Genome-wide Association Approach Research Articles

Milletomics: a metabolomics centered integrated omics approach toward genetic progression.

Producing alternative staple foods like millet will be essential to feeding ten billion people by 2050. The increased demand for millet is driving researchers to improve its genetic variation. Millets include protein, dietary fiber, phenolic substances, and flavonoid components. Its climate resilience makes millet an appealing crop for agronomic sustainability. Integrative omics technologies could potentially identify and develop millets with desirable phenotypes that may have high agronomic value. Millets' salinity and drought tolerance have been enhanced using transcriptomics. In foxtail, finger, and pearl millet, proteomics has discovered salt-tolerant protein, phytohormone-focused protein, and drought tolerance. Metabolomics studies have revealed that certain metabolic pathways including those involving lignin, flavonoids, phenylpropanoid, and lysophospholipids are critical for many processes, including seed germination, photosynthesis, energy metabolism, and the synthesis of bioactive chemicals necessary for drought tolerance. Metabolomics integration with other omics revealed metabolome engineering and trait-specific metabolite creation. Integrated metabolomics and ionomics are still in the development stage, but they could potentially assist in comprehending the pathway of ionomers to control nutrient levels and biofortify millet. Epigenomic analysis has shown alterations in DNA methylation patterns and chromatin structure in foxtail and pearl millets in response to abiotic stress. Whole-genome sequencing utilizing next-generation sequencing is the most proficient method for finding stress-induced phytoconstituent genes. New genome sequencing enables novel biotechnological interventions including genome-wide association, mutation-based research, and other omics approaches. Millets can breed more effectively by employing next-generation sequencing and genotyping by sequencing, which may mitigate climate change. Millet marker-assisted breeding has advanced with high-throughput markers and combined genotyping technologies.

Refining the scope of genetic influences on alcohol misuse through environmental stratification and gene-environment interaction.

Gene-environment interaction (G × E) is likely an important influence shaping individual differences in alcohol misuse (AM), yet it has not been extensively studied in molecular genetic research. In this study, we use a series of genome-wide gene-environment interaction (GWEIS) and in silico annotation methods with the aim of improving gene identification and biological understanding of AM. We carried out GWEIS for four AM phenotypes in the large UK Biobank sample (N = 360,314), with trauma exposure and socioeconomic status (SES) as moderators of the genetic effects. Exploratory analyses compared stratified genome-wide association (GWAS) and GWEIS modeling approaches. We applied functional annotation, gene- and gene-set enrichment, and polygenic score analyses to interpret the GWEIS results. GWEIS models showed few genetic variants with significant interaction effects across gene-environment pairs. Enrichment analyses identified moderation by SES of the genes NOXA1, DLGAP1, and UBE2L3 on drinking quantity and the gene IFIT1B on drinking frequency. Except for DLGAP1, these genes have not previously been linked to AM. The most robust results (GWEIS interaction p = 4.59e-09) were seen for SES moderating the effects of variants linked to immune-related genes on a pattern of drinking with versus without meals. Our results highlight several genes and a potential mechanism of immune system functioning behind the moderating effect of SES on the genetic influences on AM. Although GWEIS seems to be a preferred approach over stratified GWAS, modeling G × E effects at the molecular level remains a challenge even in large samples. Understanding these effects will require substantial effort and more in-depth phenotypic measurement.

Genetic Foundation of Male Spur Length and Its Correlation with Female Egg Production in Chickens.

Spurs, which mainly appear in roosters, are protrusions near the tarsometatarsus on both sides of the calves of chickens, and are connected to the tarsometatarsus by a bony core. As a male-biased morphological characteristic, the diameter and length of spurs vary significantly between different individuals, mainly related to genetics and age. As a specific behavior of hens, egg-laying also varies greatly between individuals in terms of traits such as age at first egg (AFE), egg weight (EW), and so on. At present, there are few studies on chicken spurs. In this study, we investigated the inheritance pattern of the spur trait in roosters with different phenotypes and the correlations between spur length, body weight at 18 weeks of age (BW18), shank length at 18 weeks of age (SL18), and the egg-laying trait in hens (both hens and roosters were from the same population and were grouped according to their family). These traits related to egg production included AFE, body weight at first egg (BWA), and first egg weight (FEW). We estimated genetic parameters based on pedigree and phenotype data, and used variance analysis to calculate broad-sense heritability for correcting the parameter estimation results. The results showed that the heritability of male left and right spurs ranged from 0.6 to 0.7. There were significant positive correlations between left and right spur length, BW18, SL18, and BWA, as well as between left and right spur length and AFE. We selected 35 males with the longest spurs and 35 males with the shortest spurs in the population, and pooled them into two sets to obtain the pooled genome sequencing data. After genome-wide association and genome divergency analysis by FST, allele frequency differences (AFDs), and XPEHH methods, we identified 7 overlapping genes (CENPE, FAT1, FAM149A, MANBA, NFKB1, SORBS2, UBE2D3) and 14 peak genes (SAMD12, TSPAN5, ENSGALG00000050071, ENSGALG00000053133, ENSGALG00000050348, CNTN5, TRPC6, ENSGALG00000047655,TMSB4X, LIX1, CKB, NEBL, PRTFDC1, MLLT10) related to left and right spur length through genome-wide selection signature analysis and a genome-wide association approach. Our results identified candidate genes associated with chicken spurs, which helps to understand the genetic mechanism of this trait and carry out subsequent research around it.

Unveiling genetic signatures associated with resilience to neonatal diarrhea in lambs through two GWAS approaches

Neonatal diarrhea presents a significant global challenge due to its multifactorial etiology, resulting in high morbidity and mortality rates, and substantial economic losses. While molecular-level studies on genetic resilience/susceptibility to neonatal diarrhea in farm animals are scarce, prior observations indicate promising research directions. Thus, the present study utilizes two genome-wide association approaches, pKWmEB and MLM, to explore potential links between genetic variations in innate immunity and neonatal diarrhea in Karacabey Merino lambs. Analyzing 707 lambs, including 180 cases and 527 controls, revealed an overall prevalence rate of 25.5%. The pKWmEB analysis identified 13 significant SNPs exceeding the threshold of ≥ LOD 3. Moreover, MLM detected one SNP (s61781.1) in the SLC22A8 gene (p-value, 1.85eE-7), which was co-detected by both methods. A McNemar’s test was conducted as the final assessment to identify whether there are any major effective markers among the detected SNPs. Results indicate that four markers—oar3_OAR1_122352257, OAR17_77709936.1, oar3_OAR18_17278638, and s61781.1—have a substantial impact on neonatal diarrhea prevalence (odds ratio: 2.03 to 3.10; statistical power: 0.88 to 0.99). Therefore, we propose the annotated genes harboring three of the associated markers, TIAM1, YDJC, and SLC22A8, as candidate major genes for selective breeding against neonatal diarrhea.

RadioGWAS links radiome to genome to discover driver genes with somatic mutations for heterogeneous tumor image phenotype in pancreatic cancer

Addressing the significant level of variability exhibited by pancreatic cancer necessitates the adoption of a systems biology approach that integrates molecular data, biological properties of the tumors, medical images, and clinical features of the patients. In this study, a comprehensive multi-omics methodology was employed to examine a distinctive collection of patient dataset containing rapid autopsy tumor and normal tissue samples as well as longitudinal imaging with a focus on pancreatic cancer. By performing a whole exome sequencing analysis on tumor and normal tissues to identify somatic gene variants and a radiomic feature analysis to tumor CT images, the genome-wide association approach established a connection between pancreatic cancer driver genes and relevant radiomic features, enabling a thorough and quantitative assessment of the heterogeneity of pancreatic tumors. The significant association between sets of genes and radiomic features revealed the involvement of genes in shaping tumor morphological heterogeneity. Some results of the association established a connection between the molecular level mechanism and their outcomes at the level of tumor structural heterogeneity. Because tumor structure and tumor structural heterogeneity are related to the patients’ overall survival, patients who had pancreatic cancer driver gene mutations with an association to a certain radiomic feature have been observed to experience worse survival rates than cases without these somatic mutations. Furthermore, the association analysis has revealed potential gene mutations and radiomic feature candidates that warrant further investigation in future research endeavors.

#795 Genetics of serum electrolytes: a genome-wide association approach in two European cohorts

Abstract Background and Aims Chloride, potassium and sodium are electrolytes that play a key role in several physiological processes. To date, the genetic factors underlying their differences in the general population are not fully understood and need to be further investigated. In this study, we aimed at dissecting the genetics of the levels of these serum electrolytes in the European population by genomic approaches. Method We genotyped and analysed data from 3057 North-Eastern Italian individuals participating in the INCIPE (Initiative on Nephropathy, of relevance to public health, which is Chronic, possibly in its Initial stages, and carries a Potential risk of major clinical End-points) cohort. Genomic data were processed for quality controls (using plink and bcftools), following these exclusion criteria: sample missingness >0.15, genotype missingness >0.02, relatedness up to 2nd degree, non-European ethnicity. Next, the dataset underwent genotype imputation on the Michigan Imputation Server, using the Human Reference Consortium panel and filtering for imputation confidence (R2 >0.3). Typed and imputed data were then analysed on genome-wide association studies (GWAS, using rvtest) for each of the three serum electrolytes. The same analytical procedure was applied to 14926 individuals from the Rotterdam Study (RS) cohort (a prospective cohort study ongoing since 1990 in Rotterdam). Thus, summary statistics from all the phenotypes and cohorts were jointly analysed in a genome-wide meta-analysis setting (using METAL). Meta-analyses results underwent functional annotation on the FUMAGWAS platform, to obtain biological and functional insights and to allow variants and genes prioritisation. Results Quality controls and genotype imputation resulted in a total of 857 (INCIPE1) and 1343 (INCIPE2) samples and 8 million variants for the INCIPE cohort; 2056 (RS1), 2042 (RS2) and 2958 (RS3) samples and 7.7 million variants for the Rotterdam Study cohort. GWAS showed genome-wide signals (p < 5e-8) for chloride and sodium and suggestive signals (p < 5e-5) for potassium. Meta-analyses partially replicated results obtained on the INCIPE cohort, showing signals for all the three electrolytes over the suggestive threshold only. Finally, functional annotation gave insights on associated genes and markers. Chloride showed association with genes reported in nephrotic syndrome (NUP205, p = 9e-7), voltage-gated channels (CACNA1E, p = 1e-6) and chloride channels (CLDN4, p = 4e-6; GABRA2, p = 1e-5), comprising a total of 47 candidate risk loci. Potassium showed mostly association with a gene involved in ion transport and polycystic kidney disease (PKD2L2, p = 1e-7), and a total of 28 candidate risk loci. Sodium showed association with genes implicated in several diseases with kidney involvement such as nephropathy (IMMP2L, P = 1e-7), Bardet-Biedl syndrome (BBSP, p = 1-e6) and ARCS1 (SH3BP2, p = 2e-6), and acting in cell polarity (PARD6G, p = 1e-6) and ion transport (ANO3, p = 3e-6), for a total of 76 candidate risk loci. In addition to these genes, other genes were already reported to be associated with cardiomyopathies, such as ABTB2 in chloride and sodium and MYOT and PRKAG2 in potassium. Conclusion This study showed novel candidate genes that may explain interindividual differences in serum electrolytes. Genes already reported to be associated with kidney abnormalities offer hints of their actual involvement in electrolyte imbalances and related disease. Moreover, associations pointing at cardiac diseases strengthen the involvement of these genes in renal electrolyte abnormalities, being one of the secondary causes of cardiomyopathies. Finally, the identification of risk loci across the three phenotypes opens the opportunity for the development of polygenic risk scores, which may benefit of an increasing number of tested samples to reach genome-wide significant signals and additional cohorts to validate the computed risk model.

Systematic Review of Genetic Modifiers Associated with the Development and/or Progression of Nephropathy in Patients with Sickle Cell Disease.

Sickle cell nephropathy (SCN) is a common complication of sickle cell disease (SCD) that significantly contributes to morbidity and mortality. In addition to clinical and life-style factors, genetic variants influence this risk. We performed a systematic review, searching five databases. Studies evaluating the effect of genetic modifiers on SCN were eligible. Twenty-eight studies (fair-to-good quality) were included: one genome-wide association study, twenty-six case-control studies, and one article combining both approaches. APOL1 was significantly associated with albuminuria and hyperfiltration in children and with worse glomerular filtration in adults. On the other hand, alpha-thalassemia protected patients against albuminuria and hyperfiltration, while BCL11A variants were protective against albuminuria alone. The HMOX1 long GT-tandem repeat polymorphism led to a lower glomerular filtration rate. No modifiers for the risk of hyposthenuria were identified. A genome-wide association approach identified three new loci for proteinuria (CRYL1, VWF, and ADAMTS7) and nine loci were linked with eGFR (PKD1L2, TOR2A, CUBN, AGGF1, CYP4B1, CD163, LRP1B, linc02288, and FPGT-TNNI3K/TNNI3K). In conclusion, this systematic review supports the role of genetic modifiers in influencing the risk and progression of SCN. Incorporating and expanding this knowledge is crucial to improving the management and clinical outcomes of patients at risk.

Genetic Dissection of Diverse Seed Coat Patterns in Cowpea through a Comprehensive GWAS Approach.

This study investigates the genetic determinants of seed coat color and pattern variations in cowpea (Vigna unguiculata), employing a genome-wide association approach. Analyzing a mapping panel of 296 cowpea varieties with 110,000 single nucleotide polymorphisms (SNPs), we focused on eight unique coat patterns: (1) Red and (2) Cream seed; (3) White and (4) Brown/Tan seed coat; (5) Pink, (6) Black, (7) Browneye and (8) Red/Brown Holstein. Across six GWAS models (GLM, SRM, MLM, MLMM, FarmCPU from GAPIT3, and TASSEL5), 13 significant SNP markers were identified and led to the discovery of 23 candidate genes. Among these, four specific genes may play a direct role in determining seed coat pigment. These findings lay a foundational basis for future breeding programs aimed at creating cowpea varieties aligned with consumer preferences and market requirements.

Genetic insight into a polygenic trait using a novel genome-wide association approach in a wild amphibian population.

Body size variation is central in the evolution of life-history traits in amphibians, but the underlying genetic architecture of this complex trait is still largely unknown. Herein, we studied the genetic basis of body size and fecundity of the alternative morphotypes in a wild population of the Greek smooth newt (Lissotriton graecus). By combining a genome-wide association approach with linkage disequilibrium network analysis, we were able to identify clusters of highly correlated loci thus maximizing sequence data for downstream analysis. The putatively associated variants explained 12.8% to 44.5% of the total phenotypic variation in body size and were mapped to genes with functional roles in the regulation of gene expression and cell cycle processes. Our study is the first to provide insights into the genetic basis of complex traits in newts and provides a useful tool to identify loci potentially involved in fitness-related traits in small data sets from natural populations in non-model species.

Genome-wide association study for in vitro digestibility and related traits in triticale forage

BackgroundTriticale is making its way on dairy farms as an alternative forage crop. This requires the availability of high-yielding triticale varieties with good digestibility. Triticale forage breeding mainly focussed on biomass yield, but efforts to improve digestibility are increasing. We previously investigated the interrelationships among different quality traits in soft dough triticale: starch, acid detergent fibre and in vitro digestibility of organic matter (IVOMD) and of neutral detergent fibre (IVNDFD) of the total plant, IVNDFD and Klason lignin of the stems, and ear proportion and stem length. Here we determine the genetic control of these traits, using a genome-wide association (GWAS) approach. A total of 33,231 DArTseq SNP markers assessed in a collection of 118 winter triticale genotypes, including 101 varieties and 17 breeding lines, were used.ResultsThe GWAS identified a total of 53 significant marker-trait associations (MTAs). The highest number of significantly associated SNP markers (n = 10) was identified for total plant IVNDFD. A SNP marker on chromosome 1A (4211801_19_C/T; 474,437,796 bp) was found to be significantly associated with ear proportion, and plant and stem IVNDFD, with the largest phenotypic variation for ear proportion (R²p = 0.23). Based on MTAs, candidate genes were identified which were of particular relevance for variation in in vitro digestibility (IVD) because they are putatively involved in plasma membrane transport, cytoskeleton organisation, carbohydrate metabolic processes, protein phosphorylation, and sterol and cell wall biogenesis. Interestingly, a xyloglucan-related candidate gene on chromosome 2R, SECCE2Rv1G0126340, was located in close proximity of a SNP significantly associated with stem IVNDFD. Furthermore, quantitative trait loci previously reported in wheat co-localized with significantly associated SNP markers in triticale.ConclusionsA collection of 118 winter triticale genotypes combined with DArTseq SNP markers served as a source for identifying 53 MTAs and several candidate genes for forage IVD and related traits through a GWAS approach. Taken together, the results of this study demonstrate that the genetic diversity available in this collection can be further exploited for research and breeding purposes to improve the IVD of triticale forage.

Molecular genetic foundation of a sex-linked tailless trait in Hongshan chicken by whole genome data analysis

As a Chinese local chicken breed, Hongshan chickens have 2 kinds of tail feather phenotypes, normal and taillessness. Our previous studies showed that taillessness was a sex-linked dominant trait. Abnormal development of the tail vertebrae could be explained this phenomenon in some chicken breeds. However, the number of caudal vertebrae in rumpless Hongshan chickens was normal, so rumplessness in Hongshan chicken was not related to the development of the caudal vertebrae. Afterwards, we found that rumplessness in Hongshan was due to abnormal development of tail feather rather than abnormal development of caudal vertebrae. In order to understand the genetic foundation of the rumplessness of Hongshan chickens, we compared and reanalyzed 2 sets of data in normal and rumpless Hongshan chickens from our previous studies. By joint analysis of genome-wide selection signature analysis and genome-wide association approach, we found that 1 overlapping gene (EDIL3) and 16 peak genes (ENSGALG00000051843, ENSGALG00000053498, ENSGALG00000054800, KIF27, PTPRD, ENSGALG00000047579, ENSGALG00000041052, ARHGEF28, CAMK4, SERINC5, ENSGALG00000050776, ERCC8, MCC, ADAMTS19, ENSGALG00000053322, CHRNA8) located on the Z chromosome was associated with the rumpless trait. The results of this study furtherly revealed the molecular mechanism of the rumpless trait in Hongshan chickens, and identified the candidate genes associated with this trait. Our results will help to improve the shape of chicken tail feathers and to rise individual economic value in some specific market in China.

Genetic Mechanism of Non-Targeted-Site Resistance to Diquat in Spirodela polyrhiza

Understanding non-target-site resistance (NTSR) to herbicides represents a pressing challenge as NTSR is widespread in many weeds. Using giant duckweed (Spirodela polyrhiza) as a model, we systematically investigated genetic and molecular mechanisms of diquat resistance, which can only be achieved via NTSR. Quantifying the diquat resistance of 138 genotypes, we revealed an 8.5-fold difference in resistance levels between the most resistant and most susceptible genotypes. Further experiments suggested that diquat uptake and antioxidant-related processes jointly contributed to diquat resistance in S. polyrhiza. Using a genome-wide association approach, we identified several candidate genes, including a homolog of dienelactone hydrolase, that are associated with diquat resistance in S. polyrhiza. Together, these results provide new insights into the mechanisms and evolution of NTSR in plants.

Maize green leaf area index dynamics: genetic basis of a new secondary trait for grain yield in optimal and drought conditions

Key messageGreen Leaf Area Index dynamics is a promising secondary trait for grain yield and drought tolerance. Multivariate GWAS is particularly well suited to identify the genetic determinants of the green leaf area index dynamics.Improvement of maize grain yield is impeded by important genotype-environment interactions, especially under drought conditions. The use of secondary traits, that are correlated with yield, more heritable and less prone to genotype-environment interactions, can increase breeding efficiency. Here, we studied the genetic basis of a new secondary trait: the green leaf area index (GLAI) dynamics over the maize life cycle. For this, we used an unmanned aerial vehicle to characterize the GLAI dynamics of a diverse panel in well-watered and water-deficient trials in two years. From the dynamics, we derived 24 traits (slopes, durations, areas under the curve), and showed that six of them were heritable traits representative of the panel diversity. To identify the genetic determinants of GLAI, we compared two genome-wide association approaches: a univariate (single-trait) method and a multivariate (multi-trait) method combining GLAI traits, grain yield, and precocity. The explicit modeling of correlation structure between secondary traits and grain yield in the multivariate mixed model led to 2.5 times more associations detected. A total of 475 quantitative trait loci (QTLs) were detected. The genetic architecture of GLAI traits appears less complex than that of yield with stronger-effect QTLs that are more stable between environments. We also showed that a subset of GLAI QTLs explains nearly one fifth of yield variability across a larger environmental network of 11 water-deficient trials. GLAI dynamics is a promising grain yield secondary trait in optimal and drought conditions, and the detected QTLs could help to increase breeding efficiency through a marker-assisted approach.

Genome-wide association analysis reveals genes controlling an antagonistic effect of biotic and osmotic stress on Arabidopsis thaliana growth.

While the response of Arabidopsis thaliana to drought, herbivory or fungal infection has been well-examined, the consequences of exposure to a series of such (a)biotic stresses are not well studied. This work reports on the genetic mechanisms underlying the Arabidopsis response to single osmotic stress, and to combinatorial stress, either fungal infection using Botrytis cinerea or herbivory using Pieris rapae caterpillars followed by an osmotic stress treatment. Several small-effect genetic loci associated with rosette dry weight (DW), rosette water content (WC), and the projected rosette leaf area in response to combinatorial stress were mapped using univariate and multi-environment genome-wide association approaches. A single-nucleotide polymorphism (SNP) associated with DROUGHT-INDUCED 19 (DI19) was identified by both approaches, supporting its potential involvement in the response to combinatorial stress. Several SNPs were found to be in linkage disequilibrium with known stress-responsive genes such as PEROXIDASE 34 (PRX34), BASIC LEUCINE ZIPPER 25 (bZIP25), RESISTANCE METHYLATED GENE 1 (RMG1) and WHITE RUST RESISTANCE 4 (WRR4). An antagonistic effect between biotic and osmotic stress was found for prx34 and arf4 mutants, which suggests PRX34 and ARF4 play an important role in the response to the combinatorial stress.

Genetic basis and selection of glyceollin elicitation in wild soybean.

Glyceollins, a family of phytoalexins elicited in legume species, play crucial roles in environmental stress response (e.g., defending against pathogens) and human health. However, little is known about the genetic basis of glyceollin elicitation. In the present study, we employed a metabolite-based genome-wide association (mGWA) approach to identify candidate genes involved in glyceollin elicitation in genetically diverse and understudied wild soybeans subjected to soybean cyst nematode. In total, eight SNPs on chromosomes 3, 9, 13, 15, and 20 showed significant associations with glyceollin elicitation. Six genes fell into two gene clusters that encode glycosyltransferases in the phenylpropanoid pathway and were physically close to one of the significant SNPs (ss715603454) on chromosome 9. Additionally, transcription factors (TFs) genes such as MYB and WRKY were also found as promising candidate genes within close linkage to significant SNPs on chromosome 9. Notably, four significant SNPs on chromosome 9 show epistasis and a strong signal for selection. The findings describe the genetic foundation of glyceollin biosynthesis in wild soybeans; the identified genes are predicted to play a significant role in glyceollin elicitation regulation in wild soybeans. Additionally, how the epistatic interactions and selection influence glyceollin variation in natural populations deserves further investigation to elucidate the molecular mechanism of glyceollin biosynthesis.

Genomic basis of seed colour in quinoa inferred from variant patterns using extreme gradient boosting.

Quinoa is an agriculturally important crop species originally domesticated in the Andes of central South America. One of its most important phenotypic traits is seed colour. Seed colour variation is determined by contrasting abundance of betalains, a class of strong antioxidant and free radicals scavenging colour pigments only found in plants of the order Caryophyllales. However, the genetic basis for these pigments in seeds remains to be identified. Here we demonstrate the application of machine learning (extreme gradient boosting) to identify genetic variants predictive of seed colour. We show that extreme gradient boosting outperforms the classical genome-wide association approach. We provide re-sequencing and phenotypic data for 156 South American quinoa accessions and identify candidate genes potentially controlling betalain content in quinoa seeds. Genes identified include novel cytochrome P450 genes and known members of the betalain synthesis pathway, as well as genes annotated as being involved in seed development. Our work showcases the power of modern machine learning methods to extract biologically meaningful information from large sequencing data sets.

The genomic architecture of continuous plumage colour variation in the European barn owl (Tyto alba).

The maintenance of colour variation in wild populations has long fascinated evolutionary biologists, although most studies have focused on discrete traits exhibiting rather simple inheritance patterns and genetic architectures. However, the study of continuous colour traits and their potentially oligo- or polygenic genetic bases remains rare in wild populations. We studied the genetics of the continuously varying white-to-rufous plumage coloration of the European barn owl (Tyto alba) using a genome-wide association approach on the whole-genome data of 75 individuals. We confirmed a mutation at the melanocortin-1-receptor gene (MC1R) is involved in the coloration and identified two new regions, located in super-scaffolds 9 and 42. The combination of the three regions explains most of the colour variation (80.37%, 95% credible interval 58.45-100%). One discovered region, located in the sex chromosome, differs between the most extreme colorations in owls sharing a specific MC1R genotype. This region may play a role in the colour sex dimorphism of this species, possibly in interaction with the autosomal MC1R. We thus provide insights into the genetic architecture of continuous colour variation, pointing to an oligogenic basis with potential epistatic effects among loci that should aid future studies understanding how continuous colour variation is maintained in nature.

Identification of novel sources of partial and incomplete hypersensitive resistance to rust and associated genomic regions in common bean

Common bean (Phaseolus vulgaris) is one of the legume crops most consumed worldwide and bean rust is one of the most severe foliar biotrophic fungal diseases impacting its production. In this work, we searched for new sources of rust resistance (Uromyces appendiculatus) in a representative collection of the Portuguese germplasm, known to have accessions with an admixed genetic background between Mesoamerican and Andean gene pools. We identified six accessions with incomplete hypersensitive resistance and 20 partially resistant accessions of Andean, Mesoamerican, and admixed origin. We detected 11 disease severity-associated single-nucleotide polymorphisms (SNPs) using a genome-wide association approach. Six of the associations were related to partial (incomplete non-hypersensitive) resistance and five to incomplete hypersensitive resistance, and the proportion of variance explained by each association varied from 4.7 to 25.2%. Bean rust severity values ranged from 0.2 to 49.1% and all the infection types were identified, reflecting the diversity of resistance mechanisms deployed by the Portuguese germplasm.The associations with U. appendiculatus partial resistance were located in chromosome Pv08, and with incomplete hypersensitive resistance in chromosomes Pv06, Pv07, and Pv08, suggesting an oligogenic inheritance of both types of resistance. A resolution to the gene level was achieved for eight of the associations. The candidate genes proposed included several resistance-associated enzymes, namely β-amylase 7, acyl-CoA thioesterase, protein kinase, and aspartyl protease. Both SNPs and candidate genes here identified constitute promising genomics targets to develop functional molecular tools to support bean rust resistance precision breeding.

Fast multiple-trait genome-wide association analysis for correlated longitudinal measurements

Large-scale longitudinal biobank data can be leveraged to identify genetic variation contributing to human diseases progression and traits trajectories. While methods for genome-wide association studies (GWAS) of multiple correlated traits have been proposed, an efficient multiple-trait approach to model longitudinal phenotypes is not currently available. We developed GAMUT, a genome-wide association approach for multiple longitudinal traits. GAMUT employs a mixed-effects model to fit longitudinal outcomes where a fast algorithm for inversion by recursive partitioning of the random effects submatrix is introduced. To evaluate performance of the algorithms introduced and assess their statistical power and type I error, stochastic simulation was conducted. Consistent with our expectation, power was greater for cross-sectional (CS) than longitudinal (LT) effects, particularly with a diminishing LT/CS ratio. With a minimum minor allele count of 3 within genotype by time categories, observed type I error was roughly equal to theoretical genome-wide significance. Additionally, 28 blood-based biomarkers measured at 2 time points on participants of the UK Biobank were used to compare GAMUT against single-trait standard and longitudinal GWAS (including rate of change). Across all biomarkers, we observed 539 (CS) and 248 (LT) significant independent variants for the GAMUT method, and 513 (CS) and 30 (LT) for single-trait longitudinal GWAS, respectively. Only 37 variants were identified by modeling rates of change using standard GWAS.

Genome-wide association and environmental suppression of the mortal germline phenotype of wild C. elegans.

The animal germline lineage needs to be maintained along generations. However, some Caenorhabditis elegans wild isolates display a mortal germline phenotype, leading to sterility after several generations at 25°C. Using a genome-wide association approach, we detect a significant peak on chromosome III around 5 Mb, confirmed by introgressions. Thus, a seemingly deleterious genotype is maintained at intermediate frequency in the species. Environmental rescue is a likely explanation, and indeed associated bacteria and microsporidia suppress the phenotype of wild isolates as well as mutants in small RNA inheritance (nrde-2) and histone modifications (set-2). Escherichia coli strains of the K-12 lineage suppress the phenotype compared to B strains. By shifting a wild strain from E. coli K-12 to E. coli B, we find that memory of the suppressing condition is maintained over several generations. Thus, the mortal germline phenotype of wild C. elegans is in part revealed by laboratory conditions and may represent variation in epigenetic inheritance and environmental interactions. This study also points to the importance of non-genetic memory in the face of environmental variation.