Inaba, J. | Search bioRxiv

bioRxiv2025

Integration of Proxy Intermediate Omics traits into a Nonlinear Two-Step model for accurate phenotypic prediction

Intermediate omics traits, which mediate the effects of genetic variation on phenotypic traits, are increasingly recognised as valuable components of genetic evaluation. In particular, rhizosphere microbiota play a crucial role in plant health and productivity; however, their complex interactions with host genetics remain challenging to model. Although two-step modeling frameworks have been proposed to integrate intermediate omics traits into phenotype prediction, existing approaches do not incorporate nonlinear relationships between different omics layers. To address this, we have proposed a two-step phenotype prediction framework that integrates genomic, rhizosphere microbiome, and metabolome (meta-metabolome) data, while explicitly capturing omicsomics nonlinearities. The first step is to predict meta-metabolome traits from genetic and microbial features, thus effectively isolating them from the environmental noise. In this process, intermediate "proxy" omics traits are generated as general biological information to provide robust models. The second step utilises this "proxy" to enhance the accuracy of the phenotype prediction. We compared the linear model (Best Linear Unbiased Prediction, BLUP) and the nonlinear model (Random Forest, RF) at each step, as demonstrated through simulations and empirical analysis of a multi-omics soybean dataset in which nonlinear modeling captures intricate omics interactions. Notably, our approach enables phenotype prediction without requiring the original meta-metabolome data used in model training, thereby reducing reliance on costly omics measurements. This framework integrates intermediate omics traits into genomic prediction to improve prediction accuracy and provide solutions for deeper insights into plant-microbiome interactions.

bioinformatics↗

bioRxiv2019

Excessive assimilation of ammonium by plastidic glutamine synthetase is a major cause of ammonium toxicity in Arabidopsis thaliana

Plants use nitrate and ammonium in the soil as their main nitrogen sources. Recently, ammonium has attracted attention due to evidence suggesting that, in C3 species, an elevated CO2 environment inhibits nitrate assimilation. However, high concentrations of ammonium as the sole nitrogen source for plants causes impaired growth, i.e. ammonium toxicity. Although ammonium toxicity has been studied for a long time, the primary cause remains to be elucidated. Here, we show that ammonium assimilation in plastids rather than ammonium accumulation is a primary cause for toxicity. Our genetic screen of ammonium-tolerant Arabidopsis lines with enhanced shoot growth identified plastidic GLUTAMINE SYNTHETASE 2 (GLN2) as the causal gene. Our reciprocal grafting of wild-type and GLN2 or GLN1;2-deficient lines suggested that shoot GLN2 activity results in ammonium toxicity, whilst root GLN1;2 activity prevents it. With exposure to toxic levels of ammonium, the shoot GLN2 reaction produced an abundance of protons within cells, thereby elevating shoot acidity and stimulating expression of acidic stress-responsive genes. Application of an alkaline ammonia solution to the toxic ammonium medium efficiently alleviated the ammonium toxicity with a concomitant reduction in shoot acidity. Consequently, we conclude that a primary cause of ammonium toxicity is acidic stress in the shoot. This fundamental insight provides a framework for enhanced understanding of ammonium toxicity in plants.

plant biology↗