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      Integrated examination of the transcriptome and metabolome of the gene expression response and metabolite accumulation in soybean seeds for seed storability under aging stress

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          Abstract

          Soybean quality and production are determined by seed viability. A seed’s capacity to sustain germination via dry storage is known as its seed life. Thus, one of the main objectives for breeders is to preserve genetic variety and gather germplasm resources. However, seed quality and germplasm preservation have become significant obstacles. In this study, four artificially simulated aging treatment groups were set for 0, 24, 72, and 120 hours. Following an aging stress treatment, the transcriptome and metabolome data were compared in two soybean lines with notable differences in seed vigor—R31 (aging sensitive) and R80 (aging tolerant). The results showed that 83 (38 upregulated and 45 downregulated), 30 (19 upregulated and 11 downregulated), 90 (52 upregulated and 38 downregulated), and 54 (25 upregulated and 29 downregulated) DEGs were differentially expressed, respectively. A total of 62 (29 upregulated and 33 downregulated), 94 (49 upregulated and 45 downregulated), 91 (53 upregulated and 38 downregulated), and 135 (111 upregulated and 24 downregulated) differential metabolites accumulated. Combining the results of transcriptome and metabolome investigations demonstrated that the difference between R31 and R80 responses to aging stress was caused by genes related to phenylpropanoid metabolism pathway, which is linked to the seed metabolite caffeic acid. According to this study’s preliminary findings, the aging-resistant line accumulated more caffeic acid than the aging-sensitive line, which improved its capacity to block lipoxygenase (LOX) activity. An enzyme activity inhibition test was used to demonstrate the effect of caffeic acid. After soaking seeds in 1 mM caffeic acid (a LOX inhibitor) for 6 hours and artificially aging them for 24 hours, the germination rates of the R31 and R80 seeds were enhanced. In conclusion, caffeic acid has been shown to partially mitigate the negative effects of soybean seed aging stress and to improve seed vitality. This finding should serve as a theoretical foundation for future research on the aging mechanism of soybean seeds.

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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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            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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              fastp: an ultra-fast all-in-one FASTQ preprocessor

              Abstract Motivation Quality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter trimming and quality filtering. These tools are often insufficiently fast as most are developed using high-level programming languages (e.g. Python and Java) and provide limited multi-threading support. Reading and loading data multiple times also renders preprocessing slow and I/O inefficient. Results We developed fastp as an ultra-fast FASTQ preprocessor with useful quality control and data-filtering features. It can perform quality control, adapter trimming, quality filtering, per-read quality pruning and many other operations with a single scan of the FASTQ data. This tool is developed in C++ and has multi-threading support. Based on our evaluation, fastp is 2–5 times faster than other FASTQ preprocessing tools such as Trimmomatic or Cutadapt despite performing far more operations than similar tools. Availability and implementation The open-source code and corresponding instructions are available at https://github.com/OpenGene/fastp.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/2743712Role: Role:
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                URI : https://loop.frontiersin.org/people/1627547Role: Role:
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                URI : https://loop.frontiersin.org/people/2248413Role: Role:
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                URI : https://loop.frontiersin.org/people/904374Role: Role:
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                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                08 July 2024
                2024
                : 15
                : 1437107
                Affiliations
                [1] 1 Jilin Academy of Agricultural Sciences (China Agricultural Science and Technology Northeast Innovation Center), Soybean Research Institute , Changchun, China
                [2] 2 Northeast Agricultural University , Harbin, Heilongjiang, China
                Author notes

                Edited by: Huatao Chen, Jiangsu Academy of Agricultural Sciences (JAAS), China

                Reviewed by: Hengyou Zhang, Chinese Academy of Sciences (CAS), China

                Chengfu Su, Qingdao Agricultural University, China

                *Correspondence: Qingshan Chen, qshchen@ 123456126.com ; Shuming Wang, shumingw@ 123456263.net ; Hongwei Jiang, j3994102@ 123456126.com

                †These authors have contributed equally to this work and share first authorship

                Article
                10.3389/fpls.2024.1437107
                11261460
                39040511
                f62cdfd8-0f83-435b-b160-ce53ce245ff6
                Copyright © 2024 Li, Xie, Zhang, Meng, Yang, Fan, Sun, Zheng, Zhang, Wang, Chen, Wang and Jiang

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 23 May 2024
                : 25 June 2024
                Page count
                Figures: 7, Tables: 2, Equations: 0, References: 43, Pages: 13, Words: 4780
                Funding
                Funded by: Innovative Research Group Project of the National Natural Science Foundation of China , doi 10.13039/100014718;
                Award ID: U21A20215
                Funded by: Agriculture Research System of China , doi 10.13039/501100010203;
                Award ID: CARS-04-PS08 and CARS-04-PS15
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Financial support was received from the National Science Foundation of China (U21A20215) and the China Agriculture Research System of MOF and MARA (CARS-04-PS08 and CARS-04-PS15).
                Categories
                Plant Science
                Original Research
                Custom metadata
                Functional and Applied Plant Genomics

                Plant science & Botany
                soybean,aging,caffeic acid,transcriptome,metabolomic
                Plant science & Botany
                soybean, aging, caffeic acid, transcriptome, metabolomic

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