分子生物学

Many single nucleotide polymorphisms (SNPs) identified by genome-wide association studies exert their effects on disease risk as expression quantitative trait loci (eQTL) via allele-specific expression (ASE). While databases for probing eQTLs in tissues from normal individuals exist, one may wish to ascertain eQTLs or ASE in specific tissues or disease-states not characterized in these databases. Here, we present a protocol to assess ASE of two possible target genes (GPNMB and KLHL7) of a known genome-wide association study (GWAS) Parkinson’s disease (PD) risk locus in postmortem human brain tissue from PD and neurologically normal individuals. This was done using a sequence of RNA isolation, cDNA library generation, enrichment for transcripts of interest using customizable cDNA capture probes, paired-end RNA sequencing, and subsequent analysis. This method provides increased sensitivity relative to traditional bulk RNAseq-based and a blueprint that can be extended to the study of other genes, tissues, and disease states.

Key features

• Analysis of GPNMB allele-specific expression (ASE) in brain lysates from cognitively normal controls (NC) and Parkinson’s disease (PD) individuals.

• Builds on the ASE protocol of Mayba et al. (2014) and extends application from cells to human tissue.

• Increased sensitivity by enrichment for desired transcript via RNA CaptureSeq (Mercer et al., 2014).

• Optimized for human brain lysates from cingulate gyrus, caudate nucleus, and cerebellum.

Graphical overview

Information on RNA localisation is essential for understanding physiological and pathological processes, such as gene expression, cell reprogramming, host–pathogen interactions, and signalling pathways involving RNA transactions at the level of membrane-less or membrane-bounded organelles and extracellular vesicles. In many cases, it is important to assess the topology of RNA localisation, i.e., to distinguish the transcripts encapsulated within an organelle of interest from those merely attached to its surface. This allows establishing which RNAs can, in principle, engage in local molecular interactions and which are prevented from interacting by membranes or other physical barriers. The most widely used techniques interrogating RNA localisation topology are based on the treatment of isolated organelles with RNases with subsequent identification of the surviving transcripts by northern blotting, qRT-PCR, or RNA-seq. However, this approach produces incoherent results and many false positives. Here, we describe Controlled Level of Contamination coupled to deep sequencing (CoLoC-seq), a more refined subcellular transcriptomics approach that overcomes these pitfalls. CoLoC-seq starts by the purification of organelles of interest. They are then either left intact or lysed and subjected to a gradient of RNase concentrations to produce unique RNA degradation dynamics profiles, which can be monitored by northern blotting or RNA-seq. Through straightforward mathematical modelling, CoLoC-seq distinguishes true membrane-enveloped transcripts from degradable and non-degradable contaminants of any abundance. The method has been implemented in the mitochondria of HEK293 cells, where it outperformed alternative subcellular transcriptomics approaches. It is applicable to other membrane-bounded organelles, e.g., plastids, single-membrane organelles of the vesicular system, extracellular vesicles, or viral particles.

Key features

• Tested on human mitochondria; potentially applicable to cell cultures, non-model organisms, extracellular vesicles, enveloped viruses, tissues; does not require genetic manipulations or highly pure organelles.

• In the case of human cells, the required amount of starting material is ~2,500 cm² of 80% confluent cells (or ~3 × 10⁸ HEK293 cells).

• CoLoC-seq implements a special RNA-seq strategy to selectively capture intact transcripts, which requires RNases generating 5′-hydroxyl and 2′/3′-phosphate termini (e.g., RNase A, RNase I).

• Relies on nonlinear regression software with customisable exponential functions.

Graphical overview

Inflammation of the gastrointestinal tract is a prevalent pathology in diseases such as inflammatory bowel disease (IBD). Currently, there are no therapies to prevent IBD, and available therapies to treat IBD are often sub-optimal. Thus, an unmet need exists to better understand the molecular mechanisms underlying intestinal tissue responses to damage and regeneration. The recent development of single-cell RNA (sc-RNA) sequencing-based techniques offers a unique opportunity to shed light on novel signaling pathways and cellular states that govern tissue adaptation or maladaptation across a broad spectrum of diseases. These approaches require the isolation of high-quality cells from tissues for downstream transcriptomic analyses. In the context of intestinal biology, there is a lack of protocols that ensure the isolation of epithelial and non-epithelial compartments simultaneously with high-quality yield. Here, we report two protocols for the isolation of epithelial and stromal cells from mouse and human colon tissues under inflammatory conditions. Specifically, we tested the feasibility of the protocols in a mouse model of dextran sodium sulfate (DSS)-induced colitis and in human biopsies from Crohn’s patients. We performed sc-RNA sequencing analysis and demonstrated that the protocol preserves most of the epithelial and stromal cell types found in the colon. Moreover, the protocol is suitable for immunofluorescence staining of surface markers for epithelial, stromal, and immune cell lineages for flow cytometry analyses. This optimized protocol will provide a new resource for scientists to study complex tissues such as the colon in the context of tissue damage and regeneration.

Key features

• This protocol allows the isolation of epithelial and stromal cells from colon tissues.

• The protocol has been optimized for tissues under inflammatory conditions with compromised cell viability.

• This protocol is suitable for experimental mouse models of colon inflammation and human biopsies.

Graphical overview

Graphical representation of the main steps for the processing of colon tissue from dextran sodium sulfate (DSS)-treated mice (upper panel) and frozen biopsies from Crohn’s patients (lower panel)

In eukaryotic cells, RNA biogenesis generally requires processing of the nascent transcript as it is being synthesized by RNA polymerase. These processing events include endonucleolytic cleavage, exonucleolytic trimming, and splicing of the growing nascent transcript. Endonucleolytic cleavage events that generate an exposed 5′-monophosphorylated (5′-PO₄) end on the growing nascent transcript occur in the maturation of rRNAs, tRNAs, and mRNAs. These 5′-PO₄ ends can be a target of further processing or be subjected to 5′-3′ exonucleolytic digestion that may result in termination of transcription. Here, we describe how to identify 5′-PO₄ ends of intermediates in nascent RNA metabolism. We capture these species via metabolic labeling with bromouridine followed by immunoprecipitation and specific ligation of 5′-PO₄ RNA ends with the 3′-hydroxyl group of a 5′ adaptor (5′-PO₄ Bru-Seq) using RNA ligase I. These ligation events are localized at single nucleotide resolution via highthroughput sequencing, which identifies the position of 5′-PO₄ groups precisely. This protocol successfully detects the 5′monophosphorylated ends of RNA processing intermediates during production of mature ribosomal, transfer, and micro RNAs. When combined with inhibition of the nuclear 5′-3′ exonuclease Xrn2, 5′-PO₄ Bru-Seq maps the 5′ splice sites of debranched introns and mRNA and tRNA 3′ end processing sites cleaved by CPSF73 and RNaseZ, respectively.

Key features

• Metabolic labeling for brief periods with bromouridine focuses the analysis of 5′-PO₄ RNA ends on the population of nascent transcripts that are actively transcribed.

• Detects 5′-PO₄ RNA ends on nascent transcripts produced by all RNA polymerases.

• Detects 5′-PO₄ RNA ends at single nucleotide resolution.

Long noncoding RNAs (lncRNAs) play essential roles in normal physiology and in disease but their mechanisms of action can be challenging to identify. For mechanistic studies, it is often useful to know a lncRNA’s intracellular abundance, i.e., approximately how many molecules of the lncRNA are present in a typical cell of a cell-type of interest. At least two approaches have been used to approximate lncRNA intracellular abundance: single-molecule sensitivity RNA fluorescence in situ hybridization (smFISH) and single-gene, calibrated reverse-transcription followed by quantitative PCR (RT-qPCR). However, like all experimental approaches, these methods have their limitations. smFISH, when analyzed using diffraction-limited microscopy, can underestimate intracellular abundance, especially for lncRNAs that accumulate in focused subcellular regions. Calibrated RT-qPCR may return inaccurate estimates of abundance because individual PCR amplicons spaced across the length of a transcript can vary in their efficiency of reverse transcription. Here, we describe a sequencing-based approach that is straightforward, orthogonal to smFISH and RT-qPCR, and can be used to approximate the intracellular abundance for most expressed long RNAs (lncRNAs and mRNAs) in a cell type of interest. Firstly, the average weight of total RNA per cell for the cell type of interest is estimated by replicate rounds of RNA purification from a known number of cells. Secondly, an rRNA-depletion RNA-Seq protocol is performed after adding spike-in control RNAs to a known quantity of total cellular RNA. Lastly, by comparing read counts per transcript to a standard curve derived from the spiked-in RNAs, the intracellular abundance for each transcript is estimated. The sequencing-based approach provides a powerful complement to existing methods, particularly in situations where it is desirable to quantify the abundance of multiple lncRNAs and/or mRNAs simultaneously.

RNA-Seq is a powerful method for transcriptome analysis used in varied field of biology. Although several commercial products and hand-made protocols enable us to prepare RNA-Seq library from total RNA, their cost are still expensive. Here, we established a low-cost and multiplexable whole mRNA-Seq library preparation method for illumine sequencers. In order to reduce cost, we used cost-effective and robust commercial regents with small reaction volumes. This method is a whole mRNA-Seq, which can be applied even to non-model organisms lacking the transcriptome references. In addition, we designed large number of 3′ PCR primer including 8 nucleotides barcode sequences for multiplexing up to three hundreds samples. To summarize, it is possible with this protocol to prepare 96 directional RNA-Seq libraries from purified total RNA in three days and can be pooled for up to three hundred libraries. This is beneficial for large scale transcriptome analysis in many fields of animals and plant biology.

Cell heterogeneity is high in tissues like lung. Research conducted on pure population of cells usually offers more insights than bulk tissues, such as circadian clock work. In this protocol, we provide a detailed work flow on how to do circadian clock study by RNA seq in laser capture micro-dissected mouse lung club cells. The method uses frozen tissues and is highly reproduciable.

Adaptation is thought to proceed in part through spatial and temporal changes in gene expression. Fish species such as the threespine stickleback are powerful vertebrate models to study the genetic architecture of adaptive changes in gene expression since divergent adaptation to different environments is common, they are abundant and easy to study in the wild and lab, and have well-established genetic and genomic resources. Fish gills, due to their respiratory and osmoregulatory roles, show many physiological adaptations to local water chemistry, including differences in gene expression. However, obtaining high-quality RNA using popular column-based extraction methods can be challenging from small tissue samples high in cartilage and bone such as fish gills. Here, we describe a bead-based mRNA extraction and transcriptome RNA-seq protocol that does not use purification columns. The protocol can be readily scaled according to sample size for the purposes of diverse gene expression experiments using animal or plant tissue.

Whole transcriptome analysis is a key method in biology that allows researchers to determine the effect a condition has on gene regulation. One difficulty in RNA sequencing of muscle is that traditional methods are performed on the whole muscle, but this captures non-myogenic cells that are part of the muscle. In order to analyze only the transcriptome of myofibers we combine single myofiber isolation with SMART-Seq to provide high resolution genome wide expression of a single myofiber.

RNA molecules adopt defined structural conformations that are essential to exert their function. During the course of evolution, the structure of a given RNA can be maintained via compensatory base-pair changes that occur among covarying nucleotides in paired regions. Therefore, for comparative, structural, and evolutionary studies of RNA molecules, numerous computational tools have been developed to incorporate structural information into sequence alignments and a number of tools have been developed to study covariation. The bioinformatic protocol presented here explains how to use some of these tools to generate a secondary-structure-aware multiple alignment of RNA sequences and to annotate the alignment to examine the conservation and covariation of structural elements among the sequences.