Biology subjects

Cortini, R.

Publications and source records attributed to Cortini, R..

3 recordsLinked to original sources

bioRxiv2020

Mapping short reads, faithfully

Mapping is the process of finding the original location of a DNA read in a reference sequence, typically a genome. Short read mappers are software tools used in most applications that involve high-throughput sequencing. As such, they must be continuously improved to keep up with increasing needs. Modern mappers rely on seeding heuristics, making them fast but inexact. For lack of a method to compute the reliability of their own output, mappers have so far used approximations of variable quality. Here we focus on faithfulness, the capacity to provide accurate mapping confidence, and we devise a strategy to map short reads faithfully. The key is to estimate the repetitiveness of the target reference, which is the dominant factor for the reliability of the mapping process. This approach highlights the existence of a class of reads that can be mapped with unprecedented confidence. We exploit this strategy in a prototype mapper that is competitive with state-of-the-art mappers BWA-MEM and Bowtie2, with the benefit of faithfulness. The software is open-source and available for download at https://github.com/gui11aume/mmp.

bioinformatics↗

bioRxiv2019

Calibrating seed-based heuristics to map short DNA reads

The increasing throughput of DNA sequencing technologies creates a need for faster algorithms. The fate of most reads is to be mapped to a reference sequence, typically a genome. Modern mappers rely on heuristics to gain speed at a reasonable cost for accuracy. In the seeding heuristic, short matches between the reads and the genome are used to narrow the search to a set of candidate locations. Several seeding variants used in modern mappers show good empirical performance but they are difficult to calibrate or to optimize for lack of theoretical results. Here we develop a theory to estimate the probability that the correct location of a read is filtered out during seeding, resulting in mapping errors. We describe the properties of simple exact seeds, skip-seeds and MEM seeds (Maximal Exact Match seeds). The main innovation of this work is to use concepts from analytic combinatorics to represent reads as abstract sequences, and to specify their generative function to estimate the probabilities of interest. We provide several algorithms, which combined together give a workable solution for the problem of calibrating seeding heuristics for short reads. We also provide a C implementation of these algorithms in a library called Sesame. These results can improve current mapping algorithms and lay the foundation of a general strategy to tackle sequence alignment problems. The Sesame library is open source and available for download at https://github.com/gui11aume/sesame.

bioinformatics↗

bioRxiv2017

Principles of transcription factor traffic on folded chromatin

All organisms regulate the transcription of their genes. To understand this process, it is essential to know how transcription factors find their targets in the genome. In addition to the DNA sequence, several variables have a known influence, but overall the binding patterns of transcription factors distribution remains mostly unexplained in animal genomes. Here we investigate the role of the chromosome conformation in shaping the search path of transcription factors. Using molecular dynamics simulations, we uncover the main principles of their diffusion on folded chromatin. Chromosome contacts play a conflicting role: at low density they enhance the traffic of transcription factors, but a high density they lower the traffic by volume exclusion. Consistently, we observe that in human cells, highly occupied targets, where protein binding is promiscuous, are found at sites engaged in chromosome loops within uncompact chromatin. In summary, those results provide a theoretical framework to understand the search trajectories of transcription factors and highlight the key contribution of genome conformation.

biophysics↗