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This tutorial is for using Kallisto  and Sleuth RNA seq tool in DE

Table of Contents

 

New RNA-seq tuxedo protocol using the Discovery Environment

Rational and background

RNA-seq involves preparing the mRNA which is converted to cDNA and provided as input to next generation sequencing library preparation method. Prior to RNA-seq there were hybridization based microarrays used for gene expression studies, the main drawback was the poor quantification of lowly and highly expressed genes.  RNA-seq provides distinct advantages over microarrays, it provides better insights into alternative gene splicing, post-transcriptional modifications, gene fusion and deferentially expressed genes and thus helping to understanding the gene structure and expression patterns of genes across different samples, treatment conditions and time points. The ease of sequencing and the low cost have made  RNA-seq a workhorse in transcriptomic studies and viable option even for small scale labs. But the main challenge remains in analyzing the sequenced data.

The current ecosystems of RNA-seq tools provide a varied ways of analyzing RNA-seq data. Depending on the experiment goal one could align the reads to reference genome or pseduoalign to transcriptome and perform quantification and differential expression of genes or if you want to annotate your reference, assemble RNA-seq reads using a denvo transcriptome assembler. Here we focus on workflows that pseudo align reads to reference transcriptome.  The most commonly cited and widely used quantification workflow is Kallisto and Sleuth.

Tip
Nicolas L Bray, Harold Pimentel, Páll Melsted and Lior Pachter, Near-optimal probabilistic RNA-seq quantification, Nature Biotechnology 34, 525–527 (2016), doi:10.1038/nbt.3519

 
In this example we will compare gene transcript abundance drought sensitive sorghum line under drought stress(DS) and well-watered (WW) condition. The expression of drought-related genes was more abundant in the drought sensitive genotype under DS condition compared to WW.

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If you do not have an account, please see one of the on-site CyVerse staff for a temporary account.

Specific Objectives

By the end of this module, you should

  1. Be more familiar with the DE user interface
  2. Understand the starting data for RNA-seq analysis
  3. Be able to pseduo align short sequence reads and quantify reference transcripts in the DE
  4. Be able to analyze differential gene expression in the DE and Atmosphere

Note on Staged Data:

Several of the methods in this tutorial can take 2 to 4 hrs to complete on a full-sized data set. So that you can complete the tutorial in the allotted time, we have pre-staged input and output files in the 'Community Data' folder for each step. You can start your analyses then skip to the next step using pre-staged data.

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Alessandra Fracasso,  Luisa M. Trindade and Stefano Amaducci; DOI: 10.1186/s12870-016-0800-x, May 2016

The Staged  Data can be found in the

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No Format
Community Data -> iplantcollaborative -> example_data -> Kallisto_Sleuth

 

 

 

Kallisto and Sleuth RNA seq analysis

The kallisto-sleuth pipeline is quite simple. There are basically two steps:

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Here we are doing a pairwise comparison for differential expression in sensitive genotype(IS20351) under Drought Stress(DS) and Well Watered(WW) condition. We have 3 replicates under each condition


Section 1: Connect to an instance of an Atmosphere Image and launch a instance

 

1. Go to https://atmo.cyverse.org/ and log in with IPLANT TEST USER CREDENTIALS.

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4. Once the instance is active, you will get a email confirmation and can also see  the status active on the Atmosphere portal


5. Copy the IP address "128.196.64.125", if you are using MAC or Ubuntu open a terminal window and paste the IP address on the command line using your Cyverse user name and hit enter. This will ask you your Cyverse user account passowrd, hit enter
Note- After entering the password if its ask you to add your IP address to the config, enter yes.

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kapeelc@vm64-125:~/sleuth_analysis$ ls -lh
total 8.0K
-rw-r--r-- 1 kapeelc iplant-everyone  138 Jul 10 20:45 design_matrix
drwxr-x--- 8 kapeelc iplant-everyone 4.0K Jul 10 20:44 kallisto_qaunt_output

 

Section 2: Using R studio on atmosphere to do the interactive analysis using Sleuth R package

  1.  On the command line type below three commands to start a Rstudio and enter your Cyverse password. This will install all the dependencies needed to start Rstudio.

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