Evolution of gene networks underlying adaptation to drought stress in the wild tomato Solanum chilense.

Drought stress is a key limitation for plant growth and colonization of arid habitats. We study the evolution of gene expression response to drought stress in a wild tomato, Solanum chilense, naturally occurring in dry habitats in South America. We conduct a transcriptome analysis under standard and drought experimental conditions to identify drought-responsive gene networks and estimate the age of the involved genes. We identify two main regulatory networks corresponding to two typical drought-responsive strategies: cell cycle and fundamental metabolic processes. The metabolic network exhibits a more recent evolutionary origin and a more variable transcriptome response than the cell cycle network (with ancestral origin and higher conservation of the transcriptional response). We also integrate population genomics analyses to reveal positive selection signals acting at the genes of both networks, revealing that genes exhibiting selective sweeps of older age also exhibit greater connectivity in the networks. These findings suggest that adaptive changes first occur at core genes of drought response networks, driving significant network re-wiring, which likely underpins species divergence and further spread into drier habitats. Combining transcriptomics and population genomics approaches, we decipher the timing of gene network evolution for drought stress response in arid habitats.

Nuclear compensatory evolution driven by mito-nuclear incompatibilities.

Mitochondrial function relies on the coordinated expression of mitochondrial and nuclear genes, exhibiting remarkable resilience despite high mitochondrial mutation rates. The nuclear compensation mechanism suggests deleterious mitochondrial alleles drive compensatory nuclear mutations to preserve mito-nuclear compatibility. However, prevalence and factors conditioning this phenomenon remain debated due to its conflicting evidence. Here, we investigate how mito-nuclear incompatibilities impact substitutions in a model for species radiation. Mating success depends on genetic compatibility (nuclear DNA) and spatial proximity. Populations evolve from partially compatible mito-nuclear states, simulating mitochondrial DNA (mtDNA) introgression. Mutations do not confer advantages nor disadvantages, but individual fecundity declines with increasing incompatibilities, selecting for mito-nuclear coordination. We find that selection for mito-nuclear compatibility affects each genome differently based on their initial state. In compatible gene pairs, selection reduces substitutions in both genomes, while in incompatible nuclear genes, it consistently promotes compensation, facilitated by more mismatches. Interestingly, high mitochondrial mutation rates can reduce nuclear compensation by increasing mtDNA rectification, while substitutions in initially compatible nuclear gene are boosted. Finally, the presence of incompatibilities accelerates species radiation, but equilibrium richness is not directly correlated to substitution rates, revealing the complex dynamics triggered by mitochondrial introgression and mito-nuclear coevolution. Our study provides a perspective on nuclear compensation and the role of mito-nuclear incompatibilities in speciation by exploring extreme scenarios and identifying trends that empirical data alone cannot reveal. We emphasize the challenges in detecting these dynamics and propose analyzing specific genomic signatures could shed light on this evolutionary process.

Spatially heterogeneous selection and inter-varietal differentiation maintain population structure and local adaptation in a widespread conifer.

BACKGROUND: Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco) plays a critical role in the ecology and economy of Western North America. This conifer species comprises two distinct varieties: the coastal variety (var. menziesii) along the Pacific coast, and the interior variety (var. glauca) spanning the Rocky Mountains into Mexico, with instances of inter-varietal hybridization in Washington and British Columbia. Recent investigations have focused on assessing environmental pressures shaping Douglas-fir's genomic variation for a better understanding of its evolutionary and adaptive responses. Here, we characterize range-wide population structure, estimate inter-varietal hybridization levels, identify candidate loci for climate adaptation, and forecast shifts in species and variety distribution under future climates. RESULTS: Using a custom SNP-array, we genotyped 540 trees revealing four distinct clusters with asymmetric admixture patterns in the hybridization zone. Higher genetic diversity observed in coastal and hybrid populations contrasts with lower diversity in inland populations of the southern Rockies and Mexico, exhibiting a significant isolation by distance pattern, with less marked but still significant isolation by environment. For both varieties, we identified candidate loci associated with local adaptation, with hundreds of genes linked to processes such as stimulus response, reactions to chemical compounds, and metabolic functions. Ecological niche modeling revealed contrasting potential distribution shifts among the varieties in the coming decades, with interior populations projected to lose habitat and become more vulnerable, while coastal populations are expected to gain suitable areas. CONCLUSIONS: Overall, our findings provide crucial insights into the population structure and adaptive potential of Douglas-fir, with the coastal variety being the most likely to preserve its evolutionary path throughout the present century, which carry implications for the conservation and management of this species across their range.

SNP Markers: Analysis of Genetic Diversity and Identification of Genomic Regions in Pantaneiro Sheep and Texel Sheep Under Natural Selection.

BACKGROUND: Sheep farming is growing substantially in Brazil, driven by the increasing demand for sheep meat. This rising demand has heightened the focus on sheep, making them the subject of numerous studies, including those centered on genetic analysis. A notable research area involves Pantaneiro sheep, which are indigenous to the Pantanal region of Mato Grosso do Sul and other locations. These sheep are of particular interest due to their adaptation to the unique environmental conditions of the Pantanal, a floodplain characterized by its distinctive climatic and ecological features. This study primarily aimed to conduct a comprehensive genomic analysis of Pantanal sheep subjected to natural selection within the Pantanal region and compare different sample herds using methodological approaches. METHODS: Genomic analysis was performed to examine genetic diversity and structure via GGP50K single nucleotide polymorphism (SNP) analysis. A sample of 192 adult sheep over 4 years old was categorized into seven populations based on location: Six populations comprised Pantaneiro sheep with one Texel sheep population. Outlier SNPs were assessed to pinpoint regions under natural selection, with comparisons between the Pantaneiro and the commercial Texel breeds. All data analyses were conducted using the R programming language, employing specialized genetic analysis packages. These outlier SNPs were detected using three methodologies, PCAdapt, OutFLANK, and FDIST2/fsthet, with false discovery rate (FDR) corrections applied to ensure result accuracy. Each method was evaluated, and the genes associated with the identified SNPs were cross-referenced with the most recent sheep genome database, focusing specifically on genes with known phenotypic traits. RESULTS: Analysis of a sample comprising 192 adult individuals revealed greater genetic variability within the Pantaneiro breed than the Texel breed, highlighting the adaptation of the Pantaneiro breed to the unique Pantanal environment. Conversely, the Texel breed exhibited significantly higher levels of inbreeding, attributed to its controlled breeding practices. Outlier SNPs were detected with notable variation across different methodologies, underscoring the importance of FDR correction in ensuring the reliability and concentration of identified outliers. These outlier SNPs facilitated the identification of genes associated with key phenotypic traits, including hair growth, tissue regeneration, pigmentation regulation, and muscle capacity. CONCLUSION: The integrated analysis of methodologies demonstrated significant efficiency in elucidating the genomic landscape of Pantanal sheep, highlighting the genetic richness inherent in sheep from the Pantanal region of Mato Grosso do Sul. The techniques employed effectively identified outlier SNPs associated with phenotypically relevant genes. These findings, which reveal greater genetic variability and adaptability, underscore the potential of these animals for future research and their significance within Brazilian sheep farming. The Texel breed served as a valuable comparative group, illustrating the limited genetic variability in highly controlled breeding environments.

Comparative Genomics Supports Ecologically Induced Selection as a Putative Driver of Banded Penguin Diversification.

The relative importance of genetic drift and local adaptation in facilitating speciation remains unclear. This is particularly true for seabirds, which can disperse over large geographic distances, providing opportunities for intermittent gene flow among distant colonies that span the temperature and salinity gradients of the oceans. Here, we delve into the genomic basis of adaptation and speciation of banded penguins, Galápagos (Spheniscus mendiculus), Humboldt (Spheniscus humboldti), Magellanic (Spheniscus magellanicus), and African penguins (Spheniscus demersus), by analyzing 114 genomes from the main 16 breeding colonies. We aim to identify the molecular mechanism and genomic adaptive traits that have facilitated their diversifications. Through positive selection and gene family expansion analyses, we identified candidate genes that may be related to reproductive isolation processes mediated by ecological thermal niche divergence. We recover signals of positive selection on key loci associated with spermatogenesis, especially during the recent peripatric divergence of the Galápagos penguin from the Humboldt penguin. High temperatures in tropical habitats may have favored selection on loci associated with spermatogenesis to maintain sperm viability, leading to reproductive isolation among young species. Our results suggest that genome-wide selection on loci associated with molecular pathways that underpin thermoregulation, osmoregulation, hypoxia, and social behavior appears to have been crucial in local adaptation of banded penguins. Overall, these results contribute to our understanding of how the complexity of biotic, but especially abiotic, factors, along with the high dispersal capabilities of these marine species, may promote both neutral and adaptive lineage divergence even in the presence of gene flow.

Genetic Signatures of Positive Selection in Human Populations Adapted to High Altitude in Papua New Guinea.

Papua New Guinea (PNG) hosts distinct environments mainly represented by the ecoregions of the Highlands and Lowlands that display increased altitude and a predominance of pathogens, respectively. Since its initial peopling approximately 50,000 years ago, inhabitants of these ecoregions might have differentially adapted to the environmental pressures exerted by each of them. However, the genetic basis of adaptation in populations from these areas remains understudied. Here, we investigated signals of positive selection in 62 highlanders and 43 lowlanders across 14 locations in the main island of PNG using whole-genome genotype data from the Oceanian Genome Variation Project (OGVP) and searched for signals of positive selection through population differentiation and haplotype-based selection scans. Additionally, we performed archaic ancestry estimation to detect selection signals in highlanders within introgressed regions of the genome. Among highland populations we identified candidate genes representing known biomarkers for mountain sickness (SAA4, SAA1, PRDX1, LDHA) as well as candidate genes of the Notch signaling pathway (PSEN1, NUMB, RBPJ, MAML3), a novel proposed pathway for high altitude adaptation in multiple organisms. We also identified candidate genes involved in oxidative stress, inflammation, and angiogenesis, processes inducible by hypoxia, as well as in components of the eye lens and the immune response. In contrast, candidate genes in the lowlands are mainly related to the immune response (HLA-DQB1, HLA-DQA2, TAAR6, TAAR9, TAAR8, RNASE4, RNASE6, ANG). Moreover, we find two candidate regions to be also enriched with archaic introgressed segments, suggesting that archaic admixture has played a role in the local adaptation of PNG populations.

Mitochondrial, nuclear and morphological differentiation in the swimming crab Liocarcinus depurator along the Atlantic-Mediterranean transition.

Environmental gradients in the sea may coincide with phenotypic or genetic gradients resulting from an evolutionary balance between selection and dispersal. The population differentiation of the swimming crab, Liocarcinus depurator, an important by-catch species in the Mediterranean Sea and North-East Atlantic, was assessed using both genetic and morphometric approaches. A total of 472 specimens were collected along its distribution area, and 17 morphometric landmarks, one mitochondrial gene (COI) and 11 polymorphic microsatellite markers were scored in 350, 287 and 280 individuals, respectively. Morphometric data lacked significant differences, but genetic analyses showed significant genetic differentiation between Atlantic and Mediterranean populations, with a steeper gradient in COI compared to microsatellite markers. Interestingly, nuclear differentiation was due to an outlier locus with a gradient in the Atlantic-Mediterranean transition area overlapping with the mtDNA gradient. Such overlapping clines are likely to be maintained by natural selection. Our results suggest a scenario of past isolation with local adaptation and secondary contact between the two basins. Local adaptation during the process of vicariance may reinforce genetic differentiation at loci maintained by environmental selection even after secondary contact.

Genetic divergence and truncation and simultaneous selection in inbred families (S1) of elephant grass for bioenergetic purposes via mixed models.

The State University of North Fluminense Darcy Ribeiro (UENF) has been developing for fifteen years a breeding program that aims at the development of new cultivars of elephant grass due to its high potential and the low availability of cultivars developed by genetic breeding programs that meet the needs of producers in the State of Rio de Janeiro. In this sense, inbred families were also obtained as a way of fixing potential alleles for traits related to production, as the inbreeding process apparently does not strongly affect elephant grass in aspects related to inbreeding depression. This study aimed to estimate genetic diversity, variance components and prediction of genotypic values in 11 (S1) elephant grass families, and perform the truncation and simultaneous selection of traits using the selection index, by mixed models. The experimental design consisted of randomized blocks with 11 (S1) families, three replications, and six plants per plot. For variables dry matter production, percentage of dry matter, plant height, stem diameter, number of tillers and leaf blade width, was performed the estimation of genetic parameters and selection of the best genotypes based selection index using mixed model. The descriptors were subjected to correlation analysis, distance matrices were generated by the Mahalanobis method, and individuals were grouped by the UPGMA method. In the selection via mixed models (REML/BLUP), families 6, 11, 8, 1, 3, 7, and 9 contributed most of the genotypes selected for the evaluated traits, indicating their high potential to generate superior genotype. The selection indices via mixed models indicated that the multiplicative index presented a greater selection gain.The phenotypic correlations showed the possibility of performing an indirect selection from six evaluated traits.The genotypes were separated into 18 groups by the Mahalanobis distance, allowing the observation of a wide genetic diversity. The most divergent and productive genotypes were self-fertilized to obtain the second generation (S2), continuing the development program.

A Penalized Regression Method for Genomic Prediction Reduces Mismatch between Training and Testing Sets.

Genomic selection (GS) is changing plant breeding by significantly reducing the resources needed for phenotyping. However, its accuracy can be compromised by mismatches between training and testing sets, which impact efficiency when the predictive model does not adequately reflect the genetic and environmental conditions of the target population. To address this challenge, this study introduces a straightforward method using binary-Lasso regression to estimate ß coefficients. In this approach, the response variable assigns 1 to testing set inputs and 0 to training set inputs. Subsequently, Lasso, Ridge, and Elastic Net regression models use the inverse of these ß coefficients (in absolute values) as weights during training (WLasso, WRidge, and WElastic Net). This weighting method gives less importance to features that discriminate more between training and testing sets. The effectiveness of this method is evaluated across six datasets, demonstrating consistent improvements in terms of the normalized root mean square error. Importantly, the model's implementation is facilitated using the glmnet library, which supports straightforward integration for weighting ß coefficients.

Optimizing Genomic Parental Selection for Categorical and Continuous-Categorical Multi-Trait Mixtures.

This study presents a novel approach for the optimization of genomic parental selection in breeding programs involving categorical and continuous-categorical multi-trait mixtures (CMs and CCMMs). Utilizing the Bayesian decision theory (BDT) and latent trait models within a multivariate normal distribution framework, we address the complexities of selecting new parental lines across ordinal and continuous traits for breeding. Our methodology enhances precision and flexibility in genetic selection, validated through extensive simulations. This unified approach presents significant potential for the advancement of genetic improvements in diverse breeding contexts, underscoring the importance of integrating both categorical and continuous traits in genomic selection frameworks.

Genome scans reveal signals of selection associated with pollution in fish populations of Basilichthys microlepidotus, an endemic species of Chile.

The Maipo River catchment is one of Chile's most polluted basins. In recent decades, discharges of untreated sewage and organic matter have caused eutrophication and water quality degradation. We employed the indigenous silverfish species Basilichthys microlepidotus as a model organism to investigate the process of adaptation and selection on genes influenced by pollution. Using variation at single nucleotide polymorphisms (SNPs), we determined the temporal stability of the population structure patterns previously identified in this species by varying SNPs. We also examined local adaptation to pollution-selected genes. Using the genotypes of 7684 loci in 180 individuals, we identified 429 and 700 loci that may be undergoing selection. We detected these loci using the FSTHET and ARLEQUIN outlier detection software, respectively. Both software packages simultaneously identified a total of 250 loci. B. microlepidotus' population structure did not change over time at contaminated or unpolluted sites. In addition, our analysis found: (i) selection of genes associated with pollution, consistent with observations in other organisms; (ii) identification of candidate genes that are functionally linked to the same biological processes, molecular functions and/or cellular components that previously showed differential expression in the same populations; and (iii) a candidate gene with differential expression and a non-synonymous substitution.

Across two continents: The genomic basis of environmental adaptation in house mice (Mus musculus domesticus) from the Americas.

Replicated clines across environmental gradients can be strong evidence of adaptation. House mice (Mus musculus domesticus) were introduced to the Americas by European colonizers and are now widely distributed from Tierra del Fuego to Alaska. Multiple aspects of climate, such as temperature, vary predictably across latitude in the Americas. Past studies of North American populations across latitudinal gradients provided evidence of environmental adaptation in traits related to body size, metabolism, and behavior and identified candidate genes using selection scans. Here, we investigate genomic signals of environmental adaptation on a second continent, South America, and ask whether there is evidence of parallel adaptation across multiple latitudinal transects in the Americas. We first identified loci across the genome showing signatures of selection related to climatic variation in mice sampled across a latitudinal transect in South America, accounting for neutral population structure. Consistent with previous results, most candidate SNPs were in putatively regulatory regions. Genes that contained the most extreme outliers relate to traits such as body weight or size, metabolism, immunity, fat, eye function, and the cardiovascular system. We then compared these results with the results of analyses of published data from two transects in North America. While most candidate genes were unique to individual transects, we found significant overlap among candidate genes identified independently in the three transects. These genes are diverse, with functions relating to metabolism, immunity, cardiac function, and circadian rhythm, among others. We also found parallel shifts in allele frequency in candidate genes across latitudinal gradients. Finally, combining data from all three transects, we identified several genes associated with variation in body weight. Overall, our results provide strong evidence of shared responses to selection and identify genes that likely underlie recent environmental adaptation in house mice across North and South America.

Selective and non-selective evolutionary signatures found in the simplest replicative biological entities.

Mitoviruses, which are considered evolutionary relics of extinct alpha-proteobacteria RNA phages, represent one of the simplest self-replicating biological systems. This study aims to quantitatively describe genomes and identify potential genomic signatures that support the protein phylogenetic-based classification criterion. Genomic variables, such as mononucleotide and dinucleotide composition, codon usage bias, and minimal free energy derived from optimized predicted RNA secondary structure, were analyzed. From the values obtained, the main evolutionary pressures were discussed, indicating that natural selection plays a significant role in shaping mitovirus genomes. However, neutral evolution also makes a significant contribution. This study reveals a significant discovery of structural divergence in Kvaramitovirus. The energy minimization approach employed to study 2D folding in this study reveals a distinct spatial organization of their genomes, providing evidence for the hypothesis of a single evolutionary event of circularization in the most recent common ancestor of the lineage. This hypothesis was discussed in light of recent discoveries by other researchers that partially support the existence of mitoviruses with circular genomes. Finally, this study represents a significant advancement in the understanding of mitoviruses, as it quantitatively describes the nucleotide sequence at the family and genus taxonomic levels. Additionally, we provide hypotheses that can be experimentally validated to inspire new research and address the gaps in knowledge of this fascinating, basally divergent RNA virus lineage.

Evidence for gene flow and trait reversal during radiation of Mexican Goodeid fish.

Understanding the phylogeographic history of a group and identifying the factors contributing to speciation is an important challenge in evolutionary biology. The Goodeinae are a group of live-bearing fishes endemic to Mexico. Here, we develop genomic resources for species within the Goodeinae and use phylogenomic approaches to characterise their evolutionary history. We sequenced, assembled and annotated the genomes of four Goodeinae species, including Ataeniobius toweri, the only matrotrophic live-bearing fish without a trophotaenia in the group. We estimated timings of species divergence and examined the extent and timing of introgression between the species to assess if this may have occurred during an early radiation, or in more recent episodes of secondary contact. We used branch-site models to detect genome-wide positive selection across Goodeinae, and we specifically asked whether this differs in A. toweri, where loss of placental viviparity has recently occurred. We found evidence of gene flow between geographically isolated species, suggesting vicariant speciation was supplemented by limited post-speciation gene flow, and gene flow may explain previous uncertainties about Goodeid phylogeny. Genes under positive selection in the group are likely to be associated with the switch to live-bearing. Overall, our studies suggest that both volcanism-driven vicariance and changes in reproductive mode influenced radiation in the Goodeinae.

Multi-trait index: selection and recommendation of superior black bean genotypes as new improved varieties.

Common bean provides diet rich in vitamins, fiber, minerals, and protein, which could contribute into food security of needy populations in many countries. Developing genotypes that associate favorable agronomic and grain quality traits in the common bean crop could increase the chances of adopting new cultivars black bean. In this context, the present study aimed at selection of superior black bean lines using multi-variate indexes, Smith-Hazel-index, and genotype by yield*trait biplot analysis. These trials were conducted in Campos dos Goytacazes - RJ, in 2020 and 2021. The experimental design used was randomized blocks, with 28 treatments and three replications. The experimental unit consisted of four rows 4.0 m long, spaced at 0.50 m apart, with a sowing density of 15 seeds per meter. The two central rows were used for the evaluations. The selection of superior genotypes was conducted using the multiple trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), multi-trait index based on factor analysis and genotype-ideotype distance (FAI-BLUP), Smith-Hazel index, and Genotype by Yield*Trait Biplot (GYT). The multivariate indexes efficiently selected the best black bean genotypes, presenting desirable selection gains for most traits. The use of multivariate indexes and GYT enable the selection of early genotypes with higher grain yields. These lines G9, G13, G17, G23, and G27 were selected based on their performance for multiple traits closest to the ideotype and could be recommended as new varieties.

Use of simulation to optimize a sweet corn breeding program: implementing genomic selection and doubled haploid technology.

Genomic selection and doubled haploids hold significant potential to enhance genetic gains and shorten breeding cycles across various crops. Here, we utilized stochastic simulations to investigate the best strategies for optimize a sweet corn breeding program. We assessed the effects of incorporating varying proportions of old and new parents into the crossing block (3:1, 1:1, 1:3, and 0:1 ratio, representing different degrees of parental substitution), as well as the implementation of genomic selection in two distinct pipelines: one calibrated using the phenotypes of testcross parents (GSTC scenario) and another using F1 individuals (GSF1). Additionally, we examined scenarios with doubled haploids, both with (DH) and without (DHGS) genomic selection. Across 20 years of simulated breeding, we evaluated scenarios considering traits with varying heritabilities, the presence or absence of genotype-by-environment effects, and two program sizes (50 vs 200 crosses per generation). We also assessed parameters such as parental genetic mean, average genetic variance, hybrid mean, and implementation costs for each scenario. Results indicated that within a conventional selection program, a 1:3 parental substitution ratio (replacing 75% of parents each generation with new lines) yielded the highest performance. Furthermore, the GSTC model outperformed the GSF1 model in enhancing genetic gain. The DHGS model emerged as the most effective, reducing cycle time from 5 to 4 years and enhancing hybrid gains despite increased costs. In conclusion, our findings strongly advocate for the integration of genomic selection and doubled haploids into sweet corn breeding programs, offering accelerated genetic gains and efficiency improvements.

Identifying selection strategies based on the practices and preferences of small ruminant farmers to improve the sustainability of their breeding systems.

Small ruminant farming is of socio-economic and environmental importance to many rural communities around the world. The SMARTER H2020 project aims to redefine genetic selection criteria to increase the sustainability of the sector. The objective of this study was to analyse the selection and breeding management practices of small ruminant producers and breeders, linked with socio-technical elements that shape them. The study is based on farm surveys using semi-structured interviews conducted in five countries (France, Spain, Italy, Greece, and Uruguay) across 272 producers and breeders of 13 sheep and goat breeds, and 15 breed × system combinations. The information was collected in four sections. The first and second sections dealt with general elements of structure and management of the system and the flock/herd. The third section focused on selection and breeding management practices: criteria for culling and replacement of females, selection criteria for males, use of estimated breeding values and global indexes, and preferences for indexing new traits to increase the sustainability of their system. The fourth section aimed to collect socio-technical information. We used a data abstraction method to standardise the representation of these data. A mixed data factor analysis followed by a hierarchical ascending classification allowed the characterisation of three profiles of selection and breeding management: (1) a profile of producers (n = 93) of small flocks/herds, with little knowledge or use of genetic selection and improvement tools (selection index, artificial insemination, performance recording); these farmers do not feel that new traits are needed to improve the sustainability of their system. (2) a profile of producers (n = 34) of multibreed flocks/herds that rely significantly on grazing; they are familiar with genetic tools, they currently use AI; they would like the indexes to include more health and robustness characteristics, to make their animals more resistant and to increase the sustainability of their system. And (3) a profile of producers or breeders (n = 145) of large flocks/herds, with specific culling criteria; these farmers are satisfied with the current indexes to maintain the sustainability of their system. These results are elements that can be used by private breeding companies and associations to support the evolution of selection objectives to increase the resilience of animals and to improve the sustainability of the small ruminant breeding systems.

Impact of pre-copulatory sexual cannibalism on genetic diversity and efficacy of selection.

Factors that increase reproductive variance among individuals act to reduce effective population size (Ne), which accelerates the loss of genetic diversity and decreases the efficacy of purifying selection. These factors include sexual cannibalism, offspring investment and mating system. Pre-copulatory sexual cannibalism, where the female consumes the male prior to mating, exacerbates this effect. We performed comparative transcriptomics in two spider species, the cannibalistic Trechaleoides biocellata and the non-cannibalistic T. keyserlingi, to generate genomic evidence to support these predictions. First, we estimated heterozygosity and found that genetic diversity is relatively lower in the cannibalistic species. Second, we calculated dN/dS ratios as a measure of purifying selection; a higher dN/dS ratio indicated relaxed purifying selection in the cannibalistic species. These results are consistent with the hypothesis that sexual cannibalism impacts operational sex ratio and demographic processes, which interact with evolutionary forces to shape the genetic structure of populations. However, other factors such as the mating system and life-history traits contribute to shaping Ne. Comparative analyses across multiple contrasting species pairs would be required to disentangle these effects. Our study highlights that extreme behaviours such as pre-copulatory cannibalism may have profound eco-evolutionary effects.

Selection drives divergence of eye morphology in sympatric Heliconius butterflies.

When populations experience different sensory conditions, natural selection may favor sensory system divergence, affecting peripheral structures and/or downstream neural pathways. We characterized the outer eye morphology of sympatric Heliconius butterflies from different forest types and their first-generation reciprocal hybrids to test for adaptive visual system divergence and hybrid disruption. In Panama, Heliconius cydno occurs in closed forests, whereas Heliconius melpomene resides at the forest edge. Among wild individuals, H. cydno has larger eyes than H. melpomene, and there are heritable, habitat-associated differences in the visual brain structures that exceed neutral divergence expectations. Notably, hybrids have intermediate neural phenotypes, suggesting disruption. To test for similar effects in the visual periphery, we reared both species and their hybrids in common garden conditions. We confirm that H. cydno has larger eyes and provide new evidence that this is driven by selection. Hybrid eye morphology is more H. melpomene-like despite body size being intermediate, contrasting with neural trait intermediacy. Overall, our results suggest that eye morphology differences between H. cydno and H. melpomene are adaptive and that hybrids may suffer fitness costs due to a mismatch between the peripheral visual structures and previously described neural traits that could affect visual performance.

Estimation of genetic parameters for maintenance energy requirements and residual feed intake in Nellore cattle.

We estimated heritabilities and genetic and phenotypic correlation estimates for maintenance energy requirements (NEmR), residual feed intake (RFI), growth, carcass and reproductive indicator traits, using data from 41 feed efficiency trials in Brazil, comprising 4381 males and females. Continuous traits were analysed using a linear animal model and threshold traits were analysed using a threshold animal model. The heritability estimates were low for RFI (0.190) and NEmR (0.193); other heritabilities were mainly moderate (growth and carcass traits) or high (sexual precocity traits). The genetic correlation of RFI with NEmR was high (0.701). The genetic correlations of NEmR were low with carcass and reproductive traits, and moderate with growth traits. Thus, selection to improve weaning weight and female sexual precocity indicator traits would not affect maintenance energy requirement. Genetic selection to reduce maintenance energy requirements is feasible and would also reduce DMI and RFI. Selection to improve RFI can be used to identify animals with lower maintenance energy requirements. Long-term selection to reduce RFI and NEmR would have favourable effects on yearling weight, carcass muscle indicator traits and female sexual precocity. Genetic (co)variance component estimates for NEmR, in conjunction with economic values of selection criteria, may be used to develop novel approaches for genetic selection to improve efficiency of beef production.