A Harvard University team describes a strategy for quantifying RNA transcripts within subcellular compartments using a spatial transcriptomic approach called "multiplexed error-robust fluorescence in situ hybridization," or MERFISH, in combination with cellular structure imaging. The researchers demonstrated that they could pick up the spatial distribution of some 10,050 genes in individual cells with around 80 percent efficiency, while misidentifying roughly 4 percent. From there, they followed "RNA velocity" in situ, discerning between the cell cycle states of cells based on the balance of RNA transcripts in the nucleus and cytoplasm. More generally, the authors say, "[w]e anticipate that spatially resolved transcriptome analysis will advance our understanding of the interplay between gene regulation and spatial context in biological systems."
Researchers at the University of Edinburgh, Max Planck Institute for the Science of Human History, and elsewhere present findings from a proteomic study focused on dental calculus samples from dozens of individuals who lived during Ireland's Great Famine from 1845 to 1852, which stemmed from a potato crop-destroying Phytophthora infestans blight. Using proteomic and microparticle analyses on dental calculus samples from 42 Kilkenny workhouse inmates who died during the famine, the team saw hints that the individuals had eaten corn- and milk-heavy diets, along with some potato, cereal starch, and egg protein. "Through historical contextualization, this study shows how the notoriously monotonous potato diet of the poor was opportunistically supplemented by other foodstuffs," the investigators report, arguing that the Great Irish Famine "was foremost a social disaster induced by the lack of access to food."
A team from Australia and Denmark classifies regulatory and evolutionarily significant sequence variants contributing to dozens of cattle traits. After narrowing in on variants with apparent ties to gene expression, metabolite concentrations, or histone marks in more than 400 cattle, the researchers assessed 30 variant sets in relation to 34 complex bovine traits in almost 12,000 bulls and more than 32,300 cows, tallying the predicted heritability, functional effects, and more for the variants — information they brought together using "Functional and evolutionary Trait Heritability" (FAETH) scores for the bovine trait-related variants. "The FAETH framework combines the information of gene regulation, evolution, and trait heritability to rank variants, and the publicly available FAETH data provide a set of biological priors for cattle genomic selection worldwide," the authors note.