Biology subjects

Garcia Accinelli, G.

Publications and source records attributed to Garcia Accinelli, G..

3 recordsLinked to original sources

bioRxiv2017

Skip-mers: increasing entropy and sensitivity to detect conserved genic regions with simple cyclic q-grams

Bioinformatic analyses and tools make extensive use of k-mers (fixed contiguous strings of k nucleotides) as an informational unit. K-mer analyses are both useful and fast, but are strongly affected by single-nucleotide polymorphisms or sequencing errors, effectively hindering direct-analyses of whole regions and decreasing their usability between evolutionary distant samples.\n\nWe introduce a concept of skip-mers, a cyclic pattern of used-and-skipped positions of k nucleotides spanning a region of size S [≥] k, and show how analyses are improved compared to using k-mers. The entropy of skip-mers increases with the larger span, capturing information from more distant positions and increasing the specificity, and uniqueness, of larger span skip-mers within a genome. In addition, skip-mers constructed in cycles of 1 or 2 nucleotides in every 3 (or a multiple of 3) lead to increased sensitivity in the coding regions of genes, by grouping together the more conserved nucleotides of the protein-coding regions.\n\nWe implemented a set of tools to count and intersect skip-mers between different datasets. We used these tools to show how skip-mers have advantages over k-mers in terms of entropy and increased sensitivity to detect conserved coding sequence, allowing better identification of genic matches between evolutionarily distant species. We also highlight potential applications to problems such as whole-genome alignment and multi-genome evolutionary analyses.\n\nSoftware availabilitythe skm-tools implementing the methods described in this manuscript are available under MIT license at http://github.com/bioinfologics/skm-tools/

bioinformatics↗

bioRxiv2017

W2RAP: a pipeline for high quality, robust assemblies of large complex genomes from short read data

Producing high-quality whole-genome shotgun de novo assemblies from plant and animal species with large and complex genomes using low-cost short read sequencing technologies remains a challenge. But when the right sequencing data, with appropriate quality control, is assembled using approaches focused on robustness of the process rather than maximization of a single metric such as the usual contiguity estimators, good quality assemblies with informative value for comparative analyses can be produced. Here we present a complete method described from data generation and qc all the way up to scaffold of complex genomes using Illumina short reads and its application to data from plants and human datasets. We show how to use the w2rap pipeline following a metric-guided approach to produce cost-effective assemblies. The assemblies are highly accurate, provide good coverage of the genome and show good short range contiguity. Our pipeline has already enabled the rapid, cost-effective generation of de novo genome assemblies from large, polyploid crop species with a focus on comparative genomics.\n\nAvailabilityw2rap is available under MIT license, with some subcomponents under GPL-licenses. A ready-to-run docker with all software pre-requisites and example data is also available.\n\nhttp://github.com/bioinfologics/w2rap\n\nhttp://github.com/bioinfologics/w2rap-contigger

bioinformatics↗

bioRxiv2016

An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations.

Advances in genome sequencing and assembly technologies are generating many high quality genome sequences, but assemblies of large, repeat-rich polyploid genomes, such as that of bread wheat, remain fragmented and incomplete. We have generated a new wheat whole-genome shotgun sequence assembly using a combination of optimised data types and an assembly algorithm designed to deal with large and complex genomes. The new assembly represents more than 78% of the genome with a scaffold N50 of 88.8kbp that has a high fidelity to the input data. Our new annotation combines strand-specific Illumina RNAseq and PacBio full-length cDNAs to identify 104,091 high confidence protein-coding genes and 10,156 non-coding RNA genes. We confirmed three known and identified one novel genome rearrangements. Our approach enables the rapid and scalable assembly of wheat genomes, the identification of structural variants, and the definition of complete gene models, all powerful resources for trait analysis and breeding of this key global crop. [Supplemental material is available for this article.]

genomics↗