Assembly of substrain H2¶

Preparation of the Nanopore data¶

For substrain H2 we used the trycycler pipeline. In a first step, we downloaded the already published reads for this strain from NCBI...

We then checked the sequencing runs quality using nanoplot version ...:

In [ ]:

NanoPlot --summary sequencing_summary.txt -t 20 -o /path/to/output/directory

According to https://doi.org/10.1371/journal.pcbi.1010905 filtering of the nanopore reads is important. We done this using filtlong version ... (To keep all reads bigger than 6kb and to throw away the 10 % worstest reads of them).

In [ ]:

filtlong --min_length 6000 calls.fastq > reads_qc/ont_6k.fastq
filtlong --keep_percent 90 reads_qc/ont_6k.fastq > reads_qc/ont.fastq

Preparation of the illumina data¶

For the illumina data, we used fastp for filtering:

In [ ]:

fastp --in1 reads_Illumina_1.fastq.gz --in2 reads_Illumina_2.fastq.gz --out1 reads_qc/illumina_1.fastq.gz --out2 reads_qc/illumina_2.fastq.gz --unpaired1 reads_qc/illumina_u.fastq.gz --unpaired2 reads_qc/illumina_u.fastq.gz

Nanopore only assembly using `trycycler`¶

In [ ]:

trycycler subsample --reads reads_qc/ont.fastq --out_dir read_subsets --genome_size 4.5m
threads=16  # change as appropriate for your system
mkdir assemblies

flye --nano-hq read_subsets/sample_01.fastq --threads "$threads" --out-dir assembly_01 && cp assembly_01/assembly.fasta assemblies/assembly_01.fasta && rm -r assembly_01
miniasm_and_minipolish.sh read_subsets/sample_02.fastq "$threads" > assembly_02.gfa && any2fasta assembly_02.gfa > assemblies/assembly_02.fasta && rm assembly_02.gfa
raven --threads "$threads" --disable-checkpoints read_subsets/sample_03.fastq > assemblies/assembly_03.fasta

flye --nano-hq read_subsets/sample_04.fastq --threads "$threads" --out-dir assembly_04 && cp assembly_04/assembly.fasta assemblies/assembly_04.fasta && rm -r assembly_04
miniasm_and_minipolish.sh read_subsets/sample_05.fastq "$threads" > assembly_05.gfa && any2fasta assembly_05.gfa > assemblies/assembly_05.fasta && rm assembly_05.gfa
raven --threads "$threads" --disable-checkpoints read_subsets/sample_06.fastq > assemblies/assembly_06.fasta

flye --nano-hq read_subsets/sample_07.fastq --threads "$threads" --out-dir assembly_07 && cp assembly_07/assembly.fasta assemblies/assembly_07.fasta && rm -r assembly_07
miniasm_and_minipolish.sh read_subsets/sample_08.fastq "$threads" > assembly_08.gfa && any2fasta assembly_08.gfa > assemblies/assembly_08.fasta && rm assembly_08.gfa
raven --threads "$threads" --disable-checkpoints read_subsets/sample_09.fastq > assemblies/assembly_09.fasta

flye --nano-hq read_subsets/sample_10.fastq --threads "$threads" --out-dir assembly_10 && cp assembly_10/assembly.fasta assemblies/assembly_10.fasta && rm -r assembly_10
miniasm_and_minipolish.sh read_subsets/sample_11.fastq "$threads" > assembly_11.gfa && any2fasta assembly_11.gfa > assemblies/assembly_11.fasta && rm assembly_11.gfa
raven --threads "$threads" --disable-checkpoints read_subsets/sample_12.fastq > assemblies/assembly_12.fasta

trycycler cluster --assemblies assemblies/*.fasta --reads reads_qc/ont.fastq --out_dir trycycler

trycycler reconcile --reads reads_qc/ont.fastq --cluster_dir trycycler/cluster_001
trycycler reconcile --reads reads_qc/ont.fastq --cluster_dir trycycler/cluster_002
trycycler reconcile --reads reads_qc/ont.fastq --cluster_dir trycycler/cluster_003
trycycler reconcile --reads reads_qc/ont.fastq --cluster_dir trycycler/cluster_004
trycycler reconcile --reads reads_qc/ont.fastq --cluster_dir trycycler/cluster_005
trycycler reconcile --reads reads_qc/ont.fastq --cluster_dir trycycler/cluster_006

trycycler msa --cluster_dir trycycler/cluster_001
trycycler msa --cluster_dir trycycler/cluster_002
trycycler msa --cluster_dir trycycler/cluster_003
trycycler msa --cluster_dir trycycler/cluster_004
trycycler msa --cluster_dir trycycler/cluster_005
trycycler msa --cluster_dir trycycler/cluster_006

trycycler partition --reads reads_qc/ont.fastq --cluster_dirs trycycler/cluster_*

trycycler consensus --cluster_dir trycycler/cluster_001
trycycler consensus --cluster_dir trycycler/cluster_002
trycycler consensus --cluster_dir trycycler/cluster_003
trycycler consensus --cluster_dir trycycler/cluster_004
trycycler consensus --cluster_dir trycycler/cluster_005
trycycler consensus --cluster_dir trycycler/cluster_006

medaka_consensus -i trycycler/cluster_001/4_reads.fastq -d trycycler/cluster_001/7_final_consensus.fasta -o trycycler/cluster_001/medaka -m r104_e81_sup_g610
mv trycycler/cluster_001/medaka/consensus.fasta trycycler/cluster_001/8_medaka.fasta
rm -r trycycler/cluster_001/medaka trycycler/cluster_001/*.fai trycycler/cluster_001/*.mmi

medaka_consensus -i trycycler/cluster_002/4_reads.fastq -d trycycler/cluster_002/7_final_consensus.fasta -o trycycler/cluster_002/medaka -m r104_e81_sup_g610
mv trycycler/cluster_002/medaka/consensus.fasta trycycler/cluster_002/8_medaka.fasta
rm -r trycycler/cluster_002/medaka trycycler/cluster_002/*.fai trycycler/cluster_002/*.mmi

medaka_consensus -i trycycler/cluster_003/4_reads.fastq -d trycycler/cluster_003/7_final_consensus.fasta -o trycycler/cluster_003/medaka -m r104_e81_sup_g610
mv trycycler/cluster_003/medaka/consensus.fasta trycycler/cluster_003/8_medaka.fasta
rm -r trycycler/cluster_003/medaka trycycler/cluster_003/*.fai trycycler/cluster_003/*.mmi

medaka_consensus -i trycycler/cluster_004/4_reads.fastq -d trycycler/cluster_004/7_final_consensus.fasta -o trycycler/cluster_004/medaka -m r104_e81_sup_g610
mv trycycler/cluster_004/medaka/consensus.fasta trycycler/cluster_004/8_medaka.fasta
rm -r trycycler/cluster_004/medaka trycycler/cluster_004/*.fai trycycler/cluster_004/*.mmi

medaka_consensus -i trycycler/cluster_005/4_reads.fastq -d trycycler/cluster_005/7_final_consensus.fasta -o trycycler/cluster_005/medaka -m r104_e81_sup_g610
mv trycycler/cluster_005/medaka/consensus.fasta trycycler/cluster_005/8_medaka.fasta
rm -r trycycler/cluster_005/medaka trycycler/cluster_005/*.fai trycycler/cluster_005/*.mmi

medaka_consensus -i trycycler/cluster_006/4_reads.fastq -d trycycler/cluster_006/7_final_consensus.fasta -o trycycler/cluster_006/medaka -m r104_e81_sup_g610
mv trycycler/cluster_006/medaka/consensus.fasta trycycler/cluster_006/8_medaka.fasta
rm -r trycycler/cluster_006/medaka trycycler/cluster_006/*.fai trycycler/cluster_006/*.mmi

cat trycycler/cluster_*/8_medaka.fasta > trycycler_medaka.fasta

Filtering using `polypolish`¶

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threads=16
bwa index trycycler_medaka.fasta
bwa mem -t "$threads" -a trycycler_medaka.fasta reads_qc/illumina_1.fastq.gz > alignments_1.sam
bwa mem -t "$threads" -a trycycler_medaka.fasta reads_qc/illumina_2.fastq.gz > alignments_2.sam

polypolish filter --in1 alignments_1.sam --in2 alignments_2.sam --out1 filtered_1.sam --out2 filtered_2.sam

polypolish polish trycycler_medaka.fasta filtered_1.sam filtered_2.sam > trycycler_medaka_polypolish.fasta
rm *.bwt *.pac *.ann *.amb *.sa *.sam

Adjust start points of the assembly to dnaA or repA using `dnaapler`¶

In [ ]:

dnaapler all -i trycycler_medaka_polypolish.fasta -o output_directory_path -p r_sphaeroides -t 20

Assembly of strain DSM158¶

Preparation of the input data¶

For strain DSM158 we used the autocycler pipeline. In a first step, we performed basecalling and trimming using dorado version ... with the following parameters to get the fastq files:

In [ ]:

dorado basecaller sup --emit-fastq pod5s > calls.fastq

QC check of the reads were performed in the same way, as described above (nanoplot and filtlong for the nanopore data and fastqc and fastp for the illumina data).

Fully automated assembly using autocycler¶

In [ ]:

reads=ont.fastq.gz  # your read set goes here
threads=20  # set as appropriate for your system (no more than 128)
genome_size=$(autocycler helper genome_size --reads "$reads" --threads "$threads")  # can set this manually if you know the value

# Step 1: subsample the long-read set into multiple files
autocycler subsample --reads "$reads" --out_dir subsampled_reads --genome_size "$genome_size"

# Step 2: assemble each subsampled file
mkdir assemblies
for assembler in canu flye metamdbg miniasm necat nextdenovo plassembler raven; do
    for i in 01 02 03 04; do
        autocycler helper "$assembler" --reads subsampled_reads/sample_"$i".fastq --out_prefix assemblies/"$assembler"_"$i" --threads "$threads" --genome_size "$genome_size"
    done
done

# Optional step: remove the subsampled reads to save space
rm subsampled_reads/*.fastq

# Step 3: compress the input assemblies into a unitig graph
autocycler compress -i assemblies -a autocycler_out

# Step 4: cluster the input contigs into putative genomic sequences
autocycler cluster -a autocycler_out

# Steps 5 and 6: trim and resolve each QC-pass cluster
for c in autocycler_out/clustering/qc_pass/cluster_*; do
    autocycler trim -c "$c"
    autocycler resolve -c "$c"
done

# Step 7: combine resolved clusters into a final assembly
autocycler combine -a autocycler_out -i autocycler_out/clustering/qc_pass/cluster_*/5_final.gfa

autocycler gfa2fasta -i autocycler_out/clustering/qc_pass/cluster_*/5_final.gfa -o autocycler_out/final/autocycler.fasta

Short read polishing using `pypolca` and `polypolish`¶

In [ ]:

pypolca run -a autocycler_out/final/autocycler.fasta -1 reads_qc/illumina_1.fastq.gz -2 reads_qc/illumina_2.fastq.gz -t 20 -o autocycler_out/final/autocycler_pypolca.fasta

bwa index autocycler_out/final/autocycler_pypolca.fasta
bwa mem -t 16 -a autocycler_out/final/autocycler_pypolca.fasta reads_qc/illumina_1.fastq.gz > alignments_1.sam
bwa mem -t 16 -a autocycler_out/final/autocycler_pypolca.fasta reads_qc/illumina_2.fastq.gz > alignments_2.sam
polypolish filter --in1 alignments_1.sam --in2 alignments_2.sam --out1 filtered_1.sam --out2 filtered_2.sam
polypolish polish autocycler_out/final/autocycler_pypolca.fasta  filtered_1.sam filtered_2.sam > autocycler_out/final/autocycler_pypolca_polypolish.fasta 
rm *.amb *.ann *.bwt *.pac *.sa *.sam

Adjust the starting point to dnaA or repA of each contig using `dnaapler`¶

In [ ]:

dnaapler all -i autocycler_out/final/autocycler_pypolca_polypolish.fasta -o output_directory_path -p r_sphaeroides -t 20

Assembly of substrain H2¶

Preparation of the Nanopore data¶

Preparation of the illumina data¶

Nanopore only assembly using trycycler¶

Filtering using polypolish¶

Adjust start points of the assembly to dnaA or repA using dnaapler¶

Assembly of strain DSM158¶

Preparation of the input data¶

Fully automated assembly using autocycler¶

Short read polishing using pypolca and polypolish¶

Adjust the starting point to dnaA or repA of each contig using dnaapler¶

Nanopore only assembly using `trycycler`¶

Filtering using `polypolish`¶

Adjust start points of the assembly to dnaA or repA using `dnaapler`¶

Short read polishing using `pypolca` and `polypolish`¶

Adjust the starting point to dnaA or repA of each contig using `dnaapler`¶