Low-input Low-cost amplification-free library-production method for PacBio Long-read sequencing
All the codes for LILAP are available in the 'code.sh' file. The installation of the software should be conducted with the correct versions specified in the accompanying paper.
Links for the single-fly genome (and Wolbachia) assemblies:
ISO1-1: https://drive.google.com/file/d/1-BD99hcTxMuByG2PVFB0xjcttYHY1gKu/view?usp=drive_link
ISO1-2: https://drive.google.com/file/d/1Fi6L-yJmRprQ_virCgi18QCLBRF7HUZJ/view?usp=drive_link
wISO1-1: https://drive.google.com/file/d/1f2nLqUaaNm7orrgbCTvWwSh3s43uYKLr/view?usp=drive_link
wISO1-2: https://drive.google.com/file/d/1IjXDbNlbdbVfbI8CDNQcFazp7PgJY5Yb/view?usp=drive_link
All PacBio HiFi sequencing data generated in this study are available at the NCBI Sequence Read Archive database (https://www.ncbi.nlm.nih.gov/sra) under the accession numbers PRJNA983717.
Git clone all the codes, and run the following codes on the Linux server. The necessary software for this research is detailed in the "requirements.txt" file.
Test the assembly code using both ISO1-1 and ISO1-2 ccs reads with the provided instructions.
For SVs and SNPs, utilize both the single-fly and Wolbachia genome assemblies. Examine the anticipated structural variation results in the sv.C01.ccs.hifiasm.txt file. It's important to note that some raw results necessitate additional manual verification, as elaborated in the manuscript. The complete pipeline, including the manual checking process, requires a few days for the analysis of the single-fly genome assembly.
- LILAP
cat C01.subreads.cut19.fasta | awk '{if($0 ~ /^>/){rname=$0} else{all[rname]=all[rname]+length($0)}}END{for(rname in all){print all[rname]}}' > C01.subreads.cut19.fasta.length
cat C01.ccs.cut19.fasta | awk '{if($0 ~ /^>/){rname=$0} else{all[rname]=all[rname]+length($0)}}END{for(rname in all){print all[rname]}}' > C01.ccs.cut19.fasta.length
perl Tn5_insertion_site_bias.pl
python3 ccs_circle.count.final.py C01.ccs.cut19.fasta C01.subreads.cut19.fasta C01
minimap2 -ax map-hifi --MD --eqx --secondary=no -t 10 C01.asm.p_ctg.fa C01.ccs.cut19.fasta | samtools view -F4 -F0x900 > C01.ccs.vs.asm.eqx.F4F0x900.sam
python3 rmdup.py C01
python3 ccs_identity.final.py C01.ccs.vs.asm.eqx.F4F0x900.rmdup.sam
minimap2 -ax map-hifi --MD --secondary=no dm6.fa C01.ccs.cut19bp.fastq | samtools view -bS -F0x904 > C01.ccs.cut19bp.fq.dm6.F904.bam
samtools sort C01.ccs.cut19bp.fq.dm6.F904.bam -o C01.ccs.cut19bp.fq.dm6.F904.s.bam
samtools index C01.ccs.cut19bp.fq.dm6.F904.s.bam
samtools depth -a C01.ccs.cut19bp.fq.dm6.F904.s.bam > C01.ccs.cut19bp.fq.dm6.F904.s.depth
rm C01.ccs.cut19bp.fq.dm6.F904.bam
perl relative_depth_1.pl
perl relative_depth_2.pl
perl relative_depth_3.pl
perl GC_bias_1.pl C01.ccs.cut19bp.fq.dm6.F904.s.depth C01.ccs ccs
perl GC_bias_2.pl C01.ccs.500.dgc C01.ccs.500.dgc1 ccs
python3 downsampling.py C01.ccs.cut19.fasta 15
hifiasm -t40 -o C01.ccs.cut19bp.asm -f0 C01.ccs.cut19.fasta
awk '/^S/{print ">"$2;print $3}' C01.ccs.cut19bp.asm.p_ctg.gfa > C01.ccs.cut19bp.asm.p_ctg.fa
awk '/^S/{print ">"$2;print $3}' C01.ccs.cut19bp.asm.a_ctg.gfa > C01.ccs.cut19bp.asm.a_ctg.fa
mkdir C01.ccs.cut19bp.asm
quast.py --large -t 40 -r dm6.fa -o C01.ccs.cut19bp.asm C01.ccs.cut19bp.asm.p_ctg.fa
mkdir C01.ccs.cut19bp.asm.pri.BUSCO542
busco -i C01.ccs.cut19bp.asm.p_ctg.fa -l diptera_odb10 -o C01.ccs.cut19bp.asm.pri.BUSCO542 -m genome -f
sh $MERQURY/best_k.sh 144000000
meryl count k=18 output C01.ccs.cut19bp.k18.meryl C01.ccs.cut19bp.fasta
meryl union-sum output C01.ccs.cut19bp.k18.merge.meryl C01.ccs.cut19bp.k18.meryl
merqury.sh C01.ccs.cut19bp.k18.merge.meryl C01.ccs.cut19bp.asm.p_ctg.fa C01.ccs.cut19bp.hifiasm
meryl count k=15 C01.ccs.cut19bp.asm.p_ctg.fa output C01_lDB
meryl print greater-than distinct=0.9998 C01_lDB > repetitive_k15_C01_lDB.txt
winnowmap --MD -W repetitive_k15_C01_lDB.txt -ax map-pb -t20 C01.ccs.cut19bp.asm.p_ctg.fa C01.ccs.cut19.fasta > C01.ccs.cut19bp.pasm.sam
samtools sort -@20 -m2G -T C01.ccs.cut19bp.pasm.tmp -O bam -o C01.ccs.cut19bp.pasm.sort.bam C01.ccs.cut19bp.pasm.sam
rm C01.ccs.cut19bp.pasm.sam
falconc bam-filter-clipped -F=0x104 -t --output-count-fn=C01.ccs.cut19bp.pasm.sort.bam.filtered_aln_count.txt --output-fn=C01.ccs.cut19bp.pasm.sort.falconcF104.sam --input-fn=C01.ccs.cut19bp.pasm.sort.bam
/softwares/racon_liftover/build/bin/racon -t 20 \
C01.ccs.cut19.fasta \
C01.ccs.cut19bp.pasm.sort.falconcF104.sam \
C01.asm.p_ctg.fa \
-L C01.asm.p_ctg.racon.fa > C01.asm.p_ctg.racon.fa
jellyfish count -m 19 -t 10 -s 10000000000 -C C01.ccs.cut19.fasta -o C01.ccs.cut19.fasta.jf
jellyfish histo -t 10 C01.ccs.cut19.fasta.jf > C01.ccs.cut19.fasta.histo
genomescope2 -i C01.ccs.cut19.fasta.histo -o genomescope2_output -k 19
merfin -polish \
-sequence C01.asm.p_ctg.fa \
-seqmers C01.asm.p_ctg.meryl \
-readmers C01.ccs.cut19.meryl \
-peak 30.3 \
-vcf C01.asm.p_ctg.racon.fa.vcf \
-output C01.asm.p_ctg.fa.merfin.out \
-threads 20
cat C01.0.ccs.fasta C01.1.ccs.fasta C01.4.ccs.fasta > fly_6.ccs.male.fasta
cat C01.2.ccs.fasta C01.3.ccs.fasta C01.5.ccs.fasta > fly_6.ccs.female.fasta
minimap2 -ax map-hifi --MD --secondary=no -t 20 C01.asm.p_ctg.fa fly_6.ccs.male.fasta | samtools view -bS -F0x904 > C01_6.ccs.male.C01.contigs.F904.bam
samtools sort C01_6.ccs.male.C01.contigs.F904.bam -o C01_6.ccs.male.C01.contigs.F904.s.bam
rm C01_6.ccs.male.C01.contigs.F904.bam
samtools depth -a C01_6.ccs.male.C01.contigs.F904.s.bam > C01_6.ccs.male.C01.contigs.depth
minimap2 -ax map-hifi --MD --secondary=no -t 20 C01.asm.p_ctg.fa fly_6.ccs.female.fasta | samtools view -bS -F0x904 > C01_6.ccs.female.C01.contigs.F904.bam
samtools sort C01_6.ccs.female.C01.contigs.F904.bam -o C01_6.ccs.female.C01.contigs.F904.s.bam
rm C01_6.ccs.female.C01.contigs.F904.bam
samtools depth -a C01_6.ccs.female.C01.contigs.F904.s.bam > C01_6.ccs.female.C01.contigs.depth
python3 select_XY.median.py C01 contigs
nucmer --threads 40 --maxmatch --prefix dm62C01 dm6.fa C01.ccs.cut19bp.asm.p_ctg.fa
lastz dm6.fa[multiple] C01.ccs.cut19bp.asm.p_ctg.fa[multiple] --chain --format=general:name1,strand1,start1,end1,name2,strand2,start2,end2 > dm62C01_lastz.txt
svmu dm62C01.delta dm6.fa C01.ccs.cut19bp.asm.p_ctg.fa h dm62C01_lastz.txt C01.ccs.hifiasm
perl SV_results_filter.pl
cat TE_insertion_all.all.bed | awk '{print $1"\t"$2-1001"\t"$3+1000}' > TE_insertion_all.all.2000.bed
bedtools getfasta -fi /rd/yacai/dm6.fa -bed TE_insertion_all.all.2000.bed -fo TE_insertion_all.all.2000.fasta
gfa -seq TE_insertion_all.all.2000.fasta -out TE_insertion_all.all.2000.fasta.out
cat TE_insertion_all.all.2000.fasta.out_*.tsv | grep -v "Source" > TE_insertion_all.all.2000.fasta.all.out
perl allmotifSum1.pl TE_insertion_all.all.2000 > TE_insertion_all.all.2000.fasta.xls1
python3 non-B_DNA_sum2.py
java -jar snpEff.jar BDGP6.32.105 -i vcf pav_c01.txt -csvStats pav_c01.txt.ann.csv -stats pav_c01.txt.ann.html > C01.pav.ann.vcf
cat rmsk.txt | awk '{ss=$7+1; ee=$8; if({if(($6=="chr2L" || $6=="chr2R" || $6=="chr3L" || $6=="chr3R" || $6=="chr4" || $6=="chrX" || $6=="chrY") && ($12=="Satellite")){print $6"\t"ss"\t"ee"\t"$12}}' | bedtools sort | bedtools merge | awk '{print $0"\tSatellite"}' > dm6.rmsk.Satellite.s.merge.bed
cat rmsk.txt | awk '{ss=$7+1; ee=$8; if({if(($6=="chr2L" || $6=="chr2R" || $6=="chr3L" || $6=="chr3R" || $6=="chr4" || $6=="chrX" || $6=="chrY") && ($12=="tSimple_repeat")){print $6"\t"ss"\t"ee"\t"$12}}' | bedtools sort | bedtools merge | awk '{print $0"\tSimple_repeat"}' > dm6.rmsk.Simple_repeat.s.merge.bed
cat rmsk.txt | grep -v "#" | awk '{if(($6=="chr2L" || $6=="chr2R" || $6=="chr3L" || $6=="chr3R" || $6=="chr4" || $6=="chrX" || $6=="chrY") && ($12=="LTR" || $12=="LINE" || $12=="SINE" || $12=="DNA" || $12 == "RC")){print $6"\t"$7"\t"$8"\tTE"}}' | awk '{ss=$2-50; ee=$3+50; print $1"\t"ss"\t"ee}' | bedtools sort | bedtools merge | awk '{print $0"\tTE"}' > dm6.TE.s.merge.50bp.s.merge.bed
cat simple_repeat.tsv | grep -v "#" | awk '{ss=$3+1; ee=$4; print $2"\t"ss"\t"ee"\tTRF"}' | bedtools sort | bedtools merge | awk '{print $0"\tSimple_repeat"}' > dm6.simple_repeat.trf.s.merge.bed
cat dm6.rmsk.Satellite.s.merge.bed dm6.rmsk.Simple_repeat.s.merge.bed dm6.TE.s.merge.50bp.s.merge.bed dm6.simple_repeat.trf.s.merge.bed | awk '{print $1"\t"$2"\t"$3}' | bedtools sort | bedtools merge > dm6.TE.s.merge.50bp.s.merge.simple_repeat.trf.s.merge.rmsk.Satellite_Simple_repeat.merge.bed
minimap2 -ax map-hifi --MD --secondary=no dm6.fa C01.ccs.cut19bp.fastq | samtools view -bS -F0x904 > C01.ccs.cut19bp.fq.dm6.F904.bam
samtools sort C01.ccs.cut19bp.fq.dm6.F904.bam -o C01.ccs.cut19bp.fq.dm6.F904.s.bam
samtools index C01.ccs.cut19bp.fq.dm6.F904.s.bam
rm C01.ccs.cut19bp.fq.dm6.F904.bam
python3 filter_sa_bam1.py C01.ccs.cut19bp.fq.dm6.F904.s.bam ### out file: C01.ccs.cut19bp.fq.dm6.F904.s.Fsa.bam
python3 filter_sa_bam.py C01.ccs.cut19bp.fq.dm6.F904.s.Fsa.bam ### out file: C01.ccs.cut19bp.fq.dm6.F904.s.Fsa.rm_inside_te_simple.bam
cat C01.snp.out | awk '{print $1"\t"$2}' > C01.snp.pos
samtools mpileup --output-MQ --min-MQ 1 --min-BQ 0 -f dm6.fa -l C01.snp.pos C01.ccs.cut19bp.fq.dm6.F904.s.Fsa.rm_inside_te_simple.bam > C01_E01.C01.ccs.cut19bp.fq.dm6.F904.s.Fsa.rm_inside_te_simple.bam.baseq0.mapq0.pileup
python3 validated_non_rmsk_satellite_simple_trf_snp.baseq0.mapq0.py C01.snp.out C01_E01.C01 C01_E01.C01.ccs.cut19bp.fq.dm6.F904.s.Fsa.rm_inside_te_simple.bam.baseq0.mapq0.pileup
python3 out_overlap_bed.py C01_E01.C01.filter.norm.merfin.filter.afdp.ann.vcf.shared_sp.snp.gene.repeat.repeattype.trf.rm_inside_te_simple_repeat.mapq0.baseq0.out dm6.rmsk.Satellite_Simple_repeat.trf.sm.up1500.bed up1500_vntr
cat C01_E01.C01.filter.norm.merfin.filter.afdp.ann.vcf.shared_sp.snp.gene.repeat.repeattype.trf.rm_inside_te_simple_repeat.mapq0.baseq0.up1500_vntr.out | awk '{if($18=="PASS" && $19=="out_up1500_vntr"){truetag="PASS"} else{truetag="FILTER"}}{print $0"\t"truetag}' > C01_E01.C01.filter.norm.merfin.filter.afdp.ann.vcf.shared_sp.snp.gene.repeat.repeattype.trf.rm_inside_te_simple_repeat.mapq0.baseq0.up1500_vntr.out1
python3 get_assembly_snp_vaf.baseq0.mapq0.py C01_E01.C01.snp.gene.repeat.repeattype.trf.rm_inside_te_simple_repeat.mapq0.baseq0.up1500_vntr.TRUE.rm_shared_diff.out C01_E01.C01.ccs.cut19bp.fq.dm6.F904.s.Fsa.rm_inside_te_simple.bam.baseq0.mapq0.pileup
cat C01_E01.C01.filter.norm.merfin.filter.afdp.ann.vcf.shared_sp.snp.gene.repeat.repeattype.trf.rm_inside_te_simple_repeat.mapq0.baseq0.up1500_vntr.TRUE.vaf.out | awk '{if($23>2){print $0}}' > C01_E01.C01.shared_sp.snp.gene.repeat.repeattype.trf.rm_inside_te_simple_repeat.mapq0.baseq0.up1500_vntr.TRUE.vaf.minreads3.out
samtools mpileup --output-MQ --min-MQ 1 --min-BQ 0 --output-QNAME -f dm6.fa -l C01_E01.pav.min3.C01_sp.pos C01.ccs.cut19bp.fq.dm6.F904.s.Fsa.rm_inside_te_simple.bam > C01_E01.pav.min3.C01_sp.pos.qname.pileup
for j in 1-9 1-99 1-299 1-1000
do
filename="C01_E01.pav.min3.C01_sp.gt.out"
pileup_file="C01_E01.pav.min3.C01_sp.pos.qname.pileup"
python3 same_reads_phasing.py $filename $pileup_file $j
done
python3 combine_mnp_files.same_reads.py C01_sp
minimap2 -t 10 --secondary=no -ax map-hifi GCF_016584425.1_ASM1658442v1_genomic.fna C01.ccs.cut19.fasta | samtools view -S -F4 | awk '{print ">"$1; print $10}' > C01.ccs.cut19bp.wol.fasta
minimap2 -t 10 --secondary=no -ax asm5 GCF_016584425.1_ASM1658442v1_genomic.fna C01.ccs.cut19bp.asm.p_ctg.fa | samtools view -S -F4 | awk '{print ">"$1; print $10}' > C01.ccs.cut19bp.asm.wol.fa
nucmer --threads 40 --maxmatch --prefix wMel2C01asm GCF_016584425.1_ASM1658442v1_genomic.fna C01.ccs.cut19bp.asm.wol.fa
lastz GCF_016584425.1_ASM1658442v1_genomic.fna C01.ccs.cut19bp.asm.wol.fa --chain --format=general:name1,strand1,start1,end1,name2,strand2,start2,end2 > wMel2C01asm_lastz.txt
svmu wMel2C01asm.delta GCF_016584425.1_ASM1658442v1_genomic.fna C01.ccs.cut19bp.asm.wol.fa h wMel2C01asm_lastz.txt C01.asm.wol
dnadiff -p wMel2C01asm -d wMel2C01asm.delta
blastn -db /blobtoolkit/nt \
-query C01.ccs.cut19.fasta \
-outfmt "6 qseqid staxids bitscore std" \
-max_target_seqs 10 \
-max_hsps 1 \
-evalue 1e-25 \
-num_threads 16 \
-out C01.ncbi.blastn.out
diamond blastx \
--query C01.ccs.cut19.fasta \
--db /blobtoolkit/uniprot \
--outfmt 6 qseqid staxids bitscore qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore \
--sensitive \
--max-target-seqs 1 \
--evalue 1e-25 \
--threads 16 \
> C01.diamond.blastx.out
blobtools create \
--fasta C01.ccs.cut19.fasta \
--meta C01create.yaml \
C01
blobtools view --remote C01