Different Degrees Of Relatedness Research Articles

SNP-Based Heritability of Osteochondrosis Dissecans in Hanoverian Warmblood Horses.

Before the genomics era, heritability estimates were performed using pedigree data. Data collection for pedigree analysis is time consuming and holds the risk of incorrect or incomplete data. With the availability of SNP-based arrays, heritability can now be estimated based on genotyping data. We used SNP array and 1.6 million imputed genotype data with different minor allele frequency restrictions to estimate heritabilities for osteochondrosis dissecans in the fetlock, hock and stifle joints of 446 Hanoverian warmblood horses. SNP-based heritabilities were estimated using a genomic restricted maximum likelihood (GREML) method and accounting for patterns of regional linkage disequilibrium in the equine genome. In addition, we employed GREML for family data to account for different degrees of relatedness in the study population. Our results indicate that we were able to capture a larger proportion of additive genetic variance compared to pedigree-based estimates in the same population of Hanoverian horses. Heritability estimates on the linear scale for fetlock-, hock- and stifle-osteochondrosis dissecans were 0.41-0.43, 0.62-0.63, and 0.23-0.25, respectively, with standard errors of 0.11-0.14. Accounting for linkage disequilibrium patterns had an upward effect on the imputed data and a downward impact on the SNP array genotype data. GREML for family data resulted in higher heritability estimates for fetlock-osteochondrosis dissecans and slightly higher estimates for hock-osteochondrosis dissecans, but had no effect on stifle-osteochondrosis dissecans. The largest and most consistent heritability estimates were obtained when we employed GREML for family data with genomic relationship matrices weighted through patterns of regional linkage disequilibrium. Estimation of SNP-based heritability should be recommended for traits that can only be phenotyped in smaller samples or are cost-effective.

On the flexibility of the sound-to-meaning mapping when listening to native and foreign-accented speech

Extracting linguistic information from the speech signal is critical to successfully communicate with others. We usually carry out this sound-to-meaning mapping easily, but this process may be hampered under adverse listening conditions. Thus, exploring whether foreign accents might affect the sound-to-meaning mapping is particularly relevant, as interactions with these speakers are increasingly common in the globalized world. In this study, we conducted a cross-modal priming task, in which participants (N = 24) were presented with auditory primes uttered by a native or by a French foreign-accented speaker of Spanish, and with visual targets that had different degrees of relatedness to the prime: repeated, semantically related, or unrelated words. Behavioral and EEG measures were analyzed, and we found a significant relatedness effect (i.e., a processing advantage for repeated compared to related words, and for the latter compared to unrelated words). However, speakers' accents had no effect on the results. To further explore the potential effect of speakers' accent on the sound-to-meaning mapping, we conducted a second study, in which participants (N = 22) were presented with the same task, although in this case primes were uttered by the same native speaker as in the previous experiment, and by a German foreign-accented speaker with a stronger accent. We replicated the results observed in the first study. Taken together, our results show moderate evidence that speakers' accent does not affect the sound-to-meaning mapping, suggesting that this is a robust and flexible process that is not compromised by auditory variables related to speakers' characteristics.

Evolutionary multi-task optimization with hybrid knowledge transfer strategy

As an emerging research paradigm in the field of evolutionary computation, evolutionary multi-task optimization (EMTO) has received an increasing amount of attention due to its capability in concurrently solving multiple related optimization tasks. In EMTO, without any prior knowledge about the complementarity between different tasks, the task relatedness is mainly captured dynamically through the evolving population. However, how to transfer the knowledge across tasks in accordance with different degrees of relatedness as the search proceeds has received little visibility. To address this issue and further enhance the performance of EMTOs, this paper proposes a hybrid knowledge transfer (HKT) strategy. In HKT, a population distribution-based measurement (PDM) technique is designed to evaluate the task relatedness based on the distribution characteristics of the evolving population, and then a multi-knowledge transfer (MKT) mechanism is employed to conduct multiple strategies of knowledge transfer according to the degree of relatedness between tasks. By incorporating the HKT strategy into EMTO, the resultant algorithmic framework, termed EMTO–HKT, is presented. The experimental results on the single-objective multi-task optimization test suite demonstrate the superiority of EMTO–HKT compared with other state-of-the-art EMTO algorithms.

Training set design in genomic prediction with multiple biparental families.

Genomic selection is a powerful tool to reduce the cycle length and enhance the genetic gain of complex traits in plant breeding. However, questions remain about the optimum design and composition of the training set. In this study, we used 944 soybean [Glycine max (L.) Merr.] recombinant inbred lines from eight families derived through a partial-diallel mating design among five parental lines. The cross-validated prediction accuracies for the six traits seed yield, 1,000-seed weight, protein yield, plant height, protein content, and oil content were high, ranging from 0.79 to 0.87. We investigated among-family predictions, making use of the special mating design with different degrees of relatedness among families. Generally, the prediction accuracy decreased from full-sibs to half-sib families to unrelated families. However, half-sib and unrelated families also showed substantial variation in their prediction accuracy for a given family, which appeared to be caused at least in part by the shared segregation of quantitative trait loci in both the training and prediction sets. Combining several half-sib families in composite training sets generally led to an increase in the prediction accuracy compared with the best family alone. The prediction accuracy increased with the size of the training set, but for comparable prediction accuracy, substantially more half-sibs were required than full-sibs. Collectively, our results highlight the potential of genomic selection for soybean breeding and, in a broader context, illustrate the importance of the targeted design of the training set.

Phylogenetic Typology.

In this article we propose a novel method to estimate the frequency distribution of linguistic variables while controlling for statistical non-independence due to shared ancestry. Unlike previous approaches, our technique uses all available data, from language families large and small as well as from isolates, while controlling for different degrees of relatedness on a continuous scale estimated from the data. Our approach involves three steps: First, distributions of phylogenies are inferred from lexical data. Second, these phylogenies are used as part of a statistical model to estimate transition rates between parameter states. Finally, the long-term equilibrium of the resulting Markov process is computed. As a case study, we investigate a series of potential word-order correlations across the languages of the world.

Parental asthma and risk of autism spectrum disorder in offspring: A population and family-based case-control study.

SummaryBackgroundAssociations between parental asthma and prenatal exposure to asthma medications with offspring autism spectrum disorder (ASD) have been reported. However, the associations might be confounded by unmeasured (genetic and shared environmental) familial factors.ObjectiveWe investigated the association between (a) maternal/paternal asthma and offspring ASD, and (b) prenatal exposures to β2‐agonists, other asthma medications and offspring ASD using cases and controls selected from the population as well as biological relatives with different degrees of relatedness.MethodsWe included all children (N = 1 579 263) born in Sweden 1992‐2007. A nested case‐control design was used to compare 22 894 ASD cases identified from the National Patient Register to (a) 228 940 age‐, county‐ and sex‐matched controls randomly selected from the population, (b) their eligible full‐siblings (n = 1267), (c) half‐siblings (n = 1323), (d) full‐cousins (n = 11 477) and (e) half‐cousins (n = 3337). Conditional logistic regression was used to estimate the odds ratios (OR) and 95% confidence intervals (CI) for ASD in children differentially exposed to parental asthma or prenatal asthma medications.ResultsMaternal asthma was associated with increased risk of offspring ASD (OR 1.43, 95% CI 1.38‐1.49); there was a weaker association for paternal asthma (OR 1.17, 95% CI 1.11‐1.23). The risk of offspring ASD in mothers with asthma showed similar estimates when adjusting for shared familial factors among paternal half‐siblings (OR 1.20, 95% CI 0.80‐1.81), full‐cousins (OR 1.28, 95% CI 1.16‐1.41) and half‐cousins (OR 1.30, 95% CI 1.10‐1.54), albeit with wider confidence intervals. Prenatal exposure to asthma medications among subjects whose mothers had asthma was not associated with subsequent ASD.Conclusions and Clinical RelevanceIn this large observational study, parental asthma was associated with slightly elevated risk of ASD in offspring. More specifically, the increased risk by maternal asthma did not seem to be confounded by familial factors. There was no evidence of an association between asthma medications during pregnancy and offspring ASD.

Multivariate GBLUP Improves Accuracy of Genomic Selection for Yield and Fruit Weight in Biparental Populations of Vaccinium macrocarpon Ait.

The development of high-throughput genotyping has made genome-wide association (GWAS) and genomic selection (GS) applications possible for both model and non-model species. The exploitation of genome-assisted approaches could greatly benefit breeding efforts in American cranberry (Vaccinium macrocarpon) and other minor crops. Using biparental populations with different degrees of relatedness, we evaluated multiple GS methods for total yield (TY) and mean fruit weight (MFW). Specifically, we compared predictive ability (PA) differences between univariate and multivariate genomic best linear unbiased predictors (GBLUP and MGBLUP, respectively). We found that MGBLUP provided higher predictive ability (PA) than GBLUP, in scenarios with medium genetic correlation (8–17% increase with corg~0.6) and high genetic correlations (25–156% with corg~0.9), but found no increase when genetic correlation was low. In addition, we found that only a few hundred single nucleotide polymorphism (SNP) markers are needed to reach a plateau in PA for both traits in the biparental populations studied (in full linkage disequilibrium). We observed that higher resemblance among individuals in the training (TP) and validation (VP) populations provided greater PA. Although multivariate GS methods are available, genetic correlations and other factors need to be carefully considered when applying these methods for genetic improvement.

Relatives growing together: pair density and kinship

Kin selection is often used to explain the evolution altruism towards relatives through favouring the evolution of kin recognition. However, it remains unclear whether kin recognition is affected by plant pair density and different degrees of relatedness. A two-factor experimental design of kinship (three kinship degrees including siblings, closely related strangers and distantly related strangers) and pair density (including relative small, medium and large pair densities) was conducted in this study. Plant competitive traits including rosette size, specific leaf area (SLA), stem elongation, root and leaf allocation, seed biomass and vegetative biomass were measured to reflect interactions among plants living with different relatives of Arabidopsis thaliana accessions [Columbia (Col-0), Landsberg erecta (Ler) and Wassileskijia (Ws)] in three different pair densities. The SLA only showed kinship effect, and siblings showed higher SLA than non-siblings in each pair density. The plant total biomass was only affected by pair density, which increased with decreases of pair density. The rosette size, stem elongation, root allocation and leaf allocation showed interactive effects of kinship and pair density. In the large pair density, the rosette size of siblings was lower than distantly related strangers, compared to closely related strangers; the stem elongation and root allocation were lower, while the seed biomass of siblings was higher than the closely or distantly related strangers. In the medium pair density, plants living with siblings or with closely related neighbours showed higher root allocation than with distantly related neighbours. In the small pair density, the plant rosette acted similarly to of which in the large pair density, and siblings showed higher root allocation than the two strangers. The other traits in each pair density showed no significant differences among kinship treatments. A relatively large pair density achieves kin recognition by deducing root competition ability and mutual shading, with increased efficient light capture and fitness. Similar such root and efficient light capture strategies were selected in medium pair density. Except the efficient light capture strategies, small pair density also displays allocation trade-offs between roots (decreased) and leaves (increased) for siblings. Moreover, kin responses on those attributes are also adjusted by kinship degree. Thus, kinships and pair density are important variables to mediate kin interactions.

Genomic prediction in early selection stages using multi-year data in a hybrid rye breeding program

BackgroundThe use of multiple genetic backgrounds across years is appealing for genomic prediction (GP) because past years’ data provide valuable information on marker effects. Nonetheless, single-year GP models are less complex and computationally less demanding than multi-year GP models. In devising a suitable analysis strategy for multi-year data, we may exploit the fact that even if there is no replication of genotypes across years, there is plenty of replication at the level of marker loci. Our principal aim was to evaluate different GP approaches to simultaneously model genotype-by-year (GY) effects and breeding values using multi-year data in terms of predictive ability. The models were evaluated under different scenarios reflecting common practice in plant breeding programs, such as different degrees of relatedness between training and validation sets, and using a selected fraction of genotypes in the training set. We used empirical grain yield data of a rye hybrid breeding program. A detailed description of the prediction approaches highlighting the use of kinship for modeling GY is presented.ResultsUsing the kinship to model GY was advantageous in particular for datasets disconnected across years. On average, predictive abilities were 5% higher for models using kinship to model GY over models without kinship. We confirmed that using data from multiple selection stages provides valuable GY information and helps increasing predictive ability. This increase is on average 30% higher when the predicted genotypes are closely related with the genotypes in the training set. A selection of top-yielding genotypes together with the use of kinship to model GY improves the predictive ability in datasets composed of single years of several selection cycles.ConclusionsOur results clearly demonstrate that the use of multi-year data and appropriate modeling is beneficial for GP because it allows dissecting GY effects from genomic estimated breeding values. The model choice, as well as ensuring that the predicted candidates are sufficiently related to the genotypes in the training set, are crucial.

Sex-specific repeatabilities and effects of relatedness and mating status on copulation duration in an acridid grasshopper.

In species with direct sperm transfer, copulation duration is a crucial trait that may affect male and female reproductive success and that may vary with the quality of the mating partner. Furthermore, traits such as copulation duration represent the outcome of behavioral interactions between the sexes, for which it is important—but often difficult—to determine which sex is in phenotypic control. Using a double‐mating protocol, we compared copulation durations between (1) virgin and nonvirgin and (2) sibling and nonsibling mating pairs in rufous grasshoppers Gomphocerippus rufus. Nonvirgin copulations took on average approximately 30% longer than virgin copulations, whereas relatedness of mating partners was not a significant predictor of copulation duration. Longer nonvirgin copulations may represent a male adaptation to sperm competition if longer copulations allow more sperm to be transferred or function as postinsemination mate guarding. The absence of differences between pairs with different degrees of relatedness suggests no precopulatory or preinsemination inbreeding avoidance mechanism has evolved in this species, perhaps because there is no inbreeding depression in this species, or because inbreeding avoidance occurs after copulation. Controlling for the effects of male and female mating status (virgin vs. nonvirgin) and relatedness (sibling vs. nonsibling), we found significant repeatabilities (R) in copulation duration for males (R = 0.33; 95% CI: 0.09–0.55) but not for females (R = 0.09; 95% CI: 0.00–0.30). Thus, copulation durations of males more strongly represent a nontransient trait expressed in a consistent manner with different mating partners, suggesting that some aspect of the male phenotype may determine copulation duration in this species. However, overlapping confidence intervals for our sex‐specific repeatability estimates indicate that higher sampling effort is required for conclusive evidence.

Gene-based segregation method for identifying rare variants in family-based sequencing studies.

Whole-exome sequencing using family data has identified rare coding variants in Mendelian diseases or complex diseases with Mendelian subtypes, using filters based on variant novelty, functionality, and segregation with the phenotype within families. However, formal statistical approaches are limited. We propose a gene-based segregation test (GESE) that quantifies the uncertainty of the filtering approach. It is constructed using the probability of segregation events under the null hypothesis of Mendelian transmission. This test takes into account different degrees of relatedness in families, the number of functional rare variants in the gene, and their minor allele frequencies in the corresponding population. In addition, a weighted version of this test allows incorporating additional subject phenotypes to improve statistical power. We show via simulations that the GESE and weighted GESE tests maintain appropriate type I error rate, and have greater power than several commonly used region-based methods. We apply our method to whole-exome sequencing data from 49 extended pedigrees with severe, early-onset chronic obstructive pulmonary disease (COPD) in the Boston Early-Onset COPD study (BEOCOPD) and identify several promising candidate genes. Our proposed methods show great potential for identifying rare coding variants of large effect and high penetrance for family-based sequencing data. The proposed tests are implemented in an R package that is available on CRAN (https://cran.r-project.org/web/packages/GESE/).

Identity recognition in response to different levels of genetic relatedness in commercial soya bean.

Identity recognition systems allow plants to tailor competitive phenotypes in response to the genetic relatedness of neighbours. There is limited evidence for the existence of recognition systems in crop species and whether they operate at a level that would allow for identification of different degrees of relatedness. Here, we test the responses of commercial soya bean cultivars to neighbours of varying genetic relatedness consisting of other commercial cultivars (intraspecific), its wild progenitor Glycine soja, and another leguminous species Phaseolus vulgaris (interspecific). We found, for the first time to our knowledge, that a commercial soya bean cultivar, OAC Wallace, showed identity recognition responses to neighbours at different levels of genetic relatedness. OAC Wallace showed no response when grown with other commercial soya bean cultivars (intra-specific neighbours), showed increased allocation to leaves compared with stems with wild soya beans (highly related wild progenitor species), and increased allocation to leaves compared with stems and roots with white beans (interspecific neighbours). Wild soya bean also responded to identity recognition but these responses involved changes in biomass allocation towards stems instead of leaves suggesting that identity recognition responses are species-specific and consistent with the ecology of the species. In conclusion, elucidating identity recognition in crops may provide further knowledge into mechanisms of crop competition and the relationship between crop density and yield.

Genome-wide analysis of positively selected genes in seasonal and non-seasonal breeding species.

Some mammals breed throughout the year, while others breed only at certain times of year. These differences in reproductive behavior can be explained by evolution. We identified positively-selected genes in two sets of species with different degrees of relatedness including seasonal and non-seasonal breeding species, using branch-site models. After stringent filtering by sum of pairs scoring, we revealed that more genes underwent positive selection in seasonal compared with non-seasonal breeding species. Positively-selected genes were verified by cDNA mapping of the positive sites with the corresponding cDNA sequences. The design of the evolutionary analysis can effectively lower the false-positive rate and thus identify valid positive genes. Validated, positively-selected genes, including CGA, DNAH1, INVS, and CD151, were related to reproductive behaviors such as spermatogenesis and cell proliferation in non-seasonal breeding species. Genes in seasonal breeding species, including THRAP3, TH1L, and CMTM6, may be related to the evolution of sperm and the circadian rhythm system. Identification of these positively-selected genes might help to identify the molecular mechanisms underlying seasonal and non-seasonal reproductive behaviors.

Chaotic genetic patchiness and high relatedness of a poecilogonous polychaete in a heterogeneous estuarine landscape

The genetic structure of benthic marine invertebrates is often described as “chaotic” when genetic structure cannot be explained and barriers to dispersal and gene flow cannot be identified. Here, chaotic patterns of genetic structure for the polychaete Pygospio elegans (Claparede) sampled at 16 locations from the heterogeneous Isefjord–Roskilde Fjord estuary complex in Denmark were found. There was no isolation by distance, and the geography of the estuary complex did not seem to pose a barrier to dispersal and gene flow in this species. We investigated whether characteristics of the environment could be related to the genetic structure and possibly restrict gene flow in this species. Additionally, since P. elegans is poecilogonous, producing larvae with different pelagic developmental periods, we investigated whether observed developmental modes in the samples might clarify the genetic patterns. None of the tested factors explained the population genetic structure. However, a high degree of relatedness among individuals in almost all samples was found. Samples with a larger percentage of young individuals had more related individuals, suggesting that different cohorts could be comprised of individuals with different degrees of relatedness. Relatedness within a site could be increased by limited larval dispersal, collective dispersal of related larvae, sweepstakes reproductive success, or asexual reproduction, but distinguishing between these requires further study. Using a “seascape genetics” approach allowed us to investigate some of the numerous potential factors that could influence population genetic structure in a poecilogonous species.

Many drugs contain unique scaffolds with varying structural relationships to scaffolds of currently available bioactive compounds

Molecular scaffolds were systematically extracted from approved drugs and analyzed. The majority of drug scaffolds, 552 of 700, were found to represent only a single drug. Moreover, 221 drug scaffolds were not detected in currently available bioactive compounds, i.e., the pool from which drug candidates usually originate. These “drug-unique” scaffolds displayed a variety of structural relationships to currently known bioactive scaffolds, reflecting rather different degrees of relatedness. Many drug-unique scaffolds formed only very limited structural relationships to bioactive scaffolds. These drug scaffolds should represent promising candidates for further chemical exploration and drug repositioning efforts and are made freely available.

How Late Should Johnny-Come-Lately Come?

Potential followers are heterogeneous because of their access to alternative levels of complementary assets and the different degrees of relatedness of these assets. Using a decision-theory approach, we build a model that enables us to identify under what conditions a follower can afford to wait to enter a market, and for how long the delay is viable. We demonstrate that these conditions not only depend on the effect of industry age on the follower's complementary asset characteristics, but also on both a direct and indirect effect of industry age on performance. Specifically, we show that a high degree of relatedness in the follower's complementary assets does not necessarily afford the opportunity to wait, as the ability to wait depends on whether these direct and indirect effects are weakened or intensified by the strength of the relatedness.

Kin recognition in three samples of Phytoseiulus persimilis (Acari: Phytoseiidae)

Kin recognition as an important phenomenon which influences species fitness is mediated by mechanisms such as association or familiarity. Here, we have investigated either prior association or relatedness would affect the predatory mite, Phytoseiulus persimilis prey choice for cannibalism. Three samples of the predator including UT (University of Tehran), iso-females provided from UT and Turkey population with different degrees of relatedness, were introduced to the prospective cannibal which was selected from the iso-female line. The experimental procedure was consisted of imprinting (on each of the three sample larvae) and choice (between either familiar related and unfamiliar unrelated or familiar unrelated and unfamiliar related larvae) tests. The oviposition tests were designed by introducing each of the samples as the second female to a patch contained eggs related to iso-females as the first female. We found that the cannibal protonymphs preferred unfamiliar larvae for eating regardless of kinship. The number of prey eggs was significantly dependant to the type of relation between the eggs from first and second female. The effect of relatedness on the distances between eggs is discussed.

Adaptation and modification of three CRISPR loci in two closely related cyanobacteria

An RNA-based screen was performed to reveal a possible evolutionary scenario for the CRISPR-Cas systems in two cyanobacterial model strains. Following the analysis of a draft genome sequence of Synechocystis sp PCC6714, three different CRISPR-Cas systems were characterized that have different degrees of relatedness to another three CRISPR-Cas systems in Synechocystis sp PCC6803. A subtype III-B system was identified that is extremely conserved between both strains. Strong signals in northern hybridizations and the presence of different spacers (but identical repeats) indicated this system to be active, despite the absence of a known endonuclease candidate gene involved in the maturation of its crRNAs in the two strains. The other two systems were found to differ significantly from each other, with different sets of repeat-spacer arrays and different Cas genes. In view of the otherwise very close relatedness of the two analyzed strains, this is suggestive of an unknown mechanism involved in the replacement of CRISPR-Cas cassettes as a whole. Further RNA analyses revealed the accumulation of crRNAs to be impacted by environmental conditions critical for photoautotropic growth. All six systems are associated with a gene for a possible transcriptional repressor. Indeed, we identified one of these genes, sll7009, as encoding a negative regulator specific for the CRISPR1 subtype I-D system in Synechocystis sp PCC6803.

Detecting coevolving positions in a molecule: why and how to account for phylogeny

Positions in a molecule that share a common constraint do not evolve independently, and therefore leave a signature in the patterns of homologous sequences. Exhibiting such positions with a coevolution pattern from a sequence alignment has great potential for predicting functional and structural properties of molecules through comparative analysis. This task is complicated by the existence of additional correlation sources, leading to false predictions. The nature of the data is a major source of noise correlation: sequences are taken from individuals with different degrees of relatedness, and who therefore are intrinsically correlated. This has led to several method developments in different fields that are potentially confusing for non-expert users interested in these methodologies. It also explains why coevolution detection methods are largely unemployed despite the importance of the biological questions they address. In this article, I focus on the role of shared ancestry for understanding molecular coevolution patterns. I review and classify existing coevolution detection methods according to their ability to handle shared ancestry. Using a ribosomal RNA benchmark data set, for which detailed knowledge of the structure and coevolution patterns is available, I demonstrate and explain why taking the underlying evolutionary history of sequences into account is the only way to extract the full coevolution signal in the data. I also evaluate, using rigorous statistical procedures, the best approaches to do so, and discuss several important biological aspects to consider when performing coevolution analyses.

Kin discriminators in the eusocial sweat bee Lasioglossum malachurum: the reliability of cuticular and Dufour’s gland odours

The ability to discriminate degrees of relatedness may be expected to evolve if it allows unreciprocated altruism to be preferentially directed towards kin (Hamilton in J Theor Biol 7:1–16, 1964). We explored the possibility of kin recognition in the primitively eusocial halictid bee Lasioglossum malachurum by investigating the reliability of worker odour cues that can be perceived by workers to act as indicators of either nest membership or kinship. Cuticular and Dufour’s gland compounds varied significantly among colonies of L. malachurum, providing the potential for nestmate discrimination. A significant, though weak, negative correlation between chemical distance and genetic relatedness (r = −0.055, p < 0.001) suggests a genetic component to variation in cuticular bouquet, but odour cues were not informative enough to discriminate between different degrees of relatedness within nests. This pattern of variation was similar for Dufour’s gland bouquets. The presence of unrelated individuals within nests that are not chemically different from their nestmates suggests that the discrimination system of L. malachurum is prone to acceptance errors. Compounds produced by colony members are likely combined to generate a gestalt colony chemical signature such that all nestmates have a similar smell. The correlation between odour cues and nest membership was greater for perceived compounds than for non-perceived compounds, suggesting that variability in perceived compounds is a result of positive selection for nestmate recognition despite potentially stabilising selection to reduce variability in odour differences and thereby to reduce costs derived from excessive intracolony nepotistic behaviour.