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      Soil Metagenomics Reveals Effects of Continuous Sugarcane Cropping on the Structure and Functional Pathway of Rhizospheric Microbial Community


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          The continuous cropping of plants can result in the disruption of the soil microbial community and caused significant declines in yields. However, there are few reports on the effects of continuous cropping of sugarcane on the microbial community structure and functional pathway. In the current study, we analyzed the structural and functional changes of microbial community structure in the rhizospheric soil of sugarcane in different continuous cropping years using Illumina Miseq high-throughput sequencing and metagenomics analysis. We collected rhizosphere soils from fields of no continuous cropping history (NCC), 10 years of continuous cropping (CC10), and 30 years of continuous cropping (CC30) periods in the Fujian province. The results demonstrated that continuous sugarcane cropping resulted in significant changes in the physicochemical properties of soil and the composition of soil bacterial and fungal communities. With the continuous cropping, the crop yield dramatically declined from NCC to CC30. Besides, the redundancy analysis (RDA) of the dominant bacterial and fungal phyla and soil physicochemical properties revealed that the structures of the bacterial and fungal communities were mainly driven by pH and TS. Analysis of potential functional pathways during the continuous cropping suggests that different KEGG pathways were enriched in different continuous cropping periods. The significant reduction of bacteria associated with rhizospheric soil nitrogen and sulfur cycling functions and enrichment of pathogenic bacteria may be responsible for the reduction of effective nitrogen and total sulfur content in rhizospheric soil of continuous sugarcane as well as the reduction of sugarcane yield and sugar content. Additionally, genes related to nitrogen and sulfur cycling were identified in our study, and the decreased abundance of nitrogen translocation genes and AprAB and DsrAB in the dissimilatory sulfate reduction pathway could be the cause of declined biomass. The findings of this study may provide a theoretical basis for uncovering the mechanism of obstacles in continuous sugarcane cropping and provide better guidance for sustainable development of the sugarcane.

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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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            Metagenomic biomarker discovery and explanation

            This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.
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              UniFrac: a new phylogenetic method for comparing microbial communities.

              We introduce here a new method for computing differences between microbial communities based on phylogenetic information. This method, UniFrac, measures the phylogenetic distance between sets of taxa in a phylogenetic tree as the fraction of the branch length of the tree that leads to descendants from either one environment or the other, but not both. UniFrac can be used to determine whether communities are significantly different, to compare many communities simultaneously using clustering and ordination techniques, and to measure the relative contributions of different factors, such as chemistry and geography, to similarities between samples. We demonstrate the utility of UniFrac by applying it to published 16S rRNA gene libraries from cultured isolates and environmental clones of bacteria in marine sediment, water, and ice. Our results reveal that (i) cultured isolates from ice, water, and sediment resemble each other and environmental clone sequences from sea ice, but not environmental clone sequences from sediment and water; (ii) the geographical location does not correlate strongly with bacterial community differences in ice and sediment from the Arctic and Antarctic; and (iii) bacterial communities differ between terrestrially impacted seawater (whether polar or temperate) and warm oligotrophic seawater, whereas those in individual seawater samples are not more similar to each other than to those in sediment or ice samples. These results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.

                Author and article information

                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                05 March 2021
                : 12
                : 627569
                [1] 1Key Laboratory of Sugarcane Biology and Genetic Breeding, Ministry of Agriculture, Fujian Agriculture and Forestry University , Fuzhou, China
                [2] 2College of Agricultural, Fujian Agriculture and Forestry University , Fuzhou, China
                [3] 3Province and Ministry Co-sponsored Collaborative Innovation Center of Sugar Industry , Nanning, China
                [4] 4College of Life Sciences, Fujian Agriculture and Forestry University , Fuzhou, China
                [5] 5Center for Genomics and Biotechnology, Fujian Agriculture and Forestry University , Fuzhou, China
                Author notes

                Edited by: Siu Mui Tsai, University of São Paulo, Brazil

                Reviewed by: Thiago Gumiere, Laval University, Canada; Acacio Aparecido Navarrete, Federal University of Mato Grosso do Sul, Brazil

                *Correspondence: Zhaonian Yuan, yuanzn05@ 123456163.com

                These authors have contributed equally to this work

                This article was submitted to Terrestrial Microbiology, a section of the journal Frontiers in Microbiology

                Copyright © 2021 Pang, Dong, Liu, Lin, Hu and Yuan.

                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.

                : 09 November 2020
                : 08 February 2021
                Page count
                Figures: 10, Tables: 0, Equations: 0, References: 90, Pages: 19, Words: 0
                Original Research

                Microbiology & Virology
                sugarcane,continuous cropping,rhizosphere soil,metagenome,community structure,bacterial and fungal communities,functional genes


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