Biology subjects

Carmichael, A.

Publications and source records attributed to Carmichael, A..

3 recordsLinked to original sources

bioRxiv2023

Legacy effects of precipitation and land use impact maize growth and microbiome assembly under drought stress

Background and AimsAs the climate changes, plants and their associated microbiomes face greater water limitation and increased frequency of drought. Historical environmental patterns can leave a legacy effect on soil and root-associated microbiomes, but the impact of this conditioning on future drought performance is poorly understood. Precipitation gradients provide a means to assess these legacy effects. MethodsWe collected soil microbiomes from four native prairies across a steep precipitation gradient in Kansas, USA. Seedlings of two Zea mays genotypes were inoculated with each soil microbiome in a factorial drought experiment. We investigated plant phenotypic and root microbiome responses to drought and modeled relationships between plant growth metrics and climatic conditions from the soil microbiome origin sites. ResultsDrought caused plants to accumulate shoot mass more slowly and achieve greater root/shoot mass ratios. Drought restructured the bacterial root-associated microbiome via depletion of Pseudomonadota and enrichment of Actinomycetota, whereas the fungal microbiome was largely unaffected. An environmental legacy effect on prairie soil microbiomes influenced plants drought responses: counterintuitively, prairie soil inocula from historically wetter locations increased shoot biomass under drought more than inocula from historically drier prairie soils. ConclusionWe demonstrated links between soil microbiome legacy effects and plant performance under drought, suggesting that future drying climates may condition soils to negatively impact plant performance.

plant biology↗

bioRxiv2023

Reply to Barton et al: signatures of natural selection during the Black Death

Barton et al.1 raise several statistical concerns regarding our original analyses2 that highlight the challenge of inferring natural selection using ancient genomic data. We show here that these concerns have limited impact on our original conclusions. Specifically, we recover the same signature of enrichment for high FST values at the immune loci relative to putatively neutral sites after switching the allele frequency estimation method to a maximum likelihood approach, filtering to only consider known human variants, and down-sampling our data to the same mean coverage across sites. Furthermore, using permutations, we show that the rs2549794 variant near ERAP2 continues to emerge as the strongest candidate for selection (p = 1.2x10-5), falling below the Bonferroni-corrected significance threshold recommended by Barton et al. Importantly, the evidence for selection on ERAP2 is further supported by functional data demonstrating the impact of the ERAP2 genotype on the immune response to Y. pestis and by epidemiological data from an independent group showing that the putatively selected allele during the Black Death protects against severe respiratory infection in contemporary populations.

genomics↗

bioRxiv2022

The rhizodynamics robot: Automated imaging system for studying long-term dynamic root growth

The study of plant root growth in real time has been difficult to achieve in an automated, high-throughput, and systematic fashion. Dynamic imaging of plant roots is important in order to discover novel root growth behaviors and to deepen our understanding of how roots interact with their environments. We designed and implemented the Generating Rhizodynamic Observations Over Time (GROOT) robot, an automated, high-throughput imaging system that enables time-lapse imaging of 90 containers of plants and their roots growing in a clear gel medium over the duration of weeks to months. The system uses low-cost, widely available materials. As a proof of concept, we employed GROOT to collect images of orchid root growth of multiple species over six months. Beyond imaging plant roots, our system is highly customizable and can be used to collect time-lapse image data of different container sizes and configurations regardless of what is being imaged, making it applicable to many fields that require longitudinal time-lapse recording.

plant biology↗