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      Biogeography and diversity patterns of abundant and rare bacterial communities in paddy soils along middle and lower Yangtze River

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          Abstract

          The middle and lower reaches of the Yangtze River serve as principal rice production bases in China, yet the biodiversity and ecological processes of bacterial communities in paddy soils are not well understood. This study explores the diversity, composition, ecological function, and assembly processes of abundant and rare bacterial communities in paddy soils. A total of 129 paddy soil samples from 43 sites along the middle and lower reaches of the Yangtze River were collected and analyzed using NovaSeq sequencing. The results showed that the dominant phylum for both abundant and rare taxa was Proteobacteria, with a greater relative abundance of the abundant taxa. The diversity of the abundant community was lower than that of the rare community. Soil properties and geographic variables explained more of the variation in the abundant community than in the rare community. The rare community exhibited a significant distance‐decay relationship. The assembly of the abundant community was more influenced by stochastic processes, although both the abundant and rare communities were governed by stochastic processes. It is concluded that both abundant and rare bacterial communities exhibit differing biogeographic patterns, yet they undergo similar ecological processes in the paddy soils along the middle and lower reaches of the Yangtze River. These observations offer a theoretical framework for a deeper comprehension of the function of both abundant and rare bacteria, as well as the development and preservation of soil bacterial diversity within agricultural ecosystems.

          Abstract

          Abundant and rare bacterial communities exhibited differing biogeographic patterns, and Proteobacteria was the dominant phylum for both abundant and rare taxa in the paddy soils along the middle and lower of the Yangtze River. The assembly of the abundant community was more influenced by stochastic processes, although both the abundant and rare communities were governed by stochastic processes.

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          We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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            Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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              Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

              Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community’s functional capabilities. Here we describe PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this ‘predictive metagenomic’ approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.
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                Author and article information

                Contributors
                zhuxiancan@ahnu.edu.cn
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                04 June 2024
                June 2024
                : 14
                : 6 ( doiID: 10.1002/ece3.v14.6 )
                : e11481
                Affiliations
                [ 1 ] Collaborative Innovation Center of Recovery and Reconstruction of Degraded Ecosystem in Wanjiang Basin Co‐Founded by Anhui Province and Ministry of Education Anhui Normal University Wuhu China
                [ 2 ] Anhui Provincial Key Laboratory of Molecular Enzymology and Mechanism of Major Metabolic Diseases, College of Life Sciences Anhui Normal University Wuhu China
                Author notes
                [*] [* ] Correspondence

                Xiancan Zhu, Anhui Provincial Key Laboratory of Molecular Enzymology and Mechanism of Major Metabolic Diseases, College of Life Sciences, Anhui Normal University, No 1 Beijingdong Road, Wuhu 241000, China.

                Email: zhuxiancan@ 123456ahnu.edu.cn

                Author information
                https://orcid.org/0000-0001-9855-683X
                Article
                ECE311481 ECE-2023-12-02254.R1
                10.1002/ece3.11481
                11148396
                38835524
                6dbe4be1-0d97-42fe-8b93-73e8221a69bb
                © 2024 The Author(s). Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 30 April 2024
                : 01 January 2024
                : 13 May 2024
                Page count
                Figures: 8, Tables: 0, Pages: 11, Words: 7000
                Funding
                Funded by: Outstanding Innovative Research Team for Molecular Enzymology and Detection in Anhui Provincial Universities
                Award ID: 2022AH010012
                Funded by: Anhui Natural Science Foundation
                Award ID: 2108085QC134
                Funded by: Wuhu City Science and Technology Project
                Award ID: 2023yf074
                Categories
                Agroecology
                Research Article
                Research Articles
                Custom metadata
                2.0
                June 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.4 mode:remove_FC converted:04.06.2024

                Evolutionary Biology
                agricultural ecosystem,biogeography,ecological processes,microbial community,rice field,soil bacterial diversity

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