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      Differential Response of Soil Microbial Diversity and Community Composition Influenced by Cover Crops and Fertilizer Treatments in a Dryland Soybean Production System

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      Agronomy
      MDPI AG

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          Abstract

          The response of soil microbial communities to management practices is composite, as it depends on the various environmental factors which contribute to a shift in the microbial communities. In this study we explored the impact of combinations of soil management practices on microbial diversity and community composition in a dryland soybean production system. Soil samples were collected from the experimental field maintained under no till, cover crops, and fertility treatments, at Pontotoc Ridge-Flatwoods Branch Experiment Station, MS, USA. Targeted amplicon sequencing of 16S rRNA and ITS2 genes was used to study the bacterial and fungal community composition. Poultry litter amendment and cover crops significantly influenced soil bacterial diversity. Fertilizer sources had significantly different bacterial communities, as specific microbial taxa were strongly influenced by the changes in the nutrient availability, while cover crops influenced the soil fungal community differences. Differential enrichment of advantageous bacterial (Proteobacteria, Actinobacteria and Acidobacteria) and fungal (Mortierellomycota) phyla was observed across the treatments. Soil pH and easily extractable glomalin-related soil proteins (EE-GRSP) were correlated with bacterial communities and aggregate stability (WSA) was influenced by the poultry litter amendment, thus driving the differences in bacterial and fungal communities. These findings suggest that a long-term study would provide more inferences on soil microbial community response to management changes in these dryland soybean production systems.

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          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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            Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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              Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample.

              The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                ABSGGL
                Agronomy
                Agronomy
                MDPI AG
                2073-4395
                March 2022
                March 01 2022
                : 12
                : 3
                : 618
                Article
                10.3390/agronomy12030618
                3837d0ca-a797-411b-934d-27b85a0cf65c
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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