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  • Research article
  • Open Access

Large-scale analysis reveals that the genome features of simple sequence repeats are generally conserved at the family level in insects

BMC Genomics201718:848

https://doi.org/10.1186/s12864-017-4234-0

  • Received: 29 July 2017
  • Accepted: 23 October 2017
  • Published:

Abstract

Background

Simple sequence repeats (SSR), also called microsatellites, have been widely used as genetic markers, and have been extensively studied in some model insects. At present, the genomes of more than 100 insect species are available. However, the features of SSRs in most insect genomes remain largely unknown.

Results

We identified 15.01 million SSRs across 136 insect genomes. The number of identified SSRs was positively associated with genome size in insects, but the frequency and density per megabase of genomes were not. Most insect SSRs (56.2−93.1%) were perfect (no mismatch). Imperfect (at least one mismatch) SSRs (average length 22−73 bp) were longer than perfect SSRs (16−30 bp). The most abundant insect SSRs were the di- and trinucleotide types, which accounted for 27.2% and 22.0% of all SSRs, respectively. On average, 59.1%, 36.8%, and 3.7% of insect SSRs were located in intergenic, intronic, and exonic regions, respectively. The percentages of various types of SSRs were similar among insects from the same family. However, they were dissimilar among insects from different families within orders. We carried out a phylogenetic analysis using the SSR frequencies. Species from the same family were generally clustered together in the evolutionary tree. However, insects from the same order but not in the same family did not cluster together. These results indicated that although SSRs undergo rapid expansions and contractions in different populations of the same species, the general genomic features of insect SSRs remain conserved at the family level.

Conclusion

Millions of insect SSRs were identified and their genome features were analyzed. Most insect SSRs were perfect and were located in intergenic regions. We presented evidence that the variance of insect SSRs accumulated after the differentiation of insect families.

Keywords

  • Insect
  • SSR
  • Genome features
  • Phylogenetic analysis
  • Taxon
  • Molecular marker

Background

Simple sequence repeats (SSR), also known as microsatellites, are tandem repetitions of 1–6 bp motifs that are found in all eukaryotic genomes [1]. SSRs are mainly distributed in noncoding regions, but are also found in coding regions [2]. Some studies have indicated that SSRs are preferentially associated with retrotransposons [3]. Due to replication slippage [4] and unequal crossing-over during meiosis [57], SSRs have undergone rapid expansions and contractions, leading to variation in SSR length among populations of a single species. Because of these characteristics, SSRs have been widely used as molecular markers for fingerprinting, parentage analysis, genetic mapping, and analysis of genome structure [812]. Moreover, numerous studies suggest that SSRs may have biological functions and evolve in a complex process under selective pressure [11, 13, 14]. For example, the expansion of a dinucleotide SSR (AC repeat) in the promoter region of CYP6CY3, a P450 gene, resulted in its overexpression, allowing a tobacco-adapted race of polyphagous aphid (Myzus persicae) to increase its ability to detoxify nicotine [15].

Insects are one of the most diverse animal classes on our planet. Microsatellite markers are highly polymorphic and selectively neutral [16, 17], and thus are powerful genetic tools to investigate the spatial and temporal population dynamics and evolutionary trends of insects. So far, SSR diversity has been extensively surveyed in more than 200 insects to validate their use as molecular markers to infer the demography and relationships of closely related populations or species [10, 18, 19]. A comparative analysis of SSRs occurring within protein-coding regions of 25 insect species suggested that these repeats represent characteristic features of insect genome diversity [13]. Investigation of imperfect microsatellites (at least one mismatch) in five taxonomic orders (Diptera, Hymenoptera, Lepidoptera, Coleoptera, and Hemiptera) revealed their evolutionary paths across genomes [20]. However, the diversity, features, and evolutionary significance of microsatellites in insects are far from being fully understood. Here, we investigated SSRs in 136 insect species, representing 16 taxonomic orders. Millions of insect SSRs were identified from these insects. Cluster and divergence analysis based on the frequencies of various SSRs were also performed.

Results

The number, density and relative abundance of SSRs in 136 insect genomes

We identified a total of 15.01 million SSRs from 136 insect genomes (Additional file 1: Table S1). Typically, SSRs represent only a very small proportion of insect genomes, ranging from 0.02% to 3.1% of the whole genome (Additional file 1: Table S1, Additional file 2: Fig. S1). Interestingly, we found that the body louse (Pediculus humanus) had a much higher percentage (10.53%) of SSRs. Some insects had very few SSRs, such as the cochineal insect Dactylopius coccus (225 SSRs), the small green stink bug Piezodorus guildinii (432 SSRs), and the beetle Priacma serrata (859 SSRs). In contrast, over 500,000 SSRs were identified in some insects, including the body louse Pediculus humanus, the German cockroach Blattella germanica, and the locust Locusta migratoria has the largest animal genome so far [21] and was also shown to have the largest number of SSRs (1.5 million in total). The number of SSRs is positively correlated with genome size (Spearman’s rho = 0.499, P < 0.001), indicating that the abundance of SSRs varies greatly with insect species (Fig. 1).
Fig. 1
Fig. 1

The relationship between SSR number, SSR density, and genome size. The number of identified SSRs was positively associated with genome size

SSR density (total bases of SSR (in bp) per Mb of genome) had a significantly negative relationship with genome size (Spearman’s rho = −0.228, P = 0.007) (Fig. 1). The density was significantly positively correlated with genome GC content, but the correlation was not strong (Spearman’s rho = 0.183, P = 0.033). Interestingly, the SSR frequency in various genomes (i.e., number of SSRs per Mb genome) varied tremendously in insects, ranging from 12 to 4509 (mean 251). The highest frequency (4509) was found in P. humanus, followed by the cactophilic fruitfly, Drosophila mojavensis (1038). SSR frequency was significantly negatively correlated with genome size (Spearman’s rho = −0.191, P = 0.026) and significantly positively correlated with genome GC content (Spearman’s rho = 0.178, P = 0.038), but none of the correlations was strong.

Most identified SSRs (56.2−93.1%) were perfect. The length of imperfect microsatellites (range 22−73 bp, average 34.8 bp) was significantly higher (t = −22.834, df = 175.875, P < 0.001) than that of perfect SSRs (range 16−30 bp, average 20.4 bp) in each species. To evaluate the relationship between SSR length and motif imperfection, we determined the frequency of mismatches in each locus. Imperfect SSRs contained 0.43−3.23% (1.85% on average) motif mismatches, which mainly appeared in the SSRs with a length of approximately 35 bp (Additional file 3: Table S2). Some closely related species had similar percentages of imperfect SSRs while other closely related species had very different numbers of SSRs. For example, the percentages of imperfect SSRs in 23 Drosophila species were very different, ranging from 23% to 44% [13, 20, 22]. In contrast, the imperfect SSR frequencies in two Nasonia species were the same at 21%. Similar phenomena were observed in three Papilio species (15–16%) and in three Batrocera species (22–24%).

Abundance of SSR motif types

When comparing the number of various classes of SSRs within genomes, we found that the percentages of di- and trinucleotide SSRs (27.2% and 22.0% on average, respectively) were significantly higher (P < 0.05, Tukey test) than those observed for mono- (11.6%), tetra- (17.9%), penta- (14.6%), and hexa-nucleotide repeat types (6.7%) (Additional file 4: Table S3, Fig. 2).
Fig. 2
Fig. 2

The relative percentages of six SSR motif types within 136 insect genomes. The percentages of mono-, di-, tri-, tetra-, penta- and hexanucleotide repeats are shown in different colors

Among mononucleotide repeats, the A/T type was predominant, accounting for 10.3% of the repeat motifs. AG/GA/CT/TC and AC/CA/GT/TG were the most frequent dinucleotide SSRs motifs, accounting for 10.2% and 10.0%, respectively. The next most abundant type was the sequences with AT/TA (6.6%). Among trinucleotide repeats, the AAT/ATA/TAA/ATT/TAT/TTA motif was most abundant (6.3%), and each of the other repeat types accounted for less than 3% (Additional file 5: Table S4).

Between the two types of monomer repeats, the A/T type was significantly more abundant (82.4%) than the G/C type (17.6%) (t = 22.962, df = 268, P < 0.001). Analysis of all dinucleotide repeats revealed that the GC/CG type accounted for only 0.9%, significantly lower (P < 0.05, Tukey test) than each of the other three types (AT/TA, AG/GA/CT/TC and AC/CA/GT/TG, each 30.5−36.4%). Among the trinucleotide SSR repeats, those containing two continuous Gs or Cs accounted for only 3.8−4.3%, which was significantly lower (P < 0.05, Tukey test) than other trinucleotide types (6.9−30.0%) (Additional file 6: Table S5). These data indicated that most SSRs in insect genomes consist of AT bases. AT-rich SSR containing motifs, such as AAT/AAAT/AAAAT/AAAAAT or ATA/ATAT/AATAAT/AAAATA, were very common (Fig. 3, Additional file 7: Table S6).
Fig. 3
Fig. 3

SSR abundance across insect genomes. Capital letters followed with number (A01 etc.) stand for different motif sequences as given in Additional file 3: Table S2. Zero means no SSRs of this class were identified

SSR diversity in different insect taxa

We analyzed the relative abundance of various types of SSRs in different insect taxa, and found that the frequencies of some SSR classes were different at the order level. For example, dinucleotide SSRs (the most abundant of the six types as revealed in Additional file 4: Table S3) accounted for 42.6% on average (range 13.2−71.5%) in the genomes of Hymenoptera, which was significantly higher than that observed in Hemiptera (18.2%), Lepidoptera (12.8%), and Coleoptera (9.2%) (P < 0.05, Tukey test) and also higher than that in Diptera (27.5%) (Fig. 2). At the family level, high conservation was observed in terms of the relative abundance of various types of SSRs. This was the most obvious for the families Cupedidae, Buprestidae, and Scarabaeinae that belong to the order Coleoptera. In addition, when viewed at the genus level, SSR frequency was also quite similar among genera within families (Fig. 2). The conservation of SSRs at the family level was also confirmed by analysis of the most abundant motifs. The results indicated that the most abundant motifs were conserved at the family level (Fig. 3).

At the species level, relative abundance of SSRs was very similar within some genera, such as Apis of Apidae, Nasonia of Pteromalidae, Anopheles of Culicidae, and Glossina of Glossinidae. However, interspecies differences in SSR frequency were also observed in some genera, such as Papilio, Drosophila, and Anopheles (Fig. 2). Taken together, the evolution of SSR diversity varied depending on the insect species, suggesting that insect SSRs face dissimilar selection pressures in different taxa.

Distribution of SSRs in different genomic regions

On average, 59.1% (range 49.6−62.0%) of SSRs were distributed in intergenic regions. Within genes, SSRs were mainly found in introns, which accounted for 36.8% (range 27.8−49.9%) of total SSRs, while only 3.7% (range 0.3−9.9%) were in exons (Table 1, Additional file 8: Table S7 and Additional file 9: Table S8). We compared the occurrence of SSRs in different genomic regions between Diptera and Hymenoptera genomes. In Diptera, the exonic SSRs reached 5.5% (range 1.2−9.95%), which was significantly higher than the 2.4% (range 0.3−5.8%) observed in Hymenoptera (t = 5.608, df = 36.312, P < 0.001). By contrast, the percentage of intronic SSRs were significantly lower in Diptera (average 33.2%) when compared to Hymenoptera (average 45.2%) (t = −2.296, df = 32.546, P = 0.028). The SSRs that occurred in mRNA regions were not significantly different (t = −1.758, df = 30.034, P = 0.089), accounting for 38.9% and 47.8% in Diptera and Hymenoptera, respectively.
Table 1

Total number of SSRs in different genome regions

Order

Species

Exon

Intron

Intergenic regions

Spanning exon-intron

Spanning intergenic-genetic

total number

Anoplura

P. humanus

3797

82,101

377,312

340

287

463,837

Coleoptera

D. ponderosae

275

1726

6182

23

10

8216

T. castaneum

734

7623

9493

43

21

17,914

Diptera

A. aegypti

4510

272,342

91,215

537

50

368,654

A. coluzzii

3896

22,894

52,062

127

95

79,074

A. darlingi

27,936

45,779

213,703

2749

586

290,753

A. gambiae

4781

28,746

74,093

108

106

107,834

A. sinensis

3219

5862

23,306

75

30

32,492

A. stephensi

4125

11,654

54,969

112

488

71,348

B. cucurbitae

2388

42,930

40,223

46

161

85,748

B. dorsalis

1903

27,991

29,792

37

77

59,800

C. capitata

3862

113,867

100,518

73

288

218,608

C. quinquefasciatus

10,339

53,060

221,906

1283

396

286,984

D. ananassae

3823

15,074

32,900

73

26

51,896

D. erecta

3810

10,660

23,757

49

27

38,303

D. grimshawi

8444

47,707

95,949

172

70

152,342

D. melanogaster

2201

30,075

15,571

56

95

47,998

D. mojavensis

8222

56,598

124,059

203

69

189,151

D. persimilis

5613

34,289

62,326

172

76

102,476

D. pseudoobscura

6227

32,734

67,334

137

65

106,497

D. sechellia

2527

9763

20,328

63

36

32,717

D. simulans

2253

9234

19,388

57

24

30,956

D. virilis

8114

39,513

88,738

140

60

136,565

D. willistoni

6731

45,312

97,124

142

59

149,368

D. yakuba

3571

13,101

28,165

79

35

44,951

M. destructor

3883

17,407

59,110

519

415

81,334

M. scalaris

268

770

2581

25

7

3651

M. domestica

2298

58,145

64,685

45

227

125,400

Hemiptera

A. pisum

2349

93,793

71,989

164

511

168,806

D. citri

459

78,562

78,172

115

179

157,487

N. lugens

955

9002

25,103

73

35

35,168

R. prolixus

505

24,038

87,771

42

45

112,401

Hymenoptera

A. dorsata

1083

83,173

59,480

119

334

144,189

A. florea

1484

81,374

60,290

123

368

143,639

A. mellifera

4455

82,325

133,229

724

397

221,130

A. rosae

973

54,968

41,550

60

240

97,791

B. impatiens

890

27,439

14,460

43

260

43,092

B. terrestris

892

25,178

13,437

27

267

39,801

C. floridanus

3493

22,024

92,188

682

227

118,614

C. biroi

1446

30,066

14,794

57

179

46,542

C. solmsi marchali

1579

115,235

126,743

424

985

244,966

F. arisanus

744

8932

4937

32

54

14,699

H. saltator

12,331

79,960

388,788

2777

818

484,674

L. humile

1635

6724

41,722

67

61

50,209

M. rotundata

1018

13,356

7637

35

84

22,130

M. demolitor

2343

60,307

44,657

186

553

108,046

N. vitripennis

1897

39,230

70,786

175

24

112,112

P. barbatus

1860

13,131

78,291

119

97

93,498

V. emeryi

1787

33,971

22,043

59

304

58,164

W. auropunctata

1724

51,892

36,798

64

345

90,823

A. echinatior

4443

35,426

115,736

790

203

156,598

Isoptera

Z. nevadensis

879

16,054

48,801

61

27

65,822

Lepidoptera

B. mori

501

12,750

76,795

41

21

90,108

C. suppressalis

861

5346

8584

157

6

14,954

D. plexippus

553

11,184

24,726

40

18

36,521

H. melpomene

571

13,315

23,606

45

45

37,582

M. sexta

864

17,324

24,138

40

67

42,433

P. xylostella

9700

74,901

144,119

1862

291

230,873

Evolution analysis of insect SSR

Clustering analysis showed that the frequencies of various SSRs were largely similar within different insect orders (Fig. 4). A symmetrized Kullback-Leibler divergence analysis, based on the percentage of dinucleotide combinations, could almost perfectly separate Hymenoptera and Diptera from other insects (Additional file 10: Fig. S2). For Diptera, 54 species (80.6% of the total) clustered into two branches: 1) Diptera-I, which contained only flies of most families; and 2) Diptera-II, which was comprised solely of mosquitoes. Most Dipteran families can be readily separated from others, except for several Drosophilidae species (Additional file 11: Fig. S3). All hymenopteran species, except for Cotesia vestalis and Microplitisde molitor, clustered together (Additional file 10: Fig. S2). Similar results were obtained when the analysis was carried out using the tri-, tetra-, and penta-nucleotide motif information (Additional file 12: Fig. S4, Additional file 13: Fig. S5, Additional file 14: Fig. S6). In general, most insects were clearly divided using SSR frequencies at the family level, but not at the order level.
Fig. 4
Fig. 4

Phylogenetic analysis of insect SSRs. Symmetrized Kullback-Leibler divergence analysis was used and the evolutionary tree was constructed using the UPGMA method with MEGA6 software, and viewed with ITOL software

Discussion

Here, we identified millions of SSRs in 136 insect genomes and analyzed their features. The abundance and densities of insect SSRs were correlated with genome sizes. However, no strong correlation was found between the SSR density and GC content, nor was there a strong correlation between SSR frequency and genome size. This pattern was also observed in Tombusviridae [23], potexvirus [24] and carlaviruses [25]. In contrast, SSR frequency was shown to be inversely related to genome sizes in plants [26], Bovid species [27], fungi [28], and maize [29]. Both SSR frequency and density were negatively correlated with GC-content in these species.

SSRs only account for a very small proportion of insect genomes, and they generally do not have clear functions. Therefore, SSRs are believed to face relatively low selection pressures and accumulate mutations faster than coding genes [11]. SSRs have been widely used as genetic markers to distinguish individual insects from geographically distinct populations [30, 31]. Phylogenetic analysis of 136 insect SSRs indicated that the evolutionary tree constructed with SSR genome features was largely inconsistent with species trees, especially at the family level. This suggested that too many mutations have accumulated in insect SSRs since the division of the insect families. However, we found that insect species belonging to the same family tended to cluster together in the evolutionary tree, suggesting that selection pressures of SSRs were maintained at the family level. Thus, insect SSRs are good molecular markers to distinguish closely related insect species.

We found that perfect SSRs were significantly more abundant than imperfect SSRs in insects. Overall, perfect SSRs accounted for 56−93% of the identified microsatellites, whereas imperfect SSRs made up only 7−44%. This is consistent with similar results in plants, such as the Triticeae species [32], and previous reports in insects [13, 20]. The frequency of forming mismatch motifs varied with the length of the motif. For mono-, penta-, and hexanucleiotide SSRs, <19% were imperfect. In contrast, in di- and trinucleotide SSRs, ~31% of motifs were imperfect. This pattern was conserved in almost all tested insects, suggesting that this is a conserved feature in insect microsatellites [20]. A large fraction of the trinucleotide SSRs were derived from codon repeats, and the occurrence of these trinucleotide mismatches contributed to codon bias in the insect genomes [13, 20].

In insects, nearly three fifths of SSRs were found in intergenic regions, consistent with previous reports. Only 3.7% (0.3−9.9%) of SSRs occurred in exonic regions, which can be attributed to negative selection against frameshift mutations in coding regions [33]. In contrast, intronic SSRs accounted for 36.8%, which is 10-fold higher than exonic SSRs. It has been reported that intronic SSRs may affect gene expression [34], suggesting that the functions of intronic SSR will require more exploration.

Conclusions

In this study, we carried out a comprehensive analysis of SSRs in 136 insects. This is the first large-scale analysis of insect SSRs, and included more than 100 insect species. The results confirmed some previous conclusions about insect SSRs. The numbers of insect SSRs were positively associated with the genome sizes whereas the frequency and density were not. Both phylogenetic analysis and most abundant motif analysis showed that the insect SSRs were generally evolutionary conserved at the family level but not at the order level.

Methods

Genome sequences

At present, the genomes of 136 insect species are publically available, including 67 Diptera species, 27 Hymenoptera species, 12 Hemiptera species, 11 Lepidoptera species, eight Coleoptera species, and one species each of Diplura, Ephemeroptera, Odonata, Strepsiptera, Trichoptera, Thysanoptera, Anoplura, Phasmatodea, Orthoptera, Isoptera, and Blattodea (Additional file 1: Table S1). The genome sequences of all insects were downloaded from InsectBase 1.0 [35]. Ambiguous nucleotides were removed from the genomes prior to analysis.

Identification of insect SSRs

SSRs were identified using the SciRoKo 3.4 using default parameters [36]. According to the motifs, the repeat sequences were divided into six classes: mono-, di-, tri-, tetra-, penta-, and hexa-nucleotide SSRs [20]. For each class, only sequences with a length of ≥15 nucleotides were considered as SSRs. Briefly, SSRs with no mismatch in the motif were defined as perfect SSRs, while SSRs with at least one mismatch in the motif were defined as imperfect SSRs. The criteria used for defining imperfect SSRs was as following: ≥ 30 bp SSRs with 1–3 mismatches and ≤30 bp SSRs with ≥3 mismatches.

Analysis of SSRs

We calculated the frequency and density of SSRs in each of the available insect genomes. The frequency was determined as the percentage of the total number of SSRs per megabase (Mb) of genome sequence. The relative density was determined as the length (in bp) of SSRs sequences in the total Mb of genomic sequence analyzed. The relative abundances of perfect and imperfect repeat classes were calculated within each class of SSR, and their size distribution range and mean lengths were calculated. Associations between SSR number, frequency, and density with the genome sizes and GC contents were tested using Spearman rank correlation to determine whether there was significant correlation between the two variables (IBM SPSS Statistics, 2011).

Microsatellite distribution in insect genomes

Among the 136 insect species, 58 genomes were annotated with protein-coding genes accompanied by gff3 annotation files containing the positional information on exons and introns. The distribution of SSRs in these different regions was determined by mapping the SSRs to the genome using a Perl script.

Evolutionary analysis of insect SSRs

We constructed phylogenetic trees using insect SSRs with symmetrized Kullback-Leibler divergence analysis [37, 38]. The differences between two species were measured quantitatively with the percentages of SSRs ([p(x) and q(x)] in two species respectively, where x represents the class of SSR (di-, tri-, tetra-, penta-, and hexa-nucleotide repeat types). All pairwise comparisons among the 136 insect species were performed. Cluster analysis was performed using the UPGMA method [39] with the MEGA6 software package. Phylogenetic trees were visualized with ITOL software (http://itol.embl.de/) [40].

Abbreviations

Bp: 

base pair

di-: 

dinucleotide

gff3: 

generic Feature Format3

hexa-: 

hexanucleotide

mb: 

megabase

mono-: 

mononucleotide

penta-: 

pentanucleotide

SSR: 

simple sequence repeats

tetra-: 

tetranucleotide

tri-: 

trinucleotide

Declarations

Acknowledgements

We thank Chuanlin Yin, Kun Lang, Dianhao Guo, and Ruizheng Tian for helpful discussions.

Funding

F.L. was funded by the National Key Research and Development Program [2017YFC1200602, 2016YFC1200600, 2017YFD0200900], National Science Foundation of China [31,772,238, 31,672,033].

Availability of data and materials

The gene data used in this study can be retrieved from the InsectBase (http://genome.zju.edu.cn/) [35]. The data of phylogenetic trees are deposited in the TreeBASE (Accession Number: 21,658).

Authors’ contributions

F.L. and M.J. designed the project; S.D. carried out SSR identification and analysis; S.W. distinguished fruit fries; K.H. did the PCR validation experiment; S.D. made the figures; S.D. drafted the manuscript; M.J. and S. D. analyzed the data; F.L., M.J. and S.W. wrote the paper. All authors read and approved the 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.

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Authors’ Affiliations

(1)
Ministry of Agriculture Key Lab of Molecular Biology of Crop Pathogens and Insects, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
(2)
Technical Centre for Animal Plant and Food Inspection and Quarantine, Shanghai Entry-exit Inspection and Quarantine Bureau, Shanghai, 200135, China

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