- What is MutMap?
- Installation
- Usage
- Outputs
- About multiple testing correction
- Built and use your own database for snpEff
Bulked segregant analysis, as implemented in MutMap (Abe et al., 2012), is a powerful and efficient method to identify agronomically important loci in crop plants. MutMap requires whole-genome resequencing of a single individual from the original cultivar and the pooled sequences of F2 progeny from a cross between the original cultivar and mutant. MutMap uses the sequence of the original cultivar to polarize the site frequencies of neighbouring markers and identifies loci with an unexpected site frequency, simulating the genotype of F2 progeny. The updated pipeline is approximately 5-8 times faster than the previous pipeline, are easier for novice users to use and can be easily installed through bioconda with all dependencies.
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Yu Sugihara, Lester Young, Hiroki Yaegashi, Satoshi Natsume, Daniel J. Shea, Hiroki Takagi, Helen Booker, Hideki Innan, Ryohei Terauchi, Akira Abe (2022). High performance pipeline for MutMap and QTL-seq. PeerJ, 10:e13170.
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Akira Abe, Shunichi Kosugi, Kentaro Yoshida, Satoshi Natsume, Hiroki Takagi, Hiroyuki Kanzaki, Hideo Matsumura, Kakoto Yoshida, Chikako Mitsuoka, Muluneh Tamiru, Hideki Innan, Liliana Cano, Sophien Kamoun & Ryohei Terauchi (2012). Genome sequencing reveals agronomically important loci in rice using MutMap. Nature Biotechnol. 30:174-179.
- matplotlib
- numpy
- pandas
- seaborn (optional)
You can install MutMap using bioconda.
conda install -c bioconda mutmap
Alternatively, if you want to create MutMap specific environment with Python3.
conda create -n mutmap python=3 mutmap
If you got a error during installation, you can install MutMap, manually.
git clone https://github.com/YuSugihara/MutMap.git
cd MutMap
pip install -e .
Then you have to install other dependencies by yourself. We highly recommend you to install SnpEff and Trimmomatic using bioconda.
conda install -c bioconda snpeff
conda install -c bioconda trimmomatic
After installation, please check whether SnpEff and Trimmomatic work through the commands below.
snpEff --help
trimmomatic --help
If your reference genome has more than 50 contigs (or chromosomes), only significant contigs will be plotted.
mutmap -h
usage: mutmap -r <FASTA> -c <BAM|FASTQ> -b <BAM|FASTQ>
-n <INT> -o <OUT_DIR> [-T] [-e <DATABASE>]
MutMap version 2.3.4
optional arguments:
-h, --help show this help message and exit
-r , --ref Reference fasta.
-c , --cultivar fastq or bam of cultivar. If you specify
fastq, please separate pairs by comma,
e.g. -c fastq1,fastq2. You can use this
optiion multiple times
-b , --bulk fastq or bam of mutnat bulk. If you specify
fastq, please separate pairs by comma,
e.g. -b fastq1,fastq2. You can use this
optiion multiple times
-n , --N-bulk Number of individuals in mutant bulk.
-o , --out Output directory. Specified name must not
exist.
-t , --threads Number of threads. If you specify the number
below one, then MutMap will use the threads
as many as possible. [2]
-w , --window Window size (kb). [2000]
-s , --step Step size (kb). [100]
-D , --max-depth Maximum depth of variants which will be used.
This cutoff will be applied in both of cultivar
and bulk. [250]
-d , --min-depth Minimum depth of variants which will be used.
This cutoff will be applied in both of cultivar
and bulk. [8]
-N , --N-rep Number of replicates for simulation to make
null distribution. [5000]
-T, --trim Trim fastq using trimmomatic.
-a , --adapter FASTA of adapter sequences. This will be used
when you specify "-T" for trimming.
--trim-params Parameters for trimmomatic. Input parameters
must be separated by comma with following
order: phred, ILLUMINACLIP, LEADING, TRAILING,
SLIDINGWINDOW, MINLEN. If you want to remove
adapters of illumina, please specify FASTA of
the adapter sequences with "--adapter". Specified
name will be inserted into <ADAPTER_FASTA>. If you
don't specify it, adapter trimming will be skipped.
[33,<ADAPTER_FASTA>:2:30:10,20,20,4:15,75]
-e , --snpEff Predict causal variant using SnpEff. Please
check available databases in SnpEff.
--mem Maximum memory per thread when bam sorted;
suffix K/M/G recognized. [1G]
-q , --min-MQ Minimum mapping quality in mpileup. [40]
-Q , --min-BQ Minimum base quality in mpileup. [18]
-C , --adjust-MQ "adjust-MQ" in mpileup. Default parameter
is suited for BWA. [50]
--species Consider multiple test correction derived by
Huang et al. (2019). Please spesify a species name.
With this option. QTL-seq produces a theoretical threshold.
Currently, Arabidopsis, Cucumber, Maize, Rapeseed,
Rice, Tobacco, Tomato, Wheat, and Yeast are supported.
-v, --version show program's version number and exit
MutMap can run from FASTQ (without or with trimming) and BAM. If you want to run MutMap from VCF, please use MutPlot (example 5). Once you run MutMap, MutMap automatically complete the subprocesses.
- Example 1 : run MutMap from FASTQ without trimming
- Example 2 : run MutMap from FASTQ with trimming
- Example 3 : run MutMap from BAM
- Example 4 : run MutMap from multiple FASTQs and BAMs
- Example 5 : run MutPlot from VCF
mutmap -r reference.fasta \
-c cultivar.1.fastq,cultivar.2.fastq \
-b bulk.1.fastq,bulk.2.fastq \
-n 20 \
-o example_dir
-r : reference fasta
-c : FASTQs of cultivar. Please input pair-end reads separated by comma. FASTQs can be gzipped.
-b : FASTQs of bulk. Please input pair-end reads separated by comma. FASTQs can be gzipped.
-n : number of individuals in mutant bulk.
-o : name of output directory. Specified name should not exist.
mutmap -r reference.fasta \
-c cultivar.1.fastq,cultivar.2.fastq \
-b bulk.1.fastq,bulk.2.fastq \
-n 20 \
-o example_dir \
-T
-r : reference fasta
-c : FASTQs of cultivar. Please input pair-end reads separated by comma. FASTQs can be gzipped.
-b : FASTQs of bulk. Please input pair-end reads separated by comma. FASTQs can be gzipped.
-n : number of individuals in mutant bulk.
-o : name of output directory. Specified name should not exist.
-T : trim your reads by trimmomatic.
mutmap -r reference.fasta \
-c cultivar.bam \
-b bulk.bam \
-n 20 \
-o example_dir
-r : reference fasta
-c : BAM of cultivar.
-b : BAM of bulk.
-n : number of individuals in mutant bulk.
-o : name of output directory. Specified name should not exist.
mutmap -r reference.fasta \
-c cultivar_1.1.fastq,cultivar_1.2.fastq \
-c cultivar_1.bam \
-b bulk_1.1.fastq,bulk_1.2.fastq \
-b bulk_2.bam \
-b bulk_3.bam \
-n 20 \
-o example_dir
MutMap can automatically merge multiple FASTQs and BAMs. Of course, you can merge FASTQs or BAMs using cat or samtools merge before input them to MutMap. If you specify -c multiple times, please make sure that those files include only 1 individual. On the other hand, -b can include more than 1 individuals because those are bulked samples. MutMap can automatically classify FASTQs and BAMs from whether comma exits or not.
mutplot -h
usage: mutplot -v <VCF> -o <OUT_DIR> -n <INT> [-w <INT>] [-s <INT>]
[-D <INT>] [-d <INT>] [-N <INT>] [-m <FLOAT>]
[-S <INT>] [-e <DATABASE>] [--igv] [--indel]
MutPlot version 2.3.4
optional arguments:
-h, --help show this help message and exit
-v , --vcf VCF file which contains cultivar and mutant bulk.
in this order. This VCF file must have AD field.
-o , --out Output directory. Specified name can exist.
-n , --N-bulk Number of individuals in mutant bulk.
-w , --window Window size (kb). [2000]
-s , --step Step size (kb). [100]
-D , --max-depth Maximum depth of variants which will be used.
This cutoff will be applied in both of cultivar
and bulk. [250]
-d , --min-depth Minimum depth of variants which will be used.
This cutoff will be applied in both of cultivar
and bulk. [8]
-N , --N-rep Number of replicates for simulation to make
null distribution. [5000]
-m , --min-SNPindex Cutoff of minimum SNP-index for clear results. [0.3]
-S , --strand-bias Filter spurious homo genotypes in cultivar using
strand bias. If ADF (or ADR) is higher than this
cutoff when ADR (or ADF) is 0, that SNP will be
filtered out. If you want to supress this filtering,
please set this cutoff to 0. [7]
-e , --snpEff Predict causal variant using SnpEff. Please
check available databases in SnpEff.
--igv Output IGV format file to check results on IGV.
--species Consider multiple test correction derived by
Huang et al. (2019). Please spesify a species name.
With this option. MutMap produces a theoretical threshold.
Currently, Arabidopsis, Cucumber, Maize, Rapeseed,
Rice, Tobacco, Tomato, Wheat, and Yeast are supported.
--indel Plot SNP-index with INDEL.
--fig-width Width allocated in chromosome figure. [7.5]
--fig-height Height allocated in chromosome figure. [4.0]
--white-space White space between figures. (This option
only affect vertical direction.) [0.6]
-f , --format Specifiy the format of an output image.
eps/jpeg/jpg/pdf/pgf/png/rgba/svg/svgz/tif/tiff
--version show program's version number and exit
MutPlot is included in MutMap. MutMap run MutPlot after making VCF. Then, MutPlot will work with default parameters. If you want to change some parameters, you can use VCF inside of (OUT_DIR/30_vcf/mutmap.vcf.gz) to retry plotting process like below.
mutplot -v OUT_DIR/30_vcf/mutmap.vcf.gz \
-o ANOTHER_DIR_NAME \
-n 20 \
-w 2000 \
-s 100
In this case, please make sure that:
- Your VCF include AD format.
- Your VCF include two columns of cultivar and mutant bulk in this order.
If you got a error, please try to run MutMap from FASTQ or BAM before asking in issues.
Inside of OUT_DIR is like below.
|-- 10_ref
| |-- reference.fasta
| |-- reference.fasta.amb
| |-- reference.fasta.ann
| |-- reference.fasta.bwt
| |-- reference.fasta.fai
| |-- reference.fasta.pac
| `-- reference.fasta.sa
|-- 20_bam
| |-- bulk.filt.bam
| |-- bulk.filt.bam.bai
| |-- cultivar.filt.bam
| `-- cultivar.filt.bam.bai
|-- 30_vcf
| |-- mutmap.vcf.gz
| `-- mutmap.vcf.gz.tbi
|-- 40_mutmap
| |-- snp_index.tsv
│ ├── snp_index.p95.tsv
│ ├── snp_index.p99.tsv
| |-- sliding_window.tsv
│ ├── sliding_window.p95.tsv
│ ├── sliding_window.p99.tsv
| `-- mutmap_plot.png
`-- log
|-- bcftools.log
|-- bgzip.log
|-- bwa.log
|-- mutplot.log
|-- samtools.log
`-- tabix.log
- If you run MutMap with trimming, you will get the directory of
00_fastqwhich includes FASTQs after trimming. - You can check the results in
40_mutmap.snp_index.tsv: columns in this order.- CHROM : chromosome name
- POSI : position in chromosome
- VARIANT : SNP or INDEL
- DEPTH : depth of bulk
- p99 : 99% confidence interval of simulated SNP-index
- p95 : 95% confidence interval of simulated SNP-index
- SNP-index : real SNP-index
sliding_window.tsv: columns in this order.- CHROM : chromosome name
- POSI : central position of window
- MEAN p99 : mean of p99
- MEAN p95 : mean of p95
- MEAN SNP-index : mean SNP-index
mutmap_plot.png: resulting plot (like below)- BLUE dot : variant
- RED line : mean SNP-index
- ORANGE line : mean p99
- GREEN line : mean p95
We implemented multiple testing correction in MutMap v2.
However, since multiple testing correction changes the threshold from the original MutMap threshold, we highly recommend users, who expect original MutMap algorism identifying a lot of causal mutations in many researches, to try MutMap v2 without multiple testing correction at first.
You can use multiple testing correction with the option --species like below:
mutmap -r reference.fasta \
-c cultivar.1.fastq,cultivar.2.fastq \
-b bulk.1.fastq,bulk.2.fastq \
-n 20 \
-o example_dir \
--species Rice
Currently, only nine species (Arabidopsis, Cucumber, Maize, Rapeseed, Rice, Tobacco, Tomato, Wheat, and Yeast) are supported, following the parameters defined in Huang et al. (2019).
If you want to use your own database for snpEff, you need additional steps.
Here we assume that you installed MutMap via anaconda distribution, creating new environment with conda create.
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Find the directory of snpEff that includes snpEff script, configuration file and database. You can find it in
/home/anaconda3/envs/{your_env_name_installed_mutmap}/share/snpeff-5.0-0/.anaconda3may beminiconda3. Also, the version of snpeff may be different. -
Go to this directory and follow the snpEff manual to build the database. Don't forget to add your database info to the snpEff configuration file. https://pcingola.github.io/SnpEff/se_buildingdb/#add-a-genome-to-the-configuration-file
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Run MutMap with option
-e {your_database_name}
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