Adherence to the Eatwell Guide and population and planetary health: A Rank Prize Forum report.

This report summarises a Forum conducted in June 2023 to explore the current state of the knowledge around the Eatwell Guide, which is the UK government's healthy eating tool, in relation to population and planetary health. The 1.5-day Forum highlighted the limited, albeit promising evidence linking higher adherence to the Eatwell Guide with favourable health outcomes, including reduced overall mortality risk, lower abdominal obesity in post-menopausal women and improved cardiometabolic health markers.

Deep convolutional and conditional neural networks for large-scale genomic data generation.

Applications of generative models for genomic data have gained significant momentum in the past few years, with scopes ranging from data characterization to generation of genomic segments and functional sequences. In our previous study, we demonstrated that generative adversarial networks (GANs) and restricted Boltzmann machines (RBMs) can be used to create novel high-quality artificial genomes (AGs) which can preserve the complex characteristics of real genomes such as population structure, linkage disequilibrium and selection signals. However, a major drawback of these models is scalability, since the large feature space of genome-wide data increases computational complexity vastly.

The gene in Denisovans, Neanderthals, and Modern Humans: An Evolutionary History of Recurrent Introgression and Natural Selection.

We study the gene MUC19, for which modern humans carry a Denisovan-like haplotype. MUC19 is a mucin, a glycoprotein that forms gels with various biological functions. We find the diagnostic variants for the Denisovan-like MUC19 haplotype at high frequencies in admixed Latin American individuals among global populations, and at highest frequency in 23 ancient Indigenous American individuals, all predating population admixture with Europeans and Africans.

Simulation-based Benchmarking of Ancient Haplotype Inference for Detecting Population Structure.

Paleogenomic data has informed us about the movements, growth, and relationships of ancient populations. It has also given us context for medically relevant adaptations that appear in present-day humans due to introgression from other hominids, and it continues to help us characterize the evolutionary history of humans. However, ancient DNA (aDNA) presents several practical challenges as various factors such as deamination, high fragmentation, environmental contamination of aDNA, and low amounts of recoverable endogenous DNA, make aDNA recovery and analysis more difficult than modern DNA.