HiFi-SR is a Python-based pipeline for the detection of plant mitochondrial structural rearrangements based on the mapping of PacBio high-fidelity (HiFi) reads or Circular Consensus Sequencing (ccs) data, to a reference genome (i.e., the hypothetical master cycle DNA). HiFi-SR also includes useful scripts for organellar genome analyses.
We will continuously make upgrades and modifications to hifisr to enhance its functionality and performance.
The pipeline has been tested on Ubuntu-24.04. It shall work in other Linux operating system, such as CentOS.
# /mnt/software/sys/python/python-3.13.1/bin is your path to the python executable
# /mnt/software/scripts/hifisr in the virtual environment directory
mkdir /mnt/software/scripts/hifisr
/mnt/software/sys/python/python-3.13.1/bin/python3.13 -m venv /mnt/software/scripts/hifisr
source /mnt/software/scripts/hifisr/bin/activatepip install -i https://mirrors.aliyun.com/pypi/simple/ biopython pysam pandas numpy openpyxl xlsxwriter matplotlib polars fastexcelmkdir deps && cd deps
touch soft_paths.txt# Contents of soft_paths.txt: A TAB-delimited File containing software names, and the path to the executable.
# If your have the softwares installed, add them directly to the file.
# Otherwise, you can install new versions of them.
python /mnt/software/scripts/hifisr/bin/python
minimap2 /mnt/software/scripts/hifisr/deps/minimap2-2.28_x64-linux/minimap2
samtools /mnt/software/scripts/hifisr/deps/samtools/samtools-1.21/bin/samtools
seqkit /mnt/software/scripts/hifisr/deps/seqkit
mecat /mnt/software/scripts/hifisr/deps/MECAT2/Linux-amd64/bin/mecat.pl
blastn /mnt/software/scripts/hifisr/deps/ncbi-blast-2.16.0+/bin/blastn
bcftools /mnt/software/scripts/hifisr/deps/bcftools/bcftools-1.21/bin/bcftools
bamtools /mnt/software/scripts/hifisr/deps/bamtools/bamtools-2.5.2/bin/bamtools
meryl /mnt/software/scripts/hifisr/deps/meryl-1.4.1/bin/meryl
winnowmap /mnt/software/scripts/hifisr/deps/Winnowmap-2.03/bin/winnowmap
pigz /mnt/software/scripts/hifisr/deps/pigz/pigz
bandage /mnt/software/scripts/hifisr/deps/Bandage
hifiasm /mnt/software/scripts/hifisr/deps/hifiasm/hifiasmcd /mnt/software/scripts/hifisr/deps
curl -L https://github.com/lh3/minimap2/releases/download/v2.28/minimap2-2.28_x64-linux.tar.bz2 | tar -jxvf -wget -c https://github.com/samtools/samtools/releases/download/1.21/samtools-1.21.tar.bz2
tar -xjf samtools-1.21.tar.bz2
cd samtools-1.21
autoheader
autoconf -Wno-syntax
./configure --prefix=/mnt/software/scripts/hifisr/deps/samtools/samtools-1.21
make -j 20
make install
cd ..
rm -rf samtools-1.21 samtools-1.21.tar.bz2# choose the correct executable for your platform
wget -c http://app.shenwei.me/data/seqkit/seqkit_linux_amd64.tar.gz
tar -zxf seqkit_linux_amd64.tar.gz
rm seqkit_linux_amd64.tar.gz
git clone https://github.com/xiaochuanle/MECAT2.git
cd MECAT2
make -j 20wget -c https://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/ncbi-blast-2.16.0+-x64-linux.tar.gz
tar -zxf ncbi-blast-2.16.0+-x64-linux.tar.gz && rm ncbi-blast-2.16.0+-x64-linux.tar.gzwget -c https://github.com/samtools/bcftools/releases/download/1.21/bcftools-1.21.tar.bz2
tar -xjf bcftools-1.21.tar.bz2
cd bcftools-1.21
./configure --prefix=/mnt/software/scripts/hifisr/deps/bcftools/bcftools-1.21
make -j 20
make install
cd ..
rm -rf bcftools-1.21 bcftools-1.21.tar.bz2wget -c https://github.com/pezmaster31/bamtools/archive/refs/tags/v2.5.2.zip
unzip v2.5.2.zip && rm v2.5.2.zip
cd bamtools-2.5.2
mkdir build && cd build
cmake -DCMAKE_INSTALL_PREFIX=/mnt/software/scripts/hifisr/deps/bamtools/bamtools-2.5.2 ..
make -j 20
make install
cd ../.. && rm -rf bamtools-2.5.2
wget -c https://github.com/marbl/meryl/releases/download/v1.4.1/meryl-1.4.1.Linux-amd64.tar.xz
tar -xJf meryl-1.4.1.Linux-amd64.tar.xz && rm meryl-1.4.1.Linux-amd64.tar.xzwget -c https://github.com/marbl/Winnowmap/archive/refs/tags/v2.03.tar.gz
tar -zxf v2.03.tar.gz && cd Winnowmap-2.03/
make -j 20
cd .. && rm -rf Winnowmap-2.03.tar.gzwget -c https://zlib.net/pigz/pigz.tar.gz
tar -zxf pigz.tar.gz && rm pigz.tar.gz
cd pigz
make -j 20git clone https://github.com/fenderglass/Flye
cd Flye
python setup.py installwget -c https://github.com/rrwick/Bandage/releases/download/v0.8.1/Bandage_Ubuntu_static_v0_8_1.zip
unzip Bandage_Ubuntu_static_v0_8_1.zip && rm Bandage_Ubuntu_static_v0_8_1.zip sample_LastGraphgit clone https://github.com/chhylp123/hifiasm
cd hifiasm && make -j 8pip install hifisr==0.5.0# create your working folder
mkdir -p /mnt/software/scripts/results && cd /mnt/software/scripts/results
# create a folder ref to store the references
mkdir ref && cd ref
# Download the references Col_mito.fa, Col_plastid.fa.
# rotate the reference
python adjust_ref_fasta.py /mnt/software/scripts/hifisr/deps/soft_paths.txt mito Col_mito.fa
python adjust_ref_fasta.py /mnt/software/scripts/hifisr/deps/soft_paths.txt plastid Col_plastid.faAnalysis of an example wild-type Arabidopsis thaliana dataset Col-CEN (ERR6210723, 14.6 Gb, Naish et al., 2021, Science)
# Download the data as Col-CEN.fastq
python get_mtpt_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt ATHiFi001 /mnt/software/scripts/results/mito_rotated_293434.fasta /mnt/software/scripts/results/plastid_rotated_61049.fasta /mnt/software/scripts/results/Col-CEN.fastq 32| All | mitochondria | plastid |
|---|---|---|
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# filter the reads: remove reads shorter than 10 kb
python filt_read_ids.py /mnt/software/scripts/hifisr/deps/soft_paths.txt ATHiFi001 mito_id_length_qual.txt plastid_id_length_qual.txt 10000 0
# random sampling of 4000 reads for mitochondrial and plastid genomes, respectively
python sample_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt ATHiFi001 mito filt_L10K_mito_id_length_qual.txt 4000
python sample_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt ATHiFi001 plastid filt_L10K_plastid_id_length_qual.txt 4000
# Estimation of variant frequencies
python get_variants_in_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt ATHiFi001 mito run_1 /mnt/software/scripts/results/mito_rotated_293434.fasta /mnt/software/scripts/results/ATHiFi001/reads/sample_reads/sample_4000_mito.fastq 32
python get_variants_in_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt ATHiFi001 plastid run_1 /mnt/software/scripts/results/plastid_rotated_61049.fasta /mnt/software/scripts/results/ATHiFi001/reads/sample_reads/sample_4000_plastid.fastq 32| mitochondria | plastid |
|---|---|
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# create your working folder
mkdir -p /mnt/software/scripts/results && cd /mnt/software/scripts/results
# create a folder ref to store the references
mkdir ref && cd ref
# Download the references for mt genome: KF754799.1_mt_5.fasta, KF754800.1_mt_4.fasta, KF754801.1_mt_3.fasta, KF754802.1_mt_2.fasta, KF754803.1_mt_1.fasta.
# Concatenate the files
cat KF754799.1_mt_5.fasta KF754800.1_mt_4.fasta KF754801.1_mt_3.fasta KF754802.1_mt_2.fasta KF754803.1_mt_1.fasta > mt_all.fasta
# Download the references for pt genome: AJ506156.2_pt.fasta
# rotate the pt reference
python adjust_ref_fasta.py /mnt/software/scripts/hifisr/deps/soft_paths.txt plastid AJ506156.2_pt.fastaAnalysis of the Amborella trichopoda dataset (var. Santa Cruz 75) (SRR28888927, 33.1 Gb, Carey et al., 2025, Nature Plants)
# Download the data as SRR28888927.1.fastq.gz
python get_mtpt_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 /mnt/software/scripts/results/mt_all.fasta /mnt/software/scripts/results/AJ506156.2_pt.fasta /mnt/software/scripts/results/SRR28888927.1.fastq.gz 32| All | mitochondria | plastid |
|---|---|---|
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# filter the reads: remove reads shorter than 10 kb
python filt_read_ids.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito_id_length_qual.txt plastid_id_length_qual.txt 10000 0
# random sampling of 10000 reads for mt genome
python sample_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito filt_L10K_mito_id_length_qual.txt 10000
# get the draft assembly
python get_draft_assembly.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito mt_all.fasta sample_10000_mito.fastq 20| MECAT2 + metaFlye | metaFlye |
|---|---|
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Choose the assembly (upper right, metaFlye before repeat resolution, and without running MECAT2) for downstream analysis
# Manually resolve the graph in Bandage, and save the results as draft.fasta
# Split the reads by contig
python get_reads_by_contig.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mt_draft_contigs draft.fasta sample_10000_mito.fastq 32
# Check the correctness of the contigs by calling and calculating variant frequencies
python get_variants_in_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito contig_1 contigs.part_contig_1.fa contig_1.fastq 32
python get_variants_in_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito contig_2 contigs.part_contig_2.fa contig_2.fastq 32
python get_variants_in_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito contig_3 contigs.part_contig_3.fa contig_3.fastq 32
python get_variants_in_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito contig_4 contigs.part_contig_4.fa contig_4.fastq 32
python get_variants_in_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito contig_5 contigs.part_contig_5.fa contig_5.fastq 32
# Manually correct the small errors contig_1, contig_2, contig_3 based on the results# Re-assemble contig_4 separately
python get_draft_assembly.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito contig_4.fastq 32
# Manually resolve the graph in Bandage, and save the results as contig_4_v2.fasta
# Polish the assembly and align it to KF754801.1_mt_3.fasta
python get_polished_assembly.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito KF754801.1_mt_3.fasta contig_4_v2.fasta contig_4.fastq 32
# Check the correctness again
python get_variants_in_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito contig_4_v2 mito_flye_polish_aligned.fasta contig_4.fastq 32| Coverage in Round 1 | Coverage in Round 2 |
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# Re-assemble contig_5 separately
mkdir -p Amborella_1/hifiasm_results && cd Amborella_1/hifiasm_results
/mnt/software/scripts/hifisr/deps/hifiasm/hifiasm -o contig_5_hifiasm -t 32 contig_5.fastq
cd ../..
# Manually resolve the graph in Bandage, and save the results as contig_5_hifiasm_p_ctg.fasta
# Check the structural correctness of contig_5_hifiasm_p_ctg.fasta
python get_variants_in_reads.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito contig_5_hifiasm_p_ctg contig_5_hifiasm_p_ctg.fasta contig_5.fastq 32
# Polish the assembly and align it to KF754799.1_mt_5.fasta, using only the fully-aligned reads
python get_polished_assembly.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito KF754803.1_mt_1.fasta contig_5_hifiasm_p_ctg.fasta FL.fasta 32
# Check the correctness of the polished assembly
python get_polished_assembly.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito contig_5_hifiasm_p_ctg_run_2 mito_flye_polish_aligned.fasta contig_5.fastq 32
# Manually correct the small errors based on the results, and check the correctness again
python get_polished_assembly.py /mnt/software/scripts/hifisr/deps/soft_paths.txt Amborella_1 mito contig_5_hifiasm_p_ctg_run_3 mito_flye_polish_aligned_cor.fasta contig_5.fastq 32| Coverage in Round 1 | Coverage in Round 2 |
|---|---|
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| Coverage in Round 3 | Coverage in Round 4 |
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- Yi Zou, Weidong Zhu, Daniel B. Sloan, Zhiqiang Wu. (2022). Long-read sequencing characterizes mitochondrial and plastid genome variants in Arabidopsis msh1 mutants. The Plant journal 112 (3), 738–755. https://doi.org/10.1111/tpj.15976
- Yi Zou, Weidong Zhu, Yingke Hou, Daniel B. Sloan, Zhiqiang Wu. (2025). The evolutionary dynamics of organellar pan-genomes in Arabidopsis thaliana. bioRxiv 2025.01.20.633836; doi: https://doi.org/10.1101/2025.01.20.633836