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Kerdaffrec, E.

Publications and source records attributed to Kerdaffrec, E..

3 recordsLinked to original sources

Plant genes influence microbial hubs that shape beneficial leaf communities

Although complex interactions between hosts and microbial associates are increasingly well documented, we still know little about how and why hosts shape microbial communities in nature. In addition, host genetic effects on microbial communities vary widely depending on the environment, obscuring conclusions about which microbes are impacted and which plant functions are important. We characterized the leaf microbiota of 200 A. thaliana genotypes in eight field experiments and detected consistent host effects on specific, broadly distributed microbial OTUs. Host genetics disproportionately influenced hubs within the microbial communities, with their impact then percolating through the community, as evidenced by a decline in the heritability of particular OTUs with their distance to the nearest hub. By simultaneously measuring host performance, we found that host genetics associated with microbial hubs explained over 10% of the variation in lifetime seed production among host genotypes across sites and years. We successfully cultured one of these microbial hubs and demonstrated its growth-promoting effects on plants grown in sterile conditions. Finally, genome-wide association mapping identified many putatively causal genes with small effects on the relative abundance of microbial hubs across sites and years, and these genes were enriched for those involved in the synthesis of specialized metabolites, auxins and the immune system. Using untargeted metabolomics, we corroborate the consistent association of variation in specialized metabolites and microbial hubs across field sites. Together, our results reveal that host natural variation impacts the microbial communities in consistent ways across environments and that these effects contribute to fitness variation among host genotypes.

microbiology

The Maternal Environment Interacts With Genetic Variation In Regulating Seed Dormancy In Arabidopsis thaliana

Seed dormancy is a complex adaptive trait that controls the timing of seed germination, one of the major fitness components in many plant species. Despite being highly heritable, seed dormancy is extremely plastic and influenced by a wide range of environmental cues. Here, using a set of 92 Arabidopsis thaliana lines from Sweden, we investigate the effect of seed maturation temperature on dormancy variation at the population level. The response to temperature differs dramatically between lines, demonstrating that genotype and the maternal environment interact in controlling the trait. By performing a genome-wide association study (GWAS), we identified several candidate genes that could account for this plasticity, two of which are involved in the photoinduction of germination. Altogether, our results provide insight into both the molecular mechanisms and the evolution of dormancy plasticity, and can serve to improve our understanding of environmentally dependent life-history transitions.\n\nHighlightThe effect of low seed-maturation temperatures on seed dormancy is highly variable in Arabidopsis thaliana accessions from Sweden, denoting strong genotype-environment interactions, and a genome-wide association study identified compelling candidates that could account for this plasticity.

plant biology

Verification of Arabidopsis stock collections using SNPmatch - an algorithm for genotyping high-plexed samples

Large-scale studies such as the Arabidopsis thaliana 1001 Genomes Project aim to understand genetic variation in populations and link it to phenotypic variation. Such studies require routine genotyping of stocks to avoid sample contamination and mix-ups. To genotype samples efficiently and economically, sequencing must be inexpensive and data processing simple. Here we present SNPmatch, a tool which identifies the most likely strain (inbred line, or \"accession\") from a SNP database. We tested the tool by performing low-coverage sequencing of over 2000 strains. SNPmatch could readily genotype samples correctly from 1-fold coverage sequencing data, and could also identify the parents of F1 or F2 individuals. SNPmatch can be run either on the command line or through AraGeno (https://arageno.gmi.oeaw.ac.at), a web interface that permits sample genotyping from a user-uploaded VCF or BED file.\n\nAvailability and implementation: https://github.com/Gregor-Mendel-Institute/SNPmatch.git

genomics