Heritable polygenic editing: the next frontier in genomic medicine?

Polygenic genome editing in human embryos and germ cells is predicted to become feasible in the next three decades. Several recent books and academic papers have outlined the ethical concerns raised by germline genome editing and the opportunities that it may present. To date, no attempts have been made to predict the consequences of altering specific variants associated with polygenic diseases.

Functional genomics of human skeletal development and the patterning of height heritability.

Underlying variation in height are regulatory changes to chondrocytes, cartilage cells comprising long-bone growth plates. Currently, we lack knowledge on epigenetic regulation and gene expression of chondrocytes sampled across the human skeleton, and therefore we cannot understand basic regulatory mechanisms controlling height biology. We first rectify this issue by generating extensive epigenetic and transcriptomic maps from chondrocytes sampled from different growth plates across developing human skeletons, discovering novel regulatory networks shaping human bone/joint development.

DINGO: increasing the power of locus discovery in maternal and fetal genome-wide association studies of perinatal traits.

Perinatal traits are influenced by fetal and maternal genomes. We investigate the performance of three strategies to detect loci in maternal and fetal genome-wide association studies (GWASs) of the same quantitative trait: (i) the traditional strategy of analysing maternal and fetal GWASs separately; (ii) a two-degree-of-freedom test which combines information from maternal and fetal GWASs; and (iii) a one-degree-of-freedom test where signals from maternal and fetal GWASs are meta-analysed together conditional on estimated sample overlap. We demonstrate that the optimal strategy depends on the extent of sample overlap, correlation between phenotypes, whether loci exhibit fetal and/or maternal effects, and whether these effects are directionally concordant.

The importance of family-based sampling for biobanks.

Biobanks aim to improve our understanding of health and disease by collecting and analysing diverse biological and phenotypic information in large samples. So far, biobanks have largely pursued a population-based sampling strategy, where the individual is the unit of sampling, and familial relatedness occurs sporadically and by chance. This strategy has been remarkably efficient and successful, leading to thousands of scientific discoveries across multiple research domains, and plans for the next wave of biobanks are underway.