Introductory RNA-seq Transcriptome Profiling

Before we start: Align sequence reads to the reference genome The most time-consuming part of the analysis is doing the alignments of the reads (in Sanger fastq format) for all replicates against the reference genome.

Overview: This training module is designed to provide a hands on experience in using RNA-Seq for transcriptome profiling. Question: How well is the annotated transcriptome represented in RNA-seq data in Arabidopsis WT and hy5 genetic backgrounds? How can we compare gene expression levels in the two samples? RNA-seq in the Discovery Environment

Scientific Objective LONG HYPOCOTYL 5 (HY5) is a basic leucine zipper transcription factor (TF). Mutations in the HY5 gene cause aberrant phenotypes in Arabidopsis morphology, pigmentation and hormonal response. We will use RNA-seq to compare the transcriptomes of seedlings from WT and hy5 genetic backgrounds to identify HY5-regulated genes.

Samples Experimental data downloaded from the NCBI Short Read Archive (GEO:GSM and GEO:GSM613466) Two replicates each of RNA-seq runs for Wild- type and hy5 mutant seedlings.

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 align short sequence reads with a reference genome in the DE 4)Be able to analyze differential gene expression in the DE 5)Be able to use DE text manipulation tools to explore the gene expression data

RNA-Seq Conceptual Overview Image source:

RNA-Seq Analysis Workflow Tophat (bowtie) Cufflinks Cuffmerge Cuffdiff CummeRbund Your Data iPlant Data Store FASTQ Discovery Environment

Quick Summary Find Differentially Expressed genes Align to Genome: TopHat View Alignments: IGV Differential Expression: CuffDiff Download Reads from SRA Export Reads to FASTQ

Import SRA data from NCBI SRA Extract FASTQ files from the downloaded SRA archives Pre-Configured: Getting the RNA-seq Data

Examining Data Quality with fastQC

RNA-Seq Workflow Overview

Align the four FASTQ files to Arabidopsis genome using TopHat Step 1: Align Reads to the Genome Built-in ref. genomes User provided ref. genomes A single FASTQ file Folder with >= 1 FASTQ files

TopHat TopHat is one of many applications for aligning short sequence reads to a reference genome. It uses the BOWTIE aligner internally. Other alternatives are BWA, MAQ, OLego, Stampy, Novoalign, etc.

RNA-seq Sample Read Statistics Genome alignments from TopHat were saved as BAM files, the binary version of SAM (samtools.sourceforge.net/). Reads retained by TopHat are shown below Sequence runWT-1WT-2hy5-1hy5-2 Reads10,866,70210,276,26813,410,01112,471,462 Seq. (Mbase)

Index BAM files using SAMtools Prepare BAM files for viewing

Using IGV in Atmosphere 1.We already Launched an instance of NGS Viewers in Atmosphere 2.Use VNClient to connect to your remote desktop

Pre-configured VM for NGS Viewers

The Integrative Genomics Viewer (IGV) is a high-performance visualization tool for interactive exploration of large, integrated genomic datasets. It supports a wide variety of data types, including array-based and next-generation sequence data, and genomic annotations. Use IGV to inspect outputs from TopHat Integrated Genomics Viewer (IGV)

ATG44120 (12S seed storage protein) significantly down-regulated in hy5 mutant Background (> 9-fold p=0). Compare to gene on right lacking differential expression

RNA-Seq Workflow Overview

CuffDiff CuffLinks is a program that assembles aligned RNA-Seq reads into transcripts, estimates their abundances, and tests for differential expression and regulation transcriptome-wide. CuffDiff is a program within CuffLinks that compares transcript abundance between samples

Examining Differential Gene Expression

Examining the Gene Expression Data

Filter CuffDiff results for up or down-regulated gene expression in hy5 seedlings Differentially expressed genes

Example filtered CuffDiff results generated with the Filter_CuffDiff_Results to 1)Select genes with minimum two-fold expression difference 2)Select genes with significant differential expression (q <= 0.05) 3)Add gene descriptions

Coming Soon: Downstream Analysis with cummeRbund

Coming Soon: Support for Paired End Reads and Other Sequencing Platforms ?