BackgroundNext Generation Sequencing technologies are able to provide high genome coverages at a relatively low cost. However, due to limited reads' length (from 30 bp up to 200 bp), specific bioinformatics problems have become even more difficult to solve. De novo assembly with short reads, for example, is more complicated at least for two reasons: first, the overall amount of "noisy" data to cope with increased and, second, as the reads' length decreases the number of unsolvable repeats grows. Our work's aim is to go at the root of the problem by providing a pre-processing tool capable to produce (in-silico) longer and highly accurate sequences from a collection of Next Generation Sequencing reads.ResultsIn this paper a seed-and-extend local assembler is presented. The kernel algorithm is a loop that, starting from a read used as seed, keeps extending it using heuristics whose main goal is to produce a collection of error-free and longer sequences. In particular, GapFiller carefully detects reliable overlaps and operates clustering similar reads in order to reconstruct the missing part between the two ends of the same insert. Our tool's output has been validated on 24 experiments using both simulated and real paired reads datasets. The output sequences are declared correct when the seed-mate is found. In the experiments performed, GapFiller was able to extend high percentages of the processed seeds and find their mates, with a false positives rate that turned out to be nearly negligible.ConclusionsGapFiller, starting from a sufficiently high short reads coverage, is able to produce high coverages of accurate longer sequences (from 300 bp up to 3500 bp). The procedure to perform safe extensions, together with the mate-found check, turned out to be a powerful criterion to guarantee contigs' correctness. GapFiller has further potential, as it could be applied in a number of different scenarios, including the post-processing validation of insertions/deletions detection pipelines, pre-processing routines on datasets for de novo assembly pipelines, or in any hierarchical approach designed to assemble, analyse or validate pools of sequences.

Summary Cytosolic DNA activates cyclic guanosine monophosphate-adenosine monophosphate (cGAMP) synthase (cGAS), an innate immune sensor pivotal in anti-microbial defense, senescence, auto-immunity, and cancer. cGAS is considered to be a sequence-independent DNA sensor with limited access to nuclear DNA because of compartmentalization. However, the nuclear envelope is a dynamic barrier, and cGAS is present in the nucleus. Here, we identify determinants of nuclear cGAS localization and activation. We show that nuclear-localized cGAS synthesizes cGAMP and induces innate immune activation of dendritic cells, although cGAMP levels are 200-fold lower than following transfection with exogenous DNA. Using cGAS ChIP-seq and a GFP-cGAS knockin mouse, we find nuclear cGAS enrichment on centromeric satellite DNA, confirmed by imaging, and to a lesser extent on LINE elements. The non-enzymatic N-terminal domain of cGAS determines nucleo-cytoplasmic localization, enrichment on centromeres, and activation of nuclear-localized cGAS. These results reveal a preferential functional association of nuclear cGAS with centromeres.