Biology subjects

van Doorn, A.

Publications and source records attributed to van Doorn, A..

5 recordsLinked to original sources

bioRxiv2026

Repeatability and Heritability of UAV-Derived Canopy Traits in a Cassava Breeding Population Using Time-Series Data from Two Consecutive Growing Seasons

Cassava is a major staple crop in tropical regions, particularly in Sub-Saharan Africa, yet its productivity remains constrained by genetic and agronomic limitations. A major bottleneck in cassava breeding is the difficulty of accurately phenotyping agronomic traits under field conditions using conventional, labor-intensive methods. Here, we evaluated the potential of uncrewed aerial vehicle (UAV)-based phenotyping to quantify canopy growth traits and assess their genetic relevance under realistic field conditions. For this, multi-temporal UAV imagery was collected over two growing seasons (2018-2019 and 2019-2020) in a panel of 46 cassava genotypes planted in fields of the International Institute for Tropical Agriculture (IITA), Nigeria. Canopy height, canopy volume, and their relative growth rates (RGRh and RGRv) were extracted at the plot-level, and their seasonal dynamics and canopy-yield relationships were further assessed across developmental stages and environmental conditions. Repeatability (R) and broad-sense heritability (H2) were estimated using a linear mixed model (LMM) that partitioned genetic, genotype-by-year, and residual variance components, enabling the evaluation of both measurement reliability and genetic signal. Overall, UAV-derived growth dynamics were found to exhibit comparable patterns across genotypes, reflecting shared seasonal growth trajectories, while canopy-yield relationships varied with developmental stage and environmental conditions. In terms of genetic metrics, R was high for all UAV-derived traits (R = 0.68-0.69), indicating reliable genotype-level assessment across replicates and seasons. In contrast, H2 differed substantially among traits. Canopy volume (H2 = 0.64) and canopy height (H2 = 0.58) exhibited moderate-to-high heritability, reflecting strong genotype effects and comparatively moderate genotype-by-year interactions. However, their relative growth rates showed near-zero H2 values, driven primarily by genotype-by-year interaction, indicating a dominant environmental influence. These results demonstrate that UAV-derived canopy height and volume provide a consistent basis for genetic differentiation of cassava genotypes across environments, supporting their use in selection, whereas growth-rate traits are better suited for characterizing growth plasticity and genotype-by-environment interactions.

plant biology↗

bioRxiv2026

An empirical three-dimensional metric field for color space

A complete empirical characterization of color discrimination in three dimensions has long remained out of reach. Classical studies, beginning with MacAdams ellipses, provided local measurements in restricted chromatic planes, but a spatially dense and internally consistent mapping of discrimination structure across full color space has not yet been achieved. Here we present such a systematic three-dimensional measurement of color discrimination in the standardized sRGB stimulus space. Eight observers measured discrimination regions at 35 reference colors distributed on a body-centered cubic lattice within the RGB cube. At each location, color differences were probed along seven orientations, yielding 14 directional extents. These measurements defined centrally symmetric convex regions that were fitted with minimum-volume ellipsoids, providing a compact description of local discrimination structure. Ellipsoids were represented as symmetric positive-definite matrices and analyzed using a Frobenius geometry, enabling normalization across observers and smooth interpolation to arbitrary locations. The resulting metric field is spatially smooth, highly structured, and remarkably consistent across observers up to an individual global scale factor. Grain size increases along the achromatic axis and exhibits systematic chromatic asymmetries. Comparison with CIEDE2000 reveals substantial agreement in overall scale variation but systematic differences in local anisotropy. Because the metric field is defined geometrically, it can be transformed into linear RGB or any other color representation through the corresponding coordinate transformations. Together, these data provide a coherent three-dimensional empirical mapping of color discrimination across a large ecologically relevant volume of color space and establish an empirical framework for perceptual color metrics.

neuroscience↗

bioRxiv2023

Carbon usage in yellow-fleshed Manihot esculenta storage roots shifts from starch biosynthesis to cell wall and raffinose biosynthesis via the myo-inositol pathway

Cassava is a crucial staple crop for smallholder farmers in tropical Asia and Sub-Saharan Africa. Although high yield remains the top priority for farmers, the significance of nutritional values has increased in cassava breeding programs. A notable negative correlation between provitamin A and starch accumulation poses a significant challenge for breeding efforts. The negative correlation between starch and carotenoid levels in conventional and genetically modified cassava plants implies the absence of a direct genomic connection between the two traits. The competition among various carbon pathways seems to account for this relationship. In this study, we conducted a thorough analysis of 49 African cassava genotypes with varying levels of starch and provitamin A. Our goal was to identify factors contributing to differential starch accumulation. With the carotenoid levels of the varieties considered as a confounding effect on starch production, we found that yellow and white-fleshed storage roots did not differ significantly in most measured components of starch or de novo fatty acid biosynthesis. However, genes and metabolites associated with myo-inositol synthesis and cell wall component production were substantially enriched in high provitamin A genotypes. These results indicate that yellow-fleshed cultivars, in comparison to their white-fleshed counterparts, direct more carbon towards the synthesis of raffinose and cell wall components, a finding that is supported by a significant rise in the starch-free residue to total dry yield ratio in yellow storage roots versus white storage roots. Our findings enhance comprehension of the biosynthesis of starch and carotenoids in the storage roots of cassava.

plant biology↗

bioRxiv2021

Measuring host immune response status by simultaneous quantitative measurement of activity of signal transduction pathways that coordinate functional activity of immune cells from innate and adaptive immune system

For many diseases, including cancer, viral infections such as COVID-19, bacterial infections, and auto-immune diseases, the immune response is a major determinant of progression, response to therapy, and clinical outcome. Innate and adaptive immune response are controlled by coordinated activity of multiple immune cell types. The functional activity state of immune cells is determined by cellular signal transduction pathways (STPs). A novel mRNA-based signaling pathway assay platform has been developed to quantitatively measure relevant STP activities in all types of immune cells and mixed immune cell samples for experimental and diagnostic purposes. We generated a STP activity profile, termed Immune-Pathway Activity Profile (I-PAP), for a variety of immune cell types in resting and activated state, and provide a first example for use in patient samples. MethodsThe technology to measure STP activity has been described for androgen and estrogen receptor, PI3K, MAPK, TGF{beta}, Notch, NF{kappa}B, JAK-STAT1/2, and JAK-STAT3 pathways. STP activity was measured on Affymetrix expression microarray data from preclinical studies containing public data from different types of immune cells, resting/naive or immune-activated in vitro, to establish I-PAPs. Subsequently data from a clinical study on rheumatoid arthritis were analyzed. ResultsI-PAPs of naive/resting and immune-activated CD4+ and CD8+ T cells, T helper cells, B cells, NK cells, monocytes, macrophages, and dendritic cells were established and in agreement with known experimental immunobiology. In whole blood samples of rheumatoid arthritis patients TGF{beta} pathway activity was increased; JAK-STAT3 pathway activity was selectively increased in female patients. In naive CD4+ Tregs TGF{beta} pathway activity was increased, while in memory T effector cells JAK-STAT3 pathway activity tended to increase, suggesting that these immune cell types contributed to whole blood analysis results. ConclusionSTP assay technology (currently being converted to qPCR-based assays) makes it possible to directly measure functional activity of cells of the innate and adaptive immune response enabling quantitative assessment of the immune response of an individual patient. Envisioned utility lies in (1) prediction and monitoring of response to immunomodulatory treatments for a variety of immune-mediated diseases, including RA; (2) uncovering novel treatment targets; (3) improvement and standardization of in vitro immunology research and drug development.

immunology↗

bioRxiv2020

Characterization of immunoactive and immunotolerant CD4+ T cells in breast cancer by measuring activity of signaling pathways that determine immune cell function

Cancer immunotolerance can be reversed by checkpoint blockade immunotherapy in some patients, but response prediction remains a challenge. CD4+ T cells play an important role in activating adaptive immune responses against cancer. Conversion to an immune suppressive state impairs the anti-cancer immune response and is mainly effected by CD4+ Treg cells. A number of signal transduction pathways activate and control functions of CD4+ T cell subsets. As previously described, assays have been developed which enable quantitative measurement of the activity of signal transduction pathways (e.g. TGF{beta}, NF{kappa}B, PI3K-FOXO, JAK-STAT1/2, JAK-STAT3, Notch) in a cell or tissue sample. Using these assays, pathway activity profiles for various CD4+ T cell subsets were defined and cellular mechanisms underlying breast cancer-induced immunotolerance investigated in vitro. Results were used to measure the immune response state in a clinical breast cancer study. MethodsSignal transduction pathway activity scores were measured on Affymetrix expression microarray data of resting and immune-activated CD4+ T cells, immune-activated CD4+ T cells incubated with breast cancer tissue supernatants, CD4+ Th1, Th2, and Treg cells, and of clinical study samples in which CD4+ T cells were derived from blood, lymph node and cancer tissue from primary breast cancer patients (n=10). ResultsIn vitro CD4+ T cell activation induced PI3K, NF{kappa}B, JAK-STAT1/2, and JAK-STAT3 pathway activity. Simultaneous incubation with primary cancer supernatant reduced PI3K and NF{kappa}B, and partly reduced JAK-STAT3, pathway activity, while simultaneously increasing TGF{beta} pathway activity; characteristic of an immune tolerant state. CD4+ Th1, Th2, and Treg cells all had a specific pathway activity profile, with activated immune suppressive Treg cells characterized by high NF{kappa}B, JAK-STAT3, TGF{beta}, and Notch pathway activity scores. An immune tolerant pathway profile was identified in CD4+ T cells from tumor infiltrate of a subset of primary breast cancer patients which could be contributed to activated Treg cells. A Treg pathway profile was also identified in blood samples. ConclusionSignaling pathway assays can be used to quantitatively measure the functional immune response state of lymphocyte subsets in vitro and in vivo. Clinical results suggest that in primary breast cancer the adaptive immune response of CD4+ T cells has frequently been replaced by immunosuppressive Treg cells, potentially causing resistance to checkpoint inhibition. In vitro study results suggest that this effect is mediated by soluble factors from cancer tissue (e.g. TGF{beta}). Signaling pathway activity analysis on TIL and/or blood samples is expected to improve predicting and monitoring response to checkpoint inhibitor immunotherapy.

cancer biology↗