Biology subjects

Pariyar, S.

Publications and source records attributed to Pariyar, S..

5 recordsLinked to original sources

bioRxiv2026

Integrated genomic analyses reveal hierarchical organisation of quantitative resistance to biologically distinct soil-borne pathogens in wheat

Quantitative disease resistance is essential for durable crop protection, yet how numerous small-effect loci are organised across genomic and functional scales remains poorly understood. We investigated resistance to four distinct soil-borne pathogens in bread wheat (Triticum aestivum) by integrating genome-wide association mapping, linkage disequilibrium (LD)-defined hotspot analysis, comparative genomics, epistatic network analysis, haplotype analysis, functional annotation, transcriptomics and experimental evaluation. Resistance was highly polygenic and pathogen- and environment-dependent, with associated loci distributed across all three wheat subgenomes. Approximately two-thirds of hotspot components were shared among pathosystems, although evidence for excess sharing varied among comparisons and null models. Epistatic hubs were enriched within shared components, while interaction networks were dominated by interchromosomal and cross-subgenome interactions. Haplotype effects depended on local genomic context. Despite limited sharing of individual genes, convergence increased at the putative gene-family and broader defence-related functional levels. These findings support a hierarchical model in which pathogen- and environment-dependent resistance architectures are organised through partially shared genomic regions, local haplotypes and genetic interaction networks, with increasing convergence at broader functional levels. Limited transferability of individual marker associations in the independent panel further highlights the potential of multilocus breeding strategies that integrate favourable haplotypes, recurrent genomic regions, and diverse resistance mechanisms.

plant biology↗

bioRxiv2023

Fast and efficient root phenotyping via pose estimation

Image segmentation is commonly used to estimate the location and shape of plants and their external structures. Segmentation masks are then used to localize landmarks of interest and compute other geometric features that correspond to the plants phenotype. Despite its prevalence, segmentation-based approaches are laborious (requiring extensive annotation to train), and error-prone (derived geometric features are sensitive to instance mask integrity). Here we present a segmentation-free approach which leverages deep learning-based landmark detection and grouping, also known as pose estimation. We use a tool originally developed for animal motion capture called SLEAP (Social LEAP Estimates Animal Poses) to automate the detection of distinct morphological landmarks on plant roots. Using a gel cylinder imaging system across multiple species, we show that our approach can reliably and efficiently recover root system topology at high accuracy, few annotated samples, and faster speed than segmentation-based approaches. In order to make use of this landmark-based representation for root phenotyping, we developed a Python library (sleap-roots) for trait extraction directly comparable to existing segmentation-based analysis software. We show that landmark-derived root traits are highly accurate and can be used for common downstream tasks including genotype classification and unsupervised trait mapping. Altogether, this work establishes the validity and advantages of pose estimation-based plant phenotyping. To facilitate adoption of this easy-to-use tool and to encourage further development, we make sleap-roots, all training data, models, and trait extraction code available at: https://github.com/talmolab/sleap-roots and https://osf.io/k7j9g/.

plant biology↗

bioRxiv2022

Synergism and phytotoxicity: the effects of tank-mix additives on the biological efficacy of Cu2+ against Venturia inaequalis and Podosphaera leucotricha

The wetting behaviour of the spray and biological efficacy of Cu2+ active ingredients in agrochemical formulations may be enhanced by tank-mix additives. We investigated how three BREAK-THRU(R) additives (BT301: biodegradable, BT133 and BT420: bio-based and biodegradable) as tank-mix with commercial copper preparations influence the spray distribution, leaf uptake and biological efficacy of copper additive mixtures against apple scab and apple powdery mildew under controlled conditions. We quantified the synergetic effects of these additives in foliar applications. In addition, we determined the phytotoxic potential and evaluated impacts on photosynthetic activity, non-photochemical quenching and ROS activity. The additives BT301 and BT420 strongly reduced surface tension and contact angle of copper treatments. The fluorescence observations revealed that BT301 achieved better spreading of copper formulation with more complete coverage of the leaf surface than BT420 and BT133, whereas "coffee-ring" spreading was observed with BT133. The additive BT301 showed an increase in relative fluorescence area, indicating higher ROS production as a signal of intra-cellular tissue activity. The photochemical efficiency of photosystem II (Fv/Fm) was not negatively influenced by copper or additive treatment. Thus, we observed no phytotoxic effects of copper-additive mixtures on apple leaves at treatment doses of 4 g Cu2+ L-1. All copper treatments reduced apple scab infestations significantly, by 53-76%. Interestingly, addition of BT301 to copper preparations showed the strongest biological efficacy (83% reduction) against V. inaequalis, whereas addition of BT420 showed the strongest effect against P. leucotricha (89% infection reduction). The synergetic effects of additives on the biological efficacy without phytotoxic effects on plants may have potential for reducing copper loads in horticultural production systems.

pathology↗

bioRxiv2022

Rational design yields molecular insights on leaf binding of the anchor peptide Macaque Histatin

1In times of a constantly growing world population and increasing demand for food, sustainable agriculture is crucial. To reduce the amount of applied nutrients, herbicides, and fungicides, the rainfastness of plant protection agents is of pivotal importance. As a result of protective agent wash-off, plant protection is lost, and soils and groundwater are severely polluted. To date, rainfastness of plant protection products is achieved by adding polymeric adjuvants to the agrochemicals. However, polymeric adjuvants will be regarded as microplastics in the future, and environmentally friendly alternatives are needed. Anchor peptides (APs) are promising biobased and biodegradable adhesion promoters. While the adhesion of anchor peptides to artificial surfaces, such as polymers, has already been investigated in theory and experimentally, exploiting the adhesion to biological surfaces remains challenging. The complex nature and composition of biological surfaces such as plant leaf and fruit surfaces complicate the generation of accurate models. Here, we present the first detailed three-layered atomistic model of the surface of apple leaves and use it to compute free energy profiles of the adhesion and desorption of APs to and from that surface. Our model is validated by a novel fluorescence-based MTP assay that mimicks these complex processes and allows quantifying them. For the AP Macaque Histatin, we demonstrate that aromatic and positively charged amino acids are essential for binding to the waxy apple leaf surface. The established protocols should generally be applicable for tailoring the binding properties of APs to biological interfaces.

bioengineering↗

bioRxiv2021

Variation in root system architecture among the founder parents of two 8-way MAGIC wheat populations for selection in breeding

Root system architecture (RSA) is a target for breeding because of the interest to develop crops with roots that use nutrients and water more effectively. Breeding for RSA requires phenotypic diversity in populations amenable to QTL identification to provide markers for large breeding programs. This study examined the variation for root traits across the parents of two multi-parent advanced generation inter-cross (MAGIC) wheat populations from NIAB and CSIRO for 16 days in an upgraded version of the non-invasive, germination paper-based phenotyping platform, GrowScreen-PaGe. Across all parents, total root length varied up to 1.90 fold, root biomass 2.25 fold and seminal root angle 1.16 fold. The CSIRO parents grew faster, exhibited slightly wider seminal root angle and produced larger root systems compared to NIAB parents. Lateral root lengths, leaf lengths and biomass contrasted most between fastest (Robigus - NIAB and AC Barrie - CSIRO) and slowest growing parents (Rialto - NIAB and G204 Xiaoyan54 - CSIRO). Lengths of lateral and total root, and leaf number and length had moderate to high heritability (0.30-0.67) and repeatability. Lengths of lateral roots and leaves are good targets for enhancing wheat crop establishment, a critical stage for crop productivity.

plant biology↗