The major cell classes of the brain differ in their developmental processes, metabolism, signaling, and function. To better understand the functions and interactions of the cell types that comprise these classes, we acutely purified representative populations of neurons, astrocytes, oligodendrocyte precursor cells, newly formed oligodendrocytes, myelinating oligodendrocytes, microglia, endothelial cells, and pericytes from mouse cerebral cortex. We generated a transcriptome database for these eight cell types by RNA sequencing and used a sensitive algorithm to detect alternative splicing events in each cell type. Bioinformatic analyses identified thousands of new cell type-enriched genes and splicing isoforms that will provide novel markers for cell identification, tools for genetic manipulation, and insights into the biology of the brain. For example, our data provide clues as to how neurons and astrocytes differ in their ability to dynamically regulate glycolytic flux and lactate generation attributable to unique splicing of PKM2, the gene encoding the glycolytic enzyme pyruvate kinase. This dataset will provide a powerful new resource for understanding the development and function of the brain. To ensure the widespread distribution of these datasets, we have created a user-friendly website (http://web.stanford.edu/group/barres_lab/ brain_rnaseq.html) that provides a platform for analyzing and comparing transciption and alternative splicing profiles for various cell classes in the brain.

The functional complexity of the human transcriptome is not yet fully elucidated. We report a high-throughput sequence of the human transcriptome from a human embryonic kidney and a B cell line. We used shotgun sequencing of transcripts to generate randomly distributed reads. Of these, 50% mapped to unique genomic locations, of which 80% corresponded to known exons. We found that 66% of the polyadenylated transcriptome mapped to known genes and 34% to nonannotated genomic regions. On the basis of known transcripts, RNA-Seq can detect 25% more genes than can microarrays. A global survey of messenger RNA splicing events identified 94,241 splice junctions (4096 of which were previously unidentified) and showed that exon skipping is the most prevalent form of alternative splicing.

Microglia are resident immune cells of the CNS that are activated by infection, neuronal injury and inflammation. Here we utilize flow cytometry and deep RNA sequencing of acutely isolated spinal cord microglia to define their activation in vivo. Analysis of resting microglia identified 29 genes that distinguish microglia from other CNS cells and peripheral macrophages/monocytes. We then analyzed molecular changes in microglia during neurodegenerative disease activation using the SOD1G93A mouse model of ALS. We find that SOD1G93A microglia are not derived from infiltrating monocytes, and that both potentially neuroprotective and toxic factors are concurrently up-regulated, including Alzheimer’s disease genes. Mutant microglia differed from SOD1WT, LPS activated microglia, and M1/M2 macrophages, that define an ALS-specific phenotype. Concurrent mRNA/FACS analysis revealed post-transcriptional regulation of microglia surface receptors, and T cell-associated changes in the transcriptome. These results provide insights into microglia biology and establish a resource for future studies of neuroinflammation.

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world1. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.

X-linked intellectual disability (XLID) is a clinically and genetically heterogeneous disorder. During the past two decades in excess of 100 X-chromosome ID genes have been identified. Yet, a large number of families mapping to the X-chromosome remained unresolved suggesting that more XLID genes or loci are yet to be identified. Here, we have investigated 405 unresolved families with XLID. We employed massively parallel sequencing of all X-chromosome exons in the index males. The majority of these males were previously tested negative for copy number variations and for mutations in a subset of known XLID genes by Sanger sequencing. In total, 745 X-chromosomal genes were screened. After stringent filtering, a total of 1297 non-recurrent exonic variants remained for prioritization. Co-segregation analysis of potential clinically relevant changes revealed that 80 families (20%) carried pathogenic variants in established XLID genes. In 19 families, we detected likely causative protein truncating and missense variants in 7 novel and validated XLID genes (CLCN4, CNKSR2, FRMPD4, KLHL15, LAS1L, RLIM and USP27X) and potentially deleterious variants in 2 novel candidate XLID genes (CDK16 and TAF1). We show that the CLCN4 and CNKSR2 variants impair protein functions as indicated by electrophysiological studies and altered differentiation of cultured primary neurons from Clcn4−/− mice or after mRNA knock-down. The newly identified and candidate XLID proteins belong to pathways and networks with established roles in cognitive function and intellectual disability in particular. We suggest that systematic sequencing of all X-chromosomal genes in a cohort of patients with genetic evidence for X-chromosome locus involvement may resolve up to 58% of Fragile X-negative cases.

Human pluripotent stem cells are a promising source of differentiated cells for developmental studies, cell transplantation, disease modeling, and drug testing. However, their widespread use even for intensely studied cell types like spinal motor neurons is hindered by the long duration and low yields of existing protocols for in vitro differentiation and by the molecular heterogeneity of the populations generated. We report a combination of small molecules that within 3 weeks induce motor neurons at up to 50% abundance and with defined subtype identities of relevance to neurodegenerative disease. Despite their accelerated differentiation, motor neurons expressed combinations of HB9, ISL1 and column-specific markers that mirror those observed in vivo in human fetal spinal cord. They also exhibited spontaneous and induced activity, and projected axons towards muscles when grafted into developing chick spinal cord. Strikingly, this novel protocol preferentially generates motor neurons expressing markers of limb-innervating lateral motor column motor neurons (FOXP1+/LHX3−). Access to high-yield cultures of human limb-innervating motor neuron subtypes will facilitate in-depth study of motor neuron subtype-specific properties, disease modeling, and development of large-scale cell-based screening assays.

The transcription factor affinity prediction (TRAP) method calculates the affinity of transcription factors for DNA sequences on the basis of a biophysical model. This method has proven to be useful for several applications, including for determining the putative target genes of a given factor. This protocol covers two other applications: (i) determining which transcription factors have the highest affinity in a set of sequences (illustrated with chromatin immunoprecipitation-sequencing (ChIP-seq) peaks), and (ii) finding which factor is the most affected by a regulatory single-nucleotide polymorphism. The protocol describes how to use the TRAP web tools to address these questions, and it also presents a way to run TRAP on random control sequences to better estimate the significance of the results. All of the tools are fully available online and do not need any additional installation. The complete protocol takes about 45 min, but each individual tool runs in a few minutes.

Background: Leucine-rich repeats (LRRs) are highly versatile and evolvable protein-ligand interaction motifs found in a large number of proteins with diverse functions, including innate immunity and nervous system development. Here we catalogue all of the extracellular LRR (eLRR) proteins in worms, flies, mice and humans. We use convergent evidence from several transmembrane-prediction and motif-detection programs, including a customised algorithm, LRRscan, to identify eLRR proteins, and a hierarchical clustering method based on TribeMCL to establish their evolutionary relationships.