Molecular Biology

Single-nucleus RNA sequencing (snRNA-seq) provides a powerful tool for studying cell type composition in heterogenous tissues. The liver is a vital organ composed of a diverse set of cell types; thus, single-cell technologies could greatly facilitate the deconvolution of liver tissue composition and various downstream omics analyses at the cell-type level. Applying single-cell technologies to fresh liver biopsies can, however, be very challenging, and snRNA-seq of snap-frozen liver biopsies requires some optimization given the high nucleic acid content of the solid liver tissue. Therefore, an optimized protocol for snRNA-seq specifically targeted for the use of frozen liver samples is needed to improve our understanding of human liver gene expression at the cell-type resolution. We present a protocol for performing nuclei isolation from snap-frozen liver tissues, as well as guidance on the application of snRNA-seq. We also provide guidance on optimizing the protocol to different tissue and sample types.

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.

Endogenous retroviruses (ERV) are transposable retroelements that form ~10% of the murine genome and whose family members are differentially expressed throughout embryogenesis. However, precise regulation of ERV in germ cells remains unclear. To investigate ERV expression in oocytes, we adapted a single-cell mRNA-sequencing library preparation method to generate bulk sequencing libraries from growing oocytes in a time- and cost-efficient manner. Here, we present a modified Smart-seq2 protocol that yields full-length cDNA libraries from purified RNA obtained from low numbers of pooled immature or mature oocytes. Using this method, RNA-sequencing libraries can be generated from any rare or difficult-to-isolate populations for subsequent sequencing and retroelement expression analysis.

Neuronal processes have an RNA composition that is distinct from the cell body. Therefore, to fully understand neuronal biology in health and disease we need to study both somas, dendrites and axons. Here we describe a detailed protocol of a newly refined method, Axon-seq, for RNA sequencing of axons (and dendrites) grown in isolation using single microfluidic devices. We also detail how to generate motor neurons from mouse and human pluripotent stem cells for sequencing, but Axon-seq is applicable to any neuronal cell. In Axon-seq, the axons are recruited through a growth factor gradient, lysed and directly processed to cDNA without RNA isolation. A careful bioinformatic step ensures that any soma-contaminated samples are easily identified and removed.

In virology the difference between the fitness of two viruses can be determined by using various methods, such as virus titer, growth curve analysis, measurement of virus infectivity, analysis of produced RNA copies and viral protein production. However, for closely performing viruses, it is often very hard to distinguish the differences. In vitro competition assays are a sensitive tool for determining viral replication fitness for many viruses replicating in cell culture. Relative viral replication fitness is usually measured from multiple cycle growth competition assays. Competition assays provide a sensitive measurement of viral fitness since the viruses are competing for cellular targets under identical growth conditions. This protocol describes a competition assay for enteroviruses and contains two alternative formats for initial infections, which can be varied depending on specific goals for each particular experiment. The protocol involves infection of cells with competing viruses, passaging, RNA extraction from infected cells, RT-PCR and Sanger sequencing followed by comparative analysis of resulting chromatograms obtained under various initial infection conditions. The techniques are applicable to members of many virus families, such as alphaviruses, flaviviruses, pestiviruses, and other RNA viruses with an established reverse genetics system.