Suchergebnisse

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 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. ; We acknowledge the financial support of the Spanish Ministry of Economy, Industry and Competitiveness (Centro de Excelencia Severo Ochoa 2013–2017, Plan Estatal PGC2018-099807-B-I00), of the CERCA Programme/Generalitat de Catalunya, and of the European Research Council (Synergy Grant 609989). RC was supported by the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement 608959. We also acknowledge support of the Spanish Ministry of Economy and Competitiveness (MEIC) to the EMBL partnership.

The main obstacle to curing HIV is the presence of latent proviruses in the bodies of infected patients. The partial success of reactivation therapies suggests that the genomic context of integrated proviruses can interfere with treatment. Here we developed a method called Barcoded HIV ensembles (B-HIVE) to map the chromosomal locations of thousands of individual proviruses while tracking their transcriptional activities in an infected cell population. B-HIVE revealed that, in Jurkat cells, the expression of HIV is strongest close to endogenous enhancers. The insertion site also affects the response to latency-reversing agents, because we found that phytohemagglutinin and vorinostat reactivated proviruses inserted at distinct genomic locations. From these results, we propose that combinations of drugs targeting all areas of the genome will be most effective. Overall, our data suggest that the insertion context of HIV is a critical determinant of the viral response to reactivation therapies. ; This research was supported by the Government of Catalonia and the Spanish Ministry of Economy and Competitiveness (Plan Nacional BFU2012-37168, Centro de Excelencia Severo Ochoa 2013-2017 SEV-2012-0208). J.P.M. and A.M. were supported by a grant from the Spanish Ministry of Economy and Competitiveness and FEDER (SAF2013-46077-R). E.Z. and G.J.F. are supported by the European Research Council (Synergy Grant 609989).