Publications by authors named "D A Lacoste"

The long interspersed element 1 (LINE-1 or L1) integration is affected by many cellular factors through various mechanisms. Some of these factors are required for L1 amplification, while others either suppress or enhance specific steps during L1 propagation. Previously, TRIM28 has been identified to suppress transposable elements, including L1 expression via its canonical role in chromatin remodeling.

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Background: Endogenous expression of L1 mRNA is the first step in an L1-initiated mutagenesis event. However, the contribution of individual cell types to patterns of organ-specific L1 mRNA expression remains poorly understood, especially at single-locus resolution. We introduce a method to quantify expression of mobile elements at the single-locus resolution in scRNA-Seq datasets called Single Cell Implementation to Find Expressed Retrotransposons (SCIFER).

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The selection of a single molecular handedness, or homochirality across all living matter, is a mystery in the origin of life. Frank's seminal model showed in the '50s how chiral symmetry breaking can occur in nonequilibrium chemical networks. However, an important shortcoming in this classic model is that it considers a small number of species, while there is no reason for the prebiotic system, in which homochirality first appeared, to have had such a simple composition.

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Autocatalysis is essential for the origin of life and chemical evolution. However, the lack of a unified framework so far prevents a systematic study of autocatalysis. Here, we derive, from basic principles, general stoichiometric conditions for catalysis and autocatalysis in chemical reaction networks.

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We construct a pathwise formulation of a growing population of cells, based on two different samplings of lineages within the population, namely the forward and backward samplings. We show that a general symmetry relation, called fluctuation relation relates these two samplings, independently of the model used to generate divisions and growth in the cell population. These relations lead to estimators of the population growth rate, which can be very efficient as we demonstrate by an analysis of a set of mother machine data.

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