Hi friends,
I used KAAS for KEGG annotation of a de novo assembled transcriptome from a non-model plant. I selected just available plant species in the organism list and bi-directional best hit (BBH) method for KO assignment. But, I surprised with the results since some of uncommon pathway like those involved in the Huntington's disease, Alzheimer's disease, etc. represented with about many hits, and there was not any represented pathway specific to my experimental condition. The results scared me about the quality of transcriptome assembly. Could you please let me know how I can explain these results? Actually this assembly was made on about 340 million PE, 100bp reads, is it possible just highly abundant transcripts (that have universal function) represented in the my assembly due to high coverage?
Sharing your experience with me is really kind of you.
Similar thing happened to us, with our data as well. We work on fish species, but we see some weird pathways like cancer etc. Do not know what the reason might be. Would like to hear from an expert in the forum.