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      Aluminum or Low pH – Which Is the Bigger Enemy of Barley? Transcriptome Analysis of Barley Root Meristem Under Al and Low pH Stress

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          Abstract

          Aluminum (Al) toxicity is considered to be the most harmful abiotic stress in acidic soils that today comprise more than 50% of the world’s arable lands. Barley belongs to a group of crops that are most sensitive to Al in low pH soils. We present the RNA-seq analysis of root meristems of barley seedlings grown in hydroponics at optimal pH (6.0), low pH (4.0), and low pH with Al (10 μM of bioavailable Al 3+ ions). Two independent experiments were conducted: with short-term (24 h) and long-term (7 days) Al treatment. In the short-term experiment, more genes were differentially expressed (DEGs) between root meristems grown at pH = 6.0 and pH = 4.0, than between those grown at pH = 4.0 with and without Al treatment. The genes upregulated by low pH were associated mainly with response to oxidative stress, cell wall organization, and iron ion binding. Among genes upregulated by Al, overrepresented were those related to response to stress condition and calcium ion binding. In the long-term experiment, the number of DEGs between hydroponics at pH = 4.0 and 6.0 were lower than in the short-term experiment, which suggests that plants partially adapted to the low pH. Interestingly, 7 days Al treatment caused massive changes in the transcriptome profile. Over 4,000 genes were upregulated and almost 2,000 genes were downregulated by long-term Al stress. These DEGs were related to stress response, cell wall development and metal ion transport. Based on our results we can assume that both, Al 3+ ions and low pH are harmful to barley plants. Additionally, we phenotyped the root system of barley seedlings grown in the same hydroponic conditions for 7 days at pH = 6.0, pH = 4.0, and pH = 4.0 with Al. The results correspond to transcriptomic data and show that low pH itself is a stress factor that causes a significant reduction of root growth and the addition of aluminum further increases this reduction. It should be noted that in acidic arable lands, plants are exposed simultaneously to both of these stresses. The presented transcriptome analysis may help to find potential targets for breeding barley plants that are more tolerant to such conditions.

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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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            Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

            The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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              STAR: ultrafast universal RNA-seq aligner.

              Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                19 May 2021
                2021
                : 12
                : 675260
                Affiliations
                [1] 1Institute of Biology, Biotechnology and Environmental Protection, Faculty of Natural Sciences, University of Silesia in Katowice , Katowice, Poland
                [2] 2Centre for Bioinformatics and Data Analysis, Medical University of Bialystok , Bialystok, Poland
                [3] 3Clinical Research Centre, Medical University of Bialystok , Bialystok, Poland
                [4] 4Department of Biochemistry, University of California, Riverside , Riverside, CA, United States
                Author notes

                Edited by: Joanna Jankowicz-Cieslak, International Atomic Energy Agency, Austria

                Reviewed by: Zhong-Hua Chen, Western Sydney University, Australia; Loriana Demecsová, Center of Plant Science and Biodiversity, Institute of Botany, Slovak Academy of Sciences, Slovakia

                *Correspondence: Miriam Szurman-Zubrzycka, miriam.szurman@ 123456us.edu.pl

                This article was submitted to Systems Biology, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2021.675260
                8244595
                34220949
                9447892d-aafe-4a75-bef8-f24e1b29b189
                Copyright © 2021 Szurman-Zubrzycka, Chwiałkowska, Niemira, Kwaśniewski, Nawrot, Gajecka, Larsen and Szarejko.

                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
                : 02 March 2021
                : 13 April 2021
                Page count
                Figures: 14, Tables: 1, Equations: 0, References: 106, Pages: 23, Words: 0
                Funding
                Funded by: Narodowe Centrum Badań i Rozwoju 10.13039/501100005632
                Funded by: Narodowym Centrum Nauki 10.13039/501100004442
                Categories
                Genetics
                Original Research

                Genetics
                barley,rna-seq,transcriptome,low ph,aluminum (al),stress,root meristem
                Genetics
                barley, rna-seq, transcriptome, low ph, aluminum (al), stress, root meristem

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