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Tiana, G.

Publications and source records attributed to Tiana, G..

2 recordsLinked to original sources

Modeling of DNA methylation in cis reveals principles of chromatin folding in vivo in the absence of crosslinking and ligation

Mammalian chromosomes are folded into an intricate hierarchy of structural domains, within which topologically associating domains (TADs) and CTCF-associated loops partition the physical interactions between regulatory sequences. Current understanding of chromosome folding largely relies on chromosome conformation capture (3C)-based experiments, where chromosomal interactions are detected as ligation products after crosslinking of chromatin. To measure chromosome structure in vivo, quantitatively and without relying on crosslinking and ligation, we have implemented a new method named damC. DamC combines DNA-methylation based detection of chromosomal interactions with next-generation sequencing and a biophysical model of methylation kinetics. DamC performed in mouse embryonic stem cells provides the first in vivo validation of the existence of TADs and CTCF loops, confirms 3C-based measurements of the scaling of contact probabilities within TADs, and provides evidence that mammalian chromatin in vivo is essentially rigid below 5 kilobases. Combining damC with transposon-mediated genomic engineering shows that new loops can be formed between ectopically introduced and endogenous CTCF sites, which alters the partitioning of physical interactions within TADs. This establishes damC as a crosslinking-and ligation-free framework to measure and modify chromosome interactions combined with a solid theoretical background for rigorous data interpretation. This orthogonal approach to 3C validates the existence of key structural features of mammalian chromosomes and provides novel insights into how chromosome structure within TADs can be manipulated.

genomics

Complete coverage of space favors modularity of the grid system in the brain

Grid cells in the entorhinal cortex fire when animals that are exploring a certain region of space occupy the vertices of a triangular grid that spans the environment. Different neurons feature triangular grids that differ in their properties of periodicity, orientation and ellipticity. Taken together, these grids allow the animal to maintain an internal, mental representation of physical space. Experiments show that grid cells are modular, i.e. there are groups of neurons which have grids with similar periodicity, orientation and ellipticity. We use statistical physics methods to derive a relation between variability of the properties of the grids within a module and the range of space that can be covered completely (i.e. without gaps) by the grid system with high probability. Larger variability shrinks the range of representation, providing a functional rationale for the experimentally observed co-modularity of grid cell periodicity, orientation and ellipticity. We obtain a scaling relation between the number of neurons and the period of a module, given the variability and coverage range. Specifically, we predict how many more neurons are required at smaller grid scales than at larger ones.

neuroscience