Highlights d Single-cell genomic analysis of hippocampal neurons reveals a somatic L1 insertion d The donor L1 is slightly 5ʹ truncated and lacks a conserved YY1 binding site d Young L1s with truncated or mutated YY1 binding sites are globally hypomethylated d L1 is able to mobilize in the brain because of locus-specific exceptions to repression

Summary Osteoclasts are large multinucleated bone-resorbing cells formed by the fusion of monocyte/macrophage-derived precursors that are thought to undergo apoptosis once resorption is complete. Here, by intravital imaging, we reveal that RANKL-stimulated osteoclasts have an alternative cell fate in which they fission into daughter cells called osteomorphs. Inhibiting RANKL blocked this cellular recycling and resulted in osteomorph accumulation. Single-cell RNA sequencing showed that osteomorphs are transcriptionally distinct from osteoclasts and macrophages and express a number of non-canonical osteoclast genes that are associated with structural and functional bone phenotypes when deleted in mice. Furthermore, genetic variation in human orthologs of osteomorph genes causes monogenic skeletal disorders and associates with bone mineral density, a polygenetic skeletal trait. Thus, osteoclasts recycle via osteomorphs, a cell type involved in the regulation of bone resorption that may be targeted for the treatment of skeletal diseases.

BackgroundGenome-wide association studies (GWAS) are an important method for mapping genetic variation underlying complex traits and diseases. Tools to visualize, annotate and analyse results from these studies can be used to generate hypotheses about the molecular mechanisms underlying the associations.FindingsThe Complex-Traits Genetics Virtual Lab (CTG-VL) integrates over a thousand publicly-available GWAS summary statistics, a suite of analysis tools, visualization functions and diverse data sets for genomic annotations. CTG-VL also makes available results from gene, pathway and tissue-based analyses from over 1,500 complex-traits allowing to assess pleiotropy not only at the genetic variant level but also at the gene, pathway and tissue levels. In this manuscript, we showcase the platform by analysing GWAS summary statistics of mood swings derived from UK Biobank. Using analysis tools in CTG-VL we highlight hippocampus as a potential tissue involved in mood swings, and that pathways including neuron apoptotic process may underlie the genetic associations. Further, we report a negative genetic correlation with educational attainment rG = −0.41 ± 0.018 and a potential causal effect of BMI on mood swings OR = 1.01 (95% CI = 1.00–1.02). Using CTG-VL’s database, we show that pathways and tissues associated with mood swings are also associated with neurological traits including reaction time and neuroticism, as well as traits such age at menopause and age at first live birth.ConclusionsCTG-VL is a platform with the most complete set of tools to carry out post-GWAS analyses. The CTG-VL is freely available at https://genoma.io as an online web application.