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How to annotate eukaryotic genome

I have a fragmented eukaryotic genome (contigs in fasta format) I would like to annotate (and create a genbank file for if possible). I found The NCBI Eukaryotic Genome Annotation Pipeline page on NCBI, but incredibly I see no information on how to actually run something through that pipeline (I assume I would need to submit the assembly to the database), and it seems like my genome may be too fragmented given their criteria for annotation anyway.

That being said, Are there any command-line tools that will do this for me or another pipeline I might use for this purpose?

assembly genome

You need to contact NCBI by using Request Annotation button/option at top of the page. It is kind of obscure. Once you put a ticket in (the link redirects you to create a ticket) someone from NCBI will get in touch with you to see what your options are.

Here are some of your other options: Annotation pipelines in 2018

2 answers

Hello,

We have developed a gene annotator called FINDER which can annotate eukaryotic genomes using short-read RNA-Seq reads and protein sequences. It is completely automated and requires no manual intervention. FINDER also runs BRAKER to incorporate predicted genes in the repertoire. You can access the paper from FINDER and the software from here GitHub.

Thank you.

The easiest way is to use MOSGA, a freely modern and easy-to-use eukaryotic genome annotation tool. It runs online (or you can set it up manually or as a Docker container) with no need for command-line tools: https://mosga.mathematik.uni-marburg.de

Gene predictions can be performed via ab initio, RNA-Seq or proteins, or orthology-based evidence.

Otherwise, you can check:

  • Yandell, M., & Ence, D. (2012). A beginner’s guide to eukaryotic genome annotation. Nature Reviews Genetics, 13(5), 329–342. https://doi.org/10.1038/nrg3174
  • Jung, H., Ventura, T., Chung, J. S., Kim, W.-J., Nam, B.-H., Kong, H. J., Kim, Y.-O., Jeon, M.-S., & Eyun, S. (2020). Twelve quick steps for genome assembly and annotation in the classroom. PLOS Computational Biology, 16(11), e1008325. https://doi.org/10.1371/journal.pcbi.1008325

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