- Research article
- Open Access
Helitron distribution in Brassicaceae and whole Genome Helitron density as a character for distinguishing plant species
BMC Bioinformatics volume 20, Article number: 354 (2019)
Helitron is a rolling-circle DNA transposon; it plays an important role in plant evolution. However, Helitron distribution and contribution to evolution at the family level have not been previously investigated.
We developed the software easy-to-annotate Helitron (EAHelitron), a Unix-like command line, and used it to identify Helitrons in a wide range of 53 plant genomes (including 13 Brassicaceae species). We determined Helitron density (abundance/Mb) and visualized and examined Helitron distribution patterns. We identified more than 104,653 Helitrons, including many new Helitrons not predicted by other software. Whole genome Helitron density is independent from genome size and shows stability at the species level. Using linear discriminant analysis, de novo genomes (next-generation sequencing) were successfully classified into Arabidopsis thaliana groups. For most Brassicaceae species, Helitron density negatively correlated with gene density, and Helitron distribution patterns were similar to those of A. thaliana. They preferentially inserted into sequence around the centromere and intergenic region. We also associated 13 Helitron polymorphism loci with flowering-time phenotypes in 18 A. thaliana ecotypes.
EAHelitron is a fast and efficient tool to identify new Helitrons. Whole genome Helitron density can be an informative character for plant classification. Helitron insertion polymorphism could be used in association analysis.
Transposons or transposable elements (TEs) are mobile DNA segments first described by McClintock in 1950 . They are divided into two main classes, Class I TEs (RNA transposons or retrotransposons) that require an RNA intermediate and use a ‘copy-and-paste’ mechanism to insert their copies into new locations, and Class II elements are DNA transposons which use a ‘cut-and-paste’ mechanism to mobilize themselves without RNA intermediates . Helitrons transpose by rolling-circle replication (RCR) with only one strand cut and are important DNA transposons (Class II) in diverse eukaryotic genomes. They were discovered by data mining the Arabidopsis thaliana, Oryza sativa, and Caenorhabditis elegans genomes . Canonical Helitrons have conservative 5′-TC, CTRR-3′ (mostly CTAG-3′) termini and contain a 16–20 nt GC-rich hairpin structure located 10–15 nt upstream of the 3′ end [3, 4], which is thought to serve as a stop signal in the transposition process . They have always been inserted into 5′-AT-3′ target sites and do not have terminal inverted repeats . Helitrons can be classified as either autonomous or non-autonomous based on whether they contain the RepHel sequence, which is a protein domain homologous to the prokaryotic Rep protein involved in PCR and helicases .
Brassicaceae, formerly Cruciferae, is a medium-sized plant family, composed of more than 372 genera and 4060 species . The family includes many important species, such as the model plant A. thaliana , the crop Brassica rapa , and Brassica oleracea (Cabbage) [9, 10]. Many species in this family have sequenced genomes, which are useful for Helitron evolution research at family level. Helitron length is highly variable in plants, e.g., A. thaliana repeat elements AthE1 , AtREP , and Basho  are non-autonomous Helitrons, and their length ranges from 0.5–3 kb . Some autonomous Helitrons have been found to be larger (8–15 kb in A. thaliana, 10–15 kb in O. sativa, and 5–8 kb in C. elegans) . Maize Helitron length has a wide range from 202 bp to 35.9 kb . In addition, some studies have shown that plant genomes have variable Helitron content, approximately 2% in Arabidopsis , 6.6% in maize, and 0.1–4.3% in other plants . DNA transposons use a ‘cut-and-paste’ mechanism unlike the RNA transposons that use a ‘copy-and-paste’ mechanism, and are usually present in low to moderate numbers . Helitrons are unique DNA transposons transported by RCR, a process that was confirmed by reconstructing the ancient element Helraiser from the bat genome . However, it has also been found that Helitrons can excise and leave footprints, an outcome not expected from rolling-circle transposition in maize . Therefore, Helitrons may exhibit both ‘copy-and-paste’ and ‘cut-and-paste’ modes of transposition. These reports imply that the number of Helitrons in the genome may be lower and steadier than RNA transposons. Therefore, Helitron related data may be more representative of plant genome features than RNA transposons.
Helitrons may express preference in terms of genomic position and have been reported to be more abundant in gene-poor regions of Arabidopsis , especially around the centromere as with other TEs . However, a less ordered pattern of Helitron distribution was reported in rice . Furthermore, it was found that the Helitrons of maize mainly exist in the gene-rich region rather than the gene-poor region . This may be because the maize genome is larger; therefore, the density of the maize gene-rich region is similar to that of the Arabidopsis gene-poor region. Xiong et al. found in plant Helitrons amplified by RCR that the tandemly arrayed replication products mostly accumulated in the centromeres . Helitron distribution patterns remain unclear in a wide range of plant genomes and require further research.
Similar to other transposons such as CACTA  and MULEs (Mutator-like elements) , Helitrons can capture gene fragments and move them around the genome . It is one of the most important agents in gene evolution. Helitrons can change many gene functions and have been found to cause phenotypic differences by insertion into promotors leading to changes in expression patterns. A spontaneous pearly-s mutant of Ipomoea tricolor cv. ‘Heavenly Blue’ displays stable white flowers and is caused by an 11.5 kb Helitron inserted into the DFR-B gene for anthocyanin pigmentation . In Brassicaceae, a 4.3 kb Helitron inserted into the BrTT8 intron resulted in B. rapa with a yellow seed coat . A 3.6 kb non-autonomous Helitron was inserted into the promoter of the determining gene for self-incompatibility in males BnSP11–1, which led to oilseed rape Brassica napus becoming self-compatible . Locating these Helitrons is an important task in plant functional genomic research.
There are two main types of software used for searching Helitrons. Homology comparison software, such as CENSOR , RepeatMasker , etc., are mainly based on NCBI-BLAST , WU-BLAST  and other derivatives programs (e.g. RMBlast) comparable with Repbase  and other repeat sequences databases. While BLAST is not able to fully identify various Helitrons hairpins, similarity searches alone are not effective in identifying Helitrons. The other type of software, such as HelitronFinder  and HelSearch  are based on Helitron conserved structures. HelitronScanner identifies Helitron terminal structures based on a motif-extracting algorithm proposed initially in a study of natural languages . It may be able to discover novel Helitrons but results in a high number of false positives when using the default settings . With the development of next-generation sequencing (NGS) and 3rd-generation sequencing (3GS), more plant genomes have been sequenced and assembled, and a faster and easier way to annotate Helitrons and present annotation results is required.
In this study, we developed the software easy-to-annotate Helitron (EAHelitron), a rapid and easy-to-use program for computationally identifying Helitrons. It predicted more than 104,653 Helitrons in 53 genomes of different plant species (including 16 genomes from 13 Brassicaceae species) and 18 A. thaliana ecotype genomes. We considered whole genome Helitron density to be a species-specific characteristic of plants, given its potential for plant classification. We investigated the large plant family Brassicaceae in terms of Helitron distribution and insertion patterns. Finally, we attempted to associate flowering-time phenotypes with Helitron polymorphisms in 18 different A. thaliana ecotypes. The software and results may contribute to our knowledge of Helitrons and their role in plant evolution.
Workflow of EAHelitron
EAHelitron predicts putative Helitrons based on definitive features by scanning for conserved structural traits: 5′ end with TC and 3′ end with CTAG and a GC-rich hairpin loop 2–10 nt in front of the CTAG end. Using the Perl regular expression engine, the left GC-rich part of hairpin was searched by EAHelitron, followed by the capture of reverse complementary sequence of GC-rich fragment as the right part of hairpin, using our TRSeq function by an embedded-code of Perl regular expression engine. Next, the upstream and downstream sequences of hairpin were searched simultaneously using EAHelitron, to identify possible matched structure of 5′ end with TC and 3′ end with CTAG. Subsequently, such searching process was repeatedly performed by EAHelitron using the reversed complementary chromosome sequences. Finally, all records of putative Helitrons were printed in FASTA format including the terminal ends, 3′ upstream and downstream sequences, possible full-length Helitron sequences, and a general feature format (GFF) annotation file (Fig. 1).
Comparison of EAHelitron with other software
EAHelitron supports whole genome FASTA sequences and multi-threading. Compare the time cost of Helitrons (4 min) searching in Arabidopsis TAIR10 with other software (HelitronScanner, Helsearch and RepeatMasker), EAHelitron increases the maximum speed of the prediction process by 99.3 times (38 min for HelitronScanner, 7 h for Helsearch, and 2.5 h for RepeatMasker shown in Table 1).
We ran EAHelitron against genome sequences of TAIR10 at the default 3′ terminal fuzzy level and identified 665 Helitrons. Comparing these results with those of former programs, we found that 75.0% of the EAHelitron-predicted Helitrons (499/665) were supported by HelSearch or HelitronScanner (Fig. 2, Additional file 2: Table S1). In silico verification of EAHelitron-predicted Helitrons through the study of in 18 different A. thaliana ecotypes showed that at least 508 Helitrons were active in transposition in these ecotypes (Additional file 2: Table S2), including at least 41 Helitron-insertion polymorphisms of the 166 (24.7%) Helitrons uniquely predicted by EAHelitron in TAIR10 (Additional file 2: Table S1 and S2). This indicates that EAHelitron has the ability to find genuine new Helitrons.
To estimate the false positive rates (FPR) of these programs, we predicted Helitrons in 100 randomly reconstructed genomic sequences of Arabidopsis using EAHelitron, HelSearch and HelitronScanner . HelitronScanner had the highest FPR under the default settings (32.67%, Additional file 2: Table S3), and EAHelitron showed lower FPR of 5.91% (Additional file 2: Table S3). HelSearch operates by only counting those occurrences with more than one copy; therefore, no false positive Helitrons were identified in these random genomes (not listed). However, the omission of one-copy Helitrons in this application can be a problem. EAHelitron provides outputs in the form of full length Helitrons, flanking sequences, and support-to-output GFF3 files, similar to RepeatMasker , which are easy for presenting Helitrons in genome visualization software (389 of EAHelitron-predicted Helitrons were supported by RepeatMasker, Additional file 1: Figure S1), such as IGV , GBrowse , and JBrowse . Considering the time cost, support of whole genome automatic annotation, acceptable FPR, convenience of downstream analysis, and visualization, we used EAHelitron to identify Helitrons in subsequent analysis of plant genomes.
Helitron identification in 53 plant genomes
Using EAHelitron, we identified 104,653 Helitrons in 53 published plant genomes, including a wide range of monocots and eudicots (Additional file 3: Table S4). The 5′ terminal ends of Helitrons are less conserved than 3′ ends . In addition, a Helitron may have a single 3′ end but multiple 5′ termini , which results in difficulties in predicting Helitron length. It makes genome content of Helitron that, based on Helitron length, would not be accurate to describe a genome character. Here, we used Helitron density, defined by the number of 3′ termini of Helitrons divided by the genome size, which is potentially a more accurate genomic characteristic than the proportion of Helitron sequence length in the genome. The phylogenetic relationship, based on APG  and Phytozome 11, genome sizes, and Helitron numbers, Helitron densities of 53 plant genomes were summarized in Fig. 3 and Table 2. The number of Helitrons varied dramatically among these plant genomes. B. napus contained the largest number of Helitrons (13,968), while in Ostreococcus lucimarinus and Micromonas sp. RCC299, only 38 Helitrons were detected in each of the genomes representing the minimum number of Helitrons. Notably, sibling species may have divergent Helitron densities, even though they belong to the same family (Fig. 3). For example, a 3-fold difference in Helitron density between A. thaliana and A. lyrata (5.5 and 16.3, respectively) was detected, indicating significant variation in either Helitron counts or Helitron densities in Arabidopsis genus. So, either Helitron counts or Helitron densities (0.2368–26.0412) greatly varied in these plants.
To study the Helitron features in different sequenced genomes from one species, we compared the characteristic of Helitrons in different sequenced genomes of seven species (Oryza sativa japonica, Oryza sativa indica, Eutrema salsugineum or formerly Thellungiella salsuginea, Schrenkiella parvula or formerly Thellungiella parvula, Brassica oleracea, Arabidopsis thaliana and Zea mays, Table 3). The results showed that although the genome size and Helitron numbers varied in different varieties or ecotypes of the same species, the densities of Helitrons remained relatively stable. In rice, the genome size for two indica varieties PA64s and 93–11 were 389 M and 431 M, respectively, with a standard deviation (SD) of 29.70 and coefficient of variation (CV) of 7.24%. Also, the number of Helitrons were 2863 for PA64s and 3120 for 93–11 (SD = 181.73, CV = 6.07%). However, the Helitron densities were 7.36 for PA64s and 7.24 for 93–11, which was is a constant value in rice species (SD = 0.086, CV = 1.17%). Similarly, in B. oleracea A2 v1.1 and B. oleracea TO1000 v2.1, their genome size (391 M and 498 M, respectively, SD = 75.66, CV = 17.02%) and Helitron number (5392 and 6979, respectively, SD = 1122, CV = 18.14%) were different, but their Helitron densities were similar (~ 13.90 Helitrons per Mb, SD = 0.16, CV = 1.14%). And compression of two version of Thellungiella salsuginea genomes showed that, Thellungiella salsuginea and Eutrema salsugineum (formerly Thellungiella halophila, which finally were determined to be Thellungiella salsuginea) had steadier Helitron density (~ 4.36 Helitrons per Mb, SD = 0.055, CV = 1.27%) than genome size (233.7 M and 246.2 M, respectively, SD = 6.25, CV = 2.60%). Therefore, Helitron density may be regarded as a stable genomic characteristic.
To further estimate the relationship between genome size, Helitron number, and Helitron density, we calculated the Pearson’s product-moment correlation in 53 plant genomes (Table 4, Additional file 1: Figure S2,). The results suggested that Helitron number was significantly positively correlated with genome size and Helitron density (r1 = 0.52, p1 = 7.23E-05; r2 = 0.71, p2 = 2.60E-09); however, Helitron density may not be correlated with genome size (p = 0.73). Therefore, Helitrons contributed to the size changes in plant genomes, whereas Helitron density and genome size are independent of each other, we can use Helitron density as a genome character together with genome size in the next experiments.
Considering the stability of Helitron density at the species level, it might be regarded as a species-specific characteristic for use in classification. To validate the efficacy of using Helitron density to identify species, we performed the LDA using seven genomes with at least two sequence variants (Table 3). In total, 34 genomes (including 18 A. thaliana) were used to train the model in R with Helitron density and genome size. Next, we added the Helitron information from two de novo assembled genomes of A. thaliana mutants, Denovo_genome_L (CS852557, N50: 5064, Scaffolds: 3350) and Denovo_genome_X (SALK_015201, N50: 25,619, Scaffolds: 9888) to these data, and then predicted which species groups they belong to. LDA predicted all of these 36 samples correctly (100%), including successfully identifying the two de novo samples to the A. thaliana group from six other species groups (Table 3, Additional file 1: Figure S3). This result indicated that EAHelitron can count the Helitrons of NGS de novo genome drafts successfully, and that Helitron density is informative as a species-specific characteristic in plant genomes and could be applied to expediate plant identification.
Identification of Helitrons in Brassicaceae
Many Brassicaceae species genomes are sequenced and are informative for Helitron evolution research. There were 49,213 Helitrons were predicted from 16 Brassicaceae genomes, showing a wide range of diversity in genome size, Helitron count, and Helitron density (Table 2, Additional file 1: Figure S4). Of these genomes, B. napus had the largest genome size and Helitron counts (864.5 M and 13,968, respectively). Capsella grandiflora had the smallest genome (112.3 M) and T. parvula v8 had the least number of Helitrons (202). The Helitron density reached a maximum of 25.98 in B. rapa, whereas T. parvula had the lowest Helitron density of 1.59. Most of Helitrons in Brassicaceae were non-autonomous, only 1.6–18.49% were autonomous (6.5% in average, Additional file 2: Table S5). Also, RepHel percentage was not correlated with Helitron density or Helitron number (p1 = 0.21, p2 = 0.24, Additional file 2: Table S5), which means autonomous Helitron counts were not correlated with the total Helitron number in host genomes of Brassicaceae. B. napus (genome AnAnCnCn) was formed by recent allopolyploidy (7500 to 12,500 years ago) between ancestors of B. oleracea (CoCo) and B. rapa (ArAr) . We found that the Helitron density of subgenomes in B. napus decreased relative to the ancestor genomes of B. oleracea and B. rapa. In addition, the subgenome of An had higher Helitron density relative to the Cn subgenome in B. napus (An: 7056/314.2 = 22.4570 < Ar: 25.9788, Cn: 6721/525.8 = 12.7824 < Co: 13.9888 or 13.7762, AnCn: 16.1573 < ArCo: 18.4126 or 18.9870). This inferred that allopolyploidy may affect the density of Helitrons during evolution.
Helitrons evolution in Brassicaceae
We constructed a dendrogram of 15 Brassicaceae genomes based on genome size and Helitron density with hierarchical clustering (Additional file 1: Figure S5a). This was compared with known phylogenetic trees, one based on a reconstruction using the ancestral Brassicaceae karyotype genome  (Additional file 1: Figure S5b), and the other based on sequences of nuclear ribosomal ITS-1, 5.8S ribosomal RNA, and ITS-2 region  (Additional file 1: Figure S5c). The Helitron density related dendrogram had a similar topological structure to these two known phylogenetic trees, indicating that Helitron density, which may contain the history of the transposon replications and genome size expanding, e.g. whole genome duplication (WGD), is informative in terms of species evolution.
We investigated the evolutionary process of Helitrons in eight sibling genomes in Brassicaceae (Ath, Aly, Cru, Tpa, Bol v1, Bol v2, Bra, and Bna), and upstream 1kbp sequences of 3′ termini were chosen to search for conserved sequences showing highly similarity (Additional file 2: Table S6). Although the proportion of conserved Helitrons (evalue <1e-5, qcov > 55, s_end > 950; length of upstream sequences of 3′ termini matched larger than 55 bp) was consistent with the phylogenetic relationship between the species, the number of conserved Helitrons remained at a rather low level. The divergence time of A. lyrata and A. thaliana was about 10 to 12 Mya, with approximately 90% of syntenic regions found between the two genomes. It was found that all 32,670 A. lyrata protein-coding genes were homologous to the 27,025 (98.7%) genes in A. thaliana . However, only 12.4 to 22.7% of Helitrons were conserved between the two genomes showing homology with each other (Additional file 2: Table S6). Similarly, B. oleracea and B. rapa diverged about 4.6 Mya. A total of 66.5% (34,237 genes) of B. oleracea genes and 74.9% (34,324) of B. rapa genes were regarded as homologous , whereas they only shared 50.05 to 52.60% of homologous Helitrons. The proportion of conserved Helitrons between Camelineae (Ath, Aly and Cru) and Calepineae (Tpa, Bra, Bol and Bna), which diverged around 27 Mya , reduced to less than 1%. These results suggest that Helitrons evolved much quickly than protein-coding genes, and they were likely to originate in the ancestral species but diverge or disappear in some of the lineages during the evolution. We also found that a large proportion of Helitrons in Brassicaceae, from 35.75% in Tpa to 80.63% in Aly, were multiple copies, with an average ratio of 65.72% being multi-copy Helitrons (Additional file 2: Table S6). This suggested that Helitrons were inclined to duplicate themselves in host genomes during the evolution, but still have some Helitrons remained in single copy.
Helitron distributions in Brassicaceae
We further analyzed Helitron insertion sites using CompareGFF script. The positions of all Helitrons were clustered into three types: in exon, in intron or untranslated regions (UTR), and in intergenic regions (see examples in IGV in Additional file 1: Figure S6). Among these Brassicaceae genomes, T. parvula had the highest gene zone (exon, intron and UTR) insertion rate (22.2%), whereas B. oleracea A2 v1.0 had the lowest Helitron insertion rate (2.8%). The average rate was 7% (Table 2, Fig. 4a). The Chi-square test of Helitron insertion rate (Fig. 4a) with genome components rate (Fig. 4b) showed that, Helitrons were not distributed randomly in all tested genomes (p < 0.0001). Most Helitrons were inserted in the intergenic region (77.8 to 97.2%, 93.3% average). In general, those Helitrons inserted in the gene zone were mostly found in UTR or introns (4.5%) rather than in CDS (2.6%) (Fig. 4a, Table 2).
The relationship between gene density and Helitron density was also investigated, and an overview of the Helitron distribution of nine genomes (Ath, Aly, Cru, Tpa, Bra, Bol v1, Bol v2, Bna and Csa) on the chromosome were shown on the IGV (Fig. 5). Sliding window and correlation analyses suggested that in most of these genomes (5/8), local gene densities of windows were highly negatively related to local Helitron densities (− 0.707 < r < − 0.315, p < 0.001, Additional file 2: Table S7). Two species (A. lyrata and B. napus) were found to be slightly positively correlated (r1 = 0.130, p1 < 0.05, r2 = 0.234, p2 < 0.01, Additional file 2: Table S7). B. oleracea Helitron density and gene density were not correlated significantly (p > 0.05) These results suggested that Helitrons mostly preferred low-density gene areas in Brassicaceae, and this was in accordance with previously research that suggested that most Helitrons were located in low gene density areas especially around the centromeres in Arabidopsis .
Analyses of functions of Helitron-inserted genes in Brassicaceae
A total of 2370 Helitron-inserted genes were identified in Brassicaceae (Additional file 4: Table S8). The GO terms heatmap showed that the functions of these Helitron-inserted genes exhibited some similar patterns, such as biological regulation, localization, metabolic process, multicellular organismal process, reproduction, and response to stimulus in biological process categories (BP), binding, catalytic, transporter, and nucleic acid binding transcription factor in molecular function categories (MF), and cell, membrane, organelle, and symplast in cellular component categories (CC) (Fig. 6).
Four well-annotated genomes (A. thaliana, B. rapa, B. oleracea v1, and B. napus) in GO terms or KEGG pathways were used for further enrichment analysis (all annotated genes were used as background). The significantly enriched results are listed in Additional file 5: Table S9 (P < 0.001, corrected P < 0.1 and hit genes > 2). In Arabidopsis, Helitron-inserted genes were likely to be enriched in terms of triplet codon-amino acid adaptor activity (GO: 0030533), binding (GO: 0005488), and other items in the MF category. Helitron-inserted genes in B. rapa were significantly enriched in terms of transmembrane transport (GO: 0055085, BP), xanthophyll metabolic process (GO: 0016122, BP), inorganic anion transport (GO: 0015698, BP), water transmembrane transporter activity (GO: 0005372, MF), lipase activity (GO: 0016298, MF), and others. B. oleracea v1 genome Helitron-inserted genes were enriched in terms of drug transport (GO: 0015893, BP), sexual reproduction (GO: 0019953, BP), transmembrane transporter activity (GO: 0022857, MF), antiporter activity (GO: 0015297, MF), and others (Additional file 5: Table S9). B. napus Helitron-inserted genes were enriched in terms of response to wounding (GO: 0009611, BP), suberin biosynthetic process (GO: 0010345, BP), cell periphery (GO: 0071944, CC), long-chain-fatty-acyl-CoA reductase activity (GO: 0050062, MF), carbon-oxygen lyase activity, acting on phosphates (GO: 0016838, MF), terpene synthase activity (GO: 0010333, MF), and others. The KEGG pathway enrichment showed that A. thaliana was enriched in Phenylpropanoid biosynthesis (map00940), and B. oleracea was enriched in cutin, suberine and wax biosynthesis (map00073) and lipid metabolism. However, B. rapa and B. napus were not significantly enriched in any pathways in these tests (Additional file 5: Table S9).
Helitron distributions in different ecotypes of A. thaliana
In Arabidopsis, the numbers of Helitrons in 18 ecotypes (Additional file 1: Figure S7) varied from 542 to 665 (average 572, SD = 27.7, Table 5), with an average density of 4.77 Helitrons per Mb (SD = 0.21, Table 5). Ecotype Kn-0 from Kaunas, Lithuania had the least number of Helitrons (542), while the Col-0 ecotype from USA has the largest number of Helitrons (665). Of the 665 predicted Helitrons in Col-0, 70 Helitrons had been inserted in gene regions; 18 of them were located in CDS (Table 6), and 52 were located in introns or UTR (Additional file 2: Table S10). According to the TAIR10 annotation, three Helitrons were inserted in CDS genes (AT1G62840, AT4G11700, and AT5G66580) of unknown function (Table 6).
The overview of the Helitron distributions of these ecotypes showed that Helitron distributions were similar in these genomes, despite the existence of minor variations among different ecotypes (Additional file 1: Figure S8). These 18 ecotypes of Arabidopsis genomes are of different lengths; thus, we cannot use their own physical locations for direct comparison. Therefore, the nearest gene downstream of the Helitron 3′ termini was used as a marker to represent the Helitron-inserted loci (Additional file 2: Table S2). A total of 562 loci with markers were found, and 508 of them had polymorphisms (named LOC001–508). All ecotypes sheared 54 loci and owned their unique loci (counted 1 to 14, Table 5), indicating that many active Helitron transpose events occurred in these ecotypes (Additional file 2: Table S2).
To investigate whether these Helitron distributions informed the relationship between these 18 A. thaliana ecotypes, we used the Helitron diversity LOCs matrix (Additional file 2: Table S2) and clustered the ecotypes into three main groups (Fig. 7a). Considering their geo-location information (Additional file 2: Table S2), these groups presented some aggregation of geographical distribution (Fig. 7b). The yellow group (Can-0, Sf-2, and Bur-0) in Fig. 7b, was distributed in Western and Southern Europe, and North Africa (longitude, − 13.48 to 3.03); the green group (Ct-1, Po-0, Oy-0, Ler-0, Kn-0, Mt-0, and Wil-2) was distributed in Northern, Central, Southern, and Eastern Europe, and North Africa (longitude, 6.19 to 25; latitude, 32.3 to 60.38); the red group (Ws-0, Zu-0, Hi-0, Wu-0, Rsch-0, Edi-0, except for Tsu-0 of Japan and Col-0 from the USA) were distributed in Western, Central, and Eastern Europe (longitude, − 3.16 to 34; latitude, 47.37 to 56.3). The green group was more widely distributed south-north, whereas the red group was more distributed east-west. The locations of these groups probably indicated the main direction of the spread of A. thaliana subgroups, and the Helitron polymorphism were probably correlated with the adaptation of each ecotypes to its ecological conditions.
To gain insight into the possible effect of Helitrons, we performed an associate analysis between the polymorphisms of Helitrons and flowering-time type (late type and intermediate type) in 18 ecotypes (Table 5). We found 216 single associating rules (Additional file 2: Table S11) among 13 LOC-paired rules (both 0 and 1) associated with flowing-time type (Table 7, Fig. 7c). Ten genes in upstream and downstream regions of the LOCs were searched with 306 known flowering-time related genes in Arabidopsis . We found that two Helitron polymorphism loci, LOC006 (near AT1G04425) and LOC458 (near AT5G37230), which belonged to the 13 paired rules, were closely linked with two flowering-related genes Cryptochrome-2 (CRY2, AT1G04400)  and Circadian 1/Reveille 2 (CIR1/RVE2, AT5G37260) .
To confirm the Helitron LOC diversity of these ecotypes, we cut the LOC006 part of the sequences of all 18 genomes, and the resulting VISTA plot of the LOC005 to LOC006 multiple sequence analysis is presented in Fig. 8. It shows that these two LOCs have different sequence lengths in these ecotypes (same as Fig. 7c and Additional file 2: Table S3) and that the flowering-related gene CRY2 (AT1G04400) near LOC006 (near AT1G04425) was only two genes away. The analysis might suggest a correlation between Helitron insertion and flowering-time phenotypes, and that Helitron polymorphisms may be informative for association studies.
Historically, research has focused on the protein-coding genes, and the rest of the genome was considered to be ‘junk DNA’. Recently, it has been shown in multiple studies that these ‘junk’ regions affect biological processes involving miRNA, LncRNA, and TEs . Helitrons are unique rolling-cycle type transposons for which like other transposons, their activation may involve the generation of new genes or regulating existing genes, and potentially affecting phenotype expression . Researching non-coding sequences, such as Helitrons, is an important task as well as studying protein sequences. Here, we provide another effective toolkit (EAHelitron and related scripts) for researchers to annotate Helitrons in sequenced genomes. EAHelitron was found to be fast and was able to find many new Helitrons that were not predicted by other programs. With the output GFF files, it was easy to visualize the Helitron locations, terminal ends and flanking sequences, and are useful for further study, such as insertion annotation, transposon classification, captured gene identification, model contracture, etc. EAHelitron can expediate the annotation of Helitrons in the rapidly increasing number of sequenced plant genomes.
Previous research found that most of Helitrons are relatively young with 87% of Basho elements to have originated in the last 5 Myr. This was subsequent to the divergence of A. thaliana from its closest relative A. lyrata , that occurred about 10 Mya . Our Helitron homology rate analysis of these two close species also supported a young age of most Helitrons (Additional file 2: Table S6). Random sequences analysis for FPR also found that, novel classical terminal ends are not difficult during genome recombination. It suggested that de novo Helitron ends near the RepHel motif were probably a source of younger Helitrons or lineage-specific Helitrons in a species.
Helitrons are important players in the evolution of plant genomes, and therefore genome location information may be useful for future research. Many important species in Brassicaceae have had their whole genome sequenced and are therefore useful for studying the evolution and domestication of these plants. This study noted the distribution and classification of Helitrons predicted in the Brassicaceae genomes. We found that Helitrons like other TEs, accumulate in gene-poor regions , and insertions tend not to directly insert into coding regions because most of these events are detrimental to the gene and are therefore selected against. The Brassicaceae Helitrons were concentrated near the centromeres, the regions with low recombination rates, like A. thaliana . Moreover, some Helitrons might be correlated with some domestication traces in genomes. Previous researches showed that, Helitron insertions affect seed coat color of B. rapa  and self-compatibility of B. napus . In our study, Helitron-inserted genes in B. rapa were enriched in water transmembrane transport functions, which might explain the high water content of Chinese cabbage (Additional file 5: Table S9). Besides, Helitron-inserted genes in B. napus were enriched in long-chain-fatty-acyl-CoA reductase activity (BnaA10g13850D, BnaC02g09500D, BnaCnng48650D, BnaCnng47950D, and BnaCnng48640D) and other long-chain-fatty-related terms (map00061: Fatty acid biosynthesis, Additional file 5: Table S9), thereby indicating that Helitrons might have contributed to the natural variation of lipid quality during the domestication of B. napus. We took BnaA10g13850D of B. napus Darmor as an example, which was a fatty acid reductase 1 (FAR1, AT5G22500) homologous gene involved in oxidoreductase activity, fatty-acyl-CoA reductase (alcohol-forming) activity (Fig. 9a, b). The genomic sequence of BnaA10g13850D was 4768 bp from 5′ UTR to 3′ UTR (chrA10:11115015–11,119,782, minus strand). An 892-bp Helitron insertion annotated as chrA10H117 in B. napus by EAHelitron, was observed in the first intron (941–1832) of BnaA10g13850D of B. napus, compared with its ancestral gene Bra002416 in B. rapa (3884 bp, A10: 9784847–9,788,730, minus strand). Double low oilseed rape cultivar has long been the objective of domestication. Brassica napus Darmor is a French winter double low oilseed rape cultivar, which lacks detectable erucic acid in the seed oil with low seed glucosinolate content . Brassica napus Zhongshang11 (ZS11), an Asian semi-winter oilseed rape cultivar, is also a double low oilseed rape cultivar . This cultivar ZS11 also contained Helitron chrA10H117 in the paralogous gene of BnaA10g13850D (Fig. 9 c, d), suggesting that Helitron insertions may had contributed to the lipid quality to a certain extent in the domestication of B. napus. These Helitron insertions’ effects need further research. These results imply that humans probably have selected the genomic variation caused by Helitron insertions. These Helitron insertions of Brassicaceae can be useful for future genetics and molecular breeding selection studies.
Regarding the 18 different ecotype genomes of A. thaliana, we found at least 508 active Helitron suggesting Helitron-insertion polymorphisms. Comparing the genomic differences between multiple ecotypes of a species, combined with geographic and environmental information may contribute to the study of species diversity history. And we get similar spread directions of European A. thaliana after the ice retreated (east to west, south to north), which previous research reported, starting ~ 10,000 years ago . This study attempted to use Helitron LOC diversity to correlate the phenotypes of the A. thaliana ecotypes in terms of flowering time, and we obtained 13 associated locations, including two LOCs near known flowering-related genes. We need further research to determine these Helitron insertions’ function. It suggested that Helitron polymorphisms have the potential applicability in genome wide association studies (GWAS) as a bio-marker, similar to SNP/indel and copy number variation, which will help in improving GWAS maker numbers in samples. In addition, because of the many single-copy Helitrons present in Arabidopsis, information regarding the positional variation of single-copy Helitrons between different ecotypes is informative for studying the Helitron ‘cut-and-paste’ transposition mechanism.
We annotated thousands of Helitrons in the genomes of 53 plants including monocots and eudicots. We did not observe a significant difference between monocots and eudicots, and they both had wide ranges of Helitron abundance and genome size. In Xiong’s research, they found no sign of correlation between Helitron abundance and genome size . In contrast, our study showed that Helitron abundance is positively correlated with genome size suggested that Helitrons, like other TEs, contribute to changes in genome size .
Helitron 5′ terminal ends are not as conserved as the 3′ ends, and a Helitron may have multiple 5′ ends , so the predicted full lengths of the Helitrons might not be accurate. The 3′ ends with their hairpins played important roles as a transposition terminator , thus the number of 3′ ends could be a base of a minimum number of total Helitron . Helitron density, calculated using Helitron number and genome size, could be as a more accurate characteristic. We did not find any significant Helitron density related patterns between monocots and eudicots. However, we did find that many closely related species have more changes in Helitron density. As many Helitrons use a ‘cut and paste’ mechanism, their copy numbers remain low. Genome sequencing and annotation methods might have little effect on the result. For instance, the genome sequence of maize “B73” AGPv3 (6a) was produced by the Maize Genome Sequencing Project, and the alignment of “Mo17” 454 reads to this reference sequence, finally assembled a 2067 Mbp genome (Fig. 3). An entirely new assembly of the maize genome (B73 RefGen_v4, 2134 Mbp) was further constructed from PacBio Single Molecule Real-Time (SMRT) sequencing, and the genome size of such new version became bigger, but the Helitron number reduced (8622 and 8274, respectively, Table 3, Fig. 3). It was likely the longer reads based on 3GS technology lead to reduce number of repeat sequences in final assembled genomes. In an analysis of seven multiply sequenced genomes, we found that Helitron density is probably stable at species level. We also found that Helitron density was not correlated with genome size, which suggested that Helitron density is independent from genome size. Based on these results, we consider that Helitron density has potential applicability in species classification. We used de novo assembled scaffolds from NGS data of two A. thaliana T-DNA mutants to determine genome size and Helitron density, then used LDA to identify its species. The two test samples were successfully identified as A. thaliana. Therefore, with the development of new sequencing technology, the Helitron density could be considered as a quick way to identify an unknown plant sample.
The first Angiosperm Phylogeny Group (APG I) classification of the orders and families of flowering plants is a modern molecular-based system of plant taxonomy, which is based on the cladistic analysis of the DNA sequences of two plastid/chloroplast genes (rbcL, atpB) and one gene of ribosomes (18S rDNA) . Although it is based only on molecular evidence, its constituent groups have been further supported by other morphology and chemistry evidence as well. For example, pollen feature supports the split between the eudicots and the rest of the former dicotyledons . The characteristics of Helitrons discussed herein provide genome-scale characteristics which can bolster these classifications. A combination of Helitron density and other plant characters, analyzed with modern machine-learning algorithms, such as artificial neural networks, may be informative for constructing a more accurate phylogenetic tree of plant diversity. We attempted to combine the number of chromosomes with Helitron information. However, the same species may have multiple karyotypes of chromosome numbers, not simply related to genomic features, and so no reliable results were obtained. As further species of plants have their genomes sequenced, Helitron-related features could be employed to study, e.g., the difference between angiosperms and gymnosperms, herbs and woody plants, field and horticultural crops, monocots and eudicots, wild species and domesticated species, adaptation to the environment, etc.
Helitron density may not only represent the tolerance of the host genome to them but may also represent the rate of recombination or self-fertilizing rate of the species. According to previous reports, high self-fertilizing rates reduce the importance of recombination rates on genome structure . In an outcrossing species, new TEs can spread rapidly through a population by recombination via sexual reproduction. In contrast, in self-fertilizing species, recombination is not effective at spreading TEs. New copies are therefore lost by genetic drift and/or purifying selection, and the probability of TE fixation is reduced. This would result in a lower number of new TEs copies in self-fertilizing species . In this study, we compared the Helitron density of B. napus and its ancestors, B. rapa and B. oleracea, and found that the Helitron density of the B. napus subgenome was lower than that of the ancestral genomes, which may be because the ancestors were both self-incompatible. In this scenario, B. napus have become self-compatible following allopolyploidy in the last 7000 years. Moreover, EAHelitron could probably be applied to animals or other genomes. Also, it can be easily rewritten to search for other genome-wide features, e.g., to find other TEs or tandems, or to predict the editable site of the CRISPR/Cas gene editing system, and SSR.
We developed EAHelitron, which is a fast and efficient tool to identify new Helitrons. Whole genome Helitron density can be an informative character for plant classification. We predicted thousands of Helitrons in Brassicaceae, Helitron distribution patterns of most species in this family were similar to A. thaliana. Helitron insertion polymorphism could be used in genome wide association studies. This research may contribute to speed up our research of Helitrons and understand their role in plant evolution.
Extraction of plant genome sequences and phylogenetic data
Genome sequences of 40 plants were downloaded from Phytozome version 11 (https://phytozome.jgi.doe.gov). Sequences of 16 Brassicaceae species genomes were downloaded from BARD (http://brassicadb.org/brad) and Ensemble Plant (https://plants.ensembl.org). Eighteen ecotypes of A. thaliana were analyzed, and their genomes sequences were downloaded from 1001 Genomes Project (http://1001genomes.org) . Detailed source information for all genome sequences is listed in Additional file 3: Table S4. The phylogenetic trees of 45 genomes were also obtained from Phytozome version 11, and they were edited in TreeGraph2 .
Genome sequencing and de novo assembly of LDA samples
Whole genome sequencing of two accessions of mutant A. thaliana SALK_015201 and CS852557, were sequenced by Illumina HiSeq 4000, and a total of 5.7 GB and 9 GB 150-bp paired-end reads sequence data were obtained. Sequence Read Archive IDs are SRR5249176 and SRR5249156. Raw data were cleaned by Trimmomatic . These two de novo draft genomes were assembled using SOAPdenovo 2.40 , with kmer values of 81 or 85, named Denovo_genome_X (120.2 MB, N50: 25,619, scaffolds: 9888) and Denovo_genome_L (121.1 MB, N50: 5064, scaffolds: 3350).
Performance testing of EAHelitron
The predicted results from EAHelitron are compared with those from other programs including HelSearch, HelitronScanner and RepeatMasker, based on the genome sequence of A. thaliana (TAIR10), a model plant of dicot species. Running time cost was also taken into account when assessing software efficacy. Venn diagram of these results were plotted in jvenn . To estimate the false positive rates (FPR), 100 randomized genomes were created by shuffling the genome sequence of A. thaliana (TAIR10) using RandomDNA_rate.pl (A:T:G:C = 0.319414:0.319033:0.179905:0.180095; length = 119,667,750 bp, counted by CountATGC.pl). Helitron predictions on these randomized genomes are regarded as false positives . The basic version and multi-threading version of EAHelitron, manuals and other assistant scripts are available at GitHub (https://github.com/dontkme/EAHelitron).
Helitron visualization and annotation
Using the GFF files extracted from EAHelitron, the Helitrons and Helitron inserted genes were exported to an integrative genomic viewer (IGV) . The output files containing the 3′ terminal ends (*.3.txt) were used to count the number of Helitrons, and Helitron density of the whole genome was defined as the number of Helitrons per Mb. To identify the autonomous Helitrons in Brassicaceae, 20 kb upstream sequence of the 3′ ends of the Helitrons were aligned with known RepHel protein domains in A. thaliana and O. sativa using BLASTX (evalue <1e-5). The sequences (1 kb) upstream of the 3′ end of the Helitrons were cut and filtered by Cutfa script (no N and exactly 1000 bp sequences). Then BLASTN (evalue <1e-5, qcov > 55, s_end > 950) was used to search for homologous Helitron sequences. Helitron-inserted locations were clustered using the CompareGFF script, and the GFF from EAHelitron was compared with the general transfer format of its official genome. The functions of the inserted genes were annotated by Blast2GO , and the results were combined using WEGO .
A heatmap of Gene Ontology (GO) terms was plotted using the pheatmap  package in R version 3.3.3 . GO and KEGG pathway enrichment analyses were carried out using TBtools (https://github.com/CJ-Chen/TBtools/, P < 0.001, corrected P < 0.1 and hit genes > 2) . The multiple sequences alignment was carried out in MUSCLE  and UGENE . The presence or absence of LOC005 and LOC006 was visualized in VISTA .
Statistical calculations and graph plotting were performed using R version 3.3.3 . We used the cor.test function for Pearson’s product-moment correlation, boot  package for bootstrapped p values and r (1000 replicates, seed: 1234). Chisq.test function for chi-squared test. Linear discriminant analysis (LDA) was used to estimate the capability of Helitron density as a characteristic in plant system classification. Genome sequences of 34 varieties from seven species groups were trained using lda function of MASS package, and two de novo genomes were added as test samples . For hierarchical clustering, hclust function with ‘median’ method was used to draw the Brassicaceae dendrogram. Using the SWcount script, sliding window analysis (window = 1 Mb, step = 500 kb) was carried out to investigate the local scale density of Helitron and genes.
To investigate the distribution of Helitrons in different ecotypes of A. thaliana, we selected the seeds of 18 ecotypes from different countries in the Arabidopsis Biological Resource Center. After 45 days of growing, the seedlings were photographed and their flowering-time types were recorded (Table 5). To identify the nearest genes of each Helitron as markers, 500 bp sequences downstream of Helitrons were BLASTNed against Arabidopsis TAIR10 (Col-0) coding sequence (CDS) (evalue <1e-5, q_star < 450). The genes showing similarity obtained from BLASTing and these polymorphisms loci were named LOC001 to LOC508, and were clustered in R. Geographical distribution of 18 A. thaliana ecotypes were painted by rworldmap , country boundaries were derived from version 1.4.0 of Natural Earth data 1:110 m data (http://www.naturalearthdata.com/downloads/110m-cultural-vectors/110m-admin-0-countries/). Association analysis between the Helitron insertion polymorphisms and flowering-time types in 18 ecotypes was performed, using the apriori function of the arules package (maxlen = 3, support > 0.1, confidence > 0.8, lift > 1.1) .
Availability of data and materials
The scripts developed as part of the study are available at GitHub (https://github.com/dontkme/EAHelitron). The raw data of two accessions of mutant A. thaliana SALK_015201 and CS852557, was deposited at NCBI SRA database under accession SRR5249176 and SRR5249156. All A. thaliana seeds are ordered from Arabidopsis Biological Resource Center (ABRC). Other datasets generated or analyzed during this study are included in this published article and its supplementary information files.
Angiosperm Phylogeny Group
False positive rates
General feature format
General transfer format
Genome wide association studies
Integrative genomic viewer
Linear discriminant analysis
Million years ago
Single nucleotide polymorphism
Mc CB. The origin and behavior of mutable loci in maize. Proc Natl Acad Sci U S A. 1950;36(6):344–55.
Wicker T, Sabot F, Hua-Van A, Bennetzen JL, Capy P, Chalhoub B, Flavell A, Leroy P, Morgante M, Panaud O, et al. A unified classification system for eukaryotic transposable elements. Nat Rev Genet. 2007;8(12):973–82.
Kapitonov VV, Jurka J. Rolling-circle transposons in eukaryotes. Proc Natl Acad Sci U S A. 2001;98(15):8714–9.
Xiong W, He L, Lai J, Dooner HK, Du C. HelitronScanner uncovers a large overlooked cache of Helitron transposons in many plant genomes. Proc Natl Acad Sci U S A. 2014;111(28):10263–8.
Grabundzija I, Messing SA, Thomas J, Cosby RL, Bilic I, Miskey C, Gogol-Doring A, Kapitonov V, Diem T, Dalda A, et al. A Helitron transposon reconstructed from bats reveals a novel mechanism of genome shuffling in eukaryotes. Nat Commun. 2016;7:10716.
The Plant List. [http://www.theplantlist.org/].
Arabidopsis Genome I: Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature 2000, 408(6814):796–815.
Wang X, Wang H, Wang J, Sun R, Wu J, Liu S, Bai Y, Mun JH, Bancroft I, Cheng F, et al. The genome of the mesopolyploid crop species Brassica rapa. Nat Genet. 2011;43(10):1035–9.
Liu S, Liu Y, Yang X, Tong C, Edwards D, Parkin IA, Zhao M, Ma J, Yu J, Huang S, et al. The Brassica oleracea genome reveals the asymmetrical evolution of polyploid genomes. Nat Commun. 2014;5:3930.
Parkin IA, Koh C, Tang H, Robinson SJ, Kagale S, Clarke WE, Town CD, Nixon J, Krishnakumar V, Bidwell SL, et al. Transcriptome and methylome profiling reveals relics of genome dominance in the mesopolyploid Brassica oleracea. Genome Biol. 2014;15(6):R77.
Surzycki SA, Belknap WR. Characterization of repetitive DNA elements in Arabidopsis. J Mol Evol. 1999;48(6):684–91.
Kapitonov VV, Jurka J. Molecular paleontology of transposable elements from Arabidopsis thaliana. Genetica. 1999;107(1/3):27–37.
Le QH, Wright S, Yu Z, Bureau T. Transposon diversity in Arabidopsis thaliana. Proc Natl Acad Sci U S A. 2000;97(13):7376–81.
Feschotte C, Wessler SR. Treasures in the attic: rolling circle transposons discovered in eukaryotic genomes. Proc Natl Acad Sci U S A. 2001;98(16):8923–4.
Yang L, Bennetzen JL. Distribution, diversity, evolution, and survival of Helitrons in the maize genome. Proc Natl Acad Sci U S A. 2009;106(47):19922–7.
Grabundzija I, Messing SA, Thomas J, Cosby RL, Bilic I, Miskey C, Gogol-Doring A, Kapitonov V, Diem T, Dalda A, et al. A Helitron transposon reconstructed from bats reveals a novel mechanism of genome shuffling in eukaryotes. Nat Commun. 2016;7.
Li Y, Dooner HK. Excision of Helitron transposons in maize. Genetics. 2009;182(1):399–402.
Yang L, Bennetzen JL. Structure-based discovery and description of plant and animal Helitrons. Proc Natl Acad Sci U S A. 2009;106(31):12832–7.
Wright SI, Agrawal N, Bureau TE. Effects of recombination rate and gene density on transposable element distributions in Arabidopsis thaliana. Genome Res. 2003;13(8):1897–903.
Schnable PS, Ware D, Fulton RS, Stein JC, Wei F, Pasternak S, Liang C, Zhang J, Fulton L, Graves TA, et al. The B73 maize genome: complexity, diversity, and dynamics. Science. 2009;326(5956):1112–5.
Xiong WW, Dooner HK, Du CG. Rolling-circle amplification of centromeric Helitrons in plant genomes. Plant J. 2016;88(6):1038–45.
Zabala G, Vodkin L. Novel exon combinations generated by alternative splicing of gene fragments mobilized by a CACTA transposon in Glycine max. BMC Plant Biol. 2007;7:38.
Jiang N, Bao Z, Zhang X, Eddy SR, Wessler SR. Pack-MULE transposable elements mediate gene evolution in plants. Nature. 2004;431(7008):569–73.
Morgante M, Brunner S, Pea G, Fengler K, Zuccolo A, Rafalski A. Gene duplication and exon shuffling by helitron-like transposons generate intraspecies diversity in maize. Nat Genet. 2005;37(9):997–1002.
Choi JD, Hoshino A, Park KI, Park IS, Iida S. Spontaneous mutations caused by a Helitron transposon, Hel-It1, in morning glory, Ipomoea tricolor. Plant J. 2007;49(5):924–34.
Li X, Chen L, Hong M, Zhang Y, Zu F, Wen J, Yi B, Ma C, Shen J, Tu J, et al. A large insertion in bHLH transcription factor BrTT8 resulting in yellow seed coat in Brassica rapa. PLoS One. 2012;7(9):e44145.
Gao C, Zhou G, Ma C, Zhai W, Zhang T, Liu Z, Yang Y, Wu M, Yue Y, Duan Z, et al. Helitron-like transposons contributed to the mating system transition from out-crossing to self-fertilizing in polyploid Brassica napus L. Sci Rep. 2016;6:33785.
Kohany O, Gentles AJ, Hankus L, Jurka J. Annotation, submission and screening of repetitive elements in Repbase: RepbaseSubmitter and Censor. BMC bioinformatics. 2006;7:474.
Tarailo-Graovac M, Chen N: Using RepeatMasker to identify repetitive elements in genomic sequences. Curr Protoc Bioinformatics 2009, Chapter 4:Unit 4 10.
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215(3):403–10.
Lopez R. WU-Blast2 server at the European bioinformatics institute. Nucleic Acids Res. 2003;31(13):3795–8.
Jurka J, Kapitonov VV, Pavlicek A, Klonowski P, Kohany O, Walichiewicz J. Repbase update, a database of eukaryotic repetitive elements. Cytogenetic and genome research. 2005;110(1–4):462–7.
Du C, Caronna J, He L, Dooner HK. Computational prediction and molecular confirmation of Helitron transposons in the maize genome. BMC Genomics. 2008;9(1):51.
Robinson JT, Thorvaldsdottir H, Winckler W, Guttman M, Lander ES, Getz G, Mesirov JP. Integrative genomics viewer. Nat Biotechnol. 2011;29(1):24–6.
Stein LD. Using GBrowse 2.0 to visualize and share next-generation sequence data. Brief Bioinform. 2013;14(2):162–71.
Skinner ME, Uzilov AV, Stein LD, Mungall CJ, Holmes IH. JBrowse: a next-generation genome browser. Genome Res. 2009;19(9):1630–8.
APG. An ordinal classification for the families of flowering plants. Ann Mo Bot Gard. 1998;85(4):531.
Chalhoub B, Denoeud F, Liu S, Parkin IA, Tang H, Wang X, Chiquet J, Belcram H, Tong C, Samans B, et al. Plant genetics. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome. Science. 2014;345(6199):950–3.
Murat F, Louis A, Maumus F, Armero A, Cooke R, Quesneville H, Crollius HR, Salse J. Understanding Brassicaceae evolution through ancestral genome reconstruction. Genome Biol. 2015;16(1):262.
Dittami SM, Tonon T. Genomes of extremophile crucifers: new platforms for comparative genomics and beyond. Genome Biol. 2012;13(8):166.
Hu TT, Pattyn P, Bakker EG, Cao J, Cheng JF, Clark RM, Fahlgren N, Fawcett JA, Grimwood J, Gundlach H, et al. The Arabidopsis lyrata genome sequence and the basis of rapid genome size change. Nat Genet. 2011;43(5):476–81.
Bouche F, Lobet G, Tocquin P, Perilleux C. FLOR-ID: an interactive database of flowering-time gene networks in Arabidopsis thaliana. Nucleic Acids Res. 2016;44(D1):D1167–71.
Liu H, Yu X, Li K, Klejnot J, Yang H, Lisiero D, Lin C. Photoexcited CRY2 interacts with CIB1 to regulate transcription and floral initiation in Arabidopsis. Science. 2008;322(5907):1535–9.
Zhang X, Chen Y, Wang ZY, Chen Z, Gu H, Qu LJ. Constitutive expression of CIR1 (RVE2) affects several circadian-regulated processes and seed germination in Arabidopsis. Plant J. 2007;51(3):512–25.
Biemont C, Vieira C. Genetics - junk DNA as an evolutionary force. Nature. 2006;443(7111):521–4.
Kim NS. The genomes and transposable elements in plants: are they friends or foes? Genes & Genomics. 2017;39(4):359–70.
Hollister JD, Gaut BS. Population and evolutionary dynamics of Helitron transposable elements in Arabidopsis thaliana. Mol Biol Evol. 2007;24(11):2515–24.
Sun F, Fan G, Hu Q, Zhou Y, Guan M, Tong C, Li J, Du D, Qi C, Jiang L, et al. The high-quality genome of Brassica napus cultivar 'ZS11' reveals the introgression history in semi-winter morphotype. Plant J. 2017;92(3):452–68.
Francois O, Blum MG, Jakobsson M, Rosenberg NA. Demographic history of european populations of Arabidopsis thaliana. PLoS Genet. 2008;4(5):e1000075.
Byng JW, Chase MW, Christenhusz MJM, Fay MF, Judd WS, Mabberley DJ, Sennikov AN, Soltis DE, Soltis PS, Stevens PF, et al. An update of the angiosperm phylogeny group classification for the orders and families of flowering plants: APG IV. Bot J Linn Soc. 2016;181(1):1–20.
de la Chaux N, Tsuchimatsu T, Shimizu KK, Wagner A. The predominantly selfing plant Arabidopsis thaliana experienced a recent reduction in transposable element abundance compared to its outcrossing relative Arabidopsis lyrata. Mob DNA. 2012;3(1):2.
Gan X, Stegle O, Behr J, Steffen JG, Drewe P, Hildebrand KL, Lyngsoe R, Schultheiss SJ, Osborne EJ, Sreedharan VT, et al. Multiple reference genomes and transcriptomes for Arabidopsis thaliana. Nature. 2011;477(7365):419–23.
Stover BC, Muller KF. TreeGraph 2: combining and visualizing evidence from different phylogenetic analyses. BMC bioinformatics. 2010;11:7.
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20.
Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, He G, Chen Y, Pan Q, Liu Y, et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. GigaScience. 2012(1, 1):18.
Bardou P, Mariette J, Escudie F, Djemiel C, Klopp C. jvenn: an interactive Venn diagram viewer. BMC bioinformatics. 2014;15:293.
Conesa A, Gotz S, Garcia-Gomez JM, Terol J, Talon M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005;21(18):3674–6.
Ye J, Fang L, Zheng H, Zhang Y, Chen J, Zhang Z, Wang J, Li S, Li R, Bolund L, et al. WEGO: a web tool for plotting GO annotations. Nucleic Acids Res. 2006;34(Web Server):W293–7.
Kolde R: pheatmap: Pretty Heatmaps. In., R package version 1.0.8 edn; 2015.
R Core Team: R: A Language and Environment for Statistical Computing. In.: R Foundation for Statistical Computing; 2017.
Chen C, Xia R, Chen H, He Y. TBtools, a toolkit for biologists integrating various biological data handling tools with a user-friendly interface. BioRxiv. 2018:289660.
Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32(5):1792–7.
Okonechnikov K, Golosova O, Fursov M, Team U: Unipro UGENE: a unified bioinformatics toolkit. Bioinformatics 2012, 28(8):1166–1167.
Frazer KA, Pachter L, Poliakov A, Rubin EM, Dubchak I. VISTA: computational tools for comparative genomics. Nucleic Acids Res. 2004;32(Web Server):W273–9.
Canty A, Ripley BD: boot: Bootstrap R (S-Plus) Functions. In.; 2016.
Venables WN, Ripley BD. Modern applied statistics with S. Fourth ed: Springer; 2002.
South A. Rworldmap: a new R package for mapping global data. The R Journal. 2011;3(1):35–43.
Hahsler M, Gruen B, Hornik K. Arules - a computational environment for mining association rules and frequent items sets. J Stat Softw. 2005;14(15).
We thank Shengqian Xia from The University of Chicago, Yun Zhu form The University of Hong Kong, and Chen Zhang from Michigan State University for comments on the manuscript, Xiaobin Zhao and Chunqing Liu for general support.
This study was supported by funds from the National Key Research and Development Program of China (2016YFD0100305). The funder had no role in the designing and conducting of this study and collection, analysis, and interpretation of data and in writing the manuscript.
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Figure S1. TAIR10 predicted Helitrons from RepeatMasker and EAHelitron in IGV. Figure S2. Correlation of genome size, Helitron number and Helitron density of 51 genomes (exclude maize and B. napus). Figure S3. Dot plot of LDA samples. Figure S4. Dot plot of genome size and Helitron densities of 16 Brassicaceae genomes. Figure S5. Brassicaceae phylogenetic trees. Figure S6. Helitron insertion examples in IGV. Figure S7. The 45 day live plant photos of 18 A. thaliana ecotypes. Figure S8. Helitron distribution of 18 A. thaliana ecotype genomes. (PPTX 6583 kb)
Table S1. EAHelitron uniquely predicted Helitrons and polymorphisms loci. Table S2. All Helitron LOCs and nearest TAIR ID of 18 Ath ecotypes with phenotypes. Table S3. False positive rate of Helitron programs (100 random sequences). Table S5. RepHel percent of Helitrons in Brassicaceae. Table S6. Six Brassicaceae genomes Helitron 3’ end upstream 1 kbp sequences homology rate. Table S7. Brassicaceae gene density correlation of Helitron density (window = 1 Mb, step = 500 kb). Table S10. TAIR10 predict Helitron inserted into intron or UTR genes. Table S11. The 216 single rules associated with Flowering-Time types. (XLSX 139 kb)
Table S4. All Genomes information. (XLSX 34 kb)
Table S8. Brassicaceae Helitron inserted genes. (XLSX 4171 kb)
Table S9. GO and KEGG pathway enrichment of Brassicaceae Helitron inserted genes. (XLSX 33 kb)
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Hu, K., Xu, K., Wen, J. et al. Helitron distribution in Brassicaceae and whole Genome Helitron density as a character for distinguishing plant species. BMC Bioinformatics 20, 354 (2019). https://doi.org/10.1186/s12859-019-2945-8
- Transposable element
- Plant classification
- Multivariate analysis
- Genomic evolution