Quality check, de novo assembly and annotation of Meloidogyne species genomes
| Species | Strain | Location | Insert size | Reads | Size (bp) | Exp. coverage |
|---|---|---|---|---|---|---|
| M. javanica | VW4 | California | 300 | 62,075,861 | 7,635,287,416 | 100x |
| M. javanica | VW4 | California | 500 | 123,728,247 | 15,168,259,765 | 200x |
| M. javanica | VW5 | California | 350 | 193,072,088 | 24,134,011,000 | 320x |
| M. javanica | L57 | Morocco | 32,669,417 | 4,083,677,125 | 27x | |
| M. javanicac | L15 | Thailand | - | 29,324,182 | 3,665,522,750 | 24x |
| M. javanicac | L17 | Burkina Faso | - | 31,332,441 | 3,916,555,125 | 26x |
| M. incognita | W1 | ? | 350 | 38,260,145 | 4,782,518,125 | 63x |
| M. incognita | W1 | ? | 550 | 30,290,198 | 3,786,274,750 | 50x |
| M. incognita | VW6 | ? | 350 | 28,840,610 | 3,605,076,250 | 48x |
| M. incognita | VW6 | ? | 550 | 25,746,808 | 3,218,351,000 | 42x |
| M. incognita | HarC | ? | 350 | 26,844,521 | 3,355,565,125 | 44x |
| M. incognita | HarC | ? | 550 | 35,340,761 | 4,417,595,125 | 58x |
| M. incognita | 557R | ? | 550 | 62,745,198 | 7,843,149,750 | 104x |
| M. incognita | L9 | Ivory Coast | 19,009,603 | 2,376,200,375 | 18x | |
| M. incognita | L19 | French West Indies | - | 33,486,356 | 4,185,794,500 | 28x |
| M. incognita | L27 | USA | - | 35,218,809 | 4,402,351,125 | 29x |
| M. incognita | A14 | Lybia | - | 20,025,193 | 2,503,149,125 | 17x |
| M. arenaria | HarA | California | 350 | 49,813,878 | 6,226,734,750 | 41x |
| M. arenaria | HarA | California | 550 | 46,643,017 | 9,656,831,750 | 64x |
| M. arenaria | L28 | French West Indies | - | 16,744,391 | 2,093,048,875 | 14x |
| M. arenaria | L32 | French West Indies | - | 14,159,397 | 176,9924,625 | 11x |
| M. konaensis | - | ? | 350 | 55,647,288 | 6,955,911,000 | 46x |
| M. konaensis | - | ? | 550 | 52,813,037 | 6,601,629,625 | 44x |
| M. enterolobii | L30 | ? | 350 | 143,672,079 | 17,959,009,875 | 120x |
| M. enterolobii | L30 | ? | 550 | 100,032,455 | 12,504,056,875 | 83x |
| M. floridensis | Florida |
/fastqc_v0.11.2/fastqc file.fastq.gz
# Filter and quality trim reads
sga preprocess --pe-mode 1 file_R1.fastq.gz file_R2.fastq.gz > file_ilv.fastq
#Build index
sga index -a ropebwt --no-reverse -t 8 file_ilv.fastq
#Pre-assembly quality check
sga preqc -t 8 file_ilv.fastq > file.preqc
#Create a report
source /virt_env/python/matplotlib_1.4/bin/activate
sga-preqc-report.py file.preqc
Filtering of reads (for protocol see https://blobtools.readme.io/)
#Assembly with clc
clc_assembler \
-o assembly_clc.fasta \
-q raw_R1.fastq.gz raw_R2.fastq.gz
#Mapping with bowtie
bowtie2 \
-x assembly_clc.fasta \
-1 raw_R1.fastq.gz \
-2 raw_R2.fastq.gz \
-p 16 \
| samtools-1.3.1/samtools view - -b > assembly_map.bowtie
bam
#Sort with samtools
samtools sort \
-n assembly_map.bowtie.bam \
-@ 16 \
-o assembly_map.bowtie.sorted
###Blobplots
#Blast (2.2.30+) the assembly against the nt database
blastn -task megablast
-query assembly_clc.fasta \
-db nt \
-evalue 1e-5 \
-outfmt '6 qseqid staxids bitscore std sscinames sskingdoms stitle' \
-out assembly.25cul1.1e25.megablast.out \
-max_target_seqs 25 \
-culling_limit 2 \
-num_threads 8
#Create blobplot
/blobtools-light/makeblobs.py \
-a assembly_clc.fasta \
-bam assembly_map.bowtie.sorted.bam \
-blast assembly.25cul1.1e25.megablast.out \
-o assembly -taxdb /blast_db/
#Plot (matplotlib is needed)
source /exports/virt_env/python/matplotlib/bin/activate
/blobtools-light/plotblobs.py assembly.blobplot.txt
#Index the assembly with samtools
samtools faidx assembly_clc.fasta
#Find bacteria contigs in the assembly (e.g. Proteobacteria)
grep "tax=Proteobacteria" assembly.25cul1.1e25_lib2.megablast.blobplot.txt | cut -f1 > assembly_proteobacteria.contigs
#Remove the the contigs from the indexed assembly
#grep -v -f assembly_proteobacteria.contigs assembly_clc.fasta.fai > assembly_clc_noprot.fasta.fai
#Get non-bacteria contigs with both reads mapped
samtools view \
-t assembly_clc_noprot.fasta.fai \
-bS -F12 assembly_map_lib1.bowtie.sorted.bam \
> Sp_lib1.m_m.bam
#Pull the reads that mapped to non-bacteria contigs
/samtools-1.3.1/samtools view \
-uf64 Sp_lib1.m_m.bam \
| /samtools-1.3.1/samtools bam2fq - \
| gzip > Sp_lib1.reads1.fq.gz
skewer-0.2.2-linux-x86_64 \
-n \
-y adapters.fa \
-q 20 \
-l 25 \
-m pe \
o Sp_lib \
-t 32 \
Sp_lib1.reads1.fq.gz \
Sp_lib1.reads2.fq.gz
#Contigs
platanus assemble \
-t 48 \
-m 400 \
-o Sp \
-f \
Sp_lib1-trimmed-pair1.fastq \
Sp_lib1-trimmed-pair2.fastq \
Sp_lib2-trimmed-pair1.fastq \
Sp_lib2-trimmed-pair2.fastq
#Scaffolds
platanus scaffold \
-t 48 \
-b Sp_contigBubble.fa \
-c Sp_contig.fa \
-o Sp \
-IP1 Sp_lib1-trimmed-pair1.fastq Sp_lib1-trimmed-pair2.fastq \
-IP2 Sp_lib2-trimmed-pair1.fastq Sp_lib2-trimmed-pair2.fastq
#Gap closing
platanus gap_close \
-t 48 \
-c Sp_scaffold.fa \
-IP1 Sp_lib1-trimmed-pair1.fastq Sp_lib1-trimmed-pair2.fastq \
-IP2 Sp_lib2-trimmed-pair1.fastq Sp_lib2-trimmed-pair2.fastq
###CEGMA
cegma --genome --threads 32 --output SP_assembly.platanus.fa
###BUSCO
python3 BUSCO.py \
-c 16 \
-i SP_assembly.platanus.fa \
-o sp.busco \
-m geno \
-l busco/busco-v2.0/nematoda_odb9/ \
-t sp_busco
###Map reads back to assembly with bwa
bwa mem \
Sp_assembly.platanus.fa \
raw_R1.fastq raw_R2.fastq \
| samtools view -buS - | samtools sort - Sp.bwa.sorted
###Repeatmodeler
RepeatModeler/BuildDatabase -name Sp \
Sp_assembly.platanus.fa
-engine ncbi \
###Repeatmasker(v4-0-3)
#Create a library with nematoda.repeatmasker from repeatmask, repeatmodeler output (consensi.fa.classified) and Nematoda.lib from Amir (ref?)
cat ematoda.repeatmasker consensi.fa.classified Nematoda.lib > nematoda_LibTE.repeats
#Run cdhit-est (4.6.4) with high cutoff to avoid redundancy
cd-hit-est -i \
nematoda_LibTE.repeats \
-o nematoda_LibTE.repeats.cdhitest \
-c 0.95 \
-d 0 \
-T 16 \
-M 3000
#Run repeatmasker
RepeatMasker \
Sp_assembly.platanus.fa \
-lib nematoda_LibTE.repeats.cdhitest \
-dir .
###SNAP (v2013-11-29)
maker/maker-2.31/bin/cegma2zff \
/cegma_output/Sp.cegma.gff \
Sp_assembly.platanus.fa #this creates files genome.ann, genome.dna
fathom genome.ann genome.dna \
-categorize 1000 \
fathom -export 1000 -plus uni.ann uni.dna
mkdir parameters
cd parameters
forge ../export.ann ../export.dna
cd ../
hmm-assembler.pl \
Sp_assembly.platanus.fa \
parameters > Sp.cegmasnap.hmm
###Genemark (es-2.3)
gm_es.pl \
--BP OFF \
-max_nnn 500 \
-min_contig 10000 \
Sp_assembly.platanus.fa.masked #output of repeatmask
#the output of genemark is mod.es in the mod folder as symbolik link
###Maker (2.311)
mpiexec -n 48 maker -fix_nucleotides
cd *.fa.maker.output/
gff3_merge -d *.fasta_master_datastore_index.log
###Augustus (3.0.1)
maker/bin/maker2zff Sp_assembly.platanus.fa.masked.all.gff
snap/zff2gff3.pl genome.ann | perl -plne 's/\t(\S+)$/\t\.\t$1/' > augustus.train.gff3
#/exports/software/snap/snap-2013-11-29/zff2gff3.pl genome.ann | perl -plne 's/\t(\S+)$/\t\.\t$1/' > augustus.train.gff3
autoAug.pl --species=Sp \
--genome=Sp_assembly.platanus.fa.masked \
--trainingset=augustus.train.gff3 \
--useexisting -v \
--singleCPU \
--optrounds=3 > augustus.out.txt
| M. javanica VW4 illumina | M. javanica VW4 pacbio | M. incognita W1 | M. arenaria HarA | M. enterolobii L30 | M. floridensis | |
|---|---|---|---|---|---|---|
| Scaffolds | 34,394 | 5,527 | 33,735 | 46,509 | 46,090 | 9,134 |
| Genome Span | 142,608,877 | 212,245,641 | 122,043,328 | 163,770,989 | 162,361,678 | 74,893,90 |
| Longest scaffold | 223,460 | 510,271 | 248,829 | 163,224 | 94,967 | 88,393 |
| N50 | 14,133 | 44,602 | 16,498 | 10,504 | 9,280 | 13,256 |
| GC | 29.6 | 29.3 | 0.299 | 29.5 | 29.7 | 30.2 |
| Mapped reads | 98.82% | 97.16% | 99.1% | 98.8% | 90.19% | |
| 18S | yes | yes | yes | yes | yes | |
| mitochondria | yes | yes | yes | yes | yes | |
| CEGMA completness | 90.32% | 93.95% | 82.66% | 91.13% | 81.45% | 84% |
| CEGMA average | 2.51 | 3.17 | 2.38 | 2.76 | 2.61 | 1.6 |
| BUSCO complete | 52.4% | 56.1% | 50.7% | 50.6% | ||
| BUSCO fragmented | 9% | 9.6% | 9.9% | 8.5% | ||
| BUSCO missing | 38.6% | 34.3% | 39.4% | 40.9% | ||
| Predicted Genes | 26.917 | 29.413 | 24.714 | 30.308 | 31.051 | 14,144 |
| Functional Annotated | 17.659 | 15.938 | 20.813 |