A diamond is merely a lump of coal that did well under pressure.

Project Objective:

Find the orthologs among the 5 species of beetles and annotate the orthologs.

Project Workflow:

  • Step 1: Construct a de novo transcriptome assembly.
    a. Run Trinity to construct a primary assembly.
    b. Run BUSCO to check the quality of the assembly. Use BUSCO.
  • Step 2: Identify the coding regions.
    a. Using the transcriptome from the previous step, run LongOrfs with threshold set to at least 200 aa length for each ORF. Use TransDecoder.LongOrfs with -m 200 flag.
    b. Using the cds file, predict the protein sequences for single best ORF for gene. Use TransDecoder.Predict with --single_best_only flag. 
      TransDecoder.Predict -t [name_of_the_transcriptome.fasta] --single_best_only -O [output_directory_from_TransDecoder.LongOrfs]

    c. Run BUSCO to check the quality of the filtered transcriptome. Use BUSCO.

  • Step 3: Cluster identical sequences together.
    a. Cluster all the amino acid sequences which are 100% identical within the predicted peptide file. Use cd-hit with -c 1.0 flag.
    b. Run BUSCO to check the quality of the filtered transcriptome. Use BUSCO.
  • Step 4: Find the Orthologs among 5 species.
    a. Run all vs all BLAST among 5 species. Use makeblastdb and blastp
    b. Pick the reciprocal Best BLAST hit (RBBH). Write a python script.
    c. Run a 5 way script to pull out the orthologs among 5 species. Write a python script.
  • Step 5: Add annotation to the orthologs.
    a. Using T_cas ids and T_cas reference gff files, add chromosome id (for example: LGX, LG2 etc.),chromosome name (Autosome/ Sex chromosome). Write python script. 
      # Get the gff file.
  wget ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/002/335/GCF_000002335.3_Tcas5.2/GCF_000002335.3_Tcas5.2_genomic.gff.gz
  # Uncompress the file.
  gzip -d GCF_000002335.3_Tcas5.2_genomic.gff.gz

Helpful Hints:

  • To use BUSCO, the first step is to get the lineage and then busco can be run as follows.

      # Get the lineage
  wget https://busco.ezlab.org/datasets/endopterygota_odb9.tar.gz
  # Uncompress the directory.
  tar xvf endopterygota_odb9.tar.gz --gunzip
  # Activate busco environment
  conda activate busco
  # Run BUSCO
  run_busco --in transcriptome.fasta --out [output_directory_name] -l [path_to_]endopterygota_odb9 -m tran -c 48
  • TransDecoder has two programs. These two programs can be run as follows. 
      # To run LongOrfs with minimum ORF length as 100 amino acids.
  TransDecoder.LongOrfs -t target_transcripts.fasta -m 100
  # To run Predict
  TransDecoder.Predict -t target_transcripts.fasta --single_best_only -O [output_directory_from_TransDecoder.LongOrfs]
  • cd-hit can be run as follows. 
      cd-hit -i cds_file -o nr100_cds_file -c 1.00

Reference:

De novo transcriptome assembly, annotation and comparison of four ecological and evolutionary model salmonid fish species. - PDF