Biology subjects

Hanlon, M. T.

Publications and source records attributed to Hanlon, M. T..

6 recordsLinked to original sources

bioRxiv2025

Watering regime affects aboveground and belowground trait covariation in a hybrid Silphium population

Premise of the studyPerennial, herbaceous members of the sunflower family (Asteraceae) can provide valuable agronomic products from aboveground biomass, as well as ecosystem services belowground. Aboveground and belowground trait covariation can be affected by environmental conditions such as the location of available water. Here, we investigated the effects of watering regime on trait covariation in Silphium (Asteraceae), an emerging perennial oilseed crop. MethodsSilphium integrifolium Michx. and S. perfoliatum L. are native North American species adapted to well-drained and moist soils, respectively. Using a backcrossed F1 hybrid S. integrifolium x S. perfoliatum population, we conducted a greenhouse experiment where plants were either watered at the soil line ("top-watered") or from below using watering trays ("bottom-watered"). Aboveground biomass, root distribution, and root morphology (e.g., specific root length) were measured destructively. Key resultsCompared to top-watered plants, bottom-watered plants were smaller aboveground and belowground, with a higher proportion of roots in the upper portions of the pots and higher specific root length. Negative relationships between aboveground biomass and specific root length were steeper for bottom-watered than top-watered plants. ConclusionsThe location of available water impacts aboveground biomass, the distribution and morphology of the root system, and relationships between aboveground and belowground plant structures. This work suggests that resource allocation depends in part on the location of available water, and has relevance for ongoing efforts aimed at developing perennial, herbaceous species that offer both economically viable products as well as ecosystem services.

plant biology↗

bioRxiv2025

The Rapid Anatomics Tool (RAT): A low-cost root anatomical phenotyping pipeline reveals changes in root anatomy along the root axis

Root anatomical phenotyping has become a demonstrably essential part of investigating root physiology and in acquiring a holistic understanding of plant development. However, accessible high throughput methods for root anatomical analysis are still lacking. Here, we present the Rapid Anatomics Tool (RAT), a novel, low-cost system for high throughput root anatomical imaging with a shallow learning curve for obtaining high quality images suitable for comparative analysis across a number of plant species. Its efficiency comes from combining blockface-like imaging and stain-free imaging using near-ultraviolet (nUV) autofluorescence utilising a combination of low-cost commercial equipment, readily available mechanical components, and custom designed and 3D printed tools. Using this system, we investigated the anatomy of mature tissue along the axis of wheat crown roots, revealing a tendency of reduction in vascular complexity (expressed through a reduction in metaxylem number, area, and mean area per metaxylem file) from the basal to the distal region of the root. This study highlights the importance of thorough sampling strategies for investigating root anatomy in relation to organ function and introduces an accessible, relatively high-throughput method to support such research.

plant biology↗

bioRxiv2025

A leaf phenomics approach to estimating below-ground traits in North American Licorice

Premise of the studyThousands of years of selective breeding has prioritized above-ground yield, with little regard for changes happening below-ground. Despite their central role in plant success and resilience, our knowledge of roots lags behind above-ground structures. Accurately phenotyping root traits is often labor-intensive, expensive, and destructive. In order to advance understanding of the fundamental biology underlying root systems, and to integrate hard-to-measure root traits into breeding programs, high-throughput non-destructive methods are required. MethodsThis study uses American licorice (Glycyrrhiza lepidota Pursh.), a perennial legume with a rich ethnobotanical history, as a model to investigate root system phenotypes. We assess root traits across multiple populations, analyze relationships between above- and below-ground phenotypes, and test the use of multidimensional leaf traits, including spectral reflectance, in predicting root traits. Key resultsAmerican licorice displays significant variation in root traits across source populations and strong correlations between above- and below-ground traits. Leaf spectral reflectance and elemental composition show promise in modeling below-ground traits, though the isometric relationship between plant size and root traits complicates model accuracy. ConclusionsThese findings demonstrate the use of high-dimensional leaf traits as a proxy for root traits, with potential applications for understanding foundational questions in plant biology and in breeding programs targeting the below-ground structures of perennial herbaceous species. Further optimization and larger studies are needed to improve predictive models.

plant biology↗

bioRxiv2023

LEADER (Leaf Element Accumulation from Deep Roots): a nondestructive phenotyping platform to estimate rooting depth in the field

Deeper rooted crops are an avenue to increase plant water and nitrogen uptake under limiting conditions and increase long-term soil carbon storage. Measuring rooting depth, however, is challenging due to the destructive, laborious, or imprecise methods that are currently available. Here, we present LEADER (Leaf Element Accumulation from DEep Roots) as a method to estimate in-field root depth of maize plants. We use both X-Ray fluorescence spectroscopy (XRF) and ICP-OES (Inductively Coupled Plasma Optical Emission spectroscopy) to measure leaf elemental content and relate this to metrics of root depth. Principal components of leaf elemental content correlate with measures of root length in four genotypes (R2= 0.8 for total root length), and we use linear discriminant analysis to classify plants as having different metrics related to root depth across four field sites in the United States. We can correctly classify the plots with the longest root length at depth with high accuracy (accuracy greater than 0.6) at two of our field sites (Hancock, WI and Rock Spring, PA). We also use strontium (Sr) as a tracer element in both greenhouse and field studies, showing that elemental accumulation of Sr in leaf tissue can be measured with XRF and can estimate root depth. We propose the adoption of LEADER as a tool for measuring root depth in different plant species and soils. LEADER is faster and easier than any other methods that currently exist and could allow for extensive study and understanding of deep rooting.

plant biology↗

bioRxiv2023

Genomic regions and candidate genes affect root anatomical traits in diverse rice accessions

Root anatomical traits show significant variation among rice, Oryza sativa L., genotypes and are of interest for improving adaptation to a variety of edaphic, hydrological and nutritional environments in which rice is grown. However, they are difficult to measure and the genetic controls of these traits are not well understood in rice. We conducted genome-wide association (GWA) analyses using moderate- and high-density SNP panels on a diverse rice population to identify genomic regions and candidate genes that control root anatomical traits. We identified 28 genomic regions for metaxylem vessel area and number, root cross-sectional area, stele area, and aerenchyma area. One genomic region associated with metaxylem vessel number and two regions associated with three root thickness-related traits, stele area, root cross-sectional area and metaxylem vessel area, were supported by chromosome-specific GWA using a high-density SNP panel and are regarded as highly significant regions controlling trait variation. Candidate genes in these regions were related to cell differentiation, elongation and division, and secondary cell wall formation. For genomic regions identified in the indica subpopulation, haplotype variation and root anatomical phenotypes were associated with geographic distributions of the accessions, notably the presence of alternate alleles conferring larger diameter roots, stele, and metaxylem vessels in accessions from the indica 2 and indica 3 subgroups originating largely in south and southeast Asia. The identification of genomic regions and candidate genes related to root anatomical traits in a diverse panel of rice varieties deepens our understanding of trait variation and genetic architecture and facilitates the incorporation of favorable alleles into breeding populations. Key message Genomic regions and candidate genes associated with root anatomical traits were identified in Oryza sativa using genome-wide association analyses.

plant biology↗

bioRxiv2020

DIRT/3D: 3D phenotyping for maize (Zea mays) root architecture in the field

The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture, to reduce fertilizer inputs and, to increase carbon sequestration from the atmosphere to improve soil organic fertility. A major bottleneck to achieving these improvements is high-throughput phenotyping to quantify root phenotypes of field-grown roots. We address this bottleneck with DIRT/3D, a newly developed image-based 3D root phenotyping platform, which measures 18 architecture traits from mature field-grown maize root crowns excavated with the Shovelomics technique. DIRT/3D reliably computed all 18 traits, including distance between whorls and the number, angles, and diameters of nodal roots, on a test panel of 12 contrasting maize genotypes. The computed results were validated through comparison with manual measurements. Overall, we observed a coefficient of determination of r2>0.84 and a high broad-sense heritability of [Formula] for all but one trait. The average values of the 18 traits and a newly developed descriptor to characterize a complete root architecture distinguished all genotypes. DIRT/3D is a step towards automated quantification of highly occluded maize root crowns. Therefore, DIRT/3D supports breeders and root biologists in improving carbon sequestration and food security in the face of the adverse effects of climate change.

plant biology↗