Aedes vexans RNA-seq de novo assembly
Hi all,
Does anyone have reccomendations for RNAseq sequencing depth where the transcriptome will require de novo assembly? It would be on the Aedes genome, ive not seen anything catagorical beyond 50-100 million read pairs (100 - 200 million total).
Thanks, Matt
• 1,013 views
•
link
updated
by
Brian Bushnell
•
written
by
fluentin44 •
•
written
by
fluentin44 •
0 answers
No answers yet.
Log in to answer this question.
More posts like this
-
Query regarding genome coverage in de-novo assembly
written by microorganism_001 •
-
Filtering SCRNAseq dataset
written by kanwarjag
-
Coverage Depth Transcriptome Assembly
written by babji2318 •
-
Understanding de-novo transcriptome assembly quality using Transrate
written by nayaraevelin2 •
-
Best statistical validity for RNAseq from FFPE samples at different read lengths
written by achimbell •
-
News: Upcoming Hands-On Workshop: De Novo Transcriptome Assembly and Analysis
written by David Langenberger
-
How compare two de novo assembled transcriptomes of the same sample with different sequencing depth?
written by seta
-
PacBio coverage question for a plant genome
written by arnstrm
-
why there is many broken paired reads in my Illumina reads and how to solve them?
written by seta
-
Depth of RNAseq with sensitive detection
written by sckinta
More would always be better but at some point budget reality will kick in.
Looks like there is already a publication on this topic: https://doi.org/10.1111/1748-5967.12440
The number of read pairs is not the most relevant number; it's the depth that matters. You will be able to assemble most of the genes that are 5x+ and you won't be able to assemble the ones that are under ~2x. So, it depends on the relative expression.
Depending on the organism, artificially depleting certain genes like ribosomes or albumin can be helpful to increase the abundance of informative sequences. I don't have any experience with mosquitoes but albumin is definitely a problem with human RNA-seq, and ribos are a big problem with bacterial RNA-seq. Whenever you want to do an experiment with a minimal amount of sequence, it's useful to artificially deplete sequences you know will be overexpressed ahead of time.