Neuromechanical proficiency in elite performance decision-making: An event-related potential (ERP) analysis.

This research focuses intensively on the neural mechanisms of action selection responses in elite athletes during high-stakes decision-making. It emphasizes the neuromechanical dimensions of these processes, contrasting the responses of expert and novice players within a theoretical framework of neural information processing in high-performance contexts. Utilizing advanced EEG technologies, including event-related potential (ERP) analysis, the study captures a comprehensive view of both behavioral and neurophysiological data. The central aim is to unravel the intricate neural underpinnings that distinguish elite athletes in their decision-making strategies. Key findings highlight: (1) Enhanced accuracy and swifter reaction times in elite athletes during the action selection phase; (2) Significant neurophysiological differences, marked by pronounced N1 peak amplitudes with prolonged latencies, reduced P2 peak amplitudes with stable latencies, decreased P3 peak amplitudes with reduced latencies, and increased average PSW amplitudes. These discoveries significantly advance our understanding of the neural foundations of expert decision-making in high-performance sports. This study not only sheds light on the cognitive and neural dynamics of elite sports performance but also provides a foundation for developing training and performance enhancement techniques in various high-stakes domains.

Genomic prediction and selection response for grain yield in safflower.

In plant breeding programs, multiple traits are recorded in each trial, and the traits are often correlated. Correlated traits can be incorporated into genomic selection models, especially for traits with low heritability, to improve prediction accuracy. In this study, we investigated the genetic correlation between important agronomic traits in safflower. We observed the moderate genetic correlations between grain yield (GY) and plant height (PH, 0.272-0.531), and low correlations between grain yield and days to flowering (DF, -0.157-0.201). A 4%-20% prediction accuracy improvement for grain yield was achieved when plant height was included in both training and validation sets with multivariate models. We further explored the selection responses for grain yield by selecting the top 20% of lines based on different selection indices. Selection responses for grain yield varied across sites. Simultaneous selection for grain yield and seed oil content (OL) showed positive gains across all sites with equal weights for both grain yield and oil content. Combining g×E interaction into genomic selection (GS) led to more balanced selection responses across sites. In conclusion, genomic selection is a valuable breeding tool for breeding high grain yield, oil content, and highly adaptable safflower varieties.

An insight into population structure and genetic progress of Argentinean Holstein cattle.

The objective of the present study was to investigate the most critical issues associated with the limited genetic progress evidenced in the Argentinean Holstein ("Holando Argentino") breed in the last 20 years (only 26% of the phenotypic trend in milk yield was due to genetics). The study comprised the analysis of population structure, realized genetic selection differentials, genetic progress and partition of genetic trends by sex and country of origin from 1936 to 2019 (1,045,582 records; 24,680 sires and 619,322 dams in the pedigree). Average inbreeding steadily increased in the last 15 generations (ΔF = 0.6%, which translates to Ne = 75). Partition of genetic trends revealed that local genetics made a negligible contribution to genetic progress, which for most traits was highly dependent on imported genetics (>80%). Mean generation intervals were fairly constant until 2009 (8-9 years for males and 5-6 years for females, respectively) and then decreased, especially in the paths of sires of bulls and dams of bulls (to 5 and 4 years, respectively) mostly due to the influence of imported sires. The reduction in generation intervals was counterbalanced by a marked deterioration of realized selection differentials, particularly in the path of sires of bulls that nevertheless made the largest contribution to genetic progress. In the last 20 years, realized selection differentials in this path went from 533.6 to 170.8 kg for milk yield and from 16.7 to 13.3 kg for protein yield (1.7-0.5 and 1.6-1.3 standard deviation units, respectively). Among all considered traits (milk yield, fat yield, protein yield, stature, final score and daughter pregnancy rate) in the analysed period, annual genetic gain was negative for milk yield, fairly constant for composition and conformation traits, and positive only in the case of daughter pregnancy rate. Considered together, these results suggest that limited genetic progress is due to the absence of a sound breeding programme that includes genomic selection and a carefully defined selection objective, together with the absence of stronger regulations in germplasm importation; however, other factors such as potential genetics by environment interactions cannot be ruled out.

Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus.

Common full-sib families (c 2 ) make up a substantial proportion of total phenotypic variation in traits of commercial importance in aquaculture species and omission or inclusion of the c 2 resulted in possible changes in genetic parameter estimates and re-ranking of estimated breeding values. However, the impacts of common full-sib families on accuracy of genomic prediction for commercial traits of economic importance are not well known in many species, including aquatic animals. This research explored the impacts of common full-sib families on accuracy of genomic prediction for tagging weight in a population of striped catfish comprising 11,918 fish traced back to the base population (four generations), in which 560 individuals had genotype records of 14,154 SNPs. Our single step genomic best linear unbiased prediction (ssGLBUP) showed that the accuracy of genomic prediction for tagging weight was reduced by 96.5%-130.3% when the common full-sib families were included in statistical models. The reduction in the prediction accuracy was to a smaller extent in multivariate analysis than in univariate models. Imputation of missing genotypes somewhat reduced the upward biases in the prediction accuracy for tagging weight. It is therefore suggested that genomic evaluation models for traits recorded during the early phase of growth development should account for the common full-sib families to minimise possible biases in the accuracy of genomic prediction and hence, selection response.

Prediction of Genetic Resistance for Scrapie in Ungenotyped Sheep Using a Linear Animal Model.

Selection based on scrapie genotypes could improve the genetic resistance for scrapie in sheep. However, in practice, few animals are genotyped. The objectives were to define numerical values of scrapie resistance genotypes and adjust for their non-additive genetic effect; evaluate prediction accuracy of ungenotyped animals using linear animal model; and predict and assess selection response based on estimated breeding values (EBV) of ungenotyped animals. The scrapie resistance (SR) was defined by ranking scrapie genotypes from low (0) to high (4) resistance based on genotype risk groups and was also adjusted for non-additive genetic effect of the haplotypes. Genotypes were simulated for 1,671,890 animals from pedigree. The simulated alleles were assigned to scrapie haplotypes in two scenarios of high (SRh) and low (SRl) resistance populations. A sample of 20,000 genotyped animals were used to predict ungenotyped using animal model. Prediction accuracies for ungenotyped animals for SRh and SRl were 0.60 and 0.54, and for allele content were from 0.41 to 0.71, respectively. Response to selection on SRh and SRl increased SR by 0.52 and 0.28, and on allele content from 0.13 to 0.50, respectively. In addition, the selected animals had large proportion of homozygous for the favorable haplotypes. Thus, pre-selection prior to genotyping could reduce genotyping costs for breeding programs. Using a linear animal model to predict SR makes better use of available information for the breeding programs.

A new selection index percent emphasis method using subindex weights and genetic evaluation accuracy.

The current international standard methodology to quantify trait percent emphasis in selection indexes is based on a simple multiplication of the relative contribution of each trait's economic value (converted to absolute value) and its genetic standard deviation. This method does not reflect the actual selection emphasis applied when the index is used in practice. The economic value does not reflect selection effort when traits differ considerably in their accuracy of evaluation, and no account is taken for either favorable or antagonistic correlations among traits. A new emphasis method adjusted by both accuracy and genetic correlation is proposed. Genetically highly correlated traits are grouped into subindexes by applying a hierarchical clustering method to the genetic correlation matrix. Then each trait's subindex emphasis is calculated within its subindex group, with a weighting included for trait accuracy. Finally, each subindex emphasis is converted to a full index emphasis according to the conventional relative emphasis of its corresponding subgroup. The method can also be applied to sets of breeding values and their economic weights. When applied to a New Zealand sheep breeding selection index where trait genetic correlations are distinct across subindex groups, the new method shrank the emphasis on low-heritability traits, including survival, from 51% to 19%; and expanded that on growth traits from 30% to 49%, better reflecting the selection pressure applied in reality. When genetic correlations across traits were similar, clustering became difficult. Accounting for accuracy affected traits' within-subindex group rankings, whereas the clustering to account for correlations affected all traits within a subgroup equally. Accounting for differences in trait accuracy when describing percent emphasis within selection indexes gives a more practical indication of the likely outcome of selecting on the index. Accounting for correlations among traits when defining percent emphasis made a significant difference only in a subset of case study examples.

Experimental validation of genetic selection for resistance against Streptococcus agalactiae via different routes of infection in the commercial Nile tilapia breeding programme.

The objective of this study was to validate the genetic selection for resistance to streptococcosis under experimental challenge conditions in a commercial population of Nile tilapia. Further, effects of using two different routes of infection of Streptococcus agalactiae; intraperitoneal injection (IP) and cohabitation with the shedder fish (cohab), on the genomic parameters, prediction accuracy and response to selection are compared. The comparison was made between two different lines of fish; one selected for S. agalactiae resistance for one generation and randomly mated for two generations (to mimic the multiplication activities occurring in distribution channels and hatcheries); and the other unselected. 1,500 fish, each from these two lines, were used for the experimental challenge test. Survival analysis using Kaplan-Meier estimators and Hazard's ratio was used to quantify differences in mortality between the two lines. Further genomic analysis was performed with 2,684 fish and 35,745 SNPs using both univariate and bivariate GBLUP models. Genetic selection for resistance to S. agalactiae led to the significant (p < .001) reduction in the risk of death by 65% in the selected line, compared to the unselected line. Similarly, the risk of death via cohabitation route of infection significantly (p < .01) decreased by 80%, compared to IP. The genetic correlation between these two routes of infection was ~0.9. Genetic selection changed the impact of the routes of infection, with the change in the distribution of estimated breeding values and the gain of 3.04 ± 1.25 days as selection response (p < .05).

Proactive motor control within and between hands: Effects of age, motor set, and cue type.

Several studies have reported that proactive motor control in a cued four-finger choice reaction task proceeds more efficiently with a 2-hands motor set (two fingers on each hand) than with a 1-hand motor set (four fingers on one hand). According to the Grouping Model, this is because the 2-hands motor set recruits distinct left and right hand representations located in separate cerebral hemispheres, whereas the 1-hand motor set recruits partially overlapping neural areas grouped together in one hemisphere. The latter neural organization increases neuromotor noise, thereby complicating proactive motor selection. The present study examined the effect of older age on the 2-hands motor selection advantage. A group of young and a group of older adults performed two proactive motor tasks-the procue task and the anticue task-with two motor sets: a 2-hands and 1-hand set. Predictive cues preceded the target signal at five different time intervals (100-850 ms), allowing advance selection of 2 out of 4 fingers. Older adults showed longer reaction times and smaller cueing benefits compared to younger adults. Overall, cueing benefits were greater, and accrued faster, with the 2-hands than with the 1-hand motor set, reflecting the beneficial impact of the neuroanatomical hand distinction. Importantly, the 2-hands advantage was substantially greater in the older age group, suggesting that the hand distinction might abate age-related neural dedifferentiation. These findings highlight the impact of cortical representational distinctiveness in proactive motor control, especially in older age.

Heritability of Teat Condition in Italian Holstein Friesian and Its Relationship with Milk Production and Somatic Cell Score.

In spite of the impressive advancements observed on both management and genetic factors, udder health still represents one of most demanding objectives to be attained in the dairy cattle industry. Udder morphology and especially teat condition might represent the first physical barrier to pathogens' access. The objectives of this study were to investigate the genetic component of teat condition and to elucidate its relationship with both milk yield and somatic cell scores in dairy cattle. Moreover, the effect of selection for both milk yield and somatic cell scores on teat condition was also investigated. A multivariate analysis was conducted on 10,776 teat score records and 30,160 production records from 2469 Italian Holstein cows. Three teat scoring traits were defined and included in the analysis. Heritability estimates for the teat score traits were moderate to low, ranging from 0.084 to 0.238. When teat score was based on a four-classes ordinal scoring, its genetic correlation with milk yields and somatic cell score were 0.862 and 0.439, respectively. The scale used to classify teat-end score has an impact on the magnitude of the estimates. Genetic correlations suggest that selection for milk yield could deteriorate teat health, unless more emphasis is given to somatic cell scores. Considering that both at national and international level, the current selection objectives are giving more emphasis to health traits, a further genetic deterioration in teat condition is not expected.

Inflammatory Correlated Response in Two Lines of Rabbit Selected Divergently for Litter Size Environmental Variability.

A divergent selection experiment for environmental variance of litter size variance was carried out in rabbits over thirteen generations. The aim of this study was to evaluate the inflammatory response in the two lines of the experiment, in order to analyse the effect of selection on susceptibility to diseases after challenging to stressful situations, such as 24 h after the first delivery. A total of 78 females were used in this study, 39 from each line. The line selected for litter size heterogeneity (the high line) showed lower white blood leukocyte count (WBC; -0.87 × 103/µL), lower percentage of basophils (-0.11%), higher concentration of TNF-α (+13.8 pg/mL), and greater concentration of CRP (+38.1 µg/mL) than the line selected for litter size homogeneity (the low line). The high line had also higher concentrations of bilirubin, cholesterol, gamma-glutamyl transferase (GGT) and alkaline phosphatase (ALP) compared to the low line (difference between lines were +0.08 µmol/L, +0.14 µmol/L, +0.35 U/L and +2.4 U/L, respectively). The high line showed higher inflammatory response than the low line, in accordance with a larger susceptibility to infectious disorders. In conclusion, the line selected to increase litter size environmental variability seems to have poor capacity coping with environmental stressors. Therefore, selection for litter size environmental variability can be a useful way to improve animal welfare.

Selection response and genetic parameter estimation of feeding behavior traits in Pekin ducks.

Body weight-related traits and feeding behavior traits are important in poultry breeding and production. To investigate the heritability of feeding behavior and their genetic correlation with body weight-related traits in Pekin ducks, 5,594 Pekin ducks were selected. The information about body weight-related traits and feeding behavior from 3 to 6 wk of age were recorded by automatic electronic feeders. The heritability estimates for body weight, residual feed intake, and feeding behavior traits are relatively high (ranging from 0.29 to 0.65). We observed that total feed intake, meal feed intake, body weight at the age of 3 wk, and daily body weight gain had strong positive genetic correlations with body weight at the age of 6 wk. Moreover, body weight at the age of 3 wk also showed a positive genetic correlation with the feed conversion ratio (0.33). Total feeding time, daily feed intake, and feeding rate had significant positive phenotypic correlations with feed efficiency. However, the average interval between meals, the number of daily visits, and the number of meals all had a low genetic or phenotypic relationship with body weight and feed efficiency. In conclusion, our study revealed that body weight, residual feed intake, and feeding behavior traits were all highly heritable traits, and the selection for certain feeding behaviors could improve feed efficiency in Pekin ducks. This study is the first report about genetic parameter estimates about feeding behaviors in ducks based on large datasets and provides solid data for genetic study in ducks.

Selection Response in a Divergent Selection Experiment for Birth Weight Variability in Mice Compared with a Control Line.

Birth weight (BW) in animal production is an economically important trait in prolific species. The laboratory mouse (Mus musculus) is used as an experimental animal because it is considered a suitable model for prolific species such as rabbits and pigs. Two mouse lines were divergently selected for birth weight variability with a third line of non-selected control population of the same origin as the animals starting the experiment. The objective of this study was, therefore, to compare and evaluate the differential response of each line. The animals were from the 17th generation of both low and high BW variability lines of the divergent selection experiment, including in addition animals from the control line. The dataset contained 389 records from 48 litters of the high line, 734 records from 73 litters of the low line, and 574 records from 71 litters of the control line. The studied traits were as follows: the BW, the BW variance, the BW standard deviation, the BW coefficient of variation within-litter, the weaning weight (WW), the litter size at birth and at weaning, the weight gain, and the preweaning survival. The model included the line effect jointly with the parturition number and its interaction, the linear and quadratic LS as covariates except for the LS trait itself when analyzing litter traits, as well as the pup sex when analyzing individual traits. The low line had a lower BW and WW, but a higher litter size, and greater robustness owing to a higher survival at weaning. As a model of livestock animals, the findings from this experiment led to a proposal of selection for pig production that would combine an increase in litter size with higher survival and welfare. Compared with the control line, a much higher response was observed in the low variability line than in the high line, making it extremely satisfactory given that homogeneity provides advantages in terms of animal welfare and robustness.

Combined Multistage Linear Genomic Selection Indices To Predict the Net Genetic Merit in Plant Breeding.

A combined multistage linear genomic selection index (CMLGSI) is a linear combination of phenotypic and genomic estimated breeding values useful for predicting the individual net genetic merit, which in turn is a linear combination of the true unobservable breeding values of the traits weighted by their respective economic values. The CMLGSI is a cost-saving strategy for improving multiple traits because the breeder does not need to measure all traits at each stage. The optimum (OCMLGSI) and decorrelated (DCMLGSI) indices are the main CMLGSIs. Whereas the OCMLGSI takes into consideration the index correlation values among stages, the DCMLGSI imposes the restriction that the index correlation values among stages be zero. Using real and simulated datasets, we compared the efficiency of both indices in a two-stage context. The criteria we applied to compare the efficiency of both indices were that the total selection response of each index must be lower than or equal to the single-stage combined linear genomic selection index (CLGSI) response and that the correlation of each index with the net genetic merit should be maximum. Using four different total proportions for the real dataset, the estimated total OCMLGSI and DCMLGSI responses explained 97.5% and 90%, respectively, of the estimated single-stage CLGSI selection response. In addition, at stage two, the estimated correlations of the OCMLGSI and the DCMLGSI with the net genetic merit were 0.84 and 0.63, respectively. We found similar results for the simulated datasets. Thus, we recommend using the OCMLGSI when performing multistage selection.

Zebra finches bi-directionally selected for personality differ in repeatability of corticosterone and testosterone.

Consistent between-individual differences in behaviour have been documented across the animal kingdom. Such variation between individuals has been shown to be the basis for selection and to act as a pacemaker for evolutionary change. Recently, equivocal evidence suggests that such consistent between-individual variation is also present in hormones. This observation has sparked interest in understanding the mechanisms shaping individual differences, temporal consistency and heritability of hormonal phenotypes and to understand, if and to what extent hormonal mechanisms are involved in mediating consistent variation in behaviour between individuals. Here, we used zebra finches of the fourth generation of bi-directionally selected lines for three independent behaviours: aggression, exploration and fearlessness. We investigated how these behaviours responded to artificial selection and tested their repeatability. We further tested for repeatability of corticosterone and testosterone across and within lines. Moreover, we are presenting the decomposed variance components for within-individual variance (i.e. flexibility) and between-individual variance (i.e. more or less pronounced differences between individuals) and investigate their contribution to repeatability estimates. Both hormones as well as the exploration and fearlessness but not aggressiveness, were repeatable. However, variance components and hence repeatability differed between lines and were often lower than in unselected control animals, mainly because of a reduction in between-individual variance. Our data show that artificial selection (including active selection and genetic drift) can affect the mean and variance of traits. We stress the importance for understanding how variable a trait is both between and within individuals to assess the selective value of a trait.

How migratory populations become resident.

Migratory behaviour is rapidly changing in response to recent environmental changes, yet it is difficult to predict how migration will evolve in the future. To understand what determines the rate of adaptive evolutionary change in migratory behaviour, we simulated the evolution of residency using an individual-based threshold model, which allows for variation in selection, number of genes, environmental effects and assortative mating. Our model indicates that the recent reduction in migratory activity found in a population of Eurasian blackcaps (Sylvia atricapilla) is only compatible with this trait being under strong directional selection, in which residents have the highest fitness and fitness declines exponentially with migration distance. All other factors had minor effects on the adaptive response. Under this form of selection, a completely migratory population will become partially migratory in 6 and completely resident in 98 generations, demonstrating the persistence of partial migration, even under strong directional selection. Resident populations will preserve large amounts of cryptic genetic variation, particularly if migration is controlled by a large number of genes with small effects. This model can be used to realistically simulate the evolution of any threshold trait, including semi-continuous traits like migration, for predicting evolutionary response to natural selection in the wild.

Genetic Variance Estimates for Maize Yield, Grain Moisture, and Stalk Lodging for Doubled-Haploid and Conventional Selfed-Line Hybrids.

An experiment was conducted to compare estimated genetic variance for maize doubled haploid (DH) with conventional twice-selfed (S2)-line hybrids. Starting with a 4-parent population, at least 160 lines were derived using both of these methods and crossed with two inbred testers. For both inbred testers, maize hybrid grain yield and stalk lodging had higher estimated genetic variances for DH than for S2. For one of the testers, estimated grain moisture genetic variance was higher for DH, but not for the other. The DH hybrid yield distributions on both testers were flatter and had more entries in tails compared with S2 distributions. With complete homozygosity of DH lines and the subsequent increased genetic variance among lines, the expected response to yield selection is higher for DH than for S2 line hybrids.

Resistance to Streptococcus iniae and its genetic associations with traits of economic importance in Asian seabass (Lates calcarifer).

Streptococcus iniae is one of the most serious aquatic pathogens, causing significant economic losses in marine and freshwater species, including Asian seabass (Lates calcarifer). Controlling this gram-positive bacterial pathogen has been an issue in aquaculture systems, due to the combined effects of aquaculture intensification and climatic impacts. To date, there have not been any genetic parameter estimates for S. iniae resistance in Asian seabass. The main aim of this study was to examine genetic variation in S. iniae resistance and its genetic correlations with growth and cannibalism in Asian seabass families produced from a breeding programme for high growth in 2016 and 2017. The study included a total of 5,835 individual fish that were offspring of 41 sires and 60 dams (31 half-sib and 34 full-sib families). The experimental fish were challenged by intraperitoneal injection with a volume containing 105  CFU (colony-forming unit)/fish. Resistance to S. iniae was measured as survival rate at 6 hr, 3, 5, 7, 10 and 15 days post-challenge test. There were significant variations in S. iniae resistance among families at different observation periods (ranging from 24.4% to 80%). Restricted maximum-likelihood method and mixed model analysis were applied to estimate heritability for S. iniae resistance. The heritability for S. iniae resistance ranged from 7% to 18% across different statistical models used. The common full-sib effects accounted for 0.1%-2% of the total variation in resistance to S. iniae. Genetic correlations of the S. iniae resistance at 6 hr and 3 days with later post-challenge test periods were low to moderate. However, these estimates for S. iniae resistance between successive measurement times (5, 7, 10 and 15 days) were high and close to 1. The genetic correlations of resistance with body weights at 180, 270 and 360 days post-hatch were not significant as well with cannibalism. It is concluded that there is substantial additive genetic variation in resistance to S. iniae, suggesting there is potential for genetic improvement of Asian seabass for resistance to S. iniae through selective breeding.

Efficiency of a Constrained Linear Genomic Selection Index To Predict the Net Genetic Merit in Plants.

The constrained linear genomic selection index (CLGSI) is a linear combination of genomic estimated breeding values useful for predicting the net genetic merit, which in turn is a linear combination of true unobservable breeding values of the traits weighted by their respective economic values. The CLGSI is the most general genomic index and allows imposing constraints on the expected genetic gain per trait to make some traits change their mean values based on a predetermined level, while the rest of them remain without restrictions. In addition, it includes the unconstrained linear genomic index as a particular case. Using two real datasets and simulated data for seven selection cycles, we compared the theoretical results of the CLGSI with the theoretical results of the constrained linear phenotypic selection index (CLPSI). The criteria used to compare CLGSI vs. CLPSI efficiency were the estimated expected genetic gain per trait values, the selection response, and the interval between selection cycles. The results indicated that because the interval between selection cycles is shorter for the CLGSI than for the CLPSI, CLGSI is more efficient than CLPSI per unit of time, but its efficiency could be lower per selection cycle. Thus, CLGSI is a good option for performing genomic selection when there are genotyped candidates for selection.

Selection response for Streptococcus agalactiae resistance in Nile tilapia Oreochromis niloticus.

The potential of selection to improve resistance to streptococcosis was evaluated in a commercial population of Nile tilapia in Thailand. The base generation (G0) consisted of offspring from 98 sires and 149 dams using a partly nested design. At 60 days post-hatch, 30 fish from each family were injected intraperitoneally with a Streptococcosis agalactiae solution (1 × 109  CFU/ml) and evaluated for 14 days. Disease resistance was recorded as the number of days from challenge until death (DD) and as a binary (BIN) trait (dead/alive) on day 14. Three models were used for genetic analyses: Cox frailty model for DD; animal model for DD; and animal model for BIN. Age at challenge was fitted as a covariate and contemporary group as fixed or random effect, depending on the model. Fish from the 18 most resistant families were selected to produce the first generation (G1). Heritability estimates for G0 were 0.22, 0.14 ± 0.02 and 0.11 ± 0.02 for the Cox, linear DD and linear BIN models, respectively. Selection response indicated that the risk of death decreased to 54%, survival time increased to 3.4 days and survival rate increased to 21%. These results suggest that genetic improvement is possible for this population.

Behavioural, physiological and molecular changes in alloparental caregivers may be responsible for selection response for female reproductive investment in honey bees.

Reproductive investment is a central life history variable that influences all aspects of life. Hormones coordinate reproduction in multicellular organisms, but the mechanisms controlling the collective reproductive investment of social insects are largely unexplored. One important aspect of honey bee (Apis mellifera) reproductive investment consists of raising female-destined larvae into new queens by alloparental care of nurse bees in form of royal jelly provisioning. Artificial selection for commercial royal jelly production over 40 years has increased this reproductive investment by an order of magnitude. In a cross-fostering experiment, we establish that this shift in social phenotype is caused by nurse bees. We find no evidence for changes in larval signalling. Instead, the antennae of the nurse bees of the selected stock are more responsive to brood pheromones than control bees. Correspondingly, the selected royal jelly bee nurses are more attracted to brood pheromones than unselected control nurses. Comparative proteomics of the antennae from the selected and unselected stocks indicate putative molecular mechanisms, primarily changes in chemosensation and energy metabolism. We report expression differences of several candidate genes that correlate with the differences in reproductive investment. The functional relevance of these genes is supported by demonstrating that the corresponding proteins can competitively bind one previously described and one newly discovered brood pheromone. Thus, we suggest several chemosensory genes, most prominently OBP16 and CSP4, as candidate mechanisms controlling queen rearing, a key reproductive investment, in honey bees. These findings reveal novel aspects of pheromonal communication in honey bees and explain how sensory changes affect communication and lead to a drastic shift in colony-level resource allocation to sexual reproduction. Thus, pheromonal and hormonal communication may play similar roles for reproductive investment in superorganisms and multicellular organisms, respectively.