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1.
Environ Microbiome ; 19(1): 64, 2024 Aug 29.
Artículo en Inglés | MEDLINE | ID: mdl-39210412

RESUMEN

BACKGROUND: The composition of the root microbiome affects the host's growth, with variation in the host genome associated with microbiome variation. However, it is not known whether this intra-specific variation of root microbiomes is a consequence of plants performing targeted manipulations of them to adapt to their local environment or varying passively with other traits. To explore the relationship between the genome, environment and microbiome, we sampled seeds from teosinte populations across its native range in Mexico. We then grew teosinte accessions alongside two modern maize lines in a common garden experiment. Metabarcoding was performed using universal bacterial and fungal primers to profile their root microbiomes. RESULTS: The root microbiome varied between the two modern maize lines and the teosinte accessions. We further found that variation of the teosinte genome, the ancestral environment (temperature/elevation) and root microbiome were all correlated. Multiple microbial groups significantly varied in relative abundance with temperature/elevation, with an increased abundance of bacteria associated with cold tolerance found in teosinte accessions taken from high elevations. CONCLUSIONS: Our results suggest that variation in the root microbiome is pre-conditioned by the genome for the local environment (i.e. non-random). Ultimately, these claims would be strengthened by confirming that these differences in the root microbiome impact host phenotype, for example, by confirming that the root microbiomes of high-elevation teosinte populations enhance cold tolerance.

2.
Nat Genet ; 56(6): 1245-1256, 2024 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-38778242

RESUMEN

The maize root system has been reshaped by indirect selection during global adaptation to new agricultural environments. In this study, we characterized the root systems of more than 9,000 global maize accessions and its wild relatives, defining the geographical signature and genomic basis of variation in seminal root number. We demonstrate that seminal root number has increased during maize domestication followed by a decrease in response to limited water availability in locally adapted varieties. By combining environmental and phenotypic association analyses with linkage mapping, we identified genes linking environmental variation and seminal root number. Functional characterization of the transcription factor ZmHb77 and in silico root modeling provides evidence that reshaping root system architecture by reducing the number of seminal roots and promoting lateral root density is beneficial for the resilience of maize seedlings to drought.


Asunto(s)
Adaptación Fisiológica , Domesticación , Sequías , Raíces de Plantas , Plantones , Agua , Zea mays , Zea mays/genética , Zea mays/fisiología , Raíces de Plantas/genética , Raíces de Plantas/crecimiento & desarrollo , Adaptación Fisiológica/genética , Plantones/genética , Agua/metabolismo , Mapeo Cromosómico , Fenotipo , Regulación de la Expresión Génica de las Plantas , Proteínas de Plantas/genética , Factores de Transcripción/genética , Factores de Transcripción/metabolismo
3.
Nat Plants ; 10(4): 598-617, 2024 04.
Artículo en Inglés | MEDLINE | ID: mdl-38514787

RESUMEN

Beneficial interactions with microorganisms are pivotal for crop performance and resilience. However, it remains unclear how heritable the microbiome is with respect to the host plant genotype and to what extent host genetic mechanisms can modulate plant-microbiota interactions in the face of environmental stresses. Here we surveyed 3,168 root and rhizosphere microbiome samples from 129 accessions of locally adapted Zea, sourced from diverse habitats and grown under control and different stress conditions. We quantified stress treatment and host genotype effects on the microbiome. Plant genotype and source environment were predictive of microbiome abundance. Genome-wide association analysis identified host genetic variants linked to both rhizosphere microbiome abundance and source environment. We identified transposon insertions in a candidate gene linked to both the abundance of a keystone bacterium Massilia in our controlled experiments and total soil nitrogen in the source environment. Isolation and controlled inoculation of Massilia alone can contribute to root development, whole-plant biomass production and adaptation to low nitrogen availability. We conclude that locally adapted maize varieties exert patterns of genetic control on their root and rhizosphere microbiomes that follow variation in their home environments, consistent with a role in tolerance to prevailing stress.


Asunto(s)
Microbiota , Raíces de Plantas , Rizosfera , Zea mays , Zea mays/microbiología , Zea mays/genética , Microbiota/genética , Raíces de Plantas/microbiología , Raíces de Plantas/genética , Microbiología del Suelo , Estudio de Asociación del Genoma Completo , Variación Genética , Adaptación Fisiológica/genética , Genotipo
4.
Evol Appl ; 17(3): e13673, 2024 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-38468714

RESUMEN

Mexican native maize (Zea mays ssp. mays) is adapted to a wide range of climatic and edaphic conditions. Here, we focus specifically on the potential role of root anatomical variation in this adaptation. Given the investment required to characterize root anatomy, we present a machine-learning approach using environmental descriptors to project trait variation from a relatively small training panel onto a larger panel of genotyped and georeferenced Mexican maize accessions. The resulting models defined potential biologically relevant clines across a complex environment that we used subsequently for genotype-environment association. We found evidence of systematic variation in maize root anatomy across Mexico, notably a prevalence of trait combinations favoring a reduction in axial hydraulic conductance in varieties sourced from cooler, drier highland areas. We discuss our results in the context of previously described water-banking strategies and present candidate genes that are associated with both root anatomical and environmental variation. Our strategy is a refinement of standard environmental genome-wide association analysis that is applicable whenever a training set of georeferenced phenotypic data is available.

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