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Kin recognition is an important mediator of interactions within individuals of a species. Despite increasing evidence of kin recognition in natural plant populations, relatively little is known about kin recognition in crop species where numerous cultivars have been generated by artificial selection. We identified rice (Oryza sativa) cultivars with the ability for kin recognition from two sets of indica-inbred and indica-hybrid lines at different levels of genetic relatedness. We then assessed this ability among kin and nonkin and tested potential mechanisms in a series of controlled experiments and field trails. Rice cultivars with the ability for kin recognition were capable of detecting the presence of kin and nonkin and responded to them by altering root behavior and biomass allocation, particularly for grain yield. Furthermore, we assessed the role of root exudates and found a root-secreted nitrogen-rich allantoin component to be responsible for kin recognition in rice lines. Kin recognition in rice lines mediated by root exudates occurs in a cultivar-dependent manner. Rice cultivars with the ability for kin recognition may increase grain yield in the presence of kin. Such an improvement of grain yield by kin recognition of cultivar mixtures offers many implications and applications in rice production.

In the context of social evolution, the ecological drivers of selection are the phenotypes of other individuals. The social environment can thus evolve, potentially changing the adaptive value for different social strategies. Different branches of evolutionary biology have traditionally focused on different aspects of these feedbacks. Here, we synthesize behavioral ecology theory concerning evolutionarily stable strategies when fitness is frequency dependent with quantitative genetic models providing statistical descriptions of evolutionary responses to social selection. Using path analyses, we review how social interactions influence the strength of selection and how social responsiveness, social impact, and non-random social assortment affect responses to social selection. We then detail how the frequency-dependent nature of social interactions fits into this framework and how it imposes selection on traits mediating social responsiveness, social impact, and social assortment, further affecting evolutionary dynamics. Throughout, we discuss the parameters in quantitative genetics models of social evolution from a behavioral ecology perspective and identify their statistical counterparts in empirical studies. This integration of behavioral ecology and quantitative genetic perspectives should lead to greater clarity in the generation of hypotheses and more focused empirical research regarding evolutionary pathways and feedbacks inherent in specific social interactions.

Background Population structure and cryptic relatedness between individuals (samples) are two major factors affecting false positives in genome-wide association studies (GWAS). In addition, population stratification and genetic relatedness in genomic selection in animal and plant breeding can affect prediction accuracy. The methods commonly used for solving these problems are principal component analysis (to adjust for population stratification) and marker-based kinship estimates (to correct for the confounding effects of genetic relatedness). Currently, many tools and software are available that analyze genetic variation among individuals to determine population structure and genetic relationships. However, none of these tools or pipelines perform such analyses in a single workflow and visualize all the various results in a single interactive web application. Results We developed PSReliP, a standalone, freely available pipeline for the analysis and visualization of population structure and relatedness between individuals in a user-specified genetic variant dataset. The analysis stage of PSReliP is responsible for executing all steps of data filtering and analysis and contains an ordered sequence of commands from PLINK, a whole-genome association analysis toolset, along with in-house shell scripts and Perl programs that support data pipelining. The visualization stage is provided by Shiny apps, an R-based interactive web application. In this study, we describe the characteristics and features of PSReliP and demonstrate how it can be applied to real genome-wide genetic variant data. Conclusions The PSReliP pipeline allows users to quickly analyze genetic variants such as single nucleotide polymorphisms and small insertions or deletions at the genome level to estimate population structure and cryptic relatedness using PLINK software and to visualize the analysis results in interactive tables, plots, and charts using Shiny technology. The analysis and assessment of population stratification and genetic relatedness can aid in choosing an appropriate approach for the statistical analysis of GWAS data and predictions in genomic selection. The various outputs from PLINK can be used for further downstream analysis. The code and manual for PSReliP are available at https://github.com/solelena/PSReliP .

Association mapping is a powerful approach for exploring the molecular basis of phenotypic variations in plants. A maize (Zea mays L.) association mapping panel including 527 inbred lines with tropical, subtropical and temperate backgrounds, representing the global maize diversity, was genotyped using 1,536 single nucleotide polymorphisms (SNPs). In total, 926 SNPs with minor allele frequencies of ≥0.1 were used to estimate the pattern of genetic diversity and relatedness among individuals. The analysis revealed broad phenotypic diversity and complex genetic relatedness in the maize panel. Two different Bayesian approaches identified three specific subpopulations, which were then reconfirmed by principal component analysis (PCA) and tree-based analyses. Marker–trait associations were performed to assess the suitability of different models for false-positive correction by population structure (Q matrix/PCA) and familial kinship (K matrix) alone or in combination in this panel. The K, Q + K and PCA + K models could reduce the false positives, and the Q + K model performed slightly better for flowering time, ear height and ear diameter. Our findings suggest that this maize panel is suitable for association mapping in order to understand the relationship between genotypic and phenotypic variations for agriculturally complex quantitative traits using optimal statistical methods.

Key messageHyperspectral data is a promising complement to genomic data to predict biomass under scenarios of low genetic relatedness. Sufficient environmental connectivity between data used for model training and validation is required.The demand for sustainable sources of biomass is increasing worldwide. The early prediction of biomass via indirect selection of dry matter yield (DMY) based on hyperspectral and/or genomic prediction is crucial to affordably untap the potential of winter rye (Secale cereale L.) as a dual-purpose crop. However, this estimation involves multiple genetic backgrounds and genetic relatedness is a crucial factor in genomic selection (GS). To assess the prospect of prediction using reflectance data as a suitable complement to GS for biomass breeding, the influence of trait heritability (H2) and genetic relatedness were compared. Models were based on genomic (GBLUP) and hyperspectral reflectance-derived (HBLUP) relationship matrices to predict DMY and other biomass-related traits such as dry matter content (DMC) and fresh matter yield (FMY). For this, 270 elite rye lines from nine interconnected bi-parental families were genotyped using a 10 k-SNP array and phenotyped as testcrosses at four locations in two years (eight environments). From 400 discrete narrow bands (410 nm–993 nm) collected by an uncrewed aerial vehicle (UAV) on two dates in each environment, 32 hyperspectral bands previously selected by Lasso were incorporated into a prediction model. HBLUP showed higher prediction abilities (0.41 – 0.61) than GBLUP (0.14 – 0.28) under a decreased genetic relationship, especially for mid-heritable traits (FMY and DMY), suggesting that HBLUP is much less affected by relatedness and H2. However, the predictive power of both models was largely affected by environmental variances. Prediction abilities for DMY were further enhanced (up to 20%) by integrating both matrices and plant height into a bivariate model. Thus, data derived from high-throughput phenotyping emerges as a suitable strategy to efficiently leverage selection gains in biomass rye breeding; however, sufficient environmental connectivity is needed.

Background Inappropriate use of antimicrobial agents in animal production has led to the development of antimicrobial resistance (AMR) in foodborne pathogens. Transmission of AMR foodborne pathogens from reservoirs, particularly chickens to the human population does occur. Recently, we reported that occupational exposure was a risk factor for multidrug-resistant (MDR) Escherichia coli (E. coli) among poultry-workers. Here we determined the prevalence and genetic relatedness among MDR E. coli isolated from poultry-workers, chickens, and poultry environments in Abuja, Nigeria. This study was conducted to address the gaps identified by the Nigerian AMR situation analysis. Methods We conducted a cross-sectional study among poultry-workers, chickens, and poultry farm/live bird market (LBM) environments. The isolates were tested phenotypically for their antimicrobial susceptibility profiles, genotypically characterized using whole-genome sequencing (WGS) and in silico multilocus sequence types (MLST). We conducted a phylogenetic single nucleotide polymorphism (SNPs) analysis to determine relatedness and clonality among the isolates. Results A total of 115 (26.8%) out of 429 samples were positive for E. coli. Of these, 110 isolates were viable for phenotypic and genotypic characterization. The selection comprised 47 (42.7%) isolates from poultry-workers, 36 (32.7%) from chickens, and 27 (24.5%) from poultry-farm or LBM environments. Overall, 101 (91.8%) of the isolates were MDR conferring resistance to at least three drug classes . High frequency of resistance was observed for tetracycline (n = 102; 92.7%), trimethoprim/sulfamethoxazole (n = 93; 84.5%), streptomycin (n = 87; 79.1%) and ampicillin (n = 88; 80%). Two plasmid-mediated colistin genes— mcr-1.1 harboured on IncX4 plasmids were detected in environmental isolates. The most prevalent sequence types (ST) were ST-155 (n = 8), ST-48 (n = 8) and ST-10 (n = 6). Two isolates of human and environmental sources with a SNPs difference of 6161 originating from the same farm shared a novel ST. The isolates had similar AMR genes and plasmid replicons. Conclusion MDR E.coli isolates were prevalent amongst poultry-workers, poultry, and the poultry farm/LBM environment. The emergence of MDR E. coli with novel ST in two isolates may be plasmid-mediated. Competent authorities should enforce AMR regulations to ensure prudent use of antimicrobials to limit the risk of transmission along the food chain.

Behaviour has crucial importance in dogs' adaptation to the anthropogenic environment. Functional breed selection, a relatively recent evolutionary event, resulted in strong differences regarding dogs' capacity for observational learning from humans. However, genetic distance among dog breeds has thus far not been connected to their social learning performance. Here we show first evidence that ancestry‐based clustering of dog breeds can result in biologically relevant phenotypic differences in their capacity to learn from humans. We analysed a large database of spatial problem‐solving (detour) tests, where a representative sample (N = 174) of cooperative and independent working dogs were sorted into 8 ancestry groups based on a genetic cladogram. We analysed whether ancestry would affect individual and social learning‐based spatial problem‐solving of dog breeds. Our results showed that ancestry groups with today's utility dog breeds performed this task best. Social learning was also prevalent in the ancestry group that collects English herding breeds and sight hounds as well—showing that genetically closely related cooperative and independent working dog breeds can possess similar sociocognitive traits. These results strengthen the notion that the behaviour of dog breeds can provide ecologically valid research opportunities both for proximate and ultimate evolutionary events.

A central issue in evolutionary ecology is how patterns of dispersal influence patterns of relatedness in populations. In terrestrial organisms, limited dispersal of offspring leads to groups of related individuals. By contrast, for most marine organisms, larval dispersal in open waters is thought to minimize kin associations within populations. However, recent molecular evidence and theoretical approaches have shown that limited dispersal, sibling cohesion and/or differential reproductive success can lead to kin association and elevated relatedness. Here, we tested the hypothesis that limited dispersal explains small-scale patterns of relatedness in the pajama cardinalfish Sphaeramia nematoptera . We used 19 microsatellite markers to assess parentage of 233 juveniles and pairwise relatedness among 527 individuals from 41 groups in Kimbe Bay, Papua New Guinea. Our findings support three predictions of the limited dispersal hypothesis: (i) elevated relatedness within groups, compared with among groups and elevated relatedness within reefs compared with among reefs; (ii) a weak negative correlation of relatedness with distance; (iii) more juveniles than would be expected by chance in the same group and the same reef as their parents. We provide the first example for natal philopatry at the group level causing small-scale patterns of genetic relatedness in a marine fish.

Cryptic female choice may enable polyandrous females to avoid inbreeding or bias offspring variability at key loci after mating. However, the role of these genetic benefits in cryptic female choice remains poorly understood. Female red junglefowl, Gallus gallus, bias sperm use in favour of unrelated males. Here, we experimentally investigate whether this bias is driven by relatedness per se, or by similarity at the major histocompatibility complex (MHC), genes central to vertebrate acquired immunity, where polymorphism is critical to an individual's ability to combat pathogens. Through experimentally controlled natural matings, we confirm that selection against related males' sperm occurs within the female reproductive tract but demonstrate that this is more accurately predicted by MHC similarity: controlling for relatedness per se, more sperm reached the eggs when partners were MHC-dissimilar. Importantly, this effect appeared largely owing to similarity at a single MHC locus (class I minor). Further, the effect of MHC similarity was lost following artificial insemination, suggesting that male phenotypic cues might be required for females to select sperm differentially. These results indicate that postmating mechanisms that reduce inbreeding may do so as a consequence of more specific strategies of cryptic female choice promoting MHC diversity in offspring.

Little is known about environmental transmission of Mycobacterium kansasii. We retrospectively investigated potential environmental acquisition, primarily water sources, of M. kansasii among 216 patients with pulmonary disease from an industrial city in Taiwan during 2015-2017. We analyzed sputum mycobacterial cultures using whole-genome sequencing and used hierarchical Bayesian spatial network methods to evaluate risk factors for genetic relatedness of M. kansasii strains. The mean age of participants was 67 years; 24.1% had previously had tuberculosis. We found that persons from districts served by 2 water purification plants were at higher risk of being infected with genetically related M. kansasii isolates. The adjusted odds ratios were 1.81 (1.25-2.60) for the Weng Park plant and 1.39 (1.12-1.71) for the Fongshan plant. Those findings unveiled the association between water purification plants and M. kansasii pulmonary disease, highlighting the need for further environmental investigations to evaluate the risk for M. kansasii transmission.