After starting to work a little while ago with RNA in prokaryotes in order to perform RNA-Seq analysis, I finally arrived to the moment of the bioinformatic analysis of the obtained reads.
I prepared the cDNA library by following a modified TruSeq protocol for Illumina and the quality of the preparation by analysis using DNA High Sensitivity chip in Bioanalyzer was very good.
After sequencing reaction, I used CLC Genomics Workbench to perform the RNA-Seq analysis. First of all, I run the tool for checking the quality of the reads, and the sequencing reaction seemed to be almost perfect, so I was very happy. But when running the RNA-Seq Analysis tool included in the software (using default parameters) it happens that more than 60% of the reads doesn't match with my reference genome.
I have to say that as reference genome I use a multifasta file containing the list of all CDS, but not the assemble annotated genome.
I was wondering why just 30% of the reads are mapped during the analysis. Now I think that it might be due to the use of a CDS list. That would make all reads falling in between two CDS or intergenic regions will not be mapped. Am I right? Have any of you any other suggestion?
Thank you very much in advance.
If you have a reference genome, don't even doubt on using it to map your reads. The assembly will be faster and more accurate than performing a de-novo assembly.
I am not sure on how the CLC GW works on using a CDS list file, but you are right in statting that the intergenic regions and some other reads will be lost, though 60% of unmapped reads a surprisingly high proportion.
So, if you are in position to use a reference genome, go for it.
If you don't, then I'd suggest a de-novo asembly and then extract and reassembly the reads that can't be mapped to any contig by using your CDS list file.
Also, check the default settings of the CLC and make sure they work for you. Adjust k-length/word size and bubble size to your needs.
And last, but not least, try contacting the CLC support team. They have a great customer service and might provide a more insightful answer if you let them know the output of your analysis and the parameters you used at it.
Thank Gustavo for your answer…, but I do actually use a reference genome…. The mapping results using the reference genome (.gb file) or the multicast file containing only genomic regions (.txt) are very similar.
I assume that the unmapped reads correspond to some extent to adaptors and intergenic regions, as well to a bit of just junk reads. I also learn that the RNA polymerase use in this case, for RNA-Seq, is not that accurate as the one used for Genome sequencing, so taking into account the amount of SNPs generated it might lead to a high number of unmapped reads. But the highest contribution to this %, about 20% correspond to reads that map against rRNA and tRNA…, almost 19.9% against 5S rRNA. That is logical due to the fact that I use the RiboZero kit to clean my total RNA extractions, that is not able to get rid of the 5S rRNA.
Any way, I'm now checking different parameters in the bioinformatic analysis to see if this mapping may be improved.
Gracias!!
I did most of this manually on our linux clusters, using fastQC, bowtie2 etc. One thing I did to check my sequencing wasn't contaminated by mammalian material was to blast a small portion of reads and check whether they match what I expected.
- Badges
- Science topic
- Similar topics
- Biological Science
- Molecular Biology
- Biomolecules
- Nucleic Acids
- RNA