Transcriptome Assembly - De Novo L.staminea Trimmed RNAseq Using Trinity on Mox

2023
Miscellaneous
Author

Sam White

Published

June 16, 2023

As part of this GitHub Issue to create a de novo transcriptome assembly from L.staminea RNA-seq data, I trimmed the reads earlier today. Next up is the actual do novo assembly. I performed this using Trinity on Mox.

SLURM script (GitHub):

#!/bin/bash
## Job Name
#SBATCH --job-name=20230616-lsta-trinity-RNAseq
## Allocation Definition
#SBATCH --account=srlab
#SBATCH --partition=srlab
## Resources
## Nodes
#SBATCH --nodes=1
## Walltime (days-hours:minutes:seconds format)
#SBATCH --time=10-00:00:00
## Memory per node
#SBATCH --mem=500G
##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/20230616-lsta-trinity-RNAseq


### Expects input FastQs to be in following format: *_R[12]_001.fastp-trim.20230616.fastq.gz 


###################################################################################
# These variables need to be set by user

## Assign Variables

# These variables need to be set by user

# RNAseq FastQs directory
reads_dir=/gscratch/scrubbed/samwhite/outputs/20230616-lsta-fastqc-fastp-multiqc-RNAseq/trimmed

# Set FastQ filename patterns
fastq_pattern='*.fastq.gz'
R1_fastq_pattern='*_R1_*.fastq.gz'
R2_fastq_pattern='*_R2_*.fastq.gz'

# Inititalize arrays
# Leave empty!!
R1_array=()
R2_array=()

# Variables for R1/R2 lists
# Leave empty!!!
R1_list=""
R2_list=""



# Create array of fastq R1 files
# Set filename pattern
R1_array=("${reads_dir}"/${R1_fastq_pattern})

# Create array of fastq R2 files
# Set filename pattern
R2_array=("${reads_dir}"/${R2_fastq_pattern})

# Transcriptomes directory
transcriptomes_dir=/gscratch/srlab/sam/data/L_staminea/transcriptomes

# CPU threads
threads=40

# Recommended maximum memory is 100GB, per Trinity developer
max_mem=100G

# Name output files
fasta_name="lsta-de_novo-transcriptome_v1.0.fasta"
assembly_stats="${fasta_name}_assembly_stats.txt"

# Paths to programs
samtools="/gscratch/srlab/programs/samtools-1.10/samtools"
trinity_dir="/gscratch/srlab/programs/trinityrnaseq-v2.12.0"
trinity=${trinity_dir}/Trinity


# Programs associative array
declare -A programs_array
programs_array=(
[samtools_faidx]="${samtools} faidx" \
[samtools_index]="${samtools} index" \
[samtools_sort]="${samtools} sort" \
[samtools_view]="${samtools} view" \
[trinity]="${trinity}"
)

###################################################################################

# Exit script if a command fails
set -e

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



# Create list of fastq files used in analysis
## Uses parameter substitution to strip leading path from filename
for fastq in "${!R1_array[@]}"
do
  {
    md5sum "${R1_array[${fastq}]}"
    md5sum "${R2_array[${fastq}]}"
  } >> input_fastqs.md5
done

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


# Run Trinity
## Running as "stranded" (--SS_lib_type)
${programs_array[trinity]} \
--seqType fq \
--SS_lib_type RF \
--max_memory ${max_mem} \
--CPU ${threads} \
--left "${R1_list}" \
--right "${R2_list}"

# Rename generic assembly FastA
find . -name "Trinity*.fasta" -exec mv {} 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}" \
> "${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}" \
> "${fasta_name}".seq_lens

# Move FastA to working directory
mv trinity_out_dir/"${fasta_name}" .

# Create FastA index
${programs_array[samtools_faidx]} \
"${fasta_name}"

# Copy files to transcriptome directory
mkdir --parents "${transcriptomes_dir}"
rsync -av \
"${fasta_name}"* \
"${transcriptomes_dir}"

# Cleanup
rm -rf trinity_out_dir

# Generate MD5 checksums
for file in *
do
  echo ""
  echo "Generating MD5 checksums for ${file}:"
  md5sum "${file}" | tee --append checksums.md5
  echo ""
done


#######################################################################################################

# Disable exit on error
set +e

# Capture program options
if [[ "${#programs_array[@]}" -gt 0 ]]; then
  echo "Logging program options..."
  for program in "${!programs_array[@]}"
  do
    {
    echo "Program options for ${program}: "
    echo ""
    # Handle samtools help menus
    if [[ "${program}" == "samtools_index" ]] \
    || [[ "${program}" == "samtools_sort" ]] \
    || [[ "${program}" == "samtools_view" ]]
    then
      ${programs_array[$program]}

    # Handle DIAMOND BLAST menu
    elif [[ "${program}" == "diamond" ]]; then
      ${programs_array[$program]} help

    # Handle NCBI BLASTx menu
    elif [[ "${program}" == "blastx" ]]; then
      ${programs_array[$program]} -help

    # Handle fastp menu
    elif [[ "${program}" == "fastp" ]]; then
      ${programs_array[$program]} --help
    fi
    ${programs_array[$program]} -h
    echo ""
    echo ""
    echo "----------------------------------------------"
    echo ""
    echo ""
  } &>> program_options.log || true

    # If MultiQC is in programs_array, copy the config file to this directory.
    if [[ "${program}" == "multiqc" ]]; then
      cp --preserve ~/.multiqc_config.yaml multiqc_config.yaml
    fi
  done
fi


# 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

RESULTS

Run time was ~20hrs:

Screencap of Trinity runtime on Mox showing a run time of 20hrs, 12mins, 57secs

Output folder:

################################
## Counts of transcripts, etc.
################################
Total trinity 'genes':  502826
Total trinity transcripts:  645444
Percent GC: 36.80

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

    Contig N10: 3398
    Contig N20: 2073
    Contig N30: 1301
    Contig N40: 862
    Contig N50: 609

    Median contig length: 319
    Average contig: 516.94
    Total assembled bases: 333658646


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

    Contig N10: 2495
    Contig N20: 1337
    Contig N30: 829
    Contig N40: 588
    Contig N50: 455

    Median contig length: 300
    Average contig: 439.38
    Total assembled bases: 220929754

Well, there are very large numbers of “genes” and transcripts! I’m not sure I’ve seen such high numbers in a transcriptome assembly before. I expect the numbers to be large (100,000 - 300,000 is somewhat normal), but no this large. I’m wondering if this is due to the limited data set used for assembly. The assembly was generated with just one set of paired-end reads. This could lead to a lot of reads that don’t end up aligning with anything. It also increases the likelihood of picking up lots of lowly expressed transcripts which normally are missed when there’s an overwhelming amount of data present for assembly.

I’ll go ahead and run this assembly through Transdecoder to identify open reading frames and try to get a better idea of which contigs are potentially “functional.” Could provide a more “realistic” set of genes for use (in whatever this project is; I haven’t been given much background info on this).