Genome-wide Association Study Approach Research Articles

Conditional GWAS of non-CG transposon methylation in Arabidopsis thaliana reveals major polymorphisms in five genes.

Genome-wide association studies (GWAS) have revealed that the striking natural variation for DNA CHH-methylation (mCHH; H is A, T, or C) of transposons has oligogenic architecture involving major alleles at a handful of known methylation regulators. Here we use a conditional GWAS approach to show that CHG-methylation (mCHG) has a similar genetic architecture-once mCHH is statistically controlled for. We identify five key trans-regulators that appear to modulate mCHG levels, and show that they interact with a previously identified modifier of mCHH in regulating natural transposon mobilization.

Leveraging Large-Scale Genetics of PTSD and Cardiovascular Disease to Demonstrate Robust Shared Risk and Improve Risk Prediction Accuracy.

Individuals with posttraumatic stress disorder (PTSD) are significantly more likely to be diagnosed with cardiovascular disease (CVD) (e.g., myocardial infarction, stroke). The evidence for this link is so compelling that the National Institutes of Health convened a working group to determine gaps in the literature, including the need for large-scale genomic studies to identify shared genetic risk. The aim of the present study was to address some of these gaps by utilizing PTSD and CVD genome-wide association study (GWAS) summary statistics in a large biobank sample to determine the shared genetic risk of PTSD and CVD. A large health care biobank data set was used (N=36,412), combined with GWAS summary statistics from publicly available large-scale PTSD and CVD studies. Disease phenotypes (e.g., PTSD) were collected from electronic health records. De-identified genetic data from the biobank were genotyped using Illumina SNP array. Summary statistics data sets were processed with the following quality-control criteria: 1) SNP heritability h2 >0.05, 2) compute z-statistics (z=beta/SE or z=log(OR)/SE), 3) filter nonvariable SNPs (0<freq<1), and 4) filter SNPs with low number of samples. The multitrait analysis of GWAS (MTAG) approach was used to combine GWAS summary statistics. Significant genetic correlations were found between PTSD and CVD (rG=0.24, SE=0.06), and Mendelian randomization analyses indicated a potential causal link from PTSD to hypertension (β=0.20, SE=0.04), but not the reverse. PTSD summary statistics significantly predicted PTSD diagnostic status (R2=0.27), and this was significantly improved by incorporating summary statistics from CVD and major depressive disorder (R2=1.30). Further, pathway enrichment analyses indicated that genetic variants involved in shared PTSD-CVD risk included those involved in postsynaptic structure, synapse organization, and interleukin-7-mediated signaling pathways. The results from this study suggest that PTSD and CVD may share genetic risk. Further, these results implicate PTSD as a risk factor leading to the development of hypertension and coronary artery disease. Additional research is needed to determine the clinical utility of these findings.

New Distance-Based approach for Genome-Wide Association Studies.

With the rise of genome-wide association studies (GWAS), the analysis of typical GWAS data sets with thousands of single-nucleotide polymorphisms (SNPs) has become crucial in biomedicine research. Here, we propose a new method to identify SNPs related to disease in case-control studies. The method, based on genetic distances between individuals, takes into account the possible population substructure, and avoids the issues of multiple testing. The method provides two ordered lists of SNPs; one with SNPs which minor alleles can be considered risk alleles for the disease, and another one with SNPs which minor alleles can be considered as protective. These two lists provide a useful tool to help the researcher to decide where to focus attention in a first stage.

Using the Collaborative Cross and Diversity Outbred Mice in Immunology.

The Collaborative Cross (CC) and the Diversity Outbred (DO) stock mouse panels are the most powerful murine genetics tools available to the genetics community. Together, they combine the strength of inbred animal models with the diversity of outbred populations. Using the 63 CC strains or a panel of DO mice, each derived from the same 8 parental mouse strains, researchers can map genetic contributions to exceptionally complex immunological and infectious disease traits that would require far greater powering if performed by genome-wide association studies (GWAS) in human populations. These tools allow genes to be studied in heterozygous and homozygous states and provide a platform to study epistasis between interacting loci. Most importantly, once a quantitative phenotype is investigated and quantitative trait loci are identified, confirmatory genetic studies can be performed, which is often problematic using the GWAS approach. In addition, novel stable mouse models for immune phenotypes are often derived from studies utilizing the DO and CC mice that can serve as stronger model systems than existing ones in the field. The CC/DO systems have contributed to the fields of cancer immunology, autoimmunity, vaccinology, infectious disease, allergy, tissue rejection, and tolerance but have thus far been greatly underutilized. In this article, we present a recent review of the field and point out key areas of immunology that are ripe for further investigation and awaiting new CC/DO research projects. We also highlight some of the strong computational tools that have been developed for analyzing CC/DO genetic and phenotypic data. Additionally, we have formed a centralized community on the CyVerse infrastructure where immunogeneticists can utilize those software tools, collaborate with groups across the world, and expand the use of the CC and DO systems for investigating immunogenetic phenomena. © 2022 Wiley Periodicals LLC.

Potential regulation of linoleic acid and volatile organic compound contents in meat of chickens by PLCD1

Omega-3 (linolenic acid (ALA), docosapentaenoic acid, eicosapentaenoic acid) and omega-6 (linoleic acid (LA), arachidonic acid) polyunsaturated fatty acids are essential for health and normal physiological functioning in humans. Here we report a genome-wide association study (GWAS) on LA content in chicken meat. The 19 significant single nucleotide polymorphisms (SNPs) identified by the GWAS approach were annotated in VILL, PLCD1 and OXSR1 genes with highly polymorphic linkage blocks, and explained 4.5% of the phenotypic variation in the LA content. Specifically, the PLCD1 mRNA expression level was negatively correlated with the LA content, and significantly higher in chickens with low LA content than in those with high LA content. In addition, PLCD1 was found to be involved in metabolic pathways, etc. Furthermore, the LA content was correlated with volatile organic compounds (e.g., octanal, etc.), but no relationship was found with intramuscular fat and triglycerides in chicken meat. The results indicated that there are key SNPs in PLCD1 that regulate the content of LA, and it has no significant effect on fat deposition, but may affect the content of volatile organic compounds (VOCs).

ImputAccur: fast and user-friendly calculation of genotype-imputation accuracy-measures

BackgroundImputAccur is a software tool to measure genotype-imputation accuracy. Imputation of untyped markers is a standard approach in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy for imputed genotypes is fundamental. Several accuracy measures have been proposed, but unfortunately, they are implemented on different platforms, which is impractical.ResultsWith ImputAccur, the accuracy measures info, Iam-hiQ and r2-based indices can be derived from standard output files of imputation software. Sample/probe and marker filtering is possible. This allows e.g. accurate marker filtering ahead of data analysis.ConclusionsThe source code (Python version 3.9.4), a standalone executive file, and example data for ImputAccur are freely available at https://gitlab.gwdg.de/kolja.thormann1/imputationquality.git.

A Multitrait Locus Regulates Sarbecovirus Pathogenesis.

ABSTRACTInfectious diseases have shaped the human population genetic structure, and genetic variation influences the susceptibility to many viral diseases. However, a variety of challenges have made the implementation of traditional human Genome-wide Association Studies (GWAS) approaches to study these infectious outcomes challenging. In contrast, mouse models of infectious diseases provide an experimental control and precision, which facilitates analyses and mechanistic studies of the role of genetic variation on infection. Here we use a genetic mapping cross between two distinct Collaborative Cross mouse strains with respect to severe acute respiratory syndrome coronavirus (SARS-CoV) disease outcomes. We find several loci control differential disease outcome for a variety of traits in the context of SARS-CoV infection. Importantly, we identify a locus on mouse chromosome 9 that shows conserved synteny with a human GWAS locus for SARS-CoV-2 severe disease. We follow-up and confirm a role for this locus, and identify two candidate genes, CCR9 and CXCR6, that both play a key role in regulating the severity of SARS-CoV, SARS-CoV-2, and a distantly related bat sarbecovirus disease outcomes. As such we provide a template for using experimental mouse crosses to identify and characterize multitrait loci that regulate pathogenic infectious outcomes across species.

Genome-Wide Association Study of Nucleotide Variants Associated with Resistance to Nine Antimicrobials in Mycoplasma bovis.

Antimicrobial resistance (AMR) studies of Mycoplasma bovis have generally focused on specific loci versus using a genome-wide association study (GWAS) approach. A GWAS approach, using two different models, was applied to 194 Mycoplasma bovis genomes. Both a fixed effects linear model (FEM) and a linear mixed model (LMM) identified associations between nucleotide variants (NVs) and antimicrobial susceptibility testing (AST) phenotypes. The AMR phenotypes represented fluoroquinolones, tetracyclines, phenicols, and macrolides. Both models identified known and novel NVs associated (Bonferroni adjusted p < 0.05) with AMR. Fluoroquinolone resistance was associated with multiple NVs, including previously identified mutations in gyrA and parC. NVs in the 30S ribosomal protein 16S were associated with tetracycline resistance, whereas NVs in 5S rRNA, 23S rRNA, and 50S ribosomal proteins were associated with phenicol and macrolide resistance. For all antimicrobial classes, resistance was associated with NVs in genes coding for ABC transporters and other membrane proteins, tRNA-ligases, peptidases, and transposases, suggesting a NV-based multifactorial model of AMR in M. bovis. This study was the largest collection of North American M. bovis isolates used with a GWAS for the sole purpose of identifying novel and non-antimicrobial-target NVs associated with AMR.

Omics approaches to discover pathophysiological pathways contributing to human pain.

Omics approaches to discover pathophysiological pathways contributing to human pain.

Genome-wide association studies on Northern Italy isolated populations provide further support concerning genetic susceptibility for major depressive disorder

Objectives Major depressive disorder (MDD) is a psychiatric disorder with pathogenesis influenced by both genetic and environmental factors. To date, the molecular-level understanding of its aetiology remains unclear. Thus, we aimed to identify genetic variants and susceptibility genes for MDD with a genome-wide association study (GWAS) approach. Methods We performed a meta-analysis of GWASs and a gene-based analysis on two Northern Italy isolated populations (cases/controls n = 166/472 and 33/320), followed by replication and polygenic risk score (PRS) analyses in Italian independent samples (cases n = 464, controls n = 339). Results We identified two novel MDD-associated genes, KCNQ5 (lead SNP rs867262, p = 3.82 × 10−9) and CTNNA2 (rs6729523, p = 1.25 × 10−8). The gene-based analysis revealed another six genes (p < 2.703 × 10−6): GRM7, CTNT4, SNRK, SRGAP3, TRAPPC9, and FHIT. No replication of the genome-wide significant SNPs was found in the independent cohort, even if 14 SNPs around CTNNA2 showed association with MDD and related phenotypes at the nominal level of p (<0.05). Furthermore, the PRS model developed in the discovery cohort discriminated cases and controls in the replication cohort. Conclusions Our work suggests new possible genes associated with MDD, and the PRS analysis confirms the polygenic nature of this disorder. Future studies are required to better understand the role of these findings in MDD.

Genome-wide association study identified candidate SNPs and genes associated with hypoxia tolerance in large yellow croaker (Larimichthys crocea)

The large yellow croaker (Larimichthys crocea) is an economically important fish farmed along the southeast coasts of China. In recent years, however, hypoxia has caused substantial economic losses in the L. crocea aquaculture industry. At present, the numbers of genes and molecular markers available for the selection and breeding of hypoxia tolerance traits in L. crocea remain very limited, and thus there is an urgent need to conduct breeding studies on the tolerance of this fish to hypoxia. Genome-wide association studies (GWAS) have been widely used to study the genetic basis of economically important traits in aquatic animals, and in this study, we adopted a GWAS approach to genetically characterize hypoxia tolerance in the L. crocea. A total of 1982 fish were subjected to hypoxia experiments, among which 398 individuals characterized by the most sensitive and tolerant phenotypes were genotyped. Following filtering, we obtained a total of 54,224 high-quality single-nucleotide polymorphisms (SNPs), of which four were identified as significant based on mixed linear (MLM) and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (Blink) model analyses. Using these four SNPs, we identified ten candidate genes, including one gene, egln2, directly associated with hypoxia and other involved in important regulatory pathways, such as oxidative stress, ion regulation, and energy metabolism. These findings provide new insights into the genetic basis of hypoxia tolerance in L. crocea and will facilitate future breeding for marker-assisted selection and the breeding of hypoxia-tolerant L. crocea for commercial production.

Phosphate transporter PHT1;1 is a key determinant of phosphorus acquisition in Arabidopsis natural accessions.

Phosphorus (P) is a mineral nutrient essential for plant growth and development, but most P in the soil is unavailable for plants. To understand the genetic basis of P acquisition regulation, we performed genome-wide association studies (GWASs) on a diversity panel of Arabidopsis (Arabidopsis thaliana). Two primary determinants of P acquisition were considered, namely, phosphate (Pi)-uptake activity and PHOSPHATE TRANSPORTER 1 (PHT1) protein abundance. Association mapping revealed a shared significant peak on chromosome 5 (Chr5) where the PHT1;1/2/3 genes reside, suggesting a connection between the regulation of Pi-uptake activity and PHT1 protein abundance. Genes encoding transcription factors, kinases, and a metalloprotease associated with both traits were also identified. Conditional GWAS followed by statistical analysis of genotype-dependent PHT1;1 expression and transcriptional activity assays revealed an epistatic interaction between PHT1;1 and MYB DOMAIN PROTEIN 52 (MYB52) on Chr1. Further, analyses of F1 hybrids generated by crossing two subgroups of natural accessions carrying specific PHT1;1- and MYB52-associated single nucleotide polymorphisms (SNPs) revealed strong effects of these variants on PHT1;1 expression and Pi uptake activity. Notably, the soil P contents in Arabidopsis habitats coincided with PHT1;1 haplotype, emphasizing how fine-tuned P acquisition activity through natural variants allows environmental adaptation. This study sheds light on the complex regulation of P acquisition and offers a framework to systematically assess the effectiveness of GWAS approaches in the study of quantitative traits.

Large scale across-breed genome-wide association study reveals a variant in HMGA2 associated with inguinal cryptorchidism risk in dogs.

Cryptorchidism is the most common congenital sex development disorder in dogs. Despite this, little progress has been made in understanding its genetic background. Extensive genetic testing of dogs through consumer and veterinary channels using a high-density SNP genotyping microarray coupled with links to clinical records presents the opportunity for a large-scale genome-wide association study to elucidate the molecular risk factors associated with cryptorchidism in dogs. Using an inter-breed genome-wide association study approach, a significant statistical association on canine chromosome 10 was identified, with the top SNP pinpointing a variant of HMGA2 previously associated with adult weight variance. In further analysis we show that incidence of cryptorchidism is skewed towards smaller dogs in concordance with the identified variant’s previous association with adult weight. This study represents the first putative variant to be associated with cryptorchidism in dogs.

Genome-wide association study of platelet factor 4/heparin antibodies in heparin-induced thrombocytopenia

AbstractHeparin, a widely used anticoagulant, carries the risk of an antibody-mediated adverse drug reaction, heparin-induced thrombocytopenia (HIT). A subset of heparin-treated patients produces detectable levels of antibodies against complexes of heparin bound to circulating platelet factor 4 (PF4). Using a genome-wide association study (GWAS) approach, we aimed to identify genetic variants associated with anti-PF4/heparin antibodies that account for the variable antibody response seen in HIT. We performed a GWAS on anti-PF4/heparin antibody levels determined via polyclonal enzyme-linked immunosorbent assays. Our discovery cohort (n = 4237) and replication cohort (n = 807) constituted patients with European ancestry and clinical suspicion of HIT, with cases confirmed via functional assay. Genome-wide significance was considered at α = 5 × 10−8. No variants were significantly associated with anti-PF4/heparin antibody levels in the discovery cohort at a genome-wide significant level. Secondary GWAS analyses included the identification of variants with suggestive associations in the discovery cohort (α = 1 × 10−4). The top variant in both cohorts was rs1555175145 (discovery β = −0.112 [0.018], P = 2.50 × 10−5; replication β = −0.104 [0.051], P = .041). In gene set enrichment analysis, 3 gene sets reached false discovery rate-adjusted significance (q < 0.05) in both discovery and replication cohorts: “Leukocyte Transendothelial Migration,” “Innate Immune Response,” and “Lyase Activity.” Our results indicate that genomic variation is not significantly associated with anti-PF4/heparin antibody levels. Given our power to identify variants with moderate frequencies and effect sizes, this evidence suggests genetic variation is not a primary driver of variable antibody response in heparin-treated patients with European ancestry.

Assessment of two statistical approaches for variance genome-wide association studies in plants.

Genomic loci that control the variance of agronomically important traits are increasingly important due to the profusion of unpredictable environments arising from climate change. The ability to identify such variance-controlling loci in association studies will be critical for future breeding efforts. Two statistical approaches that have already been used in the variance genome-wide association study (vGWAS) paradigm are the Brown-Forsythe test (BFT) and the double generalized linear model (DGLM). To ensure that these approaches are deployed as effectively as possible, it is critical to study the factors that influence their ability to identify variance-controlling loci. We used genome-wide marker data in maize (Zea mays L.) and Arabidopsis thaliana to simulate traits controlled by epistasis, genotype by environment (GxE) interactions, and variance quantitative trait nucleotides (vQTNs). We then quantified true and false positive detection rates of the BFT and DGLM across all simulated traits. We also conducted a vGWAS using both the BFT and DGLM on plant height in a maize diversity panel. The observed true positive detection rates at the maximum sample size considered (N = 2815) suggest that both of these vGWAS approaches are capable of identifying epistasis and GxE for sufficiently large sample sizes. We also noted that the DGLM decisively outperformed the BFT for simulated traits controlled by vQTNs at sample sizes of N = 500. Although we conclude that there are still certain aspects of vGWAS approaches that need further refinement, this study suggests that the BFT and DGLM are capable of identifying variance-controlling loci in current state-of-the-art plant or agronomic data sets.

Strain Variation in Clostridioides difficile Cytotoxicity Associated with Genomic Variation at Both Pathogenic and Nonpathogenic Loci.

ABSTRACTClinical disease from Clostridioides difficile infection can be mediated by two toxins and their neighboring regulatory genes located within the five-gene pathogenicity locus (PaLoc). We provide several lines of evidence that the cytotoxicity of C. difficile may be modulated by genomic variants outside the PaLoc. We used a phylogenetic tree-based approach to demonstrate discordance between cytotoxicity and PaLoc evolutionary history, an elastic net method to show the insufficiency of PaLoc variants alone to model cytotoxicity, and a convergence-based bacterial genome-wide association study (GWAS) to identify correlations between non-PaLoc loci and changes in cytotoxicity. Combined, these data support a model of C. difficile disease wherein cytotoxicity may be strongly affected by many non-PaLoc loci. Additionally, we characterize multiple other in vitro phenotypes relevant to human infections, including germination and sporulation. These phenotypes vary greatly in their clonality, variability, convergence, and concordance with genomic variation. Finally, we highlight the intersection of loci identified by the GWAS for different phenotypes and clinical severity. This strategy to identify overlapping loci can facilitate the identification of genetic variation linking phenotypic variation to clinical outcomes.IMPORTANCE Clostridioides difficile has two major disease-mediating toxins, A and B, encoded within the pathogenicity locus (PaLoc). In this study, we demonstrate via multiple approaches that genomic variants outside the PaLoc are associated with changes in cytotoxicity. These genomic variants may provide new avenues of exploration in the hunt for novel disease-modifying interventions. Additionally, we provide insight into the evolution of several additional phenotypes also critical for clinical infection, such as sporulation, germination, and growth rate. These in vitro phenotypes display a range of responses to evolutionary pressures and, as such, vary in their appropriateness for certain bacterial genome-wide association study approaches. We used a convergence-based association method to identify the genomic variants most correlated with both changes in these phenotypes and disease severity. These overlapping loci may be important for both bacterial function and human clinical disease.

Genetic Susceptibility in Understanding of Pancreatic Ductal Adenocarcinoma Risk: A Decade-Long Effort of the PANDORA Consortium.

Pancreatic cancer, a complex disease, emerges as a severe health problem worldwide and it exhibits a poor prognosis and high mortality. Risk factors associated with sporadic pancreatic cancer remain poorly understood, even less is known about disease prognosis due to its rapid progression. The PANcreatic Disease ReseArch (PANDoRA) consortium, of which the authors are members, was established to coordinate the efforts of different research groups to uncover new genetic factors for pancreatic cancer risk, response to treatment, and patient survival. PANDoRA consortium has contributed to the identification of several low-penetrance risk loci for the disease both by candidate variants approach and genome-wide association studies, including those in cell-cycle and DNA damage response, telomere homeostasis, SCL and ABC transporters, ABO locus variability, mitochondrial metabolism and it participated on collaborative genome-wide association study approach and implementation of a search for functional-based pancreatic cancer risk loci and long noncoding RNAs. Complex studies covering genetic, environmental and microenvironmental factors in the pancreatic cancer onset, progression and its prognosis are warranted.

Validation of Candidate Sleep Disorder Risk Genes Using Zebrafish.

Sleep disorders and chronic sleep disturbances are common and are associated with cardio-metabolic diseases and neuropsychiatric disorders. Several genetic pathways and neuronal mechanisms that regulate sleep have been described in animal models, but the genes underlying human sleep variation and sleep disorders are largely unknown. Identifying these genes is essential in order to develop effective therapies for sleep disorders and their associated comorbidities. To address this unmet health problem, genome-wide association studies (GWAS) have identified numerous genetic variants associated with human sleep traits and sleep disorders. However, in most cases, it is unclear which gene is responsible for a sleep phenotype that is associated with a genetic variant. As a result, it is necessary to experimentally validate candidate genes identified by GWAS using an animal model. Rodents are ill-suited for this endeavor due to their poor amenability to high-throughput sleep assays and the high costs associated with generating, maintaining, and testing large numbers of mutant lines. Zebrafish (Danio rerio), an alternative vertebrate model for studying sleep, allows for the rapid and cost-effective generation of mutant lines using the CRISPR/Cas9 system. Numerous zebrafish mutant lines can then be tested in parallel using high-throughput behavioral assays to identify genes whose loss affects sleep. This process identifies a gene associated with each GWAS hit that is likely responsible for the human sleep phenotype. This strategy is a powerful complement to GWAS approaches and holds great promise to identify the genetic basis for common human sleep disorders.

MPI-GWAS: a supercomputing-aided permutation approach for genomewide association studies.

Permutation testing is a robust and popular approach for significance testing in genomic research that has the advantage of reducing inflated type 1 error rates; however, its computational cost is notorious in genome-wide association studies (GWAS). Here, we developed a supercomputing-aided approach to accelerate the permutation testing for GWAS, based on the message-passing interface (MPI) on parallel computing architecture. Our application, called MPI-GWAS, conducts MPI-based permutation testing using a parallel computing approach with our supercomputing system, Nurion (8,305 compute nodes, and 563,740 central processing units [CPUs]). For 107 permutations of one locus in MPI-GWAS, it was calculated in 600 s using 2,720 CPU cores. For 107 permutations of ~30,000–50,000 loci in over 7,000 subjects, the total elapsed time was ~4 days in the Nurion supercomputer. Thus, MPI-GWAS enables us to feasibly compute the permutation-based GWAS within a reason-able time by harnessing the power of parallel computing resources.

Identification of Genomic Regions and Sources for Wheat Blast Resistance through GWAS in Indian Wheat Genotypes.

Wheat blast (WB) is a devastating fungal disease that has recently spread to Bangladesh and poses a threat to the wheat production in India, which is the second-largest wheat producing country in the world. In this study, 350 Indian wheat genotypes were evaluated for WB resistance in 12 field experiments in three different locations, namely Jashore in Bangladesh and Quirusillas and Okinawa in Bolivia. Single nucleotide polymorphisms (SNPs) across the genome were obtained using DArTseq® technology, and 7554 filtered SNP markers were selected for a genome-wide association study (GWAS). All the three GWAS approaches used identified the 2NS translocation as the only major source of resistance, explaining up to 32% of the phenotypic variation. Additional marker-trait associations were located on chromosomes 2B, 3B, 4D, 5A and 7A, and the combined effect of three SNPs (2B_180938790, 7A_752501634 and 5A_618682953) showed better resistance, indicating their additive effects on WB resistance. Among the 298 bread wheat genotypes, 89 (29.9%) carried the 2NS translocation, the majority of which (60 genotypes) were CIMMYT introductions, and 29 were from India. The 2NS carriers with a grand mean WB index of 6.6 showed higher blast resistance compared to the non-2NS genotypes with a mean index of 46.5. Of the 52 durum wheats, only one genotype, HI 8819, had the 2NS translocation and was the most resistant, with a grand mean WB index of 0.93. Our study suggests that the 2NS translocation is the only major resistance source in the Indian wheat panel analysed and emphasizes the urgent need to identify novel non-2NS resistance sources and genomic regions.