Biology subjects

Earley, A. M.

Publications and source records attributed to Earley, A. M..

3 recordsLinked to original sources

bioRxiv2023

Leaf traits predict performance under varying levels of drought stress in cultivated sunflower (Helianthus annuus L.)

Drought is a major agricultural challenge and is expected to worsen with climate change. Exploring plant traits and how they respond to drought has the potential to improve understanding of drought tolerance and inform breeding efforts to develop more drought tolerant plants. Given their importance in plant-water relations, we explored variation and plasticity in leaf traits in response to water limitation in cultivated sunflower (Helianthus annuus L.). A set of four sunflower genotypes was grown under four different levels of water availability and leaf vein and stomatal traits were measured along with total biomass (as an indicator of performance), leaf mass per area (LMA), chlorophyll content, and various mass fraction traits related to resource allocation (e.g., leaf, root, and stem mass fraction). Traits exhibited numerous bivariate correlations within treatments that generally followed expectations based on the literature. For example, stomatal size and density were negatively correlated while stomatal density and vein length per area (VLA) were positively correlated. Most traits exhibited substantial plasticity, as evidenced by significant shifts in trait values across environments and multivariate analyses revealed differentiation in trait space across treatment levels. This included an overall reduction in growth/productivity in response to stress, accompanied by a shift in traits relating to gas exchange and hydraulics including stomatal and vein density (increased), stomatal size (decreased), and theoretical gsmax (increased). We found that variation in performance across treatments (estimated as total biomass) can be largely explained by a small number of putatively size-independent traits (i.e., VLA, stomatal length and density and LMA; R2 = 0.74). Moreover, on average, more extreme changes in VLA were associated with more extreme decreases in performance across environments. A small number of leaf traits can predict plant performance, with plasticity in VLA being the best predictor of changes in productivity.

plant biology↗

bioRxiv2022

Genomic regions associate with major axes of variation in gas exchange and leaf construction traits in cultivated sunflower (Helianthus annuus L.)

Stomata and leaf veins play an essential role in transpiration and the movement of water throughout leaves. These traits are thus thought to play a key role in the adaptation of plants to drought and a better understanding of the genetic basis of their variation and coordination could inform efforts to improve drought tolerance. Here, we explore patterns of variation and covariation in leaf anatomical traits and analyze their genetic architecture via genome-wide association (GWA) analyses in cultivated sunflower (Helianthus annuus L.). Traits related to stomatal density and morphology as well as lower order veins were manually measured from digital images while the density of minor veins was estimated using a novel deep learning approach. Leaf, stomatal, and vein traits exhibited numerous significant correlations that generally followed expectations based on functional relationships. Correlated suites of traits could further be separated along three major principal component (PC) axes that were heavily influenced by variation in traits related to gas exchange, leaf hydraulics, and leaf construction. While there was limited evidence of colocalization when individual traits were subjected to GWA analyses, major multivariate PC axes that were most strongly influenced by several traits related to gas exchange or leaf construction did exhibit significant genomic associations. These results provide insight into the genetic basis of leaf trait covariation and showcase potential targets for future efforts aimed at modifying leaf anatomical traits in sunflower. Significance StatementUsing traditional and automated/high-throughput (using a novel deep learning approach) phenotyping methods we studied leaf anatomical variation in sunflower. Genome-wide association (GWA) analyses identified numerous genomic regions underlying individual trait variation and regions underlying major multivariate axes of phenotypic variation. These results illustrate the value of employing a multivariate approach to GWA analyses and shed light on the extent to which leaf trait (co-)variation can be genetically decoupled to explore novel phenotypic space.

plant biology↗

bioRxiv2020

Drainage of inflammatory macromolecules from brain to periphery targets the liver for macrophage infiltration

Many brain pathologies are associated with liver damage, but a direct link has long remained elusive. Here, we establish a new paradigm for interrogating brain-periphery interactions by leveraging zebrafish for its unparalleled access to the intact whole animal for in vivo analysis in real time after triggering focal brain inflammation. We reveal that drainage of inflammatory macromolecules from the brain led to a strikingly robust peripheral infiltration of macrophages into the liver independent of Kupffer cells. We further demonstrate that this macrophage recruitment requires signaling from the cytokine IL-34, Toll-like receptor adaptor protein MyD88, and neutrophils. These results highlight the ability for circulation of brain-derived substances to serve as a rapid mode of communication from brain to the liver. Understanding how the brain engages the periphery at times of danger may offer new perspectives for detecting and treating brain pathologies.

immunology↗