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. 2016 Oct 12;17(1):793.
doi: 10.1186/s12864-016-2759-2.

Transcriptome profiling of Diachasmimorpha longicaudata towards useful molecular tools for population management

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Transcriptome profiling of Diachasmimorpha longicaudata towards useful molecular tools for population management

M Constanza Mannino et al. BMC Genomics. .

Abstract

Background: Diachasmimorpha longicaudata (Hymenoptera: Braconidae) is a solitary parasitoid of Tephritidae (Diptera) fruit flies of economic importance currently being mass-reared in bio-factories and successfully used worldwide. A peculiar biological aspect of Hymenoptera is its haplo-diploid life cycle, where females (diploid) develop from fertilized eggs and males (haploid) from unfertilized eggs. Diploid males were described in many species and recently evidenced in D. longicaudata by mean of inbreeding studies. Sex determination in this parasitoid is based on the Complementary Sex Determination (CSD) system, with alleles from at least one locus involved in early steps of this pathway. Since limited information is available about genetics of this parasitoid species, a deeper analysis on D. longicaudata's genomics is required to provide molecular tools for achieving a more cost effective production under artificial rearing conditions.

Results: We report here the first transcriptome analysis of male-larvae, adult females and adult males of D. longicaudata using 454-pyrosequencing. A total of 469766 reads were analyzed and 8483 high-quality isotigs were assembled. After functional annotation, a total of 51686 unigenes were produced, from which, 7021 isotigs and 20227 singletons had at least one BLAST hit against the NCBI non-redundant protein database. A preliminary comparison of adult female and male evidenced that 98 transcripts showed differential expression profiles, with at least a 10-fold difference. Among the functionally annotated transcripts we detected four sequences potentially involved in sex determination and three homologues to two known genes involved in the sex determination cascade. Finally, a total of 4674SimpleSequence Repeats (SSRs) were in silico identified and characterized.

Conclusion: The information obtained here will significantly contribute to the development of D. longicaudata functional genomics, genetics and population-based genome studies. Thousands of new microsatellite markers were identified as toolkits for population genetics analysis. The transcriptome characterized here is the starting point to elucidate the molecular bases of the sex determination mechanism in this species.

Keywords: Diachasmimorpha longicaudata; Gene expression; Molecular markers; Sex determination; Transcriptomics.

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Figures

Fig. 1
Fig. 1
Frequency distribution of isotigs (a) and singletons (b). Sequence length and frequency distribution of predicted peptides from isotigs (c) and singletons (d). The histograms represent the number of isotigs and singletons sequences in relation to its length and the number of predicted peptides in relation to its length grouped in 50 amino acids boxes
Fig. 2
Fig. 2
Genome and transcriptome comparisonwithrelated model species. Circular representation of: Ring 1:N.vitripennis(named Nvit) and A.mellifera(named Amel) genomes distributed in chromosomes; Ring 2: transcript density of Nvit and Amel; Ring 3: D. longicaudata transcript density
Fig. 3
Fig. 3
Gene Ontology (GO) assignment. The total numbers of terms annotated for each main category are 13142 for “Biological Process” (a), 17188 for “Molecular Function” (elemental activities) (b), and 9911 for “Cellular Component” (c)
Fig. 4
Fig. 4
Logarithmic scale scatterplot of female/male differentially expressed transcripts. Female (y axe) and male (x axe) reads normalized to larvae of male library are represented in logarithmic scale
Fig. 5
Fig. 5
Comparative expression profiles obtained by RNA sequencing andRT-qPCR of GI. Isotigs 02512 (a/b), 01415 (c/d), 03151 (e/f), 07202 (g/h), 06880 (i/j), 08283 (k/l) between male and female. EU and NRQ are Expression Units and Normalized Read Count respectively (see methods). Reference genes for RT-qPCR: β-actin (act) and alpha 1 elongation factor (α1-ef)

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