Open Access

Segmental duplications: evolution and impact among the current Lepidoptera genomes

BMC Evolutionary BiologyBMC series – open, inclusive and trusted201717:161

https://doi.org/10.1186/s12862-017-1007-y

Received: 21 February 2017

Accepted: 23 June 2017

Published: 6 July 2017

Abstract

Background

Structural variation among genomes is now viewed to be as important as single nucleoid polymorphisms in influencing the phenotype and evolution of a species. Segmental duplication (SD) is defined as segments of DNA with homologous sequence.

Results

Here, we performed a systematic analysis of segmental duplications (SDs) among five lepidopteran reference genomes (Plutella xylostella, Danaus plexippus, Bombyx mori, Manduca sexta and Heliconius melpomene) to understand their potential impact on the evolution of these species. We find that the SDs content differed substantially among species, ranging from 1.2% of the genome in B. mori to 15.2% in H. melpomene. Most SDs formed very high identity (similarity higher than 90%) blocks but had very few large blocks. Comparative analysis showed that most of the SDs arose after the divergence of each linage and we found that P. xylostella and H. melpomene showed more duplications than other species, suggesting they might be able to tolerate extensive levels of variation in their genomes. Conserved ancestral and species specific SD events were assessed, revealing multiple examples of the gain, loss or maintenance of SDs over time. SDs content analysis showed that most of the genes embedded in SDs regions belonged to species-specific SDs (“Unique” SDs). Functional analysis of these genes suggested their potential roles in the lineage-specific evolution. SDs and flanking regions often contained transposable elements (TEs) and this association suggested some involvement in SDs formation. Further studies on comparison of gene expression level between SDs and non-SDs showed that the expression level of genes embedded in SDs was significantly lower, suggesting that structure changes in the genomes are involved in gene expression differences in species.

Conclusions

The results showed that most of the SDs were “unique SDs”, which originated after species formation. Functional analysis suggested that SDs might play different roles in different species. Our results provide a valuable resource beyond the genetic mutation to explore the genome structure for future Lepidoptera research.

Keywords

Segmental duplications Lepidoptera Evolution

Background

Segmental duplications (SDs) are DNA fragments with near-identical sequences that are greater than 1Kb [1]. They have been recognized as important mediators of gene and genome evolution, and are considered the origins for gene gain, functional diversification, and gene family expansion [1, 2]. The outcomes of a gene duplication event may lie on lineage-specific selection. In this situation, the new gene copy has the opportunity to acquire novel or modified functions or become non-functional [3, 4]. These new copies are often important for the adaption of the species to certain environments [2]. SDs can lead to various types of genome rearrangements [5] and other genome structural changes between and within species [68].

Characterization and annotation of SDs are important for understanding the structure and evolution of a genome and have been explored in many organisms’ whole genomes [915]. Few systematically comparative analyses of SDs however have been performed until now. The most important example is primate genomes, used to understand the pattern and rates of SDs during hominid evolution [6]. Here, we performed the comparative analysis of SDs in the whole genomes of five Lepidoptera insects, diamondback moth (Plutella xylostella), Monarch butterfly (Danaus plexippus), silkworm (Bombyx mori), Carolina sphinx moth (Manduca sexta), and postman butterfly (Heliconius melpomene), to understand the roles of SDs during the evolution of Lepidoptera. Our analysis revealed that duplication activities varied in terms of number of base pairs or events among these different species. The marked difference of transposable elements (TEs) content in the flanking regions of SDs among these species of Lepidoptera suggested various formation mechanisms of SDs. Our functional analysis of the SDs indicated that gene families embedded in the SDs were different among the five genomes and these gene families may be related to species-specific adaptive evolution.

Methods

Data sources

The five Lepidoptera insect species, P. xylostella, B. mori, D. plexippus, M. sexta, and H. melpomene, were used to construct the SD map. The genome and predicted transcripts of diamondback moth was downloaded from DBM database (http://www.insect-genome.com/) [16]. The other genomes resources of Lepidoptera insects were downloaded from SilkDB (http://silkworm.genomics.org.cn/) [17], Heliconius Genome Project (http://www.butterflygenome.org/) [18], MonarchBase (http://www.insect-genome.com/) [19] and Carolina sphinx dataset (ftp://ftp.bioinformatics.ksu.edu/pub/Manduca/OGS2/).

Computational analysis of lepidoptera segmental duplications

We used the Whole-Genome Assembly Comparison (WGAC) method to detect the segmental duplications in the five Lepidoptera species. The insect genomes were first masked at 15% divergence level from transposable elements (TEs), high-copy repeats or simple sequence repeats (SSR) using RepeatMasker (Smit and Green http://www.repeatmasker.org/, version 4.0.6). We then used silkworm TE dataset [20] as repeat database to re-run the RepeatMasker to mask as much TEs as possible. All these repeats were deleted from the sequences and the remaining genome sequences were used to perform BLASTN searches against themselves with reduced affine gap extension parameters, which allowed gaps up to 1000 bp and e value (1e−20).

After discarding self-alignments, the repeat sequences were reinserted back into these alignments. These seed alignments were subsequently used as queries to search against the unmasked genome using BLASTN, which generated accurate alignment statistics. Considering the high rate of heterozygosity of these Lepidoptera species (except silkworm, which has a long history of domestication and inbreeding) [16, 18, 21], we conservatively lowered the identity threshold to 75% for alignments in order to capture more divergent SDs than under the 90% usual threshold. Selected alignments were those with a length longer than 1 kb and identity higher than 75%.

Gene content and functional annotation

Gene content of segmental duplications was accessed using the GFF files obtained from the dataset above (see data sources). We also assessed whether the molecular function, biological process, and pathway terms were over-represented in SDs using Blast2Go [22]. For each SD, we computed an expected number of genes for different biological processes based on their curated representation in the reference genome. The statistical significance of the functional GO Slim enrichment was evaluated using the Fisher’s exact test (p < 0.05).This analysis showed the GO terms that were significantly enriched among genes within SDs. Pfam was also used to annotate the function of the genes in the SDs [23].

RNA-seq analysis

We collected the RNA-seq data from published sources to access the gene expression level within and outside SDs regions. These data included different tissues or different developmental stages of diamondback moth [16], silkworm [24] and Carolina sphinx moth [25]. All the reads were mapped back to its genome using TopHat [26]. The expression abundance (RPKM) was calculated using CuffLinks [27]. The expression levels were assessed as Log10 (RPKM). Gene expression levels within and outside SDs regions as well as the variables were compared using a T-test with a Bonferroni correction.

Results and discussion

Segmental duplication maps among different Lepidoptera species

Using WGAC, we developed segmental duplication maps for each of the five Lepidoptera species’ genomes (Table 1). SD contents greatly varied among the five Lepidoptera species, ranging from 1.2% in Bombyx mori to 15.2% in Heliconius melpomene (Table 1, Additional file 1: Table S1). SDs with highest identity (≥90%) was the majority (ranging from 80% in M. sexta to 93% in D. plexippus) (Table 1). Based on our analysis, duplications varied in size from 5.6 Mbp in silkworm to 43 Mbp in P. xylostella. P. xylostella and H. melpomene showed the highest number of duplications (Table 1) suggesting that their genomes could be unstable or capable of tolerating extensive levels of variation. For example, in human, segmental duplications play an “expanding” role in genomic instability [28].
Table 1

Characterization of the SDs of the five Lepidoptera species

Species

P. xylostella

M. sexta

H. melpomene

D. plexippus

B. mori

Total number of SDs

21,369

11,141

23,942

10,799

3667

Number of SDs with 90% identity

18,064

8892

21,572

10,070

3221

Number of SDs with 80-90% identity

3204

2171

2239

668

416

Number of SDs with 75-80% identity

99

78

127

60

5

Total (Mb)

43

19.1

40.5

23.5

5.6

% of genome

11

5.2

15.2

9.9

1.2

Number of genes

2235

1040

1453

1564

332

% of genes

12.4

6.8

11

10.3

2.3

The analysis of the length of SDs in all five species indicated that the Lepidoptera genomes were significantly poor in large blocks (>4 Kb) (T-test, P < 0.025; Fig. 1). This is consistent with SDs data reported in Drosophila genome (Fiston-Lavier et al. 2007) and silkworm genome [29, 30]. The number of SDs in Lepidoptera decreased along with the increase in SDs length (Fig. 1a) and this was true for all five species (Fig. 1b). Eichler [31] has suggested that SDs in invertebrates are much smaller in length than in vertebrates. These differences probably reflect some evolutionary constraints imposed by the smaller size of the invertebrate genome [32].
Fig. 1

SDs length distributions among 5 Lepidoptera species. a Boxplots showing the mean and range of the numbers of SD for each SD length category for all five Lepidoptera species combined. Most SDs were found in the 1–1.5 kb length category. b Number of SDs of different length categories for each species. The size of the circle represents the proportion of SDs

We use RepeatMasker (Smit and Green http://www.repeatmasker.org/, version 4.0.6) to mask the transposable elements (TEs; masked at 15% divergence level), high-copy repeats or simple sequence repeats (SSR). Then silkworm TE dataset [20] was used as repeat database to rerun the RepeatMasker to mask as much TEs as possible. Thus, we used different repeat databases to mask the target genomes. The result showed that almost 22.6% of the silkworm genome was masked while 2.05% - 4.97% of other Lepidoptera genomes were masked (P. xylostella: 3.12%, D. plexippus: 2.05%, M. sexta: 4.97% and H. melpomene: 2.25%). Osanai-Futahashi et al. [33] have shown that TEs are enriched in the genome of silkworm and TEs may play important roles during the domestication of silkworm [34]. Thus, the high proportion of SDs in H. melpomene may result from some TEs left in the genome.

Comparative analysis of duplication maps among five Lepidoptera species

We further characterized each SD as “unique” or “shared”, depending on whether they exist in only one or multiple genomes. The comparative SD maps revealed that most of the segmental duplications were “unique” SDs (Fig. 2). For example, the number of shared SDs among the five Lepidoptera species varied from 83 in B. mori (e.g. 83 SDs from B. mori shared with other Lepidoptera genomes) to 1817 in H. melpomene (e.g. 1817 SDs from H. melpomene shared with other Lepidoptera genomes) (Fig. 3a).
Fig. 2

Duplication map comparison of five Lepidoptera species. SDs regions in each Lepidoptera species and their paralogous regions in other four genomes were shown. Different colors represent different insects. Only the best alignments were listed

Fig. 3

“Shared” and “Unique” SDs among 5 species. a “Shared” and “Unique” SDs in each genome. Red represents “Unique” SDs while black represents “Shared” SDs. b SDs classification of the five species based on the existing SDs (marked as “+”) and absence SDs (marked as “-”). We classified the SDs into five groups to analyze evolutionary history of SDs in Lepidoptera genome. Group A are the potential ancestral SDs events. Group B showed the SDs that were only lost in Noctuoidea and Bombycoidea while Groups C, D and E showed regions where duplication patterns were inconsistent with the generally accepted phylogeny. Such a scenario could arise as a result of a de novo origin of SDs or as a result of deleted events, which might have played a role in lineage-specific evolution. “n” represents the number of group A, B, C, D or E. c Identity comparison between “Shared” and “Unique” SDs in the genomes of the five Lepidopteron species. The identity of “Shared” SDs is marked as black while the identity of “Unique” SDs is marked as red

Butterflies (D. plexippus and H. melpomene) shared more SDs with each other than with the other species (Fig. 2) indicating their closer relationship. Silkworm and Carolina sphinx moth also shared more common SDs than with the other species, indicating their close relationship. These results are consistent with the phylogeny of Lepidoptera published by Regier et al. [35].

Based on the phylogeny of Lepidoptera [35], it was possible to assess the origins of some SDs within specific lineages and ancestral events of SDs. Since segments might have mutated after divergence, we attempted to map duplication events onto the phylogenetic tree using reconciliation method (software like NOTUNG). However, based on the blast search analysis, we found that the “unique” SDs could not find the homologous sequences in other Lepidoptera species. We had two speculations to explain this result: (1) The segments might have mutated after duplications or (2) SDs arose after the divergence of each lineage. In the first situation, all the copies should have mutated and evolved rapidly, resulting in sequence variation being too high to find a blast hit in other genomes. If so, it would be difficult to trace the ancestral sequences onto the phylogenetic tree using reconciliation method such as Notung. Thus, we classified the SDs into five groups (Fig. 3b) and focused on analyzing evolutionary history of SDs in Lepidoptera genome. To identify the potential ancestral SDs events, we initially focused on shared duplications among all five species (Group A) but none were identified (Fig. 3b),suggesting that the original SDs might have been lost early during the evolution of Lepidoptera or the origins of the SDs are along with the speciation of the Lepidoptera. The second situation would lead to some SDs that only exist in one or a few genomes.

We then analyzed the SDs that were only lost in Noctuoidea and Bombycoidea (Group B, Fig. 3b). There were 46 cases found in this group. As part of our comparative analyses, we also found some regions where duplication patterns were inconsistent with the generally accepted phylogeny (Groups C, D, and E; Fig. 3b). Such a scenario could arise as a result of a de novo development of SDs or as a result of deleted events, which might play a role in lineage-specific evolution. Groups C and D (Fig. 3b) were more common than the other groups due to their closer relationship with species based on the evolution history (Fig. 3b). The previous study of Marques-Bonet et al. [6] reports that humans share a greater number of SDs with chimpanzees than macaque or orangutan. Only 49 common SDs were lost in D. plexippus and H. melpomene (Group E). Since the time of Lepidoptera speciation is relatively long, we cannot test the complete phylogeny of SDs, and a greater number of sequenced Lepidoptera genomes would be necessary to elucidate this aspect.

We speculated that the “shared” SDs between species might represent the “ancestral sequences” as they remained conserved in the genomes during the evolution of Lepidoptera. To test this speculation, we analyzed the alignment identity of “shared SDs” and “unique SDs” and found that “shared SDs” had significantly higher identity comparing with the “unique SDs” (P < 0.01, T-test), except for silkworm (Fig. 3c). The results indicated that “shared SDs” might be more conserved than the “unique SDs”. Silkworm has diverged from the other species due to its domestication and inbreeding history leading to extremely low level of heterozygosity [36]. We compared the SDs in silkworm with the artificial selected regions that were identified in Xia et al. [36] and found that eight SD regions overlapped with the artificial selected regions, suggesting that these SDs may be related with the silkworm domestication. However, none of these eight regions were “shared SDs”, which also indicated that these unique SDs may be involved in the lineage-specific domestication. We also tested the difference of variance between “shared” and “unique” SDs (Fig. 3c) and showed that in P. xylostella, D. plexippus and H. melpomene, the differences were not significant (p = 0.05755; p = 0.5304 and p = 0.6278, respectively). Only B. mori and M. sexta showed significant differences (p = 1.218e-05 and p = 0.03909).

Sequence properties of the SDs in the five studied species

The analysis and comparison of the composition of genes in the SDs among the five Lepidoptera species showed that 2235, 1036, 1453, 1564 and 332 putative genes could be identified in P. xylostella, M. sexta, H. melpomene, D. plexippus and B. mori respectively (Table 1, Additional file 2: Table S2). Most of the segmental duplication intervals identified contained gene duplicates, ranging from 58% in silkworm to 94% in H. melpomene (Additional file 3: Table S3). We further characterized the genes as “shared” or “unique” based on whether they were located in the “shared SDs” or “unique SDs”. The results showed that most of the genes belonged to the “unique” genes, with only 31, 26, 13, 6, and 3 genes belonging to “shared” genes in P. xylostella, M. sexta, D. plexippus, H. melpomene, and B. mori, respectively. These results suggested that most of the genes in SDs could play different roles in different species. We hypothesized that these genes might be involved in lineage-specific evolution and particular gene classes might be overrepresented in the SDs.

To test the hypothesis, we used Gene Ontology (GO) to annotate all the genes and showed that each species had different GO enrichments and gene families (Table 2; Additional file 4: Table S4). In P. xylostella, 25 proteins were identified such as serine-type endopeptidase activity (GO: 0004252), structural constitute of cuticle (GO: 0042302), and nucleic acid binding (GO: 0003676) (Table 2). Based on previous study of differential expression in response to host-plant on Swedish comma, Polygonia c-album, these genes may be related to host-feeding [37, 38]. Thus, we suggested that the genes in SDs of diamondback moth might be related with its host-feeding behavior.
Table 2

GO enrichment for some proteins within the SDs regions among the five Lepidoptera species

GO term

p-value

Number of proteins

P. xylostella

 Nucleic acid binding [GO:0003676]

5.78E-06

149

 Oxidoreductase activity [GO:0016491]

1.64E-05

16

 Oxidation-reduction process [GO:0055114]

0.0005938

38

 Serine-type endopeptidase activity [GO:0004252]

0.001488

54

 Protein tyrosine phosphatase activity [GO:0004725]

0.003778

12

 Protein dephosphorylation [GO:0006470]

0.005278

14

 Structural constituent of cuticle [GO:0042302]

0.006409

3

 Zinc ion binding [GO:0008270]

0.008232

151

M. sexta

 Prothoracicotrophic hormone activity [GO:0018445]

2.99E-06

10

 Growth factor activity [GO:0008083]

0.0026

5

 Phosphorylase kinase complex [GO:0005964]

0.003736

3

 SWI/SNF complex [GO:0016514]

0.003736

3

 Phosphorylase kinase activity [GO:0004689]

0.003736

3

 Phosphoprotein phosphatase activity [GO:0004721]

0.00556

6

 Neuropeptide signaling pathway [GO:0007218]

0.007097

13

 Defense response [GO:0006952]

0.00955

3

H. melpomene

 ATP-dependent peptidase activity [GO:0004176]

0.002622

2

 Misfolded or incompletely synthesized protein catabolic process [GO:0006515]

0.002622

2

 DNA integration [GO:0015074]

0.008793

2

 Inositol-1,4,5-trisphosphate 3-kinase activity [GO:0008440]

0.008793

2

D. plexippus

 Dephosphorylation [GO:0016311]

0.002541

12

 RNA-directed DNA polymerase activity [GO:0003964]

0.002617

16

 Glucuronosyltransferase activity [GO:0015020]

0.003223

10

 Endonuclease activity [GO:0004519]

0.004409

14

 Carbohydrate transport [GO:0008643]

0.005052

12

 Pyrophosphatase activity [GO:0016462]

0.008074

4

 Riboflavin metabolic process [GO:0006771]

0.009158

8

 Rho guanyl-nucleotide exchange factor activity [GO:0005089]

0.00975

10

B. mori

 Heme binding [GO:0020037]

1.30E-06

13

 Monooxygenase activity [GO:0004497]

2.09E-06

13

 Hormone activity [GO:0005179]

0.0001028

6

 Electron transport [GO:0006118]

0.0003995

18

 Calcium ion binding [GO:0005509]

0.00205

10

 Response to oxidative stress [GO:0006979]

0.003103

3

 Odorant binding [GO:0005549]

0.003145

6

 Oxidoreductase activity [GO:0016491]

0.00358

16

In M. sexta, we identified a GO enrichment of prothoracicotrophic hormone activity (GO: 0018445). The prothoracicotropic hormone (PTTH) is well studied in tobacco hornworm (Rountree and Bollenbacher 1986) and in M. sexta, it is related to molting and metamorphosis [39, 40]. In D. plexippus, we identified the GO enrichment of glucuronosyltransferase activity (GO: 0015020). In silkworm, UDP-glucuronosyltransferase (UGT) plays a role in detoxification processes, such as minimizing the harmful effects of ingested plant allelochemicals [41]. Also, we identified the enrichment of Rho guanyl-nucleotide exchange factor activity (GO: 0005089), which is a modulator in the signaling pathway of Ras/MAPK and Wnt. Previous studies have shown that this activity is associated with neuronal growth cone and planar cell polarity formation [42, 43]. In B. mori, consistent with [30], we identified the enrichment of monooxygenase activity (GO: 0004497), which might be associated with detoxification.

To further clarify the functions of SDs in each Lepidoptera species, we annotated the gene functions in the SDs regions using Pfam and although the GO enrichments differed among species, some of the gene families embedded in the SDs were the same for the five species (Additional file 5: Table S5). For example, genes in SDs can be classified into three categories: (1) detoxification, (2) immunity, and (3) environmental signal recognition, which are similar to other mammals and insects [30, 44]. These genes are very important in drug detoxification, defense, and receptor and signal reorganization. The cytochrome P450s (P450s), for example, are important proteins for insect growth and development and have been found to play various functions such as biosynthesis of hormones, and inactivation and metabolism of xenobiotic compounds such as pesticides [4547]. In this study, P450s were identified in all five species (8, 13, 15, 12, 10 SDs regions in P. xylostella, B. mori, M. sexta, D. plexippus and H. melpomene, respectively). In P. xylostella, Yu et al. [48] report strong expression of 84 functional cytochrome P450 genes, many of them, especially CYP367s, contributing to detoxification or metabolic processing of environmental chemicals.

We also identified the trypsin in the five species (55, 7, 24, 19, 2 SDs regions in P. xylostella, B. mori, M. sexta, D. plexippus and H. melpomene, respectively), which may be involved in immunity [49]. The glucose-methanol-choline (GMC) oxidoreductases, shown to be involved in developmental and physiological processes, and immunity [50], were also identified in four of the five species (1, 4, 5, 4 SDs regions in B. mori, M. sexta, D. plexippus and H. melpomene, respectively).

Some species-specific genes in SDs regions were also identified including 13 Lepidopteran-specific Lipoprotein_11 in silkworm. Zhang et al. [51] have shown that this family is involved in various physiological processes such as energy storage, embryonic development and immunity. These SDs might have played a role in the silkworm-specific evolution. Some lineage-specific expansion genes were also embedded in the SDs regions. For example, we identified 167 zinc-finger proteins in the SD regions of P. xylostella, which was much more than in any other species (20, 73, 91 and 8 in B. mori, M. sexta, D. plexippus and H. melpomene). A recent study (data unpubl.) of transcription factors in diamondback moth indicates that zinc-finger proteins may be expanded, also suggesting their potential important functions in the DBM. The zinc-finger has been shown to function in a variety of biological processes, such as DNA-binding, RNA-binding, protein-protein interactions, developmental processes and differentiation [52]. Further studies on expression patterns showed that the expression of some zinc-fingers were significantly different between susceptible and resistant strains (data unpublished). However, more researches are needed to illustrate the functions of these zinc-fingers.

Zhao et al. [30] report in silkworm that SDs are characterized by enrichment of DNA transposons and LTR retrotransposons. These observed enrichments in the flanking regions of SDs in silkworm suggest a potential implication in the formation of repeats in SDs. In this study, the TEs composition was analyzed by comparing the sequences near the SDs regions and found that DNA transposons were enriched in SDs regions as well as flanking regions of most species except H. melpomene (Table 3). Like in silkworm, DNA transposons and LTR (long terminal repeat) retrotransposons were enriched in the region of SDs and flanking regions in P. xylostella (Table 3), suggesting similar potential roles in SD formation. In M. sexta and D. plexippus, only DNA transposons were found to be enriched (Table 3). In H. melpomene, all analyzed TEs, except DNA transposons, were enriched in the SDs and flanking regions (Table 3) with LINEs (long interspersed nuclear elements) being the most abundant. These results suggest that short interspersed nuclear elements (SINEs), LTR and LINEs may also be involved in the formation of SDs in the genome of H. melpomene.
Table 3

TEs properties of the Lepidoptera genomes, duplications and 2.5 Kb flanking regions

Repeat

Duplication

%

2.5 Kb FR

%

Genome

%

Enrichment in SDs

Enrichment in FR

P. xylostella

DNA

72,462

0.167

55,718

0.053

180,461

0.046

3.653

1.152

 SINE

3040

0.007

22,679

0.021

258,493

0.066

0.107

0.327

LTR

18,614

0.043

10,333

0.010

23,611

0.006

7.173

1.632

 LINE

249,583

0.576

129,227

0.122

628,430

0.159

3.613

0.767

M. sexta

DNA

11,814

0.062

22,773

0.045

128,714

0.031

2.015

1.462

 SINE

361

0.002

2714

0.005

48,452

0.011

0.164

0.463

 LTR

131

0.001

1537

0.003

12,658

0.003

0.227

1.004

 LINE

18,312

0.096

19,895

0.039

156,948

0.037

2.561

1.048

D. plexippus

DNA

12,322

0.052

22,852

0.044

73,287

0.029

1.779

1.484

 SINE

2783

0.012

4447

0.009

21,783

0.009

1.352

0.972

 LTR

555

0.002

1975

0.004

7333

0.003

0.800

1.282

 LINE

6026

0.026

4729

0.009

57,808

0.023

1.103

0.389

H. melpomene

 DNA

483

0.001

20,348

0.017

51,129

0.019

0.064

0.938

SINE

23,660

0.058

15,872

0.014

26,036

0.009

6.169

1.436

LTR

7735

0.019

14,801

0.013

12,676

0.004

4.143

2.751

LINE

171,528

0.423

129,144

0.111

243,145

0.088

4.789

1.251

DNA DNA transposons, SINE short interspersed nuclear elements, LTR long terminal repeat, LINE long interspersed nuclear elements

The TEs contents of three regions of the genomes were compared: SDs regions; 2.5 Kb flanking regions (FR) of the SDs and the genome average. Enrichment was defined as the repeat content of duplicated sequences divided by the repeat content of unique sequences. The significance was performed by simulating the repeats in a random sample (n = 1,00) of DBM SDs (P-value < 0.05 were in bold)

Effects of SDs on gene expression

An initial study of lymphoblastoid cell lines in human has shown that CNVs have some effects on gene expression [53]. For example, changes in the number of copies can explain almost 20% of the variation in gene expression [53]. This effect can be the results of gene dosage within SDs or SDs on neighboring genes [5356]. To assess the effect of SDs on the transcriptomes, we explored the genome-wide expression of three of the Lepidoptera species, P. xylostella, B. mori, and M. sexta, at different developmental stages, different tissues and different strains using RNA-seq data (NCBI website). We found that the gene expression levels embedded within our SDs regions were significantly lower than that of other genes located elsewhere in the genome. This was true for all analyzed available developmental stages or tissues (T-test, p < 2.20E-16) (Fig. 4). For example, in P. xylostella, we analyzed the expression pattern of genes within and outside the SD regions in different developmental stages. The results showed that the expression values of genes within SDs were significantly lower than the genes outside the SDs regions (T-test, p < 0.01, Fig. 4a). We redid the same analysis on the silk gland from different strains of B. mori and different tissues of M. sexta and found similar expression patterns: genes located in SDs had lower expression values than the genes outside SDs (Fig. 4b and c).
Fig. 4

Expression levels are associated with segmental duplications in the 5 species. a Expression level analysis in P. xylostella. Different developmental stages (from egg to adult) are listed. The expression level for the genes located in SDs is marked as red while the expression level for the genes outside SDs is marked as black. b Expression level analysis in M. sexta. Different tissues and developmental stages used in the analysis are listed. The expression level for the genes located in SDs is marked as green while the expression level for the genes outside SDs is marked as black. c Expression level analysis in silk gland of B. mori. Different strains were analyzed including domesticated strain Chunhua (D_CH), domesticated strain Chunyu (D_CY), wild silkworm Ankang from Baihe county of Shanxi Province (W_AKBH) and wild silkworm Ankang from Shiquan county of Shanxi Province (W_AKSQ). d Methylation level comparison between genes within and without SDs regions based on silkworm data

A possible reason for this may be that some regulation mechanisms control the gene expression within SDs. Based on our analysis above, we found that some TEs were enriched in the SDs as well as the SDs’ flanking regions (Table 3). In silkworm, methylation levels in TEs regions are extremely low compared to the rest of the genome [57]. Epigenetic regulation in insects can have various effects on biological processes. In silkworm, CG methylation is enriched in gene bodies and is positively correlated with gene expression level, indicating its positive roles in gene transcription [57]. We therefore analyzed the CG methylation level of the genes embedded in the SD regions as well as the genes outside the SDs regions for the five species and did not find any CG methylation in gene bodies of SDs (Fig. 4c). This may explain the low gene expression levels in SDs regions. However, more CG methylation information from other Lepidoptera species may be needed to further validate this conclusion.

Conclusion

Structural variation between genomes is important in phenotype differentiation and genome evolution. Here, we performed a comparative analysis of segmental duplications (SDs) among five lepidopteran reference genomes (P. xylostella, D. plexippus, B. mori, M. sexta and H. melpomene). We found that the SDs contents greatly varied among the five species. Comparative analyses of SDs showed that most of them arose after the divergence of each lineage. The most closely related species based on the phylogenetic tree also shared more common SDs. Conserved ancestral SDs and species specific SD events were assessed, revealing multiple examples of gain, loss or maintenance of SDs over time. The results indicated that SDs might have undergone loss or gain during the evolution of the genome. We further analyzed the genes embedded in SDs regions and the result showed that most of the genes were located in the species-specific SDs (“Unique” SDs). Functional analysis of these genes suggested their potential roles in the lineage-specific evolution. Comparison of gene expression between SDs and non-SDs showed that the expression levels of genes embedded in SDs were significantly lower, suggesting that structural changes in the genomes were involved in gene expression differences within each species. Our results suggested that SDs might have been involved in the species-specific evolution. They thus provide a valuable resource beyond the genetic mutation to explore the genome structure for future Lepidoptera research.

Abbreviations

CNV: 

Copy number variations;

GO: 

Gene Ontology

SD: 

Segmental duplications

SSR: 

Simple sequence repeats

TE: 

Transposable elements

WGAC: 

Whole-Genome Assembly Comparison

Declarations

Acknowledgements

We would like to extend our gratitude to Simon Wade Baxter, for his advice and useful suggestions on this study.

Funding

This work is supported by National Natural Science Foundation of China (No. 31320103922 and No. 31230061), Natural Science Foundation of Fujian Province (No. 2017 J0102). LV is supported by the “111” Program of SAFEA and the Minjiang Scholarships.

Availability of data and materials

All data generated during this study are included in this articles and its supplementary information.

Author’s contributions

QZ carried out data processing, analysis and wrote the manuscript; MY conceived and designed the study; DM helped to collect the data used in this study and LV helped draft the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
State Key Laboratory for Ecological Pest Control of Fujian/Taiwan Crops and College of Life Science, Fujian Agriculture and Forestry University
(2)
Institute of Applied Ecology, Fujian Agriculture and Forestry University
(3)
Fujian-Taiwan Joint Centre for Ecological Control of Crop Pests, Fujian Agriculture and Forestry University
(4)
Key Laboratory of Integrated Pest Management for Fujian-Taiwan Crops, Ministry of Agriculture
(5)
Department of Biological Sciences, Brock University

References

  1. Marques-Bonet T, Girirajan S, Eichler EE. The origins and impact of primate segmental duplications. Trends Genet. 2009;25(10):443–54.View ArticlePubMedPubMed CentralGoogle Scholar
  2. Duda TF Jr, Palumbi SR. Molecular genetics of ecological diversification: duplication and rapid evolution of toxin genes of the venomous gastropod Conus. Proc Natl Acad Sci U S A. 1999;96(12):6820–3.View ArticlePubMedPubMed CentralGoogle Scholar
  3. Lynch M, Conery JS. The evolutionary fate and consequences of duplicate genes. Science. 2000;290(5494):1151–5.View ArticlePubMedGoogle Scholar
  4. Conant GC, Wolfe KH. Turning a hobby into a job: how duplicated genes find new functions. Nat Rev Genet. 2008;9:938–50.View ArticlePubMedGoogle Scholar
  5. Albano F, Anelli L, Zagaria A, Coccaro N, D'Addabbo P, Liso V, et al. Genomic segmental duplications on the basis of the rearrangement in chronic myeloid leukemia. Oncogene. 2010;29(17):2509–16.View ArticlePubMedGoogle Scholar
  6. Marques-Bonet T, Kidd JM, Ventura M, Graves TA, Cheng Z, Hillier LW, et al. A burst of segmental duplications in the genome of the African great ape ancestor. Nature. 2009;457(7231):877–81.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Goidts V, Cooper DN, Armengol L, Schempp W, Conroy J, Estivill X, et al. Complex patterns of copy number variation at sites of segmental duplications: an important category of structural variation in the human genome. Hum Genet. 2006;120(2):270–84.View ArticlePubMedGoogle Scholar
  8. Sharp AJ, Locke DP, McGrath SD, Cheng Z, Bailey JA, Vallente RU, et al. Segmental duplications and copy-number variation in the human genome. Am J Hum Genet. 2005;77(1):78–88.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Bailey JA, Gu Z, Clark RA, Reinert K, Samonte RV, Schwartz S, et al. Recent segmental duplications in the human genome. Science. 2002;297(5583):1003–7.View ArticlePubMedGoogle Scholar
  10. Cheng Z, Ventura M, She X, Khaitovich P, Graves T, Osoegawa K, et al. A genome-wide comparison of recent chimpanzee and human segmental duplications. Nature. 2005;437(7055):88–93.View ArticlePubMedGoogle Scholar
  11. Kim PM, Lam HY, Urban AE, Korbel JO, Affourtit J, Grubert F, et al. Analysis of copy number variants and segmental duplications in the human genome: Evidence for a change in the process of formation in recent evolutionary history. Genome Res. 2008;18(12):1865–74.View ArticlePubMedPubMed CentralGoogle Scholar
  12. She X, Jiang Z, Clark RA, Liu G, Cheng Z, Tuzun E, et al. Shotgun sequence assembly and recent segmental duplications within the human genome. Nature. 2004;431(7011):927–30.View ArticlePubMedGoogle Scholar
  13. She X, Cheng Z, Zollner S, Church DM, Eichler EE. Mouse segmental duplication and copy number variation. Nat Genet. 2008;40(7):909–14.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Umemori J, Mori A, Ichiyanagi K, Uno T, Koide T. Identification of both copy number variation-type and constant-type core elements in a large segmental duplication region of the mouse genome. BMC Genomics. 2013;14:455.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Nicholas TJ, Cheng Z, Ventura M, Mealey K, Eichler EE, Akey JM. The genomic architecture of segmental duplications and associated copy number variants in dogs. Genome Res. 2009;19(3):491–9.View ArticlePubMedPubMed CentralGoogle Scholar
  16. You M, Yue Z, He W, Yang X, Yang G, Xie M, et al. A heterozygous moth genome provides insights into herbivory and detoxification. Nat Genet. 2013;45(2):220–5.View ArticlePubMedGoogle Scholar
  17. Duan J, Li R, Cheng D, Fan W, Zha X, Cheng T, et al. SilkDB v2.0: a platform for silkworm (Bombyx mori) genome biology. Nucleic Acids Res. 2009;38(Database issue):D453–6.PubMedPubMed CentralGoogle Scholar
  18. Consortium THG. Butterfly genome reveals promiscuous exchange of mimicry adaptations among species. Nature. 2012;487(7405):94–8.Google Scholar
  19. Zhan S, Reppert SM. MonarchBase: the monarch butterfly genome database. Nucleic Acids Res. 2012;41(Database issue):D758–63.PubMedPubMed CentralGoogle Scholar
  20. Xu HE, Zhang HH, Xia T, Han MJ, Shen YH, Zhang Z. BmTEdb: a collective database of transposable elements in the silkworm genome. Database. 2013;2013:bat055.PubMedPubMed CentralGoogle Scholar
  21. Zhan S, Merlin C, Boore JL, Reppert SM. The monarch butterfly genome yields insights into long-distance migration. Cell. 2011;147(5):1171–85.View ArticlePubMedPubMed CentralGoogle Scholar
  22. Gotz S, Garcia-Gomez JM, Terol J, Williams TD, Nagaraj SH, Nueda MJ, et al. High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res. 2008;36(10):3420–35.View ArticlePubMedPubMed CentralGoogle Scholar
  23. Finn RD, Mistry J, Tate J, Coggill P, Heger A, Pollington JE, et al. The Pfam protein families database. Nucleic Acids Res. 2010;38(Database issue):D211–22.View ArticlePubMedGoogle Scholar
  24. Fang SM, Hu BL, Zhou QZ, Yu QY, Zhang Z. Comparative analysis of the silk gland transcriptomes between the domestic and wild silkworms. BMC Genomics. 2015;16:60.View ArticlePubMedPubMed CentralGoogle Scholar
  25. Whittington E, Zhao Q, Borziak K, Walters JR, Dorus S. Characterisation of the Manduca sexta sperm proteome: Genetic novelty underlying sperm composition in Lepidoptera. Insect Biochem Mol Biol. 2015;62:183–93.View ArticlePubMedGoogle Scholar
  26. Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25(9):1105–11.View ArticlePubMedPubMed CentralGoogle Scholar
  27. Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc. 2012;7(3):562–78.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Emanuel BS, Shaikh TH. Segmental duplications: an ‘expanding’ role in genomic instability and disease. Nat Rev Gene. 2001;2(10):791–800.View ArticleGoogle Scholar
  29. Fiston-Lavier AS, Anxolabehere D, Quesneville H. A model of segmental duplication formation in Drosophila melanogaster. Genome Res. 2007;17(10):1458–70.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Zhao Q, Zhu Z, Kasahara M, Morishita S, Zhang Z. Segmental duplications in the silkworm genome. BMC Genomics. 2013;14:521.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Eichler EE. Segmental duplications: what's missing, misassigned, and misassembled--and should we care? Genome Res. 2001;11(5):653–6.View ArticlePubMedGoogle Scholar
  32. Bailey JA, Eichler EE. Primate segmental duplications: crucibles of evolution, diversity and disease. Nat Rev Gene. 2006;7(7):552–64.View ArticleGoogle Scholar
  33. Osanai-Futahashi M, Suetsugu Y, Mita K, Fujiwara H. Genome-wide screening and characterization of transposable elements and their distribution analysis in the silkworm, Bombyx mori. Insect Biochem Mol Biol. 2008;38(12):1046–57.View ArticlePubMedGoogle Scholar
  34. Sun W, Shen YH, Han MJ, Cao YF, Zhang Z. An adaptive transposable element insertion in the regulatory region of the EO gene in the domesticated silkworm, Bombyx mori. Mol Biol Evol. 2014;31(12):3302–13.View ArticlePubMedGoogle Scholar
  35. Regier JC, Zwick A, Cummings MP, Kawahara AY, Cho S, Weller S, et al. Toward reconstructing the evolution of advanced moths and butterflies (Lepidoptera: Ditrysia): an initial molecular study. BMC Evol Biol. 2009;9:280.View ArticlePubMedPubMed CentralGoogle Scholar
  36. Xia Q, Guo Y, Zhang Z, Li D, Xuan Z, Li Z, et al. Complete resequencing of 40 genomes reveals domestication events and genes in silkworm (Bombyx). Science. 2009;326(5951):433–6.View ArticlePubMedPubMed CentralGoogle Scholar
  37. de la Paz C-MM, Wheat CW, Vogel H, Soderlind L, Janz N, Nylin S. Mechanisms of macroevolution: polyphagous plasticity in butterfly larvae revealed by RNA-Seq. Mol Ecol. 2013;22(19):4884–95.View ArticleGoogle Scholar
  38. Hughes J, Vogler AP. Gene expression in the gut of keratin-feeding clothes moths (Tineola) and keratin beetles (Trox) revealed by subtracted cDNA libraries. Insect Biochem Mol Biol. 2006;36(7):584–92.View ArticlePubMedGoogle Scholar
  39. Rountree DB, Bollenbacher WE. The release of the prothoracicotropic hormone in the tobacco hornworm, Manduca sexta, is controlled intrinsically by juvenile hormone. J Exp Biol. 1986;120:41–58.PubMedGoogle Scholar
  40. Riddiford L, Hiruma K, Zhou X, Nelson C. Insights into the molecular basis of the hormonal control of molting and metamorphosis from Manduca sexta and Drosophila melanogaster. Insect Biochem Mol Biol. 2003;33(12):1327–38.View ArticlePubMedGoogle Scholar
  41. Luque T, Okano K, O'Reilly DR. Characterization of a novel silkworm (Bombyx mori) phenol UDP-glucosyltransferase. Eur J Biochem. 2002;269(3):819–25.View ArticlePubMedGoogle Scholar
  42. Morrison DK. KSR: a MAPK scaffold of the Ras pathway? J Cell Sci. 2001;114:1609–12.PubMedGoogle Scholar
  43. Yin A, Pan L, Zhang X, Wang L, Yin Y, Jia S, et al. Transcriptomic study of the red palm weevil Rhynchophorus ferrugineus embryogenesis. Insect Sci. 2015;22(1):65–82.View ArticlePubMedGoogle Scholar
  44. Liu GE, Ventura M, Cellamare A, Chen L, Cheng Z, Zhu B, et al. Analysis of recent segmental duplications in the bovine genome. BMC Genomics. 2009;10:571.View ArticlePubMedPubMed CentralGoogle Scholar
  45. Scott JG. Cytochromes P450 and insecticide resistance. Insect Biochem Mol Biol. 1999;29(9):757–77.View ArticlePubMedGoogle Scholar
  46. Bernhardt R. Cytochromes P450 as versatile biocatalysts. J Biotechnol. 2006;124(1):128–45.View ArticlePubMedGoogle Scholar
  47. Iga M, Kataoka H. Recent studies on insect hormone metabolic pathways mediated by cytochrome P450 enzymes. Biol Pharm Bull. 2012;35(6):838–43.View ArticlePubMedGoogle Scholar
  48. Yu L, Tang W, He W, Ma X, Vasseur L, Baxter SW, et al. Characterization and expression of the cytochrome P450 gene family in diamondback moth, Plutella xylostella (L.). Sci Rep. 2015;5:8952.View ArticlePubMedPubMed CentralGoogle Scholar
  49. Kanost M, Gorman M. Phenoloxidases in insect immunity. In: Beckage N.E. (Ed.), Insect Immunol. Oxford: Academic Press; 2008. Google Scholar
  50. Sun W, Shen YH, Yang WJ, Cao YF, Xiang ZH, Zhang Z. Expansion of the silkworm GMC oxidoreductase genes is associated with immunity. Insect Biochem Mol Biol. 2012;42(12):935–45.View ArticlePubMedGoogle Scholar
  51. Zhang Y, Dong Z, Liu S, Yang Q, Zhao P, Xia Q. Identification of novel members reveals the structural and functional divergence of lepidopteran-specific Lipoprotein_11 family. Funct Integr Genomic. 2012;12(4):705–15.View ArticleGoogle Scholar
  52. Munoz-Descalzo S, Terol J, Paricio N. Cabut, a C2H2 zinc finger transcription factor, is required during Drosophila dorsal closure downstream of JNK signaling. Dev Biol. 2005;287(1):168–79.View ArticlePubMedGoogle Scholar
  53. Stranger BE, Forrest MS, Dunning M, Ingle CE, Beazley C, Thorne N, et al. Relative impact of nucleotide and copy number variation on gene expression phenotypes. Science. 2007;315(5813):848–53.View ArticlePubMedPubMed CentralGoogle Scholar
  54. Merla G, Howald C, Henrichsen CN, Lyle R, Wyss C, Zabot MT, et al. Submicroscopic deletion in patients with Williams-Beuren syndrome influences expression levels of the nonhemizygous flanking genes. Am J Hum Genet. 2006;79(2):332–41.View ArticlePubMedPubMed CentralGoogle Scholar
  55. Henrichsen CN, Vinckenbosch N, Zollner S, Chaignat E, Pradervand S, Schutz F, et al. Segmental copy number variation shapes tissue transcriptomes. Nat Genet. 2009;41(4):424–9.View ArticlePubMedGoogle Scholar
  56. Blekhman R, Oshlack A, Gilad Y. Segmental duplications contribute to gene expression differences between humans and chimpanzees. Genetics. 2009;182(2):627–30.View ArticlePubMedPubMed CentralGoogle Scholar
  57. Xiang H, Zhu J, Chen Q, Dai F, Li X, Li M, et al. Single base-resolution methylome of the silkworm reveals a sparse epigenomic map. Nat Biotechnol. 2010;28(5):516–20.View ArticlePubMedGoogle Scholar

Copyright

© The Author(s). 2017