Estimation of quantitative genetic parameters using marker-inferred relatedness in Japanese flounder: a case study of upward bias

Marker-based methods for estimating heritability have been proposed as an effective means to study quantitative traits in long-lived organisms and natural populations. However, practical examinations to evaluate the usefulness and robustness of a regression method are limited. Using several quantitative traits of Japanese flounder Paralichthys olivaceus, the present study examined the influence of relatedness estimator and population structure on the estimation of heritability and genetic correlation under a regression method with 7 microsatellite loci. Significant heritability and genetic correlation were detected for several quantitative traits in 2 laboratory populations but not in a natural population. In the laboratory populations, upward bias in heritability appeared depending on the relatedness estimators and the populations. Upward bias in heritability increased with decreasing the actual variance of relatedness, suggesting that the estimates of heritability under the regression method tend to be overestimated due to the underestimation of the actual variance of relatedness. Therefore, relationship structure and precise estimation of relatedness are critical for applying this method.     

A MARKER-BASED METHOD FOR INFERENCES ABOUT QUANTITATIVE INHERITANCE IN NATURAL POPULATIONS

A marker-based method for studying quantitative genetic characters in natural populations is presented and evaluated. The method involves regressing quantitative trait similarity on marker-estimated relatedness between individuals. A procedure is first given for estimating the narrow sense heritability and additive genetic correlations among traits, incorporating shared environments. Estimation of the actual variance of relatedness is required for heritability, but not for genetic correlations. The approach is then extended to include isolation by distance of environments, dominance, and shared levels of inbreeding. Investigations of statistical properties show that good estimates do not require great marker polymorphism, but rather require significant variation of actual relatedness; optimal allocation generally favors sampling many individuals at the expense of assaying fewer marker loci; when relatedness declines with physical distance, it is optimal to restrict comparisons to within a certain distance; the power to estimate shared environments and inbreeding effects is reasonable, but estimates of dominance variance may be difficult under certain patterns of relationship; and any linkage of markers to quantitative trait loci does not cause significant problems. This marker-based method makes possible studies with long-lived organisms or with organisms difficult to culture, and opens the possibility that quantitative trait expression in natural environments can be analyzed in an unmanipulative way.     

Using partial genotyping to estimate the genetic and maternal determinants of adaptive traits in a progeny trial of <Emphasis Type="Italic">Fagus sylvatica</Emphasis>

Understanding the determinants of phenotypic variation is critical to evaluate the ability of traits to evolve in a changing environment. In trees, the genetic component of the phenotypic variance is most often estimated based on maternal progeny tests. However, the lack of knowledge about the paternal relatedness hampers the accurate estimation of additive genetic and maternal effects. Here, we investigate how different methods accounting for paternal relatedness allow the estimation of heritability and maternal determinants of adaptive traits in a natural population of Fagus sylvatica L., presenting non-random mating. Twelve potentially adaptive functional traits were measured in 60 maternal families in a nursery. We genotyped a subset of offspring and of all the potentially reproductive adults in the population at 13 microsatellite markers to infer paternal relationships and to estimate average relatedness within and between maternal families. This relatedness information was then used in family and animal models to estimate the components of phenotypic variance. All the studied traits displayed significant genetic variance and moderate heritability. Maternal effects were detected for the diameter increment, stem volume and bud burst. Comparison of family and animal models showed that unbalanced mating system led to only slight departures from maternal family assumptions in the progeny trial. However, neglecting the significant maternal effects led to an overestimation of the heritability. Overall, we highlighted the usefulness of relatedness pattern analyses using polymorphic molecular markers to accurately analyse tree sibling designs.     

Quantifying the genetic component of phenotypic variation in unpedigreed wild plants: tailoring genomic scan for within-population use

The study of adaptive genetic variation in natural populations is central to evolutionary biology. Quantitative genetics methods, however, are hardly applicable to long-lived organisms, and current knowledge on adaptive genetic variation in wild plants mostly refers to annuals and short-lived perennials. Studies on long-lived species are essential to explore possible life-history correlates of genetic variation, selection, and trait heritability. In this paper, we propose a method based on molecular markers to quantify the genetic basis of individual phenotypic differences in wild plants under natural conditions. Rather than focusing on inferring individual relatedness to estimate the heritability of phenotypic traits, we directly estimate the proportion of observed phenotypic variance that is statistically accounted for by genotypic differences between individuals. This is achieved by (i) identifying loci that are correlated across individuals with the phenotypic trait of interest by means of an amplified fragment length polymorphism (AFLP)-based explorative genomic scan, and (ii) fitting multiple regression and linear random effect models to estimate the effects of genotype, environment and genotype × environment on phenotypes. We apply this method to estimate genotypic and environmental effects on cumulative maternal fecundity in a wild population of the long-lived Viola cazorlensis monitored for 20 years. Results show that between 56–63% (depending on estimation method) of phenotypic variance in fecundity is accounted for by genotypic differences in 11 AFLP loci that are significantly related to fecundity. Genotype × environment effects accounted for 38% of fecundity variance, which may help to explain the unexpectedly high levels of genetic variance for fecundity found.     

Marker-based quantitative genetics in the wild?: the heritability and genetic correlation of chemical defenses in eucalyptus

Marker-based methods for estimating heritability and genetic correlation in the wild have attracted interest because traditional methods may be impractical or introduce bias via G x E effects, mating system variation, and sampling effects. However, they have not been widely used, especially in plants. A regression-based approach, which uses a continuous measure of genetic relatedness, promises to be particularly appropriate for use in plants with mixed-mating systems and overlapping generations. Using this method, we found significant narrow-sense heritability of foliar defense chemicals in a natural population of Eucalyptus melliodora. We also demonstrated a genetic basis for the phenotypic correlation underlying an ecological example of conditioned flavor aversion involving different biosynthetic pathways. Our results revealed that heritability estimates depend on the spatial scale of the analysis in a way that offers insight into the distribution of genetic and environmental variance. This study is the first to successfully use a marker-based method to measure quantitative genetic parameters in a tree. We suggest that this method will prove to be a useful tool in other studies and offer some recommendations for future applications of the method.     

Identity-by-descent-based heritability analysis in the Northern Finland Birth Cohort

For most complex traits, only a small proportion of heritability is explained by statistically significant associations from genome-wide association studies (GWAS). In order to determine how much heritability can potentially be explained through larger GWAS, several different approaches for estimating total narrow-sense heritability from GWAS data have recently been proposed. These methods include variance components with relatedness estimates from allele-sharing, variance components with relatedness estimates from identity-by-descent (IBD) segments, and regression of phenotypic correlation on relatedness estimates from IBD segments. These methods have not previously been compared on real or simulated data. We analyze the narrow-sense heritability of nine metabolic traits in the Northern Finland Birth Cohort (NFBC) using these methods. We find substantial estimated heritability for several traits, including LDL cholesterol (54 % heritability), HDL cholesterol (46 % heritability), and fasting glucose levels (39 % heritability). Estimates of heritability from the regression-based approach are much lower than variance component estimates in these data, which may be due to the presence of strong population structure. We also investigate the accuracy of the competing approaches using simulated phenotypes based on genotype data from the NFBC. The simulation results substantiate the downward bias of the regression-based approach in the presence of population structure.     

Consistency between marker- and genealogy-based heritability estimates in an experimental stand of Prosopis alba (Leguminosae)

Prosopis represents a valuable forest resource in arid and semiarid regions. Management of promising species requires information about genetic parameters, mainly the heritability (h(2)) of quantitative profitable traits. This parameter is traditionally estimated from progeny tests or half-sib analysis conducted in experimental stands. Such an approach estimates h(2) from the ratio of between-family/total phenotypic variance. These analyses are difficult to apply to natural populations of species with a long life cycle, overlapping generations, and a mixed mating system, without genealogical information. A promising alternative is the use of molecular marker information to infer relatedness between individuals and to estimate h(2) from the regression of phenotypic similarity on inferred relatedness. In the current study we compared h(2) of 13 quantitative traits estimated by these two methods in an experimental stand of P. alba, where genealogical information was available. We inferred pairwise relatedness by Ritland's method using six microsatellite loci. Relatedness and heritability estimates from molecular information were highly correlated to the values obtained from genealogical data. Although Ritland's method yields lower h(2) estimates and tends to overestimate genetic correlations between traits, this approach is useful to predict the expected relative gain of different quantitative traits under selection without genealogical information.     

Selection and genetic (co)variance in bighorn sheep

Genetic theory predicts that directional selection should deplete additive genetic variance for traits closely related to fitness, and may favor the maintenance of alleles with antagonistically pleiotropic effects on fitness-related traits. Trait heritability is therefore expected to decline with the degree of association with fitness, and some genetic correlations between selected traits are expected to be negative. Here we demonstrate a negative relationship between trait heritability and association with lifetime reproductive success in a wild population of bighorn sheep (Ovis canadensis) at Ram Mountain, Alberta, Canada. Lower heritability for fitness-related traits, however, was not wholly a consequence of declining genetic variance, because those traits showed high levels of residual variance. Genetic correlations estimated between pairs of traits with significant heritability were positive. Principal component analyses suggest that positive relationships between morphometric traits constitute the main axis of genetic variation. Trade-offs in the form of negative genetic or phenotypic correlations among the traits we have measured do not appear to constrain the potential for evolution in this population.     

Field heritability of a plant adaptation to fire in heterogeneous landscapes

The strong association observed between fire regimes and variation in plant adaptations to fire suggests a rapid response to fire as an agent of selection. It also suggests that fire‐related traits are heritable, a precondition for evolutionary change. One example is serotiny, the accumulation of seeds in unopened fruits or cones until the next fire, an important strategy for plant population persistence in fire‐prone ecosystems. Here, we evaluate the potential of this trait to respond to natural selection in its natural setting. For this, we use a SNP marker approach to estimate genetic variance and heritability of serotiny directly in the field for two Mediterranean pine species. Study populations were large and heterogeneous in climatic conditions and fire regime. We first estimated the realized relatedness among trees from genotypes, and then partitioned the phenotypic variance in serotiny using Bayesian animal models that incorporated environmental predictors. As expected, field heritability was smaller (around 0.10 for both species) than previous estimates under common garden conditions (0.20). An estimate on a subset of stands with more homogeneous environmental conditions was not different from that in the complete set of stands, suggesting that our models correctly captured the environmental variation at the spatial scale of the study. Our results highlight the importance of measuring quantitative genetic parameters in natural populations, where environmental heterogeneity is a critical aspect. The heritability of serotiny, although not high, combined with high phenotypic variance within populations, confirms the potential of this fire‐related trait for evolutionary change in the wild.     

Intra-population comparison of vegetative and floral trait heritabilities estimated from molecular markers in wild Aquilegia populations

Measuring heritable genetic variation is important for understanding patterns of trait evolution in wild populations, and yet studies of quantitative genetic parameters estimated directly in the field are limited by logistic constraints, such as the difficulties of inferring relatedness among individuals in the wild. Marker-based approaches have received attention because they can potentially be applied directly to wild populations. For long-lived, self-compatible plant species where pedigrees are inadequate, the regression-based method proposed by Ritland has the appeal of estimating heritabilities from marker-based estimates of relatedness. The method has been difficult to implement in some plant populations, however, because it requires significant variance in relatedness across the population. Here, we show that the method can be readily applied to compare the ability of different traits to respond to selection, within populations. For several taxa of the perennial herb genus Aquilegia, we estimated heritabilities of floral and vegetative traits and, combined with estimates of natural selection, compared the ability to respond to selection of both types of traits under current conditions. The intra-population comparisons showed that vegetative traits have a higher potential for evolution, because although they are as heritable as floral traits, selection on them is stronger. These patterns of potential evolution are consistent with macroevolutionary trends in the European lineage of the genus.     

The role of genetic constraints on the diversification of Iberian taxa of the genus Aquilegia (Ranunculaceae)

The microevolutionary process of adaptive phenotypic differentiation of quantitative traits between populations or closely‐related taxa depends on the response of populations to the action of natural selection. However, this response can be constrained by the structure of the matrix of additive genetic variance and covariance between traits in each population ( G matrix). In the present study, we obtained additive genetic variance and narrow sense heritability for 25 floral and vegetative traits of three subspecies of Aquilegia vulgaris, and one subspecies of Aquilegia pyrenaica through a common garden crossing experiment. For two vegetative and one floral trait, we also obtained the G matrix and genetic correlations between traits in each subspecies. The amount of genetic variation available in wild populations is not responsible for the larger differentiation of vegetative than floral traits found in this group of columbines. However, the low heritability of some traits constrained their evolution because phenotypic variability among taxa was larger for traits with larger heritability. We confirmed that the process of diversification of the studied taxa involved shifts in the G matrix, mainly determined by changes in the genetic covariance between floral and vegetative traits, probably caused by linkage disequilibrium in narrow endemic taxa. © 2013 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111 , 252–261.     

Small‐scale spatial variation in evolvability for life‐history traits in the storm petrel

The evolutionary potential in the timing of recruitment and reproduction may be crucial for the ability of populations to buffer against environmental changes, allowing them to avoid unfavourable breeding conditions. The evolution of a trait in a local population is determined by its heritability and selection. In the present study, we performed pedigree‐based quantitative genetic analyses for two life‐history traits (recruiting age and laying date) using population data of the storm petrel over an 18‐year period in two adjacent breeding colonies (only 150 m apart) that share the same environmental conditions. In both traits, natal colony effect was the main source of the phenotypic variation among individuals, and cohort variance for recruitment age and additive genetic variance for laying date were natal colony‐specific. We found significant heritability only in laying date and, more specifically, only in birds born in one of the colonies. The difference in genetic variance between the colonies was statistically significant. Interestingly, selection on earlier breeding birds was detected only in the colony in which heritable variation in laying date was found. Therefore, local evolvability for a life‐history trait may vary within a unexpectedly small spatial scale, through the diversifying natural selection and insulating gene flow. © 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, 106 , 439–446.     

皂荚南方天然群体种实表型多样性

以系统揭示表型变异程度和变异规律为目的, 对皂荚(Gleditsia sinensis)南方分布区的10个天然群体的11个种实性状进行了比较分析。采用方差分析、多重比较、相关分析等多种分析方法, 对群体间和群体内的表型多样性以及与地理、环境因子的相关性进行了讨论。方差分析结果表明; 皂荚果实、种子等性状在群体间和群体内存在丰富的变异, 11个性状在群体间、群体内均达显著差异; 荚果性状在群体间和群体内的变异均大于种子性状, 11个性状的平均表型分化系数为20.42%, 群体内的变异(32.28%)大于群体间的变异(7.19%), 群体内的变异是皂荚的主要变异来源; 皂荚各性状平均变异系数为11.20%, 变异幅度为4.55%-18.38%。群体间荚果的变异(14.75%)高于群体间种子变异(6.95%), 表明种子变异稳定性高。荚果和种子各性状之间多呈极显著或显著正相关, 表现为荚果越大, 则种子越大, 种子的千粒重也越大; 荚果表现为同地理经度的南北变异, 种子则表现为同地理纬度的东西变异。研究结果为进一步开展皂荚遗传育种、保护生物学研究和皂荚种质资源利用奠定了基础。     

Quantitative analysis of correlations among flower traits in Gerbera hybrida, Compositae. III. Genetic variability and structure of principal component traits

 A sample of 36 flower traits consisting of six morphological categories in the Davis population of gerbera was restructured into phenotypic and genetic principal component traits. The first 5 phenotypic principal component traits accounted for 62% of the total phenotypic variance of the 36 traits and have moderate to high heritablities. The first 5 genetic principal component traits account for 97% of total genetic variance and all have high heritability. Morphological structure of these component traits suggest an underlying process identified by the first genetic principal component involving largely trans and disk floret traits. The results of this study indicate that the quantitative genetic structure of the gerbera flower is controlled by a few independent components and that principal component analysis is a useful tool to reveal variation in this structure. These composite traits are heritable and are expected to respond to selection. Received: 20 September 1997 / Accepted: 19 January 1998     

Pedigree-free animal models: the relatedness matrix reloaded

Animal models typically require a known genetic pedigree to estimate quantitative genetic parameters. Here we test whether animal models can alternatively be based on estimates of relatedness derived entirely from molecular marker data. Our case study is the morphology of a wild bird population, for which we report estimates of the genetic variance-covariance matrices (G) of six morphological traits using three methods: the traditional animal model; a molecular marker-based approach to estimate heritability based on Ritland's pairwise regression method; and a new approach using a molecular genealogy arranged in a relatedness matrix (R) to replace the pedigree in an animal model. Using the traditional animal model, we found significant genetic variance for all six traits and positive genetic covariance among traits. The pairwise regression method did not return reliable estimates of quantitative genetic parameters in this population, with estimates of genetic variance and covariance typically being very small or negative. In contrast, we found mixed evidence for the use of the pedigree-free animal model. Similar to the pairwise regression method, the pedigree-free approach performed poorly when the full-rank R matrix based on the molecular genealogy was employed. However, performance improved substantially when we reduced the dimensionality of the R matrix in order to maximize the signal to noise ratio. Using reduced-rank R matrices generated estimates of genetic variance that were much closer to those from the traditional model. Nevertheless, this method was less reliable at estimating covariances, which were often estimated to be negative. Taken together, these results suggest that pedigree-free animal models can recover quantitative genetic information, although the signal remains relatively weak. It remains to be determined whether this problem can be overcome by the use of a more powerful battery of molecular markers and improved methods for reconstructing genealogies.     

浙江楠种群表型变异

以探讨浙江楠(Phoebe chekiangensis)种群间和种群内的表型变异程度和变异规律为目的, 对其分布区9个种群的10个表型性状进行了研究。采用巢式方差分析、变异系数、多重比较和相关分析等多种分析方法, 对种群间和种群内的表型多样性及其与地理生态因子的相关性进行了讨论。研究结果表明: 浙江楠叶片、种子等表型性状在种群间和种群内均存在着丰富的变异, 10个性状在种群间、种群内的差异均达极显著水平; 种群内的变异(21.74%)大于种群间的变异(18.45%), 表型性状的平均分化系数为41.43%, 种群内变异是浙江楠表型变异的主要变异来源。各性状平均变异系数为12.78%, 变化幅度为6.50%-19.38%。种群间叶片的平均变异系数(16.99%)高于种群间种子的平均变异系数(8.58%), 表明种子的稳定性高于叶片。叶宽、叶面积与叶片其他性状间多呈显著或极显著相关, 种子千粒重与种子宽、种子体积显著正相关; 而种子和叶片的各性状间多无显著相关性。种子宽、种子体积和种子千粒重随着海拔的增加出现减小的趋势, 种子体积受纬度控制, 随着纬度的增大表现出增大的趋势。     

EVOLUTIONARY PREDICTABILITY IN NATURAL POPULATIONS: DO MATING SYSTEM AND NONADDITIVE GENETIC VARIANCE INTERACT TO AFFECT HERITABILITIES IN PLANTAGO LANCEOLATA?

Quantitative genetics has been an immensely powerful tool in manipulating the phenotypes of domesticated plants and animals. Much of the predictive power of quantitative genetics depends on the breeder's control over the context in which phenotype and mating are being expressed. In the natural world, these contexts are often difficult to describe, let alone control. We are left, therefore, with a poor understanding of the limits of quantitative genetics in natural populations. One of the crucial contextual elements for assessing breeding value is the genetic background in which an individual's genes are being assessed. When interacting genes are polymorphic within a population, the degree of mating among relatives can influence the correlations among mates and the predictions of a response to selection. Population structure can strongly influence the degree to which dominance and epistasis influences additive genetic variance and heritability. The extent of inbreeding can also influence heritabilities through its effect on the environmental component of phenotypic variance. The applicability of standard quantitative genetic breeding designs to the measurement of heritabilities in natural populations therefore depends in part on: (1) the mating system of the population; and (2) the importance of gene interactions in determining phenotypic variation. We tested for an effect of mating structure on the partitioning of phenotypic variance and heritability by comparing two breeding designs in a common environment. Both breeding designs used 139 pollen parents taken from mapped locations in a population of Plantago lanceolata L., and crossed to 280 seed parents from the same population. One design was random-mating, the second was biased toward near-neighbor matings to an extent determined by field measure of pollen-mediated gene flow distances. The offspring were grown randomly mixed in a common garden. Nine traits were measured: central corm diameter, number of leaves, area of the most recently fully expanded leaf, density of hairs (cm^-2) on the leaves, dry weight per unit leaf area, photosynthetic capacity, transpiration rates, water use efficiency, and reproductive dry weight. Heritabilities and variance components from the two designs were compared using randomization tests. None of the variance components or the heritabilities differed significantly between breeding designs at the 0.05 level. The test could distinguish differences between the heritabilities measured in the two breeding designs as small as 0.11, on average. Thus, for the degree of inbreeding normally exhibited in P. lanceolata there is insufficient gene interaction present within populations to influence the partitioning of variance between additive and nonadditive components or to influence heritability estimates to a meaningful extent. We suggest that for Plantago other sources of variation in heritability estimates, such as maternal effects and genotype × environment interactions, are more important influences than the interaction between inbreeding and gene interactions, and standard heritability estimate based on random breeding is as accurate as one taking the natural mating structure into account.     

Seasonal variation in the nutritional value of woody plants along a natural gradient in Eastern Africa

Several hypotheses relate a negative relationship between foliar concentration of phenolic compounds and nitrogen to physiological processes such as leaf development, seasonal variation in allocation priorities, nutrient, light and water related growth limitation, as well as herbivore attack. We sampled four common deciduous woody species of central Tanzania monthly during the growing season to assess changes in this relation and their nutritional value to ruminants. We found a negative relationship between leaf N and phenolic compounds within and among species and sites that weakens during the course of the growing season that was consistent for total phenolics, but not for condensed tannins. Leaf N concentration decreased throughout the season, its withdrawal being positively related with leaf N at first sampling date. Secondary compounds concentration showed no consistent seasonal trend. Concentrations of leaf N and phenolics were correlated with ¹³C discrimination in the two shrub species and with soil P in the two tree species. Digestibility was positively correlated with foliar N and negatively correlated with secondary compounds. We conclude that phenolic compounds may serve as reliable clues for selecting foliage rich in N at site and species level only during the first months of the growing season.     

RAD‐sequencing for estimating genomic relatedness matrix‐based heritability in the wild: A case study in roe deer

Estimating the evolutionary potential of quantitative traits and reliably predicting responses to selection in wild populations are important challenges in evolutionary biology. The genomic revolution has opened up opportunities for measuring relatedness among individuals with precision, enabling pedigree‐free estimation of trait heritabilities in wild populations. However, until now, most quantitative genetic studies based on a genomic relatedness matrix (GRM) have focused on long‐term monitored populations for which traditional pedigrees were also available, and have often had access to knowledge of genome sequence and variability. Here, we investigated the potential of RAD‐sequencing for estimating heritability in a free‐ranging roe deer (Capreolous capreolus) population for which no prior genomic resources were available. We propose a step‐by‐step analytical framework to optimize the quality and quantity of the genomic data and explore the impact of the single nucleotide polymorphism (SNP) calling and filtering processes on the GRM structure and GRM‐based heritability estimates. As expected, our results show that sequence coverage strongly affects the number of recovered loci, the genotyping error rate and the amount of missing data. Ultimately, this had little effect on heritability estimates and their standard errors, provided that the GRM was built from a minimum number of loci (above 7,000). Genomic relatedness matrix‐based heritability estimates thus appear robust to a moderate level of genotyping errors in the SNP data set. We also showed that quality filters, such as the removal of low‐frequency variants, affect the relatedness structure of the GRM, generating lower h² estimates. Our work illustrates the huge potential of RAD‐sequencing for estimating GRM‐based heritability in virtually any natural population.     

太白杜鹃天然居群的表型多样性

为揭示太白杜鹃(Rhododendron purdomii)天然居群的表型变异程度、变异规律,以秦岭山区的7个天然居群为研究对象,对其花序和叶片的10个数量性状和8个质量性状进行方差分析、相关分析与聚类分析,探讨居群间与居群内表型多样性的变异特点。结果显示:(1)在太白杜鹃的质量性状中,花色与花瓣内斑在居群间与居群内均存在丰富变异,花朵香味、花序形状、花冠形状、花梗颜色、叶片形状和株型等仅在居群间存在明显变异,在居群内则趋于一致性;其数量性状在居群间与居群内也存在广泛变异,10个数量性状在居群间和居群内平均值差异全部达显著水平;在7个居群内数量性状的变异系数为0～55.3%,其中花梗长、花丝长、花瓣宽与叶柄长变异较大,花朵数变异较小。(2)相关性分析表明,太白杜鹃花瓣长和花瓣宽分别与经度存在极显著与显著负相关关系,叶片长、叶片宽和叶片长宽比与海拔均存在显著负相关关系,而其它性状与地理因子的关系密切。(3)聚类分析显示,太白杜鹃的7个天然居群可以初步分为两大类,但性状的表型特征并没有依地理距离而聚类。研究表明,太白杜鹃天然居群的表型性状在居群内与居群间均存在丰富的变异,而且其与居群特点、分布生境等关系密切。