Unravelling the intraspecific variation in drought responses in seedlings of European black pine (Pinus nigra J.F. Arnold)
Authors: Ahmad, M., Hammerbacher, A., Priemer, C., Ciceu, A., Karolak, M., Mader, S., Olsson, S., Schinnerl, J., Seitner, S., Schoendorfer, S., Helfenbein, P., Jakub, J., Breuer, M., Espinosa, A., Caballero, T., Ganthaler, A., Mayr, S., Grosskinsky, D. K., Wienkoop, S., Schueler, S., Trujillo-Moya, C., van Loo, M.
The study examined drought tolerance across nine provenances of the conifer Pinus nigra using high‑throughput phenotyping combined with metabolomic and transcriptomic analyses under controlled soil‑drying conditions. Drought tolerance, measured by the decline in Fv/Fm, varied among provenances but was not linked to a climatic gradient and was independent of growth, with tolerant provenances showing distinct flavonoid and diterpene profiles and provenance‑specific gene expression patterns. Integrating phenotypic and molecular data revealed metabolic signatures underlying drought adaptation in this non‑model conifer.
In a two-year controlled-environment experiment, diploid and tetraploid individuals of wild-type and cultivar Marshall annual ryegrass (Lolium multiflorum) were grown under elevated CO2 (540 vs 800 ppm) and differing evapotranspiration regimes. Elevated CO2 increased total biomass by 44% across ploidy levels, and tetraploid wild-type plants matched the improved cultivar in growth and forage quality, indicating that chromosome manipulation and wild genetic resources can enhance climate resilience.
Phylogenomic challenges in polyploid-rich lineages: Insights from paralog processing and reticulation methods using the complex genus Packera (Asteraceae: Senecioneae)
Authors: Moore-Pollard, E. R., Ellestad, P., Mandel, J.
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.
Revisiting the Central Dogma: the distinct roles of genome, methylation, transcription, and translation on protein expression in Arabidopsis thaliana
Authors: Zhong, Z., Bailey, M., Kim, Y.-I., Pesaran-Afsharyan, N., Parker, B., Arathoon, L., Li, X., Rundle, C. A., Behrens, A., Nedialkova, D. D., Slavov, G., Hassani-Pak, K., Lilley, K. S., Theodoulou, F. L., Mott, R.
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 Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset
Authors: Wang, Z., Zenkl, R., Greche, L., De Solan, B., Bernigaud Samatan, L., Ouahid, S., Visioni, A., Robles-Zazueta, C. A., Pinto, F., Perez-Olivera, I., Reynolds, M. P., Zhu, C., Liu, S., D'argaignon, M.-P., Lopez-Lozano, R., Weiss, M., Marzougui, A., Roth, L., Dandrifosse, S., Carlier, A., Dumont, B., Mercatoris, B., Fernandez, J., Chapman, S., Najafian, K., Stavness, I., Wang, H., Guo, W., Virlet, N., Hawkesford, M., Chen, Z., David, E., Gillet, J., Irfan, K., Comar, A., Hund, A.
The Global Wheat Dataset Consortium released a comprehensive semantic segmentation dataset (GWFSS) of wheat organs across developmental stages, comprising 1,096 fully annotated images and 52,078 unannotated images from 11 institutions. Models based on DeepLabV3Plus and Segformer were trained, with Segformer achieving ≈90% mIoU for leaves and spikes but lower precision (54%) for stems, while also enabling weed exclusion and discrimination of necrotic, senescent, and residue tissues.
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.