The authors would like to express their gratitude to the laboratories, groups and individuals who have developed Galaxy and DAVID, and thus made NGS widely accessible for the scientific community. The help and advice provided by colleagues at the University of Pittsburgh during our bioinformatics training is acknowledged. This work was supported by an Ellison Medical Foundation New Scholar in Aging award (AG-NS-0879-12) and a grant from the National Institutes of Health (R01AG051659) to AG.

<ol>
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The authors have nothing to disclose.

Significance of the Galaxy Sequencing Platform in Modern Biology
The Galaxy Project has become instrumental in helping biologists without bioinformatics training to process and analyze high-throughput sequencing data in a fast and efficient manner. Once considered a herculean task, this publicly-available platform has made running complex bioinformatics algorithms to analyze NGS data a straightforward, reliable, and easy process. Apart from hosting a wide range of bioinformatics tools, the key to...

The first sequencing of the human genome, performed using Fred Sanger&#39;s dideoxynucleotide-sequencing method, took 10 years, and cost an estimated US $3 billion1,2. However, in a little over a decade since its inception, Next-Generation Sequencing (NGS) technology has made it possible to sequence the entire human genome within two weeks and for US $1,000. New NGS instruments that allow ever-increasing speeds of sequencing-data collection with incredible efficiency, along with sharp reductions in cost, are revolutionizing modern biology in unimaginable ways as genome sequencing projects are rapidly becoming commonplace. In addition, these developments have galvanized progress in many other areas such as gene-expression analysis through RNA-Sequencing (RNA-Seq), study of genome-wide epigenetic modifications, DNA-protein interactions, and screening for microbial diversity in human hosts. NGS-based RNA-Seq in particular has made it possible to identify and map transcriptomes comprehensively with accuracy and sensitivity, and has replaced microarray technology as the method of choice for expression profiling. While microarray technology has been used extensively, it is limited by its reliance on pre-existing arrays with known genomic information, and other drawbacks such as cross hybridization and restricted range of expression changes that can be measured reliably. RNA-seq, on the other hand, can be used to detect both known and unknown transcripts while producing low background noise due to its unambiguous DNA mapping nature. RNA-Seq, together with the numerous genetic tools offered by model organisms such as yeast, flies, worms, fish and mice, has served as the foundation for many important recent biomedical discoveries. However, significant challenges remain that make NGS inaccessible to the wider scientific community, including limitations of storage, processing, and most of all, meaningful bioinformatics analysis of large volumes of sequencing data.
The rapid advances in sequencing technologies and exponential data accumulation have created a great need for computational platforms that will allow researchers to access, analyze and understand this information. Early systems were heavily dependent upon computer programming knowledge, whereas, genome browsers such as NCBI that allowed non-programmers to access and visualize data did not permit sophisticated analyses. The web-based, open-access platform, Galaxy (<a href="https://galaxyproject.org/" target="_blank">https://galaxyproject.org/</a>), has filled this void and proven to be a valuable pipeline that enables researchers to process NGS data and perform a spectrum of simple-to-complex bioinformatics analyses. Galaxy was initially established, and is maintained, by the laboratories of Anton Nekrutenko (Penn State University) and James Taylor (Johns Hopkins University)3. Galaxy offers a wide range of computational tasks making it a &#39;one-stop shop&#39; for innumerable bioinformatics needs, including all the steps involved in an RNA-Seq study. Itallows users to perform data processing either on its servers or locally on their own machines. Data and workflows can be reproduced and shared. Online tutorials, help section, and a wiki-page (<a href="https://wiki.galaxyproject.org/Support" target="_blank">https://wiki.galaxyproject.org/Support</a>) dedicated to the Galaxy Project provide consistent support. However, for first-time users, especially those with no bioinformatics training, the pipeline can appear daunting and the process of self-learning and familiarization can be time consuming. In addition, the biological system studied, and specifics of the experiment and methods used, impact the analytical decisions at several steps, and these can be difficult to navigate without instruction.
The Overall RNA-Seq Galaxy Workflow consists of data upload and quality check followed by analysis using the Tuxedo Suite4,5,6,7,8,9, which is a collective of various tools required for different stages of RNA-Seq data analysis10,11,12,13,14. A typical RNA-Seq experiment consists of the experimental part (sample preparation, mRNA isolation and cDNA library preparation), the NGS and the bioinformatics data analysis. An overview of these sections, and the steps involved in the Galaxy pipeline, are shown in Figure 1.
<img alt="Figure 1" src="/files/ftp_upload/55473/55473fig1.jpg" /> 
Figure 1: Overview of an RNA-Seq Workflow. Illustration of the experimental and computational steps involved in an RNA-Seq experiment to compare the gene-expression profiles of two worm strains (A and B, orange and green lines and arrows, respectively). The different modules of Galaxy utilized are shown in boxes with the corresponding step in our protocol indicated in red. The outputs of various operations are written in grey with the file formats shown in blue. <a href="http://cloudflare.jove.com/files/ftp_upload/55473/55473fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The first tool in the Tuxedo Suite is an alignment program called &#39;Tophat&#39;. It breaks down the NGS input reads into smaller fragments and then maps them to a reference genome. This two-step process ensures that reads spanning intronic regions whose alignment can otherwise be disrupted or missed are accounted for and mapped. This increases coverage and facilitates the identification of novel splice junctions. Tophat output is reported as two files, a BED file (with information about splice junctions that include genomic location) and a BAM file (with mapping details of each read). Next, the BAM file is aligned against a reference genome to estimate the abundance of individual transcripts within each sample using the subsequent tool in the Tuxedo Suite called &#39;Cufflinks&#39;. Cufflinks functions by scanning the alignment to report full-length transcript fragments or &#39;transfrags&#39; that span all the possible splice variants in the input data for every gene. Based on this, it generates a &#39;transcriptome&#39; (assembly of all the transcripts generated per gene for every gene) for each sample being sequenced. These Cufflinks assemblies are then collapsed or merged together along with the reference genome to produce a single annotation file for downstream differential analysis using the next tool, &#39;Cuffmerge&#39;. Finally, the &#39;Cuffdiff&#39; tool measures differential gene expression between samples by comparing the TopHat outputs of each of the samples to the final Cuffmerge output file (Figure 1). Cufflinks uses FPKM/RPKM (Fragments/Reads Per Kilobase of transcript per Million mapped reads) values to report transcript abundances. These values reflect the normalization of the raw NGS data for depth (average number of reads from a sample that align to the reference genome) and gene length (genes have different lengths, so counts have to be normalized for length of a gene to compare levels between genes). FPKM and RPKM are essentially the same with RPKM being used for single-end RNA-Seq where every read corresponds to a single fragment, whereas, FPKM is used for paired-end RNA-Seq, as it accounts for the fact that two reads can correspond to the same fragment. Ultimately, the outcome of these analyses is a list of genes differentially expressed between the conditions and/or strains tested.
Once a successful Galaxy run is completed and a &#39;gene list&#39; is generated, the next logical step requires more bioinformatics analyses to deduce meaningful knowledge from the datasets. Many software packages have emerged to cater to this need, including publicly-available web-based computational packages such as DAVID (the Database for Annotation, Visualization and Integrated discovery)15. DAVID facilitates assigning biological meaning to large gene lists from high-throughput studies by comparing the uploaded gene list to its integrated biological knowledgebase and revealing the biological annotations associated with the gene list. This is followed by Enrichment Analysis, i.e., tests to identify if any biological process or gene class is overrepresented in the gene list(s) in a statistically significant manner. It has become a popular choice because of a combination of a wide, integrated knowledge-base and powerful analytical algorithms that enable researchers to detect biological themes enriched within genomics-derived &#39;gene lists&#39;10,16. Additional advantages include its ability to process gene lists created on any sequencing platform and a highly user-friendly interface.
The nematode Caenorhabditis elegans is a genetic model system, well known for its many advantages such as small size, transparent body, simple body plan, ease of culture and great amenability to genetic and molecular dissection. Worms have a small, simple and well-annotated genome that includes up to 40% conserved genes with known human homologs17. Indeed, C. elegans was the first metazoan whose genome was completely sequenced18, and one of the first species where RNA-Seq was used to map an organism&#39;s transcriptome19,20. Early worm studies involved experimentation with different methods for high-throughput RNA capture, library preparation and sequencing as well as bioinformatics pipelines that contributed to the advancement of the technology21,22. In recent years, RNA-Seq-based experimentation in worms has become commonplace. But, for traditional worm biologists the challenges posed by computational analysis of RNA-Seq data remain a major impediment for greater and better utilization of the technique.
In this article, we describe a protocol for using the Galaxy platform to analyze high-throughput RNA-Seq data generated from C. elegans. For many first-time and small-scale users, the most cost-efficient and straightforward way to undertake an RNA-Seq experiment is to isolate RNA in the lab and utilize a commercial (or in-house) NGS facility for preparation of sequencing cDNA libraries and the NGS itself. Hence, we have first detailed the steps involved in isolation, quantification and quality assessment of C. elegans RNA samples for RNA-Seq. Next, we provide step-by-step instructions for using the Galaxy interface for analyses of the NGS data, beginning with tests for post-sequencing quality-control checks followed by alignment, assembly, and differential quantification of gene expression. In addition, we have included directions to scrutinize the gene lists resulting from Galaxy for biological enrichment studies using DAVID. As a final step in the workflow, we provide instructions for uploading RNA-Seq data on to public servers such as the Sequence Read Archive (SRA) on NCBI (<a href="http://www.ncbi.nlm.nih.gov/sra" target="_blank">http://www.ncbi.nlm.nih.gov/sra</a>) to make it freely accessible to the scientific community. Overall, we anticipate that this article will provide comprehensive and sufficient information to worm biologists undertaking RNA-Seq experiments for the first time as well as frequent users running a small number of samples.

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transcriptomic analysis of c. elegans rna sequencing data through the tuxedo suite on the galaxy project

Next generation sequencing (NGS) technologies have revolutionized the nature of biological investigation. Of these, RNA Sequencing (RNA-Seq) has emerged as a powerful tool for gene-expression analysis and transcriptome mapping. However, handling RNA-Seq datasets requires sophisticated computational expertise and poses inherent challenges for biology researchers. This bottleneck has been mitigated by the open access Galaxy project that allows users without bioinformatics skills to analyze RNA-Seq data, and the Database for Annotation, Visualization, and Integrated Discovery (DAVID), a Gene Ontology (GO) term analysis suite that helps derive biological meaning from large data sets. However, for first-time users and bioinformatics' amateurs, self-learning and familiarization with these platforms can be time-consuming and daunting. We describe a straightforward workflow that will help C. elegans researchers to isolate worm RNA, conduct an RNA-Seq experiment and analyze the data using Galaxy and DAVID platforms. This protocol provides stepwise instructions for using the various Galaxy modules for accessing raw NGS data, quality-control checks, alignment, and differential gene expression analysis, guiding the user with parameters at every step to generate a gene list that can be screened for enrichment of gene classes or biological processes using DAVID. Overall, we anticipate that this article will provide information to C. elegans researchers undertaking RNA-Seq experiments for the first time as well as frequent users running a small number of samples.

In C. elegans, elimination of the germline stem cells (GSCs) extends lifespan, enhances stress resilience, and elevates body fat24,28. Loss of GSCs, either brought about by laser-ablation or by mutations such as glp-1, causes lifespan extension through activation of a network of transcription factors29. One such factor, TCER-1, encodes the worm homolog of the human transcription elongation...

Watch this Scientific Journal Video about Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project at JoVE.com

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Galaxy and DAVID have emerged as popular tools that allow investigators without bioinformatics training to analyze and interpret RNA-Seq data. We describe a protocol for C. elegans researchers to perform RNA-Seq experiments, access and process the dataset using Galaxy and obtain meaningful biological information from the gene lists using DAVID.

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Next generation sequencing (NGS) technologies have revolutionized the nature of biological investigation. Of these, RNA Sequencing (RNA-Seq) has emerged ...

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Research

JoVE Journal

Genetics

17.3K Views.  University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh.  Galaxy en David hebben zich ontwikkeld tot populaire tools die het mogelijk maken de onderzoekers zonder bioinformatica training te analyseren en RNA-Seq gegevens te interpreteren. We beschrijven een protocol voor C. elegans onderzoekers RNA-Seq experimenten toegang voeren en verwerken dataset behulp Galaxy en zinvolle biologische informatie uit het gen lijsten met behulp DAVID verkrijgen. 

Video: Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response

Complex changes in gene expression typically mediate a large portion of a cellular response. Each gene may change expression with unique kinetics as the gene is regulated by the particular timing of one of many stimuli, signaling pathways or secondary effects. In order to capture the entire gene expression response to hypoxia in the yeast S. cerevisiae, RNA-seq analysis was used to monitor the mRNA levels of all genes at specific times after exposure to hypoxia. Hypoxia was established by growing cells in ~100% N2 gas. Importantly, unlike other hypoxic studies, ergosterol and unsaturated fatty acids were not added to the media because these metabolites affect gene expression. Time points were chosen in the range of 0 - 4 h after hypoxia because that period captures the major changes in gene expression. At each time point, mid-log hypoxic cells were quickly filtered and frozen, limiting exposure to O2 and concomitant changes in gene expression. Total RNA was extracted from cells and used to enrich for mRNA, which was then converted to cDNA. From this cDNA, multiplex libraries were created and eight or more samples were sequenced in one lane of a next-generation sequencer. A post-sequencing pipeline is described, which includes quality base trimming, read mapping and determining the number of reads per gene. DESeq2 within the R statistical environment was used to identify genes that change significantly at any one of the hypoxic time points. Analysis of three biological replicates revealed high reproducibility, genes of differing kinetics and a large number of expected O2-regulated genes. These methods can be used to study how the cells of various organisms respond to hypoxia over time and adapted to study gene expression during other cellular responses.

Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response

Here, we present a protocol using RNA-seq to monitor mRNA levels over time during the hypoxic response of S. cerevisiae cells. This method can be adapted to analyze gene expression during any cellular response.

Complex changes in gene expression typically mediate a large portion of a cellular response. Each gene may change expression with unique kinetics as the ...

Defining Gene Functions in Tumorigenesis by Ex vivo Ablation of Floxed Alleles in Malignant Peripheral Nerve Sheath Tumor Cells

The development of new drugs that precisely target key proteins in human cancers is fundamentally altering cancer therapeutics. However, before these drugs can be used, their target proteins must be validated as therapeutic targets in specific cancer types. This validation is often performed by knocking out the gene encoding the candidate therapeutic target in a genetically engineered mouse (GEM) model of cancer and determining what effect this has on tumor growth. Unfortunately, technical issues such as embryonic lethality in conventional knockouts and mosaicism in conditional knockouts often limit this approach. To overcome these limitations, an approach to ablating a floxed embryonic lethal gene of interest in short-term cultures of malignant peripheral nerve sheath tumors (MPNSTs) generated in a GEM model was developed.
This paper describes how to establish a mouse model with the appropriate genotype, derive short-term tumor cultures from these animals, and then ablate the floxed embryonic lethal gene using an adenoviral vector that expresses Cre recombinase and enhanced green fluorescent protein (eGFP). Purification of cells transduced with adenovirus using fluorescence-activated cell sorting (FACS) and the quantification of the effects that gene ablation exerts on cellular proliferation, viability, the transcriptome, and orthotopic allograft growth is then detailed. These methodologies provide an effective and generalizable approach to identifying and validating therapeutic targets in vitro and in vivo. These approaches also provide a renewable source of low-passage tumor-derived cells with reduced in vitro growth artifacts. This allows the biological role of the targeted gene to be studied in diverse biologic processes such as migration, invasion, metastasis, and intercellular communication mediated by the secretome.

Defining Gene Functions in Tumorigenesis by Ex vivo Ablation of Floxed Alleles in Malignant Peripheral Nerve Sheath Tumor Cells

Here, we present a protocol for performing gene knockouts that are embryonic lethal in vivo in genetically engineered mouse model-derived tumors and then assessing the effect that the knockout has on tumor growth, proliferation, survival, migration, invasion, and the transcriptome in vitro and in vivo.

The development of new drugs that precisely target key proteins in human cancers is fundamentally altering cancer therapeutics. However, before these ...

Cancer Research

Epigenetic Inheritance and ChIP in Caenorhabditis elegans

Analysis of Transgenerational Epigenetic Inheritance in C. elegans Using a Fluorescent Reporter and Chromatin Immunoprecipitation (ChIP)

Transgenerational epigenetic inheritance (TEI) allows the transmission of information through the germline without changing the genome sequence, through factors such as non-coding RNAs and chromatin modifications. The phenomenon of RNA interference (RNAi) inheritance in the nematode Caenorhabditis elegans is an effective model to investigate TEI that takes advantage of this model organism's short life cycle, self-propagation, and transparency. In RNAi inheritance, exposure of animals to RNAi leads to gene silencing and altered chromatin signatures at the target locus that persist for multiple generations in the absence of the initial trigger. This protocol describes the analysis of RNAi inheritance in C. elegans using a germline-expressed nuclear green fluorescent protein (GFP) reporter. Reporter silencing is initiated by feeding the animals bacteria expressing double-stranded RNA targeting GFP. At each generation, animals are passaged to maintain synchronized development, and reporter gene silencing is determined by microscopy. At select generations, populations are collected and processed for chromatin immunoprecipitation (ChIP)-quantitative polymerase chain reaction (qPCR) to measure histone modification enrichment at the GFP reporter locus. This protocol for studying RNAi inheritance can be easily modified and combined with other analyses to further investigate TEI factors in small RNA and chromatin pathways.

Author Spotlight: RNAi Inheritance and ChIP in C. elegans 

This protocol describes an RNA interference and ChIP assay to study the epigenetic inheritance of RNAi-induced silencing and associated chromatin modifications in C. elegans.

Transgenerational epigenetic inheritance (TEI) allows the transmission of information through the germline without changing the genome sequence, through ...

RNA-Seq Analysis of Differential Gene Expression in Electroporated Chick Embryonic Spinal Cord

In ovo electroporation of the chick neural tube is a fast and inexpensive method for identification of gene function during neural development. Genome wide analysis of differentially expressed transcripts after such an experimental manipulation has the potential to uncover an almost complete picture of the downstream effects caused by the transfected construct. This work describes a simple method for comparing transcriptomes from samples of transfected embryonic spinal cords comprising all steps between electroporation and identification of differentially expressed transcripts. The first stage consists of guidelines for electroporation and instructions for dissection of transfected spinal cord halves from HH23 embryos in ribonuclease-free environment and extraction of high-quality RNA samples suitable for transcriptome sequencing. The next stage is that of bioinformatic analysis with general guidelines for filtering and comparison of RNA-Seq datasets in the Galaxy public server, which eliminates the need of a local computational structure for small to medium scale experiments. The representative results show that the dissection methods generate high quality RNA samples and that the transcriptomes obtained from two control samples are essentially the same, an important requirement for detection of differential expression genes in experimental samples. Furthermore, one example is provided where experimental overexpression of a DNA construct can be visually verified after comparison with control samples. The application of this method may be a powerful tool to facilitate new discoveries on the function of neural factors involved in spinal cord early development.

This video shows the basic steps for performing whole transcriptome analysis on dissected chick embryonic spinal cord samples after transfection with in ovo electroporation.

In ovo electroporation of the chick neural tube is a fast and inexpensive method for identification of gene function during neural development. Genome ...

Neuroscience

Determining Genetic Expression Profiles in C. elegans Using Microarray and Real-time PCR

Synapses are composed of a presynaptic active zone in the signaling cell and a postsynaptic terminal in the target cell. In the case of chemical synapses, messages are carried by neurotransmitters released from presynaptic terminals and received by receptors on postsynaptic cells. Our previous research in Caenorhabditis elegans has shown that VSM-1 negatively regulates exocytosis. Additionally, analysis of synapses in vsm-1 mutants showed that animals lacking a fully functional VSM-1 have increased synaptic connectivity. Based on these preliminary findings, we hypothesized that C. elegans VSM-1 may play a crucial role in synaptogenesis. To test this hypothesis, double-labeled microarray analysis was performed, and gene expression profiles were determined. First, total RNA was isolated, reversely transcribed to cDNA, and hybridized to the DNA microarrays. Then, in-silico analysis of fluorescent probe hybridization revealed significant induction of many genes coding for members of the major sperm protein family (MSP) in mutants with enhanced synaptogenesis. MSPs are the major component of sperm in C. elegans and appear to signal nematode oocyte maturation and ovulation . In fruit flies, Chai and colleagues 1 demonstrated that MSP-like molecules regulate presynaptic bouton number and size at the neuromuscular junction. Moreover, analysis performed by Tsuda and coworkers 2 suggested that MSPs may act as ligands for Eph receptors and trigger receptor tyrosine kinase signaling cascades. Lastly, real time PCR analysis corroborated that the gene coding for MSP-32 is induced in vsm-1(ok1468) mutants. Taken together, research performed by our laboratory has shown that vsm-1 mutants have a significant increase in synaptic density, which could be mediated by MSP-32 signaling.

Determining Genetic Expression Profiles in C. elegans Using Microarray and Real-time PCR

Microarray analysis was conducted to determine genetic expression profiles in C. elegans, and real-time PCR was used to validate and quantify microarray data.

Synapses are composed of a presynaptic active zone in the signaling cell and a postsynaptic terminal in the target cell. In the case of chemical synapses, ...

Biology

Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans

RNA interference is a powerful method to understand gene function, especially when conducted at a whole-genome scale and in a quantitative context. In C. elegans, gene function can be knocked down simply and efficiently by feeding worms with bacteria expressing a dsRNA corresponding to a specific gene 1. While the creation of libraries of RNAi clones covering most of the C. elegans genome 2,3 opened the way for true functional genomic studies (see for example 4-7), most established methods are laborious. Moy and colleagues have developed semi-automated protocols that facilitate genome-wide screens 8. The approach relies on microscopic imaging and image analysis. 
	Here we describe an alternative protocol for a high-throughput genome-wide screen, based on robotic handling of bacterial RNAi clones, quantitative analysis using the COPAS Biosort (Union Biometrica (UBI)), and an integrated software: the MBioLIMS (Laboratory Information Management System from Modul-Bio) a technology that provides increased throughput for data management and sample tracking. The method allows screens to be conducted on solid medium plates. This is particularly important for some studies, such as those addressing host-pathogen interactions in C. elegans, since certain microbes do not efficiently infect worms in liquid culture.
	We show how the method can be used to quantify the importance of genes in anti-fungal innate immunity in C. elegans. In this case, the approach relies on the use of a transgenic strain carrying an epidermal infection-inducible fluorescent reporter gene, with GFP under the control of the promoter of the antimicrobial peptide gene nlp 29 and a red fluorescent reporter that is expressed constitutively in the epidermis. The latter provides an internal control for the functional integrity of the epidermis and nonspecific transgene silencing9. When control worms are infected by the fungus they fluoresce green. Knocking down by RNAi a gene required for nlp 29 expression results in diminished fluorescence after infection. Currently, this protocol allows more than 3,000 RNAi clones to be tested and analyzed per week, opening the possibility of screening the entire genome in less than 2 months.

Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans

We describe a protocol using C. elegans and RNAi feeding libraries that allows automated measurement of multiple parameters such as fluorescence, size and opacity of individual worms in a population. We give one example of a screen to identify genes involved in anti-fungal innate immunity in C. elegans.

RNA interference is a powerful method to understand gene function, especially when conducted at a whole-genome scale and in a quantitative context. In C. ...

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Hematopoietic stem cells (HSCs) are used clinically for transplantation treatment to rebuild a patient&#39;s hematopoietic system in many diseases such as leukemia and lymphoma. Elucidating the mechanisms controlling HSCs self-renewal and differentiation is important for application of HSCs for research and clinical uses. However, it is not possible to obtain large quantity of HSCs due to their inability to proliferate in vitro. To overcome this hurdle, we used a mouse bone marrow derived cell line, the EML (Erythroid, Myeloid, and Lymphocytic) cell line, as a model system for this study.
RNA-sequencing (RNA-Seq) has been increasingly used to replace microarray for gene expression studies. We report here a detailed method of using RNA-Seq technology to investigate the potential key factors in regulation of EML cell self-renewal and differentiation. The protocol provided in this paper is divided into three parts. The first part explains how to culture EML cells and separate Lin-CD34+ and Lin-CD34- cells. The second part of the protocol offers detailed procedures for total RNA preparation and the subsequent library construction for high-throughput sequencing. The last part describes the method for RNA-Seq data analysis and explains how to use the data to identify differentially expressed transcription factors between Lin-CD34+ and Lin-CD34- cells. The most significantly differentially expressed transcription factors were identified to be the potential key regulators controlling EML cell self-renewal and differentiation. In the discussion section of this paper, we highlight the key steps for successful performance of this experiment.
In summary, this paper offers a method of using RNA-Seq technology to identify potential regulators of self-renewal and differentiation in EML cells. The key factors identified are subjected to downstream functional analysis in vitro and in vivo.

RNA-sequencing and bioinformatics analyses were used to identify significantly and differentially expressed transcription factors in Lin-CD34+ and Lin-CD34- subpopulations of mouse EMLcells. These transcription factors might play important roles in determining the switch between self-renewing Lin-CD34+ and partially differentiated Lin-CD34- cells.

Hematopoietic stem cells (HSCs) are used clinically for transplantation treatment to rebuild a patient&#39;s hematopoietic system in many diseases such as ...

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding RNAs. Standard RNAseq requires 30 - 100 million sequencing reads and can include multiple RNA products such as mRNA and noncoding RNAs. We demonstrate how targeted RNAseq (capture) permits a focused study on selected RNA products using a desktop sequencer. RNAseq capture can characterize unannotated, low, or transiently expressed transcripts that may otherwise be missed using traditional RNAseq methods. Here we describe the extraction of RNA from cell lines, ribosomal RNA depletion, cDNA synthesis, preparation of barcoded libraries, hybridization and capture of targeted transcripts and multiplex sequencing on a desktop sequencer. We also outline the computational analysis pipeline, which includes quality control assessment, alignment, fusion detection, gene expression quantification and identification of single nucleotide variants. This assay allows for targeted transcript sequencing to characterize gene expression, gene fusions, and mutations.

We describe a targeted RNA sequencing-based method that includes preparation of indexed cDNA libraries, hybridization and capture with custom probes and data analysis to interrogate selected transcripts for gene expression, mutations, and gene fusions. Targeted RNAseq permits cost-effective, rapid evaluation of selected transcripts on a desktop sequencer.

RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding ...

Combined Nucleotide and Protein Extractions in Caenorhabditis elegans

A single biological sample holds a plethora of information, and it is now common practice to simultaneously investigate several macromolecules to capture a full picture of the multiple levels of molecular processing and changes between different conditions. This protocol presents the method of isolating DNA, RNA, and protein from the same sample of the nematode Caenorhabditis elegans to remove the variation introduced when these biomolecules are isolated from replicates of similarly treated but ultimately different samples. Nucleic acids and protein are extracted from the nematode using the acid guanidinium thiocyanate-phenol-chloroform extraction method, with subsequent precipitation, washing, and solubilization of each. We show the successful isolation of RNA, DNA, and protein from a single sample from three strains of nematode and HeLa cells, with better protein isolation results in adult animals. Additionally, guanidinium thiocyanate-phenol-chloroform-extracted protein from nematodes improves the resolution of larger proteins, with enhanced detectable levels as observed by immunoblotting, compared to the traditional RIPA extraction of protein.
The method presented here is useful when investigating samples using a multiomic approach, specifically for the exploration of the proteome and transcriptome. Techniques that simultaneously assess multiomics are appealing because molecular signaling underlying complex biological phenomena is thought to occur at complementary levels; however, it has become increasingly common to see that changes in mRNA levels do not always reflect the same change in protein levels and that the time of collection is relevant in the context of circadian regulations. This method removes any intersample variation when assaying different contents within the same sample (intrasample.)

Combined Nucleotide and Protein Extractions in Caenorhabditis elegans

Here, we present a protocol for the isolation of RNA, DNA, and protein from the same sample, in an effort to reduce variation, improve reproducibility, and facilitate interpretations.

A single biological sample holds a plethora of information, and it is now common practice to simultaneously investigate several macromolecules to capture ...

Hand Dissection of Caenorhabditis elegans Intestines

Comprised of only 20 cells, the Caenorhabditis elegans intestine&#160;is the nexus of many life-supporting functions, including digestion, metabolism, aging, immunity, and environmental response. Critical interactions between the C. elegans host and its environment converge within the intestine, where gut microbiota concentrate. Therefore, the ability to isolate intestine tissue away from the rest of the worm is necessary to assess intestine-specific processes. This protocol describes a method for hand dissecting adult C. elegans intestines. The procedure can be performed in fluorescently labeled strains for ease or training purposes. Once the technique is perfected, intestines can be collected from unlabeled worms of any genotype. This microdissection approach allows for the simultaneous capture of host intestinal tissue and gut microbiota, a benefit to many microbiome studies. As such, downstream applications for the intestinal preparations generated by this protocol can include but are not limited to RNA isolation from intestinal cells and DNA isolation from captured microbiota. Overall, hand dissection of C. elegans intestines affords a simple and robust method to investigate critical aspects of intestine biology.

Hand Dissection of Caenorhabditis elegans Intestines

The present protocol describes a procedure for isolating intestines from adult Caenorhabditis elegans nematode worms by hand for input in genomics, proteomics, microbiome, or other assays.

Comprised of only 20 cells, the Caenorhabditis elegans intestine&#160;is the nexus of many life-supporting functions, including digestion, metabolism, ...

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

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