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Geopolitical instability has prompted renewed discussions on the risks of DNA technology being weaponized in international conflict. With today’s changing security environment, the authors argue that risk assessments must be broadened from genetically targeted weapons to a series of new domains.
Marnie Blewitt highlights the visionary 1961 paper by Mary Lyon in which she proposed that dosage compensation in female mammals involves X-inactivation and recognized its implications for sex-specific phenotypes in X-linked disorders.
Luis Barreiro highlights a 2007 paper by Tishkoff et al. that identified genetic variants associated with lactose persistence in East African populations, representing one of the first examples of convergent evolution in humans.
This Review summarizes the genetic and non-genetic factors that impact the transferability of polygenic risk scores (PRSs) across populations, highlighting the technical challenges of existing PRS construction methods for diverse ancestries and the emerging resources for more widespread use of PRSs.
In this Review, Zhou et al. discuss our current understanding of the genetic control of key steps involved in human brain development and diseases, and they describe current and emerging approaches for investigating the underlying genetic architecture.
This Review explores the use of non-mammalian model organisms in the genetic diagnosis of rare diseases, focusing on the use of worms, flies and zebrafish. The strategies, genetic technologies and approaches to using these models are discussed, as well as how they can provide insight into more common disease mechanisms.
Applying deep learning to large-scale genomic data of species or populations is providing new opportunities to understand the evolutionary forces that drive genetic diversity. This Review introduces common deep learning architectures and provides comprehensive guidelines to implement deep learning models for population genetic inference. The authors also discuss current opportunities and challenges for deep learning in population genetics.
