Single and double mutant DEG analysis using DESeq2
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Cloud • 0
@cloud-14623
Last seen 6.3 years ago

Hi,

I have don't have much experience, but I was asked to analyze a one-off RNA-seq experiment. The experimental design is as follows:

> coldata
     Condition       Genotype Batch
DMU1 Untreated  Double mutant     2
DMU2 Untreated  Double mutant     2
DMT1   Treated  Double mutant     2
DMT2   Treated  Double mutant     2
WTU1 Untreated       Wildtype     1
WTU2 Untreated       Wildtype     1
M1U1 Untreated        mutant1     1
M1U2 Untreated        mutant1     1
M2U1 Untreated        mutant2     1
M2U2 Untreated        mutant2     1
M1T1   Treated        mutant1     1
M1T2   Treated        mutant1     1
WTT1   Treated       Wildtype     1
WTT2   Treated       Wildtype     1
M2T1   Treated        mutant2     1
M2T2   Treated        mutant2     1

Basically, there are four genotypes: WT, mutant 1, mutant 2, and double mutant (mutant 1 + mutant 2); and two conditions (Treated, Untreated). Double mutant samples (batch 2), were collected at the same time as the batch 1. However, batch1 and batch2 samples were sent to different companies at different times with different platforms (BGI-seq vs illumina) to sequence. The two batches were also sequenced differently: batch 1 was single end 50bp reads, whereas batch 2 was paired-end reads, 150bp. Because of the differences, I expected a batch effect,

From the literature and analyzing batch 1 samples alone using DESeq2, expression of many genes are induced after treatment in WT. These genes are not as highly induced in the two mutants (mutant1/mutant2 affected genes). The affected genes in mutant 1 and mutant 2 largely overlap, but not completely. The major questions we want to answer are as follows: (1) are the induced genes in WT after treatment still induced in the double mutant after treatment? (2) Are the genes that are still induced in the single mutants still induced in the double mutant? I think both these questions require comparison between the samples from different batches. However, from reading other posts (Correcting for Batch Effects Prior to Differential Gene Expression Analysis with limma), the DESeq2 vignette section on this, and from trying it myself using DESeq2 (trying to add batch to the design to account for the batch effect resulting in a "Model matrix not full rank" error), I'm not sure I can separate the batch effect from the condition/genotype effect of the double mutant samples since there wasn't WT controls included in batch 2. I was wondering if there's any way I can salvage anything from the double mutant data in my case to answer the questions above? Thanks in advanced for any help!

deseq2 batch effect rnaseq • 967 views
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@mikelove
Last seen 13 hours ago
United States

It's unfortunate that all the double mutant samples were sequenced on a different platform, but the experiment is salvageable from an analysis point of view, you are just limited to comparing the treatment effects across genotype (you can't compare directly untreated or treated samples across genotype, but you can compare the treated vs untreated across genotype).

You would use a design of: ~genotype + genotype:condition

Then you can extract individual condition effects with results() and 'name', or contrast the condition effects across genotype using results() with contrast=list(..., ...).

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I will try the comparisons you suggested. Thanks for your prompt reply and guidance!

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