I am currently working on a RNAseq data set from 2 conditions in 1 species. For this species the genome is nice (I have full chromosomes) and well annotated. I used the
New tuxedo pipeline to analyse my results. This worked very well.
I now retrieved some RNAseq data from a very close species with the same 2 conditions. I would like to perform the same analysis on this species and find some up-regulated genes in the first species that are down-regulated in the other species for example. But in this species, the genome is quite bad compared to the first one (400 000 scaffolds).
I though about different ways of doing it:
New tuxedopipeline again using the "bad" genome and then figuring out which gene corresponds to which gene in the first species.
Using directly the genome of the first species for the second species (Ok it is different but at least it is good).
Using the transcripts I assembled in the first species to quantify their expression with the reads of the second species (i.e. not using the
I don't know which solution would be better, if you have any ideas, thanks!
The overall alignement rate for the "good" genome RNAseq vs "good" genome:
Overall alignment rate for the "bad" genome RNAseq vs the "good" genome :
Overall alignment rate for the "bad" genome RNAseq vs the "bad" genome :