CRISPR/Cas9-targeted removal of unwanted sequences from small-RNA sequencing libraries

Untacking small RNA profiling and RNA fragment footprinting: Approaches and challenges in library construction

Small RNAs (sRNAs) with sizes ranging from 15 to 50 nucleotides (nt) are critical regulators of gene expression control. Prior studies have shown that sRNAs are involved in a broad range of biological processes, such as organ development, tumorigenesis, and epigenomic regulation; however, emerging evidence unveils a hidden layer of diversity and complexity of endogenously encoded sRNAs profile in eukaryotic organisms, including novel types of sRNAs and the previously unknown post-transcriptional RNA modifications. This underscores the importance for accurate, unbiased detection of sRNAs in various cellular contexts. A multitude of high-throughput methods based on next-generation sequencing (NGS) are developed to decipher the sRNA expression and their modifications. Nonetheless, distinct from mRNA sequencing, the data from sRNA sequencing suffer frequent inconsistencies and high variations emanating from the adapter contaminations and RNA modifications, which overall skew the sRNA libraries. Here, we summarize the sRNA-sequencing approaches, and discuss the considerations and challenges for the strategies and methods of sRNA library construction. The pros and cons of sRNA sequencing have significant implications for implementing RNA fragment footprinting approaches, including CLIP-seq and Ribo-seq. We envision that this review can inspire novel improvements in small RNA sequencing and RNA fragment footprinting in future. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Processing of Small RNAs Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs.

SingmiR: a single-cell miRNA alignment and analysis tool

Single-cell RNA sequencing (RNA-seq) has revolutionized our understanding of cell biology, developmental and pathophysiological molecular processes, paving the way toward novel diagnostic and therapeutic approaches. However, most of the gene regulatory processes on the single-cell level are still unknown, including post-transcriptional control conferred by microRNAs (miRNAs). Like the established single-cell gene expression analysis, advanced computational expertise is required to comprehensively process newly emerging single-cell miRNA-seq datasets. A web server providing a workflow tailored for single-cell miRNA-seq data with a self-explanatory interface is currently not available. Here, we present SingmiR, enabling the rapid (pre-)processing and quantification of human miRNAs from noncoding single-cell samples. It performs read trimming for different library preparation protocols, generates automated quality control reports and provides feature-normalized count files. Numerous standard and advanced analyses such as dimension reduction, clustered feature heatmaps, sample correlation heatmaps and differential expression statistics are implemented. We aim to speed up the prototyping pipeline for biologists developing single-cell miRNA-seq protocols on small to medium-sized datasets. SingmiR is freely available to all users without the need for a login at https://www.ccb.uni-saarland.de/singmir.

CRISPR/Cas9-based depletion of 16S ribosomal RNA improves library complexity of single-cell RNA-sequencing in planarians

BACKGROUND

Single-cell RNA-sequencing (scRNA-seq) relies on PCR amplification to retrieve information from vanishingly small amounts of starting material. To selectively enrich mRNA from abundant non-polyadenylated transcripts, poly(A) selection is a key step during library preparation. However, some transcripts, such as mitochondrial genes, can escape this elimination and overwhelm libraries. Often, these transcripts are removed in silico, but whether physical depletion improves detection of rare transcripts in single cells is unclear.

RESULTS

We find that a single 16S ribosomal RNA is widely enriched in planarian scRNA-seq datasets, independent of the library preparation method. To deplete this transcript from scRNA-seq libraries, we design 30 single-guide RNAs spanning its length. To evaluate the effects of depletion, we perform a side-by-side comparison of the effects of eliminating the 16S transcript and find a substantial increase in the number of genes detected per cell, coupled with virtually complete loss of the 16S RNA. Moreover, we systematically determine that library complexity increases with a limited number of PCR cycles following CRISPR treatment. When compared to in silico depletion of 16S, physically removing it reduces dropout rates, retrieves more clusters, and reveals more differentially expressed genes.

CONCLUSIONS

Our results show that abundant transcripts reduce the retrieval of informative transcripts in scRNA-seq and distort the analysis. Physical removal of these contaminants enables the detection of rare transcripts at lower sequencing depth, and also outperforms in silico depletion. Importantly, this method can be easily customized to deplete any abundant transcript from scRNA-seq libraries.

Blocking Abundant RNA Transcripts by High-Affinity Oligonucleotides during Transcriptome Library Preparation

BACKGROUND

RNA sequencing has become the gold standard for transcriptome analysis but has an inherent limitation of challenging quantification of low-abundant transcripts. In contrast to microarray technology, RNA sequencing reads are proportionally divided in function of transcript abundance. Therefore, low-abundant RNAs compete against highly abundant - and sometimes non-informative - RNA species.

RESULTS

We developed an easy-to-use strategy based on high-affinity RNA-binding oligonucleotides to block reverse transcription and PCR amplification of specific RNA transcripts, thereby substantially reducing their abundance in the final sequencing library. To demonstrate the broad application potential of our method, we applied it to different transcripts and library preparation strategies, including YRNAs in small RNA sequencing of human blood plasma, mitochondrial rRNAs in both 3' end sequencing and long-read sequencing, and MALAT1 in single-cell 3' end sequencing. We demonstrate that the blocking strategy is highly efficient, reproducible, specific, and generally results in better transcriptome coverage and complexity.

CONCLUSION

Our method does not require modifications of the library preparation procedure apart from simply adding blocking oligonucleotides to the RT reaction and can thus be easily integrated into virtually any RNA sequencing library preparation protocol.

Low-input RNase footprinting for simultaneous quantification of cytosolic and mitochondrial translation

We describe a low-input RNase footprinting approach for the rapid quantification of ribosome-protected fragments with as few as 1000 cultured cells. The assay uses a simplified procedure to selectively capture ribosome footprints based on optimized RNase digestion. It simultaneously maps cytosolic and mitochondrial translation with single-nucleotide resolution. We applied it to reveal selective functions of the elongation factor TUFM in mitochondrial translation, as well as synchronized repression of cytosolic translation after TUFM perturbation. We show the assay is applicable to small amounts of primary tissue samples with low protein synthesis rates, including snap-frozen tissues and immune cells from an individual's blood draw. We showed its feasibility to characterize the personalized immuno-translatome. Our analyses revealed that thousands of genes show lower translation efficiency in monocytes compared with lymphocytes, and identified thousands of translated noncanonical open reading frames (ORFs). Altogether, our RNase footprinting approach opens an avenue to assay transcriptome-wide translation using low-input samples from a wide range of physiological conditions.

Translation complex stabilization on messenger RNA and footprint profiling to study the RNA responses and dynamics of protein biosynthesis in the cells

During protein biosynthesis, ribosomes bind to messenger (m)RNA, locate its protein-coding information, and translate the nucleotide triplets sequentially as codons into the corresponding sequence of amino acids, forming proteins. Non-coding mRNA features, such as 5' and 3' untranslated regions (UTRs), start sites or stop codons of different efficiency, stretches of slower or faster code and nascent polypeptide interactions can alter the translation rates transcript-wise. Most of the homeostatic and signal response pathways of the cells converge on individual mRNA control, as well as alter the global translation output. Among the multitude of approaches to study translational control, one of the most powerful is to infer the locations of translational complexes on mRNA based on the mRNA fragments protected by these complexes from endonucleolytic hydrolysis, or footprints. Translation complex profiling by high-throughput sequencing of the footprints allows to quantify the transcript-wise, as well as global, alterations of translation, and uncover the underlying control mechanisms by attributing footprint locations and sizes to different configurations of the translational complexes. The accuracy of all footprint profiling approaches critically depends on the fidelity of footprint generation and many methods have emerged to preserve certain or multiple configurations of the translational complexes, often in challenging biological material. In this review, a systematic summary of approaches to stabilize translational complexes on mRNA for footprinting is presented and major findings are discussed. Future directions of translation footprint profiling are outlined, focusing on the fidelity and accuracy of inference of the native in vivo translation complex distribution on mRNA.

Single-cell microRNA sequencing method comparison and application to cell lines and circulating lung tumor cells

Molecular single cell analyses provide insights into physiological and pathological processes. Here, in a stepwise approach, we first evaluate 19 protocols for single cell small RNA sequencing on MCF7 cells spiked with 1 pg of 1,006 miRNAs. Second, we analyze MCF7 single cell equivalents of the eight best protocols. Third, we sequence single cells from eight different cell lines and 67 circulating tumor cells (CTCs) from seven SCLC patients. Altogether, we analyze 244 different samples. We observe high reproducibility within protocols and reads covered a broad spectrum of RNAs. For the 67 CTCs, we detect a median of 68 miRNAs, with 10 miRNAs being expressed in 90% of tested cells. Enrichment analysis suggested the lung as the most likely organ of origin and enrichment of cancer-related categories. Even the identification of non-annotated candidate miRNAs was feasible, underlining the potential of single cell small RNA sequencing.

Technologies for small non-coding RNA sequencing at the single-cell level are less mature than for sequencing mRNAs. Here the authors evaluate available protocols for analysis of circulating lung cancer tumour cells.

Small RNA-Sequencing: Approaches and Considerations for miRNA Analysis

MicroRNAs (miRNAs) are a class of small RNA molecules that have an important regulatory role in multiple physiological and pathological processes. Their disease-specific profiles and presence in biofluids are properties that enable miRNAs to be employed as non-invasive biomarkers. In the past decades, several methods have been developed for miRNA analysis, including small RNA sequencing (RNA-seq). Small RNA-seq enables genome-wide profiling and analysis of known, as well as novel, miRNA variants. Moreover, its high sensitivity allows for profiling of low input samples such as liquid biopsies, which have now found applications in diagnostics and prognostics. Still, due to technical bias and the limited ability to capture the true miRNA representation, its potential remains unfulfilled. The introduction of many new small RNA-seq approaches that tried to minimize this bias, has led to the existence of the many small RNA-seq protocols seen today. Here, we review all current approaches to cDNA library construction used during the small RNA-seq workflow, with particular focus on their implementation in commercially available protocols. We provide an overview of each protocol and discuss their applicability. We also review recent benchmarking studies comparing each protocol's performance and summarize the major conclusions that can be gathered from their usage. The result documents variable performance of the protocols and highlights their different applications in miRNA research. Taken together, our review provides a comprehensive overview of all the current small RNA-seq approaches, summarizes their strengths and weaknesses, and provides guidelines for their applications in miRNA research.

Novel CRISPR-based sequence specific enrichment methods for target loci and single base mutations

The programmable sequence specificity of CRISPR has found uses in gene editing and diagnostics. This manuscript describes an additional application of CRISPR through a family of novel DNA enrichment technologies. CAMP (CRISPR Associated Multiplexed PCR) and cCAMP (chimeric CRISPR Associated Multiplexed PCR) utilize the sequence specificity of the Cas9/sgRNA complex to target loci for the ligation of a universal adapter that is used for subsequent amplification. cTRACE (chimeric Targeting Rare Alleles with CRISPR-based Enrichment) also applies this method to use Cas9/sgRNA to target loci for the addition of universal adapters, however it has an additional selection for specific mutations through the use of an allele-specific primer. These three methods can produce multiplex PCR that significantly reduces the optimization required for every target. The methods are also not specific to any downstream analytical platform. We additionally will present a mutation specific enrichment technology that is non-amplification based and leaves the DNA in its native state: TRACE (Targeting Rare Alleles with CRISPR-based Enrichment). TRACE utilizes the Cas9/sgRNA complex to sterically protect the ends of targeted sequences from exonuclease activity which digests both the normal variant as well as any off-target sequences.

Construction of prokaryotic strand-specific primary-transcripts saturated RNASeq library by controlled heat magnesium-dependent mRNA degradation

The main limiting factors for RNA-Seq analysis are quality and quantity of the isolated mRNA. In prokaryotes, the proportion of messenger RNA to total RNA is rather low. Therefore, the main strategy of library preparation for sequencing is mRNA enrichment. Ribosomal and transfer RNAs, both monophosphorylated at the 5'-ends, are the major fractions of total RNA, while the bulk of primary transcripts is triphosphorylated at the 5'-teminus. Due to its low molecular weight, transfer RNA could be easily removed by a quick precipitation in LiCl solution. Ribosomal RNA may be degraded enzymatically by 5'-end terminal exonuclease XRN-1. These steps allow enriching samples in mRNA during the first stages of RNA-Seq library preparation. The desired level of fragmentation of enriched mRNA necessary for the 2^nd generation sequencing can be controlled by the duration of incubation at elevated temperatures in the presence of Mg²⁺-ions. Here, we describe a simple protocol for construction of the primary prokaryotic mRNA-saturated library without long depletion procedures.

Improved bacterial RNA-seq by Cas9-based depletion of ribosomal RNA reads

A major challenge for RNA-seq analysis of gene expression is to achieve sufficient coverage of informative nonribosomal transcripts. In eukaryotic samples, this is typically achieved by selective oligo(dT)-priming of messenger RNAs to exclude ribosomal RNA (rRNA) during cDNA synthesis. However, this strategy is not compatible with prokaryotes in which functional transcripts are generally not polyadenylated. To overcome this, we adopted DASH (depletion of abundant sequences by hybridization), initially developed for eukaryotic cells, to improve both the sensitivity and depth of bacterial RNA-seq. DASH uses the Cas9 nuclease to remove unwanted cDNA sequences prior to library amplification. We report the design, evaluation, and optimization of DASH experiments for standard bacterial short-read sequencing approaches, including software for automated guide RNA (gRNA) design for Cas9-mediated cleavage in bacterial rDNA sequences. Using these gRNA pools, we effectively removed rRNA reads (56%-86%) in RNA-seq libraries from two different model bacteria, the Gram-negative pathogen Salmonella enterica and the anaerobic gut commensal Bacteroides thetaiotaomicron DASH works robustly, even with subnanogram amounts of input RNA. Its efficiency, high sensitivity, ease of implementation, and low cost (∼$5 per sample) render DASH an attractive alternative to rRNA removal protocols, in particular for material-constrained studies where conventional ribodepletion techniques fail.

Depletion of erythropoietic miR-486-5p and miR-451a improves detectability of rare microRNAs in peripheral blood-derived small RNA sequencing libraries

Erythroid-specific miR-451a and miR-486-5p are two of the most dominant microRNAs (miRNAs) in human peripheral blood. In small RNA sequencing libraries, their overabundance reduces diversity as well as complexity and consequently causes negative effects such as missing detectability and inaccurate quantification of low abundant miRNAs. Here we present a simple, cost-effective and easy to implement hybridization-based method to deplete these two erythropoietic miRNAs from blood-derived RNA samples. By utilization of blocking oligonucleotides, this method provides a highly efficient and specific depletion of miR-486-5p and miR-451a, which leads to a considerable increase of measured expression as well as detectability of low abundant miRNA species. The blocking oligos are compatible with common 5′ ligation-dependent small RNA library preparation protocols, including commercially available kits, such as Illumina TruSeq and Perkin Elmer NEXTflex. Furthermore, the here described method and oligo design principle can be easily adapted to target many other miRNA molecules, depending on context and research question.