Impaired GABA–mediated neurotransmission has been implicated in many neurologic diseases including epilepsy, intellectual disability, and psychiatric disorders. Here we report that inhibitory neuron transplantation into the hippocampus of adult mice with confirmed epilepsy at the time of grafting dramatically reduced the occurrence of electrographic seizures and restored behavioral deficits in spatial learning, hyperactivity, and the aggressive response to handling. In the recipient brain, GABA progenitors migrated up to 1500 μm from the injection site, expressed genes and proteins characteristic for interneurons, differentiated into functional inhibitory neurons, and received excitatory synaptic input. In contrast to hippocampus, cell grafts into basolateral amygdala rescued the hyperactivity deficit but did not alter seizure activity or other abnormal behaviors. Our results highlight a critical role for interneurons in epilepsy and suggest that interneuron cell transplantation is a powerful approach to halt seizures and rescue accompanying deficits in severely epileptic mice.

Resolving lineage relationships between cells in an organism is a fundamental interest of developmental biology. Furthermore, investigating lineage can drive understanding of pathological states, including cancer, as well as understanding of developmental pathways that are amenable to manipulation by directed differentiation. Although lineage tracking through the injection of retroviral libraries has long been the state of the art, a recent explosion of methodological advances in exogenous labelling and single-cell sequencing have enabled lineage tracking at larger scales, in more detail, and in a wider range of species than was previously considered possible. In this Review, we discuss these techniques for cell lineage tracking, with attention both to those that trace lineage forwards from experimental labelling, and those that trace backwards across the life history of an organism.

The human cerebral cortex is distinguished by its large size and abundant gyrification, or folding, yet the evolutionary mechanisms driving cortical size and structure are unknown. While genes essential for cortical developmental expansion have been identified from the genetics of human primary microcephaly (“small head”, associated with reduced brain size and intellectual disability)1, studies of these genes in mice, whose smooth cortex is one thousand times smaller than that of humans, have provided limited insight. Mutations of abnormal spindle-like microcephaly-associated (ASPM), the most common recessive microcephaly gene, reduce cortical volume by ≥50% in humans2–4, but have little effect in mice5–9, likely reflecting evolutionarily divergent functions of ASPM10,11. We used genome editing to create a germline knockout (KO) of Aspm in the ferret (Mustela putorius furo), a species with a larger, gyrified cortex and greater neural progenitor cell (NPC) diversity12–14 than mice, and closer Aspm protein sequence homology to human. Aspm KO ferrets exhibit severe microcephaly (25–40% decreases in brain weight), reflecting reduced cortical surface area without significant change in cortical thickness, as in human patients3,4, suggesting loss of “cortical units”. The mutant ferret fetal cortex displays a massive premature displacement of ventricular radial glial cells (VRG) to the outer subventricular zone (OSVZ), where many resemble outer radial glia (ORG), an NPC subtype essentially absent in mice and implicated in cerebral cortical expansion in primates12–16. These data suggest an evolutionary mechanism whereby Aspm regulates cortical expansion by controlling the affinity of VRG for the ventricular surface, thus modulating the ratio of VRG, the most undifferentiated cell type, to ORG, a more differentiated progenitor.

Summary Background Rhythmic behaviors are driven by endogenous biological clocks in pacemakers, which must reliably transmit timing information to target tissues that execute rhythmic outputs. During the defecation motor program in C. elegans, calcium oscillations in the pacemaker (intestine), which occur about every 50 seconds, trigger rhythmic enteric muscle contractions through downstream GABAergic neurons that innervate enteric muscles. However, the identity of the timing signal released by the pacemaker and the mechanism underlying the delivery of timing information to the GABAergic neurons are unknown. Results Here we show that a neuropeptide-like protein (NLP-40) released by the pacemaker triggers a single rapid calcium transient in the GABAergic neurons during each defecation cycle. We find that mutants lacking nlp-40 have normal pacemaker function, but lack enteric muscle contractions. NLP-40 undergoes calcium-dependent release that is mediated by the calcium sensor, SNT-2/synaptotagmin. We identify AEX-2, the G protein-coupled receptor on the GABAergic neurons, as the receptor of NLP-40. Functional calcium imaging reveals that NLP-40 and AEX-2/GPCR are both necessary for rhythmic activation of these neurons. Furthermore, acute application of synthetic NLP-40-derived peptide depolarizes the GABAergic neurons in vivo. Conclusions Our results show that NLP-40 carries the timing information from the pacemaker via calcium-dependent release and delivers it to the GABAergic neurons by instructing their activation. Thus, we propose that rhythmic release of neuropeptides can deliver temporal information from pacemakers to downstream neurons to execute rhythmic behaviors.

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We characterize the landscape of somatic mutations—mutations occurring after fertilization—in the human brain using ultra-deep (~250X) whole-genome sequencing of prefrontal cortex from 59 autism spectrum disorder (ASD) cases and 15 controls. We observe a mean of 26 somatic single nucleotide variants (sSNVs) per brain present in ≥4% of cells, with enrichment of mutations in coding and putative regulatory regions. Our analysis reveals that the first cell division after fertilization produces ~3.4 mutations, followed by 2–3 mutations in subsequent generations. This suggests that a typical individual possesses ~80 sSNVs present in ≥2% of cells—comparable to the number of de novo germline mutations per generation—with about half of individuals having at least one potentially function-altering somatic mutation somewhere in the cortex. ASD brains show an excess of somatic mutations in neural enhancer sequences compared to controls, suggesting that mosaic enhancer mutations may contribute to ASD risk.

Although somatic mutations have well-established roles in cancer and certain focal epilepsies, the extent to which mutational mosaicism shapes the developing human brain is poorly understood. Here we characterize the landscape of somatic mutations in the human brain using ultra-deep (~250×) whole-genome sequencing of brains from 59 autism spectrum disorder (ASD) cases and 15 controls. We observe a mean of 26 (±10, range 10-60) somatic single nucleotide variants (sSNVs) per brain present in ≥ 4% of cells, with enrichment of mutations in coding and putative regulatory regions. Our analysis reveals that the first cell division after fertilization produces ~3.4 mutations, followed by 2-3 mutations in subsequent generations. This rate suggests that a typical individual possesses ~80 sSNVs present in ≥ 2% of cells-comparable to the number of de novo germline mutations per generation-with about half of individuals having at least one potentially function-altering somatic mutation somewhere in the cortex.Although limited by sample size, ASD brains show an excess of somatic mutations in neural enhancer sequences compared to controls, suggesting that mosaic enhancer mutations may contribute to ASD risk.

In the version of this article initially published, the second sentence of the Methods section "Comparison of mutational signatures between earlier and later mutations" should have read, "To avoid over-fitting, we extracted the two most common clock-like signatures (signature S1 and signature S5), as well as a reactive oxygen species signature (signature S18) from the PCAWG signatures, and deconstructed mutational signatures for the mosaic mutations using the R package deconstructSigs 67. " The error has been corrected in the PDF and HTML versions of this article.