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      Changes in m 6A RNA methylation are associated with male sterility in wolfberry

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          Abstract

          Background

          N 6-methyladenosine (m 6A) modification is the most abundant type of RNA modification in eukaryotic cells, playing pivotal roles in multiple plant growth and development processes. Yet the potential role of m 6A in conferring the trait of male sterility in plants remains unknown.

          Results

          In this study, we performed RNA-sequencing (RNA-Seq) and m 6A-sequencing (m 6A-Seq) of RNAs obtained from the anther tissue of two wolfberry lines: ‘Ningqi No.1’ ( LB1) and its natural male sterile mutant ‘Ningqi No.5’ ( LB5). Based on the newly assembled transcriptome, we established transcriptome-wide m 6A maps for LB1 and LB5 at the single nucleus pollen stage. We found that the gene XLOC_021201, a homolog of m 6A eraser-related gene ALKBH10 in Arabidopsis thaliana, was significantly differentially expressed between LB1 and LB5. We also identified 1642 and 563 m 6A-modified genes with hypermethylated and hypomethylated patterns, respectively, in LB1 compared with LB5. We found the hypermethylated genes significantly enriched in biological processes related to energy metabolism and lipid metabolism, while hypomethylation genes were mainly linked to cell cycle process, gametophyte development, and reproductive process. Among these 2205 differentially m 6A methylated genes, 13.74% (303 of 2205) were differentially expressed in LB1 vis-à-vis LB5.

          Conclusions

          This study constructs the first m 6A transcriptome map of wolfberry and establishes an association between m 6A and the trait of male sterility in wolfberry.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12870-023-04458-7.

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          Most cited references67

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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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            MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

            We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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              featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

              Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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                Author and article information

                Contributors
                gcp1214@163.com
                cma@nwafu.edu.cn
                Journal
                BMC Plant Biol
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central (London )
                1471-2229
                29 September 2023
                29 September 2023
                2023
                : 23
                : 456
                Affiliations
                [1 ]State Key Laboratory of Crop Stress Biology for Arid Areas, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, ( https://ror.org/0051rme32) Yangling, Shaanxi 712100 China
                [2 ]College of Life Science, Ningxia University, ( https://ror.org/04j7b2v61) Yinchuan, Ningxia 750021 China
                Article
                4458
                10.1186/s12870-023-04458-7
                10540408
                37770861
                7b1b103b-d813-4530-94b2-bdbab7a11484
                © BioMed Central Ltd., part of Springer Nature 2023

                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/. 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
                : 12 April 2023
                : 12 September 2023
                Funding
                Funded by: Ningxia Natural Science Foundation
                Award ID: 2022AAC05020
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 32170681
                Award Recipient :
                Funded by: Hundred Talents Program of Shaanxi Province of China
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Plant science & Botany
                differential methylation,m6a regulators,male sterility,n6-methyladenosine,wolfberry

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