Lewy bodies with APOE ε4 (P = 0.034, OR = 1.87, 95%, 95% CI = 1.05-3.37). We then divided 495 neuropathologically examined dementia with Lewy bodies cases into three groups based on the extent of concomitant Alzheimer's disease co-pathology: pure dementia with Lewy bodies (n = 88), dementia with Lewy bodies with intermediate Alzheimer's disease co-pathology (n = 66) and dementia with Lewy bodies with high Alzheimer's disease co-pathology (n = 341). In each group, we tested the association of the APOE ε4 against the 2928 neurologically healthy controls. Our examination found that APOE ε4 was associated with dementia with Lewy bodies + Alzheimer's disease (P = 1.29 × 10-32, OR = 4.25, 95% CI = 3.35-5.39) and dementia with Lewy bodies + intermediate Alzheimer's disease (P = 0.0011, OR = 2.31, 95% CI = 1.40-3.83), but not with pure dementia with Lewy bodies (P = 0.31, OR = 0.75, 95% CI = 0.43-1.30). In conclusion, although deep clinical data were not available for these samples, our findings do not support the notion that APOE ε4 is an independent driver of α-synuclein pathology in pure dementia with Lewy bodies, but rather implicate GBA as the main risk gene for the pure dementia with Lewy bodies subgroup.

Identification of Novel Quantitative Trait Nucleotides and Candidate Genes for Bacterial Wilt Resistance in Tobacco (Nicotiana tabacum L.) Using Genotyping-by-Sequencing and Multi-Locus Genome-Wide Association Studies.

Tobacco bacterial wilt (TBW) is a devastating soil-borne disease threatening the yield and quality of tobacco. However, its genetic foundations are not fully understood. In this study, we identified 126,602 high-quality single-nucleotide polymorphisms (SNPs) in 94 tobacco accessions using genotyping-by-sequencing (GBS) and a 94.56 KB linkage disequilibrium (LD) decay rate for candidate gene selection. The population structure analysis revealed two subpopulations with 37 and 57 tobacco accessions. Four multi-locus genome-wide association study (ML-GWAS) approaches identified 142 quantitative trait nucleotides (QTNs) in E1–E4 and the best linear unbiased prediction (BLUP), explaining 0.49–22.52% phenotypic variance. Of these, 38 novel stable QTNs were identified across at least two environments/methods, and their alleles showed significant TBW-DI differences. The number of superior alleles associated with TBW resistance for each accession ranged from 4 to 24; eight accessions had more than 18 superior alleles. Based on TBW-resistant alleles, the five best cross combinations were predicted, including MC133 × Ruyuan No. 1 and CO258 × ROX28. We identified 52 candidate genes around 38 QTNs related to TBW resistance based on homologous functional annotation and KEGG enrichment analysis, e.g., CYCD3;2, BSK1, Nitab4.5_0000641g0050, Nitab4.5_0000929g0030. To the best of our knowledge, this is the first comprehensive study to identify QTNs, superior alleles, and their candidate genes for breeding TBW-resistant tobacco varieties. The results provide further insight into the genetic architecture, marker-assisted selection, and functional genomics of TBW resistance, improving future breeding efforts to increase crop productivity.

Genome-wide association study and population structure analysis of seed-bound amino acids and total protein in watermelon.

BackgroundWatermelon seeds are a powerhouse of value-added traits such as proteins, free amino acids, vitamins, and essential minerals, offering a paleo-friendly dietary option. Despite the availability of substantial genetic variation, there is no sufficient information on the natural variation in seed-bound amino acids or proteins across the watermelon germplasm. This study aimed to analyze the natural variation in watermelon seed amino acids and total protein and explore underpinning genetic loci by genome-wide association study (GWAS).MethodsThe study evaluated the distribution of seed-bound free amino acids and total protein in 211 watermelon accessions of Citrullus spp, including 154 of Citrullus lanatus, 54 of Citrullus mucosospermus (egusi) and three of Citrullus amarus. We used the GWAS approach to associate seed phenotypes with 11,456 single nucleotide polymorphisms (SNPs) generated by genotyping-by-sequencing (GBS).ResultsOur results demonstrate a significant natural variation in different free amino acids and total protein content across accessions and geographic regions. The accessions with high protein content and proportion of essential amino acids warrant its use for value-added benefits in the food and feed industries via biofortification. The GWAS analysis identified 188 SNPs coinciding with 167 candidate genes associated with watermelon seed-bound amino acids and total protein. Clustering of SNPs associated with individual amino acids found by principal component analysis was independent of the speciation or cultivar groups and was not selected during the domestication of sweet watermelon. The identified candidate genes were involved in metabolic pathways associated with amino acid metabolism, such as Argininosuccinate synthase, explaining 7% of the variation in arginine content, which validate their functional relevance and potential for marker-assisted analysis selection. This study provides a platform for exploring potential gene loci involved in seed-bound amino acids metabolism, useful in genetic analysis and development of watermelon varieties with superior seed nutritional values.

Grass pea natural variation reveals oligogenic resistance to Fusarium oxysporum f. sp. pisi.

Grass pea (Lathyrus sativus L.) is an annual legume species, phylogenetically close to pea (Pisum sativum L.), that may be infected by Fusarium oxysporum f. sp. pisi (Fop), the causal agent of fusarium wilt in peas with vast worldwide yield losses. A range of responses varying from high resistance to susceptibility to this pathogen has been reported in grass pea germplasm. Nevertheless, the genetic basis of that diversity of responses is still unknown, hampering its breeding exploitation. To identify genomic regions controlling grass pea resistance to fusarium wilt, a genome-wide association study approach was applied on a grass pea worldwide collection of accessions inoculated with Fop race 2. Disease responses were scored in this collection that was also subjected to high-throughput based single nucleotide polymorphisms (SNP) screening through genotyping-by-sequencing. A total of 5,651 high-quality SNPs were considered for association mapping analysis, performed using mixed linear models accounting for population structure. Because of the absence of a fully assembled grass pea reference genome, SNP markers' genomic positions were retrieved from the pea's reference genome v1a. In total, 17 genomic regions were associated with three fusarium wilt response traits in grass pea, anticipating an oligogenic control. Seven of these regions were located on pea chromosomes 1, 6, and 7. The candidate genes underlying these regions were putatively involved in secondary and amino acid metabolism, RNA (regulation of transcription), transport, and development. This study revealed important fusarium wilt resistance favorable grass pea SNP alleles, allowing the development of molecular tools for precision disease resistance breeding.

Genome-Wide Association Study Reveals Genetic Markers for Antimicrobial Resistance in Mycoplasma bovis.

ABSTRACTMycoplasma bovis causes many health and welfare problems in cattle. Due to the absence of clear insights regarding transmission dynamics and the lack of a registered vaccine in Europe, control of an outbreak depends mainly on antimicrobial therapy. Unfortunately, antimicrobial susceptibility testing (AST) is usually not performed, because it is time-consuming and no standard protocol or clinical breakpoints are available. Fast identification of genetic markers associated with acquired resistance may at least partly resolve former issues. Therefore, the aims of this study were to implement a first genome-wide association study (GWAS) approach to identify genetic markers linked to antimicrobial resistance (AMR) in M. bovis using rapid long-read sequencing and to evaluate different epidemiological cutoff (ECOFF) thresholds. High-quality genomes of 100 M. bovis isolates were generated by Nanopore sequencing, and isolates were categorized as wild-type or non-wild-type isolates based on MIC testing results. Subsequently, a k-mer-based GWAS analysis was performed to link genotypes with phenotypes based on different ECOFF thresholds. This resulted in potential genetic markers for macrolides (gamithromycin and tylosin) (23S rRNA gene and 50S ribosomal unit) and enrofloxacin (GyrA and ParC). Also, for tilmicosin and the tetracyclines, previously described mutations in both 23S rRNA alleles and in one or both 16S rRNA alleles were observed. In addition, two new 16S rRNA mutations were possibly associated with gentamicin resistance. In conclusion, this study shows the potential of quick high-quality Nanopore sequencing and GWAS analysis in the evaluation of phenotypic ECOFF thresholds and the rapid identification of M. bovis strains with acquired resistance.IMPORTANCE Mycoplasma bovis is a leading cause of pneumonia but also causes other clinical signs in cattle. Since no effective vaccine is available, current M. bovis outbreak treatment relies primarily on the use of antimicrobials. However, M. bovis is naturally resistant to different antimicrobials, and acquired resistance against macrolides and fluoroquinolones is frequently described. Therefore, AST is important to provide appropriate and rapid antimicrobial treatment in the framework of AMR and to prevent the disease from spreading and/or becoming chronic. Unfortunately, phenotypic AST is time-consuming and, due to the lack of clinical breakpoints, the interpretation of AST in M. bovis is limited to the use of ECOFF values. Therefore, the objective of this study was to identify known and potentially new genetic markers linked to AMR phenotypes of M. bovis isolates, exploiting the power of a GWAS approach. For this, we used high-quality and complete Nanopore-sequenced M. bovis genomes of 100 isolates.

Exploration of Candidate Genes Derived from SNPs Associated with Phenotypic Root Plasticity Using Philippine Rice Germplasm for Drought Adaptation

Phenotypic root plasticity is a crucial trait for stable growth, adaptability, and productivity under abiotic-stressed growing environments. However, the genetic determinants and mechanisms controlling the trait are largely unknown, thus limiting its breeding application. We previously found 17 single nucleotide polymorphism (SNPs) significantly associated with phenotypic root plasticity traits – particularly, total root length (TRL), total nodal root length (TNRL), and total lateral root length (TLRL) – under moderate and severe drought using selected Philippine rice germplasm by employing the genome-wide association studies (GWAS) approach. Here, we present around 92 candidate genes using these SNP data. The genes were derived from various functional categories and drought intensity dependent. These were further narrowed via Gene Ontology and gene expression profile at root apical regions using databases to those whose putative functions were likely to be associated with root development in response to drought stress. Sixteen (16) more interesting known or novel genes were selected and discussed. When these genes are validated, they can help improve rice adaptation to water-limited environments.

Multi-phenotype genome-wide association studies of the Norfolk Island isolate implicate pleiotropic loci involved in chronic kidney disease

Chronic kidney disease (CKD) is a persistent impairment of kidney function. Genome-wide association studies (GWAS) have revealed multiple genetic loci associated with CKD susceptibility but the complete genetic basis is not yet clear. Since CKD shares risk factors with cardiovascular diseases and diabetes, there may be pleiotropic loci at play but may go undetected when using single phenotype GWAS. Here, we used multi-phenotype GWAS in the Norfolk Island isolate (n = 380) to identify new loci associated with CKD. We performed a principal components analysis on different combinations of 29 quantitative traits to extract principal components (PCs) representative of multiple correlated phenotypes. GWAS of a PC derived from glomerular filtration rate, serum creatinine, and serum urea identified a suggestive peak (pmin = 1.67 × 10–7) that mapped to KCNIP4. Inclusion of other secondary CKD measurements with these three kidney function traits identified the KCNIP4 locus with GWAS significance (pmin = 1.59 × 10–9). Finally, we identified a group of two SNPs with increased minor allele frequencies as potential functional variants. With the use of genetic isolate and the PCA-based multi-phenotype GWAS approach, we have revealed a potential pleotropic effect locus for CKD. Further studies are required to assess functional relevance of this locus.

A genome-wide association study reveals that the cytochrome b5 involved in seed reserve mobilization during seed germination in rice.

A candidate gene cytochrome b5 for the major QTL qSRMP9 for rice seed reserve mobilization was validated during seed germination using a genome-wide association study approach. Seed reserve mobilization plays important roles in the early seedling growth in rice. However, the genetic basis underlying this process is poorly understood. In this study, the genetic architecture of variation in seed reserve mobilization during seed germination was studied using a genome-wide association study approach in rice. Three quantitative trait loci (QTL) including qSRMP6, qSRMP9, and qSRMP12 for seed reserve mobilization percentage were identified. In which, the candidate gene cytochrome b5 (OsCyb5) for the major QTL qSRMP9 was validated. Disruption of this gene in Oscyb5 mutants reduced the seed reserve mobilization and seedling growth compared with wild-type (WT) in rice. There were no significant differences of grain size, starch, protein and total soluble sugar content in the mature grains between Oscyb5 mutants and WT. However, the α-amylase activity in the germinating seeds of Oscyb5 mutants was significantly decreased compared to that of WT, and then, the starch and sugar mobilization and the glucose accumulation during seed germination were significantly decreased in Oscyb5 mutants. Two elite haplotypes of OsCyb5 associated with the higher seed reserve mobilization percentage and its elite single nucleotide polymorphism variations were mainly existed in the INDICA and AUS accessions. The natural variation of OsCyb5 contributing to seed reserve mobilization might be useful for the future rice breeding.

Vertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology

Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we extended the Multivariate Omnibus Statistical Test (MOSTest) and applied it to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology robustly replicated in 8,060 children of mixed ethnicity from the Adolescent Brain Cognitive Development (ABCD) Study®. This reflects more than 8-fold increase in genetic discovery at no cost to generalizability compared to the commonly used univariate GWAS methods applied to region of interest (ROI) data. Functional follow up including gene-based analyses implicated 10% of all protein-coding genes and pointed towards pathways involved in neurogenesis and cell differentiation. Power analysis indicated that applying the MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. The large boost in power obtained with the vertex-wise MOSTest together with pronounced replication rates and highlighted biologically meaningful pathways underscores the advantage of multivariate approaches in the context of highly distributed polygenic architecture of the human brain.

Host genetics of pediatric SARS-CoV-2 COVID-19 and multisystem inflammatory syndrome in children.

Purpose of reviewThis review is meant to describe the genetic associations with pediatric severe COVID-19 pneumonia and the postinfectious complication of the multisystem inflammatory syndrome in children (MIS-C). Multiple genetic approaches have been carried out, primarily in adults with extrapolation to children, including genome-wide association studies (GWAS), whole exome and whole genome sequencing (WES/WGS), and target gene analyses.Recent findingsData from adults with severe COVID-19 have identified genomic regions (human leukocyte antigen locus and 3p21.31) as potential risk factors. Genes related to viral entry into cells (ABO blood group locus, ACE2, TMPRS22) have been linked to severe COVID-19 patients by GWAS and target gene approaches. Type I interferon (e.g. IFNAR2) and antiviral gene (e.g. TLR7) associations have been identified by several genetic approaches in severe COVID-19. WES has noted associations with several immune regulatory genes (e.g. SOCS1). Target gene approaches have identified mutations in perforin-mediated cytolytic pathway genes in children and adults with severe COVID-19 and children with MIS-C.SummarySeveral genetic associations have been identified in individuals with severe COVID-19 and MIS-C via various genetic approaches. Broadly speaking, COVID-19 genetic associations include genes involved with antiviral functions, viral cell entry, immune regulation, chemotaxis of white blood cells, and lymphocyte cytolytic function.

Best practices for analyzing imputed genotypes from low-pass sequencing in dogs

Although DNA array-based approaches for genome-wide association studies (GWAS) permit the collection of thousands of low-cost genotypes, it is often at the expense of resolution and completeness, as SNP chip technologies are ultimately limited by SNPs chosen during array development. An alternative low-cost approach is low-pass whole genome sequencing (WGS) followed by imputation. Rather than relying on high levels of genotype confidence at a set of select loci, low-pass WGS and imputation rely on the combined information from millions of randomly sampled low-confidence genotypes. To investigate low-pass WGS and imputation in the dog, we assessed accuracy and performance by downsampling 97 high-coverage (> 15×) WGS datasets from 51 different breeds to approximately 1× coverage, simulating low-pass WGS. Using a reference panel of 676 dogs from 91 breeds, genotypes were imputed from the downsampled data and compared to a truth set of genotypes generated from high-coverage WGS. Using our truth set, we optimized a variant quality filtering strategy that retained approximately 80% of 14 M imputed sites and lowered the imputation error rate from 3.0% to 1.5%. Seven million sites remained with a MAF > 5% and an average imputation quality score of 0.95. Finally, we simulated the impact of imputation errors on outcomes for case–control GWAS, where small effect sizes were most impacted and medium-to-large effect sizes were minorly impacted. These analyses provide best practice guidelines for study design and data post-processing of low-pass WGS-imputed genotypes in dogs.

Network mapping of root\u2013microbe interactions in Arabidopsis thaliana

Understanding how plants interact with their colonizing microbiota to determine plant phenotypes is a fundamental question in modern plant science. Existing approaches for genome-wide association studies (GWAS) are often focused on the association analysis between host genes and the abundance of individual microbes, failing to characterize the genetic bases of microbial interactions that are thought to be important for microbiota structure, organization, and function. Here, we implement a behavioral model to quantify various patterns of microbe-microbe interactions, i.e., mutualism, antagonism, aggression, and altruism, and map host genes that modulate microbial networks constituted by these interaction types. We reanalyze a root-microbiome data involving 179 accessions of Arabidopsis thaliana and find that the four networks differ structurally in the pattern of bacterial-fungal interactions and microbiome complexity. We identify several fungus and bacterial hubs that play a central role in mediating microbial community assembly surrounding A. thaliana root systems. We detect 1142 significant host genetic variants throughout the plant genome and then implement Bayesian networks (BN) to reconstruct epistatic networks involving all significant SNPs, of which 91 are identified as hub QTLs. Results from gene annotation analysis suggest that most of the hub QTLs detected are in proximity to candidate genes, executing a variety of biological functions in plant growth and development, resilience against pathogens, root development, and abiotic stress resistance. This study provides a new gateway to understand how genetic variation in host plants influences microbial communities and our results could help improve crops by harnessing soil microbes.

Mutations in the gdpP gene are a clinically relevant mechanism for β-lactam resistance in meticillin-resistant Staphylococcus aureus lacking mec determinants

In Staphylococcus aureus , resistance to β-lactamase stable β-lactam antibiotics is mediated by the penicillinbinding protein 2a, encoded by mecA or by its homologues mecB or mecC. However, a substantial number of meticillin-resistant isolates lack known mec genes and, thus, are called meticillin resistant lacking mec (MRLM). This study aims to identify the genetic mechanisms underlying the MRLM phenotype. A total of 141 MRLM isolates and 142 meticillin-susceptible controls were included in this study. Oxacillin and cefoxitin minimum inhibitory concentrations were determined by broth microdilution and the presence of mec genes was excluded by PCR. Comparative genomics and a genome-wide association study (GWAS) approach were applied to identify genetic polymorphisms associated with the MRLM phenotype. The potential impact of such mutations on the expression of PBP4, as well as on cell morphology and biofilm formation, was investigated. GWAS revealed that mutations in gdpP were significantly associated with the MRLM phenotype. GdpP is a phosphodiesterase enzyme involved in the degradation of the second messenger cyclic-di-AMP in S. aureus . A total of 131 MRLM isolates carried truncations, insertions or deletions as well as amino acid substitutions, mainly located in the functional DHH-domain of GdpP. We experimentally verified the contribution of these gdpP mutations to the MRLM phenotype by heterologous complementation experiments. The mutations in gdpP had no effect on transcription levels of pbp4; however, cell sizes of MRLM strains were reduced. The impact on biofilm formation was highly strain dependent. We report mutations in gdpP as a clinically relevant mechanism for β-lactam resistance in MRLM isolates. This observation is of particular clinical relevance, since MRLM are easily misclassified as MSSA (meticillin-susceptible S. aureus ), which may lead to unnoticed spread of β-lactam-resistant isolates and subsequent treatment failure.