Quantitative trait locus mapping identifies Col4a6 as a novel regulator of striatal dopamine level and axonal branching in mice

The features of dopaminergic neurons (DAns) of nigrostriatal circuitry are orchestrated by a multitude of yet unknown factors, many of them genetic. Genetic variation between individuals at baseline can lead to differential susceptibility to and severity of diseases. As decline of DAns, a characteristic of Parkinson’s disease, heralds a significant decrease in dopamine level, measuring dopamine can reflect the integrity of DAns. To identify novel genetic regulators of the integrity of DAns, we used the Collaborative Cross (CC) mouse strains as model system to search for quantitative trait loci (QTLs) related to dopamine levels in the dorsal striatum. The dopamine levels in dorsal striatum varied greatly in the eight CC founder strains, and the differences were inheritable in 32 derived CC strains. QTL mapping in these CC strains identified a QTL associated with dopamine level on chromosome X containing 393 genes. RNA-seq analysis of the ventral midbrain of two of the founder strains with large striatal dopamine difference (C57BL/6J and A/J) revealed 24 differentially expressed genes within the QTL. The protein-coding gene with the highest expression difference was Col4a6, which exhibited a 9-fold reduction in A/J compared to C57BL/6J, consistent with decreased dopamine levels in A/J. Publicly available single cell RNA-seq data from developing human midbrain suggests that Col4a6 is highly expressed in radial glia-like cells and neuronal progenitors, indicating possible involvement in neurogenesis. Interestingly, the lowered dopamine levels were accompanied by reduced striatal axonal branching of striatal DAns in A/J compared to C57BL/6J. Because Col4a6 is known to control axogenesis in non-mammal model organisms, we hypothesize that different dopamine levels in mouse dorsal striatum are due to differences in axogenesis induced by varying COL4A6 levels during neural development.

PKCγ promotes axonal remodeling in the cortico-spinal tract via GSK3β/β-catenin signaling after traumatic brain injury

Traumatic brain injury (TBI) is a common cause of death and disability. Enhancing the midline-crossing of the contralateral corticospinal tract (CST) to the denervated side of spinal cord facilitates functional recovery after TBI. Activation of the gamma isoform of PKC (PKCγ) in contralateral CST implicates its roles in promoting CST remodeling after TBI. In this study, we deployed loss and gain of function strategies in N2a cells and primary cortical neurons in vitro, and demonstrated that PKCγ is not only important but necessary for neuronal differentiation, neurite outgrowth and axonal branching but not for axonal extension. Mechanically, through the phosphorylation of GSK3β, PKCγ stabilizes the expression of cytosolic β-catenin and increase GAP43 expression, thus promoting axonal outgrowth. Further, rAAV2/9-mediated delivery of constitutive PKCγ in the corticospinal tract after unilateral TBI in vivo additionally showed that specifically delivery of active PKCγ mutant to cortical neuron promotes midline crossing of corticospinal fibers from the uninjured side to the denervated cervical spinal cord. This PKCγ-mediated injury response promoted sensorimotor functional recovery. In conclusion, PKCγ mediates stability of β-catenin through the phosphorylation of GSK3β to facilitate neuronal differentiation, neurite outgrowth and axonal branching, and PKCγ maybe a novel therapeutic target for physiological and functional recovery after TBI.

Recapitulation and reversal of schizophrenia-related phenotypes in Setd1a-deficient mice

SummarySETD1A, a histone methyltransferase, is a key schizophrenia susceptibility gene. Mutant mice carrying a heterozygous loss-of-function mutation of the orthologous gene exhibit alterations in axonal branching and cortical synaptic dynamics, accompanied by specific deficits in working memory that recapitulates SCZ-related alterations. We show that Setd1a targets mostly enhancers and reveal a striking overlap between Setd1a and Mef2 chromatin targets. Setd1a targets are highly expressed in pyramidal neurons and enriched for genes with postnatally-biased expression involved in synaptic structure and function. Notably, evolutionary conserved Setd1a binding sites and target genes are strongly associated with neuropsychiatric genetic risk burden. Reinstating Setd1a expression in adulthood rescues working memory deficits. We identify LSD1 as a major demethylase counteracting the effects of Setd1a methyl transferase activity and show that LSD1 antagonism in adult Setd1a-deficient mice results in a full rescue of the behavioral abnormalities and axonal branching deficits. Our findings advance our understanding of how SETD1A mutations predispose to SCZ and point to therapeutic interventions.

A Generative Growth Model for Thalamocortical Axonal Branching in Primary Visual Cortex

Axonal morphology displays large variability and complexity, yet the canonical regularities of the cortex suggest that such wiring is based on the repeated initiation of a small set of genetically encoded rules. Extracting underlying developmental principles can hence shed light on what genetically encoded instructions must be available during cortical development. Within a generative model, we investigate growth rules for axonal branching patterns in cat area 17, originating from the lateral geniculate nucleus of the thalamus. This target area of synaptic connections is characterized by extensive ramifications and a high bouton density, characteristics thought to preserve the spatial resolution of receptive fields and to enable connections for the ocular dominance columns. We compare individual and global statistics, such as a newly introduced asymmetry index and the global segment-length distribution, of generated and real branching patterns as the benchmark for growth rules. We show that the proposed model surpasses the statistical accuracy of the Galton-Watson model, which is the most commonly employed model for biological growth processes. In contrast to the Galton-Watson model, our model can recreate the log-normal segment-length distribution of the experimental dataset and is considerably more accurate in recreating individual axonal morphologies. To provide a biophysical interpretation for statistical quantifications of the axonal branching patterns, the generative model is ported into the physically accurate simulation framework of Cx3D. In this simulation environment we demonstrate how the proposed growth process can be formulated as an interactive process between genetic growth rules and chemical cues in the local environment.