A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana

Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance explains the insignificant narrow-sense and significant broad-sense heritability by using a combination of careful statistical epistatic analyses and functional genetic experiments.     

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.     

The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance

Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or “missing heritability”. Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.     

Diverse phosphate and auxin transport loci distinguish phosphate tolerant from sensitive Arabidopsis accessions

Phosphorus (P) is an essential element for plant growth often limiting agroecosystems. To identify genetic determinants of performance under variable phosphate (Pi) supply, we conducted genome-wide association studies on five highly predictive Pi starvation response traits in 200 Arabidopsis (Arabidopsis thaliana) accessions. Pi concentration in Pi-limited organs had the strongest, and primary root length had the weakest genetic component. Of 70 trait-associated candidate genes, 17 responded to Pi withdrawal. The PHOSPHATE TRANSPORTER1 gene cluster on chromosome 5 comprises PHT1;1, PHT1;2, and PHT1;3 with known impact on P status. A second locus featured uncharacterized endomembrane-associated auxin efflux carrier encoding PIN-LIKES7 (PILS7) which was more strongly suppressed in Pi-limited roots of Pi-starvation sensitive accessions. In the Col-0 background, Pi uptake and organ growth were impaired in both Pi-limited pht1;1 and two pils7 T-DNA insertion mutants, while Pi -limited pht1;2 had higher biomass and pht1;3 was indistinguishable from wild-type. Copy number variation at the PHT1 locus with loss of the PHT1;3 gene and smaller scale deletions in PHT1;1 and PHT1;2 predicted to alter both protein structure and function suggest diversification of PHT1 is a key driver for adaptation to P limitation. Haplogroup analysis revealed a phosphorylation site in the protein encoded by the PILS7 allele from stress-sensitive accessions as well as additional auxin-responsive elements in the promoter of the “stress tolerant” allele. The former allele’s inability to complement the pils7-1 mutant in the Col-0 background implies the presence of a kinase signaling loop controlling PILS7 activity in accessions from P-rich environments, while survival in P-poor environments requires fine-tuning of stress-responsive root auxin signaling.

A series of insertion/deletion nucleotide polymorphisms at PHOSPHATE TRANSPORTER1 and PIN-LIKES7 loci confer natural variation in low phosphate tolerance in 200 Arabidopsis accessions.     

Genome-wide association study reveals the genetic architecture of 27 agronomic traits in tomato

Tomato (Solanum lycopersicum) is a highly valuable fruit crop, and yield is one of the most important agronomic traits. However, the genetic architecture underlying tomato yield-related traits has not been fully addressed. Based on ∼4.4 million single nucleotide polymorphisms obtained from 605 diverse accessions, we performed a comprehensive genome-wide association study for 27 agronomic traits in tomato. A total of 239 significant associations corresponding to 129 loci, harboring many previously reported and additional genes related to vegetative and reproductive development, were identified, and these loci explained an average of ∼8.8% of the phenotypic variance. A total of 51 loci associated with 25 traits have been under selection during tomato domestication and improvement. Furthermore, a candidate gene, Sl-ACTIVATED MALATE TRANSPORTER15, that encodes an aluminum-activated malate transporter was functionally characterized and shown to act as a pivotal regulator of leaf stomata formation, thereby affecting photosynthesis and drought resistance. This study provides valuable information for tomato genetic research and breeding.

A large-scale genome-wide association study sheds light on genetic and genomic bases underlying important yield-related traits in tomato.     

Genetic Variation for Life History Sensitivity to Seasonal Warming in Arabidopsis thaliana

Climate change has altered life history events in many plant species; however, little is known about genetic variation underlying seasonal thermal response. In this study, we simulated current and three future warming climates and measured flowering time across a globally diverse set of Arabidopsis thaliana accessions. We found that increased diurnal and seasonal temperature (1°–3°) decreased flowering time in two fall cohorts. The early fall cohort was unique in that both rapid cycling and overwintering life history strategies were revealed; the proportion of rapid cycling plants increased by 3–7% for each 1° temperature increase. We performed genome-wide association studies (GWAS) to identify the underlying genetic basis of thermal sensitivity. GWAS identified five main-effect quantitative trait loci (QTL) controlling flowering time and another five QTL with thermal sensitivity. Candidate genes include known flowering loci; a cochaperone that interacts with heat-shock protein 90; and a flowering hormone, gibberellic acid, a biosynthetic enzyme. The identified genetic architecture allowed accurate prediction of flowering phenotypes (R² > 0.95) that has application for genomic selection of adaptive genotypes for future environments. This work may serve as a reference for breeding and conservation genetic studies under changing environments.     

Genomic insight into the developmental history of southern highbush blueberry populations

Interspecific hybridization is a common breeding approach for introducing novel traits and genetic diversity to breeding populations. Southern highbush blueberry (SHB) is a blueberry cultivar group that has been intensively bred over the last 60 years. Specifically, it was developed by multiple interspecific crosses between northern highbush blueberry [NHB, Vaccinium corymbosum L. (2n = 4x = 48)] and low-chill Vaccinium species to expand the geographic limits of highbush blueberry production. In this study, we genotyped polyploid blueberries, including 105 SHB, 17 NHB, and 10 rabbiteye blueberry (RE) (Vaccinium virgatum Aiton), from the accessions planted at Poplarville, Mississippi, and accessions distributed in Japan, based on the double-digest restriction site-associated DNA sequencing. The genome-wide SNP data clearly indicated that RE cultivars were genetically distinct from SHB and NHB cultivars, whereas NHB and SHB were genetically indistinguishable. The population structure results appeared to reflect the differences in the allele selection strategies that breeders used for developing germplasm adapted to local climates. The genotype data implied that there are no or very few genomic segments that were commonly introgressed from low-chill Vaccinium species to the SHB genome. Principal component analysis-based outlier detection analysis found a few loci associated with a variable that could partially differentiate NHB and SHB. These SNP loci were detected in Mb-scale haplotype blocks and may be close to the functional genes related to SHB development. Collectively, the data generated in this study suggest a polygenic adaptation of SHB to the southern climate, and may be relevant for future population-scale genome-wide analyses of blueberry.Subject terms: Agricultural genetics, Plant breeding     

Detection of favorable alleles for yield and yield components by association mapping in upland cotton

Association mapping based on linkage disequilibrium provides a promising tool for dissecting the genetic basis underlying complex traits. To reveal the genetic variations of yield and yield components traits in upland cotton, 403 upland cotton accessions were collected and analyzed by 560 genome-wide simple sequence repeats (SSRs). A diverse panel consisting of 403 upland cotton accessions was grown in six different environments, and the yield and yield component traits were measured, and 560 SSR markers covering the whole genome were mapped. Association studies were performed to uncover the genotypic and phenotypic variations using a mixed linear model. Favorable alleles and typical accessions for yield traits were identified. A total of 201 markers were polymorphic, revealing 394 alleles. The average gene diversity and polymorphism information content were 0.556 and 0.483, respectively. Based on a population structure analysis, 403 accessions were divided into two subgroups. A mixed linear model analysis of the association mapping detected 43 marker loci according to the best linear unbiased prediction and in at least three of the six environments(??lgP?>?1.30, P?<?0.05). Among the 43 associated markers, five were associated with more than two traits simultaneously and nine were coincident with those identified previously. Based on phenotypic effects, favorable alleles and typical accessions that contained the elite allele loci related to yield traits were identified and are widely used in practical breeding. This study detected favorable quantitative trait loci’s alleles and typical accessions for yield traits, these are excellent genetic resources for future high-yield breeding by marker-assisted selection in upland cotton in China.     

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis‐regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low‐frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis‐regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic‐acid pathway to local adaptation.     

Genetic Architecture of Natural Variation of Telomere Length in Arabidopsis thaliana

Telomeres represent the repetitive sequences that cap chromosome ends and are essential for their protection. Telomere length is known to be highly heritable and is derived from a homeostatic balance between telomeric lengthening and shortening activities. Specific loci that form the genetic framework underlying telomere length homeostasis, however, are not well understood. To investigate the extent of natural variation of telomere length in Arabidopsis thaliana, we examined 229 worldwide accessions by terminal restriction fragment analysis. The results showed a wide range of telomere lengths that are specific to individual accessions. To identify loci that are responsible for this variation, we adopted a quantitative trait loci (QTL) mapping approach with multiple recombinant inbred line (RIL) populations. A doubled haploid RIL population was first produced using centromere-mediated genome elimination between accessions with long (Pro-0) and intermediate (Col-0) telomere lengths. Composite interval mapping analysis of this population along with two established RIL populations (Ler-2/Cvi-0 and Est-1/Col-0) revealed a number of shared and unique QTL. QTL detected in the Ler-2/Cvi-0 population were examined using near isogenic lines that confirmed causative regions on chromosomes 1 and 2. In conclusion, this work describes the extent of natural variation of telomere length in A. thaliana, identifies a network of QTL that influence telomere length homeostasis, examines telomere length dynamics in plants with hybrid backgrounds, and shows the effects of two identified regions on telomere length regulation.     

Reciprocal adaptation of rice and Xanthomonas oryzae pv. oryzae: cross-species 2D GWAS reveals the underlying genetics

A 1D/2D genome-wide association study strategy was adopted to investigate the genetic systems underlying the reciprocal adaptation of rice (Oryza sativa) and its bacterial pathogen, Xanthomonas oryzae pv. oryzae (Xoo) using the whole-genome sequencing and large-scale phenotyping data of 701 rice accessions and 23 diverse Xoo strains. Forty-seven Xoo virulence-related genes and 318 rice quantitative resistance genes (QR-genes) mainly located in 41 genomic regions, and genome-wide interactions between the detected virulence-related genes and QR genes were identified, including well-known resistance genes/virulence genes plus many previously uncharacterized ones. The relationship between rice and Xoo was characterized by strong differentiation among Xoo races corresponding to the subspecific differentiation of rice, by strong shifts toward increased resistance/virulence of rice/Xoo populations and by rich genetic diversity at the detected rice QR-genes and Xoo virulence genes, and by genome-wide interactions between many rice QR-genes and Xoo virulence genes in a multiple-to-multiple manner, presumably resulting either from direct protein–protein interactions or from genetic epistasis. The observed complex genetic interaction system between rice and Xoo likely exists in other crop–pathogen systems that would maintain high levels of diversity at their QR-loci/virulence-loci, resulting in dynamic coevolutionary consequences during their reciprocal adaptation.

A complex system of genetic interactions leads to reciprocal adaptation between rice and its bacterial pathogen, Xanthomonas oryzae pv. oryzae.     

Genome-wide association mapping in Arabidopsis identifies previously known flowering time and pathogen resistance genes

There is currently tremendous interest in the possibility of using genome-wide association mapping to identify genes responsible for natural variation, particularly for human disease susceptibility. The model plant Arabidopsis thaliana is in many ways an ideal candidate for such studies, because it is a highly selfing hermaphrodite. As a result, the species largely exists as a collection of naturally occurring inbred lines, or accessions, which can be genotyped once and phenotyped repeatedly. Furthermore, linkage disequilibrium in such a species will be much more extensive than in a comparable outcrossing species. We tested the feasibility of genome-wide association mapping in A. thaliana by searching for associations with flowering time and pathogen resistance in a sample of 95 accessions for which genome-wide polymorphism data were available. In spite of an extremely high rate of false positives due to population structure, we were able to identify known major genes for all phenotypes tested, thus demonstrating the potential of genome-wide association mapping in A. thaliana and other species with similar patterns of variation. The rate of false positives differed strongly between traits, with more clinal traits showing the highest rate. However, the false positive rates were always substantial regardless of the trait, highlighting the necessity of an appropriate genomic control in association studies.     

"Missing" G x E Variation Controls Flowering Time in Arabidopsis thaliana

Understanding how genetic variation interacts with the environment is essential for understanding adaptation. In particular, the life cycle of plants is tightly coordinated with local environmental signals through complex interactions with the genetic variation (G x E). The mechanistic basis for G x E is almost completely unknown. We collected flowering time data for 173 natural inbred lines of Arabidopsis thaliana from Sweden under two growth temperatures (10°C and 16°C), and observed massive G x E variation. To identify the genetic polymorphisms underlying this variation, we conducted genome-wide scans using both SNPs and local variance components. The SNP-based scan identified several variants that had common effects in both environments, but found no trace of G x E effects, whereas the scan using local variance components found both. Furthermore, the G x E effects appears to be concentrated in a small fraction of the genome (0.5%). Our conclusion is that G x E effects in this study are mostly due to large numbers of allele or haplotypes at a small number of loci, many of which correspond to previously identified flowering time genes.     

Rapid microevolution during recent range expansion to harsh environments

Background

Adaptive evolution is one of the crucial mechanisms for organisms to survive and thrive in new environments. Recent studies suggest that adaptive evolution could rapidly occur in species to respond to novel environments or environmental challenges during range expansion. However, for environmental adaptation, many studies successfully detected phenotypic features associated with local environments, but did not provide ample genetic evidence on microevolutionary dynamics. It is therefore crucial to thoroughly investigate the genetic basis of rapid microevolution in response to environmental changes, in particular on what genes and associated variation are responsible for environmental challenges. Here, we genotyped genome-wide gene-associated microsatellites to detect genetic signatures of rapid microevolution of a marine tunicate invader, Ciona robusta, during recent range expansion to the harsh environment in the Red Sea.

Results

The Red Sea population was significantly differentiated from the other global populations. The genome-wide scan, as well as multiple analytical methods, successfully identified a set of adaptive genes. Interestingly, the allele frequency largely varied at several adaptive loci in the Red Sea population, and we found significant correlations between allele frequency and local environmental factors at these adaptive loci. Furthermore, a set of genes were annotated to get involved in local temperature and salinity adaptation, and the identified adaptive genes may largely contribute to the invasion success to harsh environments.

Conclusions

All the evidence obtained in this study clearly showed that environment-driven selection had left detectable signatures in the genome of Ciona robusta within a few generations. Such a rapid microevolutionary process is largely responsible for the harsh environmental adaptation and therefore contributes to invasion success in different aquatic ecosystems with largely varied environmental factors.

     

Genome-wide association study of relative telomere length

Telomere function is essential to maintaining the physical integrity of linear chromosomes and healthy human aging. The probability of forming proper telomere structures depends on the length of the telomeric DNA tract. We attempted to identify common genetic variants associated with log relative telomere length using genome-wide genotyping data on 3,554 individuals from the Nurses'' Health Study and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial that took part in the National Cancer Institute Cancer Genetic Markers of Susceptibility initiative for breast and prostate cancer. After genotyping 64 independent SNPs selected for replication in additional Nurses'' Health Study and Women''s Genome Health Study participants, we did not identify genome-wide significant loci; however, we replicated the inverse association of log relative telomere length with the minor allele variant [C] of rs16847897 at the TERC locus (per allele β = −0.03, P = 0.003) identified by a previous genome-wide association study. We did not find evidence for an association with variants at the OBFC1 locus or other loci reported to be associated with telomere length. With this sample size we had >80% power to detect β estimates as small as ±0.10 for SNPs with minor allele frequencies of ≥0.15 at genome-wide significance. However, power is greatly reduced for β estimates smaller than ±0.10, such as those for variants at the TERC locus. In general, common genetic variants associated with telomere length homeostasis have been difficult to detect. Potential biological and technical issues are discussed.     

A Scale-Corrected Comparison of Linkage Disequilibrium Levels between Genic and Non-Genic Regions

The understanding of non-random association between loci, termed linkage disequilibrium (LD), plays a central role in genomic research. Since causal mutations are generally not included in genomic marker data, LD between those and available markers is essential for capturing the effects of causal loci on localizing genes responsible for traits. Thus, the interpretation of association studies requires a detailed knowledge of LD patterns. It is well known that most LD measures depend on minor allele frequencies (MAF) of the considered loci and the magnitude of LD is influenced by the physical distances between loci. In the present study, a procedure to compare the LD structure between genomic regions comprising several markers each is suggested. The approach accounts for different scaling factors, namely the distribution of MAF, the distribution of pair-wise differences in MAF, and the physical extent of compared regions, reflected by the distribution of pair-wise physical distances. In the first step, genomic regions are matched based on similarity in these scaling factors. In the second step, chromosome- and genome-wide significance tests for differences in medians of LD measures in each pair are performed. The proposed framework was applied to test the hypothesis that the average LD is different in genic and non-genic regions. This was tested with a genome-wide approach with data sets for humans (Homo sapiens), a highly selected chicken line (Gallus gallus domesticus) and the model plant Arabidopsis thaliana. In all three data sets we found a significantly higher level of LD in genic regions compared to non-genic regions. About 31% more LD was detected genome-wide in genic compared to non-genic regions in Arabidopsis thaliana, followed by 13.6% in human and 6% chicken. Chromosome-wide comparison discovered significant differences on all 5 chromosomes in Arabidopsis thaliana and on one third of the human and of the chicken chromosomes.     

Genome-Wide Association Analyses for Fatty Acid Composition in Porcine Muscle and Abdominal Fat Tissues

Fatty acid composition is an important phenotypic trait in pigs as it affects nutritional, technical and sensory quality of pork. Here, we reported a genome-wide association study (GWAS) for fatty acid composition in the longissimus muscle and abdominal fat tissues of 591 White Duroc×Erhualian F₂ animals and in muscle samples of 282 Chinese Sutai pigs. A total of 46 loci surpassing the suggestive significance level were identified on 15 pig chromosomes (SSC) for 12 fatty acids, revealing the complex genetic architecture of fatty acid composition in pigs. Of the 46 loci, 15 on SSC5, 7, 14 and 16 reached the genome-wide significance level. The two most significant SNPs were ss131535508 (P = 2.48×10⁻²⁵) at 41.39 Mb on SSC16 for C20∶0 in abdominal fat and ss478935891 (P = 3.29×10⁻¹³) at 121.31 Mb on SSC14 for muscle C18∶0. A meta-analysis of GWAS identified 4 novel loci and enhanced the association strength at 6 loci compared to those evidenced in a single population, suggesting the presence of common underlying variants. The longissimus muscle and abdominal fat showed consistent association profiles at most of the identified loci and distinct association signals at several loci. All loci have specific effects on fatty acid composition, except for two loci on SSC4 and SSC7 affecting multiple fatness traits. Several promising candidate genes were found in the neighboring regions of the lead SNPs at the genome-wide significant loci, such as SCD for C18∶0 and C16∶1 on SSC14 and ELOVL7 for C20∶0 on SSC16. The findings provide insights into the molecular basis of fatty acid composition in pigs, and would benefit the final identification of the underlying mutations.