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      Identifying plant genes shaping microbiota composition in the barley rhizosphere

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          Abstract

          A prerequisite to exploiting soil microbes for sustainable crop production is the identification of the plant genes shaping microbiota composition in the rhizosphere, the interface between roots and soil. Here, we use metagenomics information as an external quantitative phenotype to map the host genetic determinants of the rhizosphere microbiota in wild and domesticated genotypes of barley, the fourth most cultivated cereal globally. We identify a small number of loci with a major effect on the composition of rhizosphere communities. One of those, designated the QRMC-3HS, emerges as a major determinant of microbiota composition. We subject soil-grown sibling lines harbouring contrasting alleles at QRMC-3HS and hosting contrasting microbiotas to comparative root RNA-seq profiling. This allows us to identify three primary candidate genes, including a Nucleotide-Binding-Leucine-Rich-Repeat ( NLR) gene in a region of structural variation of the barley genome. Our results provide insights into the footprint of crop improvement on the plant’s capacity of shaping rhizosphere microbes.

          Abstract

          A prerequisite to exploiting soil microbes for sustainable crop production is the identification of the plant genes shaping microbiota composition in the rhizosphere. Here, the authors report QTLs and the associated candidate genes underlying rhizosphere microbiome composition in barley.

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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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            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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              Basic local alignment search tool.

              A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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                Author and article information

                Contributors
                d.bulgarelli@dundee.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                16 June 2022
                16 June 2022
                2022
                : 13
                : 3443
                Affiliations
                [1 ]GRID grid.8241.f, ISNI 0000 0004 0397 2876, University of Dundee, Plant Sciences, School of Life Sciences, ; Dundee, UK
                [2 ]GRID grid.8241.f, ISNI 0000 0004 0397 2876, University of Dundee, Computational Biology, School of Life Sciences, ; Dundee, UK
                [3 ]Mohammed VI Polytechnic University, Agrobiosciences Program, Plant & Soil Microbiome Subprogram, Bengurir, Morocco
                [4 ]GRID grid.43641.34, ISNI 0000 0001 1014 6626, The James Hutton Institute, ; Invergowrie, UK
                [5 ]GRID grid.10373.36, ISNI 0000000122055422, Department of Biosciences and Territory, , University of Molise, ; Campobasso, Italy
                [6 ]GRID grid.34988.3e, ISNI 0000 0001 1482 2038, Faculty of Science and Technology, , Free University of Bozen-Bolzano, ; Bolzano, Italy
                [7 ]GRID grid.34988.3e, ISNI 0000 0001 1482 2038, Competence Centre for Plant Health, , Free University of Bozen-Bolzano, ; Bolzano, Italy
                [8 ]GRID grid.426884.4, ISNI 0000 0001 0170 6644, Scotland’s Rural College, ; Edinburgh, UK
                [9 ]GRID grid.9906.6, ISNI 0000 0001 2289 7785, Department of Biological and Environmental Sciences and Technologies, , University of Salento, ; Lecce, Italy
                [10 ]GRID grid.9018.0, ISNI 0000 0001 0679 2801, Institute of Agricultural and Nutritional Sciences, , Martin-Luther-University, ; Halle-Wittenberg, Germany
                Author information
                http://orcid.org/0000-0002-8162-3618
                http://orcid.org/0000-0002-3124-9146
                http://orcid.org/0000-0002-2916-7475
                http://orcid.org/0000-0003-4646-6351
                http://orcid.org/0000-0002-2375-8370
                http://orcid.org/0000-0002-9014-5355
                http://orcid.org/0000-0003-1045-3065
                http://orcid.org/0000-0002-2020-6642
                Article
                31022
                10.1038/s41467-022-31022-y
                9203816
                35710760
                638f63bc-bd2a-461f-98f1-70d431150e20
                © The Author(s) 2022

                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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 20 December 2021
                : 30 May 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000268, RCUK | Biotechnology and Biological Sciences Research Council (BBSRC);
                Award ID: BB/S002871/1
                Award ID: BB/S002871/1
                Award ID: BB/S002871/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000332, Royal Society of Edinburgh (RSE);
                Award ID: Personal Fellowship 2013-18
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                plant domestication,microbiome,agricultural genetics
                Uncategorized
                plant domestication, microbiome, agricultural genetics

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