I ran Trinotate (v3.1.1) on Mox to annotate the P.generosa larvae transcriptome I previously assembled with the HiSeq data from Illumina.
NOTE: I have this mislabelled as “juvenile” in all previous steps!
Trinity:
Transdecoder:
BLASTx:
SBATCH script (GitHub):
#!/bin/bash
## Job Name
#SBATCH --job-name=tate_juvD5
## Allocation Definition
#SBATCH --account=coenv
#SBATCH --partition=coenv
## Resources
## Nodes
#SBATCH --nodes=1
## Walltime (days-hours:minutes:seconds format)
#SBATCH --time=25-00:00:00
## Memory per node
#SBATCH --mem=120G
##turn on e-mail notification
#SBATCH --mail-type=ALL
#SBATCH --mail-user=samwhite@uw.edu
## Specify the working directory for this job
#SBATCH --workdir=/gscratch/scrubbed/samwhite/outputs/20190318_trinotate_geoduck_juvD5_RNAseq
# Load Python Mox module for Python module availability
module load intel-python3_2017
# Document programs in PATH (primarily for program version ID)
date >> system_path.log
echo "" >> system_path.log
echo "System PATH for $SLURM_JOB_ID" >> system_path.log
echo "" >> system_path.log
printf "%0.s-" {1..10} >> system_path.log
echo ${PATH} | tr : \\n >> system_path.log
wd="$(pwd)"
# Paths to input/output files
## Non-working directory locations
blastp_out_dir="/gscratch/scrubbed/samwhite/outputs/20190318_transdecoder_geoduck_juvD5_RNAseq/blastp_out"
blastx_out_dir="/gscratch/scrubbed/samwhite/outputs/20190318_blastx_geoduck_juvD5_RNAseq"
pfam_out_dir="/gscratch/scrubbed/samwhite/outputs/20190318_transdecoder_geoduck_juvD5_RNAseq/pfam_out"
trinity_out_dir="/gscratch/scrubbed/samwhite/outputs/20190215_trinity_geoduck_juvD5_RNAseq/trinity_out_dir"
transdecoder_out_dir="/gscratch/scrubbed/samwhite/outputs/20190318_transdecoder_geoduck_juvD5_RNAseq/Trinity.fasta.transdecoder_dir"
## New folders for working directory
rnammer_out_dir="${wd}/RNAmmer_out"
signalp_out_dir="${wd}/signalp_out"
tmhmm_out_dir="${wd}/tmhmm_out"
blastp_out="${blastp_out_dir}/blastp.outfmt6"
blastx_out="${blastx_out_dir}/blastx.outfmt6"
pfam_out="${pfam_out_dir}/pfam.domtblout"
lORFs_pep="${transdecoder_out_dir}/longest_orfs.pep"
rnammer_out="${rnammer_out_dir}/Trinity.fasta.rnammer.gff"
signalp_out="${signalp_out_dir}/signalp.out"
tmhmm_out="${tmhmm_out_dir}/tmhmm.out"
trinity_fasta="${trinity_out_dir}/Trinity.fasta"
trinity_gene_map="${trinity_out_dir}/Trinity.fasta.gene_trans_map"
trinotate_report="${wd}/trinotate_annotation_report.txt"
# Paths to programs
rnammer_dir="/gscratch/srlab/programs/RNAMMER-1.2"
rnammer="${rnammer_dir}/rnammer"
signalp_dir="/gscratch/srlab/programs/signalp-4.1"
signalp="${signalp_dir}/signalp"
tmhmm_dir="/gscratch/srlab/programs/tmhmm-2.0c/bin"
tmhmm="${tmhmm_dir}/tmhmm"
trinotate_dir="/gscratch/srlab/programs/Trinotate-v3.1.1"
trinotate="${trinotate_dir}/Trinotate"
trinotate_rnammer="${trinotate_dir}/util/rnammer_support/RnammerTranscriptome.pl"
pfam_db="${trinotate_dir}/admin/Pfam-A.hmm"
sp_db="${trinotate_dir}/admin/uniprot_sprot.pep"
trinotate_sqlite_db="Trinotate.sqlite"
# Make output directories
mkdir ${rnammer_out_dir} ${signalp_out_dir} ${tmhmm_out_dir}
# Copy sqlite database template
cp ${trinotate_dir}/admin/Trinotate.sqlite .
# Run signalp
${signalp} \
-f short \
-n ${signalp_out} \
${lORFs_pep}
# Run tmHMM
${tmhmm} \
--short \
< ${lORFs_pep} \
> ${tmhmm_out}
# Run RNAmmer
cd ${rnammer_out_dir}
${trinotate_rnammer} \
--transcriptome ${trinity_fasta} \
--path_to_rnammer ${rnammer}
cd ${wd}
# Run Trinotate
## Load transcripts and coding regions into database
${trinotate} \
${trinotate_sqlite_db} \
init \
--gene_trans_map ${trinity_gene_map} \
--transcript_fasta ${trinity_fasta} \
--transdecoder_pep ${lORFs_pep}
## Load BLAST homologies
${trinotate} \
${trinotate_sqlite_db} \
LOAD_swissprot_blastp \
${blastp_out}
${trinotate} \
${trinotate_sqlite_db} \
LOAD_swissprot_blastx \
${blastx_out}
## Load Pfam
${trinotate} \
${trinotate_sqlite_db} \
LOAD_pfam \
${pfam_out}
## Load transmembrane domains
${trinotate} \
${trinotate_sqlite_db} \
LOAD_tmhmm \
${tmhmm_out}
## Load signal peptides
${trinotate} \
${trinotate_sqlite_db} \
LOAD_signalp \
${signalp_out}
## Load RNAmmer
${trinotate} \
${trinotate_sqlite_db} \
LOAD_rnammer \
${rnammer_out}
## Creat annotation report
${trinotate} \
${trinotate_sqlite_db} \
report \
> ${trinotate_report}
RESULTS
Output folder:
Trinotate Annotation Table (text):
Trinotate SQLlite Database:
The output has the following column headers:
0 #gene_id
1 transcript_id
2 sprot_Top_BLASTX_hit
3 RNAMMER
4 prot_id
5 prot_coords
6 sprot_Top_BLASTP_hit
7 custom_pombe_pep_BLASTX
8 custom_pombe_pep_BLASTP
9 Pfam
10 SignalP
11 TmHMM
12 eggnog
13 Kegg
14 gene_ontology_blast
15 gene_ontology_pfam
16 transcript
17 peptide
and the data are formatted like so:
0 TRINITY_DN179_c0_g1
1 TRINITY_DN179_c0_g1_i1
2 GCS1_SCHPO^GCS1_SCHPO^Q:53-2476,H:1-808^100%ID^E:0^RecName: Full=Probable mannosyl-oligosaccharide glucosidase;^Eukaryota; Fungi; Dikarya; Ascomycota; Taphrinomycotina; Schizosaccharomycetes; Schizosaccharomycetales; Schizosaccharomycetaceae; Schizosaccharomyces
3 .
4 TRINITY_DN179_c0_g1_i1|m.1
5 2-2479[+]
6 GCS1_SCHPO^GCS1_SCHPO^Q:18-825,H:1-808^100%ID^E:0^RecName: Full=Probable mannosyl-oligosaccharide glucosidase;^Eukaryota; Fungi; Dikarya; Ascomycota; Taphrinomycotina; Schizosaccharomycetes; Schizosaccharomycetales; Schizosaccharomycetaceae; Schizosaccharomyces
7 SPAC6G10_09_SPAC6G10_09_I_alpha_glucosidase_I_Gls1_predicte^SPAC6G10_09_SPAC6G10_09_I_alpha_glucosidase_I_Gls1_predicte^Q:53-2476,H:1-808^100%ID^E:0^.^.
8 SPAC6G10_09_SPAC6G10_09_I_alpha_glucosidase_I_Gls1_predicte^SPAC6G10_09_SPAC6G10_09_I_alpha_glucosidase_I_Gls1_predicte^Q:18-825,H:1-808^100%ID^E:0^.^.
9 PF16923.2^Glyco_hydro_63N^Glycosyl hydrolase family 63 N-terminal domain^58-275^E:6.9e-60`PF03200.13^Glyco_hydro_63^Glycosyl hydrolase family 63 C-terminal domain^315-823^E:5.1e-187
10 .
11 .
12 .
13 KEGG:spo:SPAC6G10.09`KO:K01228
14 GO:0005783^cellular_component^endoplasmic reticulum`GO:0005789^cellular_component^endoplasmic reticulum membrane`GO:0016021^cellular_component^integral component of membrane`GO:0004573^molecular_function^mannosyl-oligosaccharide glucosidase activity`GO:0009272^biological_process^fungal-type cell wall biogenesis`GO:0009311^biological_process^oligosaccharide metabolic process`GO:0006487^biological_process^protein N-linked glycosylation
15 .
16 .
17 .
Backticks and carets (^) are used as delimiters for data packed within an individual field, such as separating E-values, percent identity, and taxonomic info for best matches. When there are multiple assignments in a given field, the assignments are separated by (`) and the fields within an assignment are separated by (^).