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RNA-Seq of single cells has been limited by biases in transcript coverage and unknown technical variability. Ramsköld et al . describe a protocol to reproducibly recover full-length transcripts and use it to quantitatively analyze splice isoforms in single cells. Genome-wide transcriptome analyses are routinely used to monitor tissue-, disease- and cell type–specific gene expression, but it has been technically challenging to generate expression profiles from single cells. Here we describe a robust mRNA-Seq protocol (Smart-Seq) that is applicable down to single cell levels. Compared with existing methods, Smart-Seq has improved read coverage across transcripts, which enhances detailed analyses of alternative transcript isoforms and identification of single-nucleotide polymorphisms. We determined the sensitivity and quantitative accuracy of Smart-Seq for single-cell transcriptomics by evaluating it on total RNA dilution series. We found that although gene expression estimates from single cells have increased noise, hundreds of differentially expressed genes could be identified using few cells per cell type. Applying Smart-Seq to circulating tumor cells from melanomas, we identified distinct gene expression patterns, including candidate biomarkers for melanoma circulating tumor cells. Our protocol will be useful for addressing fundamental biological problems requiring genome-wide transcriptome profiling in rare cells.

Genomic imprinting results in preferential expression of the paternal or maternal allele of certain genes. We have performed a genome-wide characterization of imprinting in the mouse embryonic and adult brain. This approach uncovered parent-of-origin allelic effects of more than 1300 loci. We identified parental bias in the expression of individual genes and of specific transcript isoforms, with differences between brain regions. Many imprinted genes are expressed in neural systems associated with feeding and motivated behaviors, and parental biases preferentially target genetic pathways governing metabolism and cell adhesion. We observed a preferential maternal contribution to gene expression in the developing brain and a major paternal contribution in the adult brain. Thus, parental expression bias emerges as a major mode of epigenetic regulation in the brain.

Through alternative processing of pre-messenger RNAs, individual mammalian genes often produce multiple mRNA and protein isoforms that may have related, distinct or even opposing functions. Here we report an in-depth analysis of 15 diverse human tissue and cell line transcriptomes on the basis of deep sequencing of complementary DNA fragments, yielding a digital inventory of gene and mRNA isoform expression. Analyses in which sequence reads are mapped to exon–exon junctions indicated that 92–94% of human genes undergo alternative splicing, ∼86% with a minor isoform frequency of 15% or more. Differences in isoform-specific read densities indicated that most alternative splicing and alternative cleavage and polyadenylation events vary between tissues, whereas variation between individuals was approximately twofold to threefold less common. Extreme or ‘switch-like’ regulation of splicing between tissues was associated with increased sequence conservation in regulatory regions and with generation of full-length open reading frames. Patterns of alternative splicing and alternative cleavage and polyadenylation were strongly correlated across tissues, suggesting coordinated regulation of these processes, and sequence conservation of a subset of known regulatory motifs in both alternative introns and 3′ untranslated regions suggested common involvement of specific factors in tissue-level regulation of both splicing and polyadenylation. Gene expression: one gene, many proteins When the human genome was decoded, the lower than expected number of genes prompted renewed interest in alternative splicing — a mechanism by which more than one protein is made from a single gene. Licatalosi et al . have developed an unbiased, genome-wide method to characterize RNA–protein binding interactions in living tissue, and demonstrate its potential by applying it to the mammalian brain. They characterize the binding sites of the neuronal alternative splicing regulator, Nova, and make the unexpected discovery that it may have an additional function in regulating alternative polyadenylation. In a separate study, Wang et al . used deep sequencing of mRNAs to study alternative splicing in various human tissues and cancers. By mapping sequence reads to splice junctions, they show that alternative splicing is essentially universal in human multi-exon genes. They also show that alternative splicing is mechanistically linked to mRNA polyadenylation. This paper reports on an intensive bioinformatic analysis of human alternative splicing in various tissues and cancers. The analysis offers insight into tissue specificity, coordinated regulation and sequence conservation of alternative splicing. Evidence is also obtained that alternative splicing is mechanistically linked to a modification of mRNAs known as polyadenylation.

12 microRNA expression profiling platforms are compared for their reproducibility, sensitivity, accuracy and specificity, and the strengths and weaknesses of each platform are discussed. MicroRNAs are important negative regulators of protein-coding gene expression and have been studied intensively over the past years. Several measurement platforms have been developed to determine relative miRNA abundance in biological samples using different technologies such as small RNA sequencing, reverse transcription–quantitative PCR (RT-qPCR) and (microarray) hybridization. In this study, we systematically compared 12 commercially available platforms for analysis of microRNA expression. We measured an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples and synthetic spikes from microRNA family members with varying homology. We developed robust quality metrics to objectively assess platform performance in terms of reproducibility, sensitivity, accuracy, specificity and concordance of differential expression. The results indicate that each method has its strengths and weaknesses, which help to guide informed selection of a quantitative microRNA gene expression platform for particular study goals.

New regulatory roles continue to emerge for both natural and engineered noncoding RNAs, many of which have specific secondary and tertiary structures essential to their function. Thus there is a growing need to develop technologies that enable rapid characterization of structural features within complex RNA populations. We have developed a high-throughput technique, SHAPE-Seq, that can simultaneously measure quantitative, single nucleotide-resolution secondary and tertiary structural information for hundreds of RNA molecules of arbitrary sequence. SHAPE-Seq combines selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemistry with multiplexed paired-end deep sequencing of primer extension products. This generates millions of sequencing reads, which are then analyzed using a fully automated data analysis pipeline, based on a rigorous maximum likelihood model of the SHAPE-Seq experiment. We demonstrate the ability of SHAPE-Seq to accurately infer secondary and tertiary structural information, detect subtle conformational changes due to single nucleotide point mutations, and simultaneously measure the structures of a complex pool of different RNA molecules. SHAPE-Seq thus represents a powerful step toward making the study of RNA secondary and tertiary structures high throughput and accessible to a wide array of scientific pursuits, from fundamental biological investigations to engineering RNA for synthetic biological systems.

The paucity of enzymes that efficiently deconstruct plant polysaccharides represents a major bottleneck for industrial-scale conversion of cellulosic biomass into biofuels. Cow rumen microbes specialize in degradation of cellulosic plant material, but most members of this complex community resist cultivation. To characterize biomass-degrading genes and genomes, we sequenced and analyzed 268 gigabases of metagenomic DNA from microbes adherent to plant fiber incubated in cow rumen. From these data, we identified 27,755 putative carbohydrate-active genes and expressed 90 candidate proteins, of which 57% were enzymatically active against cellulosic substrates. We also assembled 15 uncultured microbial genomes, which were validated by complementary methods including single-cell genome sequencing. These data sets provide a substantially expanded catalog of genes and genomes participating in the deconstruction of cellulosic biomass.

We have developed a novel approach called parallel analysis of RNA ends (PARE) for high-throughput identification of microRNA (miRNA) targets and diverse applications for the study of the RNA degradome. The method described here comprises a modified 5′-rapid amplification of cDNA ends, deep sequencing of 3′ cleavage products of mRNA and bioinformatic analysis. Following RNA extraction and isolation of polyadenylated RNA, a 5′-RNA adapter that includes an Mme I recognition site is ligated to 5′-monophosphorylated products, which contain mRNA fragments generated through miRNA-induced cleavage. The ligated products are reverse-transcribed, slightly amplified and cleaved with Mme I. The 5′ equally-sized fragments are gel-selected, ligated to a 3′ double-stranded DNA adapter and PCR-amplified. Following gel purification, the products are subjected to deep sequencing. The data are then matched to cDNAs and analyzed through bioinformatics filters. We describe the high-throughput protocol in detail and indicate alternative uses for PARE. The procedure presented here can be accomplished in 6–7 d.

We describe a new algorithm, meraculous, for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast Pichia stipitis. More than 95% of the genome is recovered, with no errors; half the assembled sequence is in contigs longer than 101 kilobases and in scaffolds longer than 269 kilobases. Incorporating fosmid ends recovers entire chromosomes. Meraculous relies on an efficient and conservative traversal of the subgraph of the k-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. A novel memory-efficient hashing scheme is introduced. The resulting contigs are ordered and oriented using paired reads separated by ∼280 bp or ∼3.2 kbp, and many gaps between contigs can be closed using paired-end placements. Practical issues with the dataset are described, and prospects for assembling larger genomes are discussed.

The targets of a microRNA (miRNA) are usually identified by computational analysis of sequences complementary to the miRNA. Working with inflorescence tissue of Arabidopsis , German et al . devise an experimental approach in which the products of miRNA-mediated cleavage are sequenced and used to identify miRNA–target RNA pairs. MicroRNAs (miRNAs) are important regulatory molecules in most eukaryotes and identification of their target mRNAs is essential for their functional analysis. Whereas conventional methods rely on computational prediction and subsequent experimental validation of target RNAs, we directly sequenced >28,000,000 signatures from the 5′ ends of polyadenylated products of miRNA-mediated mRNA decay, isolated from inflorescence tissue of Arabidopsis thaliana , to discover novel miRNA–target RNA pairs. Within the set of ∼27,000 transcripts included in the 8,000,000 nonredundant signatures, several previously predicted but nonvalidated targets of miRNAs were found. Like validated targets, most showed a single abundant signature at the miRNA cleavage site, particularly in libraries from a mutant deficient in the 5′-to-3′ exonuclease AtXRN4. Although miRNAs in Arabidopsis have been extensively investigated, working in reverse from the cleaved targets resulted in the identification and validation of novel miRNAs. This versatile approach will affect the study of other aspects of RNA processing beyond miRNA–target RNA pairs.

Somatic mutations during stem cell division are responsible for several cancers. In principle, a similar process could occur during the intense cell proliferation accompanying human brain development, leading to the accumulation of regionally distributed foci of mutations. Using dual platform >5000-fold depth sequencing of 102 genes in 173 adult human brain samples, we detect and validate somatic mutations in 27 of 54 brains. Using a mathematical model of neurodevelopment and approximate Bayesian inference, we predict that macroscopic islands of pathologically mutated neurons are likely to be common in the general population. The detected mutation spectrum also includes DNMT3A and TET2 which are likely to have originated from blood cell lineages. Together, these findings establish developmental mutagenesis as a potential mechanism for neurodegenerative disorders, and provide a novel mechanism for the regional onset and focal pathology in sporadic cases. Similar to cancers, somatic mutations might lead to neurodegenerative diseases. Here, the authors perform ultra-deep sequencing of 102 genes in 173 adult human brains, detect somatic mutations in 54 brains, and develop a mathematical model to estimate the frequency of mutated foci in human brains.