MitoSIS (Mitochondrial Species Identification System) is a wrapper for mitochondrial genome assembly and identification of sample contamination or mislabeling. Specifically, MitoSIS maps raw or trimmed reads to a database of reference mitochondrial sequences. It calculates the percentage of reads that map to different species using Kallisto to assess potential sample contamination. It then uses MITGARD to assemble and MitoZ annotate the full mitochondrial genome. It then BLASTs the resulting mitogenome or barcoding genes (e.g., CYTB, COX1, ND4, 16S, etc.) to check for sample mislabeling. Finally, MitoSIS uses a MAFFT and IQ-TREE to calculate phylogenetic distance to closely related species.
- Map fastq reads to reference fasta using
kallisto- Calculate total reads/tpm for each species in database
- Identify the best reference sequence
- Assemble the mitogenome using
MITGARD - Annotate mitogenome using
MitoZ- Extract protein coding/barcoding genes
- Blast mitogenome or genes to reference database
- Calculate mean percent identity for each species
- Align sequences and build phylogeny
- Calculate mean/minimum phylogenetic distance for each species
| flag | description |
|---|---|
| -h, --help | Show this help message and exit. |
| -f1, --fastq1 | fastq read pair 1 (forward). Default: None |
| -f2, --fastq2 | fastq read pair 2 (reverse). Default: None |
| -s, --single | single-end fastq. Default: None |
| -r, --reference | genbank OR fasta+sp database Default: None See section below on fasta & custom databases Recommend downloading all mitochondrial data for your clade of interest e.g., snakes; Genbank Example Send to > Complete Record > Genbank |
| -o, --output | Prefix for output files. Default: 'ZZZ' |
| -c, --cpu | Number of threads to be used in each step. Default: 8 |
| -M, --memory | Max memory for Trinity (see Trinity for format). Default: '30G' |
| --clade | Clade used for MitoZ. Options: 'Chordata' or 'Arthropoda'. Default: 'Chordata' |
| --convert | Only perform Genbank to Fasta conversion and create a tab-delimited taxa id file |
| --version | Show program's version number and exit |
The user can download nucleotide sequences from the taxonomic group of interest from the database of NCBI. For instance, the user can search for "snakes[porgn]AND mitochondrion[filter]" and send all complete records to a Genbank formatted file. Then the GenBank fromat file is used as input in the option -r to be used as reference in MitoSIS pipeline.
The GenBank format file is converted into two files to generate a fasta+sp database, which is used in all steps of MitoSIS workflow. To improve the reference database by adding custom/private sequences, see the section below.
Fasta reference databases must be accompanied by a tab-delimited taxa id (.sp) file. We refer to this combination of files as a fasta+sp database. The tab-delimited taxa id (.sp) file must occur in the same directory as the fasta file and have the same filename with .sp appended (i.e., ReferenceDB.fasta and ReferenceDB.fasta.sp).
If you have a Genbank database and only want to add additional or custom/private sequences, we recommend first running --convert.
MitoSIS.py -r ReferenceDB.gb --convert
--convert will convert your Genbank file to a fasta+sp database without running the rest of MitoSIS. Output will be:
ReferenceDB.fastaReferenceDB.fasta.sp
With the initial fasta+sp database created...
Manually add your additional or custom sequences to the fasta and the identifer/taxa information to the .sp file.
Each fasta sequences must have unique identifiers (similar to Genbank Accession Numbers) and those identifiers must match in the tab-delimited taxa id file. Ensure to not have descriptions in the fasta header (i.e., no spaces " " in the header, only the sequence id).
{ReferenceDB}.fasta
>ID_1
ACTGACTGACTGACTGACTGACTGACTGACTGACTGACTGACTG
>ID_2
ACTGACTGACTGACTGACTGACTGACTGACTGACTGACTGACTG
{ReferenceDB}.fasta.sp
ID_1 Genus species
ID_2 Genus species
System Requirement
- Linux
Conda Installation
# Clone this Repository
git clone https://github.com/RhettRautsaw/MitoSIS.git
cd MitoSIS
echo "export PATH=\$PATH:$PWD" >> ~/.bash_profile
# Clone MITGARD Repository
git clone https://github.com/pedronachtigall/MITGARD.git
# Fix shebangs in MITGARD supporting scripts
sed -i '1 s/^.*$/\#\!\/usr\/bin\/env python/' MITGARD/bin/sam2msa.py
sed -i '1 s/^.*$/\#\!\/usr\/bin\/env python/' MITGARD/bin/msa2consensus.py
echo "export PATH=\$PATH:$PWD/MITGARD/bin" >> ~/.bash_profile
# Clone MitoZ Repository
git clone https://github.com/linzhi2013/MitoZ.git
tar -jxvf MitoZ/version_2.4-alpha/release_MitoZ_v2.4-alpha.tar.bz2
echo "export PATH=\$PATH:$PWD/release_MitoZ_v2.4-alpha" >> ~/.bash_profile
# Make sure everythig has proper permissions and source your bash_profile
chmod -R 755 *
source ~/.bash_profile
# Create Conda Environment
conda env create -f mitosis_env.yml
conda activate mitosis_env
# Install dfply
pip install dfply
# Install Taxonomy Database for MitoZ
python MITGARD/install_NCBITaxa.py
# YOU'RE READY TO GO
# Check if MitoSIS.py is in your path
MitoSIS.py -h
Before running, we recommend testing MitoSIS with our Tutorial dataset.
We also recommend trimming your own data first prior to running this program. Example trimming using Trim-Galore shown below. Depending on whether you are working with DNA or RNA-Seq data, you may want to change the length/quality parameters.
# Trimming
trim_galore --paired --phred33 --length 30 -q 20 -o 02_trim 00_raw/{}_F.fastq.gz 00_raw/{}_R.fastq.gz &> {}_tg.log
Below are outlines for running MitoSIS.
# MitoSIS - paired-end
MitoSIS.py -f1 {}_F_trim.fastq.gz -f2 {}_R_trim.fastq.gz -r ReferenceDB.gb -o {} -c 16 -M 55G &> MitoSIS.log
# MitoSIS - single
MitoSIS.py -s {}_merged.fastq.gz -r ReferenceDB.gb -o {} -c 16 -M 55G &> MitoSIS.log
# MitoSIS - paired-end & fasta+sp reference database
# NOTE: MitoSIS expects ReferenceDB.fasta.sp to occur in the same directory as ReferenceDB.fasta
MitoSIS.py -f1 {}_F_trim.fastq.gz -f2 {}_R_trim.fastq.gz -r ReferenceDB.fasta -o {} -c 16 -M 55G &> MitoSIS.log
The user can find a detailed results in the MitoSIS_summary_output.html with the potential contamination, percent identity and alignment distance across genes and all phylogenetic trees build. Moreover, during processing MitoSIS print messages at the terminal summarizing all results, which may also be used by the user to check the results. Find below an example of the printed message and a detailed information about all files generated by MitoSIS pipeline that can be used/analyzed a posteriori by the user.
MitoSIS.py -f1 CON45_R1.fq.gz -f2 CON45_R2.fq.gz -r ReferenceDB.gb -o CON45 -c 16 -M 62G
o O o O o O o O o O o O
o | | O o | | O o | | O o | | O o | | O o | | O
O | | | | O | | | | O | | | | O | | | | O | | | | O | | | | O
O-oO | | o O | | o O | | o O | | o O | | o O | | oO-o
O---o O o O o O o O o O o O o O---o
O-----O O-----o
o-----O ___ ____ _ _____ _____ _____ o-----O
o---O | \/ (_) | / ___|_ _/ ___| o---O
o-O | . . |_| |_ ___ \ `--. | | \ `--. o-O
O | |\/| | | __/ _ \ `--. \ | | `--. \ O
O-o | | | | | || (_) /\__/ /_| |_/\__/ / O-O
O---o \_| |_/_|\__\___/\____/ \___/\____/ O---o
O-----o v1.2 O-----o
o-----O o-----O
o---O o O o O o O o O o O o O o---O
o-Oo | | O o | | O o | | O o | | O o | | O o | | Oo-O
O | | | | O | | | | O | | | | O | | | | O | | | | O | | | | O
O | | o O | | o O | | o O | | o O | | o O | | o
O o O o O o O o O o O o
2021-10-12 10:39:21 ::: starting MitoSIS...
Forward Reads -> /zfs/venom/Rhett/bin/MitoSIS/Tutorial/CON45_R1.fq.gz
Reverse Reads -> /zfs/venom/Rhett/bin/MitoSIS/Tutorial/CON45_R2.fq.gz
Reference Database -> /zfs/venom/Rhett/bin/MitoSIS/Tutorial/ReferenceDB.gb
Output -> /zfs/venom/Rhett/bin/MitoSIS/Tutorial/MitoSIS_results/CON45*
Number of CPU -> 16
Amount of memory -> 62G
MitoZ Clade -> Chordata
2021-10-12 10:39:21 ::: Converting Genbank to Fasta :::
2021-10-12 10:39:21 ::: Converted 521 Genbank records to Fasta :::
2021-10-12 10:39:21 ::: Running kallisto index :::
2021-10-12 10:39:21 ::: Running kallisto :::
2021-10-12 10:39:21 ::: Summarizing kallisto to assess potential contamination :::
species read_count_sum read_count_mean tpm_sum tpm_mean read_sum_percent read_mean_percent tpm_sum_percent tpm_mean_percent
Crotalus adamanteus 3389.0 12.191 850947.699 3060.963 85.044 67.018 85.095 67.126
Crotalus horridus 198.0 3.882 49427.400 969.165 4.969 21.343 4.943 21.253
Agkistrodon piscivorus 398.0 2.117 99625.600 529.923 9.987 11.638 9.963 11.621
2021-10-12 10:39:21 ::: Identifying best reference sequence :::
sseqid length read_count tpm species
Selected Reference > NC_041524.1 17242 1693.75 423259.0 Crotalus adamanteus
MH626511.1 17242 1693.75 423259.0 Crotalus adamanteus
DQ523161.1 17213 199.00 49812.8 Agkistrodon piscivorus
NC_009768.1 17213 199.00 49812.8 Agkistrodon piscivorus
NC_014400.1 17260 99.00 24713.7 Crotalus horridus
HM641837.1 17260 99.00 24713.7 Crotalus horridus
2021-10-12 10:39:22 ::: Running MITGARD :::
2021-10-12 10:52:17 ::: Annotating MITGARD mitogenome with MitoZ :::
2021-10-12 10:59:57 ::: Moving onto BLAST :::
2021-10-12 10:59:57 ::: Running makeblastdb :::
2021-10-12 10:59:57 ::: Running BLAST :::
2021-10-12 10:59:58 ::: Summarizing Mean Percent Identity across genes :::
species Mean_Percent_Identity
Crotalus adamanteus 99.838545
Crotalus horridus horridus 96.175000
Crotalus horridus 89.570667
Agkistrodon piscivorus 84.574576
2021-10-12 11:00:03 ::: Extracting BLAST matches for Phylogenetics :::
2021-10-12 11:00:03 ::: Aligning, Trimming, and Inferring Phylogeny for ND1.fasta :::
species minimum_distance mean_distance
Crotalus adamanteus 0.000000 0.000003
Crotalus horridus 0.386271 0.424664
Agkistrodon piscivorus 0.738328 0.738328
/ NC_009768.1 Agkistrodon piscivorus
/--------------------------------------------------+
| \ DQ523161.1 Agkistrodon piscivorus
|
| /GAAZ01001454.1 Crotalus horridus
+ +
| |GBKC01002148.1 Crotalus horridus
| /---------+
| | | / HM641837.1 Crotalus horridus
| | \--------------------------------+
\-------+ \ NC_014400.1 Crotalus horridus
|
| /JU175111.1 Crotalus adamanteus
\----------------+
|MH626511.1 Crotalus adamanteus
+
|GBEX01002025.1 Crotalus adamanteus
+
|CON45
+
\NC_041524.1 Crotalus adamanteus
... MORE GENES ...
2021-10-12 11:01:10 ::: Summarizing Phylogenetic Distance across genes :::
species minimum_distance mean_distance
Crotalus adamanteus 0.000000 0.071839
Crotalus horridus 0.199598 0.479474
Crotalus horridus horridus 0.241776 0.314130
Agkistrodon piscivorus 0.461318 0.708560
2021-10-12 11:01:10 ::: Concatenating Genes and Removing Individuals with > 50% Missing :::
2021-10-12 11:01:12 ::: Running Concatenated Phylogeny :::
/NC_009768.1_Agkistrodon_piscivorus
/------------------+
/------------------+ \DQ523161.1_Agkistrodon_piscivorus
| |
| \------------------------ EF669477.1_Agkistrodon_piscivorus
+
| /HM641837.1_Crotalus_horridus
| /---------------------------------+
| | \NC_014400.1_Crotalus_horridus
\--------+
| /MH626511.1_Crotalus_adamanteus
\-------------------+
|CON45_
+
\NC_041524.1_Crotalus_adamanteus
2021-10-12 11:01:14 ::: Generating plots and HTML output :::
2021-10-12 11:01:20 ::: FINISHED :::
You should expect the following output files; however, sometimes the mitoz.result folder may be absent if the mitogenome assembly is not complete. Regardless, results include kallisto contamination results/summary (mean/sum read counts and tpm to each species), blast results/summary (mean percent identity to different species), the mitochondrial genome, MitoZ annotation results, and phylogenies/phylogenetic distance summary. The log file (or STDOUT if log file not saved) will print each phylogeny.
MitoSIS_results/
├── alternate_references.tsv
├── best_reference.fasta
├── blast_query.fasta
├── blast_results.tsv
├── blast_summary.png
├── blast_summary.tsv
├── CON45_mitogenome.fasta
├── kallisto
│ ├── abundance.h5
│ ├── abundance.tsv
│ ├── abundance_species.tsv
│ └── run_info.json
├── kallisto_contamination.png
├── kallisto_contamination.tsv
├── MitoSIS_summary_output.html
├── mitoz.result
│ ├── CON45.cds
│ ├── CON45.circos.karyotype.txt
│ ├── CON45.circos.png
│ ├── CON45.circos.svg
│ ├── CON45.errorsummary.val
│ ├── CON45.fasta
│ ├── CON45.misc_feature
│ ├── CON45_mitoscaf.fa.gbf
│ ├── CON45_mitoscaf.fa.sqn
│ ├── CON45_mitoscaf.fa.tbl
│ ├── CON45_mitoscaf.fa.val
│ ├── CON45.rrna
│ ├── CON45.trna
│ └── summary.txt
├── phylogenetic_distance_summary.png
├── phylogenetic_distance_summary.tsv
├── Phylogenetics
│ ├── gene.fasta
│ ├── gene.fasta.aln
│ ├── gene.fasta.contree
│ ├── gene.fasta.iqtree
│ ├── gene.fasta.phylodist.tsv
│ ├── gene.fasta.png
│ ├── gene.fasta.trim
│ ├── gene.nex
│ ├── Concatenated.nex
│ ├── Concatenated.phy
│ ├── Concatenated.phy.bionj
│ ├── Concatenated.phy.ckp.gz
│ ├── Concatenated.phy.contree
│ ├── Concatenated.phy.iqtree
│ ├── Concatenated.phy.log
│ ├── Concatenated.phy.mldist
│ ├── Concatenated.phy.model.gz
│ ├── Concatenated.phy.png
│ ├── Concatenated.phy.splits.nex
│ ├── Concatenated.phy.treefile
│ └── Concatenated.phy.uniqueseq.phy
└── RearrangementCheck
├── align0.sam
├── consensus0.mfa.fasta
├── contigs0
├── newref0
└── newref0_mitogenome.fa
Because this program only works as a wrapper for other programs, we recommend that you cite them as well.
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