Towards a Socio-Economic Model for Southwest Asian Cereal Domestication

Mechanisms of selection for domestication traits in cereals and other annual plants are commonly explained from agro-technological and genetic perspectives. Since archaeobotanical data showed that domestication processes were slow and protracted, research focused on genetic constraints and hypothetical ‘non-selective’ management regimes to explain the low selection rates. I argue that these factors only partially explain the observed patterns and develop a model that contextualises the archaeobotanical data in their socio-economic settings. I propose that developments towards individual storage by small household units and the gradual increase in storage capacities with the development of extended households represent key factors for establishing the conditions for selection, as these practices isolated individually managed and stored cereal subpopulations and gradually reduced the need to replenish grain stocks with grains from unmanaged populations. This genetic isolation resulted in stronger and more persistent selection rates and facilitated the genetic fixation of domestication traits on a population level. Moreover, individual storage facilities within buildings reflect gradual developments towards households as the social units that mobilised agricultural labour, which negotiated new sharing principles over cultivated resources and drove the intensification of cultivation practices. In this sense, selection rates and the slow domestication process can be understood as a function of limited food sharing networks and increased labour-inputs into early arable environments—socio-economic processes that also unfolded gradually over a protracted period of time.

Evolvability: A Quantitative-Genetics Perspective

The concept of evolvability emerged in the early 1990s and soon became fashionable as a label for different streams of research in evolutionary biology. In evolutionary quantitative genetics, evolvability is defined as the ability of a population to respond to directional selection. This differs from other fields by treating evolvability as a property of populations rather than organisms or lineages and in being focused on quantification and short-term prediction rather than on macroevolution. While the term evolvability is new to quantitative genetics, many of the associated ideas and research questions have been with the field from its inception as biometry. Recent research on evolvability is more than a relabeling of old questions, however. New operational measures of evolvability have opened possibilities for understanding adaptation to rapid environmental change, assessing genetic constraints, and linking micro- and macroevolution.

Integrating genomics and multivariate evolutionary quantitative genetics: a case study of constraints on sexual selection in Drosophila serrata

In evolutionary quantitative genetics, the genetic variance–covariance matrix, G , and the vector of directional selection gradients, β , are key parameters for predicting multivariate selection responses and genetic constraints. Historically, investigations of G and β have not overlapped with those dissecting the genetic basis of quantitative traits. Thus, it remains unknown whether these parameters reflect pleiotropic effects at individual loci. Here, we integrate multivariate genome-wide association study (GWAS) with G and β estimation in a well-studied system of multivariate constraint: sexual selection on male cuticular hydrocarbons (CHCs) in Drosophila serrata . In a panel of wild-derived re-sequenced lines, we augment genome-based restricted maximum likelihood to estimate G alongside multivariate single nucleotide polymorphism (SNP) effects, detecting 532 significant associations from 1 652 276 SNPs. Constraint was evident, with β lying in a direction of G with low evolvability. Interestingly, minor frequency alleles typically increased male CHC-attractiveness suggesting opposing natural selection on β . SNP effects were significantly misaligned with the major eigenvector of G , g max , but well aligned to the second and third eigenvectors g 2 and g 3 . We discuss potential factors leading to these varied results including multivariate stabilizing selection and mutational bias. Our framework may be useful as researchers increasingly access genomic methods to study multivariate selection responses in wild populations.

Exceptionally Steep Brain-Body Evolutionary Allometry Underlies the Unique Encephalization of Osteoglossiformes

Brain-body static allometry, which is the relationship between brain size and body size within species, is thought to reflect developmental and genetic constraints. Existing evidence suggests that the evolution of large brain size without accompanying changes in body size (that is, encephalization) may occur when this constraint is relaxed. Teleost fish species are generally characterized by having close-fitting brain-body static allometries, leading to strong allometric constraints and small relative brain sizes. However, one order of teleost, Osteoglossiformes, underwent extreme encephalization, and its mechanistic bases are unknown. Here, I used a dataset and phylogeny encompassing 859 teleost species to demonstrate that the encephalization of Osteoglossiformes occurred through an increase in the slope of evolutionary (among-species) brain-body allometry. The slope is virtually isometric (1.03 ± 0.09 SE), making it one of the steepest evolutionary brain-body allometric slopes reported to date, and it deviates significantly from the evolutionary brain-body allometric slopes of other clades of teleost. Examination of the relationship between static allometric parameters (intercepts and slopes) and evolutionary allometry revealed that the dramatic steepening of the evolutionary allometric slope in Osteoglossiformes was a combined result of evolution in the slopes and intercepts of static allometry. These results suggest that the evolution of static allometry, which likely has been driven by evolutionary changes in the rate and timing of brain development, has facilitated the unique encephalization of Osteoglossiformes.

Integrating genomics and multivariate evolutionary quantitative genetics: A case study of multivariate constraints on sexual selection in Drosophila serrata

In evolutionary quantitative genetics, the genetic variance-covariance matrix, G, and the vector of directional selection gradients, β , are key parameters for predicting multivariate selection responses and genetic constraints. Historically, investigations of G and β have not overlapped with those dissecting the genetic basis of quantitative traits. Thus, it remains unknown whether these parameters reflect pleiotropic effects at individual loci. Here, we integrate multivariate GWAS with G and β estimation in a well-studied system of multivariate constraint; sexual selection on male cuticular hydrocarbons (CHCs) in Drosophila serrata. In a panel of wild-derived resequenced lines, we augment genome-based REML, (GREML) to estimate G alongside multivariate SNP effects, detecting 532 significant associations from 1,652,276 SNPs. Constraint was evident, with β lying in a direction of G with low evolvability. Interestingly, minor frequency alleles typically increased male CHC-attractiveness suggesting opposing natural selection on β. SNP effects were significantly misaligned with the major eigenvector of G, gmax, but well aligned to the second and third eigenvectors g2 and g3. We discuss potential factors leading to these varied results including multivariate stabilising selection and mutational bias. Our framework may be useful as researchers increasingly access genomic methods to study multivariate selection responses in wild populations.

Genetic influences on hub connectivity of the human connectome

Brain network hubs are both highly connected and highly inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization are poorly understood. Using diffusion-weighted magnetic resonance imaging in twins, we identify a major role for genes, showing that they preferentially influence connectivity strength between network hubs of the human connectome. Using transcriptomic atlas data, we show that connected hubs demonstrate tight coupling of transcriptional activity related to metabolic and cytoarchitectonic similarity. Finally, comparing over thirteen generative models of network growth, we show that purely stochastic processes cannot explain the precise wiring patterns of hubs, and that model performance can be improved by incorporating genetic constraints. Our findings indicate that genes play a strong and preferential role in shaping the functionally valuable, metabolically costly connections between connectome hubs.

Footprints in the Sand: Deep Taxonomic Comparisons in Vertebrate Genomics to Unveil the Genetic Programs of Human Longevity

With the modern quality, quantity, and availability of genomic sequencing across species, as well as across the expanse of human populations, we can screen for shared signatures underlying longevity and lifespan. Knowledge of these mechanisms would be medically invaluable in combating aging and age-related diseases. The diversity of longevities across vertebrates is an opportunity to look for patterns of genetic variation that may signal how this life history property is regulated, and ultimately how it can be modulated. Variation in human longevity provides a unique window to look for cases of extreme lifespan within a population, as well as associations across populations for factors that influence capacity to live longer. Current large cohort studies support the use of population level analyses to identify key factors associating with human lifespan. These studies are powerful in concept, but have demonstrated limited ability to resolve signals from background variation. In parallel, the expanding catalog of sequencing and annotation from diverse species, some of which have evolved longevities well past a human lifespan, provides independent cases to look at the genomic signatures of longevity. Recent comparative genomic work has shown promise in finding shared mechanisms associating with longevity among distantly related vertebrate groups. Given the genetic constraints between vertebrates, we posit that a combination of approaches, of parallel meta-analysis of human longevity along with refined analysis of other vertebrate clades having exceptional longevity, will aid in resolving key regulators of enhanced lifespan that have proven to be elusive when analyzed in isolation.

Widening Inborn Constraints for Language Ability: The Case for Autism

What does the way autistics bypass, learn, and eventually master language tell us about human linguistic ability? Here, we argue that non-social acquisition of language, in addition to representing a strong argument for nativist models of human language, may be encompassed within the human-specific orientation and mastery of complex embedded structures, of which language represents one realization. Non-social language learning could thus represent the extension of available linguistic, and non-linguistic material processed by human genetic constraints, allowing language acquisition. This deviation from typical developmental language acquisition may ultimately allow access to language, sometimes in its most elaborate forms, and also explains the possibility of the absence of its development when applied to primarily non-linguistic structured material. However, such enlargement of material-specificity does not cast doubts about its human nature. Regardless of the adaptive success or failure of non-social language learning, it is up to science, legal policies, and ethical principles to strive to maintain autism as a human potentiality to further foster our vision of a plural society.

Using Wolbachia to eliminate dengue – will the virus fight back?

Recent field trials have demonstrated that dengue incidence can be substantially reduced by introgressing strains of the endosymbiotic bacterium, Wolbachia into Aedes aegypti mosquito populations. This strategy relies on Wolbachia reducing the susceptibility of Ae. aegypti to disseminated infection by positive-sense RNA viruses like dengue. However, RNA viruses are well known to adapt to antiviral pressures. Here we review the viral infection stages where selection for Wolbachia-resistant virus variants could occur. We also consider the genetic constraints imposed on viruses that alternate between vertebrate and invertebrate hosts, and the likely selection pressures that dengue virus might adapt to in order to be effectively transmitted by Ae. aegypti that carry Wolbachia. Whilst there are hurdles to dengue viruses developing resistance to Wolbachia, we suggest that long-term surveillance for resistant viruses should be an integral component of Wolbachia-introgression biocontrol programs.