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      MicroRNA (miRNA) profiling of maize genotypes with differential response to Aspergillus flavus implies zma-miR156–squamosa promoter binding protein (SBP) and zma-miR398/zma-miR394–F -box combinations involved in resistance mechanisms

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          Abstract

          Maize ( Zea mays), a major food crop worldwide, is susceptible to infection by the saprophytic fungus Aspergillus flavus that can produce the carcinogenic metabolite aflatoxin (AF) especially under climate change induced abiotic stressors that favor mold growth. Several studies have used “-omics” approaches to identify genetic elements with potential roles in AF resistance, but there is a lack of research identifying the involvement of small RNAs such as microRNAs (miRNAs) in maize- A. flavus interaction. In this study, we compared the miRNA profiles of three maize lines (resistant TZAR102, moderately resistant MI82, and susceptible Va35) at 8 h, 3 d, and 7 d after A. flavus infection to investigate possible regulatory antifungal role of miRNAs. A total of 316 miRNAs (275 known and 41 putative novel) belonging to 115 miRNA families were identified in response to the fungal infection across all three maize lines. Eighty-two unique miRNAs were significantly differentially expressed with 39 miRNAs exhibiting temporal differential regulation irrespective of the maize genotype, which targeted 544 genes (mRNAs) involved in diverse molecular functions. The two most notable biological processes involved in plant immunity, namely cellular responses to oxidative stress (GO:00345990) and reactive oxygen species (GO:0034614) were significantly enriched in the resistant line TZAR102. Coexpression network analysis identified 34 hubs of miRNA-mRNA pairs where nine hubs had a node in the module connected to their target gene with potentially important roles in resistance/susceptible response of maize to A. flavus. The miRNA hubs in resistance modules (TZAR102 and MI82) were mostly connected to transcription factors and protein kinases. Specifically, the module of miRNA zma-miR156b-nb – squamosa promoter binding protein (SBP), zma-miR398a-3p – SKIP5, and zma-miR394a-5p – F-box protein 6 combinations in the resistance-associated modules were considered important candidates for future functional studies.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s44154-024-00158-w.

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          Most cited references51

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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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.

                Author and article information

                Contributors
                kanniah.rajasekaran@usda.gov
                nbaisakh@agcenter.lsu.edu
                Journal
                Stress Biol
                Stress Biol
                Stress Biology
                Springer Nature Singapore (Singapore )
                2731-0450
                10 May 2024
                10 May 2024
                December 2024
                : 4
                : 1
                : 26
                Affiliations
                [1 ]School of Plant, Environmental and Soil Sciences, Louisiana State University Agricultural Center, ( https://ror.org/01b8rza40) Baton Rouge, LA 70803 USA
                [2 ]Food and Feed Safety Research Unit, Southern Regional Research Center, USDA-ARS, ( https://ror.org/01cghcn81) New Orleans, LA 70726 USA
                Author notes

                Handling editor: Dr. Mukesh Jain.

                Author information
                http://orcid.org/0000-0001-8733-0923
                Article
                158
                10.1007/s44154-024-00158-w
                11087424
                38727957
                21a09685-365f-4948-8eac-ebf52befc05b
                © The Author(s) 2024

                Open Access This 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/.

                History
                : 10 January 2024
                : 5 March 2024
                Funding
                Funded by: USDA-ARS
                Award ID: NACA Agreement# 58-6054-0-010
                Award Recipient :
                Categories
                Original Paper
                Custom metadata
                © Northwest A&F University (NWAFU) 2024

                aspergillus flavus,aflatoxin,coexpression network,microrna,resistance,transcription factor

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