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      Arabidopsis transcriptome responses to low water potential using high-throughput plate assays

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          Abstract

          Soil-free assays that induce water stress are routinely used to investigate drought responses in the plant Arabidopsis thaliana. Due to their ease of use, the research community often relies on polyethylene glycol (PEG), mannitol, and salt (NaCl) treatments to reduce the water potential of agar media, and thus induce drought conditions in the laboratory. However, while these types of stress can create phenotypes that resemble those of water deficit experienced by soil-grown plants, it remains unclear how these treatments compare at the transcriptional level. Here, we demonstrate that these different methods of lowering water potential elicit both shared and distinct transcriptional responses in Arabidopsis shoot and root tissue. When we compared these transcriptional responses to those found in Arabidopsis roots subject to vermiculite drying, we discovered many genes induced by vermiculite drying were repressed by low water potential treatments on agar plates (and vice versa). Additionally, we also tested another method for lowering water potential of agar media. By increasing the nutrient content and tensile strength of agar, we show the ‘hard agar’ (HA) treatment can be leveraged as a high-throughput assay to investigate natural variation in Arabidopsis growth responses to low water potential.

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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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            HTSeq—a Python framework to work with high-throughput sequencing data

            Motivation: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. Results: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. Availability and implementation: HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. Contact: sanders@fs.tum.de
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              Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype

              Rapid advances in next-generation sequencing technologies have dramatically changed our ability to perform genome-scale analyses. The human reference genome used for most genomic analyses represents only a small number of individuals, limiting its usefulness for genotyping. We designed a novel method, HISAT2, for representing and searching an expanded model of the human reference genome, in which a large catalogue of known genomic variants and haplotypes is incorporated into the data structure used for searching and alignment. This strategy for representing a population of genomes, along with a fast and memory-efficient search algorithm, enables more detailed and accurate variant analyses than previous methods. We demonstrate two initial applications of HISAT2: HLA typing, a critical need in human organ transplantation, and DNA fingerprinting, widely used in forensics. These applications are part of HISAT-genotype, with performance not only surpassing earlier computational methods, but matching or exceeding the accuracy of laboratory-based assays.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                21 June 2024
                2024
                : 12
                : RP84747
                Affiliations
                [1 ] Plant Biology Laboratory, The Salk Institute for Biological Studies ( https://ror.org/03xez1567) La Jolla United States
                [2 ] The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, Faculty of Agriculture, Food, and Environment, The Hebrew University of Jerusalem ( https://ror.org/03qxff017) Rehovot Israel
                [3 ] Genomic Analysis Laboratory, The Salk Institute for Biological Studies ( https://ror.org/03xez1567) La Jolla United States
                [4 ] Howard Hughes Medical Institute, The Salk Institute for Biological Studies ( https://ror.org/03xez1567) La Jolla United States
                Stanford University ( https://ror.org/00f54p054) United States
                University of Freiburg ( https://ror.org/0245cg223) Germany
                Stanford University United States
                Howard Hughes Medical Institute, Salk Institute for Biological Studies La Jolla United States
                Howard Hughes Medical Institute, Salk Institute for Biological Studies La Jolla United States
                The Hebrew University of Jerusalem Rehovot Israel
                Howard Hughes Medical Institute, Salk Institute for Biological Studies La Jolla United States
                Salk Institute for Biological Studies La Jolla United States
                Howard Hughes Medical Institute, Salk Institute for Biological Studies La Jolla United States
                Salk Institute for Biological Studies La Jolla United States
                Salk Institute for Biological Studies La Jolla United States
                The Hebrew University of Jerusalem Rehovot Israel
                Howard Hughes Medical Institute, Salk Institute for Biological Studies La Jolla United States
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0009-0005-8339-9911
                https://orcid.org/0000-0001-9559-1699
                https://orcid.org/0000-0001-5799-5895
                Article
                84747
                10.7554/eLife.84747
                11192529
                38904663
                3994c863-df39-4bed-bb6e-1dc1583cc1fb
                © 2023, Gonzalez, Swift et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 27 November 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000011, Howard Hughes Medical Institute;
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Short Report
                Plant Biology
                Custom metadata
                The 'low water' agar assay provides a reliable and practical high-throughput method for studying plant molecular signaling responses to drought stress.
                prc

                Life sciences
                drought,gene expression,high-throughput assay,a. thaliana
                Life sciences
                drought, gene expression, high-throughput assay, a. thaliana

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