The study examined how polyploidy, hybridization, and incomplete lineage sorting affect phylogenetic reconstructions in the genus Packera, evaluating several published paralog‑processing pipelines. Results showed that the choice of orthology and paralog handling methods markedly altered tree topology, time‑calibrated phylogenies, biogeographic histories, and detection of ancient reticulation, underscoring the need for careful methodological selection alongside comprehensive taxon sampling.

The study integrates genome, transcriptome, and chromatin accessibility data from 380 soybean accessions to dissect the genetic and regulatory basis of symbiotic nitrogen fixation (SNF). Using GWAS, TWAS, eQTL mapping, and ATAC-seq, the authors identify key loci, co‑expression modules, and regulatory elements, and validate the circadian clock gene GmLHY1b as a negative regulator of nodulation via CRISPR and CUT&Tag. These resources illuminate SNF networks and provide a foundation for soybean improvement.

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 evaluated natural genetic variation in non-photochemical quenching and photoprotection across 861 sorghum accessions grown in the field over two years, revealing moderate to high broad-sense heritability for chlorophyll fluorescence traits. By integrating genome-wide association studies (GWAS) with transcriptome-wide association studies (TWAS) and covariance analyses, the authors identified 110 high-confidence candidate genes underlying photoprotection, highlighting a complex, polygenic architecture for these traits.

The study combined long‑read whole‑genome assembly, multi‑omics profiling (DNA methylation, mRNA, ribosome‑associated transcripts, tRNA abundance, and protein levels) in two Arabidopsis thaliana accessions to evaluate how genomic information propagates through the Central Dogma. Codon usage in gene sequences emerged as the strongest predictor of both mRNA and protein abundance, while methylation, tRNA levels, and ribosome‑associated transcripts contributed little additional information under stable conditions.

The study performed a comprehensive computational analysis of the Arabidopsis thaliana proteome, classifying 48,359 proteins by melting temperature (Tm) and melting temperature index (TI) and linking thermal stability to amino acid composition, molecular mass, and codon usage. Machine‑learning and evolutionary analyses revealed that higher molecular mass and specific codon pairs correlate with higher Tm, and that gene duplication has driven the evolution of high‑Tm proteins, suggesting a genomic basis for stress resilience.