Answers.Body: <p>BlastX is the last thing I'd use for miRNA. Are you sure you haven't confused this for mRNA (see my response below the line section)? For mRNA you could use Blastx agreed.</p>
  <p>miRNA = microRNA are a class of non-coding RNAs, ncRNA, used to assist the translation process. Thus the purpose of Blastx is to perform a translation of your query sequence against an amino acid database. Hence this could not work for non-coding RNA. Very little work has been done of miRNA in plants, albeit I presume work has been done on model organisms.</p>
  <p>Personally I would consider the Bioconductor packages such as <a href="https://bioconductor.org/packages/release/bioc/html/microRNA.html" rel="nofollow noreferrer">microRNA</a>, <a href="https://www.bioconductor.org/packages/release/bioc/html/miRNApath.html" rel="nofollow noreferrer">miRNApath</a>, or your <a href="https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-022-08558-w" rel="nofollow noreferrer">mirTarRnaSeq</a> which is linking the mRNA to the miRNA. The title of the question would be addressed via mirTarRnaSeq.</p>
  <hr />
  <p>Having read the question again you appear to be using mRNA and mapping these against a plant genome, i.e. not miRNA. It is a bit confusing because mature versus primary &quot;RNAs&quot; does apply to miRNA.
  Anyway if the question is mRNA then BlastX is not the tool I would use, but you can use it, it is really inefficient at this scale of operation however. Others will know mRNA mapping software much better than I for higher eukaryotes. Your data will be sectioned up by introns, lower eukaryotes and bacteria don't have them. Thus tools, which I'd use, such as mmseqs2 and minimap2 are not specialised for a higher eukaryotes for this sort of mapping.</p>
  
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Answers.Text: Thanks for the response, as I understand it right miRNAs don't code for proteins, and my logic was along the same concept; a BLASTx algorithm translates the nucleotide sequence into an amino acid sequence and then looks for protein homologs. This way I could potentially be able to filter out those predicted miRNAs that "actually" are miRNAs (if they don't have BLASTx results).
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Answers.Text: It is much more preferable for accepts (green tick) than notes of thanks. BlastX filtering at best could go badly wrong. You should use established tools for miRNA, which have been rigorously tested, rather than ad hoc solutions. There is a long history of advanced tools in this field.
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Answers.Text: Okay, I consider your suggestion and will look for tools that could serve the purpose I am looking for. Incidentally, I came across two papers that explained how they narrowed down to potential miRNAs from a bunch of predicted candidates using BLASTx (also further testing for the stem-loop structure): https://www.sciencedirect.com/science/article/pii/S2352407316000081 and https://horticultureresearch.net/journal_pdf/Computational%20prediction%20and%20characterization%20of%20miRNA%20from%20coconut%20leaf%20transcriptome.pdf
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Answers.Text: Thanks. The papers you've cited are different - the authors are using BlastN - that makes sense but the algorithm is inefficient. Stem-loops make sense. You're using BlastX ... it's the "X" part that could cause problems not the use of Blast.
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Answers.Text: Okay, if I understood correctly, the authors used BlastN to pull out the miRNA candidates from the species' EST database, using mature miRNAs as a reference. This searched for miRNA homologs in the EST data. In my case, I already have done the prediction using a different algorithm(https://pubmed.ncbi.nlm.nih.gov/33999024/). Next, I am looking forward to a way to find out which among the predicted candidates are "potential" miRNAs. If protein homologs (using BlastX) are detected those 'nt' sequences can be labeled as "not a potential miRNA".
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Answers.Text: Right, the problem is that BlastX could remove valid miRNA. Thats my concern.
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Body: <p>I am doing miRNA annotation of a plant genome. I have two files - one containing all the predicted mature miRNAs and another containing all the predicted primary miRNAs. I want to find out which are actual miRNAs and which aren't. I have decided to perform a BLASTx against the non-redundant protein database and filter out the non-coding sequences.
  Now, I have the following questions:</p>
  <ol>
  <li>Is this the only method I can follow to perform this task?</li>
  <li>What can I provide as my query sequence - mature miRNA or primary miRNA for BLASTx?</li>
  </ol>
  <p>I request experts to go through this question and provide helpful input.</p>
  
Tags: <ngs><gene><sequence-annotation><rna><functional-annotation>
Title: "BLASTx for miRNA Annotation: Mature vs. Primary miRNAs as Query Sequences"
ThreadText: # "BLASTx for miRNA Annotation: Mature vs. Primary miRNAs as Query Sequences"
  
  (Asked by: username_0 on 2024-06-20)
  
  I am doing miRNA annotation of a plant genome. I have two files - one containing all the predicted mature miRNAs and another containing all the predicted primary miRNAs. I want to find out which are actual miRNAs and which aren't. I have decided to perform a BLASTx against the non-redundant protein database and filter out the non-coding sequences.
  Now, I have the following questions:
  
  1. Is this the only method I can follow to perform this task?
  2. What can I provide as my query sequence - mature miRNA or primary miRNA for BLASTx?
  
  I request experts to go through this question and provide helpful input.
  
  **Tags:** ngs, gene, sequence-annotation, rna, functional-annotation
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2024-06-21. Score: 0 | Accepted answer
  
  BlastX is the last thing I'd use for miRNA. Are you sure you haven't confused this for mRNA (see my response below the line section)? For mRNA you could use Blastx agreed.
  
  miRNA = microRNA are a class of non-coding RNAs, ncRNA, used to assist the translation process. Thus the purpose of Blastx is to perform a translation of your query sequence against an amino acid database. Hence this could not work for non-coding RNA. Very little work has been done of miRNA in plants, albeit I presume work has been done on model organisms.
  
  Personally I would consider the Bioconductor packages such as [microRNA](https://bioconductor.org/packages/release/bioc/html/microRNA.html), [miRNApath](https://www.bioconductor.org/packages/release/bioc/html/miRNApath.html), or your [mirTarRnaSeq](https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-022-08558-w) which is linking the mRNA to the miRNA. The title of the question would be addressed via mirTarRnaSeq.
  
  ---
  
  Having read the question again you appear to be using mRNA and mapping these against a plant genome, i.e. not miRNA. It is a bit confusing because mature versus primary "RNAs" does apply to miRNA.
  Anyway if the question is mRNA then BlastX is not the tool I would use, but you can use it, it is really inefficient at this scale of operation however. Others will know mRNA mapping software much better than I for higher eukaryotes. Your data will be sectioned up by introns, lower eukaryotes and bacteria don't have them. Thus tools, which I'd use, such as mmseqs2 and minimap2 are not specialised for a higher eukaryotes for this sort of mapping.
  
  > **Comments:**
  > **username_0**: Thanks for the response, as I understand it right miRNAs don't code for proteins, and my logic was along the same concept; a BLASTx algorithm translates the nucleotide sequence into an amino acid sequence and then looks for protein homologs. This way I could potentially be able to filter out those predicted miRNAs that "actually" are miRNAs (if they don't have BLASTx results).  
  > **username_1**: It is much more preferable for accepts (green tick) than notes of thanks. BlastX filtering at best could go badly wrong. You should use established tools for miRNA, which have been rigorously tested, rather than ad hoc solutions. There is a long history of advanced tools in this field.  
  > **username_0**: Okay, I consider your suggestion and will look for tools that could serve the purpose I am looking for. Incidentally, I came across two papers that explained how they narrowed down to potential miRNAs from a bunch of predicted candidates using BLASTx (also further testing for the stem-loop structure): https://www.sciencedirect.com/science/article/pii/S2352407316000081 and https://horticultureresearch.net/journal_pdf/Computational%20prediction%20and%20characterization%20of%20miRNA%20from%20coconut%20leaf%20transcriptome.pdf  
  > **username_1**: Thanks. The papers you've cited are different - the authors are using BlastN - that makes sense but the algorithm is inefficient. Stem-loops make sense. You're using BlastX ... it's the "X" part that could cause problems not the use of Blast.  
  > **username_0**: Okay, if I understood correctly, the authors used BlastN to pull out the miRNA candidates from the species' EST database, using mature miRNAs as a reference. This searched for miRNA homologs in the EST data. In my case, I already have done the prediction using a different algorithm(https://pubmed.ncbi.nlm.nih.gov/33999024/). Next, I am looking forward to a way to find out which among the predicted candidates are "potential" miRNAs. If protein homologs (using BlastX) are detected those 'nt' sequences can be labeled as "not a potential miRNA".  
  > **username_1**: Right, the problem is that BlastX could remove valid miRNA. Thats my concern.  
  
  ---
  
  