Journal club: uORFs, eukaryotic "operon"?
Paper: Small open reading frames associated with morphogenesis are hidden in plant genomes. (Hanada et al 2013).
Overall, I liked the paper. It was the first time I had been made aware of the abundance of un-annotated small open reading frames, and I think it adds awareness in the field to something new, a method of detection, and an example of its applications.
Comment 1: Their investigation of expression of both RNA and protein reminded me that we often make assumptions about the relationships between transcript abundance and protein abundance; even if we detect translation, it doesn't guarantee that the we can detect transcription accumulating, and vice versa.
Comment 2: I had never heard of upstream ORFs; they sound conceptually similar to operons/polycistronic DNA found in prokaryotes, so I thought it was interesting that they exist in a eukaryotic system.
Comment 3: The paper described some techniques (controls) that I had never heard of before that I thought were interesting and useful. For example, determining the null distribution of the Ka/Ks ratio with random sequences to obtain a neutrality baseline to identify sORFs under selection was a new idea to me.
Comment/Question 4: What tissue types were used for the 17 different environmental conditions? They refer to seedling, but what tissue on the seedling?
Comment 5: They made a mention that other organisms such as humans contain sORFs, and specifically they reference the ENCODE project. I was wondering what ENCODE used to identify these sORFs; was it a similar algorithm, and if not, maybe it could be used to identify more un-annotated genes?
Comment 6: I'm a bit skeptical of their claim that their prediction algorithm has the best performance of identifying small ORFs. I agree that it performed well and was able to identify a significant number of previously un-annotated genes, however their training set to obtain their a prior hexamer composition bias was done in the same organism, Arabidopsis, that they go on to test in. I question whether it would perform as well in other organisms.
Overall, I liked the paper. It was the first time I had been made aware of the abundance of un-annotated small open reading frames, and I think it adds awareness in the field to something new, a method of detection, and an example of its applications.
Comment 1: Their investigation of expression of both RNA and protein reminded me that we often make assumptions about the relationships between transcript abundance and protein abundance; even if we detect translation, it doesn't guarantee that the we can detect transcription accumulating, and vice versa.
Comment 2: I had never heard of upstream ORFs; they sound conceptually similar to operons/polycistronic DNA found in prokaryotes, so I thought it was interesting that they exist in a eukaryotic system.
Comment 3: The paper described some techniques (controls) that I had never heard of before that I thought were interesting and useful. For example, determining the null distribution of the Ka/Ks ratio with random sequences to obtain a neutrality baseline to identify sORFs under selection was a new idea to me.
Comment/Question 4: What tissue types were used for the 17 different environmental conditions? They refer to seedling, but what tissue on the seedling?
Comment 5: They made a mention that other organisms such as humans contain sORFs, and specifically they reference the ENCODE project. I was wondering what ENCODE used to identify these sORFs; was it a similar algorithm, and if not, maybe it could be used to identify more un-annotated genes?
Comment 6: I'm a bit skeptical of their claim that their prediction algorithm has the best performance of identifying small ORFs. I agree that it performed well and was able to identify a significant number of previously un-annotated genes, however their training set to obtain their a prior hexamer composition bias was done in the same organism, Arabidopsis, that they go on to test in. I question whether it would perform as well in other organisms.
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