Genome transposon analysis of blackleg causal pathogen

doi:10.21203/rs.3.rs-3987713/v1

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Genome transposon analysis of blackleg causal pathogen

https://doi.org/10.21203/rs.3.rs-3987713/v1

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Background

To understand genome transposon presence of blackleg pathogen and the relationship between its pathogenicity and transposons, we performed transposon analysis of blackleg pathogen through bioinformatics.

Results

For three pathogen strains, their genome transposon proportion was distantly beyond 4%, the pathogen strain Lmb V23.1.3 indicated the most genome transposons, followed by Lbb B3.5 and Lbb CA1, the LTR retrotransposons proportion was obviously more than other types of transposons and the Ty3/Gypsy retrotransposon proportion was greater than Ty1/Copia retrotransposons. there were no Ty1/Copia retrotransposons in Lbb CA1. Most Ty1/Copia and Ty3/Gypsy retrotransposons presented distinct evolutionary distance among different pathogen strains. Besides, the higher LTR retrotransposon density, the lower gene density, the Solo-LTR retrotransposons were much greater than intact LTR retrotransposons. Both Solo-LTR and intact LTR retrotransposon counts were the highest in Lmb V23.1.3, followed by Lbb B3.5 and Lbb CA1 respectively. Many intact LTR retrotransposons in Lmb V23.1.3 were more ancient than those in Lbb B3.5 and Lbb CA1. However, lots of homologous LTR retrotransposons in Lmb V23.1.3 were younger than those in Lbb B3.5 and Lbb CA1. No common intact LTR retrotransposons were identified between L. maculans species and L. biglobosa species, and significantly few even between two strains of the same pathogen species. Large number of special intact LTR retrotransposons in L. biglobosa were relatively younger than those in L. maculans. In addition, the LINE elements only occurred in Lmb V23.1.3, which was possibly responsible for its stronger pathogenicity.

Conclusions

Some pathogen strains of L. biglobosa species also contained genome transposon of distantly beyond 4%. For both L. biglobosa and L. biglobosa species, the LTR retrotransposon proportion was obviously more than other types of transposons. There was distinct evolutionary distance of LTR retrotransposons and no common intact LTR retrotransposons between two pathogen species. The Ty3/Gypsy retrotransposon proportion was greater than Ty1/Copia retrotransposons. Large number of special intact LTR retrotransposons in L. biglobosa were relatively younger than those in L. maculans. The LINE elements only occurred in Lmb V23.1.3 of L. maculans species, which was possibly responsible for its stronger pathogenicity.

Blackleg pathogen

transposon analysis

bioinformatics

All eukaryotes almost contain transposon elements. For example, transposon sequences accounted for 55% in the genome of zebrafish (Chalopin et al. 2015). In Maize, transposon sequences covered 90% of its genome (San Miguel et al. 1996). For the genome of locusts, the proportion of transposon sequences was 65% (Wang et al. 2014). Transposons were mainly divided into two categories: DNA transposons and RNA-involved retrotransposons, and additionally, DNA transposons were classified into replication transposons and retention transposons. Replication DNA transposons, collectively known as Helitron transposons, finished transposition process through copy-paste mode (Li and Dooner 2009). There were no inverted repeat sequences at both ends, but there were conservative sequences at both ends (5 '- TC starts, 3' - CTRR ends, R represents purine, and CTRR upstream has a hairpin structure) (Kapitonov and Jurka 2001; Fu et al. 2013), The kind of transposons could encode some proteins such as helicases required for transposition process of transposons (Kapitonov and Jurka 2001), and so on. Retention DNA transposons completed transposition process through cut-paste mode, with inverted repeat sequences at both ends of transposons. Most DNA transposons in eukaryotes usually belong to the latter, retention DNA transposons, such as Ac-Ds system in Maize (Lazarow et al. 2013)d element in fruit flies (Onder et al. 2014).

RNA-involved retrotransposons could be divided into LTR retrotransposons and non- LTR retrotransposons based on whether they contained long terminal repeat (LTR) sequences at both ends of transposons. LTR retrotransposons mainly included the seven following superfamilies: Ty1/Copia, Ty3 /Gypsy, Bel/Pao, Retroviridae, Caulioviridae, LARD (Large retrotransposons derivatives), TRIM (Terminal repeat retrotransposons in miniature) (Llorens et al. 2011). Both copia element in Drosophila (Vu and Nuzhdin 2011) and Ty elements of yeast (Smokowski et al. 2021) belonged to the LTR retrotransposons. Besides, LTR retrotransposon was one kind of widely studied transposons, and exist in almost all eukaryotic genomes (Muszewska et al. 2011; Daboussi and Capy 2003). Non-LTR retrotransposons consisted of long interspersed element (LINE) and short interspersed element (SINE). In mammals, non-LTR retrotransposons were more abundant than LTR retrotransposons. The LTR retrotransposon abundance was the highest in plant genomes. Besides, LTR retrotransposons usually concentrated in the telomere region of genome and were the main cause of plant genome expansion. Upon LTR retrotransposon amplification and periodic genome replication, the majority of LTR retrotransposons lost transposition activity due to DNA methylation, small RNA-mediated gene silencing and so on, or were deleted or truncated as a result of abnormal recombination. LTR retrotransposons played an important role in maintaining chromatin structure, centromere function, as well as in regulating expression level of effector protein encoding genes (Zhao and Ma 2013). In addition, based on whether transposons could autonomously perform transposition process, they could also be divided into autonomous transposons and non-autonomous transposons.

According to relevant literature reports, transposon sequences accounted for 32.5% genome of Leptophaeria macaulans ' brassicae ' V23.1.3 (Lmb V23.1.3), while in genomes of other closely related blackleg pathogenic strains, transposon proportion was less than 4% (Grandaubert et al. 2014). For blackleg causal pathogen, large masses of transposons typically contributed to improving its adaption to host plants, especially to oilseed rape crops. With continuous expansion of genome transposons of blackleg causal pathogen, chromosome structures might undergo rearrangement, leading to evolution of pathogenic ability and generation of new susceptible symptoms on host plants (Friesen et al. 2006; Raffaele and Kamoun 2012; Spanu et al. 2010). In genome of blackleg causal pathogen, effector protein encoding genes were usually located near transposon sequences. Some studies showed that transposons of blackleg causal pathogen could affect the expression level of effector protein coding genes at the early stage of infection (Rouxel et al. 2011; Soyer et al. 2014). In general, loads of transposons in fungal genomes could lead to function inactivation of effector protein coding genes, and achieved successful infection for host plants. In addition, those scattered and truncated transposons would accelerate clearance of genome transposons, resulting in smaller and smaller genome size over time.

In order to elaborate the relationship between the pathogenicity of blackleg causal pathogen and its genome transposons, we implemented genome transposon analysis of three different blackleg causal pathogen strains, which included statistics of categories, counts, proportion, divergence, insertion time and other transposon information. Through relevant transposon information, we also analyzed the relationship between transposon density and gene density in different blackleg pathogenic strains. Besides, the evolutionary relationship of intact LTR retrotransposons from different blackleg pathogenic strains was also learned through constructing phylogeny tree. Apart from that, some other associated transposon analysis was also performed in this study.

2.1. Genome transposon annotation of blackleg causal pathogen

In an effort to clarify the transposon size, categories, counts, we enforced genome transposon annotation for three blackleg causal pathogen strains and made statistical analysis based on annotation results.

Firstly, genome transposon annotation of different pathogen strains was conducted by running EDTA program. Pathogen strain genomes were downloaded from NCBI database, including three genomes of Leptophaeria biglobosa 'brassicae' B3.5 (Lbb B3.5), Leptophaeria biglobosa 'brassicae' CA1 (Lbb CA1), and Leptophaeria maculans' brassicae 'V23.1.3 (Lmb V23.1.3). Then, unknown LTR retrotransposons were extracted from transposon library of pathogen and reclassified through software DeepTE. Finally, the pathogen genome was conducted transposon annotation again by homologous alignment with the reclassified transposon library of pathogen. When implementing transposon annotation by the EDTA program, we additionally afforded a SINE_LINE database sorted from website (https://sines.eimb.ru/) for annotating various kinds of transposons. When running the DeepTE program, the fungal classification model of unknown LTR retrotransposons originated from official website of DeepTE (https://github.com/LiLabAtVT/DeepTE). After completing genome transposon annotation of three pathogenic strains, the annotation results were organized and analyzed in R Studio. The parameter settings of EDTA annotation and DeepTE classification were as follows.

EDTA.pl --genome genome.fna --species others --sensitive 0 --anno 1 --threads 20 --curatedlib ../../11.software/SINE_LINE/SINE_LINE.fa

Python /pub/software/DeepTE/DeepTE.py -I LTR_unknown.fa -sp F -m_dir ../../11.software/Model_dir/Fungi_model -fam LTR 1 > DeepTE.log 2>&1

EDTA.pl --genome genome.fna --step anno --overwrite 1 --anno 1 --threads 20

2.2. Statistics of size, proportion and counts of various transposons of blackleg causal pathogen

The above transposon annotation results of three pathogen strains were imported into RStudio, converted into the table format, then merged together. At the same time, genome index files of pathogen were constructed in Linux and were also imported into RStudio for calculating genome size of pathogen. Finally, size, proportion and counts of different types of transposons were counted and displayed in RStudio. The shell command of constructing genome index files was as follows.

samtools faidx genome.fna

2.3. Transposon divergence analysis of blackleg causal pathogen

In order to learn about the divergence between genome transposons and their corresponding ancestor sequences, we carried out transposon divergence analysis for three different blackleg causal pathogen strains.

2.3.1. Analysis of transposon divergence based on identity

Through the above EDTA annotation program, non-redundant transposon libraries of different blackleg causal pathogen strains were obtained. Then, genome transposons of pathogen were made alignment with ancestor sequences in transposon library for calculating identity. Afterwards, transposon divergence of different pathogen strains was statistically analyzed based on identity. The specific steps were as follows. The transposon annotation file gene.fna.mod.EDTA.RM.gff3 from software RepeatMasker of EDTA annotation program was converted into table format and made further arrangement in Rstudio. Finally, the sorted transposon annotation files of three pathogen strains were merged together, and transposon identity of different pathogen strains was counted and displayed in RStudio.

2.3.2. Analysis of transposon divergence based on Kimura coefficient

Firstly, Kimura coefficient was calculated based on alignment results between genome transposons of pathogen and ancestral sequences in transposon library. Then, for each type of transposons, proportion of transposons with different Kimura coefficient was calculated in different pathogen strain genomes. The specific steps were as follows. To start with, Kimura coefficient was calculated based on the following shell commands.

cp ../../23.EDTA/sp_Lbi/genome.fna.mod.EDTA.anno/genome.fna.mod.cat.gz ./

gunzip genome.fna.mod.cat.gz

/pub/software/RepeatMasker/util/calcDivergenceFromAlign.pl -s TE.div genome.fna.mod.cat

grep -P "^\d+|Div" TE.div > TE.divsum

Afterwards, the result file TE.divsum containing size information of various transposons with different kimura coefficients was imported into Rstudio, and made further arrangement. Meanwhile, the genome index files were also imported into RStudio for obtaining genome size of pathogen. Finally, proportion of various transposons with different kimura coefficients were calculated and displayed in RStudio. The shell command of constructing genome index file of pathogen was shown in Statistics of size, proportion and counts of transposons of blackleg causal pathogen.

2.4. Insertion time estimation of intact LTR retrotransposons of blackleg causal pathogen

As mentioned above, LTR retrotransposons were usually the main cause of plant genome expansion. Moreover, LTR retrotransposons played an important role in maintaining chromatin structure, centromere function, as well as in regulating expression level of effector protein encoding genes. So as to additionally understand LTR retrotransposons of blackleg causal pathogen, we performed the insertion time estimation for them. Because the estimation method was based on difference between two long terminal repeat sequences at both ends, we only analyzed the insertion time of intact LTR retrotransposons in this paper.

Firstly, intact LTR retrotransposons were extracted according to the annotation file geneme.fna.mod.EDTA.TEAnno.gff3 and the corresponding pathogen strain genome sequences, and reclassified by using software TEsorter. The relevant shell commands were as follows.

awk \ '$3~"LTR_retrotransposon"' ../../23.EDTA/sp_Lbi/genome.fna.mod.EDTA.TEanno.gff3 | grep "Method = structural" >intact.LTR.gff3

awk -F';' '{print $1}' intact.LTR.gff3 |sed 's/ID=//' |awk '$7!="?"' |awk '{print"JACTNT"$1".1""\t"$4 − 1"\t"$5"\t"$9"\t.\t"$7}' >intact.LTR.bed6

awk -F';' '{print $1}' intact.LTR.gff3|sed 's/ID=//' |awk '$7=="?"'|awk '{print"JACTNT"$1".1""\t"$4 − 1"\t"$5"\t"$9"\t.\t+"}' >>intact.LTR.bed6

bedtools getfasta -fi ../../12.ref/Lbi.genome.fna -bed intact.LTR.bed6 -fo - -name -s | awk -F'::' '{print $1}' | seqtk seq -l 60 > intact.LTR.fa

TEsorter -db rexdb intact.LTR.fa

Afterwards, intact LTR retrotransposon annotation file of pathogen genome was imported into Rstudio, converted into table format, made further arrangement. Then, certain columns such as Sequence name, and so on were extracted from the above sorted results. Similarly, another result file gene.fna.mod.pass.list containing insertion time of intact LTR retrotransposon was imported into RStudio, made arrangement and extracted certain columns such as Insertion time, and so on. Besides, the result file intact.LTR.fa.rexdb.cls.tsv containing classification information of intact LTR retrotransposons was also imported into RStudio, and the above extracted information columns from different result files were merged together. Finally, insertion time of intact LTR retrotransposons was analyzed and displayed in RStudio.

2.5. Phylogeny tree construction of intact LTR retrotransposons of blackleg causal pathogen

For the sake of grasping phylogeny relationship among intact LTR retrotransposons from different blackleg causal pathogen strains, we also implemented phylogeny tree construction for them based on their amino acid sequences of intermediate RT domains.

2.5.1. Phylogeny tree construction of intact Ty1/Copia retrotransposons

To begin with, based on the classification result files intact.LTR.fa.rexdb.dom.tsv and intact.LTR.fa.rexdb.dom.faa of software TEsorter, amino acid sequences of RT domains of intact Ty1/Copia superfamily retrotransposons were extracted in Linux. Afterwards, these obtained amino acid sequences were performed multiple sequence alignment via software Mafft. Eventually, according to the multiple sequence alignment results, phylogeny tree was constructed through software Iqtree and visualized on website server ( https://itol.embl.de/) of software ITOL. The relevant shell commands were as follows.

grep "Ty1_copia" ../../31.intactLTR/sp_Lbi/intact.LTR.fa.rexdb.dom.tsv | grep -P "\-RT\t" | cut -f 1 | seqtk subseq ../../31.intactLTR/sp_Lbi/intact.LTR.fa.rexdb.dom.faa - > LbbCA1.RT.raw.fa

awk -F':' '{print $1}' LbbCA1.RT.raw.fa | sed 's/\Class_I\/LTR\///'|sed 's/>/> LbbCA1-/' > LbbCA1.RT.fa

grep "Ty1_copia" ../../31.intactLTR/sp_Lbib/intact.LTR.fa.rexdb.dom.tsv | grep -P "\-RT\t" | cut -f 1 | seqtk subseq ../../31.intactLTR/sp_Lbib/intact.LTR.fa.rexdb.dom.faa - > LbbB3.5.RT.raw.fa

awk -F':' '{print $1}' LbbB3.5.RT.raw.fa | sed 's/\Class_I\/LTR\///'|sed 's/>/> LbbB3.5-/' > LbbB3.5.RT.fa

grep "Ty1_copia" ../../31.intactLTR/sp_Lma/intact.LTR.fa.rexdb.dom.tsv | grep -P "\-RT\t" | cut -f 1 | seqtk subseq ../../31.intactLTR/sp_Lma/intact.LTR.fa.rexdb.dom.faa - > LmbV23.1.3.RT.raw.fa

awk -F':' '{print $1}' LmbV23.1.3.RT.raw.fa | sed 's/\Class_I\/LTR\///'|sed 's/>/> LmbV23.1.3-/' > LmbV23.1.3.RT.fa

cat LbbCA1.RT.fa LbbB3.5.RT.fa LmbV23.1.3.RT.fa > RT.aln

mafft --auto RT.fa > RT.aln

iqtree -s RT.aln -bb 1000 -nt AUTO -pre Ty1_copia.iqtree 1 > iqtree.log 2>&1 &

2.5.2. Phylogeny tree construction of intact Ty3/Gypsy retrotransposons

Likely, amino acid sequences of RT domains of intact Ty3/Gypsy superfamily retrotransposons were also extracted from the classification result files intact.LTR.fa.rexdb.dom.tsv and intact.LTR.fa.rexdb.dom.faa of software TEsorter. Afterwards, the remaining steps were shown in Phylogeny tree construction of intact Ty1/Copia retrotransposons. The relevant shell commands were as follows.

grep "Ty3_gypsy" ../../31.intactLTR/sp_Lbi/intact.LTR.fa.rexdb.dom.tsv | grep -P "\-RT\t" | cut -f 1 | seqtk subseq ../../31.intactLTR/sp_Lbi/intact.LTR.fa.rexdb.dom.faa - > LbbCA1.RT.raw.fa

awk -F':' '{print $1}' LbbCA1.RT.raw.fa | sed 's/\Class_I\/LTR\///'|sed 's/>/> LbbCA1-/' > LbbCA1.RT.fa

grep "Ty3_gypsy" ../../31.intactLTR/sp_Lbib/intact.LTR.fa.rexdb.dom.tsv | grep -P "\-RT\t" | cut -f 1 | seqtk subseq ../../31.intactLTR/sp_Lbib/intact.LTR.fa.rexdb.dom.faa - > LbbB3.5.RT.raw.fa

awk -F':' '{print $1}' LbbB3.5.RT.raw.fa | sed 's/\Class_I\/LTR\///'|sed 's/>/> LbbB3.5-/' > LbbB3.5.RT.fa

grep "Ty3_gypsy" ../../31.intactLTR/sp_Lma/intact.LTR.fa.rexdb.dom.tsv | grep -P "\-RT\t" | cut -f 1 | seqtk subseq ../../31.intactLTR/sp_Lma/intact.LTR.fa.rexdb.dom.faa - > LmbV23.1.3.RT.raw.fa

awk -F':' '{print $1}' LmbV23.1.3.RT.raw.fa | sed 's/\Class_I\/LTR\///'|sed 's/>/> LmbV23.1.3-/' > LmbV23.1.3.RT.fa

cat LbbCA1.RT.fa LbbB3.5.RT.fa LmbV23.1.3.RT.fa > RT.aln

mafft --auto RT.fa > RT.aln

iqtree -s RT.aln -bb 1000 -nt AUTO -pre Ty1_copia.iqtree 1 > iqtree.log 2>&1 &

2.6. Gene density and LTR retrotransposon density statistics of blackleg causal pathogen

Commonly, the lower LTR retrotransposon density, the higher gene density. In an effort to figure out the relationship between gene density and LTR retrotransposon density of blackleg causal pathogen, we executed statistical analysis of gene density and LTR retrotransposon density for three blackleg causal pathogen strains. Firstly, contigs greater than or equal to 1M were selected out and conducted sliding window analysis with size of 1M and step length of 200K. Then the position and other information of sliding windows were sorted into a bed format file. Combined with gene structure annotation file and LTR retrotransposon annotation file, gene density and LTR retrotransposon density of sliding windows were analyzed and displayed in RStudio. There was no available gene structure annotation file for pathogen strain Lbb B3.5 in NCBI database. Therefore, the gene structure annotation file of Lbb B3.5 was obtained by making advantage of software BRAKER and MAKER. The specific annotation process was shown in our previous work (Tian et al, unpublished). The relevant shell commands in the analysis were as follows.

samtools faidx ../../12.ref/Lbi.genome.fna

awk '{print $1"\t"$2}' ../../12.ref/Lbi.genome.fna.fai |awk -F"\t" '{if($2 > = 1000000) print $1"\t"$2}' >genome.txt

bedtools makewindows -g genome.txt -w 1000000 -s 200000 > chr_sw.bed3

awk '{print $1"\t"$2"\t"$3"\t"NR"\t.\t."}' chr_sw.bed3 > chr_sw.bed6

awk '$3=="gene"' ../../12.ref/Lbi.genes.gtf|bedtools coverage -a chr_sw.bed6 -b - -counts -F 0.5 > chr_sw.gene.density.txt

awk '$3=="Copia_LTR_retrotransposon"' ../../31.intactLTR/sp_Lbi/modify_intact.LTR.gff3 | bedtools coverage -a chr_sw.bed6 -b - -counts -F 0.5 > chr_sw.intact_Copia.density.txt

awk '$3=="Copia_LTR_retrotransposon"' ../../23.EDTA/sp_Lbi/modify_genome.fna.mod.EDTA.TEanno.gff3 | bedtools coverage -a chr_sw.bed6 -b - -counts -F 0.5 > chr_sw.truncated_Copia.density.txt

awk '$3=="Gypsy_LTR_retrotransposon"' ../../31.intactLTR/sp_Lbi/modify_intact.LTR.gff3 | bedtools coverage -a chr_sw.bed6 -b - -counts -F 0.5 > chr_sw.intact_Gypsy.density.txt

awk '$3=="Gypsy_LTR_retrotransposon"' ../../23.EDTA/sp_Lbi/modify_genome.fna.mod.EDTA.TEanno.gff3 | bedtools coverage -a chr_sw.bed6 -b - -counts -F 0.5 > chr_sw.truncated_Gypsy.density.txt

awk '{print $7}' chr_sw.truncated_Copia.density.txt > truncated_Copia.density.txt

awk '{print $1}' truncated_Copia.density.txt |paste - chr_sw.intact_Copia.density.txt |awk '{print $8=$8+$1; print $0}' |awk '{print $1 = null; print$0}' |awk -v OFS="\t" '$1=$1' >chr_sw.Copia.density.txt

awk '{print $7}' chr_sw.truncated_Gypsy.density.txt > truncated_Gypsy.density.txt

awk '{print $1}' truncated_Gypsy.density.txt |paste - chr_sw.intact_Gypsy.density.txt |awk '{print $8=$8+$1; print $0}' |awk '{print $1 = null; print$0}' |awk -v OFS="\t" '$1=$1' >chr_sw.Gypsy.density.txt

2.7. Solo-LTR counts and intact LTR retrotransposon counts statistics of blackleg causal pathogen

To further understand the LTR retrotransposons in blackleg causal pathogen, the LTR retrotransposon were also divided into solo-LTR and intact LTR retrotransposons. Afterwards, we carried out the statistical analysis of solo-LTR and intact LTR retrotransposons in three pathogen strains. Firstly, based on the genome transposon annotation file and the transposon library index file of blackleg causal pathogen, the R script solo_intact_ltr_edta.R was enforced to generate the result file soloLTR_RM.tsv containing position of INT domain of LTR retrotransposons, distance, upstream and downstream, away from the nearest long terminal repeat sequence and so on. Afterwards, the obtained result file soloLTR_RM.tsv was combined with the intact LTR retrotransposon annotation intact.LTR.gff3 to analyze solo-LTR retrotransposon counts and intact LTR retrotransposon counts. Finally, solo-LTR retrotransposon counts and intact LTR retrotransposon counts were analyzed and displayed in RStudio. The relevant shell commands were as follows.

ln -s ../../23.EDTA/sp_Lbi/genome.fna.mod.EDTA.anno/genome.fna.mod.EDTA.RM.gff3

ln -s ../../23.EDTA/sp_Lbi/genome.fna.mod.EDTA.final/genome.fna.mod.EDTA.TElib.fa

samtools faidx genome.fna.mod.EDTA.TElib.fa

Rscript ../../11.software/solo_intact_ltr_edta.R -g genome.fna.mod.EDTA.RM.gff3 -T genome.fna.mod.EDTA.TElib.fa.fai

The main function of R script solo_intact_ltr_edta.R was as follows. Through the genome transposon annotation file and the genome index file of pathogen, INT domains and long end repeat sequences of pathogen genome were extracted, ending up with a annotation file containing positions of INT domains and long end repeat sequences, alignment scores, coverage, etc. Meanwhile, the distance between the INT domain and its upstream and downstream nearest long terminal repeat sequences was also calculated. If only upstream or downstream long terminal repeat sequence of INT domain was within the given distance range, then the LTR retrotransposon in the position was considered as the Solo-LTR retrotransposon. The R script would finally produce a solo-LTR retrotransposon annotation file containing location of INT domain, the distance between the INT domain and its upstream and downstream the nearest long terminal repeat sequence, and so on.

2.8. Pan-genome transposon analysis of blackleg causal pathogen

So as to identify more genome transposons and perform common and special transposon statistical analysis among different pathogen strains, we conducted pan-genome transposon analysis of blackleg causal pathogen by using four genomes: Lmb V23.1.3, Leptosphaeria maculans ‘brassicae’ CAN1 (Lmb CAN1), Lbb CA1, and Lbb B3.5. Firstly, Transposon library of each pathogen strain was constructed by software EDTA, and then the four transposon libraries were clustered to construct pan-genome transposon library. Upon utilizing the constructed pan-genome transposon library, each pathogen strain was made transposon annotation again by running EDTA program. Then common and special intact LTR retrotransposons among four pathogen strains and their insertion time were counted and analyzed based on the second annotation results. When initially constructing transposon library of pathogen strains, the parameter setting of software EDTA referred to Genome transposon annotation of blackleg causal pathogen, except for the parameters anno and curatedlib. The parameter value of anno was changed from 1 to 0. And the parameter curatedlib was removed. The related shell commands were as follows.

ln -s ../23.EDTA/Lbb_B35/genome.fna.mod.EDTA.TElib.fa Lbb_B35.genome.fna.mod.EDTA.TElib.fa

ln -s ../23.EDTA/Lbb_CA1/genome.fna.mod.EDTA.TElib.fa Lbb_CA1.genome.fna.mod.EDTA.TElib.fa

ln -s ../23.EDTA/Lmb_CAN1/genome.fna.mod.EDTA.TElib.fa Lmb_CAN1.genome.fna.mod.EDTA.TElib.fa

ln -s ../23.EDTA/Lmb_V2313/genome.fna.mod.EDTA.TElib.fa Lmb_V2313.genome.fna.mod.EDTA.TElib.fa

ln -s ../../TEAnalysis/11.software/SINE_LINE/SINE_LINE.fa

ls *.TElib.fa > liblist.txt

perl /pub/anaconda3/envs/EDTA/share/EDTA/util/make_panTElib.pl -liblist liblist.txt -mincov 0.70 -miniden 70 -threads 20 --curatedlib SINE_LINE.fa

The shell commands of genome transposon reannotation of pathogen were as follows.

source activate EDTA

cd genome.fna.mod.EDTA.combine

rm genome.fna.mod.LTR.TIR.Helitron.fa.stg1

ln -s ../../../24.make_panTElib/liblist.txt.panTE.fa genome.fna.mod.LTR.TIR.Helitron.fa.stg1

cd ..

EDTA.pl --genome genome.fna --species others --sensitive 0 --anno 1 --step final --force 1 --threads 20 --overwrite 1

source deactivate

2.8.1. Analysis of common and special pan-genome intact LTR retrotransposons in blackleg causal pathogen

Pan-genome intact LTR retrotransposons of four pathogen strains were extracted through shell commands and reclassified through software TEsorter. The specific steps were shown in the above Insertion time estimation of intact LTR retrotransposons of blackleg causal pathogen. Afterwards, pan-genome intact LTR retrotransposon IDs of pathogen strain were extracted and removed redundancy in RStudio. Finally, common and special pan-genome intact LTR retrotransposon counts were visualized by Venn plot.

2.8.2. Insertion time estimation of common and special pan-genome intact LTR retrotransposons of blackleg causal pathogen

In RStudio, the pan-genome intact LTR retrotransposon annotation file including insertion time was made arrangement referring to Insertion time estimation of intact LTR retrotransposons of blackleg causal pathogen. Afterwards, insertion time of pan-genome intact LTR retrotransposons was displayed in RStudio.

3.1. Genome transposon percent of blackleg causal pathogen

According to the EDTA annotation results of three blackleg causal pathogen strains, the pathogen strain Lbb V23.1.3, more progressive, showed the highest transposon percent, near to 30% (Fig. 1C), while the pathogen strain Lbb CA1, weakly pathogenic, had the lowest transposon percent, less than 10% (Fig. 1B). Another pathogen strain Lbb B3.5, causal pathogen of blackleg disease in Chinese cabbage (Tian et al. unpublished), supposedly weakly pathogenic, its transposon percent was clearly higher than that of Lbb CA1 but significantly lower than that of Lmb V23.1.3 (Fig. 1A).

3.2. Size, proportion, counts of various transposons of blackleg causal pathogen

Among different types of transposons, size, proportion, and counts of LTR retrotransposons were significantly greater than DNA transposons and other types of transposons for all three pathogen strains (Fig. 2, 3, 4). Amid diverse LTR retrotransposons, size, proportion, and counts of Ty3/Gypsy family retrotransposons were higher than that of Ty1/Copia superfamily retrotransposons in three blackleg causal pathogen strain genomes (Fig. 2, 3, 4). Usually, the counts and activity of LTR retrotransposons played an important role for genome expansion. In filamentous fungal genomes, there were two major superfamilies of LTR retrotransposons: Ty1/Copia and Ty3/Gypsy, and the latter also held more abundance. In addition, the LINE elements, non-LTR retrotransposons, only appeared in genome of strongly pathogenic pathogen strain Lmb V23.1.3, but no LINE elements were identified in genomes of weakly pathogenic pathogen strains Lbb B3.5 and Lbb CA1 (Fig. 2, 3, 4), which was possibly responsible for stronger progressiveness of Lmb V23.1.3. The LINE element was the most active transposon in human genomes (Ramos et al. 2021), participating in regulation of telomere structure, and leading to malignant cell proliferation (Mueller et al. 2018) and tumor formation. Therefore, we speculated that the LINE elements in Lmb V23.1.3 could maintain telomere structure of genome, producing unlimited cell proliferation, and resulting in stronger pathogenicity.

3.3. Transposon divergence of blackleg causal pathogen

For different transposons, taking LTR retrotransposons as example, the identity of most of homologous transposons in pathogen strain Lmb V23.1.3 was around 0.95 (Fig. 5) with ancestral sequences of transposon library, while the identity of large bulks of homologous transposons in pathogen strains Lbb B3.5 and Lbb CA1 was less than 0.90 (Fig. 5). Therefore, masses of homologous transposons in strongly pathogenic pathogen strain were younger than that in weakly pathogenic pathogen strain. In fact, the majority of homologous transposons in all three pathogen strain genomes had the identity greater than 0.70 (Fig. 5). So, most of homologous transposons in blackleg causal pathogen were all relatively young.

As opposed to ancestral sequences of transposon library, the divergence of a great many of transposons in three pathogen strains was all parallelly low (Fig. 6, 7, 8), which from another perspective indicated that a great majority of homologous transposons in blackleg causal pathogen were all comparatively young. In addition, the three pathogen strain genomes all experienced a recent transposon outbreak. For pathogen strains Lbb B3.5 and Lmb V23.1.3, there was also another larger transposon outbreak before the recent outbreak event. The difference was that the time interval between two transposon outbreaks in Lmb V23.1.3 was shorter than that in Lbb B3.5 (Fig. 6, 8). Due to the longer time interval between two transposon outbreaks in Lbb B3.5, some existed transposons have possibly been cleared when the second transposon outbreak happened, Therefore, the 34M genome size of Lbb B3.5 was smaller than the 44M genome size of Lmb V23.1.3. The 32M genome size of Lbb CA1 was the smallest in the three pathogen strains. There was only one recent transposon outbreak in Lbb CA1(Fig. 7).

3.4. Insertion time of intact LTR retrotransposons of blackleg causal pathogen

The intact LTR retrotransposons in blackleg causal pathogen strains Lbb B3.5 and Lmb V23.1.3, especially intact Ty3/Gypsy retrotransposons, experienced two obvious outbreaks, one of which occurred recently (Fig. 9). The difference was that the time of intact LTR retrotransposon outbreaks in Lbb V23.1.3 was earlier than that in Lbb B3.5. what’s more, the insertion time of most intact LTR retrotransposons in V23.1.3, especially LTR/ Copia retrotransposons, were earlier than that in both Lbb B3.5 and Lbb CA1 (Fig. 9). So, the majority of intact LTR retrotransposons in the strongly pathogenic pathogen strain were more ancient than that in the weakly pathogenic pathogen strain.

In addition, the intact LTR retrotransposons in Lbb CA1 only experienced one obvious outbreak. Moreover, there were no intact Ty1/Copia retrotransposons and only Ty3/Gypsy retrotransposons were identified in Lbb CA1 (Fig. 9). For pathogen strains Lbb B3.5 and Lmb V23.1.3, there were both intact Ty1/Copia and Ty3/Gypsy superfamily retrotransposons (Fig. 9). The LTR retrotransposons played a significant role for genome expansion, the higher LTR retrotransposon proportion and the more category counts, the larger genome size. In our opinion, the fewer category counts and outbreak frequency of intact LTR retrotransposons were possibly responsible for the smallest genome size of Lbb CA1.

3.5. Evolutionary relationship of intact LTR retrotransposons of blackleg causal pathogen

3.5.1. Evolutionary relationship of intact Ty1/Copia retrotransposons

Without Ty1/Copia retrotransposons in pathogen strain Lbb CA1, so the constructed phylogeny tree of intact Ty1/Copia retrotransposons only contained pathogen strains Lbb B3.5 and Lmb V23.1.3 (Fig. 10). According to the phylogeny tree of intact Ty1/Copia retrotransposons, the RT domain amino acid sequences of large bulks of intact Ty1/Copia retrotransposons in pathogen strains Lbb B3.5 and Lmb V23.1.3 were separately clustered into one branch (Fig. 10), Therefore, there was larger difference between the majority of intact LTR retrotransposons in Lmb V23.1.3 and Lbb B3.5. However, one intact Ty1/Copia retrotransposon in Lmb V23.1.3 showed closer distance with intact Ty1/Copia transposons in Lbb B3.5 as opposed to the other intact Ty1/Copia retrotransposons in Lmb V23.1.3. The possible reason was inferred as follows. Commonly, the causal pathogen of blackleg disease was not a single pathogen strain but a complexity of several pathogen strains. Hence, it was possible that horizontal transfer events of intact Ty1/Copia retrotransposons occurred between pathogen strains Lmb V23.1.3 and Lbb B3.5. In addition, Ty1/Copia retrotransposons in a large branch were clustered into many small branches, which indicated there were also various levels of divergence among different transposons in one pathogen strain. This might be related to insertion time difference of Ty1/Copia retrotransposons. If transposon accumulated too much variation, it might lose transposase activity, resulting in inability to autonomously perform transposition.

3.5.2. Evolutionary relationship of intact Ty3/Gypsy retrotransposons

Intact Ty3/Gypsy retrotransposons of three blackleg causal pathogen strains were not separately clustered into a large branch in the constructed phylogeny tree of Ty3/Gypsy retrotransposons (Fig. 11). However, in the four larger subbranches of the phylogeny tree, two of which contained intact Ty3/Gypsy retrotransposons of strongly pathogenic pathogen strain Lmb V23.1.3 and weakly pathogenic pathogen strains Lbb B3.5 and Lbb CA1, respectively. For another two larger subbranches, though their transposons from two kinds of pathogen strains, intact Ty3/Gypsy retrotransposons of strongly pathogenic pathogen strain Lmb V23.1.3 were clustered together, and those of weakly pathogenic pathogen strains Lbb B3.5 and Lbb CA1 were also clustered together (Fig. 11). Consequently, there were also relatively distinct difference among intact Ty3/Gypsy retrotransposons from different blackleg causal pathogen strains. Similarly, some intact Ty3/Gypsy retrotransposons in Lmb V23.1.3 were yet clustered together with those in Lbb B3.5 and Lbb CA1. The likely factor was speculated as follows. As mentioned above, the causal pathogen of blackleg disease was usually a complexity of several pathogen strains, so the intact Ty3/Gypsy retrotransposons might undergo horizontal transfer, producing a closer distance between different blackleg causal pathogen strains. Like the intact Ty1/Copia retrotransposons, a large branch of intact Ty3/Gypsy retrotransposons in one pathogen strain were also classified into many small branches, which might be relevant to insertion time difference of intact Ty3/Gypsy retrotransposons, resulting in different levels of divergence among various transposons.

3.6. The negative relationship between gene density and LTR retrotransposon density of blackleg causal pathogen

For the strongly pathogenic pathogen strain Lmb V23.1.3, although the density of LTR/Gypsy retrotransposons was clearly more than that of Ty1/Copia retrotransposons, the change trend of Ty1/Copia retrotransposon density was consistent with that of Ty3/Gypsy retrotransposon density (Fig. 12). Besides, the LTR retrotransposon density was negatively related with gene density in Lmb V23.1.3 (Fig. 12), in other words, the higher LTR retrotransposon density but the lower gene density. Conversely, there was no obvious negative relationship between gene density and LTR retrotransposon density for some small size of contig fragments (Fig. 12). In summary, insertion of LTR retrotransposons could negatively affect the gene density of pathogen strain Lmb V23.1.3.

For the weakly pathogenic pathogen strain Lbb CA1, no Ty1/Copia retrotransposons were identified in its genome, and there were only Ty3/Gypsy retrotransposons (Fig. 13). What’s more, the Ty3/Gypsy retrotransposon counts in Lbb CA1 was distinctly lower than that in Lmb V23.1.3. Equally, the relationship between gene density and LTR retrotransposon density was also negatively correlated in the pathogen strain Lbb CA1 (Fig. 13). With fewer categories and less counts of LTR retrotransposons, the negative relationship was not as obvious as that in Lmb V23.1.3. Especially in some small size of contig fragments, the negative relationship was more not obvious.

In terms of another weakly pathogenic pathogen strain Lbb B3.5, there were also both Ty1/Copia and Ty3/Gypsy retrotransposons (Fig. 14). Similar to Lmb V23.1.3, the Ty3/Gypsy retrotransposon counts was significantly higher than Ty1/Copia retrotransposon counts in Lbb B3.5 (Fig. 14). The LTR retrotransposon density and gene density of Lbb B3.5 were the lowest in three blackleg causal pathogen strains (Fig. 12, 13, 14). Besides, there were also fewer contig fragments (above or equal to 1M) in Lbb B3.5 in contrast to the two other pathogen strains. However, it could be seen that there was still a negative relationship between gene density and LTR retrotransposon density (Fig. 14).

To sum up, the gene density was negatively correlated with LTR retrotransposon density in three blackleg causal pathogen strains. Besides, with the contig level of genome sequences in this analysis, the negative relationship was not very clear in some small size of contig fragments.

3.7. Solo-LTR counts and intact LTR retrotransposons counts of blackleg causal pathogen

The solo-LTR retrotransposon counts were much greater than intact LTR retrotransposon counts in all three blackleg causal pathogen strains (Fig. 15). The relevant reason was inferred as follows. Genome regions rich in AT bases and GC bases alternatively occurred in blackleg causal pathogen, known as isochore structures, and transposons were mostly located in the region of AT isochore. As a result of repeat-induced point mutation, the long terminal repeat sequences of a great majority of intact LTR retrotransposons were disrupted, forming a lot of truncated LTR retrotransposons, so the solo-LTR retrotransposon counts was much greater. Both solo-LTR retrotransposon counts and intact LTR retrotransposon counts were the highest in the strongly pathogenic strain Lmb V23.1.3, then followed by the weakly pathogenic strains Lbb B3.5 and the Lbb CA1, respectively (Fig. 15). With important role of LTR retrotransposons for genome expansion, then a greater number of LTR retrotransposons resulted in the larger genome size of Lmb V23.1.3, and a smaller number of LTR retrotransposons led to the smaller genome size of Lbb CA1.

3.8. Pan-genome transposon analysis results of blackleg causal pathogen

According to pan-genome transposon annotation results of four blackleg causal pathogen strains, the transposon proportion of Lbb B3.5, Lbb CA1, Lmb CAN1 and Lmb V23.1.3 was 14.28%, 7.68%, 24.92% and 28.38%, respectively (Fig. 16). For the three pathogen strains Lbb B3.5, Lbb CA1, Lmb V23.1.3, the pan-genome transposon proportion was all lower than that annotated with their own single transposon library (Fig. 1). The inconsistent results were discussed in section of Discussion.

3.8.1. Common and special intact LTR retrotransposons of blackleg causal pathogen

There were no common intact LTR retrotransposons among four different blackleg causal pathogen strains. Even for different strains of same causal pathogen species, the common intact LTR retrotransposon were still quite few (Fig. 17). Only three common intact LTR retrotransposons were identified between Lmb V23.1.3 and Lmb CAN1, and there were also only two common intact LTR retrotransposons between Lbb CA1 and Lbb B3.5 (Fig. 17). However, we didn’t identify any common intact LTR retrotransposons between four different blackleg causal pathogen strains. Consequently, the majority of intact LTR retrotransposons were special and only occurred in a unique blackleg causal pathogen strain.

3.8.2. Insertion time of common and special intact LTR retrotransposons of blackleg causal pathogen

Without common intact LTR retrotransposons among four blackleg causal pathogen strains, so there were only insertion time information of special intact LTR retrotransposons in Fig. 18. It could be seen that the insertion time of most of special intact LTR retrotransposons in Lbb CA1and Lbb B3.5 was obviously later than that in LmbV23.1.3 and Lmb CAN1 (Fig. 18). Therefore, lots of special intact LTR retrotransposons of L. biglobsosa, weakly pathogenic, were relatively younger than those of L. macaulans, strongly pathogenic. Besides, only the pathogen strain Lbb B3.5 recently experienced the outbreak of intact LTR retrotransposons for four blackleg causal pathogen strains. Since 0.5 million years ago, there was already no insertion of intact LTR retrotransposons in pathogen strain Lbb CA1. When large amounts of intact LTR retrotransposons broke into genomes of LmbV23.1.3 and Lmb CAN1, there was also one outbreak of intact LTR retrotransposons in Lbb B3.5.

In this study, genome transposons of different blackleg causal pathogen strains were analyzed through bioinformatics methods. According to our analysis results, among two strains of weakly pathogen species Leptosphaeria biglobosa, the genome transposon proportion of pathogen strain Lbb B3.5 reached over 17% (Fig. 1A), and the transposon proportion of pathogen strain Lbb CA1 was 9.27% (Fig. 1B), all more than 4%. In some literature reports, the genome transposon proportion of blackleg causal pathogen other than Leptosphaeria macaulans species was distinctly low, usually less than 4% (Grandaubert et al. 2014). The possible reason was inferred as follows. Possibly, a higher transposase activity in Leptosphaeria bioglobosa species resulted in more quick transposon expansion of Lbb B3.5 and Lbb CA1. In addition, annotation method might also produce influence on the genome transposon proportion. The EDTA software used in the analysis combined structural identification and homologous alignment. Compared with the single structural identification or homologous alignment (Flutre et al. 2011), the EDTA software were more likely to identify more transposons.

In our study, the negative relationship between gene density and LTR retrotransposon density was not very clear in blackleg causal pathogen, especially in Lbb B3.5 (Fig. 12, 13, 14). While in many species such as Arabidopsis thaliana, there was usually an obvious negative relationship between gene density and LTR retrotransposon density (Quesneville 2020; Daccord et al. 2017), indicating that the presence of LTR retrotransposons reduced gene density of genome. The possible factor was inferred as follows. The genome sequences of blackleg causal pathogen used for analysis were various sizes of contig fragments. Moreover, there were many small sizes of contig fragments (less than 1M). So, the negative relationship between gene density and LTR retrotransposon density could not be fully reflected through parts of contig fragments in genome.

When conducting transposon annotation with pan-genome transposon library, the transposon proportion of blackleg causal pathogen did not increase, even showed different levels of drop for three pathogen strains (Fig. 16), compared with transposon proportion with their own single transposon library ((Fig. 1). In general, the transposon proportion with pan-genome transposon library was higher than that with single transposon library. With only four blackleg causal pathogen strain genomes, so it was less likely to identify more new transposons. Besides, we adopted a lower value for the parameter miniden when constructing pan-genome transposon library. Hence, some ancient transposons in pathogen strain were not got annotation as a result of their lower similarity with sequences in pan-genome transposon library, resulting in a decreased transposon proportion.

Generally, compared with the blackleg causal pathogen species L. biglobosa, another blackleg causal pathogen species L. maculans demonstrated the stronger pathogenicity on host plants, especially on B.napus crops. The possible reasons were as follows. Firstly, according to genome transposon analysis of pathogen strains, LINE elements only occurred in the genome of pathogen strain Lmb V23.1.3 (Fig. 2, 3, 4). the LINE element participated in the regulation of telomere structure, producing malignant cell proliferation (Mueller et al. 2018) and leading to the stronger pathogenicity. Secondly, the pathogen strain Lmb 23.1.3 held the highest transposons counts in an earlier time ago. Large masses of transposons in pathogen genome contributed to improving adaption ability to host plants, forming stronger pathogenicity (Grandaubert et al. 2014; Kang et al. 2001; Zhou et al. 2007). Finally, the B.napus crops, the most common host plants of blackleg causal pathogen, have a longer growth period, and the leaves, petioles, stems, and pods of oilseed rape were easily infected by blackleg causal pathogen. So, the blackleg causal pathogen species Leptosphaeria maculans could survive in rapeseed crops for a rather long time (Hamond and Lewis 1987; Rouxel and Balesdent 2005; Elliott et al. 2007; West et al. 2002), gradually evolving into more pathogenic strains.

Typically, the proportion of LTR retrotransposons in plant genomes was relatively high (Galindo Gonz á lez et al. 2017; Zhao and Ma 2017), while in animal genomes, most of retrotransposons were non-LTR retrotransposons such as LINE, Alu, SVA, and other elements (Cordaux and Batzer 2009). The LTR retrotransposon proportion in most fungal genomes were also very small (Muszewska et al. 2011). However, the proportion of LTR retrotransposons was the highest for all three blackleg causal pathogen strains (Fig. 2, 3, 4). The relevant reasons were inferred as follows. With the blackleg causal pathogen surviving in cruciferous plants, especially in rapeseed crops, for a longer period, horizontal transfer of LTR retrotransposons possibly took place between pathogen strains and host plants, resulting in larger number of LTR retrotransposons in blackleg causal pathogen.

The majority of intact LTR retrotransposons in strongly pathogenic strain Lmb V23.1.3 were more ancient than in weakly pathogenic strains Lbb B3.5 and Lbb CA1. However, most of homologous LTR retrotransposons in pathogen strain Lmb V23.1.3 were younger than in pathogen strains Lbb B3.5 and Lbb CA1. In our explanation, when LTR retrotransposons broke into the genome of Lmb V23.1.3, although much variation was gradually accumulated in long terminal repeat sequences of LTR retrotransposon, the intermediate domains were still relatively conservative over time. Among three blackleg causal pathogen strains, the pathogen strain Lbb B3.5 was also the blackleg causal pathogen of Chinese cabbage. In our previous work, we isolated and identified the blackleg causal pathogen of Chinese cabbage, and the results showed that the causal pathogen strain was the Lbb B3.5, belonged to the Leptosphaeria biglobosa species (Tian et al. unpublished). Afterwards, we also carried out the localization of blackleg-resistant candidate interval in Chinese cabbage, the results indicated that the blackleg-resistant candidate interval, containing 7 resistance-related genes, was situated on chromosome A06 (Tian et al. unpublished). Finally, we performed candidate blackleg-resistant gene screening through interaction docking between resistance proteins and effector proteins, and the results showed that the blackleg-resistant genes BraA06g035480.3C and BraA06g035550.3C within the candidate interval displayed the stronger interaction with effector proteins of blackleg causal pathogen strain Lbb B3.5 (Tian et al. unpublished).

According to our previous pathogenicity testing results, the blackleg causal pathogen strain Lbb B3.5 showed the obvious susceptible symptoms on both cotyledons and true leaves of Chinese cabbage seedlings (Tian et al. unpublished). Combined with the transposon analysis of pathogen strain Lbb B3.5 in this study, the genome transposon proportion of Lbb B3.5 was distinctly higher than that of pathogen strain Lbb CA1, but lower than that of pathogen strain Lmb V23.1.3. Usually, the large number of transposons in pathogen contributed to promoting the pathogenicity evolution, leading to the disfunction of resistance genes and generation of disease symptoms. From the perspective of transposons, we speculated that though the pathogen strain Lbb B3.5 was not as progressive as pathogen strain Lmb V23.1.3, but its pathogenicity was stronger than that of pathogen strain Lbb CA1.

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The study was not involved in relevant bioethics legislation and standards.

Consent for publication

All authors have agreed with the submission to the journal.

Availability of Data

The relevant genome sequence files and gene structure annotation files of blackleg pathogen strains in this paper are openly available in NCBI database (https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/022/343/325/GCA_022343325.1_CAIQ.LN.1/GCA_022343325.1_CAIQ.LN.1_genomic.fna.gz;https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/
022/343/325/GC
A_022343325.1_CAIQ.LN.1/GCA_022343325.1_CAIQ.LN.1_genomic.gtf.gz;https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/900/465/125/
GCA_900465125.1_G12-14_Genome_assembly/GCA_900465125.1_G12-14_Genome_assembly_genomic.fna.gz;https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/230/375/GCF_000230375.1_ASM23037v1/GCF_0002
30375.1_ASM23037v1_genomic.fna.gz;https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/230/375/GCF_000230375.1_ASM23037v1/GCF_
000230375.1_ASM23037v1_genomic.gtf.gz;https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/022/343/315/GCA_022343315.1_CAIQ.LM.1/
GCA_022343315.1_CAIQ.LM.1_genomic.fna.gz ).

Competing interests

The authors declared that there is no conflict of interest.

Funding

Not applicable.

Authors' contributions

Lugang Zhang, financial support as well as paper review; Ru Li and Lingyu Hao, providing assistance in data analysis and paper writing; Min Tian, enforcement of data analysis, conceptualization and drafting of manuscript.

Acknowledgements

For fulfillment of research work in this paper, I would also like to express gratitude to the bioinformatic platform Genek (https://genek.cn/) for support of sequence and data analysis.

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Genome transposon analysis of blackleg causal pathogen

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Abstract

Background

Results

Conclusions

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1. Introduction

2. Materials and Materials

2.1. Genome transposon annotation of blackleg causal pathogen

2.2. Statistics of size, proportion and counts of various transposons of blackleg causal pathogen

2.3. Transposon divergence analysis of blackleg causal pathogen

2.3.1. Analysis of transposon divergence based on identity

2.3.2. Analysis of transposon divergence based on Kimura coefficient

2.4. Insertion time estimation of intact LTR retrotransposons of blackleg causal pathogen

2.5. Phylogeny tree construction of intact LTR retrotransposons of blackleg causal pathogen

2.5.1. Phylogeny tree construction of intact Ty1/Copia retrotransposons

2.5.2. Phylogeny tree construction of intact Ty3/Gypsy retrotransposons

2.6. Gene density and LTR retrotransposon density statistics of blackleg causal pathogen

2.7. Solo-LTR counts and intact LTR retrotransposon counts statistics of blackleg causal pathogen

2.8. Pan-genome transposon analysis of blackleg causal pathogen

2.8.1. Analysis of common and special pan-genome intact LTR retrotransposons in blackleg causal pathogen

2.8.2. Insertion time estimation of common and special pan-genome intact LTR retrotransposons of blackleg causal pathogen

3. Results

3.1. Genome transposon percent of blackleg causal pathogen

3.2. Size, proportion, counts of various transposons of blackleg causal pathogen

3.3. Transposon divergence of blackleg causal pathogen

3.4. Insertion time of intact LTR retrotransposons of blackleg causal pathogen

3.5. Evolutionary relationship of intact LTR retrotransposons of blackleg causal pathogen

3.5.1. Evolutionary relationship of intact Ty1/Copia retrotransposons

3.5.2. Evolutionary relationship of intact Ty3/Gypsy retrotransposons

3.6. The negative relationship between gene density and LTR retrotransposon density of blackleg causal pathogen

3.7. Solo-LTR counts and intact LTR retrotransposons counts of blackleg causal pathogen

3.8. Pan-genome transposon analysis results of blackleg causal pathogen

3.8.1. Common and special intact LTR retrotransposons of blackleg causal pathogen

3.8.2. Insertion time of common and special intact LTR retrotransposons of blackleg causal pathogen

4. Discussion

Declarations

References

Additional Declarations

Status:

Version 1