Explore the vast range of titles available.

Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here, we present Flye, a long-read assembly algorithm that generates arbitrary paths in an unknown repeat graph, called disjointigs, and constructs an accurate repeat graph from these error-riddled disjointigs. We benchmark Flye against five state-of-the-art assemblers and show that it generates better or comparable assemblies, while being an order of magnitude faster. Flye nearly doubled the contiguity of the human genome assembly (as measured by the NGA50 assembly quality metric) compared with existing assemblers.Flye improves the speed and accuracy of genome assembly by using repeat graphs to resolve repeat regions.

The recent breakthroughs in assembling long error-prone reads were based on the overlap-layout-consensus (OLC) approach and did not utilize the strengths of the alternative de Bruijn graph approach to genome assembly. Moreover, these studies often assume that applications of the de Bruijn graph approach are limited to short and accurate reads and that the OLC approach is the only practical paradigm for assembling long error-prone reads. We show how to generalize de Bruijn graphs for assembling long error-prone reads and describe the ABruijn assembler, which combines the de Bruijn graph and the OLC approaches and results in accurate genome reconstructions.

Centromeric variation has been linked to cancer and infertility, but centromere sequences contain multiple tandem repeats and can only be assembled manually from long error-prone reads. Here we describe the centroFlye algorithm for centromere assembly using long error-prone reads, and apply it to assemble human centromeres on chromosomes 6 and X. Our analyses reveal putative breakpoints in the manual reconstruction of the human X centromere, demonstrate that human X chromosome is partitioned into repeat subfamilies and provide initial insights into centromere evolution. We anticipate that centroFlye could be applied to automatically close remaining multimegabase gaps in the reference human genome.CentroFlye resolves tandem repeats to assemble human centromeres from nanopore reads.

A mathematical concept known as a de Bruijn graph turns the formidable challenge of assembling a contiguous genome from billions of short sequencing reads into a tractable computational problem. The development of algorithmic ideas for next-generation sequencing is examined.

Natural products have traditionally been rich sources for drug discovery. In order to clear the road toward the discovery of unknown natural products, biologists need dereplication strategies that identify known ones. Here we report DEREPLICATOR+, an algorithm that improves on the previous approaches for identifying peptidic natural products, and extends them for identification of polyketides, terpenes, benzenoids, alkaloids, flavonoids, and other classes of natural products. We show that DEREPLICATOR+ can search all spectra in the recently launched Global Natural Products Social molecular network and identify an order of magnitude more natural products than previous dereplication efforts. We further demonstrate that DEREPLICATOR+ enables cross-validation of genome-mining and peptidogenomics/glycogenomics results. New natural products can be identified via mass spectrometry by excluding all known ones from the analysis, a process called dereplication. Here, the authors extend a previously published dereplication algorithm to different classes of secondary metabolites.

CrAssphage is the most abundant human-associated virus and the founding member of a large group of bacteriophages, discovered in animal-associated and environmental metagenomes, that infect bacteria of the phylum Bacteroidetes. We analyze 4907 Circular Metagenome Assembled Genomes (cMAGs) of putative viruses from human gut microbiomes and identify nearly 600 genomes of crAss-like phages that account for nearly 87% of the DNA reads mapped to these cMAGs. Phylogenetic analysis of conserved genes demonstrates the monophyly of crAss-like phages, a putative virus order, and of 5 branches, potential families within that order, two of which have not been identified previously. The phage genomes in one of these families are almost twofold larger than the crAssphage genome (145-192 kilobases), with high density of self-splicing introns and inteins. Many crAss-like phages encode suppressor tRNAs that enable read-through of UGA or UAG stop-codons, mostly, in late phage genes. A distinct feature of the crAss-like phages is the recurrent switch of the phage DNA polymerase type between A and B families. Thus, comparative genomic analysis of the expanded assemblage of crAss-like phages reveals aspects of genome architecture and expression as well as phage biology that were not apparent from the previous work on phage genomics. Here, the authors analyze 4907 Circular Metagenome Assembled Genomes from human microbiomes and identify and characterize nearly 600 diverse genomes of crAss-like phages, finding two putative families with unusual genomic features, including high density of self-splicing introns and inteins.

Aggregated mass spectral data by consortia such as the Global Natural Products Social (GNPS) molecular networking infrastructure enable natural product discovery. DEREPLICATOR, validated on peptidic natural products, is a computational tool to identify known metabolites in complex samples. Peptidic natural products (PNPs) are widely used compounds that include many antibiotics and a variety of other bioactive peptides. Although recent breakthroughs in PNP discovery raised the challenge of developing new algorithms for their analysis, identification of PNPs via database search of tandem mass spectra remains an open problem. To address this problem, natural product researchers use dereplication strategies that identify known PNPs and lead to the discovery of new ones, even in cases when the reference spectra are not present in existing spectral libraries. DEREPLICATOR is a new dereplication algorithm that enables high-throughput PNP identification and that is compatible with large-scale mass-spectrometry-based screening platforms for natural product discovery. After searching nearly one hundred million tandem mass spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure, DEREPLICATOR identified an order of magnitude more PNPs (and their new variants) than any previous dereplication efforts.

Although the use of long-read sequencing improves the contiguity of assembled viral genomes compared to short-read methods, assembling complex viral communities remains an open problem. We describe the viralFlye tool for identification and analysis of metagenome-assembled viruses in long-read assemblies. We show it significantly improves viral assemblies and demonstrate that long-reads result in a much larger array of predicted virus-host associations as compared to short-read assemblies. We demonstrate that the identification of novel CRISPR arrays in bacterial genomes from a newly assembled metagenomic sample provides information for predicting novel hosts for novel viruses.

Recent advances in top-down mass spectrometry enabled identification of intact proteins, but this technology still faces challenges. For example, top-down mass spectrometry suffers from a lack of sensitivity since the ion counts for a single fragmentation event are often low. In contrast, nanopore technology is exquisitely sensitive to single intact molecules, but it has only been successfully applied to DNA sequencing, so far. Here, we explore the potential of sub-nanopores for single-molecule protein identification (SMPI) and describe an algorithm for identification of the electrical current blockade signal (nanospectrum) resulting from the translocation of a denaturated, linearly charged protein through a sub-nanopore. The analysis of identification p-values suggests that the current technology is already sufficient for matching nanospectra against small protein databases, e.g., protein identification in bacterial proteomes.

The V(D)J recombination forms the immunoglobulin genes by joining the variable (V), diversity (D), and joining (J) germline genes. Since variations in germline genes have been linked to various diseases, personalized immunogenomics aims at finding alleles of germline genes across various patients. Although recent studies described algorithms for inference of V and J genes from immunosequencing data, they stopped short of solving a more difficult problem of reconstructing D genes that form the highly divergent CDR3 regions and provide the most important contribution to the antigen binding. We present the IgScout algorithm for D gene reconstruction and apply it to reveal new alleles of human D genes and previously unknown D genes in camel, an important model organism in immunology. We further analyze non-canonical V(DD)J recombination that results in unusually long CDR3s with tandem fused IGHD genes and thus expands the diversity of the antibody repertoires. We demonstrate that tandem CDR3s represent a consistent and functional feature of all analyzed immunosequencing datasets, reveal ultra-long CDR3s, and shed light on the mechanism responsible for their formation.