Biology subjects

Routhier, E.

Publications and source records attributed to Routhier, E..

4 recordsLinked to original sources

bioRxiv2023

In silico design of DNA sequences for in vivo nucleosome positioning

The computational design of synthetic DNA sequences with desired in vivo properties is gaining traction in the field of synthetic genomics. We propose here a computational method which combines a kinetic Monte Carlo framework with a deep mutational screening based on deep learning predictions. We apply our method to build regular nucleosome arrays with tailored nucleosomal repeat lengths (NRL) in yeast. Our design is validated in vivo by successfully engineering and integrating thousands of kilobases long tandem arrays of computationally optimized sequences which could accommodate NRLs much larger than the yeast natural NRL. This method delineates the key sequence rules for nucleosome positioning in yeast and is readily applicable to other sequence properties and other genomes.

synthetic biology↗

bioRxiv2022

Exogenous chromosomes reveal how sequence composition drives chromatin assembly, activity, folding and compartmentalization

Genomic sequences co-evolve with DNA-associated proteins to ensure the multiscale folding of long DNA molecules into functional chromosomes. In eukaryotes, different molecular complexes organize the chromosomes hierarchical structure, ranging from nucleosomes and cohesin- mediated DNA loops to large scale chromatin compartments. To explore the relationships between the DNA sequence composition and the spontaneous loading and activity of these DNA-associated complexes in the absence of co-evolution, we characterized chromatin assembly and activity in yeast strains carrying exogenous bacterial chromosomes that diverged from eukaryotic sequences over 1.5 billion years ago. We show that nucleosome assembly, transcriptional activity, cohesin-mediated looping, and chromatin compartmentalization can occur in a bacterial chromosome with a largely divergent sequence integrated in a eukaryotic host, and that the chromatinization of bacterial chromosomes is highly correlated with their sequence composition. These results are a step forward in understanding how foreign sequences are interpreted by a host nuclear machinery during natural horizontal gene transfers, as well as in synthetic genomics projects.

genetics↗

bioRxiv2021

Nucleosome positioning on large tandem DNA repeats of the '601' sequence engineered in Saccharomyces cerevisiae

The so-called 601 DNA sequence is often used to constrain the position of nucleosomes on a DNA molecule in vitro. Although the ability of the 147 base pair sequence to precisely position a nucleosome in vitro is well documented, in vivo application of this property has been explored only in a few studies and yielded contradictory conclusions. Our goal in the present study was to test the ability of the 601 sequence to dictate nucleosome positioning in Saccharomyces cerevisiae in the context of a long tandem repeat array inserted in a yeast chromosome. We engineered such arrays with three different repeat size, namely 167, 197 and 237 base pairs. Although our arrays are able to position nucleosomes in vitro as expected, analysis of nucleosome occupancy on these arrays in vivo revealed that nucleosomes are not preferentially positioned as expected on the 601-core sequence along the repeats and that the measured nucleosome repeat length does not correspond to the one expected by design. Altogether our results demonstrate that the rules defining nucleosome positions on this DNA sequence in vitro are not valid in vivo, at least in this chromosomal context, questioning the relevance of using the 601 sequence in vivo to achieve precise nucleosome positioning on designer synthetic DNA sequences.

synthetic biology↗

bioRxiv2018

Genome Functional Annotation using Deep Convolutional Neural Network

Deep neural network application is today a skyrocketing field in many disciplinary domains. In genomics the development of deep neural networks is expected to revolutionize current practice. Several approaches relying on convolutional neural networks have been developed to associate short genomic sequences with a functional role such as promoters, enhancers or protein binding sites along genomes. These approaches rely on the generation of sequences batches with known annotations for learning purpose. While they show good performance to predict annotations from a test subset of these batches, they usually perform poorly when applied genome-wide.\n\nIn this study, we address this issue and propose an optimal strategy to train convolutional neural networks for this specific application. We use as a case study transcription start sites and show that a model trained on one organism can be used to predict transcription start sites in a different specie. This cross-species application of convolutional neural networks trained with genomic sequence data provides a new technique to annotate any genome from previously existing annotations in related species. It also provides a way to determine whether the sequence patterns recognized by chromatin associated proteins in different species are conserved or not.

bioinformatics↗