The Genetic Architecture of Dewlap Pattern in Hispaniola Anoles (Anolis distichus)

Color and pattern are often critical to survival and fitness, but we know little about their genetic architecture and heritability in groups like reptiles. We investigated the genetic architecture for the pattern of the dewlap - an extensible throat fan important for communication - in anole lizards. We studied the Hispaniolan bark anole (Anolis distichus) - a species that exhibits impressive intraspecific dewlap polymorphism across its range - by conducting multi-generational experimental crosses with two populations, one with a solid pale yellow dewlap and another with an orange dewlap surrounded by a yellow margin. Upon rejecting the hypothesis that the extent of the orange pattern is a quantitative trait resulting from many loci of minor effect, we used a maximum likelihood model-fitting framework to show that it is better explained as a simple Mendelian trait, with the solid yellow morph being dominant over the blush orange. The relatively simple genetic architecture underlying this important trait helps explain the complex distribution of dewlap color variation across the rage of A. distichus and suggests that changes in dewlap color and pattern may evolve rapidly in response to natural selection.

Multi-locus genome-wide association study and genomic prediction for flowering time in chrysanthemum

MAIN CONCLUSION

Multi-locus GWAS detected several known and candidate genes responsible for flowering time in chrysanthemum. The associations could greatly increase the predictive ability of genome selection that accelerates the possible application of GS in chrysanthemum breeding. Timely flowering is critical for successful reproduction and determines the economic value for ornamental plants. To investigate the genetic architecture of flowering time in chrysanthemum, a multi-locus genome-wide association study (GWAS) was performed using a collection of 200 accessions and 330,710 single-nucleotide polymorphisms (SNPs) via 3VmrMLM method. Five flowering time traits including budding (FBD), visible colouring (VC), early opening (EO), full-bloom (OF) and senescing (SF) stages, plus five derived conditional traits were recorded in two environments. Extensive phenotypic variations were observed for these flowering time traits with coefficients of variation ranging from 6.42 to 38.27%, and their broad-sense heritability ranged from 71.47 to 96.78%. GWAS revealed 88 stable quantitative trait nucleotides (QTNs) and 93 QTN-by-environment interactions (QEIs) associated with flowering time traits, accounting for 0.50-8.01% and 0.30-10.42% of the phenotypic variation, respectively. Amongst the genes around these stable QTNs and QEIs, 21 and 10 were homologous to known flowering genes in Arabidopsis; 20 and 11 candidate genes were mined by combining the functional annotation and transcriptomics data, respectively, such as MYB55, FRIGIDA-like, WRKY75 and ANT. Furthermore, genomic selection (GS) was assessed using three models and seven unique marker datasets. We found the prediction accuracy (PA) using significant SNPs identified by GWAS under SVM model exhibited the best performance with PA ranging from 0.90 to 0.95. Our findings provide new insights into the dynamic genetic architecture of flowering time and the identified significant SNPs and candidate genes will accelerate the future molecular improvement of chrysanthemum.

An exploratory data analysis on genetic architecture in Bos taurus through miRNAs within QTLs and their target genes

Understanding the genetic architecture is important because it allows us to understand the relationship between molecular markers, like miRNAs, QTLs and SNPs, and traits of interest such as milk yield, lipidic content in milk, heat tolerance etc. In the present study we performed an exploratory analysis that found an association of 480 miRNAs within QTLs related to 155 traits. We also discovered that those 480 miRNAs might modulate the expression of 12.374 genes. The most predominant traits available in the data were milk related, such as milk yield and fatty acids content in milk. Besides, the functional enrichment analysis revealed that some of those genes were linked to sensory perception, olfactory perception, perception of stimulus and chemical stimulus, localization, establishment of localization, transport etc. Furthermore, the discovery of miRNAs within QTLs and their target analysis suggests that they might be associated with characteristics of interest. By analyzing these relationships, we strongly encourage that future QTL studies should include miRNAs analysis. Altogether, our analysis enabled us to explore the association between multiple complex traits, miRNAs within QTLs and their target genes in Bos taurus that might have implications in breeding programs.

A phenome-wide scan reveals convergence of common and rare variant associations

BACKGROUND

Common and rare variants contribute to the etiology of complex traits. However, the extent to which the phenotypic effects of common and rare variants involve shared molecular mediators remains poorly understood. The question is essential to the basic and translational goals of the science of genomics, with critical basic-science, methodological, and clinical consequences.

METHODS

Leveraging the latest release of whole-exome sequencing (WES, for rare variants) and genome-wide association study (GWAS, for common variants) data from the UK Biobank, we developed a metric, the COmmon variant and RAre variant Convergence (CORAC) signature, to quantify the convergence for a broad range of complex traits. We characterized the relationship between CORAC and effective sample size across phenome-wide association studies.

RESULTS

We found that the signature is positively correlated with effective sample size (Spearman ρ = 0.594, P < 2.2e - 16), indicating increased functional convergence of trait-associated genetic variation, across the allele frequency spectrum, with increased power. Sensitivity analyses, including accounting for heteroskedasticity and varying the number of detected association signals, further strengthened the validity of the finding. In addition, consistent with empirical data, extensive simulations showed that negative selection, in line with enhancing polygenicity, has a dampening effect on the convergence signature. Methodologically, leveraging the convergence leads to enhanced association analysis.

CONCLUSIONS

The presented framework for the convergence signature has important implications for fine-mapping strategies and drug discovery efforts. In addition, our study provides a blueprint for the expectation from future large-scale whole-genome sequencing (WGS)/WES and sheds methodological light on post-GWAS studies.

Genetic correlation for alcohol consumption between Europeans and East Asians

Genome-wide association studies (GWAS) have identified many genetic variants associated with alcohol consumption in Europeans and East Asians, as well as other populations. However, the genetic homogeneity and heterogeneity between these populations have not been thoroughly investigated, despite evidence of varying effect sizes of variants between ethnicities and the presence of population-specific strong signals of selection on loci associated with alcohol consumption. In order to better understand the relationship between Europeans and East Asians in the genetic architecture of alcohol consumption, we compared their heritability and evaluated their genetic correlation using GWAS results from UK Biobank (UKB) and Biobank Japan (BBJ). We found that these two populations have low genetic correlation due to the large difference on chromosome 12. After excluding this chromosome, the genetic correlation was moderately high ([Formula: see text] = 0.544, p = 1.12e-4) and 44.31% of the genome-wide causal variants were inferred to be shared between Europeans and East Asians. Given those observations, we conducted a meta-analysis on UKB and BBJ and identified new signals, including the CADM2 gene on chromosome 3, which has been associated with various behavioral and metabolic traits. Overall, our findings suggest that the genetic architecture of alcohol consumption is largely shared between Europeans and East Asians, but there are exceptions such as the enrichment of heritability on chromosome 12 in East Asians.

The pivotal role of the X-chromosome in the genetic architecture of the human brain

Genes on the X-chromosome are extensively expressed in the human brain, resulting in substantial influences on brain development, intellectual disability, and other brain-related disorders. To comprehensively investigate the X-chromosome's impact on the cerebral cortex, white matter tract microstructures, and intrinsic and extrinsic brain functions, we examined 2,822 complex brain imaging traits obtained from n = 34,000 subjects in the UK Biobank. We unveiled potential autosome-X-chromosome interaction, while proposing an atlas of dosage compensation (DC) for each set of traits. We observed a pronounced X-chromosome impact on the corticospinal tract and the functional amplitude and connectivity of visual networks. In association studies, we identified 50 genome-wide significant trait-locus pairs enriched in Xq28, 22 of which replicated in independent datasets (n = 4,900 ). Notably, 13 newly identified pairs were in the X-chromosome's non-pseudo-autosomal regions (NPR). The volume of the right ventral diencephalon shared genetic architecture with schizophrenia and educational attainment in a locus indexed by rs2361468 (located ~3kb upstream of PJA1, a conserved and ubiquitously expressed gene implicated in multiple psychiatric disorders). No significant associations were identified in the pseudo-autosomal regions (PAR) or the Y-chromosome. Finally, we explored sex-specific associations on the X-chromosome and compared differing genetic effects between sexes. We found much more associations can be identified in males (33 versus 9) given a similar sample size. In conclusion, our research provides invaluable insights into the X-chromosome's role in the human brain, contributing to the observed sex differences in brain structure and function.

Identifying shared genetic architecture between rheumatoid arthritis and other conditions: a phenome-wide association study with genetic risk scores

BACKGROUND

Rheumatoid arthritis (RA) shares genetic variants with other autoimmune conditions, but existing studies test the association between RA variants with a pre-defined set of phenotypes. The objective of this study was to perform a large-scale, systemic screen to determine phenotypes that share genetic architecture with RA to inform our understanding of shared pathways.

METHODS

In the UK Biobank (UKB), we constructed RA genetic risk scores (GRS) incorporating human leukocyte antigen (HLA) and non-HLA risk alleles. Phenotypes were defined using groupings of International Classification of Diseases (ICD) codes. Patients with an RA code were excluded to mitigate the possibility of associations being driven by the diagnosis or management of RA. We performed a phenome-wide association study, testing the association between the RA GRS with phenotypes using multivariate generalized estimating equations that adjusted for age, sex, and first five principal components. Statistical significance was defined using Bonferroni correction. Results were replicated in an independent cohort and replicated phenotypes were validated using medical record review of patients.

FINDINGS

We studied n = 316,166 subjects from UKB without evidence of RA and screened for association between the RA GRS and n = 1317 phenotypes. In the UKB, 20 phenotypes were significantly associated with the RA GRS, of which 13 (65%) were immune mediated conditions including polymyalgia rheumatica, granulomatosis with polyangiitis (GPA), type 1 diabetes, and multiple sclerosis. We further identified a novel association in Celiac disease where the HLA and non-HLA alleles had strong associations in opposite directions. Strikingly, we observed that the non-HLA GRS was exclusively associated with greater risk of the validated conditions, suggesting shared underlying pathways outside the HLA region.

INTERPRETATION

This study replicated and identified novel autoimmune phenotypes verified by medical record review that share immune pathways with RA and may inform opportunities for shared treatment targets, as well as risk assessment for conditions with a paucity of genomic data, such as GPA.

FUNDING

This research was funded by the US National Institutes of Health (P30AR072577, R21AR078339, R35GM142879, T32AR007530) and the Harold and DuVal Bowen Fund.

Evolution with recombination as Gibbs sampling

This work presents a population genetic model of evolution, which includes haploid selection, mutation, recombination, and drift. The mutation-selection equilibrium can be expressed exactly in closed form for arbitrary fitness functions without resorting to diffusion approximations. Tractability is achieved by generating new offspring using n-parent rather than 2-parent recombination. While this enforces linkage equilibrium among offspring, it allows analysis of the whole population under linkage disequilibrium. We derive a general and exact relationship between fitness fluctuations and response to selection. Our assumptions allow analytical calculation of the stationary distribution of the model for a variety of non-trivial fitness functions. These results allow us to speak to genetic architecture, i.e., what stationary distributions result from different fitness functions. This paper presents methods for exactly deriving stationary states for finite and infinite populations. This method can be applied to many fitness functions, and we give exact calculations for four of these. These results allow us to investigate metastability, tradeoffs between fitness functions, and even consider error-correcting codes.

Disease patterns of coronary heart disease and type 2 diabetes harbored distinct and shared genetic architecture

BACKGROUND

Coronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D.

METHOD

A data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets.

RESULTS

We identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × [Formula: see text]). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × [Formula: see text]). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy).

CONCLUSION

The SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

Identify novel, shared and disorder-specific genetic architecture of major depressive disorder, insomnia and chronic pain

Major depressive disorder (MDD), insomnia (INS) and chronic pain (CP) often have high comorbidity and show high genetic correlation. Here we aimed to better characterize their novel, shared and disorder-specific genetic architecture. Based on genome-wide association study (GWAS) summary data, we applied the conditional false discovery rate (condFDR) and conjunctional FDR (conjFDR) approach to investigate the novel and overlapped genetic loci for MDD, INS and CP. In addition, putative disorder-specific SNP associations were analyzed by conditioning the other two traits. The functions of the identified genomic loci were explored by performing gene set enrichment analysis (GSEA) for the loci mapped genes. We identified 22, 43 and 91 novel risk loci for MDD, INS and CP. GSEA for the loci mapped genes highlighted olfactory signaling pathway for MDD novel loci, breast cancer related gene set for both INS and CP novel loci, and nervous system related development, structure and activity for CP. Furthermore, we identified three loci jointly associated with the three disorders, including 13q14.3 locus with nearby gene OLFM4, 14q21.1 locus with nearby gene LRFN5 and 5q21.2 locus located in intergenic region. In addition, we identified one specific loci for MDD, 7 for INS and 11 for CP respectively by conditioning the other two traits, which were mapped to 68 genes for MDD, 85 for INS and 100 for CP. The MDD specific genes are enriched in immune system related pathways. This study increases understanding of the genetic architectures underlying MDD, INS and CP. The shared underlying genetic risk may help to explain the high comorbidity rates of the disorders.

Genetic architecture of tuberculosis susceptibility: A comprehensive research synopsis, meta-analyses, and epidemiological evidence

To date, many studies have been conducted to investigate associations between variants and tuberculosis risk; however, the results have been inconclusive. Here, we systematically provide a summary of the understanding of the genetic architecture of tuberculosis susceptibility. We searched PubMed, Embase and Web of Science to identify genetic association studies of tuberculosis published through October 31, 2021. We conducted meta-analyses for the genetic association with tuberculosis risk. We graded levels of cumulative epidemiological evidence of significant associations with risk of tuberculosis and false-positive report probability tests. We performed functional annotations for these variants using data from the Encyclopedia of DNA Elements (ENCODE) Project and other databases. We identified 703 eligible articles comprising 298,074 cases and 879,593 controls through screening a total of 24,398 citations. Meta-analyses were conducted for 614 genetic variants in 469 genes or loci. We found 39 variants that were nominally significantly associated with tuberculosis risk. Cumulative epidemiological evidence for a significant association was graded strong for 9 variants in or near 9 genes. Among them, 5 variants were associated with tuberculosis risk in at least three main ethnicity (African, Asian and White) which together explained approximately 9.59% of the familial relative risk of tuberculosis. Data from ENCODE and other databases suggested that 8 of these 9 genetic variants with strong evidence might fall within putative functional regions. Our study summarizes the current literature on the genetic architecture of tuberculosis susceptibility and provides useful data for designing future studies to investigate the genetic association with tuberculosis risk.

Alcohol use and alcohol use disorder differ in their genetic relationships with PTSD: A genomic structural equation modelling approach

PURPOSE

Posttraumatic Stress Disorder (PTSD) is associated with increased alcohol use and alcohol use disorder (AUD), which are all moderately heritable. Studies suggest the genetic association between PTSD and alcohol use differs from that of PTSD and AUD, but further analysis is needed.

BASIC PROCEDURES

We used genomic Structural Equation Modeling (genomicSEM) to analyze summary statistics from large-scale genome-wide association studies (GWAS) of European Ancestry participants to investigate the genetic relationships between PTSD (both diagnosis and re-experiencing symptom severity) and a range of alcohol use and AUD phenotypes.

MAIN FINDINGS

When we differentiated genetic factors for alcohol use and AUD we observed improved model fit relative to models with all alcohol-related indicators loading onto a single factor. The genetic correlations (rG) of PTSD were quite discrepant for the alcohol use and AUD factors. This was true when modeled as a three-correlated-factor model (PTSD-AUD rG:.36, p < .001; PTSD-alcohol use rG: -0.17, p < .001) and as a Bifactor model, in which the common and unique portions of alcohol phenotypes were pulled out into an AUD-specific factor (rG with PTSD:.40, p < .001), AU-specific factor (rG with PTSD: -0.57, p < .001), and a common alcohol factor (rG with PTSD:.16, NS).

PRINCIPAL CONCLUSIONS

These results indicate the genetic architecture of alcohol use and AUD are differentially associated with PTSD. When the portions of variance unique to alcohol use and AUD are extracted, their genetic associations with PTSD vary substantially, suggesting different genetic architectures of alcohol phenotypes in people with PTSD.

Challenge accepted: uncovering the role of rare genetic variants in Alzheimer's disease

The search for rare variants in Alzheimer's disease (AD) is usually deemed a high-risk - high-reward situation. The challenges associated with this endeavor are real. Still, the application of genome-wide technologies to large numbers of cases and controls or to small, well-characterized families has started to be fruitful.Rare variants associated with AD have been shown to increase risk or cause disease, but also to protect against the development of AD. All of these can potentially be targeted for the development of new drugs.Multiple independent studies have now shown associations of rare variants in NOTCH3, TREM2, SORL1, ABCA7, BIN1, CLU, NCK2, AKAP9, UNC5C, PLCG2, and ABI3 with AD and suggested that they may influence disease via multiple mechanisms. These genes have reported functions in the immune system, lipid metabolism, synaptic plasticity, and apoptosis. However, the main pathway emerging from the collective of genes harboring rare variants associated with AD is the Aβ pathway. Associations of rare variants in dozens of other genes have also been proposed, but have not yet been replicated in independent studies. Replication of this type of findings is one of the challenges associated with studying rare variants in complex diseases, such as AD. In this review, we discuss some of these primary challenges as well as possible solutions.Integrative approaches, the availability of large datasets and databases, and the development of new analytical methodologies will continue to produce new genes harboring rare variability impacting AD. In the future, more extensive and more diverse genetic studies, as well as studies of deeply characterized families, will enhance our understanding of disease pathogenesis and put us on the correct path for the development of successful drugs.

Estimating prevalence of human traits among populations from polygenic risk scores

The genetic basis of phenotypic variation across populations has not been well explained for most traits. Several factors may cause disparities, from variation in environments to divergent population genetic structure. We hypothesized that a population-level polygenic risk score (PRS) can explain phenotypic variation among geographic populations based solely on risk allele frequencies. We applied a population-specific PRS (psPRS) to 26 populations from the 1000 Genomes to four phenotypes: lactase persistence (LP), melanoma, multiple sclerosis (MS) and height. Our models assumed additive genetic architecture among the polymorphisms in the psPRSs, as is convention. Linear psPRSs explained a significant proportion of trait variance ranging from 0.32 for height in men to 0.88 for melanoma. The best models for LP and height were linear, while those for melanoma and MS were nonlinear. As not all variants in a PRS may confer similar, or even any, risk among diverse populations, we also filtered out SNPs to assess whether variance explained was improved using psPRSs with fewer SNPs. Variance explained usually improved with fewer SNPs in the psPRS and was as high as 0.99 for height in men using only 548 of the initial 4208 SNPs. That reducing SNPs improves psPRSs performance may indicate that missing heritability is partially due to complex architecture that does not mandate additivity, undiscovered variants or spurious associations in the databases. We demonstrated that PRS-based analyses can be used across diverse populations and phenotypes for population prediction and that these comparisons can identify the universal risk variants.

Integration of selection signatures and multi-trait GWAS reveals polygenic genetic architecture of carcass traits in beef cattle

Carcass merits are widely considered as economically important traits affecting beef production in the beef cattle industry. However, the genetic basis of carcass traits remains to be well understood. Here, we applied multiple methods, including the Composite of Likelihood Ratio (CLR) and Genome-wide Association Study (GWAS), to explore the selection signatures and candidate variants affecting carcass traits. We identified 11,600 selected regions overlapping with 2214 candidate genes, and most of those were enriched in binding and gene regulation. Notably, we identified 66 and 110 potential variants significantly associated with carcass traits using single-trait and multi-traits analyses, respectively. By integrating selection signatures with single and multi-traits associations, we identified 12 and 27 putative genes, respectively. Several highly conserved missense variants were identified in OR5M13D, NCAPG, and TEX2. Our study supported polygenic genetic architecture of carcass traits and provided novel insights into the genetic basis of complex traits in beef cattle.

Admixture mapping reveals the association between Native American ancestry at 3q13.11 and reduced risk of Alzheimer's disease in Caribbean Hispanics

BACKGROUND

Genetic studies have primarily been conducted in European ancestry populations, identifying dozens of loci associated with late-onset Alzheimer's disease (AD). However, much of AD's heritability remains unexplained; as the prevalence of AD varies across populations, the genetic architecture of the disease may also vary by population with the presence of novel variants or loci.

METHODS

We conducted genome-wide analyses of AD in a sample of 2565 Caribbean Hispanics to better understand the genetic contribution to AD in this population. Statistical analysis included both admixture mapping and association testing. Evidence for differential gene expression within regions of interest was collected from independent transcriptomic studies comparing AD cases and controls in samples with primarily European ancestry.

RESULTS

Our genome-wide association study of AD identified no loci reaching genome-wide significance. However, a genome-wide admixture mapping analysis that tests for association between a haplotype's ancestral origin and AD status detected a genome-wide significant association with chromosome 3q13.11 (103.7-107.7Mb, P = 8.76E-07), driven by a protective effect conferred by the Native American ancestry (OR = 0.58, 95%CI = 0.47-0.73). Within this region, two variants were significantly associated with AD after accounting for the number of independent tests (rs12494162, P = 2.33E-06; rs1731642, P = 6.36E-05). The significant admixture mapping signal is composed of 15 haplotype blocks spanning 5 protein-coding genes (ALCAM, BBX, CBLB, CCDC54, CD47) and four brain-derived topologically associated domains, and includes markers significantly associated with the expression of ALCAM, BBX, CBLB, and CD47 in the brain. ALCAM and BBX were also significantly differentially expressed in the brain between AD cases and controls with European ancestry.

CONCLUSION

These results provide multiethnic evidence for a relationship between AD and multiple genes at 3q13.11 and illustrate the utility of leveraging genetic ancestry diversity via admixture mapping for new insights into AD.

Low-Level Brain Somatic Mutations Are Implicated in Schizophrenia

BACKGROUND

Somatic mutations arising from the brain have recently emerged as significant contributors to neurodevelopmental disorders, including childhood intractable epilepsy and cortical malformations. However, whether brain somatic mutations are implicated in schizophrenia (SCZ) is not well established.

METHODS

We performed deep whole exome sequencing (average read depth > 550×) of matched dorsolateral prefrontal cortex and peripheral tissues from 27 patients with SCZ and 31 age-matched control individuals, followed by comprehensive and strict analysis of somatic mutations, including mutagenesis signature, substitution patterns, and involved pathways. In particular, we explored the impact of deleterious mutations in GRIN2B through primary neural culture.

RESULTS

We identified an average of 4.9 and 5.6 somatic mutations per exome per brain in patients with SCZ and control individuals, respectively. These mutations presented with average variant allele frequencies of 8.0% in patients with SCZ and 7.6% in control individuals. Although mutational profiles, such as the number and type of mutations, showed no significant difference between patients with SCZ and control individuals, somatic mutations in SCZ brains were significantly enriched for SCZ-related pathways, including dopamine receptor, glutamate receptor, and long-term potentiation pathways. Furthermore, we showed that brain somatic mutations in GRIN2B (encoding glutamate ionotropic NMDA receptor subunit 2B), which were found in two patients with SCZ, disrupted the location of GRIN2B across the surface of dendrites among primary cultured neurons.

CONCLUSIONS

Taken together, this study shows that brain somatic mutations are associated with the pathogenesis of SCZ.

Genome-wide association studies: assessing trait characteristics in model and crop plants

GWAS involves testing genetic variants across the genomes of many individuals of a population to identify genotype–phenotype association. It was initially developed and has proven highly successful in human disease genetics. In plants genome-wide association studies (GWAS) initially focused on single feature polymorphism and recombination and linkage disequilibrium but has now been embraced by a plethora of different disciplines with several thousand studies being published in model and crop species within the last decade or so. Here we will provide a comprehensive review of these studies providing cases studies on biotic resistance, abiotic tolerance, yield associated traits, and metabolic composition. We also detail current strategies of candidate gene validation as well as the functional study of haplotypes. Furthermore, we provide a critical evaluation of the GWAS strategy and its alternatives as well as future perspectives that are emerging with the emergence of pan-genomic datasets.

Characterizing the oligogenic architecture of plant growth phenotypes informs genomic selection approaches in a common wheat population

BACKGROUND

Genetic variation in growth over the course of the season is a major source of grain yield variation in wheat, and for this reason variants controlling heading date and plant height are among the best-characterized in wheat genetics. While the major variants for these traits have been cloned, the importance of these variants in contributing to genetic variation for plant growth over time is not fully understood. Here we develop a biparental population segregating for major variants for both plant height and flowering time to characterize the genetic architecture of the traits and identify additional novel QTL.

RESULTS

We find that additive genetic variation for both traits is almost entirely associated with major and moderate-effect QTL, including four novel heading date QTL and four novel plant height QTL. FT2 and Vrn-A3 are proposed as candidate genes underlying QTL on chromosomes 3A and 7A, while Rht8 is mapped to chromosome 2D. These mapped QTL also underlie genetic variation in a longitudinal analysis of plant growth over time. The oligogenic architecture of these traits is further demonstrated by the superior trait prediction accuracy of QTL-based prediction models compared to polygenic genomic selection models.

CONCLUSIONS

In a population constructed from two modern wheat cultivars adapted to the southeast U.S., almost all additive genetic variation in plant growth traits is associated with known major variants or novel moderate-effect QTL. Major transgressive segregation was observed in this population despite the similar plant height and heading date characters of the parental lines. This segregation is being driven primarily by a small number of mapped QTL, instead of by many small-effect, undetected QTL. As most breeding populations in the southeast U.S. segregate for known QTL for these traits, genetic variation in plant height and heading date in these populations likely emerges from similar combinations of major and moderate effect QTL. We can make more accurate and cost-effective prediction models by targeted genotyping of key SNPs.

Genome-Wide Association Analysis Reveals the Genetic Architecture of Parasite (Cryptocaryon irritans) Resistance in Large Yellow Croaker (Larimichthys crocea)

Large yellow croaker is an important marine culture species in China. Recently, the large yellow croaker industry is threatened by various disease problems, especially for the white spot disease, which is caused by parasite Cryptocaryon irritans. In the current study, we conducted a genome-wide association study (GWAS) for C. irritans resistance in two large yellow croaker populations (n = 264 and n = 480, respectively). We identified 15 QTL with explained genetic variance ranging from 1 to 8% in the two populations. One QTL on chromosome 23 was shared by the two populations, and three QTL had been reported in the previous study. We identified a lot of biological pathways associated with C. irritans resistance, such as hormone transport, response to bacterium, apoptotic process, acute inflammatory response to antigenic stimulus, and NF-kappa B signaling pathway. The genes casp8 and traf6 involved in regulatory network for apoptosis and inflammation were identified to be candidate genes for C. irritans resistance. Our results showed the complex polygenic architecture of resistance of large yellow croaker against C. irritans. These results would be helpful for the researches of the molecular mechanism of C. irritans resistance and genome-assisted breeding of large yellow croaker.

Adoption and Optimization of Genomic Selection To Sustain Breeding for Apricot Fruit Quality

Genomic selection (GS) is a breeding approach which exploits genome-wide information and whose unprecedented success has shaped several animal and plant breeding schemes through delivering their genetic progress. This is the first study assessing the potential of GS in apricot (Prunus armeniaca) to enhance postharvest fruit quality attributes. Genomic predictions were based on a F1 pseudo-testcross population, comprising 153 individuals with contrasting fruit quality traits. They were phenotyped for physical and biochemical fruit metrics in contrasting climatic conditions over two years. Prediction accuracy (PA) varied from 0.31 for glucose content with the Bayesian LASSO (BL) to 0.78 for ethylene production with RR-BLUP, which yielded the most accurate predictions in comparison to Bayesian models and only 10% out of 61,030 SNPs were sufficient to reach accurate predictions. Useful insights were provided on the genetic architecture of apricot fruit quality whose integration in prediction models improved their performance, notably for traits governed by major QTL. Furthermore, multivariate modeling yielded promising outcomes in terms of PA within training partitions partially phenotyped for target traits. This provides a useful framework for the implementation of indirect selection based on easy-to-measure traits. Thus, we highlighted the main levers to take into account for the implementation of GS for fruit quality in apricot, but also to improve the genetic gain in perennial species.

Genome-Wide Association Study of Rice Rooting Ability at the Seedling Stage

BACKGROUND

Rice rooting ability is a complex agronomical trait that displays heterosis and plays an important role in rice growth and production. Only a few quantitative trait loci (QTLs) have been identified by bi-parental population. More genes or QTLs are required to dissect the genetic architecture of rice rooting ability.

RESULTS

To characterize the genetic basis for rice rooting ability, we used a natural rice population, genotyped by a 90 K single nucleotide polymorphism (SNP) array, to identify the loci associated with rooting-related traits through the genome-wide association study (GWAS). Population structure analysis divided the natural population into two subgroups: indica and japonica. We measured four traits for evaluating rice rooting ability, namely root growth ability (RGA), maximum root length (MRL), root length (RL), and root number (RN). Using the association study in three panels consisting of one for the full population, one for indica, and one for japonica, 24 SNPs associated with rooting ability-related traits were identified. Through comparison of the relative expression levels and DNA sequences between germplasm with extreme phenotypes, results showed that LOC_Os05g11810 had non-synonymous variations at the coding region, which may cause differences in root number, and that the expression levels of LOC_Os04g09900 and LOC_Os04g10060 are closely associated with root length variation.

CONCLUSIONS

Through evaluation of the rice rooting ability-related traits and the association mapping, we provided useful information for understanding the genetic basis of rice rooting ability and also identified some candidate genes and molecular markers for rice root breeding.

Characterization of genetic determinants of the resistance to phylloxera, Daktulosphaira vitifoliae, and the dagger nematode Xiphinema index from muscadine background

BACKGROUND

Muscadine (Muscadinia rotundifolia) is known as a resistance source to many pests and diseases in grapevine. The genetics of its resistance to two major grapevine pests, the phylloxera D. vitifoliae and the dagger nematode X. index, vector of the Grapevine fanleaf virus (GFLV), was investigated in a backcross progeny between the F1 resistant hybrid material VRH8771 (Vitis-Muscadinia) derived from the muscadine R source 'NC184-4' and V. vinifera cv. 'Cabernet-Sauvignon' (CS).

RESULTS

In this pseudo-testcross, parental maps were constructed using simple-sequence repeats markers and single nucleotide polymorphism markers from a GBS approach. For the VRH8771 map, 2271 SNP and 135 SSR markers were assembled, resulting in 19 linkage groups (LG) and an average distance between markers of 0.98 cM. Phylloxera resistance was assessed by monitoring root nodosity number in an in planta experiment and larval development in a root in vitro assay. Nematode resistance was studied using 10-12 month long tests for the selection of durable resistance and rating criteria based on nematode reproduction factor and gall index. A major QTL for phylloxera larval development, explaining more than 70% of the total variance and co-localizing with a QTL for nodosity number, was identified on LG 7 and designated RDV6. Additional QTLs were detected on LG 3 (RDV7) and LG 10 (RDV8), depending on the in planta or in vitro experiments, suggesting that various loci may influence or modulate nodosity formation and larval development. Using a Bulked Segregant Analysis approach and a proportion test, markers clustered in three regions on LG 9, LG 10 and LG 18 were shown to be associated to the nematode resistant phenotype. QTL analysis confirmed the results and QTLs were thus designated respectively XiR2, XiR3 and XiR4, although a LOD-score below the significant threshold value was obtained for the QTL on LG 18.

CONCLUSIONS

Based on a high-resolution linkage map and a segregating grapevine backcross progeny, the first QTLs for resistance to D. vitifoliae and to X. index were identified from a muscadine source. All together these results open the way to the development of marker-assisted selection in grapevine rootstock breeding programs based on muscadine derived resistance to phylloxera and to X. index in order to delay GFLV transmission.

The genetic basis of hybrid male sterility in sympatric Primulina species

BACKGROUND

Sympatric sister species provide an opportunity to investigate the genetic mechanisms and evolutionary forces that maintain species boundaries. The persistence of morphologically and genetically distinct populations in sympatry can only occur if some degree of reproductive isolation exists. A pair of sympatric sister species of Primulina (P. depressa and P. danxiaensis) was used to explore the genetic architecture of hybrid male sterility.

RESULTS

We mapped one major- and seven minor-effect quantitative trait loci (QTLs) that underlie pollen fertility rate (PFR). These loci jointly explained 55.4% of the phenotypic variation in the F2 population. A Bateson-Dobzhansky-Muller (BDM) model involving three loci was observed in this system. We found genotypic correlations between hybrid male sterility and flower morphology, consistent with the weak but significant phenotypic correlations between PFR and floral traits.

CONCLUSIONS

Hybrid male sterility in Primulina is controlled by a polygenic genetic basis with a complex pattern. The genetic incompatibility involves a three-locus BDM model. Hybrid male sterility is genetically correlated with floral morphology and divergence hitchhiking may occur between them.

Genome-wide association study on Fourier transform infrared milk spectra for two Danish dairy cattle breeds

Background

Infrared spectral analysis of milk is cheap, fast, and accurate. Infrared light interacts with chemical bonds present inside the milk, which means that Fourier transform infrared milk spectra are a reflection of the chemical composition of milk. Heritability of Fourier transform infrared milk spectra has been analysed previously. Further genetic analysis of Fourier transform infrared milk spectra could give us a better insight in the genes underlying milk composition. Breed influences milk composition, yet not much is known about the effect of breed on Fourier transform infrared milk spectra. Improved understanding of the effect of breed on Fourier transform infrared milk spectra could enhance efficient application of Fourier transform infrared milk spectra. The aim of this study is to perform a genome wide association study on a selection of wavenumbers for Danish Holstein and Danish Jersey. This will improve our understanding of the genetics underlying milk composition in these two dairy cattle breeds.

Results

For each breed separately, fifteen wavenumbers were analysed. Overall, more quantitative trait loci were observed for Danish Jersey compared to Danish Holstein. For both breeds, the majority of the wavenumbers was most strongly associated to a genomic region on BTA 14 harbouring DGAT1. Furthermore, for both breeds most quantitative trait loci were observed for wavenumbers that interact with the chemical bond C-O. For Danish Jersey, wavenumbers that interact with C-H were associated to genes that are involved in fatty acid synthesis, such as AGPAT3, AGPAT6, PPARGC1A, SREBF1, and FADS1. For wavenumbers which interact with –OH, associations were observed to genomic regions that have been linked to alpha-lactalbumin.

Conclusions

The current study identified many quantitative trait loci that underlie Fourier transform infrared milk spectra, and thus milk composition. Differences were observed between groups of wavenumbers that interact with different chemical bonds. Both overlapping and different QTL were observed for Danish Holstein and Danish Jersey.

Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: I: feed efficiency and component traits

BACKGROUND

Genome wide association studies (GWAS) on residual feed intake (RFI) and its component traits including daily dry matter intake (DMI), average daily gain (ADG), and metabolic body weight (MWT) were conducted in a population of 7573 animals from multiple beef cattle breeds based on 7,853,211 imputed whole genome sequence variants. The GWAS results were used to elucidate genetic architectures of the feed efficiency related traits in beef cattle.

RESULTS

The DNA variant allele substitution effects approximated a bell-shaped distribution for all the traits while the distribution of additive genetic variances explained by single DNA variants followed a scaled inverse chi-squared distribution to a greater extent. With a threshold of P-value < 1.00E-05, 16, 72, 88, and 116 lead DNA variants on multiple chromosomes were significantly associated with RFI, DMI, ADG, and MWT, respectively. In addition, lead DNA variants with potentially large pleiotropic effects on DMI, ADG, and MWT were found on chromosomes 6, 14 and 20. On average, missense, 3'UTR, 5'UTR, and other regulatory region variants exhibited larger allele substitution effects in comparison to other functional classes. Intergenic and intron variants captured smaller proportions of additive genetic variance per DNA variant. Instead 3'UTR and synonymous variants explained a greater amount of genetic variance per DNA variant for all the traits examined while missense, 5'UTR and other regulatory region variants accounted for relatively more additive genetic variance per sequence variant for RFI and ADG, respectively. In total, 25 to 27 enriched cellular and molecular functions were identified with lipid metabolism and carbohydrate metabolism being the most significant for the feed efficiency traits.

CONCLUSIONS

RFI is controlled by many DNA variants with relatively small effects whereas DMI, ADG, and MWT are influenced by a few DNA variants with large effects and many DNA variants with small effects. Nucleotide polymorphisms in regulatory region and synonymous functional classes play a more important role per sequence variant in determining variation of the feed efficiency traits. The genetic architecture as revealed by the GWAS of the imputed 7,853,211 DNA variants will improve our understanding on the genetic control of feed efficiency traits in beef cattle.

Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: II: carcass merit traits

BACKGROUND

Genome wide association studies (GWAS) were conducted on 7,853,211 imputed whole genome sequence variants in a population of 3354 to 3984 animals from multiple beef cattle breeds for five carcass merit traits including hot carcass weight (HCW), average backfat thickness (AFAT), rib eye area (REA), lean meat yield (LMY) and carcass marbling score (CMAR). Based on the GWAS results, genetic architectures of the carcass merit traits in beef cattle were elucidated.

RESULTS

The distributions of DNA variant allele substitution effects approximated a bell-shaped distribution for all the traits while the distribution of additive genetic variances explained by single DNA variants conformed to a scaled inverse chi-squared distribution to a greater extent. At a threshold of P-value < 10-5, 51, 33, 46, 40, and 38 lead DNA variants on multiple chromosomes were significantly associated with HCW, AFAT, REA, LMY, and CMAR, respectively. In addition, lead DNA variants with potentially large pleiotropic effects on HCW, AFAT, REA, and LMY were found on chromosome 6. On average, missense variants, 3'UTR variants, 5'UTR variants, and other regulatory region variants exhibited larger allele substitution effects on the traits in comparison to other functional classes. The amounts of additive genetic variance explained per DNA variant were smaller for intergenic and intron variants on all the traits whereas synonymous variants, missense variants, 3'UTR variants, 5'UTR variants, downstream and upstream gene variants, and other regulatory region variants captured a greater amount of additive genetic variance per sequence variant for one or more carcass merit traits investigated. In total, 26 enriched cellular and molecular functions were identified with lipid metabolisms, small molecular biochemistry, and carbohydrate metabolism being the most significant for the carcass merit traits.

CONCLUSIONS

The GWAS results have shown that the carcass merit traits are controlled by a few DNA variants with large effects and many DNA variants with small effects. Nucleotide polymorphisms in regulatory, synonymous, and missense functional classes have relatively larger impacts per sequence variant on the variation of carcass merit traits. The genetic architecture as revealed by the GWAS will improve our understanding on genetic controls of carcass merit traits in beef cattle.

Insights about collective decision-making at the genetic level

By living in a collective, individuals can share and aggregate information to base their decisions on the many rather than on the one, thereby increasing accuracy. But a collective can also be defined at the molecular level. In the following, we reason that genes, by working collectively, share fundamental features with social organisms, which ends, without invoking cognition, in wiser responses. For that, we compile into a single picture the terms redundancy, stochastic resonance, intrinsic and extrinsic noise, and cross-regulation.

Polygenic risk score for disability and insights into disability-related molecular mechanisms

Late life disability is a highly devastating condition affecting 20% or more of persons aged 65 years and older in the USA; it is an important determinant of acute medical and long-term care costs which represent a growing burden on national economies. Disability is a multifactorial trait that contributes substantially to decline of health/wellbeing. Accordingly, gaining insights into the genetics of disability could help in identifying molecular mechanisms of this devastating condition and age-related processes contributing to a large fraction of specific geriatric conditions, concordantly with geroscience. We performed a genome-wide association study of disability in a sample of 24,068 subjects from five studies with 12,550 disabled individuals. We identified 30 promising disability-associated polymorphisms in 19 loci at p < 10^-4; four of them attained suggestive significance, p < 10^-5. In contrast, polygenic risk scores aggregating effects of minor alleles of independent SNPs that were adversely or beneficially associated with disability showed highly significant associations in meta-analysis, p = 3.13 × 10^-45 and p = 5.60 × 10^-23, respectively, and were replicated in each study. The analysis of genetic pathways, related diseases, and biological functions supported the connections of genes for the identified SNPs with disabling and age-related conditions primarily through oxidative/nitrosative stress, inflammatory response, and ciliary signaling. We identified musculoskeletal system development, maintenance, and regeneration as important components of gene functions. The beneficial and adverse gene sets may be differently implicated in the development of musculoskeletal-related disability with the beneficial set characterized, e.g., by regulation of chondrocyte proliferation and bone formation, and the adverse set by inflammation and bone loss.

HOPS: a quantitative score reveals pervasive horizontal pleiotropy in human genetic variation is driven by extreme polygenicity of human traits and diseases

Horizontal pleiotropy, where one variant has independent effects on multiple traits, is important for our understanding of the genetic architecture of human phenotypes. We develop a method to quantify horizontal pleiotropy using genome-wide association summary statistics and apply it to 372 heritable phenotypes measured in 361,194 UK Biobank individuals. Horizontal pleiotropy is pervasive throughout the human genome, prominent among highly polygenic phenotypes, and enriched in active regulatory regions. Our results highlight the central role horizontal pleiotropy plays in the genetic architecture of human phenotypes. The HOrizontal Pleiotropy Score (HOPS) method is available on Github at https://github.com/rondolab/HOPS.

A Novel Model to Explain Extreme Feather Pecking Behavior in Laying Hens

Feather pecking (FP) is a serious economic and welfare problem in the domestic fowl. It has recently been shown that the distribution of FP bouts within groups is heterogeneous and contains a sub-population of extreme feather peckers (EFP). The present study proposed a novel model to detect EFP hens. A mixture of two negative binomial distributions was fitted to FP data of a F₂ cross of about 960 hens, and, based on the results, a calculation of the posterior probability for each hen belonging to the EFP subgroup (pEFP) was done. The fit of the mixture distribution revealed that the EFP subgroup made up a proportion of one third of the F₂ cross. The EFP birds came more frequently into pecking mood and showed higher pecking intensities compared to the remaining birds. Tonic immobility and emerge box tests were conducted at juvenile and adult age of the hens to relate fearfulness to EFP. After dichotomization, all traits were analyzed in a multivariate threshold model and a genomewide association study was performed. The new trait pEFP has a medium heritability of 0.35 and is positively correlated with the fear traits. Breeding for this new trait could be an interesting option to reduce the proportion of extreme feather peckers. An index of fear related traits might serve as a proxy to breed indirectly for pEFP. GWAS revealed that all traits are typical quantitative traits with many genes and small effects contributing to the genetic variance.

Causal phenotypic networks for egg traits in an F2 chicken population

Traditional single-trait genetic analyses, such as quantitative trait locus (QTL) and genome-wide association studies (GWAS), have been used to understand genotype-phenotype relationships for egg traits in chickens. Even though these techniques can detect potential genes of major effect, they cannot reveal cryptic causal relationships among QTLs and phenotypes. Thus, to better understand the relationships involving multiple genes and phenotypes of interest, other data analysis techniques must be used. Here, we utilized a QTL-directed dependency graph (QDG) mapping approach for a joint analysis of chicken egg traits, so that functional relationships and potential causal effects between them could be investigated. The QDG mapping identified a total of 17 QTLs affecting 24 egg traits that formed three independent networks of phenotypic trait groups (eggshell color, egg production, and size and weight of egg components), clearly distinguishing direct and indirect effects of QTLs towards correlated traits. For example, the network of size and weight of egg components contained 13 QTLs and 18 traits that are densely connected to each other. This indicates complex relationships between genotype and phenotype involving both direct and indirect effects of QTLs on the studied traits. Most of the QTLs were commonly identified by both the traditional (single-trait) mapping and the QDG approach. The network analysis, however, offers additional insight regarding the source and characterization of pleiotropy affecting egg traits. As such, the QDG analysis provides a substantial step forward, revealing cryptic relationships among QTLs and phenotypes, especially regarding direct and indirect QTL effects as well as potential causal relationships between traits, which can be used, for example, to optimize management practices and breeding strategies for the improvement of the traits.

Dissection of the Genetic Architecture of Rice Tillering using a Genome-wide Association Study

BACKGROUND

Rice tiller number (TN) is one of the most important components associated with rice grain yield. Around one hundred rice TN genes have been identified, but dissecting the genetic architecture of rice TN variations remains difficult because of its complex trait and control by both major genes and quantitative trait loci (QTLs).

RESULTS

In this study, we used a subset of the rice diversity population II (S-RDP-II), genotyped with 700,000 single nucleotide polymorphisms (SNPs), to identify the loci associated with tiller number variations (LATNs) through a genome-wide association study (GWAS). The analysis revealed that 23 LATNs are significantly associated with TN variations. Among the 23 LATNs, eight are co-localized with previously cloned TN genes, and the remaining 15 LATNs are novel. DNA sequence analysis of the 15 novel LATNs led to the identification of five candidate genes using the accessions with extreme TN phenotypes. Genetic variations in two of the genes are mainly located in the promoter regions. qRT-PCR analysis showed that the expression levels of these two genes are also closely associated with TN variations.

CONCLUSIONS

We identified 15 novel LATNs that contribute significantly to the genetic variation of rice TN. Of these 15, the five identified TN-associated candidate genes will enhance our understanding of rice tillering and can be used as molecular markers for improving rice yield.

The Contribution of Low-Frequency and Rare Coding Variation to Susceptibility to Type 2 Diabetes

PURPOSE OF REVIEW

Soon after the first genome-wide association study (GWAS) for type 2 diabetes (T2D) was published, it was hypothesized that rare and low-frequency variants might explain a substantial proportion of disease risk. Rare coding variants in particular were emphasized given their large expected role in disease. This review summarizes the extent to which recent T2D genetic studies provide evidence for or against this hypothesis.

RECENT FINDINGS

Following a comprehensive study of T2D genetic architecture using three sequencing and genotyping technologies, four even larger studies have provided a yet higher resolution view of the role of rare and low-frequency coding variation in T2D susceptibility. Empirical evidence strongly suggests that common regulatory variants are the dominant contributor to T2D heritability. However, rare coding variants may nonetheless be pervasive across T2D-relevant genes. A strategy using common variants to map disease genes, and rare coding variants to link molecular gene perturbations to cellular and phenotypic effects, may be an effective means to investigate T2D pathogenesis and potential new therapies.

Polygenic and sex specific architecture for two maturation traits in farmed Atlantic salmon

BACKGROUND

A key developmental transformation in the life of all vertebrates is the transition to sexual maturity, whereby individuals are capable of reproducing for the first time. In the farming of Atlantic salmon, early maturation prior to harvest size has serious negative production impacts.

RESULTS

We report genome wide association studies (GWAS) using fish measured for sexual maturation in freshwater or the marine environment. Genotypic data from a custom 50 K single nucleotide polymorphism (SNP) array was used to identify 13 significantly associated SNP for freshwater maturation with the most strongly associated on chromosomes 10 and 11. A higher number of associations (48) were detected for marine maturation, and the two peak loci were found to be the same for both traits. The number and broad distribution of GWAS hits confirmed a highly polygenetic nature, and GWAS performed separately within males and females revealed sex specific genetic behaviour for loci co-located with positional candidate genes phosphatidylinositol-binding clathrin assembly protein-like (picalm) and membrane-associated guanylate kinase, WW and PDZ domain-containing protein 2 (magi2).

CONCLUSIONS

The results extend earlier work and have implications for future applied breeding strategies to delay maturation in this important aquaculture species.

Genomic Prediction Using Multi-trait Weighted GBLUP Accounting for Heterogeneous Variances and Covariances Across the Genome

Implicit assumption of common (co)variance for all loci in multi-trait Genomic Best Linear Unbiased Prediction (GBLUP) results in a genomic relationship matrix (G) that is common to all traits. When this assumption is violated, Bayesian whole genome regression methods may be superior to GBLUP by accounting for unequal (co)variance for all loci or genome regions. This study aimed to develop a strategy to improve the accuracy of GBLUP for multi-trait genomic prediction, using (co)variance estimates of SNP effects from Bayesian whole genome regression methods. Five generations (G1-G5, test populations) of genotype data were available by simulations based on data of 2,200 Danish Holstein cows (G0, reference population). Two correlated traits with heritabilities of 0.1 or 0.4, and a genetic correlation of 0.45 were generated. First, SNP effects and breeding values were estimated using BayesAS method, assuming (co)variance was the same for SNPs within a genome region, and different between regions. Region size was set as one SNP, 100 SNPs, a whole chromosome or whole genome. Second, posterior (co)variances of SNP effects were used to weight SNPs in construction of G matrices. In general, region size of 100 SNPs led to highest prediction accuracies using BayesAS, and wGBLUP outperformed GBLUP at this region size. Our results suggest that when genetic architectures of traits favor Bayesian methods, the accuracy of multi-trait GBLUP can be as high as the Bayesian method if SNPs are weighted by the Bayesian posterior (co)variances.

Replication study of GWAS risk loci in Greek multiple sclerosis patients

OBJECTIVES

To validate in an ethnically homogeneous Greek multiple sclerosis (MS) cohort, genetic risk factors for the disease, identified through a number of previous multi-ethnic genome-wide association studies (GWAS).

METHODS

A total of 1228 MS cases and 1014 controls were recruited in the study, from 3 MS centers in Greece. We genotyped 35 susceptibility SNPs that emerged from previous GWAS or meta-analyses of GWAS. Allele and genotype single locus regression analysis, adjusted for gender and site, was performed. Permutation testing was applied to all analyses.

RESULTS

Six polymorphisms reached statistical significance (permutation p value < 0.05). In particular, rs2760524 of LOC105371664, near RGS1 (permutation p value 0.001), rs3129889 of HLA-DRA, near HLA-DRB1 (permutation p value < 1.00e-04), rs1738074 of TAGAP (permutation p value 0.007), rs703842 of METTL1/CYP27B1 (permutation p value 0.008), rs9596270 of DLEU1 (permutation p value < 1.00e-04), and rs17445836 of LincRNA, near IRF8 (permutation p value 0.001) were identified as susceptibility risk factors in our group.

CONCLUSION

The current study replicated a number of GWAS susceptibility SNPs, which implies that some similarities between the examined Greek population and the MS genetic architecture of the GWAS populations do exist.

A longitudinal quantitative trait locus mapping of chicken growth traits

Since the growth traits of chickens are largely related to the production of meat and eggs, it is definitely important to understand genetic basis of growth traits. Although many quantitative trait loci (QTLs) that affect growth traits have recently been reported in chickens, little is known about genetic architecture of growth traits across all growth stages. Therefore, we conducted a longitudinal QTL study of growth traits measured from 0 to 64 weeks of age using 134 microsatellite DNA markers on 26 autosomes from 406 F₂ females, which resulted from an intercross of Oh-Shamo and White Leghorn chicken breeds. We found 27 and 21 independent main-effect QTLs for body weight and shank length, respectively. Moreover, 15 and 4 pairs of epistatic QTLs were found for body weight and shank length, respectively. Taken together, the present study revealed 48 QTLs for growth traits on 21 different autosomes, and these loci clearly have age-specific effects on phenotypes throughout stages that are important for meat and egg productions. Approximately 60% of Oh-Shamo-derived alleles increased the phenotypic values, corresponding to the fact that Oh-Shamo traits were higher than those of White Leghorn. On the other hand, remaining Oh-Shamo alleles decreased the phenotypic values. Our results clearly indicated that the growth traits of chickens are regulated by several main and epistatic QTLs that are widely distributed in the chicken genome, and that the QTLs have age-dependent manners of controlling the traits. This study implies importance of not only cross-sectional but also longitudinal growth data for further understanding of the complex genetic architecture in animal.

Phage spanins: diversity, topological dynamics and gene convergence

BACKGROUND

Spanins are phage lysis proteins required to disrupt the outer membrane. Phages employ either two-component spanins or unimolecular spanins in this final step of Gram-negative host lysis. Two-component spanins like Rz-Rz1 from phage lambda consist of an integral inner membrane protein: i-spanin, and an outer membrane lipoprotein: o-spanin, that form a complex spanning the periplasm. Two-component spanins exist in three different genetic architectures; embedded, overlapped and separated. In contrast, the unimolecular spanins, like gp11 from phage T1, have an N-terminal lipoylation signal sequence and a C-terminal transmembrane domain to account for the topology requirements. Our proposed model for spanin function, for both spanin types, follows a common theme of the outer membrane getting fused with the inner membrane, effecting the release of progeny virions.

RESULTS

Here we present a SpaninDataBase which consists of 528 two-component spanins and 58 unimolecular spanins identified in this analysis. Primary analysis revealed significant differences in the secondary structure predictions for the periplasmic domains of the two-component and unimolecular spanin types, as well as within the three different genetic architectures of the two-component spanins. Using a threshold of 40% sequence identity over 40% sequence length, we were able to group the spanins into 143 i-spanin, 125 o-spanin and 13 u-spanin families. More than 40% of these families from each type were singletons, underlining the extreme diversity of this class of lysis proteins. Multiple sequence alignments of periplasmic domains demonstrated conserved secondary structure patterns and domain organization within family members. Furthermore, analysis of families with members from different architecture allowed us to interpret the evolutionary dynamics of spanin gene arrangement. Also, the potential universal role of intermolecular disulfide bonds in two-component spanin function was substantiated through bioinformatic and genetic approaches. Additionally, a novel lipobox motif, AWAC, was identified and experimentally verified.

CONCLUSIONS

The findings from this bioinformatic approach gave us instructive insights into spanin function, evolution, domain organization and provide a platform for future spanin annotation, as well as biochemical and genetic experiments. They also establish that spanins, like viral membrane fusion proteins, adopt different strategies to achieve fusion of the inner and outer membranes.

Association analysis of drought tolerance in cut chrysanthemum (Chrysanthemum morifolium Ramat.) at seedling stage

Understanding the genetic architecture is a prerequisite for crop improvement. The current research aimed to characterize the extent of genetic variation of drought tolerance harbored in a global collection of 159 chrysanthemum cultivars over 2 years. An average subordinate function value (ASFV), integrating the wilting index, the fresh weight retention rate, and the survival rate after re-watering under two drought-stressed trials, was used to quantify the level of drought tolerance. The performance of ASFV was generally correlated between the 2 years; and a high magnitude (0.95) of broad-sense heritability, coupled with the moderate genetic advance, was estimated for the ASFV. By applying MLM model with both population structure and kinship matrix as covariates association mapping identified 16 markers linked to drought tolerance, with the proportion of the phenotypic variation explained by an individual marker ranging from 4.4 to 7.6%. Of the eight markers predictive across the 2 years, four (E11M24-9, E3M2-8, E1M5-5, and EST-SSR34-3) were identified as favorable alleles for drought tolerance. Several cultivars that carry at least three of the four favorable alleles were identified as potential donor parents for future improvement of the drought tolerance. The findings provide an insight into the genetic basis of the drought tolerance in chrysanthemum and will, therefore, aid in developing new cultivars with enhanced tolerance against drought stress.

Genetic background effects in quantitative genetics: gene-by-system interactions

Proper cell function depends on networks of proteins that interact physically and functionally to carry out physiological processes. Thus, it seems logical that the impact of sequence variation in one protein could be significantly influenced by genetic variants at other loci in a genome. Nonetheless, the importance of such genetic interactions, known as epistasis, in explaining phenotypic variation remains a matter of debate in genetics. Recent work from our lab revealed that genes implicated from an association study of toxin tolerance in Saccharomyces cerevisiae show extensive interactions with the genetic background: most implicated genes, regardless of allele, are important for toxin tolerance in only one of two tested strains. The prevalence of background effects in our study adds to other reports of widespread genetic-background interactions in model organisms. We suggest that these effects represent many-way interactions with myriad features of the cellular system that vary across classes of individuals. Such gene-by-system interactions may influence diverse traits and require new modeling approaches to accurately represent genotype-phenotype relationships across individuals.

Evolution of sex-specific pace-of-life syndromes: genetic architecture and physiological mechanisms

Sex differences in life history, physiology, and behavior are nearly ubiquitous across taxa, owing to sex-specific selection that arises from different reproductive strategies of the sexes. The pace-of-life syndrome (POLS) hypothesis predicts that most variation in such traits among individuals, populations, and species falls along a slow-fast pace-of-life continuum. As a result of their different reproductive roles and environment, the sexes also commonly differ in pace-of-life, with important consequences for the evolution of POLS. Here, we outline mechanisms for how males and females can evolve differences in POLS traits and in how such traits can covary differently despite constraints resulting from a shared genome. We review the current knowledge of the genetic basis of POLS traits and suggest candidate genes and pathways for future studies. Pleiotropic effects may govern many of the genetic correlations, but little is still known about the mechanisms involved in trade-offs between current and future reproduction and their integration with behavioral variation. We highlight the importance of metabolic and hormonal pathways in mediating sex differences in POLS traits; however, there is still a shortage of studies that test for sex specificity in molecular effects and their evolutionary causes. Considering whether and how sexual dimorphism evolves in POLS traits provides a more holistic framework to understand how behavioral variation is integrated with life histories and physiology, and we call for studies that focus on examining the sex-specific genetic architecture of this integration.

Polygenic risk score of sporadic late-onset Alzheimer's disease reveals a shared architecture with the familial and early-onset forms

OBJECTIVE

To determine whether the extent of overlap of the genetic architecture among the sporadic late-onset Alzheimer's Disease (sLOAD), familial late-onset AD (fLOAD), sporadic early-onset AD (sEOAD), and autosomal dominant early-onset AD (eADAD).

METHODS

Polygenic risk scores (PRSs) were constructed using previously identified 21 genome-wide significant loci for LOAD risk.

RESULTS

We found that there is an overlap in the genetic architecture among sEOAD, fLOAD, and sLOAD. The highest association of the PRS and risk (odds ratio [OR] = 2.27; P = 1.29 × 10-7) was observed in sEOAD, followed by fLOAD (OR = 1.75; P = 1.12 × 10-7) and sLOAD (OR = 1.40; P = 1.21 × 10-3). The PRS was associated with cerebrospinal fluid ptau181-Aβ42 on eADAD (P = 4.36 × 10-2).

CONCLUSION

Our analysis confirms that the genetic factors identified for LOAD modulate risk in sLOAD and fLOAD and also sEOAD cohorts. Specifically, our results suggest that the burden of these risk variants is associated with familial clustering and earlier onset of AD. Although these variants are not associated with risk in the eADAD, they may be modulating age at onset.

Genome-wide association mapping of QTL underlying seed oil and protein contents of a diverse panel of soybean accessions

To investigate the genetic basis of variation in oil and protein contents in soybean seeds, a diverse collection of 421 mainly Chinese soybean cultivars was genotyped using 1536 SNPs, mostly from candidate genes related to acyl-lipid metabolism and from regions harboring known QTL. Six significant associations were identified for each of seed oil and protein contents which individually explained 2.7-5.9% of the phenotypic variance. Six associations occurred in or near known QTL and the remaining are putative novel QTL. Ten significant associations influenced the oil content without decreasing protein content, and vice versa. One SNP was pleiotropic, with opposite effects on oil and protein contents. The genetic region covering Map-6076 and-6077 was shown to be involved in controlling oil content in soybean by integrating the results of association mapping with information on known QTL and tissue-specific expression data. This region was subject to strong selection during the genetic improvement of soybean. Our results not only confirm and refine the map positions of known QTL but also contribute to a further elucidation of the genetic architecture of protein and oil contents in soybean seeds by identifying new associations exhibiting pleiotropic effects on seed protein and oil contents.

Common functional variants of the glutamatergic system in Autism spectrum disorder with high and low intellectual abilities

The genetic architecture underlying Autism spectrum disorder (ASD) has been suggested to differ between individuals with lower (IQ ≤ 70; LIQ) and higher intellectual abilities (IQ > 70; HIQ). Among the identified pathomechanisms, the glutamatergic signalling pathway is of specific interest in ASD. We investigated 187 common functional variants of this neurotransmitter system for association with ASD and with symptom severity in two independent samples, a German (German-ALL: N = 583 families) and the Autism Genome Project cohort (AGP-ALL: N = 2001 families), split into HIQ, and LIQ subgroups. We did not identify any association withstanding correction for multiple testing. However, we report a replicated nominal significant under-transmission (OR < 0.79, p < 0.04) of the AKAP13 rs745191-T allele in both LIQ cohorts, but not in the much larger HIQ cohorts. At the phenotypic level, we nominally replicated associations of CAMK2A-rs2241694 with non-verbal communication in both combined LIQ and HIQ ASD cohorts. Variants PLD1-rs2124147 and ADCY1-rs2461127 were nominally associated with impaired non-verbal abilities and AKAP2-rs3739456 with repetitive behaviour in both LIQ cohorts. All four LIQ-associated genes are involved in G-protein coupled signal transduction, a downstream pathway of metabotropic glutamate receptor activation. We conclude that functional common variants of glutamatergic genes do not have a strong impact on ASD, but seem to moderately affect ASD risk and phenotypic expression. Since most of our nominally replicated hits were identified in the LIQ cohort, further investigation of the glutamatergic system in this subpopulation might be warranted.

Natural Variation and Genetics of Photoperiodism in Wyeomyia smithii

Seasonal change in the temperate and polar regions of Earth determines how the world looks around us and, in fact, how we live our day-to-day lives. For biological organisms, seasonal change typically involves complex physiological and metabolic reorganization, the majority of which is regulated by photoperiodism. Photoperiodism is the ability of animals and plants to use day length or night length, resulting in life-historical transformations, including seasonal development, migration, reproduction, and dormancy. Seasonal timing determines not only survival and reproductive success but also the structure and organization of complex communities and, ultimately, the biomes of Earth. Herein, a small mosquito, Wyeomyia smithii, that lives only in the water-filled leaves of a carnivorous plant over a wide geographic range, is used to explore the genetic and evolutionary basis of photoperiodism. Photoperiodism in W. smithii is considered in the context of its historical biogeography in nature to examine the startling finding that recent rapid climate change can drive genetic change in plants and animals at break-neck speed, and to challenge the ponderous 80+ year search for connections between daily and seasonal time-keeping mechanisms. Finally, a model is proposed that reconciles the seemingly disparate 24-h daily clock driven by the invariant rotation of Earth about its axis with the evolutionarily flexible seasonal timer orchestrated by variable seasonality driven by the rotation of Earth about the Sun.

Identification of putative markers linked to grain plumpness in rice (Oryza sativa L.) via association mapping

BACKGROUND

Poor grain plumpness (GP) is one of the main constraints to reaching the yield potential of hybrid rice.

RESULTS

In this study, the GP of 177 rice varieties was investigated in three locations across 2 years. By combining the genotype data of 261 simple sequence repeat (SSR) markers, association mapping was conducted to identify the marker-GP association loci. Among 31 marker-GP association loci detected in two or more environments and determined using general linear model (GLM) analyses, seven association loci were also detected using mixed linear model (MLM) analyses. The seven common loci detected by the two analytical methods were located on chromosomes 2, 3 (2), 7, 8 and 12 (2) and explained 7.24~22.28% of the variance. Of these 7 association loci, five markers linked to GP were newly detected: RM5340 on Chr2, RM5480 and RM148 on Chr3, RM1235 on Chr8, and RM5479 on Chr12.

CONCLUSIONS

Five marker-GP association loci were newly detected using both the GLM and MLM analytical methods. Elite allele RM505-170 bp had the highest average phenotypic effect on increasing the GP, and the typical carrier variety was 'Maozitou'. Based on the distribution of the elite alleles among the carrier varieties, the top 10 parental combinations for improving the GP in rice via cross-breeding were predicted.

Genetic architecture and temporal patterns of biomass accumulation in spring barley revealed by image analysis

BACKGROUND

Genetic mapping of phenotypic traits generally focuses on a single time point, but biomass accumulates continuously during plant development. Resolution of the temporal dynamics that affect biomass recently became feasible using non-destructive imaging.

RESULTS

With the aim to identify key genetic factors for vegetative biomass formation from the seedling stage to flowering, we explored growth over time in a diverse collection of two-rowed spring barley accessions. High heritabilities facilitated the temporal analysis of trait relationships and identification of quantitative trait loci (QTL). Biomass QTL tended to persist only a short period during early growth. More persistent QTL were detected around the booting stage. We identified seven major biomass QTL, which together explain 55% of the genetic variance at the seedling stage, and 43% at the booting stage. Three biomass QTL co-located with genes or QTL involved in phenology. The most important locus for biomass was independent from phenology and is located on chromosome 7HL at 141 cM. This locus explained ~20% of the genetic variance, was significant over a long period of time and co-located with HvDIM, a gene involved in brassinosteroid synthesis.

CONCLUSIONS

Biomass is a dynamic trait and is therefore orchestrated by different QTL during early and late growth stages. Marker-assisted selection for high biomass at booting stage is most effective by also including favorable alleles from seedling biomass QTL. Selection for dynamic QTL may enhance genetic gain for complex traits such as biomass or, in the future, even grain yield.

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds

Background

A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of “Gene Ontology” (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability.

Results

Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020).

Conclusions

Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of independent biological knowledge.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4004-z) contains supplementary material, which is available to authorized users.

Strong epistatic and additive effects of linked candidate SNPs for Drosophila pigmentation have implications for analysis of genome-wide association studies results

Background

The mapping resolution of genome-wide association studies (GWAS) is limited by historic recombination events and effects are often assigned to haplotype blocks rather than individual SNPs. It is not clear how many of the SNPs in the block, and which ones, are causative. Drosophila pigmentation is a powerful model to dissect the genetic basis of intra-specific and inter-specific phenotypic variation. Three tightly linked SNPs in the t-MSE enhancer have been identified in three D. melanogaster populations as major contributors to female abdominal pigmentation. This enhancer controls the expression of the pigmentation gene tan (t) in the abdominal epidermis. Two of the three SNPs were confirmed in an independent study using the D. melanogaster Genetic Reference Panel established from a North American population.

Results

We determined the functional impact of SNP1, SNP2, and SNP3 using transgenic lines to test all possible haplotypes in vivo. We show that all three candidate SNPs contribute to female Drosophila abdominal pigmentation. Interestingly, only two SNPs agree with the effect predicted by GWAS; the third one goes in the opposite direction because of linkage disequilibrium between multiple functional SNPs. Our experimental design uncovered strong additive effects for the three SNPs, but we also found significant epistatic effects explaining up to 11% of the total variation.

Conclusions

Our results suggest that linked causal variants are important for the interpretation of GWAS and functional validation is needed to understand the genetic architecture of traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1262-7) contains supplementary material, which is available to authorized users.