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Recruitment of microorganisms to the rhizosphere varies among plant genotypes, yet an understanding of whether the microbiome can be altered by selection on the host is relatively unknown. Here, we performed a common garden study to characterize recruitment of rhizosphere microbiome, functional groups, for 20 expired Plant Variety Protection Act maize lines spanning a chronosequence of development from 1949 to 1986. This time frame brackets a series of agronomic innovations, namely improvements in breeding and the application of synthetic nitrogenous fertilizers, technologies that define modern industrial agriculture. We assessed the impact of chronological agronomic improvements on recruitment of the rhizosphere microbiome in maize, with emphasis on nitrogen cycling functional groups. In addition, we quantified the microbial genes involved in nitrogen cycling and predicted functional pathways present in the microbiome of each genotype. Both genetic relatednesses of host plant and decade of germplasm development were significant factors in the recruitment of the rhizosphere microbiome. More recently developed germplasm recruited fewer microbial taxa with the genetic capability for sustainable nitrogen provisioning and larger populations of microorganisms that contribute to N losses. This study indicates that the development of high-yielding varieties and agronomic management approaches of industrial agriculture inadvertently modified interactions between maize and its microbiome.
Pubmed ID: 33692487
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Collection of data related to crop plant and model organism Zea mays. Used to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models and to provide support services to the community of maize researchers. Data stored at MaizeGDB was inherited from the MaizeDB and ZmDB projects. Sequence data are from GenBank. Data are searchable by phenotype, traits, Pests, Gel Pattern, and Mutant Images.
View all literature mentionsWeb server to provide germplasm information about plants, animals, microbes, invertebrates and access to databases that maintain passport, characterization, evaluation, inventory, and distribution data for the management and utilization of national germplasm collections. Under control of the U.S. Department of Agriculture's Agricultural Research Service to support the National Genetic Resources Program (NGRP). Operated by the Database Management Unit of the National Germplasm Resource Laboratory in Beltsville, Maryland.
View all literature mentionsIt contains the genotype, phenotype, and polymorphism data produced by the NSF-funded project; Genetic Architecture of Maize and Teosinte. The PANZEA project will identify genes that control domestication traits and three key agronomic traits: flowering time, plant height, and kernel quality. Genetic linkage, association, and fine mapping analyses will be performed on the largest and most diverse set of mapping families publicly available for any species. A large series of isogenic lines will be used to characterize allelic series and epistatic interactions. The genetic architecture of each of the four trait groups will be compared and contrasted, and the influence of recombination and past domestication bottlenecks on the genomic distribution of functional diversity will be examined. Finally, the ability of genetic architecture-based models to predict phenotype will be evaluated in a broad range of germplasm, including elite US hybrids. This project will take a step toward the ultimate goal of predicting phenotype from genotype.
View all literature mentionsFunctional gene pipeline and repository. Functional gene repository provides collections of genes in interactive platform, while functional gene pipeline offers suite of tools for functional gene amplicon processing and analysis. Together they enable key steps in functional gene based microbial community analysis, from target selection and primer analysis to amplicon processing and ecological discovery.
View all literature mentionsHigh quality ribosomal RNA databases providing comprehensive, quality checked and regularly updated datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal RNA (rRNA) sequences for all three domains of life (Bacteria, Archaea and Eukarya). Supplementary services include a rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. 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. Alignment tool, SINA, is available for download as well as available for use online.
View all literature mentionsMetaCyc is a database of nonredundant, experimentally elucidated metabolic pathways. MetaCyc contains more than 1,200 pathways from more than 1,600 different organisms, and is curated from the scientific experimental literature. MetaCyc contains pathways involved in both primary and secondary metabolism, as well as associated compounds, enzymes, and genes.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data, but also supporting analysis of other types of data. QIMME analyzes and transforms raw sequencing data generated on Illumina or other platforms to publication quality graphics and statistics.
View all literature mentionsSoftware package which performs a variety of genetic analyses including association mapping, diversity estimation and calculating linkage disequilibrium. The association analysis between genotypes and phenotypes can be performed by either a general linear model or a mixed linear model. The general linear model now allows users to analyze complex field designs, environmental interactions, and epistatic interactions. The mixed model is specially designed to handle polygenic effects at multiple levels of relatedness including pedigree information. These new analyses should permit association analysis in a wide range plant and animal species. (entry from Genetic Analysis Software)
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