The human brain has enormously complex cellular diversity and connectivities fundamental to our neural functions, yet difficulties in interrogating individual neurons has impeded understanding of the underlying transcriptional landscape. We developed a scalable approach to sequence and quantify RNA molecules in isolated neuronal nuclei from post-mortem brain, generating 3,227 sets of single neuron data from six distinct regions of the cerebral cortex. Using an iterative clustering and classification approach, we identified 16 neuronal subtypes that were further annotated on the basis of known markers and cortical cytoarchitecture. These data demonstrate a robust and scalable method for identifying and categorizing single nuclear transcriptomes, revealing shared genes sufficient to distinguish novel and orthologous neuronal subtypes as well as regional identity within the human brain.

polymerase, ATP sulfurylase, firefly luw ciferase, and a nucleotide-degrading enzyme (such as apyrase). Repeated cycles of deoxynucleotide addition are performed. A A Sequencing Method Based On deoxynucleotide d l incorporated into the growing DNA strand if it is com-Real-Time Pyrophosphate plementary strand. The synthesis to the base of DNA in the is accompa-template ---Mostafa Ronaghi, Mathias UhlCn, and Pi1 NyrCn* nied by releak of PPi equal in molarit; to that of the incorporated deoxynucleotide.

and PCT/EP2016/057355 applied for by Spatial Transcriptomics AB (10x Genomics) covering the described technology. M.R. is employed by Illumina Inc. A.R. is a founder and equity holder of Celsius Therapeutics and an SAB member of Syros Pharmaceuticals and Thermo Fisher Scientific.Reporting summary: Further information on research design is available in the Life Sciences Reporting Summary linked to this article. Data availability:The raw mouse data have been deposited to NCBI's GEO archive GSE130682. Raw files for the breast cancer sample are available through an MTA with Åke Borg

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BackgroundThe investigation of the interconnections between the molecular and genetic events that govern biological systems is essential if we are to understand the development of disease and design effective novel treatments. Microarray and next-generation sequencing technologies have the potential to provide this information. However, taking full advantage of these approaches requires that biological connections be made across large quantities of highly heterogeneous genomic datasets. Leveraging the increasingly huge quantities of genomic data in the public domain is fast becoming one of the key challenges in the research community today.Methodology/ResultsWe have developed a novel data mining framework that enables researchers to use this growing collection of public high-throughput data to investigate any set of genes or proteins. The connectivity between molecular states across thousands of heterogeneous datasets from microarrays and other genomic platforms is determined through a combination of rank-based enrichment statistics, meta-analyses, and biomedical ontologies. We address data quality concerns through dataset replication and meta-analysis and ensure that the majority of the findings are derived using multiple lines of evidence. As an example of our strategy and the utility of this framework, we apply our data mining approach to explore the biology of brown fat within the context of the thousands of publicly available gene expression datasets.ConclusionsOur work presents a practical strategy for organizing, mining, and correlating global collections of large-scale genomic data to explore normal and disease biology. Using a hypothesis-free approach, we demonstrate how a data-driven analysis across very large collections of genomic data can reveal novel discoveries and evidence to support existing hypothesis.

DNA sequencing is one of the most important platforms for the study of biological systems today. Sequence determination is most commonly performed using dideoxy chain termination technology. Recently, pyrosequencing has emerged as a new sequencing methodology. This technique is a widely applicable, alternative technology for the detailed characterization of nucleic acids. Pyrosequencing has the potential advantages of accuracy, flexibility, parallel processing, and can be easily automated. Furthermore, the technique dispenses with the need for labeled primers, labeled nucleotides, and gel-electrophoresis. This article considers key features regarding different aspects of pyrosequencing technology, including the general principles, enzyme properties, sequencing modes, instrumentation, and potential applications.

The detection of mutant spectra within a population of microorganisms is critical for the management of drug-resistant infections. We performed ultra-deep pyrosequencing to detect minor sequence variants in HIV-1 protease and reverse transcriptase (RT) genes from clinical plasma samples. We estimated empirical error rates from four HIV-1 plasmid clones and used them to develop a statistical approach to distinguish authentic minor variants from sequencing errors in eight clinical samples. Ultra-deep pyrosequencing detected an average of 58 variants per sample compared with an average of eight variants per sample detected by conventional direct-PCR dideoxynucleotide sequencing. In the clinical sample with the largest number of minor sequence variants, all 60 variants present in Ն3% of genomes and 20 of 35 variants present in <3% of genomes were confirmed by limiting dilution sequencing. With appropriate analysis, ultra-deep pyrosequencing is a promising method for characterizing genetic diversity and detecting minor yet clinically relevant variants in biological samples with complex genetic populations.[Supplemental material is available online at www.genome.org. The raw data from this study are available online at http://dbpartners.stanford.edu/454/pub.] Dideoxynucleotide (Sanger) sequencing of non-clonal PCR products (direct PCR sequencing) of plasma viral cDNA is widely used to detect more than 50 drug-resistance mutations in the molecular targets of HIV-1 therapy-reverse transcriptase (RT) and protease-in clinical settings (US Department of Health and Human Services Panel on Clinical Practices for Treatment of HIV Infection 2006). A major limitation of direct PCR sequencing, however, is its inability to detect low proportions of drug-resistant variants in the heterogeneous virus population existing in a patient's plasma sample (Palmer et al. 2005). Several studies have shown that minor drug-resistant variants that are not detected by population-based sequencing are clinically relevant in that they are often responsible for the virological failure of a new antiretroviral treatment regimen (Jourdain et al. 2004;Kapoor et al. 2004;Lecossier et al. 2005;Palmer et al. 2006b). Multiple approaches have been developed to detect minor HIV-1 variants in research settings; however, no single approach has proved useful for clinical settings.The 454 Life Sciences GS20 sequencing platform allows massively parallel picoliter-scale amplification and pyrosequencing of individual DNA molecules (Margulies et al. 2005). Simons and colleagues described two cases in which ultra-deep pyrosequencing detected minority variant drug-resistance mutations in a previously treated patient in whom mutations were no longer detectable by standard direct PCR sequencing (Simons et al. 2005). Tsibris and colleagues demonstrated that ultra-deep pyrosequencing could accurately quantify a mixture of three HIV-1 envelope variants pooled in defined proportions of 89%, 10%, and 1% (Tsibris et al. 2006). Here, we systematically investigate the potential...

We report on the development of molecular inversion probe (MIP) genotyping, an efficient technology for large-scale single nucleotide polymorphism (SNP) analysis. This technique uses MIPs to produce inverted sequences, which undergo a unimolecular rearrangement and are then amplified by PCR using common primers and analyzed using universal sequence tag DNA microarrays, resulting in highly specific genotyping. With this technology, multiplex analysis of more than 1,000 probes in a single tube can be done using standard laboratory equipment. Genotypes are generated with a high call rate (95%) and high accuracy (>99%) as determined by independent sequencing.