Sara B. Linker

Nuclear RNA-seq of single neurons reveals molecular signatures of activation

Single-cell sequencing methods have emerged as powerful tools for identification of heterogeneous cell types within defined brain regions. Application of single-cell techniques to study the transcriptome of activated neurons can offer insight into molecular dynamics associated with differential neuronal responses to a given experience. Through evaluation of common whole-cell and single-nuclei RNA-sequencing (snRNA-seq) methods, here we show that snRNA-seq faithfully recapitulates transcriptional patterns associated with experience-driven induction of activity, including immediate early genes (IEGs) such as Fos, Arc and Egr1. SnRNA-seq of mouse dentate granule cells reveals large-scale changes in the activated neuronal transcriptome after brief novel environment exposure, including induction of MAPK pathway genes. In addition, we observe a continuum of activation states, revealing a pseudotemporal pattern of activation from gene expression alone. In summary, snRNA-seq of activated neurons enables the examination of gene expression beyond IEGs, allowing for novel insights into neuronal activation patterns in vivo.

Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons

A protocol is described for sequencing the transcriptome of a cell nucleus. Nuclei are isolated from specimens and sorted by FACS, cDNA libraries are constructed and RNA-seq is performed, followed by data analysis. Some steps follow published methods (Smart-seq2 for cDNA synthesis and Nextera XT barcoded library preparation) and are not described in detail here. Previous single-cell approaches for RNA-seq from tissues include cell dissociation using protease treatment at 30 °C, which is known to alter the transcriptome. We isolate nuclei at 4 °C from tissue homogenates, which cause minimal damage. Nuclear transcriptomes can be obtained from postmortem human brain tissue stored at -80 °C, making brain archives accessible for RNA-seq from individual neurons. The method also allows investigation of biological features unique to nuclei, such as enrichment of certain transcripts and precursors of some noncoding RNAs. By following this procedure, it takes about 4 d to construct cDNA libraries that are ready for sequencing.

The role of adult hippocampal neurogenesis in brain health and disease

Adult neurogenesis in the dentate gyrus of the hippocampus is highly regulated by a number of environmental and cell-intrinsic factors to adapt to environmental changes. Accumulating evidence suggests that adult-born neurons may play distinct physiological roles in hippocampus-dependent functions, such as memory encoding and mood regulation. In addition, several brain diseases, such as neurological diseases and mood disorders, have deleterious effects on adult hippocampal neurogenesis, and some symptoms of those diseases can be partially explained by the dysregulation of adult hippocampal neurogenesis. Here we review a possible link between the physiological functions of adult-born neurons and their roles in pathological conditions.

Examining non-LTR retrotransposons in the context of the evolving primate brain

Researchers have long sought to understand the genetic basis of the cognitive differences between primates, with particular focus on the human brain. Although all mutational types have worked in concert with evolutionary forces to generate the current human brain, in this review we will explore the impact of mobile elements, specifically non-LTR retrotransposons. Non-LTR retrotransposons have contributed coding and regulatory sequences to the genome throughout evolution. During primate evolution there have been multiple waves of LINE retrotransposition as well as the birth of new mobile elements such as the SINEs Alu and SVA and we will explore what kinds of impacts these may have had on the evolving human brain.

Environment-driven somatic mosaicism in brain disorders

Editorial summaryThe identification of somatic mosaicism in the brain lends a new perspective to our understanding of the role of gene and environment interactions in psychiatric disease risk. Somatic mutations, such as retrotransposon insertions, that are precipitated by modern environmental factors may alter neuronal function and neurological traits, increasing the societal prevalence of mental disorders.

Prediction of response to drug therapy in psychiatric disorders

Personalized medicine has become increasingly relevant to many medical fields, promising more efficient drug therapies and earlier intervention. The development of personalized medicine is coupled with the identification of biomarkers and classification algorithms that help predict the responses of different patients to different drugs. In the last 10 years, the Food and Drug Administration (FDA) has approved several genetically pre-screened drugs labelled as pharmacogenomics in the fields of oncology, pulmonary medicine, gastroenterology, haematology, neurology, rheumatology and even psychiatry. Clinicians have long cautioned that what may appear to be similar patient-reported symptoms may actually arise from different biological causes. With growing populations being diagnosed with different psychiatric conditions, it is critical for scientists and clinicians to develop precision medication tailored to individual conditions. Genome-wide association studies have highlighted the complicated nature of psychiatric disorders such as schizophrenia, bipolar disorder, major depression and autism spectrum disorder. Following these studies, association studies are needed to look for genomic markers of responsiveness to available drugs of individual patients within the population of a specific disorder. In addition to GWAS, the advent of new technologies such as brain imaging, cell reprogramming, sequencing and gene editing has given us the opportunity to look for more biomarkers that characterize a therapeutic response to a drug and to use all these biomarkers for determining treatment options. In this review, we discuss studies that were performed to find biomarkers of responsiveness to different available drugs for four brain disorders: bipolar disorder, schizophrenia, major depression and autism spectrum disorder. We provide recommendations for using an integrated method that will use available techniques for a better prediction of the most suitable drug.

A novel environment-evoked transcriptional signature predicts reactivity in single dentate granule neurons

Activity-induced remodeling of neuronal circuits is critical for memory formation. This process relies in part on transcription, but neither the rate of activity nor baseline transcription is equal across neuronal cell types. In this study, we isolated mouse hippocampal populations with different activity levels and used single nucleus RNA-seq to compare their transcriptional responses to activation. One hour after novel environment exposure, sparsely active dentate granule (DG) neurons had a much stronger transcriptional response compared to more highly active CA1 pyramidal cells and vasoactive intestinal polypeptide (VIP) interneurons. Activity continued to impact transcription in DG neurons up to 5 h, with increased heterogeneity. By re-exposing the mice to the same environment, we identified a unique transcriptional signature that selects DG neurons for reactivation upon re-exposure to the same environment. These results link transcriptional heterogeneity to functional heterogeneity and identify a transcriptional correlate of memory encoding in individual DG neurons.Single nuclei RNA-seq has been used to characterize transcriptional signature of environment-related activity in cells of the dentate gyrus. Here the authors use this approach to show that whether a neuron will be reactivated in response to re-exposure to a previous environment can be predicted by its transcriptional signature.

Evaluating different DNA binding domains to modulate L1 ORF2p-driven site-specific retrotransposition events in human cells

DNA binding domains (DBDs) have been used with great success to impart targeting capabilities to a variety of proteins creating highly useful genomic tools. We evaluated the ability of five types of DBDs and strategies (AAV Rep proteins, Cre, TAL effectors, zinc finger proteins, and Cas9/gRNA system) to target the L1 ORF2 protein to drive retrotransposition of Alu inserts to specific sequences in the human genome. First, we find that the L1 ORF2 protein tolerates the addition of protein domains both at the amino- and carboxy-terminus. Although in some instances retrotransposition efficiencies slightly diminished, all fusion proteins containing an intact ORF2 were capable of driving retrotransposition. Second, the stability of individual ORF2 fusion proteins varies and difficult to predict. Third, DBDs that require the formation of multimers for target recognition are unlikely to modify targeting of ORF2p-driven insertions. Fourth, the more components needed to assemble into a complex to drive targeted retrotransposition, the less likely the strategy will increase targeted insertions. Fifth, abundance of target sequences present in the genome will likely dictate the effectiveness and efficiency of targeted insertions. Lastly, the cleavage capabilities of Cas9 (or a Cas9 nickase variant) are unable to substitute for the L1 ORF2 endonuclease domain functions, suggestive that the endonuclease domain has alternate functions needed for retrotransposition. From these studies, we conclude that the most critical component for the modification of the human L1 ORF2 protein to drive targeted insertions is the selection of the DBD due to the varying functional requirements and impacts on protein stability.

BrainImageR: spatiotemporal gene set analysis referencing the human brain

Motivation: Neuronal analyses such as transcriptomics, epigenetics and genome‐wide association studies must be assessed in the context of the human brain to generate biologically meaningful inferences. It is often difficult to access primary human brain tissue; therefore, approximations are made using alternative sources such as peripheral tissues or in vitro‐derived neurons. Gene sets from these studies are then assessed for their association with the post‐mortem human brain. However, most analyses of post‐mortem datasets are achieved by building new computational tools each time in‐house, which can cause discrepancies from study to study. The field is in need of a user‐friendly tool to examine spatiotemporal expression with respect to the postmortem brain. Such a tool will be of use in the molecular interrogation of neurological and psychiatric disorders, with direct advantages for the disease‐modeling and human genetics communities. Results: We have developed brainImageR, an R package that calculates both the spatial and temporal association of a dataset with post‐mortem human brain. BrainImageR identifies anatomical regions enriched for candidate gene set expression. It further predicts the developmental time point of the sample, a task that has become increasingly important in the field of in vitro neuronal modeling. These functionalities of brainImageR enable a quick and efficient characterization of a given dataset across normal human brain development. Availability and implementation: BrainImageR is released under the Creative Commons CC BY‐SA 4.0 license and can be accessed directly at brainimager.salk.edu or the R code can be downloaded through github at https://github.com/saralinker/brainImageR.

Corrigendum: Nuclear RNA-seq of single neurons reveals molecular signatures of activation

Nature Communications 7: Article number:1102210.1038/ncomms11022 (2016); Published April192016; Updated June142016