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AI-summarized plant biology research papers from bioRxiv

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Wheat diversity reveals new genomic loci and candidate genes for vegetation indices using genome-wide association analysis

Authors: Rustamova, S., Jahangirov, A., Leon, J., Naz, A. A., Huseynova, I.

Date: 2026-01-14 · Version: 1
DOI: 10.64898/2026.01.14.699455

Category: Plant Biology

Model Organism: Triticum aestivum

AI Summary

A genome‑wide association study of 187 bread wheat genotypes identified 812 significant loci linked to 25 spectral vegetation indices under rainfed drought conditions, revealing a major QTL hotspot on chromosome 2A that accounts for up to 20% of variance in greenness and pigment traits. Candidate gene analysis at this hotspot uncovered stress‑responsive genes, demonstrating that vegetation indices are heritable digital phenotypes useful for selection and genetic analysis of drought resilience.

Triticum aestivum drought stress spectral vegetation indices GWAS QTL hotspot

Choosing the Best Route: Comparative Optimization of Wheat Transformation Methods for Improving Yield by Targeting TaARE1-D with CRISPR/Cas9

Authors: Tek, M. I., Budak Tek, K., Sarikaya, P., Ahmed, A. R., Fidan, H.

Date: 2025-09-12 · Version: 1
DOI: 10.1101/2025.09.11.675438

Category: Plant Biology

Model Organism: Triticum aestivum

AI Summary

The study optimized three wheat transformation methods—immature embryo, callus, and in planta injection—by systematically adjusting Agrobacterium strain, bacterial density, acetosyringone concentration, and incubation conditions, achieving transformation efficiencies up to 66.84%. Using these protocols, CRISPR/Cas9 knockout of the negative regulator TaARE1-D produced mutants with increased grain number, spike length, grain size, and a stay‑green phenotype, demonstrating the platform’s potential to accelerate yield and stress‑tolerance improvements in wheat.

Triticum aestivum CRISPR/Cas9 Agrobacterium-mediated transformation TaARE1-D yield improvement

Host genotype shapes root mycobiota in durum wheat

Authors: TRINQUIER, M., COLOMBO, M., FREVILLE, H., JACQUES, D., ROCHER, A., LEFEBVRE, B., ROUX, C.

Date: 2025-03-06 · Version: 3
DOI: 10.1101/2024.10.27.616629

Category: Plant Biology

Model Organism: Triticum aestivum

AI Summary

The study examined how genetic variation among 181 wheat (Triticum aestivum) lines influences root endophytic fungal communities using ITS2 metabarcoding. Heritability estimates and GWAS identified 11 QTLs linked to fungal clade composition, highlighting genetic control of mycobiota, especially for biotrophic AMF. These findings suggest breeding can be used to modulate beneficial root-fungal associations.

wheat genotype root endophytic mycobiota ITS2 barcoding GWAS QTL