Consistent individual differences drive collective behaviour and group functioning of schooling fish

The ubiquity of consistent inter-individual differences in behavior (“animal personalities”) [1, 2] suggests that they might play a fundamental role in driving the movements and functioning of animal groups [3, 4], including their collective decision-making, foraging performance, and predator avoidance. Despite increasing evidence that highlights their importance [5–16], we still lack a unified mechanistic framework to explain and to predict how consistent inter-individual differences may drive collective behavior. Here we investigate how the structure, leadership, movement dynamics, and foraging performance of groups can emerge from inter-individual differences by high-resolution tracking of known behavioral types in free-swimming stickleback (Gasterosteus aculeatus) shoals. We show that individual’s propensity to stay near others, measured by a classic “sociability” assay, was negatively linked to swim speed across a range of contexts, and predicted spatial positioning and leadership within groups as well as differences in structure and movement dynamics between groups. In turn, this trait, together with individual’s exploratory tendency, measured by a classic “boldness” assay, explained individual and group foraging performance. These effects of consistent individual differences on group-level states emerged naturally from a generic model of self-organizing groups composed of individuals differing in speed and goal-orientedness. Our study provides experimental and theoretical evidence for a simple mechanism to explain the emergence of collective behavior from consistent individual differences, including variation in the structure, leadership, movement dynamics, and functional capabilities of groups, across social and ecological scales. In addition, we demonstrate individual performance is conditional on group composition, indicating how social selection may drive behavioral differentiation between individuals.We acknowledge financial support from the Biotechnology and Biological Sciences Research Council (Graduate Research Fellowship to J.W.J), the Association for the Study of Animal Behaviour (Research Grants to J.W.J and N.J.B), the Royal Society (Dorothy Hodgkin Fellowship to N.J.B), the National Science Foundation (PHY-0848755, IOS-1355061, EAGER-IOS- 1251585 to I.D.C), the Office of Naval Research (N00014-09-1-1074, N00014-14-1-0635 to I.D.C), the Army Research Office (W911NG-11-1-0385, W911NF-14-1-0431 to I.D.C), the Human Frontier Science Program (RGP0065/2012 to I.D.C), the Ministerium für Wissenschaft, Forschung und Kunst Baden- Württemberg (SI-BW to I.D.C), and the Max Planck Institute for Ornithology. Open Access funded by Biotechnology and Biological Sciences Research Counci

Mapping RNA-Chromatin Interactions In Vivo with RNA-DamID

Long-noncoding RNAs (lncRNAs) are emerging as regulators of development and disease. lncRNAs are expressed in exquisitely precise expression patterns in vivo and many interact with chromatin to regulate gene expression. However, the limited sensitivity of RNA-purification techniques has precluded the identification of genomic targets of cell-type specific lncRNAs. RNA-DamID is a powerful new approach to understand the mechanisms by which lncRNAs act in vivo. RNA-DamID is highly sensitive and accurate, and can resolve cell-type-specific chromatin binding patterns without cell isolation. The determinants of RNA-chromatin interactions can be identified with RNA-DamID by analyzing RNA and protein cofactor mutants. Here we describe how to implement RNA-DamID and the design considerations to take into account to accurately identify lncRNA-chromatin interactions in vivo

Mapping RNA-Chromatin Interactions In Vivo with RNA-DamID.

Long-noncoding RNAs (lncRNAs) are emerging as regulators of development and disease. lncRNAs are expressed in exquisitely precise expression patterns in vivo and many interact with chromatin to regulate gene expression. However, the limited sensitivity of RNA-purification techniques has precluded the identification of genomic targets of cell-type specific lncRNAs. RNA-DamID is a powerful new approach to understand the mechanisms by which lncRNAs act in vivo. RNA-DamID is highly sensitive and accurate, and can resolve cell-type-specific chromatin binding patterns without cell isolation. The determinants of RNA-chromatin interactions can be identified with RNA-DamID by analyzing RNA and protein cofactor mutants. Here we describe how to implement RNA-DamID and the design considerations to take into account to accurately identify lncRNA-chromatin interactions in vivo