Ran a de novo assembly using the extracted reads classified under Arthropoda from:

The assembly was performed with Trinity on Mox. It’s important to note that this assembly was not performed using the “stranded” option in Trinity. The previous Trinity assembly from 20200122 was performed using the “stranded” setting. The reason for this difference is that the most recent RNAseq libraries from 20200318 were not stranded libraries. As such, I think it might be best to use the “lowest common denominator” approach.

SBATCH script (GitHub):

20200330_cbai_trinity_megan_RNAseq.sh

#!/bin/bash
## Job Name
#SBATCH --job-name=trinity_cbai
## Allocation Definition
#SBATCH --account=srlab
#SBATCH --partition=srlab
## Resources
## Nodes
#SBATCH --nodes=1
## Walltime (days-hours:minutes:seconds format)
#SBATCH --time=6-00:00:00
## 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 --chdir=/gscratch/scrubbed/samwhite/outputs/20200330_cbai_trinity_megan_RNAseq

# Exit script if a command fails
set -e

# Load Python Mox module for Python module availability
module load intel-python3_2017

# Document programs in PATH (primarily for program version ID)
{
date
echo ""
echo "System PATH for $SLURM_JOB_ID"
echo ""
printf "%0.s-" {1..10}
echo "${PATH}" | tr : \\n
} >> system_path.log

# User-defined variables
reads_dir=/gscratch/srlab/sam/data/C_bairdi/RNAseq
transcriptome_dir=/gscratch/srlab/sam/data/C_bairdi/transcriptomes
threads=27
assembly_stats=assembly_stats.txt
timestamp=$(date +%Y%m%d)
fasta_name="${timestamp}.C_bairdi.megan.Trinity.fasta"

# Paths to programs
trinity_dir="/gscratch/srlab/programs/trinityrnaseq-v2.9.0"
samtools="/gscratch/srlab/programs/samtools-1.10/samtools"


## Inititalize arrays
R1_array=()
R2_array=()

# Variables for R1/R2 lists
R1_list=""
R2_list=""

# Create array of fastq R1 files
R1_array=("${reads_dir}"/*_R1.fq)

# Create array of fastq R2 files
R2_array=("${reads_dir}"/*_R2.fq)

# Create list of fastq files used in analysis
## Uses parameter substitution to strip leading path from filename
for fastq in "${reads_dir}"/*.fq
do
  echo "${fastq##*/}" >> fastq.list.txt
done

# Create comma-separated lists of FastQ reads
R1_list=$(echo "${R1_array[@]}" | tr " " ",")
R2_list=$(echo "${R2_array[@]}" | tr " " ",")


# Run Trinity
## Not running as "stranded", due to mix of library types
${trinity_dir}/Trinity \
--seqType fq \
--max_memory 120G \
--CPU ${threads} \
--left "${R1_list}" \
--right "${R2_list}"

# Rename generic assembly FastA
mv trinity_out_dir/Trinity.fasta trinity_out_dir/"${fasta_name}"

# Assembly stats
${trinity_dir}/util/TrinityStats.pl trinity_out_dir/"${fasta_name}" \
> ${assembly_stats}

# Create gene map files
${trinity_dir}/util/support_scripts/get_Trinity_gene_to_trans_map.pl \
trinity_out_dir/"${fasta_name}" \
> trinity_out_dir/"${fasta_name}".gene_trans_map

# Create sequence lengths file (used for differential gene expression)
${trinity_dir}/util/misc/fasta_seq_length.pl \
trinity_out_dir/"${fasta_name}" \
> trinity_out_dir/"${fasta_name}".seq_lens

# Create FastA index
${samtools} faidx \
trinity_out_dir/"${fasta_name}"

# Copy files to transcriptome directory
rsync -av \
trinity_out_dir/"${fasta_name}"* \
${transcriptome_dir}

RESULTS

Took ~4hrs to run:

Output folder:

20200330_cbai_trinity_megan_RNAseq/

Assembly (FastA; 36MB):

20200330_cbai_trinity_megan_RNAseq/trinity_out_dir/20200408.C_bairdi.megan.Trinity.fasta

FastA Index (FAI):

20200330_cbai_trinity_megan_RNAseq/trinity_out_dir/20200408.C_bairdi.megan.Trinity.fasta.fai

Trinity Gene Trans Map (txt):

20200330_cbai_trinity_megan_RNAseq/trinity_out_dir/Trinity.fasta.gene_trans_map

Assembly Stats (txt):

20200330_cbai_trinity_megan_RNAseq/assembly_stats.txt

################################
## Counts of transcripts, etc.
################################
Total trinity 'genes':  24727
Total trinity transcripts:  40435
Percent GC: 53.17

########################################
Stats based on ALL transcript contigs:
########################################

    Contig N10: 3497
    Contig N20: 2502
    Contig N30: 1977
    Contig N40: 1611
    Contig N50: 1322

    Median contig length: 488
    Average contig: 824.28
    Total assembled bases: 33329770


#####################################################
## Stats based on ONLY LONGEST ISOFORM per 'GENE':
#####################################################

    Contig N10: 3196
    Contig N20: 2364
    Contig N30: 1885
    Contig N40: 1534
    Contig N50: 1239

    Median contig length: 403
    Average contig: 741.81
    Total assembled bases: 18342751

When compared to the previous assembly, this certainly has more genes (24,727 vs 12,803), more transcripts (40,435 vs 19,670), and more assembled bases. However, the median length, average length and N50 values are all lower.