WGS and RNA-seq integrated in analysis of expression

[barthez95]

I need to find some publications about an analysis of the diversity of gene expression based on WGS and RNA-Seq.

I would like to sequent the genome and the transtriptome (a sample of liver tissue and muscle tissue) in three individuals of pig. So I will have a 6 samples in RNA-Seq and 3 samples of WGS. I would like to explain differences in expression. Research will be based on WGS and RNA-Seq. Do you know articles about similar issues? Or any other proposition how to use a WGS and RNA-Seq together to do research about expression analysis?

[sdriscoll]

I don't know any articles but it sounds to me like you're going to have to use these steps:
1. use the WGS to assemble the genome
2. align RNA-Seq to the assembled genome using an RNA-Seq aligner like STAR
3. use Stringtie or Cufflinks to estimate transcript models from the aligned reads for each RNA-Seq sample
4. merge the individual transcriptome assemblies with cuffmerge (if you used cufflinks) or Stringtie --merge (if you used stringtie)
5. quantify each RNA-Seq sample's expression against the merged annotation (there are many options for this)
6. Do differential expression testing in R using one of the many programs (DESeq2, edgeR, etc).

Is there a reason why you cannot just align and quantify your RNA-Seq against the current Pig genome and gene annotations (susScr3)? Regardless, as a control I'd recommend doing that first so you can sanity check the de-novo pipeline.