The study examined chromosomal evolution across 230 Andropogoneae species using literature/database surveys and phylogenetic analysis of complete plastome sequences, with Bayesian inference for ancestral state reconstruction. It found extensive chromosome-number variation (2n = 8–140), 30% polyploidy, and identified 2n = 20 as the likely ancestral state, highlighting the dynamic nature of chromosomal changes in the tribe.

The study evaluated a transgenic soybean line (VPZ-34A) expressing Arabidopsis VDE, PsbS, and ZEP for combined improvements in light‑use efficiency and carbon assimilation under ambient and elevated CO2 in a FACE experiment. While VPZ‑34A showed enhanced maximum quantum efficiency of PSII under fluctuating light, it did not increase carbon assimilation efficiency or yield, and transcriptome analysis revealed limited gene expression changes. The results suggest that VPZ‑mediated photosynthetic gains are insufficient to boost productivity under elevated CO2.

The study introduces a data-augmented adaptive multiple importance sampling (DA‑AMIS) framework that combines Bayesian inference with stochastic epidemic modeling to estimate transmission parameters of banana bunchy top virus from a small 24‑plant field experiment. Validation with independent BBTV trial data from Burundi and Malawi confirmed the robustness of the estimated primary and secondary infection rates, revealing a 12% infection risk from replanting suckers and pinpointing April as the period of peak infection for targeted surveillance.

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.