TL;DR: This report reports multiplexed error-robust FISH (MERFISH), a single-molecule imaging method that allows thousands of RNA species to be imaged in single cells by using combinatorial FISH labeling with encoding schemes capable of detecting and/or correcting errors.
Abstract: INTRODUCTION: The copy number and in- tracellular localization of RNA are important regulators of gene expression. Measurement of these properties at the transcriptome scale in single cells will give answers to many ques- tions related to gene expression and regulation. Single-molecule RNA imaging approaches, such as single-molecule fluorescence in situ hybrid- ization(smFISH), are powerful toolsforcount- ing and mappingRNA; however, the number of RNA species that can be simultaneously im- aged in individual cells has been limited. This makes it challenging to perform transcriptomic analysis of single cells in a spatially resolved manner. Here, we report multiplexed error- robust FISH (MERFISH), a single-molecule im- aging method that allows thousands of RNA species to be imaged in single cells by using combinatorial FISH labeling with encoding schemes capable of detecting and/or correct- ing errors. RATIONALE: We labeled each cellular RNA with a set of encoding probes, which contain targeting sequences that bind the RNA and readout sequences that bind fluorescently la- beled readout probes. Each RNA species is encodedwithaparticular combinationofread- out sequences. We used successive rounds of hybridization and imaging, each with a differ- ent readout probe, to identify the readout se- quences bound to each RNA and to decode the RNA. In principle, combinatorial labeling al- lows the number of detectable RNA species to
TL;DR: This study provides a path to high-throughput and low-cost direct RNA sequencing and achieving the ultimate goal of a comprehensive and bias-free understanding of transcriptomes.
Abstract: Our understanding of human biology and disease is ultimately dependent on a complete understanding of the genome and its functions. The recent application of microarray and sequencing technologies to transcriptomics has changed the simplistic view of transcriptomes to a more complicated view of genome-wide transcription where a large fraction of transcripts emanates from unannotated parts of genomes, and underlined our limited knowledge of the dynamic state of transcription. Most of this broad body of knowledge was obtained indirectly because current transcriptome analysis methods typically require RNA to be converted to complementary DNA (cDNA) before measurements, even though the cDNA synthesis step introduces multiple biases and artefacts that interfere with both the proper characterization and quantification of transcripts. Furthermore, cDNA synthesis is not particularly suitable for the analysis of short, degraded and/or small quantity RNA samples. Here we report direct single molecule RNA sequencing without prior conversion of RNA to cDNA. We applied this technology to sequence femtomole quantities of poly(A)(+) Saccharomyces cerevisiae RNA using a surface coated with poly(dT) oligonucleotides to capture the RNAs at their natural poly(A) tails and initiate sequencing by synthesis. We observed transcript 3' end heterogeneity and polyadenylated small nucleolar RNAs. This study provides a path to high-throughput and low-cost direct RNA sequencing and achieving the ultimate goal of a comprehensive and bias-free understanding of transcriptomes.
TL;DR: RNA and the cellular biochemistry revisited - a rationale transcription and the organization of eukaryotic gene sequences messenger RNA resilient ribonucleases RNA isolation strategies isolation of polyadenylated RNA electrohoresis.
Abstract: RNA and the cellular biochemistry revisited - a rationale transcription and the organization of eukaryotic gene sequences messenger RNA resilient ribonucleases RNA isolation strategies isolation of polyadenylated RNA electrohoresis - principles and parameters electrophoresis of RNA the Northern blot nucleic acid probe technology practical nucleic acid hybridization principles of detection quantititation of specific mRNAs by the S1 nuclease assay analysis of nuclear RNA transcription rate assays extraction of nuclear RNA for steady state analysis an RNA paradigm.
TL;DR: The synthesized recombinant RNA molecules that function both as hybridization probes and as templates for exponential amplification by Qβ replicase demonstrate the feasibility of employing exponentially replicatable RNAs in bioassays, where they serve the dual role of specific probe and amplifiable reporter.
Abstract: We have synthesized recombinant RNA molecules that function both as hybridization probes and as templates for exponential amplification by Qβ replicase. Each recombinant consists of a sequence specific for the protozoan parasite, Plasmodium falciparum, embedded within the sequence of MDV-1 RNA, which is a natural template for Qβ replicase. The probe sequence was inserted within a hairpin loop that occurs on the exterior of MDV-1 RNA. The recombinant RNAs hybridize specifically to complementary DNA, despite topological constraints on the probe domain, are replicated at the same rate as MDV-1 RNA, despite their additional length, and are able to serve as templates for the synthesis of a large number of RNA copies. A Qβ replicase reaction initiated with only 0.14 femtograms of recombinant RNA (1,000 molecules) can produce 129 nanograms of recombinant RNA product in 30 minutes. This represents a one-billion fold amplification. Our results demonstrate the feasibility of employing exponentially replicatable RNAs in bioassays, where they would serve the dual role of specific probe and amplifiable reporter.
TL;DR: Ribo-Zero-Seq provides equivalent rRNA removal efficiency, coverage uniformity, genome-based mapped reads, and consistently high quality quantification of transcripts, suggesting that RNA-Sequ can be used with FFPE-derived RNAs for gene expression profiling.
Abstract: RNA sequencing (RNA-Seq) is often used for transcriptome profiling as well as the identification of novel transcripts and alternative splicing events. Typically, RNA-Seq libraries are prepared from total RNA using poly(A) enrichment of the mRNA (mRNA-Seq) to remove ribosomal RNA (rRNA), however, this method fails to capture non-poly(A) transcripts or partially degraded mRNAs. Hence, a mRNA-Seq protocol will not be compatible for use with RNAs coming from Formalin-Fixed and Paraffin-Embedded (FFPE) samples. To address the desire to perform RNA-Seq on FFPE materials, we evaluated two different library preparation protocols that could be compatible for use with small RNA fragments. We obtained paired Fresh Frozen (FF) and FFPE RNAs from multiple tumors and subjected these to different gene expression profiling methods. We tested 11 human breast tumor samples using: (a) FF RNAs by microarray, mRNA-Seq, Ribo-Zero-Seq and DSN-Seq (Duplex-Specific Nuclease) and (b) FFPE RNAs by Ribo-Zero-Seq and DSN-Seq. We also performed these different RNA-Seq protocols using 10 TCGA tumors as a validation set. The data from paired RNA samples showed high concordance in transcript quantification across all protocols and between FF and FFPE RNAs. In both FF and FFPE, Ribo-Zero-Seq removed rRNA with comparable efficiency as mRNA-Seq, and it provided an equivalent or less biased coverage on gene 3′ ends. Compared to mRNA-Seq where 69% of bases were mapped to the transcriptome, DSN-Seq and Ribo-Zero-Seq contained significantly fewer reads mapping to the transcriptome (20-30%); in these RNA-Seq protocols, many if not most reads mapped to intronic regions. Approximately 14 million reads in mRNA-Seq and 45–65 million reads in Ribo-Zero-Seq or DSN-Seq were required to achieve the same gene detection levels as a standard Agilent DNA microarray. Our results demonstrate that compared to mRNA-Seq and microarrays, Ribo-Zero-Seq provides equivalent rRNA removal efficiency, coverage uniformity, genome-based mapped reads, and consistently high quality quantification of transcripts. Moreover, Ribo-Zero-Seq and DSN-Seq have consistent transcript quantification using FFPE RNAs, suggesting that RNA-Seq can be used with FFPE-derived RNAs for gene expression profiling.