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Related Concept Videos

RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
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Experimental RNAi

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RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
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RACE - Rapid Amplification of cDNA Ends02:35

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Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific...
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Next-generation Sequencing03:00

Next-generation Sequencing

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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Synthetic Biology02:55

Synthetic Biology

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Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
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Related Experiment Video

Updated: Oct 6, 2025

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
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CyVerse for Reproducible Research: RNA-Seq Analysis.

Jason Williams1

  • 1DNA Learning Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. williams@cshl.edu.

Methods in Molecular Biology (Clifton, N.J.)
|January 17, 2022
PubMed
Summary

Cloud cyberinfrastructures address complex research reproducibility challenges. CyVerse offers solutions for data-intensive research, including RNA-Seq analysis, enhancing collaboration and computational power.

Keywords:
Cloud computingContainersCyberinfrastructureData life cycleKallistoMetadataRNA-SeqReproducible researchWorkflow management

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Last Updated: Oct 6, 2025

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Data Science

Background:

  • Reproducibility in data-intensive research faces challenges with long-term data management, secure storage, and collaborative big data sharing across institutions.
  • Complex analyses often exceed individual institutional resources, necessitating cloud and high-performance computing infrastructure.
  • Funder and publisher mandates for data availability, accessibility, and computational reproducibility at publication add further complexity.

Purpose of the Study:

  • To highlight the capabilities of cloud-based cyberinfrastructures, specifically CyVerse, in addressing the reproducibility challenges of data-intensive research.
  • To demonstrate how CyVerse facilitates high-powered analyses, including RNA-Seq data analysis, without requiring command-line expertise.
  • To illustrate how CyVerse infrastructure supports reproducibility through metadata management and containers, team science via data sharing, and flexible computing.

Main Methods:

  • Utilizing the CyVerse cyberinfrastructure to perform RNA-Seq data analysis.
  • Leveraging CyVerse features for metadata management and containerization to ensure reproducibility.
  • Employing CyVerse's data sharing capabilities to facilitate team science.
  • Exploring interactive computing and scaling options within CyVerse for flexible analysis.

Main Results:

  • CyVerse provides solutions for high-powered analyses, including RNA-Seq, that do not require command-line knowledge.
  • The platform supports reproducibility goals through features like metadata management and containers.
  • CyVerse enhances team science with robust data sharing functionalities.
  • Flexible computing environments, including interactive computing and scaling, are readily available.

Conclusions:

  • Cloud-based cyberinfrastructures like CyVerse are crucial for meeting the demands of data-intensive research and ensuring reproducibility.
  • CyVerse offers a user-friendly environment for complex analyses, empowering researchers to overcome resource limitations.
  • The lessons learned from RNA-Seq analysis in CyVerse are transferable to other computing environments, promoting broader adoption of reproducible research practices.