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      Comparative transcriptomic and metabolomics analysis of ovary in Nilaparvata lugens after trehalase inhibition

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          Abstract

          The fecundity of Nilaparvata lugens (brown planthopper) is influenced by trehalase (TRE). To investigate the mechanism by which trehalose affects the reproduction of N. lugens, we conducted a comparative transcriptomic and metabolomic analysis of the ovaries of N. lugens following injection with dsTREs and validamycin (a TRE inhibitor). The results revealed that 844 differentially expressed genes (DEGs) were identified between the dsGFP and dsTREs injection groups, with 317 up-regulated genes and 527 down-regulated genes. Additionally, 1451 DEGs were identified between the water and validamycin injection groups, with 637 up-regulated genes and 814 down-regulated genes. The total number of DEGs identified between the two comparison groups was 236. The overlapping DEGs were implicated in various biological processes, including protein metabolism, fatty acid metabolism, AMPK signaling, mTOR signaling, insulin/insulin-like growth factor signaling (IIS), the tricarboxylic acid (TCA) cycle, oxidative phosphorylation, and the cellular process of meiosis in oocytes. These results suggest that the inhibition of TRE expression may lead to alterations in ovarian nutrient and energy metabolism by modulating glucose transport and affecting amino acid metabolic pathways. These alterations may influence the reproduction of N. lugens by modulating reproductive regulatory signals. These findings provide robust evidence supporting the mechanism through which trehalase inhibition reduces the reproductive capacity of N. lugens.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-025-11268-8.

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            HISAT: a fast spliced aligner with low memory requirements.

            HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
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              Differential expression analysis for sequence count data

              High-throughput sequencing assays such as RNA-Seq, ChIP-Seq or barcode counting provide quantitative readouts in the form of count data. To infer differential signal in such data correctly and with good statistical power, estimation of data variability throughout the dynamic range and a suitable error model are required. We propose a method based on the negative binomial distribution, with variance and mean linked by local regression and present an implementation, DESeq, as an R/Bioconductor package.
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                Author and article information

                Contributors
                tanxiaoling@caas.cn
                tbzm611@hznu.edu.cn
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                1 February 2025
                1 February 2025
                2025
                : 26
                : 98
                Affiliations
                [1 ]College of Life and Environmental Sciences, Hangzhou Normal University, ( https://ror.org/014v1mr15) Hangzhou, Zhejiang 311121 P.R. China
                [2 ]Chinese Education Modernization Research Institute of Hangzhou Normal University, Hangzhou Normal University, ( https://ror.org/014v1mr15) Hangzhou, Zhejiang 311121 P.R. China
                [3 ]State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, ( https://ror.org/0313jb750) Beijing, 100193 P.R. China
                [4 ]Zhongyuan Research Center, Chinese Academy of Agricultural Sciences, ( https://ror.org/0313jb750) Xinxiang, 453500 P.R. China
                Article
                11268
                10.1186/s12864-025-11268-8
                11787742
                39893429
                ee55e44f-488f-4ce0-a649-81fd4ac5aa0b
                © The Author(s) 2025

                Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/.

                History
                : 4 July 2024
                : 21 January 2025
                Funding
                Funded by: National Key R & D Program of China
                Award ID: 2023YFE0104800
                Funded by: ADOPT- IPM project
                Award ID: 101060430
                Funded by: National Natural Science Foundation of China
                Award ID: No.32272608
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2025

                Genetics
                nilaparvata lugens,transcriptomic,metabolomics,ovary development,trehalase
                Genetics
                nilaparvata lugens, transcriptomic, metabolomics, ovary development, trehalase

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