Bradysia odoriphaga (Diptera: Sciaridae) is the most important pest of Chinese chive (Allium tuberosum) in Asia; however, the molecular genetics are poorly understood. To explore the molecular biological mechanism of development, Illumina sequencing and de novo assembly were performed in the third-instar, fourth-instar, and pupal B. odoriphaga. The study resulted in 16.2 Gb of clean data and 47,578 unigenes (≥125bp) contained in 7,632,430contigs, 46.21% of which were annotated from non-redundant protein (NR), Gene Ontology (GO), Clusters of Orthologous Groups (COG), Eukaryotic Orthologous Groups (KOG), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. It was found that 19.67% of unigenes matched the homologous species mainly, including Aedes aegypti, Culex quinquefasciatus, Ceratitis capitata, and Anopheles gambiae. According to differentially expressed gene (DEG) analysis, 143, 490, and 309 DEGs were annotated as involved in the developmental process in the GO database respectively, in the comparisons of third-instar and fourth-instar larvae, third-instar larvae and pupae, and fourth-instar larvae and pupae. Twenty-five genes were closely related to these processes, including developmental process, reproduction process, and reproductive organs development and programmed cell death (PCD). The information of unigenes assembled in B. odoriphaga through transcriptome and DEG analyses could provide a detailed genetic basis and regulated information for elaborating the developmental mechanism from the larval, pre-pupal to pupal stages of B. odoriphaga.
Citation: Gao H, Zhai Y, Wang W, Chen H, Zhou X, Zhuang Q, et al. (2016) Transcriptome Analysis and Discovery of Genes Relevant to Development in Bradysia odoriphaga at Three Developmental Stages. PLoS ONE 11(2): e0146812. https://doi.org/10.1371/journal.pone.0146812
Editor: Youjun Zhang, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, CHINA
Received: July 15, 2015; Accepted: December 21, 2015; Published: February 18, 2016
Copyright: © 2016 Gao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: ***PA: Please note that the R2R states, "The raw data has been uploaded to NCBI-SRA database (Accession number: SRP066929)."*** All the raw data files are available from the NCBI-SRA database (Accession number: SRP066929).
Funding: Funding for this study was provided by grants from the Special Fund for Agro-scientific Research in the Public Interest from the Ministry of Agriculture of China (201303027). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
The family Sciaridae (Diptera: Sciaroidea) is composed of approximately 347 species in 32 genera in China . Some species of this group are important vegetables pests. For example, Bradysia odoriphaga—(Diptera: Sciaridae) is the most important pest of Chinese chive (Allium tuberosum Rottler ex Sprengel) , which is grown over a vast geographic area from Asia through the Middle East and to Europe and North America [3,4]. During the entire developmental phase, the third-instar B. odoriphaga damages chives the most. Tissue rot and 30–80% yield losses can result from larvae feeding on root, bulbs, and even immature stem of chives, whereas adults cause minimal direct plant damage . Mature larvae decrease their feeding amount and prepare to overwinter in the soil or in the residue of chives as pupae, which can protect against drought, enemies, and pesticides during their pupal stages. In addition to Chinese chive, this insect also has a wide distribution of hosts, including welsh onion, garlic, onion, lettuce, cucumber, Chinese cabbage, and mushroom[6–9]. In order to decrease the damage of B. odoriphaga, until now, chemical control has been the most effective method for the control of them . However, the sustained dependence on insecticides has led to pesticide residue, soil pollution, and insecticide resistance. The integrated management of B. odoriphaga now has become an urgent problem.
Although ecological and physiological aspects of B. odoriphaga have been studied in recent years, molecular biological research about B. odoriphaga is still very limited. Fortunately, in recent years, next-generation high-throughput transcriptome sequencing techniques have improved dramatically the efficiency and speed of gene discovery in the life sciences [11,12], especially for organisms without a reference genome. Many studies using this technology have surveyed the complex transcriptomes of various insects, including Drosophila melanogaster , Bombyx mori , Anopheles gambiae and A. aegypti , Maruca vitrata , and Spodoptera exigua . Moreover, transcriptome sequencing is also an efficient way to measure transcriptome composition, uncover the information of functional genes, and differentially express genes for the insects with different kinds, during different developmental stages, and in different developmental conditions [18–20].
The characterization of larval transcriptomes was studied by de novo sequencing, and, in B. odoriphaga , researchers found 408 unigenes related to insecticide resistance and metabolism in 16,829 assembled unigenes. However, the molecular regulatory mechanisms of B. odoriphaga remained unexplored, especially those related to developmental transition. Therefore, to understand the mechanism of the developmental process, it is essential to develop DEGs from B. odoriphaga at different developmental stages. In this study, the third-instar larvae, fourth-instar larvae, and pupal insects were selected as the research objects due to the close association between their damage to plants and their development. As the homologous species of B. odoriphaga, the genomic publication of Diptera insects, including A. aegypti  and C. quinquefasciatus , also could provide some reference information for gene discovery of B. odoriphaga. In this study, the annotated transcriptome sequences and gene expression profiles could provide useful information for the identification of genes involved in regulating the developmental process of B. odoriphaga at the third-instar, fourth-instar and pupal stages. The assembled and annotated unigenes in the transcriptome will help us to better explore the key regulated genes related to development and provide the molecular basis for the developmental process and functional analysis of these key genes.
Materials and Methods
Bradysia odoriphaga were collected from bulbs of Chinese chives in Jinan (117°00’E, 36°40’N), Shandong Province, China during April 2014. They were reared on bulbs of Chinese chives for 4–5 consecutive generations at 25± 0.3°C, 60% relative humidity, and 24: 0 L: D in a climatecontrolled chamber. Coming from the same generation, individuals of B. odoriphaga in three developmental stages (third -instar, fourth-instar, pupa) were collected successively and stored at -80°C. Due to two replicates in each development stage, six samples in total were used for transcriptomic analysis. The species are common agricultural pests and not included in the ‘‘List of Protected Animals in China”. No specific permissions were required as these fields are experimental plots that belong to the Shandong Academy of Agricultural Sciences, Jinan, Shandong in China.
Rna Isolation and Quality Controls
Total RNA was extracted from 30 mg insects in each sample using TRI Reagent (Sigma Life Science, USA) according to the manufacturer’s protocol. The quality and quantity and integrity of each RNA sample was assessed using a Nanodrop spectrophotometer (Thermo Scientific, USA), Qubit 2.0 (Life Tech, USA), Aglient 2100 (Life Tech, USA). Only the RNA samples with 260: 230 ratio from 2.0 to 2.5, 260: 280 ratio from 1.9 to 2.1and an RNA integrity number (RIN) more than 8.0, were used for the analysis.
Illumina Sequencing and De Novo Assembly
According to the Illumina manufacturer’s instructions, mRNA of each sample was gathered using oligo (dT) magnetic beads and fragmented into short sequences in the presence of fragmentation buffer. The cleaved mRNA was transcribed with random hexamers, and then second-strand cDNA synthesis was performed by adding dNTPs, RNase H and DNA polymerase I. After the purification of cDNA using AMPure XP (Beckman Coulter, USA) beads, endrepair and ligation of adaptors, the products were selected by AMPure XP beads and amplified by polymerase chain reaction (PCR) to create a cDNA library.
The cDNA library was sequenced on an Illumina sequencing platform (Hiseq 2500) (Illumina, USA). The raw reads from the images were generated using Solexa GA pipeline 1.6 sequencing by synthesis. After removal of low-quality reads containing primer/adaptor sequences and trimming of read lengths using SeqClean, high-quality reads considered as clean data with an identity value of 95% and a coverage length of 125 bp were assembled de novo using Trinity (http://trinityrnaseq.sourceforge.net/) software and clustered using the De Bruijn graph algorithm . Ten the unigene sequence was then generated after unbinding the De Bruijn graph. According to the alignment with the sequences in the unigene library, the mapped reads in the clean data of each sample were applied for quality evaluation of the transcriptome sequencing library, such as randomness of mRNA fragmentation and saturation tests of sequencing data.
Similarity Search and Functional Annotation
Unigene annotation of B. odoriphaga in three developmental stages was performed by searching the GenBank database with the BLASTX algorithm (http://www.ncbi.nlm.nih.gov/). NR (ftp://ftp.ncbi.nih.gov/blast/db/), GO (http://www.geneontology.org/), COG (http://www.ncbi.nlm.nih.gov/COG/), KOG (http://www.ncbi.nlm.nih.gov/COG/) and KEGG (http://www.genome.jp/kegg/) annotations of the unigenes were determined using BLAST software.
Differentially expressed genes among B. Odoriphaga at three developmental stages
Reads sequenced from each sample of B. odoriphaga at different developmental stages were aligned with the unigene library by Bowtie (http://bowtie-bio.sourceforge.net/index.shtml). To obtain relative expression levels in each sample, fragments per kilobase of transcript per killion mapped reads (FPKM) in each sample were counted and combined with RSEM . To ensure the reliability of differential expression of genes, the Pearson’s Correlation Coefficient (r) was deeded as evaluation indicator of correlation of two biological replicates . The differential gene expression analysis was then performed using DESeq (http://www.bioconductor.org/packages/release/bioc/html/DESeq.html) for three compared groups (e.g., third vs fourth: the comparison of third-instar and fourth-instar B. odoriphaga; third vs pupa: the comparison of third-instar and pupal insects; and fourth vs pupa: the comparison of fourth-instar and pupal insects). The significance of differential gene expression was assessed using the Benjamini-Hochberg. A gene was considered to be differentially expressed when results from the above tests were all significant at a level of False Discovery Rate (FDR) <0.01 and a ratio of FPKM value of two compared goups (FC) ≥2. The GO, COG, KOG and KEGG annotations were performed using BLAST software for the differential expression of genes.
Reverse transcription (RT-PCR) and Quantitative real-time PCR (qRT-PCR) validation
Total RNA was extracted from B. odoriphaga at three developmental stages as described above. Approximately 2μg of total RNA per sample were reverse-transcribed using a reverse transcription system (Promega, China). Forty-five genes were selected randomly in the common differential expression of genes among three comparisons of third-instar and fourth-instar larvae, third-instar larvae and pupa, and fourth-instar larvae and pupa for quantitative qRT-PCR validation. The RT-PCR and qRT-PCR were performed with the PrimeScript RT-PCR Kit and the SYBR Premix Ex Taq Kit (TaKaRa, China), repectively, according to the manufacturer’s protocol. The primers for RT-PCR was S1 Table. β-actin and β-tubulin were reference genes. Gene-specific primers, shown in S2 Table, were used for detecting the relative quantification of each gene. qRT-PCR expression levels were compared based on the means of three independent experimental repeats. Internal control genes (β-actin and β-tubulin) and a no template control (NTC) sample (nuclease free water) were included for normalization. A relative quantitative method (△△Ct) was used to calculate relative expression level.
Activity assay of enzymes
100mg B. odoriphaga collected at three developmental stages, respectively, was used to assay the activity of enzymes. There biological replicates were designed for this study. According to the NR annotation of 45 genes selected randomly in the common differential expression of genes among three comparisons, ten DEGs that could be expressed as eight functional enzymes were selected to validate the gene expression profiles. Pectate lyase (PEL) activity and glucose dehydrogenase (GLD) activity were assayed as described by Kovtunovych et al.  and Fender et al. , respectively. The activity of glutathione s-transferase (GST) was detected according to Glutathione S-Transferase Fluorescent Activity Kit (Enzo life science, USA). The assay of Carboxylesterase (CarE) activity referenced the methods of Zou et al. . Alpha-Amylase Assay Kit (Abnova, USA), Lipase Activity Assay Kit III (Sigma, USA), Nitric Oxide Synthase Assay Kit (Antibodies-online, Germany), Fatty Acid Synthase assay Kit (Solarbio, China) were used to assayed the activity of alpha-amylase (AA), lipase (Lip), nitric oxide synthase (NOS) and fatty acid synthase (FAS).
Illumina sequencing and de novo assembly
Illumina sequencing and de novo assembly were performed through merging all the sample of B. odoriphaga at three developmental stages (third-instar and fourth instar larval and pupal stages), resulting in the generation of 47,578 unigenes in total and a total length of 40,913,658 bp, with an N50 length of 1,517 bp and mean length of 859.93 bp. The corresponding information of contigs and transcripts is also shown in Table 1. The size distribution indicated that the lengths of the 12,772 unigenes were more than 1000 bp (S1 Fig). A total of 7,632,430 contigs were assembled and generated into 64,548,073 clean reads from all the libraries (Tables 1 and 2). The pupae library produced the most data (11,411,520 clean reads), while the fourth-instar larvae library produced the fewest clean reads (10,434,294).As a whole, all libraries exhibited good quality, with an average of 86.95% of clean reads with base call quality at Q30 and 92.12% at Q20. According to the alignments with the sequences in the unigene library, the statistics of mapped reads in each sample are shown in Table 2. The quality evaluation of the transcriptome sequencing library was then carried out according to the randomness of mRNA fragmentation and saturation test of sequencing data. The results revealed that the mapped reads of each sample were distributed in mRNA equally and the randomness of mRNA fragmentation was good (S2 Fig). The sufficient and effective information was applied in this study due to the saturation of gene number with the increase of sequenced reads (S3 Fig). Therefore, the eligible transcriptome sequencing library could ensure the reliability of transcriptome sequencing results.
Functional annotation of all unigenes
To classify the functions of the predicted unigenes of three developmental stages, among 47,578 unigenes of B. odoriphaga, 21,985 of them were annotated from NR (21,095), GO (10,023), COG (7,856), KOG (14,712) and KEGG (6,820) database using a cut-off E-value of 10−5. For the NR annotation, 44.33% of all unigenes (47,578) provided a BLAST result, and the best-match results of NR homologous species distribution are shown in Fig 1. The sequences of B. odoriphaga showed 3,687 matches with A aegypti sequences followed by C quinquefasciatus (2,139), C capitata (1,952), and A gambiae (1,583). In each of the three main categories (cellular component, molecular function and biological process) of the GO classification, the terms “cell part”, “binding”, and “cellular process” were the most dominant, respectively (Fig 2). There are 2,794 genes related to the developmental process in the biological process category. In the KOG and COG functional classifications, “translation, ribosomal structure, and biologenesis” was the dominant function except for the general function predication only (S4 and S5 Figs). Five main categories (Metabolism, Cellular processes, Genetic information processing, Organism systems, Environmental information processing) in KEGG annotation are shown in Fig 3. Almost half of all unigenes (47.19%) were annotated as pathways related to the category “Genetic information processing”.
The number means the matched unigenes with the corresponding homologous species for all unigenes of Bradysia odoriphaga at three developmental stages.
Unigenes were classified into different functional groups based on the Gene Ontology (GO) data library within cellular component, molecular function and biological process categories.
Differentially expressed genes
According to the gene expression level (FPKM), the reliability of DEGs was analyzed by evaluating the correlation of two biological replicates in each developmental stage (S6 Fig). It was revealed that the gene expression tendency of two biological replicates was similar because the majority of points were clustered around the diagonal line.
Based on the DEG analysis, among 3,822 genes expressed differentially between third and fourth-instar larvae, 643 and 3,197 genes were up-regulated and down-regulated, respectively. A total of 4,369 genes with significantly different expression levels was revealed between fourth-instar larvae and pupae. Among them, 1,462 and 2,907 genes were up-regulated and down-regulated, respectively, in the comparison of pupal stage and fourth-instar larvae. However, 8,022 genes expressed differentially were analyzed between third-instar and pupal B. odoriphaga; differential expression was most significant due to a longer interval of developmental stages (Fig 4A). In all the DEGs, with an increasing developmental stage, the number of down-regulated genes was more than that of up-regulated genes (Fig 4B). Moreover, the results revealed 485 DEGs all expressed differentially in three comparisons of third-instar and forth instar larvae, third-instar larvae and pupae, and fourth-instar larvae and pupae, some of which were selected and used for validation via qRT-PCR.
(A) Comparison of differentially expressed unigenes in each comparison. (B) Regulated characteristics of differentially expressed unigenes in each comparison. Three comparisons of third-instar and fourth-instar B. odoriphaga (3rd vs 4th), third-instar and pupal insects (3rd vs Pupa), and fourth-instar and pupal insects (4th vs Pupa) are shown.
Expression variation of DEGs related to the developmental process among three different developmental stages
To discover the genes related to the developmental process of B. odoriphaga, the functions of DEGs were annotated from GO, COG, KOG, and KEGG databases according to the annotated information of all unigenes of B. odoriphaga.
In the comparison of third-instar and fourth-instar larvae, 3,250 DEGs were annotated in the GO database (Fig 5). Among 143 genes related to the developmental process, three genes were selected according to the standard (log2FC≥2) (S3 Table). Genes GL1336 and HIV-1 rev binding protein 2 in Homo sapiens were down-regulated in fourth-instar larvae compared to those of the third-instar stage. They were annotated as involved in the developmental process in the GO database (Tables 3 and 4), and the gene GL1336 was involved in transcription according to the KOG and COG annotations (S4 Table). Expression of the gene caspase Nc-like was up-regulated in fourth-instar larvae compared to that in the third- instar stage. It positively regulated cell division and chromosome partitioning of the apoptotic process, tissue development, eye development and nervours system development (Tables 3 and 4, and S4 Table).
The results of genes related to the developmental process are shown. 3rd vs 4th: the comparison of third-instar and fourth-instar Bradysia odoriphaga; 3rd vs Pupa: the comparison of third-instar and pupal insects; 4th vs Pupa: the comparison of fourth-instar and pupal insects.
The comparison between fourth-instar and pupal B. odoriphaga revealed 309 DEGs related to the developmental process (Fig 5). Among them, 11 genes were selected according to the standard (log2 FC≥2) (S3 Table) and all were up-regulated in the pupal stage compared to the fourth-instar larvae. They were participated in the “developmental process involved in reproduction”, “developmental process”, “developmental pigmentation”, “developmental programmed cell death” and reproductive organs development such as oogenesis, gamete and embry (Tables 3 and 4). In the KOG annotation, a gene encoding a tyrosine-protein kinase receptor regulated signal transduction mechanism through mitogen-activated protein kinase (MAPK) signaling pathway (S4 Table). Gene GG21746 positively regulated the process of imaginal disc-derived wing morphogenesis. Moreover, ecdysone-induced protein 63E not only regulated instar larval development but also was involved in embryonic development in the pupal stage (Tables 3 and 4).
In the comparison of third-instar and pupal insects, although 19 genes were selected among 490 DEGs (Fig 5) related to the developmental process according to the standard (log2 FC≥2) (S3 Table), the majority of them showed similarly regulated profile and function. Similar to the comparison of fourth-instar and pupal stages, 11 genes positively regulated the developmental processes of reproduction, PCD, and reproductive organs in the pupal stage compared to those of the third-instar larvae. With the exception of those, the expression levels of genes dynamin and GK10804 related to the proceses of the open tracheal system, heart, and stem cell development weres lower in the pupal stage of B. odoriphaga.
Moreover, among 45 genes selected of the 485 common DEGs among three comparisons of third-instar and fourth-instar larvae, third-instar larvae and pupae, and fourth-instar larvae and pupae, five DEGs was related to the developmental process, such as chitin-based cuticle development (probable H/ACA ribonucleoprotein complex subunit 1-like), tube development (P450), regulation of organ growth (NOS), mitotic spindle elongation (acidic endochitinase SP2-like) and mesoderm development (glucose dehydrogenase) (Table 3). According to the functional annotation, it was found that, nitric oxide synthase (NOS) regulated the organ growth and energy production and conversion negatively through regulating the “arginine and proline metabolism” pathway.
Reverse transcription (RT-PCR) and Quantitative real-time PCR validation
Forty-five genes selected among 485common DEGs in three comparisons of third-instar and fourth-instar larvae, third-instar larvae and pupae, and fourth-instar larvae and pupae were classified into four gene expression profiles, such as, those up-regulated in fourth-instar and pupal stages compared to third-instar stage (I); down-regulated in fourth-instar and pupal stages compared with third-instar stage (II); down-regulated in fourth-instar and up-regulated in pupal stages compared to third-instar stage (III); up-regulated in fourth-instar and down-regulated in pupal stage compared to third-instar stage (IV). There were two, five, three, and 35 genes in the four gene expression profiles respectively (S5 Table and Fig 6).
Three comparisons of third-instar and fourth-instar Bradysia odoriphaga (3rd vs 4th), third-instar and pupal insects (3rd vs Pupa), and fourth-instar and pupal insects (4th vs Pupa) are shown.
To further validate the gene expression profiles, RT-PCR and qRT-PCR were carried out for the 45 DEGs among the three compared groups. The number of genes in each gene expression profiles through qRT-PCR (Fig 7) were almost invariant compared with the electronic data of gene expression analysis (S7 Fig). The expression profiles of genes analyzed by two methods, such as qRT-PCR and RT-PCR (S8 Fig), were consistent completely. It was revealed that the gene expression profiles were similar under the condition of two reference genes (A: β-actin; B: β-tubulin). The majority of genes were up-regulated in fourth-instar and down-regulated in pupal stage compared to those of the third-instar stage. For example, these included metabolism-related genes (lipase, delta-5 desaturase, acidic endochitinase, pectate lyase, lysosomal alpha-mannosidase, regucalcin, etc.), defense response related genes (cytochrome P450, glutathione S-transferase, carboxylesterase, defensin, etc.) (S5 Table). qRT-PCR results showed that, two type I genes, three type III genes (Fig 7A-1 and 7B-1) and 28 type IV genes (Fig 7A-4 and 7B-4) were confirmed from the results of the DEG analysis. Only gene c30388 of type II (Fig 7A-2 and 7B-2) and seven genes in type IV (Fig 7A-3 and 7B-3) were not confirmed from the results of the DEG analysis. Therefore, statistically, 82.22% of genes in the qRT-PCR results were in accordance with the electronic data of gene expression analysis.
(A) β-actin was a reference gene. (B) β-tubulin was a reference gene. (1) The genes c24076 and c31255 belong to regulated type I, while c10499, c11110, and c28873 belong to type III. (2) qRT-PCR analysis of type II gene expression; (3) qRT-PCR analysis of inconsistent type IV gene expression. (4) qRT-PCR analysis of type IV gene expression. qRT-PCR data calculated with the 2-△△Ct method. The value of relative expression level on the y-axis calculated according to log(2-△△Ct). The expression level of each gene in third-instar insects was arbitrarily set as 1, the value of the y-axis was 0, and its corresponding transcript levels in fourth-instar (3rd vs 4th) and pupal stages (3rd vs Pupa) were calibrated against the third one. *, p < 0.05, as determined by one-way analysis of variance (ANOVA).
For the five DEGs related to the development process, their qRT-PCR results were identical to those obtained by DEG expression profiling. Genes probable H/ACA ribonucleoprotein complex subunit 1-like (c11110) related to chitin-based cuticle development and P450 (c28873) related to tube development were down-regulated in fourth-instar-stage and up-regulated in pupal stage compared to third- instar insects (Fig 7A-1 and 7B-1). Similar to the digital analysis results, NOS (c29314) related to organ growth, was negatively regulated in fourth-instar and pupal-stage compared to the third- instar B. odoriphaga (Fig 7-2).
Activity assay of enzymes
At the basis of RT-PCR and qRT-PCR validation, activity assay of enzymes was carried out to validate gene expression profiles in protein expression level. The compared results between gene expression profiles and relative activity of enzymes were showed in Fig 8. Except for glutathione S-transferase 1-like and pectate lyase, the gene expression profiles of the other eight genes (80%) were all consistent with the relative activity of relative activity of enzymes (Fig 8A and 8B).
To discover and annotate the gene involved in important physiological and biochemical process, de novo assembly and the analysis of differential expression genes had provided an effective way for the species without reference genome or sequence . Therefore, under the condition of no reference genome of B. odoriphaga, 47,578 unigenes (≥125bp) were generated from the third-instar, fourth-instar, and pupal B. odoriphaga through Illumina sequencing and combined de novo assembly. The results were similar to those from the study by Chen et al. , in which 16,829 unigenes were assembled by de novo sequencing in the single larval transcriptome of B. odoriphaga, namely about one-third of the unigene numbers in the three developmental stages. However, the number of unigenes (21,095) annotated in the NR protein database in all the three developmental stages was not more than twice the unigenes (12,024) in the single larval transcriptome. The same conclusion was also found in the GO annotation (10,023 and 7,903); this was because many unigenes in the third-instar, fourth-instar, and pupal B. odoriphaga had the same function. Moreover, we found that 9,361 unigenes of B. odoriphaga matched homologous genes in Diptera insects, such as A. aegypti sequences followed by C. quinquefasciatus, C. capitata and A. gambiae (Fig 1). Now, genomic research involves many insects, for instance, Hymenoptera , Lepidoptera [33,34] and Coleoptera insects . Regarding Diptera, 15,419 coding genes were analyzed in the genome of A. aegypti . 18,883 genes were discovered in genome of C. quinquefasciatus . The unigenes of B. odoriphaga from transcriptome sequencing could provide abundant genetic information at the genomic level for B. odoriphaga and other Diptera insects.
Through qRT-PCR analysis for 45 genes selected from 485 genes expressed differently among third-instar, fourth-instar, and pupal B. odoriphaga, it was found that the majority of genes were up-regulated in fourth-instar and down-regulated in pupal stages compared to the third-instar stage (S5 Table). Example of these include ecdysteroid regulated-like protein, metabolism-related genes (lipase, delta-5 desaturase, acidic endochitinase, pectate lyase, lysosomal alpha-mannosidase, regucalcin, etc.), and defense response related genes (glutathione S-transferase, carboxylesterase, defensin, etc.). These conclusions were related to physiological characteristics at each stage of the B. odoriphaga life cycle. During the life history of B. odoriphaga, the metabolic activity of insects reaches to the highest point in the last larval stage, which is convenient for finishing every physiological function of larvae . After ecdysis in the fourth-instar stage, B. odoriphaga enters the pupal stage, in which insects began to store fat and energy for overwintering through reductions in metabolic activities [37,38]. With the exception of the 45 genes expressed differently among third-instar, fourth-instar, and pupal B. odoriphaga, the DEGs related to the developmental process were selected also from the comparisons of third-instar and fourth-instar larvae, third-instar larvae and pupae, and fourth-instar larvae and pupae. Twenty closely related DEGs of development were selected according to the standard (log2 FC≥2) (Table 3 and S3 Table). Many researchers also have discovered genes related to the developmental process through transcriptome sequencing [39–44]. In the horned beetle Onthophagus taurus, 8% of variable genes were annotated as involved in the developmental process in the GO database and contributed to horn formation and plasticity in horned beetle development . The genes ecdysone receptor isoform A of O. taurus and ecdysone-induced protein 63E isoform N (c26961) of B. odoriphaga discovered in this study were both related to embryonic development. He et al.  discovered more than100 unigenes involved in gamete generation, ovarian follicle cell development and mating behavior of Phyllotreta striolata. The genes dynamin and glucose dehydrogenase in P. striolata were also found in B. odoriphaga (c4206 and c20905). Therefore, the discovery of similar genes in different species demonstrates the conservative functions of these genes.
Moreover, the expression levels of genes involved in the open tracheal system, heart, and stem cell development were stable in the third-instar and fourth-instar in B. odoriphaga. During the entire developmental phase of B. odoriphaga, the third-instar insects had a full-grown circulatory system and a digestive system, and the mostly damaged chives , which explains the fact that the related genes, such as (GK10804 [c24932]), expressed stably during the larval stage. In the pupal stage, the genes involved in the reproductive process, reproductive organ development, and PCD were all up-regulated, and those genes in the circulatory and digestive systems were down-regulated compared to larval-stage B. odoriphaga (Table 3 and S3 Table). It was related to the phenomenon in which adult B. odoriphaga took mating and laying eggs instead of feeding behavior completely . Therefore, the organs not related to reproduction, including salivary gland and other digestive organs, also entered into PCD [47–49]. The gene caspase Nc-like (c33601) was annotated in the KEGG apoptosis pathway (Ko04210). In the PCD process, production of lysosome organelleS was the important process. Genes ecdysteroid regulated-like protein (c17315) and lysosomal α-mannosidase (c30916) were annotated in the KEGG lysosome pathway (Ko04142). Therefore, the research of the KEGG pathway related to PCD could provide more regulated information for explaining the developmental mechanism from larval to pupal stages of B. odoriphaga. However, this will still need further verification through RNA interference (RNAi) technique in the next step. If the function of the key genes related to the developmental process can be demonstraed by RNAi in the next step, the aim of control of B. odoriphaga can be reached through silencing the key genes.
In our study, although the functions and the related signal transduction pathways of many unigenes have not been discovered, the information from transcriptome and DEG analysis could also provide a genetic basis for researching the developmental mechanism.
S1 Fig. Distribution of all unigenes of Bradysia odoriphaga at three developmental stages.
S2 Fig. Location distribution of mapped reads in mRNA.
Horizontal axis indicates the location of mRNA after dividing the mRNA into100 sections. Vertical axis indicates the ratio of mapped reads in the corresponding location of mRNA. The more even distribution of mapped reads in mRNA means a higher randomness of mRNA fragmentation.
S3 Fig. Simulated diagram of saturation test of sequencing data.
Horizontal axis indicates the number of reads (106) after dividing the mapped reads into100 sections. Vertical axis indicates the number of detected unigenes (fragments per kilobase of transcript per million mapped reads [FPKM] ≥ 0.1).
S4 Fig. Frequency of occurrence of annotated Bradysia odoriphaga unigenes in the Eukaryotic Orthologous Groups (KOG) data library.
S5 Fig. Frequency of occurrence of annotated Bradysia odoriphaga unigenes in the Clusters of Orthologous Groups (COG) data library.
S6 Fig. Correlation plot diagram of expression levels for unigenes of two biological replicates.
Horizontal axis and vertical axis indicate the value calculated according to log(fragments per kilobase of transcript per million mapped reads [FPKM] + 1) of two biological replicates of Bradysia odoriphaga in each developmental stage (3rd: Third-instar insects; 4th: Fourth-instar insects; Pupa: Pupal insects).
S7 Fig. Numbers of 45 differentially expressed genes (DEGs) together in each comparison analyzed by quantitative real-time polymerase chain reaction (qRT-PCR).
A: β-actin was a reference gene. B: β-tubulin was a reference gene. Three comparisons of third-instar and fourth-instar Bradysia odoriphaga (3rd vs 4th), third-instar and pupal insects (3rd vs Pupa), and fourth-instar and pupal insects (4th vs Pupa) are shown.
S8 Fig. PCR amplification analysis of 45 differentially expressed genes (DEGs) in Bradysia odoriphaga at three stages.
M: DNA marker (D2000); 1: Third-instar larvae; 2: Forth-instar larvae; 3: Pupa.
S1 Table. Primer sequence and fragment length of genes for RT-PCR.
S2 Table. Primer sequence of genes for qRT-PCR.
S3 Table. Regulated and annotated information of differentially expressed genes (DEGs) related to Bradysia odoriphaga development.
S4 Table. COG, KOG, and KEGG annotations of differentially expressed genes (DEGs) related to Bradysia odoriphaga development.
We are grateful to Biomarker Technologies Co. Ltd for transcriptome analysis related experiments. This work was financially supported through a grant from the Special Fund for Agro-scientific Research in the Public Interest from the Ministry of Agriculture of China (201303027).
Conceived and designed the experiments: HHG YFZ YY. Performed the experiments: HHG YFZ WBW. Analyzed the data: HHG YFZ HC XHZ QYZ YY RML. Contributed reagents/materials/analysis tools: HHG YFZ WBW YY. Wrote the paper: HHG YFZ.
- 1. Shi K. Taxonomy of eight genera and phylogenic study of Sciaridae from China (Diptera: Sciaridae). Hangzhou: Zhejiang A&F University. 2013.
- 2. Mei ZX, Wu QJ, Zhang YJ, Hua L. The biology, ecology and management of Bradysia odoriphaga. Entomol Knowl. 2003; 40: 396–398.
- 3. Imahori Y, Suzuki Y, Uemura K, Kishioka I, Fujiwara H, Ueda Y, et al. Physiological and quality responses of Chinese chive leaves to low oxygen atmospheres. Postharvest Biol Tech. 2004; 31: 295–303.
- 4. Misawa T, Kuninaga S. First report of white leaf rot on Chinese chives caused by Rhizoctonia solani AG-2-1. J Gen Plant Pathol. 2013; 79: 280–283.
- 5. Lu QY, Zhang WX, Guo WL, Zhang Y. A preliminary study on distributing phase and sampling methods of Bradysia odoriphaga larva in Chinese chive field. Acta Agric Boreali-Occident Sin. 2006; 15(2): 75–77.
- 6. Yang JK, Zhang XM. Notes on the fragrant onion gnats with descriptions of two new species of Bradysia odoriphaga (Diptera: Sciaridae). Acta Agri Univ Pekinen. 1985; 11: 153–156.
- 7. Feng HQ, Zheng FQ. Studies of the occurrence and control of Bradysia odoriphagaYang and Zhang. J Shandong Agric Univ. 1987; 18: 71–80.
- 8. Zhen JQ. Handbook of contemporary vegetable pests and diseases identification and management. Beijing: China Agriculture Press; 2004.
- 9. Li H, Zhu F, Zhou XM, Li N. Bionomics and control of the root maggot, Bradysia odoriphaga, infested on the watermelon. Entomol Knowl. 2007; 44: 834–836.
- 10. Zhang P, Liu F, Mu W, Wang QH, Li H, Chen CY. Life table study of the effects of sublethal concentrations of thiamethoxam on Bradysia odoriphaga Yang and Zhang. Pestic Biochem Phys. 2014; 111: 31–37.
- 11. Schuster SC. Next-generation sequencing transforms today’s biology. Nat Methods. 2008; 5: 16–18. pmid:18165802
- 12. Ansorge WJ. Next-generation DNA sequencing techniques. N Biotechnol. 2009; 25: 195–203. pmid:19429539
- 13. Anholt RRH, Dilda CL, Chang S, Fanara JJ, Kulkarni NH, GangulyI , et al. The genetic architecture of odor-guided behavior in Drosophila: Epistasis and the transcriptome. Nat Genes. 2003; 35: 180–184.
- 14. Huang JH, Miao XX, Jin WR, Couble P, Mita K, Zhang Y, et al. Serial analysis of gene expression in the silkworm, Bombyx mori. Genomics. 2005; 86: 233–241. pmid:15963683
- 15. Gibbons JG, Janson EM, Hittinger CT, Johnston M, Abbot P, Rokas A. Benchmarking next-generation transcriptome sequencing for functional and evolutionary genomics. Mol Biol Evol. 2009; 26: 2731–2744. pmid:19706727
- 16. Margam VM, Coates BS, Bayles DO, Hellmich RL, Agunbiade T, Seufferheld MJ, et al. Transcriptome sequencing, and rapid development and application of SNP markers for the legume pod borer Marucavitrata (Lepidoptera: Crambidae). PLoS ONE. 2011; 6(7): e21388. pmid:21754987
- 17. Pascual L, Jakubowska AK, Blanca JM, Canizares J, Ferre J, Gloeckner G, et al. The transcriptome of Spodoptera exigua larvae exposed to different types of microbes. Insect Biochem Molec. 2012; 42: 557–570.
- 18. Mardis ER. The impact of next-generation sequencing technology on genetics. Trends Genet. 2008; 24: 133–141. pmid:18262675
- 19. Morozova O, Marra MA. Applications of next-generation sequencing technologies in functional genomics. Genomics. 2008; 92: 255–264. pmid:18703132
- 20. Parchman TL, Geist KS, Grahnen JA, Benkman CW, Buerkle CA. Transcriptome sequencing in an ecologically important tree species: assembly, annotation, and marker discovery. BMC Genomics. 2010; 11: 180. pmid:20233449
- 21. Chen H, Lin L, Xie M, Zhang G, Su W. De novo sequencing and characterization of the Bradysia odoriphaga (Diptera: Sciaridae) larval transcriptome. Comp Biochem Phys D. 2015; 16: 20–27.
- 22. Arensburger P, Megy K, Waterhouse RM, Abrudan J, Amedeo P, Antelo B, et al. Sequencing of Culex quinquefasciatus establishes a platform for mosquito comparative genomics. Science. 2010; 330: 86–88. pmid:20929810
- 23. Nene V, Wortman JR, Lawson D, Haas B, Kodira C, Tu Z, et al. Genome sequence of Aedes aegypti, a major arbovirus vector. Science. 2007; 316: 1718–1723. pmid:17510324
- 24. Zerbino DR, Birney E. Velvet: Algorithms for de novo short-read assembly using de Bruijn graphs. Genome Res. 2008; 18: 821–829. pmid:18349386
- 25. Li B, Colin ND. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011; 12: 323. pmid:21816040
- 26. Schulze SK, Kanwar R, Glzenleuchter M, Therneau TM, Beutler AS. SERE: Single-parameter quality control and sample comparison for RNA-Seq. BMC Genomics 2012; 13(1): 524.
- 27. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2-△△Ct method. Methods. 2001; 25: 402–408. pmid:11846609
- 28. Kovtunovych G, Lar O, Kamalova S, Kordyum V, Kleiner D, Kozyrovska N. 1999. Correlation between pectate lyase activity and ability of diazotrophic Klebsiella oxytoca VN 13 to penetrate into plant tissues. Plant and Soil 215: 1–6.
- 29. Fender JE, Bender CM, Stella NA, Lahr RM, Kalivoda EJ, Shanks RMQ. Serratia marcescens Quinoprotein Glucose Dehydrogenase Activity Mediates Medium Acidification and Inhibition of Prodigiosin Production by Glucose. Applied and Environmental Microbiology, 2012; 78 (17): 6225 pmid:22752173
- 30. Zou CS, Cao CW, Zhang GC, Wang ZY. Purification, characterization, and sensitivity to pesticides of carboxylesterase from Dendrolimus superans (Lepidoptera: Lasiocampidae). J. Insect Sci. 14(260): 2014;
- 31. Mizrachi E, Hefer CA, Ranik M, Joubert F, Myburg AA. De novo assembled expressed gene catalog of a fast-growing Eucalyptus tree producedby Illumina mRNA-Seq. BMC Genomics. 2010; 11: 681–693. pmid:21122097
- 32. Munoz-Torres MC, Reese JT, Childers CP, Bennett AK, Sundaram JP, Childs KL, et al. Hymenoptera Genome Database: Integrated community resources for insect species of the order Hymenoptera. Nucleic Acids Res. 2011; 39: 658–662.
- 33. Papanicolaou A, Steffi GJ, Blaxter ML, McMillan WO, Jiggins CD. ButterflyBase: a platform for lepidopteran genomics. Nucleic Acids Res. 2008; 36: D582–D587. pmid:17933781
- 34. Xia Q, Wang J, Zhou Z, Li R, Fan W, Cheng D, et al. The genome of a lepidopteran model insect, the silkworm Bombyx mori. Insect Biochem Molec. 2008; 38(12): 1036–1045.
- 35. Keeling CI, Yuen MMS, Liao NY, Docking TR, Chan SK, Taylor GA, et al. Draft genome of the mountain pine beetle, Dendroctonus ponderosae Hopkins, a major forest pest. Genome Biol. 2013; 14: R27. pmid:23537049
- 36. Arrese EL, Soulages JL. Insect fat body: Enegy, metabolism, and regulation. Annu Rev Entomol. 2010; 55: 207–225. pmid:19725772
- 37. Joanisse DR, Storey KB. Enzyme activity profiles in an overwintering population of freeze-avoiding gall moth larvae, Epiblema scudderiana. Can J Zool. 1994; 72(6): 1079–1086.
- 38. Li YP, Gong H, Park HY. Enzymes of fatty acid metabolism in overwintering mature larvae of the pine needle gall midge, Thecodiplosos japonejsis. Insect Sci. 2000; 7(2): 135–141.
- 39. Daines B, Wang H, Wang L, Li Y, Han Y, Emmert D, et al. The Drosophila melanogaster transcriptome by paired-end RNA sequencing. Genome Res. 2010; 21: 315–324. pmid:21177959
- 40. Hahn DA, Ragland GJ, Shoemaker DD, Denlinger DL. Gene discovery using massively parallel pyrosequencing to develop ESTs for the flesh fly Sarcophaga crassipalpis. BMC Genomics. 2009; 10: 234. pmid:19454017
- 41. Lemke S, Antonopoulos DA, Meyer F, Domanus MH, Schmidt-Ott U. BMP signaling components in embryonic transcriptomes of the hover fly Episyrphus balteatus (Syrphidae). BMC Genomics. 2011; 12: 278. pmid:21627820
- 42. Nirmala X, Schetelig MF, Yu FH, Handler AM. An EST database of the Caribbean fruit fly, Anastrepha suspense (Diptera: Tephritidae). Gene. 2013; 517: 212–217. pmid:23296060
- 43. Sze SH, Dunham JP, Carey B, Chang PL, Li F, Edman RM, et al. A de novo transcriptome assembly of Lucilia sericata (Diptera: Calliphoridae) with predicted alternative splices, single nucleotide polymorphisms and transcript expression estimates. Insect Mol Biol. 2012; 21: 205–221. pmid:22283785
- 44. Wang ET, Cody NAL, Jog S, Biancolella M, Wang TT, Treacy DJ, et al. Transcriptome-wide regulation of pre- mRNA splicing and mRNA localization by muscle blindproteins. Cell. 2012; 150: 710–724. pmid:22901804
- 45. Choi JH, Kijimoto T, Snell-Rood E, Tae H, Yang Y, Moczek AP, et al. Gene discovery in the horned beetle Onthophagus Taurus. BMC Genomics. 2010; 11: 703. pmid:21156066
- 46. He HL, Bin SY, Wu ZZ, Lin JT. Transcriptome characteristics of Phyllotreta striolata (Fabricius) (Coleoptera: cehrysomelidae) analyzed by using Illumin’s Solexa sequencing technology. Acta Entomol Sinica. 2012; 55: 1–11.
- 47. Manji GA, Friesen PD. Apoptosis in motion. An apical, P35-insensitive caspase mediates programmed cell deathin insect cells. J Biol Chem. 2001; 276 (20): 16704–16710. pmid:11278634
- 48. Simon CR, de Almeida JC. Programmed cell death in Bradysia hygida (Diptera:Sciaridae) salivary glands presents apoptotic features. Mol Cell Biol. 2004; 40: 22–31.
- 49. Lanella P, Azeredo-Oliveira MTV, Itoyama MM. Programmed cell death in salivary glands of Drosophila arizonae and Drosophila mulleri. Genet Mol Res. 2008; 7: 476–486. pmid:18561381