High-throughput profiling of diapause regulated genes from  Trichogramma dendrolimi  (Hymenoptera: Trichogrammatidae)

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Abstract

Background

The parasitoid wasp, Trichogramma dendrolimi, can enter diapause at the prepupal stage. Thus, diapause is an efficient preservation method during the mass production of T. dendrolimi. Previous studies on diapause have mainly focused on ecological characteristics, so the molecular basis of diapause in T. dendrolimi is unknown. We compared transcriptomes of diapause and non-diapause T. dendrolimi to identify key genes and pathways involved in diapause development.

Results

Transcriptome sequencing was performed on diapause prepupae, pupae after diapause, non-diapause prepupae, and pupae. Analysis yielded a total of 87,022 transcripts with an average length of 1604 bp. By removing redundant sequences and those without significant BLAST hits, a non-redundant dataset was generated, containing 7593 sequences with an average length of 3351 bp. Among them, 5702 genes were differentially expressed. The result of Gene Ontology (GO) enrichment analysis revealed that regulation of transcription, DNA-templated, oxidation-reduction process, and signal transduction were significantly affected. Ten genes were selected for validation using quantitative real-time PCR (qPCR). The changes showed the same trend as between the qPCR and RNA-Seq results. Several genes were identified as involved in diapause, including ribosomal proteins, zinc finger proteins, homeobox proteins, forkhead box proteins, UDP-glucuronosyltransferase , Glutathione-S-transferase, p53, and DNA damage-regulated gene 1 ( pdrg1). Genes related to lipid metabolism were also included.

Conclusions

We generated a large amount of transcriptome data from T. dendrolimi, providing a resource for future gene function research. The diapause-related genes identified help reveal the molecular mechanisms of diapause, in T. dendrolimi, and other insect species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07285-4.

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Most cited references 66

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Manfred Grabherr, Brian Haas, Moran Yassour … (2011)

Massively-parallel cDNA sequencing has opened the way to deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here, we present the Trinity methodology for de novo full-length transcriptome reconstruction, and evaluate it on samples from fission yeast, mouse, and whitefly – an insect whose genome has not yet been sequenced. Trinity fully reconstructs a large fraction of the transcripts present in the data, also reporting alternative splice isoforms and transcripts from recently duplicated genes. In all cases, Trinity performs better than other available de novo transcriptome assembly programs, and its sensitivity is comparable to methods relying on genome alignments. Our approach provides a unified and general solution for transcriptome reconstruction in any sample, especially in the complete absence of a reference genome.

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High-throughput functional annotation and data mining with the Blast2GO suite

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Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologist-oriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) high-throughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data.

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Author and article information

Contributors

Changchun Ruan: ruanchangchun@126.com

Journal

Journal ID (nlm-ta): BMC Genomics

Journal ID (iso-abbrev): BMC Genomics

Title: BMC Genomics

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2164

Publication date (Electronic): 4 December 2020

Publication date PMC-release: 4 December 2020

Publication date Collection: 2020

Volume: 21

Electronic Location Identifier: 864

Affiliations

[1 ]GRID grid.464353.3, ISNI 0000 0000 9888 756X, Engineering Research Center of Natural Enemies, , Institute of Biological Control, Jilin Agricultural University, ; Changchun, 130118 China

[2 ]GRID grid.458458.0, ISNI 0000 0004 1792 6416, State Key Laboratory of Integrated Management of Pest Insect and Rodents, , Institute of Zoology, Chinese Academy of Sciences, ; Beijing, 100101 China

Article

Publisher ID: 7285

DOI: 10.1186/s12864-020-07285-4

PMC ID: 7718664

PubMed ID: 33276726

SO-VID: 7c9a7ade-8ae9-4907-8162-0f19e04128f4

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

History

Date received : 12 February 2020

Date accepted : 26 November 2020

Funding

Funded by: National Key R&D Program of China

Award ID: 2017YFD0200400

Award Recipient : Junjie Zhang

Funded by: National Key R&D Program of China

Award ID: 2019YFC1200504

Award Recipient : Zhen Zou

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: trichogramma dendrolimi,transcriptome,rna-seq,diapause,diapause-related genes

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ScienceOpen disciplines: Genetics

Keywords: trichogramma dendrolimi, transcriptome, rna-seq, diapause, diapause-related genes

High-throughput profiling of diapause regulated genes from Trichogramma dendrolimi (Hymenoptera: Trichogrammatidae)

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Abstract

Background

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Supplementary Information

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Hymenoptera

Most cited references 66

Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data

High-throughput functional annotation and data mining with the Blast2GO suite

p53, the cellular gatekeeper for growth and division.

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