Quantitative Genetic Variation Research Articles

MPH: fast REML for large-scale genome partitioning of quantitative genetic variation.

Genome partitioning of quantitative genetic variation is useful for dissecting the genetic architecture of complex traits. However, existing methods, such as Haseman-Elston regression and linkage disequilibrium score regression (LDSC), often face limitations when handling extensive farm animal datasets, as demonstrated in this study. To overcome this challenge, we present MPH, a novel software tool designed for efficient genome partitioning analyses using restricted maximum likelihood. The computational efficiency of MPH primarily stems from two key factors: the utilization of stochastic trace estimators and the comprehensive implementation of parallel computation. Evaluations with simulated and real datasets demonstrate that MPH achieves comparable accuracy and significantly enhances convergence, speed, and memory efficiency compared to widely used tools like GCTA and LDAK. These advancements facilitate large-scale, comprehensive analyses of complex genetic architectures in farm animals. The MPH software is available at https://jiang18.github.io/mph/. Supplementary data are available at Bioinformatics online.

The effects of case/control ratio and sample size on genome-wide association studies: A simulation study.

Genome-wide association studies (GWAS) is a useful tool for the detection of disease or quantitative trait-related genetic variations in the veterinary field. For a binary trait, a case/control experiment is designed in GWAS. However, there is limited information on the optimal case/control and sample size in GWAS. In this study, it was aimed to detect the effects of case/control ratio and sample size for GWAS using computer simulation under certain assumptions. Using the PLINK software, we simulated three different disease scenarios. In scenario 1, we simulated 10 different case/control ratios with increasing ratio of cases to controls. In scenario 2, we did versa of scenario 1 with the increasing ratio of controls to cases. In scenarios 1 and 2, sample size gradually was increased with the change case/control ratios. In scenario 3, the total sample size was fixed to 2000 to see real effects of case/control ratio on the number of disease-related single nucleotide polymorphisms (SNPs). The results showed that the number of disease-related SNPs were the highest when the case/control ratio is close to 1:1 in scenarios 1 and 2 and did not change with an increase in sample size. Similarly, the number of disease-related SNPs was the highest in case/control ratios 1:1 in scenario 3. However, unbalanced case/control ratio caused the detection of lower number of disease-related SNPs in scenario 3. The estimated average power of SNPs was highest when case/control ratio is 1:1 in all scenarios. All findings led to the conclusion that an increase in sample size may enhance the statistical power of GWAS when the number of cases is small. In addition, case/control ratio 1:1 may be the optimal ratio for GWAS. These findings may be valuable not only for veterinary field but also for human clinical experiments.

Qualitative and quantitative genetic variations in bitter gourd (Momordica charantia L.)

Qualitative and quantitative genetic variations in bitter gourd (Momordica charantia L.)

A Study of The Biological Effect of Egy Pride on The Quantitative Genetic Variation of The Cucurbit Fruit Fly, Dacus Ciliatus (Diptera: Tephritidae)

This study investigates the influence of the insecticide Egy Pride on the quantitative genetic variation and wing morphology of the Cucurbita fruit fly, Dacus ciliatus, a pest of agricultural significance. Geometric morphometrics were applied to analyze the shape and size of right wings from 30 specimens, half of which were treated with Egy Pride. The analysis revealed a 67% match rate in landmark coordinates between treated and untreated specimens, with notable deviations at landmarks 2, 6, 8, 9, and 15. Treated specimens exhibited variations in wing shape and size, with a central size measurement of 868.6 microns compared to 850.8 microns in the control group. Statistical analysis showed a Mahalanobis distance of 9.49, indicating differentiation between the groups. Classification rates based on wing morphology were 74% for treated and 53% for untreated specimens, with an 83% rate when based on the Mahalanobis distance. The study suggests that Egy Pride induces quantitative genetic variation and morphological changes in D. ciliatus, potentially affecting their flight and mobility. These findings highlight the unique properties of Egy Pride in pest control and its impact on the genetic and morphological aspects of targeted species.

Quantifying the role of genome size and repeat content in adaptive variation and the architecture of flowering time in Amaranthus tuberculatus.

Genome size variation, largely driven by repeat content, is poorly understood within and among populations, limiting our understanding of its significance for adaptation. Here we characterize intraspecific variation in genome size and repeat content across 186 individuals of Amaranthus tuberculatus, a ubiquitous native weed that shows flowering time adaptation to climate across its range and in response to agriculture. Sequence-based genome size estimates vary by up to 20% across individuals, consistent with the considerable variability in the abundance of transposable elements, unknown repeats, and rDNAs across individuals. The additive effect of this variation has important phenotypic consequences-individuals with more repeats, and thus larger genomes, show slower flowering times and growth rates. However, compared to newly-characterized gene copy number and polygenic nucleotide changes underlying variation in flowering time, we show that genome size is a marginal contributor. Differences in flowering time are reflected by genome size variation across sexes and marginally, habitats, while polygenic variation and a gene copy number variant within the ATP synthesis pathway show consistently stronger environmental clines than genome size. Repeat content nonetheless shows non-neutral distributions across the genome, and across latitudinal and environmental gradients, demonstrating the numerous governing processes that in turn influence quantitative genetic variation for phenotypes key to plant adaptation.

Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective.

Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.

Estimating Population Abundance Of Seahorse In Sebong Bay, Bintan Island

The decline in seahorse populations in the wild due to high fishing activity and habitat degradation prompted the inclusion of all seahorse species in Appendix II of CITES (Convention on International Trade in Endangered Species of Wild Fauna and Flora) in 2002. By being included in Appendix II of CITES, data and information on the abundance of seahorse populations become crucial as the basis for determining the quota for fishing and trade. Estimating population abundance of seahorse requires knowledge of habitat area, which can be modeled using the MaxEnt (maximum entropty). In this study, an estimation of the abundance of seahorses was carried out in the waters of Sebong Bay, Bintan Island. MaxEnt modeling was implemented with data on seahorse presence locations and environmental parameter maps consisting of chlorophyll-a as primary productivity parameter, benthic habitat as habitat type parameter, and dissolved oxygen, salinity, and pH as physiological parameters. From this model, the value of the area of suitable habitat for seahorses is 54,6 ha, while the density of seahorse in this area is 60 ind/ha, so it can be determined that the abundance of seahorses in the Sebong Bay is 3.276 individuals. Therefore, seahorse population in Sebong Bay is critically endangered since it is below the number of individuals that required to prevent the loss of quantitative genetic variation in a species.

William George Hill. 7 August 1940—17 December 2021

William (Bill) Hill was an internationally acclaimed statistical, population and quantitative geneticist. His work was inspired by practical problems in animal breeding, but is widely applicable to evolutionary biology and human genetics. Bill's work focused on the joint effects of linkage, mutation and genetic architecture in finite populations. He showed that linked loci under selection can interfere with each other, reducing the rate of response to selection. He derived a widely used metric for linkage disequilibrium and showed that there is likely to be substantial linkage disequilibrium between closely linked variants in finite populations. He also showed that the sampling variance of linkage disequilibrium is very large, hampering its use in estimating effective population size or recombination rates. Bill derived sampling variances for inbreeding and realized relatedness between individuals with the same expected degree of relatedness. He raised awareness about the importance of new mutations for quantitative genetic variation and the response to artificial selection, and developed models for the maintenance of quantitative genetic variation by a balance between mutation and stabilizing selection. His experimental designs for estimating heritability and conducting artificial selection experiments have been widely adopted, and were utilized in his own long-term mouse selection experiments. Bill influenced animal breeding directly through consultancies with breeding companies, and his influence on quantitative genetics continues today via his numerous mentees.

Tests for associations between sexual dimorphism and patterns of quantitative genetic variation in the water strider, Aquarius remigis

The evolution of sexual dimorphisms requires divergence between sexes in the evolutionary trajectories of the traits involved. Discerning how genetic architecture could facilitate such divergence has proven challenging because of the difficulty in estimating non-additive and sex-linked genetic variances using traditional quantitative genetic designs. Here we use a three-generation, double-first-cousin pedigree design to estimate additive, sex-linked and dominance (co)variances for 12 traits in the water strider, Aquarius remigis. Comparisons among these traits, which have size ratios ranging from 1 to 5 (larger/smaller), allow us to ask if sexual dimorphisms are associated with characteristic patterns of quantitative genetic variation. We frame our analysis around three main questions, derived from existing theory and empirical evidence: Are sexual dimorphisms associated with (1) lower additive inter-sex genetic correlations, (2) higher proportions of sex-linked variance, or (3) differences between sexes in autosomal additive and dominance genetic variances? For questions (1) and (2), we find weak and non-significant trends in the expected directions, which preclude definitive conclusions. However, in answer to question (3), we find strong evidence for a positive relationship between sexual dimorphism and differences between sexes in proportions of autosomal dominance variance. We also find strong interactions among the three genetic components indicating that their relative influence differs among traits and between sexes. These results highlight the need to include all three components of genetic (co)variance in both theoretical evolutionary models and empirical estimations of the genetic architecture of dimorphic traits.

Reduced within-population quantitative genetic variation is associated with climate harshness in maritime pine.

How evolutionary forces interact to maintain genetic variation within populations has been a matter of extensive theoretical debates. While mutation and exogenous gene flow increase genetic variation, stabilizing selection and genetic drift are expected to deplete it. To date, levels of genetic variation observed in natural populations are hard to predict without accounting for other processes, such as balancing selection in heterogeneous environments. We aimed to empirically test three hypotheses: (i) admixed populations have higher quantitative genetic variation due to introgression from other gene pools, (ii) quantitative genetic variation is lower in populations from harsher environments (i.e., experiencing stronger selection), and (iii) quantitative genetic variation is higher in populations from heterogeneous environments. Using growth, phenological and functional trait data from three clonal common gardens and 33 populations (522 clones) of maritime pine (Pinus pinaster Aiton), we estimated the association between the population-specific total genetic variances (i.e., among-clone variances) for these traits and ten population-specific indices related to admixture levels (estimated based on 5165 SNPs), environmental temporal and spatial heterogeneity and climate harshness. Populations experiencing colder winters showed consistently lower genetic variation for early height growth (a fitness-related trait in forest trees) in the three common gardens. Within-population quantitative genetic variation was not associated with environmental heterogeneity or population admixture for any trait. Our results provide empirical support for the potential role of natural selection in reducing genetic variation for early height growth within populations, which indirectly gives insight into the adaptive potential of populations to changing environments.

Rapid evolution during climate change: demographic and genetic constraints on adaptation to severe drought.

Populations often vary in their evolutionary responses to a shared environmental perturbation. A key hurdle in building more predictive models of rapid evolution is understanding this variation-why do some populations and traits evolve while others do not? We combined long-term demographic and environmental data, estimates of quantitative genetic variance components, a resurrection experiment and individual-based evolutionary simulations to gain mechanistic insights into contrasting evolutionary responses to a severe multi-year drought. We examined five traits in two populations of a native California plant, Clarkia xantiana, at three time points over 7 years. Earlier flowering phenology evolved in only one of the two populations, though both populations experienced similar drought severity and demographic declines and were estimated to have considerable additive genetic variance for flowering phenology. Pairing demographic and experimental data with evolutionary simulations suggested that while seed banks in both populations probably constrained evolutionary responses, a stronger seed bank in the non-evolving population resulted in evolutionary stasis. Gene flow through time via germ banks may be an important, underappreciated control on rapid evolution in response to extreme environmental perturbations.

Indirect genetic effects for social network structure in Drosophila melanogaster.

The position an individual holds in a social network is dependent on both its direct and indirect social interactions. Because social network position is dependent on the actions and interactions of conspecifics, it is likely that the genotypic composition of individuals within a social group impacts individuals' network positions. However, we know very little about whether social network positions have a genetic basis, and even less about how the genotypic makeup of a social group impacts network positions and structure. With ample evidence indicating that network positions influence various fitness metrics, studying how direct and indirect genetic effects shape network positions is crucial for furthering our understanding of how the social environment can respond to selection and evolve. Using replicate genotypes of Drosophila melanogaster fruit flies, we created social groups that varied in their genotypic makeup. Social groups were videoed, and networks were generated using motion-tracking software. We found that both an individual's own genotype and the genotypes of conspecifics in its social group affect its position within a social network. These findings provide an early example of how indirect genetic effects and social network theory can be linked, and shed new light on how quantitative genetic variation shapes the structure of social groups. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Contrasting adaptive trait variation in response to drought in two Mediterranean shrubs

Adaptive evolution and phenotypic plasticity are key mechanisms of climate change responses. However, we still lack a detailed understanding of the strategies different species use to cope with climatic changes such as increased droughts, particularly for species with special edaphic requirements and limited dispersal such as gypsum endemics. In this study, we assessed phenotypic and genotypic selection, phenotypic plasticity and genetic variation in traits potentially related to drought response in two dominant gypsum Mediterranean species, Helianthemum squamatum and Centaurea hyssopifolia. We established a common garden in which 524 plants from 79 maternal families from both species were grown under two contrasting watering treatments. Our results revealed that selection was stronger under drought than well-watered conditions for both species, but we found contrasting adaptive strategies and genetic variation. In H. squamatum, a drought-escape strategy with advanced reproductive phenology and faster growth rates was positively associated with fitness under dry conditions, and most adaptive traits exhibited quantitative genetic variation. In contrast, in C. hyssopifolia, selection under dry conditions favored a drought-tolerance strategy with thicker leaves and longer phenologies, but all traits lacked quantitative genetic variation, indicating that their evolutionary potential may be limited. Most traits exhibited significant plasticity in response to drought and genetic variation for trait plasticity in both species, indicating that trait plasticity can evolve independently of the evolution of trait means in these gypsophiles. Our results show that these gypsum endemic species vary in strategies and adaptive potential in response to drought, which contributes to our understanding of potential adaptive responses to climate change in such edaphic specialists.

Are populations less genetically diverse and more differentiated at the species range edges? Analysis of the quantitative trait and molecular variation in wild oat Avena sterilis

Abstract Although understanding factors determining the genetic makeup of natural populations has long been an important goal of evolutionary biology, the effect of population position within the species range (i.e., interior vs. edge) on species genetic variation is still unclear. According to the ‘abundant center’ hypothesis, the range edge populations are expected to exhibit lower genetic variation and higher differentiation than core populations because of their greater spatial isolation and smaller size. We tested these predictions by comparing the extent and structure of neutral (SSR) and quantitative trait genetic variation in 20 populations of an annual grass Avena sterilis hierarchically sampled at the species range core and two opposite edges. Within-population genetic diversity was reduced at the desert range edge compared to the range core as assessed by six SSR markers but not by eight quantitative traits; no reduction was detected at the mountain edge. Genetic differentiation among populations was higher at the desert range edge than the range core in both molecular markers and quantitative traits, but not at the mountain edge. Our results imply that the pattern of population genetic variation at the species range edges largely depends on the steepness of the environmental cline that has a major effect on species fitness. The more gradual the environmental cline from the species interior towards the edge, the higher the probability of detecting reduced genetic diversity and increased differentiation of peripheral populations as predicted by the ‘abundant center’ hypothesis.

Molecular and quantitative genetic variation within and between populations of the declining grassland species Saxifraga granulata.

Formerly common plant species are expected to be particularly susceptible to recent habitat fragmentation. We studied the population genetics of 19 recently fragmented Saxifraga granulata populations (max. distance 61 km) in Luxembourg and neighboring Germany using RAPD markers and a common garden experiment. We assessed (1) the relationships between plant fitness, quantitative genetic variation, molecular genetic variation, and population size; and (2) the relative importance of genetic drift and selection in shaping genetic variation. Molecular genetic diversity was high but did not correlate with population size, habitat conditions, or plant performance. Genetic differentiation was low (F ST=0.079 ± 0.135), and there was no isolation by distance. Longevity, clonality, and the long-lived seed bank of S.granulata may have prevented strong genetic erosion and genetic differentiation among populations. However, genetic distinctness increased with decreasing genetic diversity indicating that random genetic drift occurred in the studied populations. Quantitative and molecular genetic variations were correlated, and their differentiation (Q ST vs. F ST) among S.granulata populations was similar, suggesting that mainly random processes have shaped the quantitative genetic differentiation among populations. However, pairwise quantitative genetic distances increased with geographic and climatic distances, even when adjusted for molecular genetic distances, indicating diversifying selection. Our results indicate that long-lived clonal species may be buffered at least temporarily against the negative effects of fragmentation. The relationship between quantitative genetic and geographic distance may be a more sensitive indicator of selection than Q ST-F ST differences.

Mapping and identification of quantitative trait loci controlling test weight and seed yield of pearl millet in multi agro-climatic zones of India

Pearl millet [ Pennisetum glaucum (L.) R. Br.] is a climate-resilient nutri-cereal and is a staple food for the inhabitants of arid and semi-arid regions of the world. Yield stability is a major problem and requires exploiting key breeding strategies for the improvement of yield component traits in pearl millet. The main objective of the present study was the genomic dissection of yield and its component traits by identifying multi-environmental QTL in order to increase the efficiency and accuracy of pearl millet breeding. An experiment was designed for mapping agronomically important traits in 210 Recombinant inbred lines (RIL) derived from the cross PPMI 683 × PPMI 627. These RILs were evaluated in three diverse pearl millet growing regions in India for three consecutive years. Over the consecutive years and locations, thousand seed weight (TSW) showed a significant positive association with other agronomic traits. QTL analysis revealed three significant common QTL for TSW. the flanking markers of common QTL were Xpsmp2273- Xipes0203; Xpsmp2077- Xpsmp2059 and ICMP3058- Xipes0147 . The identified common QTL markers explained the total phenotypic variance of 27.57, 22.61,7.59% for QTL 1 on LG 1; 21.38, 24.13,12.14% for QTL 2 on LG 2, and 7.34, 15.26, 9.6% for QTL 3 on LG 6 across three consecutive years (2014–2016) at Delhi (E1), Dharwad (E2) and Jodhpur (E3), respectively. Two constitutive expressing QTL markers for Seed Yield per Plant (SYPP) were found at a significant threshold LOD value of 3.5 and flanked by the markers: Xpsmp2273- Xipes0203 and Xpsmp2077- Xpsmp2059 with a total phenotypic variance of 28.24 , 19.95%, and 6.31% for QTL 1 on LG 1; 19.78, 21.38, 7.17% for QTL 2 on LG 2 across consecutive years at Delhi, Dharwad and Jodhpur, respectively. In total, 34 and 29 significant digenic interactions were detected for TSW and SYPP, respectively. In the present study, using quantitative genetic variation for TSW and SYPP, major and stable QTLs were found across environments. Some potential genes that may affect the traits were identified in the comparative genomics scan using rice and Arabidopsis. Three significant and stable QTLs for TSW and two for SYPP were detected across all environments. The digenic interactions were detected for TSW (34) and SYPP (29) at Delhi, Dharwad, and Jodhpur. The mapped QTL for TSW and SYPP in the current study could be exploited to develop elite hybrid parental genotypes/cultivars through marker-assisted selection and genomic selection in breeding programs. • In an era of climate change, pearl millet has promising prospects to achieve economic returns. • Major and stable QTLs for TSW (3 QTLs) and SYPP (2 QTLs) were detected across the environments. • Two genomic regions with pleiotropic effects for TSW and SYPP at Delhi, Dharwad, and Jodhpur were detected. • Digenic interactions were detected for TSW (34) and SYPP (29) at Delhi, Dharwad, and Jodhpur. • All favorable QTLs to break down genetic barriers to yield for sustainable food security.

An exploration into the conversion of dominance to additive genetic variance in contrasting environments.

The evolutionary response of a trait to environmental change depends upon the level of additive genetic variance. It has been long argued that sustained selection will tend to deplete additive genetic variance as favored alleles approach fixation. Non-additive genetic variance, due to interactions among alleles within and between loci, does not immediately contribute to an evolutionary response. However, shifts in the allele frequencies within and between interacting loci may convert non-additive variance into additive variance. Here we consider the possibility that an environmental shift may alter allelic interactions in ways that convert dominance into additive genetic variance. We grew a pedigreed population of Brassica rapa in greenhouse and field conditions. The field conditions mimicked agricultural conditions from which the base population was drawn, while the greenhouse featured benign conditions. We used Bayesian models to estimate the additive, dominance, and maternal components of quantitative genetic variance. We also estimated genetic correlations across environments using parental breeding values. Although the additive genetic variance was elevated in the greenhouse condition, no consistent pattens emerged that would indicate a conversion of dominance variance. The unusually low genetic variance and broad confidence intervals for the variance estimates obtained through this analysis preclude definitive interpretations. Further studies are needed to determine whether between-environment changes in additive genetic variance can be traced to conversion of dominance variance.

Drivers of population differentiation in phenotypic plasticity in a temperate conifer: A 27-year study.

Phenotypic plasticity is a main mechanism for organisms to cope with changing environments and broaden their ecological range. Plasticity is genetically based and can evolve under natural selection, such that populations within a species show distinct phenotypic responses to the environment if evolved under different conditions. Understanding how intraspecific variation in phenotypic plasticity arises is critical to assess potential adaptation to ongoing climate change. Theory predicts that plasticity is favored in more favorable but variable environments. Yet, many theoretical predictions about benefits, costs, and selection on plasticity remain untested. To test these predictions, we took advantage of three genetic trials in the northern Rocky Mountains, USA, which assessed 23 closely located Pinus ponderosa populations over 27 years. Mean environmental conditions and their spatial patterns of variation at the seed source populations were characterized based on six basic climate parameters. Despite the small area of origin, there was significant genetic variation in phenotypic plasticity for tree growth among populations. We found a significant negative correlation between phenotypic plasticity and the patch size of environmental heterogeneity at the seed source populations, but not with total environmental spatial variance. These results show that populations exposed to high microhabitat heterogeneity have evolved higher phenotypic plasticity and that the trigger was the grain rather than the total magnitude of spatial heterogeneity. Contrary to theoretical predictions, we also found a positive relationship between population plasticity and summer drought at the seed source, indicating that drought can act as a trigger of plasticity. Finally, we found a negative correlation between the quantitative genetic variance within populations and their phenotypic plasticity, suggesting compensatory adaptive mechanisms for the lack of genetic diversity. These results improve our understanding of the microevolutionary drivers of phenotypic plasticity, a critical process for resilience of long-lived species under climate change, and support decision-making in tree genetic improvement programs and seed transfer strategies.

Analysis a number of Quantitative Traits and Genetic Variation of Different Generation of Wheat (Tritecum aestivum) by using RAPD-PCR

RAPD-PCR genetic markers were used to assess genetic variation in wheat plants and connections among six wheat genotypes. Four random primers produced 140 DNA fragments, averaging 6.7 identifiable bands per primer. Among the six genotypes, 85 pieces (44.64 percent) were polymorphic. Several RAPD marker bands had distinct signify recurrence patterns that thing differently amongst germplasm of wheat plants groupings. Within-community genetic variation accounted for 78 to 89 percent of the overall variance. Wheat genotypes may be characterized and classified using RAPD analysis. These findings will be a benefit in wheat-producing offspring efforts in the future. Keywords. Barley, Genetic variation, RAPD-PCR.

Maintenance of quantitative genetic variance in complex, multitrait phenotypes: the contribution of rare, large effect variants in 2 Drosophila species.

The interaction of evolutionary processes to determine quantitative genetic variation has implications for contemporary and future phenotypic evolution, as well as for our ability to detect causal genetic variants. While theoretical studies have provided robust predictions to discriminate among competing models, empirical assessment of these has been limited. In particular, theory highlights the importance of pleiotropy in resolving observations of selection and mutation, but empirical investigations have typically been limited to few traits. Here, we applied high-dimensional Bayesian Sparse Factor Genetic modeling to gene expression datasets in 2 species, Drosophila melanogaster and Drosophila serrata, to explore the distributions of genetic variance across high-dimensional phenotypic space. Surprisingly, most of the heritable trait covariation was due to few lines (genotypes) with extreme [>3 interquartile ranges (IQR) from the median] values. Intriguingly, while genotypes extreme for a multivariate factor also tended to have a higher proportion of individual traits that were extreme, we also observed genotypes that were extreme for multivariate factors but not for any individual trait. We observed other consistent differences between heritable multivariate factors with outlier lines vs those factors without extreme values, including differences in gene functions. We use these observations to identify further data required to advance our understanding of the evolutionary dynamics and nature of standing genetic variation for quantitative traits.