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214 results for “Quantitative traits”
Quantitative trait locus mapping reveals an independent genetic basis for joint divergence in leaf function, life-history, and floral traits between scarlet monkeyflower (Mimulus cardinalis) populations
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Data from: Genome-wide search for quantitative trait loci controlling important plant and flower traits in petunia using an interspecific recombinant inbred population of Petunia axillaris and Petunia exserta
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Seaweed functional diversity revisited: confronting traditional groups with quantitative traits
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Data from: Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population
<p><span><span><b>Background</b>: Human demand for wheat will continue to increase together with the continuous global population growth. Agronomic traits in wheat are susceptible to environmental conditions. Therefore, in breeding practice, priority is given to QTLs of agronomic traits that can be stably detected across multiple environments and over many years.</span></span></p> <p><span><span><b>Results: </b>In this study, QTL analysis was conducted for eight agronomic traits using an introgression line population across eight environments (drought stressed and well-watered) for five years. In total, 44 additive QTLs for the above agronomic traits were detected on 15 chromosomes. Among these, <i>qPH-6A</i>, <i>qHD-1A</i>, <i>qSL-2A</i>, <i>qHD-2D</i> and<i> qSL-6A</i> were detected across seven, six, five, five and four environments, respectively. The means in the phenotypic variation explained by these five QTLs were 12.26%, 9.51%, 7.77%, 7.23%, and 8.49%, respectively. </span></span></p> <p><b>Conclusions: </b>We identified five stable QTLs, which includes <i>qPH-6A</i>, <i>qHD-1A</i>, <i>qSL-2A</i>, <i>qHD-2D</i> and<i> qSL-6A</i>. They play a critical role in wheat agronomic traits. One of the dwarf genes<i> Rht14</i>, <i>Rht16</i>, <i>Rht18</i> and <i>Rht25</i> on chromosome 6A might be the candidate gene for <i>qPH-6A</i>. The <i>qHD-1A</i> and <i>qHD-2D</i> were novel stable QTLs for heading date and they differed from known vernalization genes, photoperiod genes and earliness per se genes.</p>
Dataset - A complex network of additive and epistatic quantitative trait loci underlies natural variation of Arabidopsis thaliana quantitative disease resistance to Ralstonia solanacearum under heat stress
<p>Plant immunity is often negatively impacted by heat stress. However, the underlying molecular mechanisms remain poorly characterized. Based on a genome-wide association mapping approach, this study aims to identify in <em>Arabidopsis thaliana</em> the genetic bases of robust resistance mechanisms to the devastating pathogen<em> Ralstonia solanacearum</em> under heat stress. A local mapping population was phenotyped against the <em>R. solanacearum</em> GMI1000 strain at 27 and 30 °C. To obtain a precise description of the genetic architecture underlying natural variation of quantitative disease resistance (QDR), we applied a genome-wide local score analysis. Alongside an extensive genetic variation found in this local population at both temperatures, we observed a playful dynamics of quantitative trait loci along the infection stages. In addition, a complex genetic network of interacting loci could be detected at 30 °C. As a first step to investigate the underlying molecular mechanisms, the atypical meiotic cyclin <em>SOLO DANCERS</em> gene was validated by a reverse genetic approach as involved in QDR to <em>R. solanacearum </em>at 30 °C. In the context of climate change, the complex genetic architecture underlying QDR under heat stress in a local mapping population revealed candidate genes with diverse molecular functions.</p>
Efficient weighting methods for genomic best linear unbiased prediction (BLUP) adaption to the genetic architectures of quantitative traits
<p><a name="_Hlk19877414"></a>Genomic best linear unbiased prediction (GBLUP) assumes equal variance for all marker effects, which is suitable for traits that conform to the infinitesimal model. For traits controlled by major genes, Bayesian methods with shrinkage priors or genome-wide association study (GWAS) methods can be used to identify <a name="_Hlk24974556">causal variants</a> effectively. The information from Bayesian/GWAS methods can be used to construct the weighted genomic relationship matrix (<b>G</b>). However, it remains unclear which methods perform best for traits varying in genetic architecture. Therefore, we developed several methods to <a name="_Hlk23592218">optimize</a> the performance of weighted GBLUP and compare them with other available methods using simulated and real datasets. First, two types of methods (marker effects with local-shrinkage or normal prior) were used to obtain test statistics and estimates for each marker effect. Second, three weighted <b>G</b> matrices were constructed based on the marker information from the first step: (1) the genomic-feature weighted <b>G</b> (GFWG), (2) the estimated marker-variance weighted <b>G</b> (EVWG), and (3) the absolute value of estimated marker-effect weighted <b>G</b> (AEWG). Following the above process, six different weighted GBLUP methods (local-shrinkage/normal prior GF/EV/AE-WGBLUP) were proposed for genomic prediction. Analyses with both simulated and real data demonstrated that these options offer flexibility for optimizing the weighted GBLUP for traits with a broad spectrum of genetic architectures. The advantage of weighting methods over GBLUP in terms of accuracy were trait dependent, ranging from 14.8% to marginal for simulated traits and from 44% to marginal for real traits. Local-shrinkage prior EVWGBLUP is superior for traits mainly controlled by loci of large effect. Normal prior AEWGBLUP performs well for traits mainly controlled by loci of moderate effect. For traits controlled by some loci with large effects (<a name="_Hlk49869847">explain 25%~50% genetic variance</a>) and a range of loci with small effects, GFWGBLUP has advantages. In conclusion, the optimal weighted GBLUP method for genomic selection should take both the genetic architecture and number of QTLs of traits into consideration carefully.</p>
Using genomic prediction to detect microevolutionary change of a quantitative trait
<p>Detecting microevolutionary responses to natural selection by observing temporal changes in individual breeding values is challenging. The collection of suitable datasets can take many years and disentangling the contributions of the environment and genetics to phenotypic change is not trivial. Furthermore, pedigree-based methods of obtaining individual breeding values have known biases. Here, we apply a genomic prediction approach to estimate breeding values of adult weight in a 35-year dataset of Soay sheep (<i>Ovis aries)</i>. Comparisons are made with a traditional pedigree-based approach. During the study period adult body weight decreased, but the underlying genetic component of body weight increased, at a rate that is unlikely to be attributable to genetic drift. Thus cryptic microevolution of greater adult body weight has probably occurred. Genomic and pedigree-based approaches gave largely consistent results. Thus, using genomic prediction to study microevolution in wild populations can remove the requirement for pedigree data, potentially opening up new study systems for similar research.</p>
Data from: Widespread cumulative influence of small effect size mutations on yeast quantitative traits
Quantitative traits are influenced by pathways that have traditionally been defined through genes that have a large loss- or gain-of-function effect. However, in theory, a large number of small effect-size genes could cumulatively play a substantial role in pathway function. Here, we determined the number, strength and identity of all non-essential test genes that affect two quantitative galactose-responsive traits, in addition to re-analyzing two previously screened quantitative traits. We find that over a quarter of assayed genes have a detectable, quantitative effect on phenotype. Despite their ubiquity, these genes are enriched in core cellular processes in a trait-specific manner. In a simulated population with 50% frequency of all-or-none alleles, we show that small effect-size alleles are capable of contributing more to trait variation than alleles in a canonical, large-effect size pathway. In total, by demonstrating that the genes effecting quantitative traits can be highly distributed and interconnected, this work challenges the concept of pathways as modular and independent.
Data from: Evolutionary dynamics of quantitative variation in an adaptive trait at the regional scale: the case of zinc hyperaccumulation in Arabidopsis halleri
Metal hyperaccumulation in plants is an ecological trait whose biological significance remains debated, in particular because the selective pressures that govern its evolutionary dynamics are complex. One of the possible causes of quantitative variation in hyperaccumulation may be local adaptation to metalliferous soils. Here we explored the population genetic structure of Arabidopsis halleri at fourteen metalliferous and non-metalliferous sampling sites in Southern Poland. The results were integrated with a quantitative assessment of variation in zinc hyperaccumulation to trace local adaptation. We identified a clear hierarchical structure with two distinct genetic groups at the upper level of clustering. Interestingly, these groups corresponded to different geographic sub-regions, rather than to ecological types (i.e. metallicolous vs non-metallicolous). Also, approximate Bayesian computation analyses suggested that the current distribution of A. halleri in Southern Poland could be relictual as a result of habitat fragmentation caused by climatic shifts during the Holocene, rather than due to recent colonization of industrially polluted sites. In addition, we find evidence that some non-metallicolous lowland populations may have actually derived from metallicolous populations. Meanwhile, the distribution of quantitative variation in zinc hyperaccumulation did separate metallicolous and non-metallicolous accessions, indicating more recent adaptive evolution and diversifying selection between metalliferous and non-metalliferous habitats. This suggests that zinc hyperaccumulation evolves both ways – towards higher levels at non-metalliferous sites and lower levels at metalliferous sites. Our results open a new perspective on possible evolutionary relationships between A. halleri edaphic types that may inspire future genetic studies of quantitative variation in metal hyperaccumulation.
Data from: Ontogenetic stage-specific quantitative trait loci contribute to divergence in developmental trajectories of sexually dimorphic fins between medaka populations
Sexual dimorphism can evolve when males and females differ in phenotypic optima. Genetic constraints can, however, limit the evolution of sexual dimorphism. One possible constraint is derived from alleles expressed in both sexes. Because males and females share most of their genome, shared alleles with different fitness effects between sexes are faced with intralocus sexual conflict. Another potential constraint is derived from genetic correlations between developmental stages. Sexually dimorphic traits are often favoured at adult stages, but selected against as juvenile, so developmental decoupling of traits between ontogenetic stages may be necessary for the evolution of sexual dimorphism in adults. Resolving intralocus conflicts between sexes and ages is therefore a key to the evolution of age-specific expression of sexual dimorphism. We investigated the genetic architecture of divergence in the ontogeny of sexual dimorphism between two populations of the Japanese medaka (Oryzias latipes) that differ in the magnitude of dimorphism in anal and dorsal fin length. Quantitative trait loci (QTL) mapping revealed that few QTL had consistent effects throughout ontogenetic stages and the majority of QTL change the sizes and directions of effects on fin growth rates during ontogeny. We also found that most QTL were sex-specific, suggesting that intralocus sexual conflict is almost resolved. Our results indicate that sex- and age-specific QTL enable the populations to achieve optimal developmental trajectories of sexually dimorphic traits in response to complex natural and sexual selection.
Data from: Assessing the effects of quantitative host resistance on the life-history traits of sporulating parasites with growing lesions
Assessing life-history traits of parasites on resistant hosts is crucial in evolutionary ecology. In the particular case of sporulating pathogens with growing lesions, phenotyping is difficult because one needs to disentangle properly pathogen spread from sporulation. By considering Phytophthora infestans on potato, we use mathematical modelling to tackle this issue and refine the assessment pathogen response to quantitative host resistance. We elaborate a parsimonious leaf-scale model by convolving a lesion growth model and a sporulation function, after a latency period. This model is fitted to data obtained on two isolates inoculated on three cultivars with contrasted resistance level. Our results confirm a significant host-pathogen interaction on the various estimated traits, and a reduction of both pathogen spread and spore production, induced by host resistance. Most interestingly, we highlight that quantitative resistance also changes the sporulation function, whose mode is significantly time-lagged.This alteration of the infectious period distribution on resistant hosts may have strong impacts on the dynamics of parasite populations, and should be considered when assessing the durability of disease control tactics based on plant resistance management. This inter-disciplinary work also supports the relevance of mechanistic models for analysing phenotypic data of plant-pathogen interactions.
Data from: Quantitative trait loci for cold tolerance in chickpea
Fall-sown chickpea (Cicer arietinum L.) yields are often double those of spring-sown chickpea in regions with Mediterranean climates that have mild winters. However, winter kill can limit the productivity of fall-sown chickpea. Developing cold-tolerant chickpea would allow the expansion of the current geographic range where chickpea is grown and also improve productivity. The objective of this study was to identify the quantitative trait loci (QTL) associated with cold tolerance in chickpea. An interspecific recombinant inbred line population of 129 lines derived from a cross between ICC 4958, a cold-sensitive desi type (C. arietinum), and PI 489777, a cold-tolerant wild relative (C. reticulatum Ladiz), was used in this study. The population was phenotyped for cold tolerance in the field over four field seasons (September 2011–March 2015) and under controlled conditions two times. The population was genotyped using genotyping-by-sequencing, and an interspecific genetic linkage map consisting of 747 single nucleotide polymorphism (SNP) markers, spanning a distance of 393.7 cM, was developed. Three significant QTL were found on linkage groups (LGs) 1B, 3, and 8. The QTL on LGs 3 and 8 were consistently detected in six environments with logarithm of odds score ranges of 5.16 to 15.11 and 5.68 to 23.96, respectively. The QTL CT Ca-3.1 explained 7.15 to 34.6% of the phenotypic variance in all environments, whereas QTL CT Ca-8.1 explained 11.5 to 48.4%. The QTL-associated SNP markers may become useful for breeding with further fine mapping for increasing cold tolerance in domestic chickpea.
Data from: Development of a genomic resource and quantitative trait loci mapping of male calling traits in the lesser wax moth, Achroia grisella
In the study of sexual selection among insects, the Lesser Waxmoth, Achroia grisella (Lepidoptera: Pyralidae), has been one of the more intensively studied species over the past 20 years. Studies have focused on how the male calling song functions in pair formation and on the quantitative genetics of male song characters and female preference for the song. Recent QTL studies have attempted to elucidate the genetic architecture of male song and female preference traits using AFLP markers. We continued these QTL studies using SNP markers derived from an EST library that allowed us to measure both DNA sequence variation and map loci with respect to the lepidopteran genome. We report that the level of sequence variation within A. grisella is typical among other Lepidoptera that have been examined, and that comparison with the Bombyx mori genome shows that macrosynteny is conserved. Our QTL map shows that a QTL for a male song trait, pulse-pair rate, is situated on the Z chromosome, a prediction for sexually selected traits in Lepidoptera. Our findings will be useful for future studies of genetic architecture of this model species and may help identify the genetics associated with the evolution of its novel acoustic communication.
Data from: The quantitative genetics of incipient speciation: heritability and genetic correlations of skeletal traits in populations of diverging Favia fragum ecomorphs.
Recent speciation events provide potential opportunities to understand the microevolution of reproductive isolation. We used a marker-based approach and a common garden to estimate the additive genetic variation in skeletal traits in a system of two ecomorphs within the coral species Favia fragum: a Tall ecomorph that is a seagrass specialist, and a Short ecomorph that is most abundant on coral reefs. Considering both ecomorphs, we found significant narrow-sense heritability (h²) in a suite of measurements that define corallite architecture, and could partition additive and non-additive variation for some traits. We found positive genetic correlations for homologous height and length measurements among different types of vertical plates (costosepta) within corallites, but negative correlations between height and length within, as well as between costosepta. Within ecomorphs, h² estimates were generally lower, compared to the combined ecomorph analysis. Marker-based estimates of h² were comparable to broad-sense heritability (H) obtained from parent-offspring regressions in a common garden for most traits, and similar genetic co-variance matrices for common garden and wild populations may indicate relatively small G × E interactions. The patterns of additive genetic variation in this system invite hypotheses of divergent selection or genetic drift as potential evolutionary drivers of reproductive isolation.
Data from: The quantitative genetics of physiological and morphological traits in an invasive terrestrial snail: additive versus non-additive genetic variation
1. The distribution of additive versus non-additive genetic variation in natural populations represents a central topic of research in evolutionary/organismal biology. For evolutionary physiologists, functional or whole-animal performance traits ("physiological traits") are frequently studied assuming they are heritable and variable in populations. 2. Physiological traits of evolutionary relevance are those functional capacities measured at the whole-organism level, with a potential impact on fitness. They can be classified as capacities (or performances) or costs, the former being directly correlated with fitness, and the latter being inversely correlated with fitness (usually assumed as constraints). 3. In spite of their obvious adaptive significance, the additive genetic variation of physiological traits, and its relative contribution to phenotypic variance (or narrow-sense heritability) in comparison to maternal, dominance or epistatic variance, is known only for a few groups such as insects and mammals. 4. In this study, we assessed the additive and maternal/non-additive genetic variation in a suite of physiological and morphological traits in populations of the land snail Cornu aspersum. 5.Except for dehydration rate (h2= 0.32 ± 0.15), egg mass (h2= 0.82 ± 0.30) and hatchling mass (h2= 1.01 ± 0.31) (population = fixed effect), we found very low additive genetic variation. Large non-additive/maternal effects were found in all traits. Cage effects did not change the results, indicating low contribution of common environmental variance to our results. No differences were found between the phenotypic or non-additive genetic variance/covariance matrices. 6. Even though we compared populations across 1300 km in a common garden setup, our results suggest an absence of physiological as well as morphological differentiation in these populations. 7. These results contrast with previous analyses in the original distributional range of this species, which found high additive genetic variation in morphological traits. These are intriguing results demanding further quantitative genetic studies in the original distributional range of this species as well as the history of colonization of this invasive species.
Genetics of quantitative traits with dominance under stabilizing and directional selection in partially selfing species
<p>Recurrent self-fertilization is thought to lead to reduced adaptive potential by decreasing the genetic diversity of populations, thus leading selfing lineages down an evolutionary 'blind alley'. Though well supported theoretically, empirical support for reduced adaptability in selfing species is limited. One limitation of classical theoretical models is that they assume pure additivity of the fitness-related traits that are under stabilizing selection, despite ample evidence that quantitative traits are subject to dominance. Here we relax this assumption and explore the effect of dominance on a fitness-related trait under stabilizing selection for populations that differ in selfing rates. By decomposing the genetic variance into additional components specific to inbred populations, we show that dominance components can explain a substantial part of the genetic variance of inbred populations. We also show that ignoring these components leads to an upward bias in the predicted response to selection. Finally, we show that when considering the effect of dominance, the short-term evolutionary potential of populations remains comparable across the entire gradient in outcrossing rates, and genetic associations can even make selfing populations more evolvable on the longer term, reconciling theoretical and empirical results.</p>
Dataset for Quantitative Trait Loci Associated with Lodging in Dry Field Peas. Data for PR Population (Carerra x Striker).
<p>Dataset for Quantitative Trait Loci Associated with Lodging in Dry Field Peas. Data for PR Population (Carerra x Striker). Here is data on lodging, height, stem diameter, side branch diameter, and epicotyl diameter for both site years with the PR population.</p>
Dataset for Quantitative Trait Loci Associated with Lodging, Stem Strength, Yield, and Other Important Agronomic Traits in Dry Field Peas, All SNP markers
<p>Dataset for Quantitative Trait Loci Associated with Lodging, Stem Strength, Yield, and Other Important Agronomic Traits in Dry Field Peas. All SNP markers were included in the dataset. U designates a missing datapoint. The data was not inputed.</p>
Dataset for Quantitative Trait Loci Associated with Lodging, Stem Strength, Yield, and Other Important Agronomic Traits in Dry Field Peas with data for 330 markers
<p>Dataset for Quantitative Trait Loci Associated with Lodging, Stem Strength, Yield, and Other Important Agronomic Traits in Dry Field Peas with data for 330 markers. This dataset is associated with the dissertation entitled, Quantitative Trait Loci Associated with Lodging, Stem Strength, Yield, and Other Important Agronomic Traits in Dry Field Peas.</p>
Causal effect of familial short stature on three quantitative traits in Taiwan
<p><span><strong>Objectives</strong>: </span><span>With the accumulation of genetic basis for </span><span>familial (genetic) short stature (FSS)</span><span>, the genetic association of FSS with health-related outcomes remains to be elucidated. In this study, we aimed to investigate the FSS genetic architecture and its causal effect on three quantitative traits in Taiwan. </span></p> <p><span><strong>Methods</strong>:</span><span> We </span><span>conducted an FSS genome-wide association study (GWAS) analysis (1,640 FSS cases and 22,372 controls). We performed a GWAS meta-analysis for the Taiwanese meta-height from the Taiwan Biobank (</span><span>TWB)_height (N = 67,452) and the China Medical University Hospital (CMUH)_height GWAS summary statistics (N = 88,854). </span><span>We calculated three polygenic risk scores (PRSs) of SNPs (<em>P</em> < 5 x 10<sup>-8</sup>) for FSS and Taiwanese meta-height with/without FSS, respectively. We explored the associations between three PRSs and the measured height, respectively. We also performed </span><span>Mendelian randomization (MR) analysis</span><span> for the causal effect of FSS and Taiwanese meta-height with/without FSS, on anthropometric, bone mineral density (BMD), and female reproductive traits</span><span>. </span></p> <p><span><strong>Results</strong>: </span><span>FSS GWAS identified 172 SNPs in 4 genomic regions, reported in height </span><span>(<em>P</em> < 5 x 10<sup>-8</sup>)</span><span>. Higher FSS genetic scores correlate with an increased risk of short stature and height reduction tendency </span><span>(</span><em><span>p</span></em> <span><</span><span> 0.001).</span><span> The causal effect showed that a higher risk of FSS was associated with decreased body height, but increased body mass index, and body fat</span> <span>(</span><em><span>p</span></em> <span><</span><span> 0.001)</span><span>. However, higher genetic scores of Taiwanese meta-height with/without FSS correspond with increased body height, body weight, hip circumference, and age at menarche, but decreased BMD_T-score, BMD_Z-score, and stiffness index </span><span>(</span><em><span>p</span></em> <span><</span><span> 0.001)</span><span>. </span></p> <p><span><strong>Conclusion</strong>: </span><span>This study </span><span>contributes to the FSS and height genetic features and their causal effects on three quantitative traits </span><span>in individuals of Han Chinese ancestry in Taiwan. </span></p>
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