Jia Qian Wu

An RNA-Sequencing Transcriptome and Splicing Database of Glia, Neurons, and Vascular Cells of the Cerebral Cortex

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.

Dynamic transcriptomes during neural differentiation of human embryonic stem cells revealed by short, long, and paired-end sequencing

To examine the fundamental mechanisms governing neural differentiation, we analyzed the transcriptome changes that occur during the differentiation of hESCs into the neural lineage. Undifferentiated hESCs as well as cells at three stages of early neural differentiation—N1 (early initiation), N2 (neural progenitor), and N3 (early glial-like)—were analyzed using a combination of single read, paired-end read, and long read RNA sequencing. The results revealed enormous complexity in gene transcription and splicing dynamics during neural cell differentiation. We found previously unannotated transcripts and spliced isoforms specific for each stage of differentiation. Interestingly, splicing isoform diversity is highest in undifferentiated hESCs and decreases upon differentiation, a phenomenon we call isoform specialization. During neural differentiation, we observed differential expression of many types of genes, including those involved in key signaling pathways, and a large number of extracellular receptors exhibit stage-specific regulation. These results provide a valuable resource for studying neural differentiation and reveal insights into the mechanisms underlying in vitro neural differentiation of hESCs, such as neural fate specification, neural progenitor cell identity maintenance, and the transition from a predominantly neuronal state into one with increased gliogenic potential.

Systematic analysis of transcribed loci in ENCODE regions using RACE sequencing reveals extensive transcription in the human genome

BackgroundRecent studies of the mammalian transcriptome have revealed a large number of additional transcribed regions and extraordinary complexity in transcript diversity. However, there is still much uncertainty regarding precisely what portion of the genome is transcribed, the exact structures of these novel transcripts, and the levels of the transcripts produced.ResultsWe have interrogated the transcribed loci in 420 selected ENCyclopedia Of DNA Elements (ENCODE) regions using rapid amplification of cDNA ends (RACE) sequencing. We analyzed annotated known gene regions, but primarily we focused on novel transcriptionally active regions (TARs), which were previously identified by high-density oligonucleotide tiling arrays and on random regions that were not believed to be transcribed. We found RACE sequencing to be very sensitive and were able to detect low levels of transcripts in specific cell types that were not detectable by microarrays. We also observed many instances of sense-antisense transcripts; further analysis suggests that many of the antisense transcripts (but not all) may be artifacts generated from the reverse transcription reaction. Our results show that the majority of the novel TARs analyzed (60%) are connected to other novel TARs or known exons. Of previously unannotated random regions, 17% were shown to produce overlapping transcripts. Furthermore, it is estimated that 9% of the novel transcripts encode proteins.ConclusionWe conclude that RACE sequencing is an efficient, sensitive, and highly accurate method for characterization of the transcriptome of specific cell/tissue types. Using this method, it appears that much of the genome is represented in polyA+ RNA. Moreover, a fraction of the novel RNAs can encode protein and are likely to be functional.

RNA polymerase II stalling: loading at the start prepares genes for a sprint

Stalling of RNA polymerase II near the promoter has recently been found to be much more common than previously thought. Genome-wide surveys of the phenomenon suggest that it is likely to be a rate-limiting control on gene activation that poises developmental and stimulus-responsive genes for prompt expression when inducing signals are received.

Systematic discovery of regulated and conserved alternative exons in the mammalian brain reveals NMD modulating chromatin regulators

Significance Alternative splicing (AS) plays an important role in the mammalian brain, but our atlas of AS events is incomplete. Here, we conducted comprehensive analysis of deep RNA-Seq data of mouse cortex to identify new AS events and evaluate their functionality. We expanded the number of annotated AS events more than 10-fold and demonstrated that, like many known events, thousands of newly discovered events are regulated, conserved, and likely functional. In particular, some can regulate gene expression levels through nonsense-mediated decay, a known mechanism for RNA binding protein autoregulation. Surprisingly, we discovered a number of chromatin regulators as novel targets of this mechanism, revealing a new regulatory link between epigenetics and AS that primarily emerged in the mammalian lineage. Alternative splicing (AS) dramatically expands the complexity of the mammalian brain transcriptome, but its atlas remains incomplete. Here we performed deep mRNA sequencing of mouse cortex to discover and characterize alternative exons with potential functional significance. Our analysis expands the list of AS events over 10-fold compared with previous annotations, demonstrating that 72% of multiexon genes express multiple splice variants in this single tissue. To evaluate functionality of the newly discovered AS events, we conducted comprehensive analyses on central nervous system (CNS) cell type-specific splicing, targets of tissue- or cell type-specific RNA binding proteins (RBPs), evolutionary selection pressure, and coupling of AS with nonsense-mediated decay (AS-NMD). We show that newly discovered events account for 23–42% of all cassette exons under tissue- or cell type-specific regulation. Furthermore, over 7,000 cassette exons are under evolutionary selection for regulated AS in mammals, 70% of which are new. Among these are 3,058 highly conserved cassette exons, including 1,014 NMD exons that may function directly to control gene expression levels. These NMD exons are particularly enriched in RBPs including splicing factors and interestingly also regulators for other steps of RNA metabolism. Unexpectedly, a second group of NMD exons reside in genes encoding chromatin regulators. Although the conservation of NMD exons in RBPs frequently extends into lower vertebrates, NMD exons in chromatin regulators are introduced later into the mammalian lineage, implying the emergence of a novel mechanism coupling AS and epigenetics. Our results highlight previously uncharacterized complexity and evolution in the mammalian brain transcriptome.

RNA-seq characterization of spinal cord injury transcriptome in acute/subacute phases: A resource for understanding the pathology at the systems level

Spinal cord injury (SCI) is a devastating neurological disease without effective treatment. To generate a comprehensive view of the mechanisms involved in SCI pathology, we applied RNA-Sequencing (RNA-Seq) technology to characterize the temporal changes in global gene expression after contusive SCI in mice. We sequenced tissue samples from acute and subacute phases (2 days and 7 days after injury) and systematically characterized the transcriptomes with the goal of identifying pathways and genes critical in SCI pathology. The top enriched functional categories include “inflammation response,” “neurological disease,” “cell death and survival” and “nervous system development.” The top enriched pathways include LXR/RXR Activation and Atherosclerosis Signaling, etc. Furthermore, we developed a systems-based analysis framework in order to identify key determinants in the global gene networks of the acute and sub-acute phases. Some candidate genes that we identified have been shown to play important roles in SCI, which demonstrates the validity of our approach. There are also many genes whose functions in SCI have not been well studied and can be further investigated by future experiments. We have also incorporated pharmacogenomic information into our analyses. Among the genes identified, the ones with existing drug information can be readily tested in SCI animal models. Therefore, in this study we have described an example of how global gene profiling can be translated to identifying genes of interest for functional tests in the future and generating new hypotheses. Additionally, the RNA-Seq enables splicing isoform identification and the estimation of expression levels, thus providing useful information for increasing the specificity of drug design and reducing potential side effect. In summary, these results provide a valuable reference data resource for a better understanding of the SCI process in the acute and sub-acute phases.

Comprehensive Identification of Long Non-coding RNAs in Purified Cell Types from the Brain Reveals Functional LncRNA in OPC Fate Determination

Long non-coding RNAs (lncRNAs) (> 200 bp) play crucial roles in transcriptional regulation during numerous biological processes. However, it is challenging to comprehensively identify lncRNAs, because they are often expressed at low levels and with more cell-type specificity than are protein-coding genes. In the present study, we performed ab initio transcriptome reconstruction using eight purified cell populations from mouse cortex and detected more than 5000 lncRNAs. Predicting the functions of lncRNAs using cell-type specific data revealed their potential functional roles in Central Nervous System (CNS) development. We performed motif searches in ENCODE DNase I digital footprint data and Mouse ENCODE promoters to infer transcription factor (TF) occupancy. By integrating TF binding and cell-type specific transcriptomic data, we constructed a novel framework that is useful for systematically identifying lncRNAs that are potentially essential for brain cell fate determination. Based on this integrative analysis, we identified lncRNAs that are regulated during Oligodendrocyte Precursor Cell (OPC) differentiation from Neural Stem Cells (NSCs) and that are likely to be involved in oligodendrogenesis. The top candidate, lnc-OPC, shows highly specific expression in OPCs and remarkable sequence conservation among placental mammals. Interestingly, lnc-OPC is significantly up-regulated in glial progenitors from experimental autoimmune encephalomyelitis (EAE) mouse models compared to wild-type mice. OLIG2-binding sites in the upstream regulatory region of lnc-OPC were identified by ChIP (chromatin immunoprecipitation)-Sequencing and validated by luciferase assays. Loss-of-function experiments confirmed that lnc-OPC plays a functional role in OPC genesis. Overall, our results substantiated the role of lncRNA in OPC fate determination and provided an unprecedented data source for future functional investigations in CNS cell types. We present our datasets and analysis results via the interactive genome browser at our laboratory website that is freely accessible to the research community. This is the first lncRNA expression database of collective populations of glia, vascular cells, and neurons. We anticipate that these studies will advance the knowledge of this major class of non-coding genes and their potential roles in neurological development and diseases.

Large-scale RT-PCR recovery of full-length cDNA clones

Pseudogenes, alternative transcripts, noncoding RNA, and polymorphisms each add extensive complexity to the mammalian transcriptome and confound estimation of the total number of genes. Despite advanced algorithms for gene prediction and several large-scale efforts to obtain cDNA clones for all human open reading frames (ORFs), no single collection is complete. To enhance this effort, we have developed a high-throughput pipeline for reverse transcription PCR (RT-PCR) gene recovery. Most importantly, novel molecular strategies for improving RT-PCR yield of transcripts that have been difficult to isolate by other means and computational strategies for clone sequence validation have been developed and optimized. This systematic gene recovery pipeline allows both rescue of predicted human and rat genes and provides insight into the complexity of the transcriptome through comparisons with existing data sets.

Building an RNA Sequencing Transcriptome of the Central Nervous System

The composition and function of the central nervous system (CNS) is extremely complex. In addition to hundreds of subtypes of neurons, other cell types, including glia (astrocytes, oligodendrocytes, and microglia) and vascular cells (endothelial cells and pericytes) also play important roles in CNS function. Such heterogeneity makes the study of gene transcription in CNS challenging. Transcriptomic studies, namely the analyses of the expression levels and structures of all genes, are essential for interpreting the functional elements and understanding the molecular constituents of the CNS. Microarray has been a predominant method for large-scale gene expression profiling in the past. However, RNA-sequencing (RNA-Seq) technology developed in recent years has many advantages over microarrays, and has enabled building more quantitative, accurate, and comprehensive transcriptomes of the CNS and other systems. The discovery of novel genes, diverse alternative splicing events, and noncoding RNAs has remarkably expanded the complexity of gene expression profiles and will help us to understand intricate neural circuits. Here, we discuss the procedures and advantages of RNA-Seq technology in mammalian CNS transcriptome construction, and review the approaches of sample collection as well as recent progress in building RNA-Seq-based transcriptomes from tissue samples and specific cell types.

Single-cell RNA-sequencing of the brain

Single-cell RNA-sequencing (scRNA-seq) is revolutionizing our understanding of the genomic, transcriptomic and epigenomic landscapes of cells within organs. The mammalian brain is composed of a complex network of millions to billions of diverse cells with either highly specialized functions or support functions. With scRNA-seq it is possible to comprehensively dissect the cellular heterogeneity of brain cells, and elucidate their specific functions and state. In this review, we describe the current experimental methods used for scRNA-seq. We also review bioinformatic tools and algorithms for data analyses and discuss critical challenges. Additionally, we summarized recent mouse brain scRNA-seq studies and systematically compared their main experimental approaches, computational tools implemented, and important findings. scRNA-seq has allowed researchers to identify diverse cell subpopulations within many brain regions, pinpointing gene signatures and novel cell markers, as well as addressing functional differences. Due to the complexity of the brain, a great deal of work remains to be accomplished. Defining specific brain cell types and functions is critical for understanding brain function as a whole in development, health, and diseases.