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      Genetic variation and evolutionary history of a mycorrhizal fungus regulate the currency of exchange in symbiosis with the food security crop cassava

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          Abstract

          Most land plants form symbioses with arbuscular mycorrhizal fungi (AMF). Diversity of AMF increases plant community productivity and plant diversity. For decades, it was known that plants trade carbohydrates for phosphate with their fungal symbionts. However, recent studies show that plant-derived lipids probably represent the most essential currency of exchange. Understanding the regulation of plant genes involved in the currency of exchange is crucial to understanding stability of this mutualism. Plants encounter many different AMF genotypes that vary greatly in the benefit they confer to plants. Yet the role that fungal genetic variation plays in the regulation of this currency has not received much attention. We used a high-resolution phylogeny of one AMF species ( Rhizophagus irregularis) to show that fungal genetic variation drives the regulation of the plant fatty acid pathway in cassava ( Manihot esculenta); a pathway regulating one of the essential currencies of trade in the symbiosis. The regulation of this pathway was explained by clearly defined patterns of fungal genome-wide variation representing the precise fungal evolutionary history. This represents the first demonstrated link between the genetics of AMF and reprogramming of an essential plant pathway regulating the currency of exchange in the symbiosis. The transcription factor RAM1 was also revealed as the dominant gene in the fatty acid plant gene co-expression network. Our study highlights the crucial role of variation in fungal genomes in the trade of resources in this important symbiosis and also opens the door to discovering characteristics of AMF genomes responsible for interactions between AMF and cassava that will lead to optimal cassava growth.

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          Most cited references 35

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          Testing for phylogenetic signal in comparative data: behavioral traits are more labile.

          The primary rationale for the use of phylogenetically based statistical methods is that phylogenetic signal, the tendency for related species to resemble each other, is ubiquitous. Whether this assertion is true for a given trait in a given lineage is an empirical question, but general tools for detecting and quantifying phylogenetic signal are inadequately developed. We present new methods for continuous-valued characters that can be implemented with either phylogenetically independent contrasts or generalized least-squares models. First, a simple randomization procedure allows one to test the null hypothesis of no pattern of similarity among relatives. The test demonstrates correct Type I error rate at a nominal alpha = 0.05 and good power (0.8) for simulated datasets with 20 or more species. Second, we derive a descriptive statistic, K, which allows valid comparisons of the amount of phylogenetic signal across traits and trees. Third, we provide two biologically motivated branch-length transformations, one based on the Ornstein-Uhlenbeck (OU) model of stabilizing selection, the other based on a new model in which character evolution can accelerate or decelerate (ACDC) in rate (e.g., as may occur during or after an adaptive radiation). Maximum likelihood estimation of the OU (d) and ACDC (g) parameters can serve as tests for phylogenetic signal because an estimate of d or g near zero implies that a phylogeny with little hierarchical structure (a star) offers a good fit to the data. Transformations that improve the fit of a tree to comparative data will increase power to detect phylogenetic signal and may also be preferable for further comparative analyses, such as of correlated character evolution. Application of the methods to data from the literature revealed that, for trees with 20 or more species, 92% of traits exhibited significant phylogenetic signal (randomization test), including behavioral and ecological ones that are thought to be relatively evolutionarily malleable (e.g., highly adaptive) and/or subject to relatively strong environmental (nongenetic) effects or high levels of measurement error. Irrespective of sample size, most traits (but not body size, on average) showed less signal than expected given the topology, branch lengths, and a Brownian motion model of evolution (i.e., K was less than one), which may be attributed to adaptation and/or measurement error in the broad sense (including errors in estimates of phenotypes, branch lengths, and topology). Analysis of variance of log K for all 121 traits (from 35 trees) indicated that behavioral traits exhibit lower signal than body size, morphological, life-history, or physiological traits. In addition, physiological traits (corrected for body size) showed less signal than did body size itself. For trees with 20 or more species, the estimated OU (25% of traits) and/or ACDC (40%) transformation parameter differed significantly from both zero and unity, indicating that a hierarchical tree with less (or occasionally more) structure than the original better fit the data and so could be preferred for comparative analyses.
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            Gapped BLAST and PSI‐BLAST: a new generation of protein database search programs

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              A novel class of gibberellin 2-oxidases control semidwarfism, tillering, and root development in rice.

              Gibberellin 2-oxidases (GA2oxs) regulate plant growth by inactivating endogenous bioactive gibberellins (GAs). Two classes of GA2oxs inactivate GAs through 2beta-hydroxylation: a larger class of C(19) GA2oxs and a smaller class of C(20) GA2oxs. In this study, we show that members of the rice (Oryza sativa) GA2ox family are differentially regulated and act in concert or individually to control GA levels during flowering, tillering, and seed germination. Using mutant and transgenic analysis, C(20) GA2oxs were shown to play pleiotropic roles regulating rice growth and architecture. In particular, rice overexpressing these GA2oxs exhibited early and increased tillering and adventitious root growth. GA negatively regulated expression of two transcription factors, O. sativa homeobox 1 and TEOSINTE BRANCHED1, which control meristem initiation and axillary bud outgrowth, respectively, and that in turn inhibited tillering. One of three conserved motifs unique to the C(20) GA2oxs (motif III) was found to be important for activity of these GA2oxs. Moreover, C(20) GA2oxs were found to cause less severe GA-defective phenotypes than C(19) GA2oxs. Our studies demonstrate that improvements in plant architecture, such as semidwarfism, increased root systems and higher tiller numbers, could be induced by overexpression of wild-type or modified C(20) GA2oxs.
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                Author and article information

                Contributors
                ian.sanders@unil.ch
                Journal
                ISME J
                ISME J
                The ISME Journal
                Nature Publishing Group UK (London )
                1751-7362
                1751-7370
                17 February 2020
                17 February 2020
                June 2020
                : 14
                : 6
                : 1333-1344
                Affiliations
                [1 ]ISNI 0000 0001 2165 4204, GRID grid.9851.5, Department of Ecology and Evolution, , University of Lausanne, ; 1015 Lausanne, Switzerland
                [2 ]ISNI 0000000121839049, GRID grid.5333.6, Laboratory for Biological Geochemistry, School of Architecture, Civil and Environmental Engineering, , École Polytechnique Fédérale de Lausanne, ; Lausanne, Switzerland
                [3 ]ISNI 0000 0001 2165 4204, GRID grid.9851.5, Vital-IT Group, Swiss Institute of Bioinformatics, , University of Lausanne, ; 1015 Lausanne, Switzerland
                [4 ]ISNI 0000 0001 0674 042X, GRID grid.5254.6, Department of Plant and Environmental Sciences, , University of Copenhagen, ; 1871 Copenhagen, Denmark
                Article
                606
                10.1038/s41396-020-0606-6
                7242447
                32066875
                © The Author(s) 2020

                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/.

                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation);
                Award ID: 31003A_162549
                Award Recipient :
                Categories
                Article
                Custom metadata
                © International Society for Microbial Ecology 2020

                Microbiology & Virology

                microbial ecology, fungal ecology

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