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.     

The influence of nonrandom extra‐pair paternity on heritability estimates derived from wild pedigrees

Quantitative genetic analysis is often fundamental for understanding evolutionary processes in wild populations. Avian populations provide a model system due to the relative ease of inferring relatedness among individuals through observation. However, extra‐pair paternity (EPP) creates erroneous links within the social pedigree. Previous work has suggested this causes minor underestimation of heritability if paternal misassignment is random and hence not influenced by the trait being studied. Nevertheless, much literature suggests numerous traits are associated with EPP and the accuracy of heritability estimates for such traits remains unexplored. We show analytically how nonrandom pedigree errors can influence heritability estimates. Then, combining empirical data from a large great tit (Parus major) pedigree with simulations, we assess how heritability estimates derived from social pedigrees change depending on the mode of the relationship between EPP and the focal trait. We show that the magnitude of the underestimation is typically small (<15%). Hence, our analyses suggest that quantitative genetic inference from pedigrees derived from observations of social relationships is relatively robust; our approach also provides a widely applicable method for assessing the consequences of nonrandom EPP.     

Heritability of resting metabolic rate in a wild population of blue tits

We report the first study with the aim to estimate heritability in a wild population, a nest box breeding population of blue tits. We estimated heritability as well as genetic and phenotypic correlations of resting metabolic rate (RMR), body mass and tarsus length with an animal model based on data from a split cross‐fostering experiment with brood size manipulations. RMR and body mass, but not tarsus length, showed significant levels of explained variation but for different underlying reasons. In body mass, the contribution to the explained variation is mainly because of a strong brood effect, while in RMR it is mainly because of a high heritability. The additive variance in RMR was significant and the heritability was estimated to 0.59. The estimates of heritability of body mass (0.08) and tarsus length (0.00) were both low and based on nonsignificant additive variances. Thus, given the low heritability (and additive variances) in body mass and tarsus length the potential for direct selection on RMR independent of the two traits is high in this population. However, the strong phenotypic correlation between RMR and mass (0.643 ± 0.079) was partly accounted for by a potentially strong, although highly uncertain, genetic correlation (1.178 ± 0.456) between the two traits. This indicates that the additive variance of body mass, although low, might still somewhat constrain the independent evolvability of RMR.     

Molecular and pedigree measures of relatedness provide similar estimates of inbreeding depression in a bottlenecked population

Individual‐based estimates of the degree of inbreeding or parental relatedness from pedigrees provide a critical starting point for studies of inbreeding depression, but in practice wild pedigrees are difficult to obtain. Because inbreeding increases the proportion of genomewide loci that are identical by descent, inbreeding variation within populations has the potential to generate observable correlations between heterozygosity measured using molecular markers and a variety of fitness related traits. Termed heterozygosity‐fitness correlations (HFCs), these correlations have been observed in a wide variety of taxa. The difficulty of obtaining wild pedigree data, however, means that empirical investigations of how pedigree inbreeding influences HFCs are rare. Here, we assess evidence for inbreeding depression in three life‐history traits (hatching and fledging success and juvenile survival) in an isolated population of Stewart Island robins using both pedigree‐ and molecular‐derived measures of relatedness. We found results from the two measures were highly correlated and supported evidence for significant but weak inbreeding depression. However, standardized effect sizes for inbreeding depression based on the pedigree‐based kin coefficients (k) were greater and had smaller standard errors than those based on molecular genetic measures of relatedness (RI), particularly for hatching and fledging success. Nevertheless, the results presented here support the use of molecular‐based measures of relatedness in bottlenecked populations when information regarding inbreeding depression is desired but pedigree data on relatedness are unavailable.     

Estimating quantitative genetic parameters in wild populations: a comparison of pedigree and genomic approaches

The estimation of quantitative genetic parameters in wild populations is generally limited by the accuracy and completeness of the available pedigree information. Using relatedness at genomewide markers can potentially remove this limitation and lead to less biased and more precise estimates. We estimated heritability, maternal genetic effects and genetic correlations for body size traits in an unmanaged long‐term study population of Soay sheep on St Kilda using three increasingly complete and accurate estimates of relatedness: (i) Pedigree 1, using observation‐derived maternal links and microsatellite‐derived paternal links; (ii) Pedigree 2, using SNP‐derived assignment of both maternity and paternity; and (iii) whole‐genome relatedness at 37 037 autosomal SNPs. In initial analyses, heritability estimates were strikingly similar for all three methods, while standard errors were systematically lower in analyses based on Pedigree 2 and genomic relatedness. Genetic correlations were generally strong, differed little between the three estimates of relatedness and the standard errors declined only very slightly with improved relatedness information. When partitioning maternal effects into separate genetic and environmental components, maternal genetic effects found in juvenile traits increased substantially across the three relatedness estimates. Heritability declined compared to parallel models where only a maternal environment effect was fitted, suggesting that maternal genetic effects are confounded with direct genetic effects and that more accurate estimates of relatedness were better able to separate maternal genetic effects from direct genetic effects. We found that the heritability captured by SNP markers asymptoted at about half the SNPs available, suggesting that denser marker panels are not necessarily required for precise and unbiased heritability estimates. Finally, we present guidelines for the use of genomic relatedness in future quantitative genetics studies in natural populations.     

Quantitative genetic parameters for wild stream‐living brown trout: heritability and parental effects

Adaptability depends on the presence of additive genetic variance for important traits. Yet few estimates of additive genetic variance and heritability are available for wild populations, particularly so for fishes. Here, we estimate heritability of length‐at‐age for wild‐living brown trout (Salmo trutta), based on long‐term mark‐recapture data and pedigree reconstruction based on large‐scale genotyping at 15 microsatellite loci. We also tested for the presence of maternal and paternal effects using a Bayesian version of the Animal model. Heritability varied between 0.16 and 0.31, with reasonable narrow confidence bands, and the total phenotypic variance increased with age. When introducing dam as an additional random effect (accounting for c. 7% of total phenotypic variance), the level of additive genetic variance and heritability decreased (0.12–0.21). Parental size (both for sires and for dams) positively influenced length‐at‐age for juvenile trout – either through direct parental effects or through genotype‐environment correlations. Length‐at‐age is a complex trait reflecting the effects of a number of physiological, behavioural and ecological processes. Our data show that fitness‐related traits such as length‐at‐age can retain high levels of additive genetic variance even when total phenotypic variance is high.     

Gene flow does not prevent personality and morphological differentiation between two blue tit populations

Understanding the causes and consequences of population phenotypic divergence is a central goal in ecology and evolution. Phenotypic divergence among populations can result from genetic divergence, phenotypic plasticity or a combination of the two. However, few studies have deciphered these mechanisms for populations geographically close and connected by gene flow, especially in the case of personality traits. In this study, we used a common garden experiment to explore the genetic basis of the phenotypic divergence observed between two blue tit (Cyanistes caeruleus) populations inhabiting contrasting habitats separated by 25 km, for two personality traits (exploration speed and handling aggression), one physiological trait (heart rate during restraint) and two morphological traits (tarsus length and body mass). Blue tit nestlings were removed from their population and raised in a common garden for up to 5 years. We then compared adult phenotypes between the two populations, as well as trait‐specific Q_st and F_st. Our results revealed differences between populations similar to those found in the wild, suggesting a genetic divergence for all traits. Q_st–F_st comparisons revealed that the trait divergences likely result from dissimilar selection patterns rather than from genetic drift. Our study is one of the first to report a Q_st–F_st comparison for personality traits and adds to the growing body of evidence that population genetic divergence is possible at a small scale for a variety of traits including behavioural traits.     

Genetic background,and not ontogenetic effects,affects avian seasonal timing of reproduction

Avian seasonal timing is a life‐history trait with important fitness consequences and which is currently under directional selection due to climate change. To predict micro‐evolution in this trait, it is crucial to properly estimate its heritability. Heritabilities are often estimated from pedigreed wild populations. As these are observational data, it leaves the possibility that the resemblance between related individuals is not due to shared genes but to ontogenetic effects; when the environment for the offspring provided by early laying pairs differs from that by late pairs and the laying dates of these offspring when they reproduce themselves is affected by this environment, this may lead to inflated heritability estimates. Using simulation studies, we first tested whether and how much such an early environmental effect can inflate heritability estimates from animal models, and we showed that pedigree structure determines by how much early environmental effects inflate heritability estimates. We then used data from a wild population of great tits (Parus major) to compare laying dates of females born early in the season in first broods and from sisters born much later, in second broods. These birds are raised under very different environmental conditions but have the same genetic background. The laying dates of first and second brood offspring do not differ when they reproduce themselves, clearly showing that ontogenetic effects are very small and hence, family resemblance in timing is due to genes. This finding is essential for the interpretation of the heritabilities reported from wild populations and for predicting micro‐evolution in response to climate change.     

Contrasting results from GWAS and QTL mapping on wing length in great reed warblers

A major goal in evolutionary biology is to understand the genetic basis of adaptive traits. In migratory birds, wing morphology is such a trait. Our previous work on the great reed warbler (Acrocephalus arundinaceus) shows that wing length is highly heritable and under sexually antagonistic selection. Moreover, a quantitative trait locus (QTL) mapping analysis detected a pronounced QTL for wing length on chromosome 2, suggesting that wing morphology is partly controlled by genes with large effects. Here, we re‐evaluate the genetic basis of wing length in great reed warblers using a genomewide association study (GWAS) approach based on restriction site‐associated DNA sequencing (RADseq) data. We use GWAS models that account for relatedness between individuals and include covariates (sex, age and tarsus length). The resulting association landscape was flat with no peaks on chromosome 2 or elsewhere, which is in line with expectations for polygenic traits. Analysis of the distribution of p‐values did not reveal biases, and the inflation factor was low. Effect sizes were however not uniformly distributed on some chromosomes, and the Z chromosome had weaker associations than autosomes. The level of linkage disequilibrium (LD) in the population decayed to background levels within c. 1 kbp. There could be several reasons to why our QTL study and GWAS gave contrasting results including differences in how associations are modelled (cosegregation in pedigree vs. LD associations), how covariates are accounted for in the models, type of marker used (multi‐ vs. biallelic), difference in power or a combination of these. Our study highlights that the genetic architecture even of highly heritable traits is difficult to characterize in wild populations.     

How do misassigned paternities affect the estimation of heritability in the wild?

Studies of birds have recently played an important role in the increasing success of quantitative genetics applied to natural populations. However, these studies mostly base their pedigree relationships on social information, despite the known widespread genetic polygamy in avian species. Here, we study the influence of misassigned paternities, combined with the effect of pedigree size and depth, on the estimation of heritability. First, we compute simulations of a polygenic trait for two levels of heritability (0.1 and 0.4), several extra-pair paternity rates (ranging from 5% to 40%), and varying sample sizes (20, 50 and 100 broods) or pedigree depth (2 or 4 generations). We compare heritability estimates from the social and the genetic pedigree, running a restricted maximum-likelihood 'animal model'. Social pedigree underestimates heritability by an average of 0-17% for 5-20% extra-pair paternities and by up to 18% for 40% extra-pair paternities and a heritability of 0.4. Second, we identifyied extra-pair offspring using microsatellite loci in two populations of blue tits (Parus caeruleus) showing high levels of extra-pair paternities (15% and 25% of extra-pair offspring). We compare heritabilities of tarsus length and body mass estimated with pedigrees of increasing accuracy. These analyses suggest that the bias induced by misassigned paternities on heritability estimation depends on the level of heritability and the rate of paternity error. Typical rates of extra-pair paternities in birds (around 20% of offspring) should result in an underestimation of heritability of less than 15% when estimated over a minimum of 100 broods.     

Genomic dissection of variation in clutch size and egg mass in a wild great tit (Parus major) population

Clutch size and egg mass are life history traits that have been extensively studied in wild bird populations, as life history theory predicts a negative trade‐off between them, either at the phenotypic or at the genetic level. Here, we analyse the genomic architecture of these heritable traits in a wild great tit (Parus major) population, using three marker‐based approaches – chromosome partitioning, quantitative trait locus (QTL) mapping and a genome‐wide association study (GWAS). The variance explained by each great tit chromosome scales with predicted chromosome size, no location in the genome contains genome‐wide significant QTL, and no individual SNPs are associated with a large proportion of phenotypic variation, all of which may suggest that variation in both traits is due to many loci of small effect, located across the genome. There is no evidence that any regions of the genome contribute significantly to both traits, which combined with a small, nonsignificant negative genetic covariance between the traits, suggests the absence of genetic constraints on the independent evolution of these traits. Our findings support the hypothesis that variation in life history traits in natural populations is likely to be determined by many loci of small effect spread throughout the genome, which are subject to continued input of variation by mutation and migration, although we cannot exclude the possibility of an additional input of major effect genes influencing either trait.     

Heritability of interpack aggression in a wild pedigreed population of North American grey wolves

Aggression is a quantitative trait deeply entwined with individual fitness. Mapping the genomic architecture underlying such traits is complicated by complex inheritance patterns, social structure, pedigree information and gene pleiotropy. Here, we leveraged the pedigree of a reintroduced population of grey wolves (Canis lupus) in Yellowstone National Park, Wyoming, USA, to examine the heritability of and the genetic variation associated with aggression. Since their reintroduction, many ecological and behavioural aspects have been documented, providing unmatched records of aggressive behaviour across multiple generations of a wild population of wolves. Using a linear mixed model, a robust genetic relationship matrix, 12,288 single nucleotide polymorphisms (SNPs) and 111 wolves, we estimated the SNP‐based heritability of aggression to be 37% and an additional 14% of the phenotypic variation explained by shared environmental exposures. We identified 598 SNP genotypes from 425 grey wolves to resolve a consensus pedigree that was included in a heritability analysis of 141 individuals with SNP genotype, metadata and aggression data. The pedigree‐based heritability estimate for aggression is 14%, and an additional 16% of the phenotypic variation was explained by shared environmental exposures. We find strong effects of breeding status and relative pack size on aggression. Through an integrative approach, these results provide a framework for understanding the genetic architecture of a complex trait that influences individual fitness, with linkages to reproduction, in a social carnivore. Along with a few other studies, we show here the incredible utility of a pedigreed natural population for dissecting a complex, fitness‐related behavioural trait.     

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.     

Inferences of genetic architecture of bill morphology in house sparrow using a high‐density SNP array point to a polygenic basis

Understanding the genetic architecture of quantitative traits can provide insights into the mechanisms driving phenotypic evolution. Bill morphology is an ecologically important and phenotypically variable trait, which is highly heritable and closely linked to individual fitness. Thus, bill morphology traits are suitable candidates for gene mapping analyses. Previous studies have revealed several genes that may influence bill morphology, but the similarity of gene and allele effects between species and populations is unknown. Here, we develop a custom 200K SNP array and use it to examine the genetic basis of bill morphology in 1857 house sparrow individuals from a large‐scale, island metapopulation off the coast of Northern Norway. We found high genomic heritabilities for bill depth and length, which were comparable with previous pedigree estimates. Candidate gene and genomewide association analyses yielded six significant loci, four of which have previously been associated with craniofacial development. Three of these loci are involved in bone morphogenic protein (BMP) signalling, suggesting a role for BMP genes in regulating bill morphology. However, these loci individually explain a small amount of variance. In combination with results from genome partitioning analyses, this indicates that bill morphology is a polygenic trait. Any studies of eco‐evolutionary processes in bill morphology are therefore dependent on methods that can accommodate polygenic inheritance of the phenotype and molecular‐scale evolution of genetic architecture.     

Multivariate selection and intersexual genetic constraints in a wild bird population

When selection differs between the sexes for traits that are genetically correlated between the sexes, there is potential for the effect of selection in one sex to be altered by indirect selection in the other sex, a situation commonly referred to as intralocus sexual conflict (ISC). While potentially common, ISC has rarely been studied in wild populations. Here, we studied ISC over a set of morphological traits (wing length, tarsus length, bill depth and bill length) in a wild population of great tits (Parus major) from Wytham Woods, UK. Specifically, we quantified the microevolutionary impacts of ISC by combining intra‐ and intersex additive genetic (co)variances and sex‐specific selection estimates in a multivariate framework. Large genetic correlations between homologous male and female traits combined with evidence for sex‐specific multivariate survival selection suggested that ISC could play an appreciable role in the evolution of this population. Together, multivariate sex‐specific selection and additive genetic (co)variance for the traits considered accounted for additive genetic variance in fitness that was uncorrelated between the sexes (cross‐sex genetic correlation = ?0.003, 95% CI = ?0.83, 0.83). Gender load, defined as the reduction in a population's rate of adaptation due to sex‐specific effects, was estimated at 50% (95% CI = 13%, 86%). This study provides novel insights into the evolution of sexual dimorphism in wild populations and illustrates how quantitative genetics and selection analyses can be combined in a multivariate framework to quantify the microevolutionary impacts of ISC.     

Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations

Currently, there is much debate on the genetic architecture of quantitative traits in wild populations. Is trait variation influenced by many genes of small effect or by a few genes of major effect? Where is additive genetic variation located in the genome? Do the same loci cause similar phenotypic variation in different populations? Great tits (Parus major) have been studied extensively in long‐term studies across Europe and consequently are considered an ecological ‘model organism’. Recently, genomic resources have been developed for the great tit, including a custom SNP chip and genetic linkage map. In this study, we used a suite of approaches to investigate the genetic architecture of eight quantitative traits in two long‐term study populations of great tits—one in the Netherlands and the other in the United Kingdom. Overall, we found little evidence for the presence of genes of large effects in either population. Instead, traits appeared to be influenced by many genes of small effect, with conservative estimates of the number of contributing loci ranging from 31 to 310. Despite concordance between population‐specific heritabilities, we found no evidence for the presence of loci having similar effects in both populations. While population‐specific genetic architectures are possible, an undetected shared architecture cannot be rejected because of limited power to map loci of small and moderate effects. This study is one of few examples of genetic architecture analysis in replicated wild populations and highlights some of the challenges and limitations researchers will face when attempting similar molecular quantitative genetic studies in free‐living populations.     

Investigating the genetic and environmental architecture of interpack aggression in North American grey wolves

Aggression confers several fitness benefits including increased breeding opportunities and resource acquisition. Determining the relative contributions of genetic and environmental components to shaping aggression is essential for advancing our understanding of how selection affects the distribution of aggressive phenotypes in a population. In a From the Cover article in this issue of Molecular Ecology, vonHoldt et al. (2020) used RAD‐seq methods to obtain genome‐wide single nucleotide polymorphism (SNP) data to estimate heritability of interpack aggression of 141 North American grey wolves (Canis lupus) surveyed from 1995–2018. The authors inferred heritability using both a SNP‐based genetic relationship matrix (GRM) and a consensus pedigree informed by: (a) previously obtained microsatellite data; (b) past observations of parentage; and (c) statistical reconstruction of parent‐offspring pairs. SNP‐based (i.e., GRM) and pedigree‐based (i.e., consensus pedigree) heritability estimates were 37% and 14%, respectively, with an additional 14%–16% explained by natal pack effects. The study confirmed the previously discovered strong effects of relative pack size and breeding status on interpack aggression, illustrating how social dynamics and density‐dependent factors induce variance in aggressive behaviours. Finally, the authors found associations between average individual aggression scores (IAS) and specific candidate genes (MY09A and TRAK1). In sum, vonHoldt et al. (2020) provides an unprecedented and nuanced synthesis that not only suggests gene‐aggression associations, but also emphasizes how additive genetic variance and density‐dependent factors interact to maintain phenotypic variance in aggression over time.     

Resistance to oxidative stress shows low heritability and high common environmental variance in a wild bird

Oxidative stress was recently demonstrated to affect several fitness‐related traits and is now well recognized to shape animal life‐history evolution. However, very little is known about how much resistance to oxidative stress is determined by genetic and environmental effects and hence about its potential for evolution, especially in wild populations. In addition, our knowledge of phenotypic sexual dimorphism and cross‐sex genetic correlations in resistance to oxidative stress remains extremely limited despite important evolutionary implications. In free‐living great tits (Parus major), we quantified heritability, common environmental effect, sexual dimorphism and cross‐sex genetic correlation in offspring resistance to oxidative stress by performing a split‐nest cross‐fostering experiment where 155 broods were split, and all siblings (n = 791) translocated and raised in two other nests. Resistance to oxidative stress was measured as both oxidative damage to lipids and erythrocyte resistance to a controlled free‐radical attack. Both measurements of oxidative stress showed low additive genetic variances, high common environmental effects and phenotypic sexual dimorphism with males showing a higher resistance to oxidative stress. Cross‐sex genetic correlations were not different from unity, and we found no substantial heritability in resistance to oxidative stress at adult age measured on 39 individuals that recruited the subsequent year. Our study shows that individual ability to resist to oxidative stress is primarily influenced by the common environment and has a low heritability with a consequent low potential for evolution, at least at an early stage of life.     

Mhc polymorphisms fail to explain the heritability of phytohaemagglutinin-induced skin swelling in a wild passerine

Genetic estimates of the variability of immune responses are rarely examined in natural populations because of confounding environmental effects. As a result, and because of the difficulty of pinpointing the genetic determinants of immunity, no study has to our knowledge examined the contribution of specific genes to the heritability of an immune response in wild populations. We cross-fostered nestling house sparrows to disrupt the association between genetic and environmental effects and determine the heritability of the response to a classic immunological test, the phytohaemagglutinin (PHA)-induced skin swelling. We detected significant heritability estimates of the response to PHA, of body mass and tarsus length when nestlings were 5 and 10 days old. Variation at Mhc genes, however, did not explain a significant portion of the genetic variation of nestling swelling to PHA. Our results suggest that while PHA-induced swelling is influenced by the nest of origin, the importance of additive genetic variation relative to non-additive genetic variation and the genetic factors that influence the former in wild populations still need to be identified for this trait.     

Inference of genetic architecture from chromosome partitioning analyses is sensitive to genome variation,sample size,heritability and effect size distribution

Genomewide association studies have contributed immensely to our understanding of the genetic basis of complex traits. One major conclusion arising from these studies is that most traits are controlled by many loci of small effect, confirming the infinitesimal model of quantitative genetics. A popular approach to test for polygenic architecture involves so‐called “chromosome partitioning” where phenotypic variance explained by each chromosome is regressed on the size of the chromosome. First developed for humans, this has now been repeatedly used in other species, but there has been no evaluation of the suitability of this method in species that can differ in their genome characteristics such as number and size of chromosomes. Nor has the influence of sample size, heritability of the trait, effect size distribution of loci controlling the trait or the physical distribution of the causal loci in the genome been examined. Using simulated data, we show that these characteristics have major influence on the inferences of the genetic architecture of traits we can infer using chromosome partitioning analyses. In particular, small variation in chromosome size, small sample size, low heritability, a skewed effect size distribution and clustering of loci can lead to a loss of power and consequently altered inference from chromosome partitioning analyses. Future studies employing this approach need to consider and derive an appropriate null model for their study system, taking these parameters into consideration. Our simulation results can provide some guidelines on these matters, but further studies examining a broader parameter space are needed.