The genomic health of ancient hominins

The genomes of ancient humans, Neandertals, and Denisovans contain many alleles that influence disease risks. Using genotypes at 3180 disease-associated loci, we estimated the disease burden of 147 ancient genomes. After correcting for missing data, genetic risk scores were generated for nine disease categories and the set of all combined diseases. These genetic risk scores were used to examine the effects of different types of subsistence, geography, and sample age on the number of risk alleles in each ancient genome. On a broad scale, hereditary disease risks are similar for ancient hominins and modern-day humans, and the GRS percentiles of ancient individuals span the full range of what is observed in present day individuals. In addition, there is evidence that ancient pastoralists may have had healthier genomes than hunter-gatherers and agriculturalists. We also observed a temporal trend whereby genomes from the recent past are more likely to be healthier than genomes from the deep past. This calls into question the idea that modern lifestyles have caused genetic load to increase over time. Focusing on individual genomes, we find that the overall genomic health of the Altai Neandertal is worse than 97% of present day humans and that Ötzi the Tyrolean Iceman had a genetic predisposition to gastrointestinal and cardiovascular diseases. As demonstrated by this work, ancient genomes afford us new opportunities to diagnose past human health, which has previously been limited by the quality and completeness of remain

Nourishment level affects caste-related gene expression in Polistes wasps

Background: Social insects exhibit striking phenotypic plasticity in the form of distinct reproductive (queen) and non-reproductive (worker) castes, which are typically driven by differences in the environment during early development. Nutritional environment and nourishment during development has been shown to be broadly associated with caste determination across social insect taxa such as bees, wasps, and termites. In primitively social insects such as Polistes paper wasps, caste remains flexible throughout adulthood, but there is evidence that nourishment inequalities can bias caste development with workers receiving limited nourishment compared to queens. Dominance and vibrational signaling are behaviors that have also been linked to caste differences in paper wasps, suggesting that a combination of nourishment and social factors may drive caste determination. To better understand the molecular basis of nutritional effects on caste determination, we used RNA-sequencing to investigate the gene expression changes in response to proteinaceous nourishment deprivation in Polistes metricus larvae. Results: We identified 285 nourishment-responsive transcripts, many of which are related to lipid metabolism and oxidation-reduction activity. Via comparisons to previously identified caste-related genes, we found that nourishment restriction only partially biased wasp gene expression patterns toward worker caste-like traits, which supports the notion that nourishment, in conjunction with social environment, is a determinant of developmental caste bias. In addition, we conducted cross-species comparisons of nourishment-responsive genes, and uncovered largely lineage-specific gene expression changes, suggesting few shared nourishment-responsive genes across taxa. Conclusion: Overall, the results from this study highlight the complex and multifactorial nature of environmental effects on the gene expression patterns underlying plastic phenotypes

At the brink of eusociality: transcriptomic correlates of worker behaviour in a small carpenter bee

Background: There is great interest in understanding the genomic underpinnings of social evolution, in particular, the evolution of eusociality (caste-containing societies with non-reproductives that care for siblings). Subsociality is a key precursor for the evolution of eusociality and characterized by prolonged parental care and parent-offspring interaction. Here, we provide the first transcriptomic data for the small carpenter bee, Ceratina calcarata. This species is of special interest because it is subsocial and in the same family as the highly eusocial honey bee, Apis mellifera. In addition, some C. calcarata females demonstrate alloparental care without reproduction, which provides a unique opportunity to study worker behaviour in a non-eusocial species. Results: We uncovered similar gene expression patterns related to maternal care and sibling care in different groups of females. This agrees with the maternal heterochrony hypothesis, specifically, that changes in timing of offspring care gene expression are related to worker behaviour in incipient insect societies. In addition, we also detected some similarity to caste-related gene expression patterns in highly eusocial honey bees, and uncovered large lifetime changes in gene expression that accompany shifts in reproductive and maternal care behaviour. Conclusions: For Ceratina calcarata, we found that transcript expression profiles were most similar between sibling care and maternal care females. The maternal care behaviour exhibited post-reproductively by Ceratina mothers is concordant in terms of transcript expression with the alloparental care exhibited by workers. In line with theoretical predictions, our data are consistent with the maternal heterochrony hypothesis for the evolutionary development of worker behaviour in subsocial bees

Genetic disease risks can be misestimated across global populations

Abstract Background Accurate assessment of health disparities requires unbiased knowledge of genetic risks in different populations. Unfortunately, most genome-wide association studies use genotyping arrays and European samples. Here, we integrate whole genome sequence data from global populations, results from thousands of genome-wide association studies (GWAS), and extensive computer simulations to identify how genetic disease risks can be misestimated. Results In contrast to null expectations, we find that risk allele frequencies at known disease loci are significantly different for African populations compared to other continents. Strikingly, ancestral risk alleles are found at 9.51% higher frequency in Africa, and derived risk alleles are found at 5.40% lower frequency in Africa. By simulating GWAS with different study populations, we find that non-African cohorts yield disease associations that have biased allele frequencies and that African cohorts yield disease associations that are relatively free of bias. We also find empirical evidence that genotyping arrays and SNP ascertainment bias contribute to continental differences in risk allele frequencies. Because of these causes, polygenic risk scores can be grossly misestimated for individuals of African descent. Importantly, continental differences in risk allele frequencies are only moderately reduced if GWAS use whole genome sequences and hundreds of thousands of cases and controls. Finally, comparisons between uncorrected and corrected genetic risk scores reveal the benefits of considering whether risk alleles are ancestral or derived. Conclusions Our results imply that caution must be taken when extrapolating GWAS results from one population to predict disease risks in another population