The study presents a deep‑learning pipeline that uses state‑of‑the‑art convolutional neural networks to automatically estimate the establishment of perennial groundcovers in agricultural research plots from smartphone images. By employing region‑of‑interest markers and deploying the models on AWS SageMaker with a lightweight Django web interface, the approach provides fast, objective, and reproducible assessments that can be adopted by researchers and growers across the Midwest.

The study identifies the pseudokinase CRN in Medicago truncatula as a regulator of inflorescence meristem branching and a negative modulator of root interactions with arbuscular mycorrhizal (AM) fungi, operating partially independently of the AM autoregulation CLE peptide MtCLE53. Transcriptomic profiling of crn mutant roots reveals disruptions in nutrient, symbiosis, and stress signaling pathways, highlighting the multifaceted role of MtCRN in plant development and environmental interactions.

The study examined how varying temperature regimes, including cold deprivation and early cold exposure, affect dormancy onset and maintenance in sweet cherry (Prunus avium) flower buds. Phenological monitoring combined with transcriptomic analyses revealed that temperature drives dormancy progression, identifying specific genes and pathways responsive to cold, and uncovering a distinct shallow dormancy phase induced by cold deprivation with a unique molecular signature.

The study combined cell biology, transcriptomics, and ionomics to reveal that zinc deficiency reduces root apical meristem size while preserving meristematic activity and local Zn levels, leading to enhanced cell elongation and differentiation in Arabidopsis thaliana. ZIP12 was identified as a highly induced gene in the zinc‑deficient root tip, and zip12 mutants displayed impaired root growth, altered RAM structure, disrupted Zn‑responsive gene expression, and abnormal metal partitioning, highlighting ZIP12’s role in maintaining Zn homeostasis and meristem function.

The study used an interpretable convolutional neural network to predict ABA responsiveness from proximal promoter sequences in Arabidopsis thaliana, revealing both known ABF-binding motifs and novel regulatory elements. Model performance was boosted by advanced data augmentation, and predicted regulatory regions were experimentally validated using reporter lines, confirming the inferred cis‑regulatory code.

The study used transcriptomic and lipidomic profiling to investigate how chia (Salvia hispanica) leaves respond to short‑term (3 h) and prolonged (27 h) heat stress at 38 °C, revealing rapid activation of calcium‑signaling and heat‑shock pathways and reversible changes in triacylglycerol levels. Nearly all heat‑responsive genes returned to baseline expression after 24 h recovery, highlighting robust thermotolerance mechanisms that could inform improvement of other oilseed crops.

The study used Arabidopsis thaliana mutants with low (vtc2, vtc4) and high (vtc2/OE-VTC2) ascorbate levels to examine how ascorbate concentration affects gene expression and cellular homeostasis. Transcriptomic analysis revealed that altered ascorbate levels modulate defense and stress pathways, and that TAA1/TAR2‑mediated auxin biosynthesis is required for coping with elevated ascorbate in a light‑dependent manner.

The study performed daily large-scale glycome, transcriptome, and proteome profiling of developing fibers from the two cultivated cotton species, Gossypium barbadense and G. hirsutum, across primary and secondary cell wall stages. It identified delayed cellulose accumulation and distinct compositions of xyloglucans, homogalacturonans, rhamnogalacturonan‑I, and heteroxylans in G. barbadense, along with higher expression of specific glycosyltransferases and expansins, suggesting these molecular differences underlie the superior fiber length and strength of G. barbadense.

The study examines how the SnRK1 catalytic subunit KIN10 integrates carbon availability with root growth regulation in Arabidopsis thaliana. Loss of KIN10 reduces glucose‑induced inhibition of root elongation and triggers widespread transcriptional reprogramming of metabolic and hormonal pathways, notably affecting auxin and jasmonate signaling under sucrose supplementation. These findings highlight KIN10 as a central hub linking energy status to developmental and environmental cues in roots.

The study presents GenoRetriever, an interpretable deep learning framework trained on STRIPE-seq data from soybean and other crops, that predicts transcription start site locations and usage by identifying 27 core promoter motifs. Validation using in silico motif insertions, saturation mutagenesis, and CRISPR‑Cas9 promoter editing demonstrates high predictive accuracy and reveals domestication‑driven motif usage shifts and lineage‑specific effects. The tool is provided via a web server for promoter analysis and design, offering a new resource for plant functional genomics and crop improvement.