Biology subjects

Schachtman, D.

Publications and source records attributed to Schachtman, D..

5 recordsLinked to original sources

bioRxiv2026

Heritability of leaf stable carbon isotope signature in a diversity panel of the C4 plant Sorghum bicolor

A strategy to improve agricultural water productivity is to increase water use efficiency (WUE) at the level of plant transpiration through genetic selection. This requires detectable genetic variability in WUE and the ability to phenotype and select plants with higher WUE within a population. A proxy for phenotyping leaf level WUE by measuring carbon isotope signature ({delta}13Cleaf) has been supported by theory and data in C4 species. However, the functional relationship of {delta}13Cleaf and WUE in C4 species can be driven by genetics and environment. Therefore, a wide survey of existing natural variation is needed to quantify the heritability and identify various genetic factors that influence {delta}13Cleaf and WUE. In this study a genome-wide association panel was used to quantify the heritability of {delta}13Cleaf. We measured {delta}13Cleaf across a population of 360 genetically diverse lines of the C4 species Sorghum bicolor with single nucleotide polymorphic (SNP) markers determined from whole-genome resequencing. This analysis was conducted on two independent field environments where heritability of {delta}13Cleaf was evident and was driven by small genetic effects from loci that were consistently identified across environments. Candidate genes are presented that offer insights on future targets to manipulate and explore the functional relationship between {delta}13Cleaf and WUEi in C4 plants.

plant biology↗

bioRxiv2021

Natural variation in root exudation of GABA and DIMBOA impacts the maize root endosphere and rhizosphere microbiomes

Root exudates are important for shaping root-associated microbiomes. However, studies on a wider range of metabolites in exudates are required for a comprehensive understanding about their influence on microbial communities. We identified maize inbred lines that differ in exudate concentrations of DIMBOA and GABA using a semi-hydroponic system. These lines were grown in the field to determine the changes in microbial diversity and gene expression due to varying concentrations of DIMBOA and GABA in exudates using 16S rRNA amplicon sequencing and metatranscriptomics. Results showed individual and interaction effects of DIMBOA and GABA on the rhizosphere and root endosphere {beta}-diversity, most strongly at the V10 growth stage. The main bacterial families affected by both compounds were Ktedonobacteraceae and Xanthomonadaceae. Higher concentrations of DIMBOA in exudates affected the rhizosphere metatranscriptome, enriching for KEGG pathways associated with plant disease. This study validated the use of natural variation within plant species as a powerful approach for understanding the role of root exudates on microbiome selection. We also showed that a semi-hydroponic system can be used to identify maize genotypes that differ in GABA and DIMBOA exudate concentrations under field conditions. The impact of GABA exudation on root-associated microbiomes was shown for the first time.

microbiology↗

bioRxiv2021

Increased signal to noise ratios within experimental field trials by regressing spatially distributed soil properties as principal components.

Environmental variability poses a major challenge to any field study. Researchers attempt to mitigate this challenge through replication. Thus, the ability to detect experimental signals is determined by the degree of replication and the amount of environmental variation, noise, within the experimental system. A major source of noise in field studies comes from the natural heterogeneity of soil properties which create micro-treatments throughout the field. To make matters worse, the variation within different soil properties is often non-randomly distributed across a field. We explore this challenge through a sorghum field trial dataset with accompanying plant, microbiome and soil property data. Diverse sorghum genotypes and two watering regimes were applied in a split-plot design. We describe a process of identifying, estimating, and controlling for the effects of spatially distributed soil properties on plant traits and microbial communities using minimal degrees of freedom. Importantly, this process provides a tool with which sources of environmental variation in field data can be identified and removed, improving our ability to resolve effects of interest and to quantify subtle phenotypes. IMPORTANCEData from field experiments are notoriously noisy. Proper field designs with high replication aid in mitigating this challenge, yet true biological correlations are still often masked by environmental variability. This work identifies soil property composition as a spatially distributed source of variance to three types of characteristics: plant phenotype, microbiome composition, and leaf traits. We show that once identified, spatial principal component regression was able to account for these effects so that more precise estimates of experimental factors were obtained. This generalizable method is applicable to diverse field experiments.

systems biology↗

bioRxiv2021

Identification of beneficial and detrimental bacteria that impact sorghum responses to drought using multi-scale and multi-system microbiome comparisons

BackgroundDrought is a major abiotic stress that limits agricultural productivity. Previous field-level experiments have demonstrated that drought decreases microbiome diversity in the root and rhizosphere and may lead to enrichment of specific groups of microbes, such as Actinobacteria. How these changes ultimately affect plant health is not well understood. In parallel, model systems have been used to tease apart the specific interactions between plants and single, or small groups of microbes. However, translating this work into crop species and achieving increased crop yields within noisy field settings remains a challenge. Thus, the next scientific leap forward in microbiome research must cross the great lab-to-field divide. Toward this end, we combined reductionist, transitional and ecological approaches, applied to the staple cereal crop sorghum to identify key beneficial and detrimental, root associated microbes that robustly affect drought stressed plant phenotypes. ResultsFifty-three bacterial strains, originally characterized for association with Arabidopsis, were applied to sorghum seeds and their effect on root growth was monitored for seven days. Two Arthrobacter strains, members of the Actinobacteria phylum, caused root growth inhibition (RGI) in Arabidopsis and sorghum. In the context of synthetic communities, strains of Variovorax were able to protect both Arabidopsis and sorghum from the RGI caused by Arthrobacter. As a transitional system, we tested the synthetic communities through a 24-day high-throughput sorghum phenotyping assay and found that during drought stress, plants colonized by Arthrobacter were significantly smaller and had reduced leaf water content as compared to control plants. However, plants colonized by both Arthrobacter and Variovorax performed as well or better than control plants. In parallel, we performed a field trial wherein sorghum was evaluated across well-watered and drought conditions. Drought responsive microbes were identified, including an enrichment in Actinobacteria, consistent with previous findings. By incorporating data on soil properties into the microbiome analysis, we accounted for experimental noise with a newly developed method and were then able to observe that the abundance of Arthrobacter strains negatively correlated with plant growth. Having validated this approach, we cross-referenced datasets from the high-throughput phenotyping and field experiments and report a list of high confidence bacterial taxa that positively associated with plant growth under drought stress. ConclusionsA three-tiered experimental system connected reductionist and ecological approaches and identified beneficial and deleterious bacterial strains for sorghum under drought stress.

microbiology↗

bioRxiv2020

The effects of soil depth on the structure of microbial communities in agricultural soils in Iowa, USA

The determination of how microbial community structure changes within the soil profile, will be beneficial to understanding the long-term health of agricultural soil ecosystems and will provide a first step towards elucidating how deep soil microbial communities contribute to carbon sequestration. This study aimed to investigate the differences in the microbial community abundance, composition and diversity throughout from the surface layers down to deep soils in corn and soybean fields in Iowa, USA. We used 16S rRNA amplicon sequencing of soil samples to characterize the change in microbial community structure. Our results revealed decreased richness and diversity in bacterial community structure with increasing soil depth. We also observed distinct distribution patterns of bacterial community composition along soil profiles. Soil and root data at different depths enabled us to demonstrate that the soil organic matter, soil bulk density and plant water availability were all significant factors in explaining the variation in soil microbial community composition. Our findings provide valuable insights in the changes in microbial community structure to depths of 180 cm in one of the most productive agricultural regions in the world. This knowledge will be important for future management and productivity of agroecosystems in the face of increasing demand for food and climate change.

microbiology↗