Biology subjects

Kageyama, J.

Publications and source records attributed to Kageyama, J..

3 recordsLinked to original sources

bioRxiv2026

Joint analysis of multiply perturbed cells improves statistical power and cost efficiency in Perturb-seq

Perturb-seq measures transcriptomic responses to genetic perturbations at scale, but conventional designs that enrich for one guide RNA per cell remain resource-intensive. Standard analyses discard cells carrying multiple guides, further limiting the usable yield from each experiment. Here, we characterize how incorporating these guide multiplets affects signal recovery, information loss, and cost reduction. At the highest guide burden, cells showed increased stress and suppressed cell-cycle progression. We develop PerturbMatch, a scalable statistical framework to analyze guide multiplets. Among different classes of guide multiplets, doublets and triplets recovered perturbation responses more accurately than higher-order multiplets. Across three 5000-gene Perturb-seq screens with increasing guide loading, per-cell costs decreased by up to 81% while information loss remained within 1.5-fold of the loss observed between technical replicates. In existing genome-wide Perturb-seq data, incorporating previously discarded guide multiplets increased usable cell numbers and improved statistical power. Compared with a singlet holdout set, adding guide multiplets moved signal recovery closer to the theoretical expected reproducibility. Overall, we recommend a design that intentionally includes single-guide cells, guide doublets, and guide triplets to improve cost efficiency while preserving signal recovery.

genomics↗

bioRxiv2025

Assessing the Molecular Validity of Spontaneous Lupus Mouse Models and Its Implication for Human Studies

BackgroundSystemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by a loss of self-tolerance, causing inflammation and tissue damage in multiple organs. Animal models have advanced our understanding of SLEs molecular basis, but the FDAs recent elimination of animal testing requirements for drug approval has raised concerns about their validity, prompting a reevaluation of their role in basic research, especially for heterogeneous diseases like SLE. MethodsFour different spontaneous SLE mouse models were studied: MRLlpr/lpr, NZB/W, BXSB.Yaa, and Tlr7.Tg6. Transcriptome sequencing from blood, spleen, and kidney, flow cytometry from the spleen, and cytokines and autoantibody measurement in plasma were performed at four time points. Similar molecular data from human SLE patients was used for the integration. ResultsThe study identified specific molecular pathways driving the phenotype in each mouse model and established optimal time points for future experimental designs. By comparing these pathways to human SLE, the most similar ones and their relationship with disease activity were identified, providing crucial insight into translational relevance. Importantly, disease severity across models was linked to the extent and timing of molecular dysregulations. As expected, MRLlpr/lpr showed the most aggressive phenotype with early immune activation and apoptosis dysregulation, while Tlr7.Tg6 presented late-onset signatures associated with interferon and inflammation. Shared molecular features with human SLE included interferon responses, T and B cell depletion, and neutrophil activation. Integration analysis revealed distinct yet overlapping immune pathways between models and species, with some signatures such as age-associated B cells and double-negative memory T cells being model-specific but potentially relevant to early disease processes. ConclusionsThese findings build a valuable framework for future SLE research, reinforcing the utility of mouse models in studying specific molecular pathways related to human SLE pathogenesis and heterogeneity. The integration of longitudinal mouse data with human transcriptomes highlights the models that best recapitulate key aspects of human disease, offering guidance for the study of specific immunopathological mechanisms or therapeutic targets.

immunology↗

bioRxiv2017

A rainfall-manipulation experiment with 517 Arabidopsis thaliana accessions

The gold standard for studying natural selection and adaptation in the wild is to quantify lifetime fitness of individuals from natural populations that have been grown together in a common garden, or that have been reciprocally transplanted. By combining fitness values with species traits and genome sequences, one can infer selection coefficients at the genetic level. Here we present a rainfall-manipulation experiment with 517 whole-genome sequenced natural accessions of the plant Arabidopsis thaliana spanning the global distribution of the species. The experiments were conducted in two field stations in contrasting climates, in the Mediterranean and in Central Europe, where we built rainout shelters and simulated high and low rainfall. Using custom image analysis we quantified fitness- and phenology-related traits for 23,154 pots, which contained about 14,500 plants growing independently, and over 310,000 plants growing in small populations (max. 30 plants). This large field experiment dataset, which associates fitness and ecologically-relevant traits with genomes, will provide an important resource to test eco-evolutionary genetic theories and to understand the potential evolutionary impacts of future climates on an important plant model species.

evolutionary biology↗