Biology subjects

Sergey Koren

Publications and source records attributed to Sergey Koren.

9 recordsLinked to original sources

bioRxiv2016

Evaluation of GRCh38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly

The human reference genome assembly plays a central role in nearly all aspects of todays basic and clinical research. GRCh38 is the first coordinate-changing assembly update since 2009 and reflects the resolution of roughly 1000 issues and encompasses modifications ranging from thousands of single base changes to megabase-scale path reorganizations, gap closures and localization of previously orphaned sequences. We developed a new approach to sequence generation for targeted base updates and used data from new genome mapping technologies and single haplotype resources to identify and resolve larger assembly issues. For the first time, the reference assembly contains sequence-based representations for the centromeres. We also expanded the number of alternate loci to create a reference that provides a more robust representation of human population variation. We demonstrate that the updates render the reference an improved annotation substrate, alter read alignments in unchanged regions and impact variant interpretation at clinically relevant loci. We additionally evaluated a collection of new de novo long-read haploid assemblies and conclude that while the new assemblies compare favorably to the reference with respect to continuity, error rate, and gene completeness, the reference still provides the best representation for complex genomic regions and coding sequences. We assert that the collected updates in GRCh38 make the newer assembly a more robust substrate for comprehensive analyses that will promote our understanding of human biology and advance our efforts to improve health.

Genomics↗

bioRxiv2016

Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation

Long-read single-molecule sequencing has revolutionized de novo genome assembly and enabled the automated reconstruction of reference-quality genomes. However, given the relatively high error rates of such technologies, efficient and accurate assembly of large repeats and closely related haplotypes remains challenging. We address these issues with Canu, a successor of Celera Assembler that is specifically designed for noisy single-molecule sequences. Canu introduces support for nanopore sequencing, halves depth-of-coverage requirements, and improves assembly continuity while simultaneously reducing runtime by an order of magnitude on large genomes versus Celera Assembler 8.2. These advances result from new overlapping and assembly algorithms, including an adaptive overlapping strategy based on tf-idf weighted MinHash and a sparse assembly graph construction that avoids collapsing diverged repeats and haplotypes. We demonstrate that Canu can reliably assemble complete microbial genomes and near-complete eukaryotic chromosomes using either PacBio or Oxford Nanopore technologies, and achieves a contig NG50 of greater than 21 Mbp on both human and Drosophila melanogaster PacBio datasets. For assembly structures that cannot be linearly represented, Canu provides graph-based assembly outputs in graphical fragment assembly (GFA) format for analysis or integration with complementary phasing and scaffolding techniques. The combination of such highly resolved assembly graphs with long-range scaffolding information promises the complete and automated assembly of complex genomes.

Bioinformatics↗

bioRxiv2016

The evolution of the natural killer complex; a comparison between mammals using new high-quality genome assemblies and targeted annotation

Natural killer (NK) cells are a diverse population of lymphocytes with a range of biological roles including essential immune functions. NK cell diversity is created by the differential expression of cell surface receptors which modulate activation and function, including multiple subfamilies of C-type lectin receptors encoded within the NK gene complex (NKC). Little is known about the gene content of the NKC beyond rodent and primate lineages, other than it appears to be extremely variable between mammalian groups. We compared the NKC structure between mammalian species using new high quality draft genome assemblies for cattle and goat, re-annotated sheep, pig and horse genome assemblies and the published human, rat and mouse lemur NKC. The major NKC genes are largely in syntenic positions in all eight species, with significant independent expansions and deletions between species, allowing us to present a model for NKC evolution during mammalian radiation. The ruminant species, cattle and goats, have independently evolved a second KLRC locus flanked by KLRA and KLRJ and a novel KLRH-like gene has acquired an activating tail. This novel gene has duplicated several times within cattle, while other activating receptor genes have been selectively disrupted. Targeted genome enrichment in cattle identified varying levels of allelic polymorphism between these NKC genes concentrated in the predicted extracellular ligand binding domains. This novel recombination and allelic polymorphism is consistent with NKC evolution under balancing selection, suggesting this diversity influences individual immune responses and may impact on differential outcomes of pathogen infection and vaccination.

Genetics↗

bioRxiv2016

Hybrid assembly of the large and highly repetitive genome of Aegilops tauschii, a progenitor of bread wheat, with the mega-reads algorithm

Long sequencing reads generated by single-molecule sequencing technology offer the possibility of dramatically improving the contiguity of genome assemblies. The biggest challenge today is that long reads have relatively high error rates, currently around 15%. The high error rates make it difficult to use this data alone, particularly with highly repetitive plant genomes. Errors in the raw data can lead to insertion or deletion errors (indels) in the consensus genome sequence, which in turn create significant problems for downstream analysis; for example, a single indel may shift the reading frame and incorrectly truncate a protein sequence. Here we describe an algorithm that solves the high error rate problem by combining long, high-error reads with shorter but much more accurate Illumina sequencing reads, whose error rates average <1%. Our hybrid assembly algorithm combines these two types of reads to construct mega-reads, which are both long and accurate, and then assembles the mega-reads using the CABOG assembler, which was designed for long reads. We apply this technique to a large data set of Illumina and PacBio sequences from the species Aegilops tauschii, a large and highly repetitive plant genome that has resisted previous attempts at assembly. We show that the resulting assembled contigs are far larger than in any previous assembly, with an N50 contig size of 486,807. We compare the contigs to independently produced optical maps to evaluate their large-scale accuracy, and to a set of high-quality bacterial artificial chromosome (BAC)-based assemblies to evaluate base-level accuracy.

Bioinformatics↗

bioRxiv2016

Single-molecule sequencing and conformational capture enable de novo mammalian reference genomes

The decrease in sequencing cost and increased sophistication of assembly algorithms for short-read platforms has resulted in a sharp increase in the number of species with genome assemblies. However, these assemblies are highly fragmented, with many gaps, ambiguities, and errors, impeding downstream applications. We demonstrate current state of the art for de novo assembly using the domestic goat (Capra hircus), based on long reads for contig formation, short reads for consensus validation, and scaffolding by optical and chromatin interaction mapping. These combined technologies produced the most contiguous de novo mammalian assembly to date, with chromosome-length scaffolds and only 663 gaps. Our assembly represents a >250-fold improvement in contiguity compared to the previously published C. hircus assembly, and better resolves repetitive structures longer than 1 kb, supporting the most complete repeat family and immune gene complex representation ever produced for a ruminant species.

Genomics↗

bioRxiv2015

Mash: fast genome and metagenome distance estimation using MinHash

Mash extends the MinHash dimensionality-reduction technique to include a pairwise mutation distance and P-value significance test, enabling the efficient clustering and search of massive sequence collections. Mash reduces large sequences and sequence sets to small, representative sketches, from which global mutation distances can be rapidly estimated. We demonstrate several use cases, including the clustering of all 54,118 NCBI RefSeq genomes in 33 CPU hours; real-time database search using assembled or unassembled Illumina, Pacific Biosciences, and Oxford Nanopore data; and the scalable clustering of hundreds of metagenomic samples by composition. Mash is freely released under a BSD license (https://github.com/marbl/mash).

Bioinformatics↗

bioRxiv2014

Assembling Large Genomes with Single-Molecule Sequencing and Locality Sensitive Hashing

We report reference-grade de novo assemblies of four model organisms and the human genome from single-molecule, real-time (SMRT) sequencing. Long-read SMRT sequencing is routinely used to finish microbial genomes, but the available assembly methods have not scaled well to larger genomes. Here we introduce the MinHash Alignment Process (MHAP) for efficient overlapping of noisy, long reads using probabilistic, locality-sensitive hashing. Together with Celera Assembler, MHAP was used to reconstruct the genomes of Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, Drosophila melanogaster, and human from high-coverage SMRT sequencing. The resulting assemblies include fully resolved chromosome arms and close persistent gaps in these important reference genomes, including heterochromatic and telomeric transition sequences. For D. melanogaster, MHAP achieved a 600-fold speedup relative to prior methods and a cloud computing cost of a few hundred dollars. These results demonstrate that single-molecule sequencing alone can produce near-complete eukaryotic genomes at modest cost.

Bioinformatics↗

bioRxiv2014

Rapid Core-Genome Alignment and Visualization for Thousands of Intraspecific Microbial Genomes

Though many microbial species or clades now have hundreds of sequenced genomes, existing whole-genome alignment methods do not efficiently handle comparisons on this scale. Here we present the Harvest suite of core-genome alignment and visualization tools for quickly analyzing thousands of intraspecific microbial strains. Harvest includes Parsnp, a fast core-genome multi-aligner, and Gingr, a dynamic visual platform. Combined they provide interactive core-genome alignments, variant calls, recombination detection, and phylogenetic trees. Using simulated and real data we demonstrate that our approach exhibits unrivaled speed while maintaining the accuracy of existing methods. The Harvest suite is open-source and freely available from: http://github.com/marbl/harvest.

Bioinformatics↗

bioRxiv2014

Automated ensemble assembly and validation of microbial genomes

BackgroundThe continued democratization of DNA sequencing has sparked a new wave of development of genome assembly and assembly validation methods. As individual research labs, rather than centralized centers, begin to sequence the majority of new genomes, it is important to establish best practices for genome assembly. However, recent evaluations such as GAGE and the Assemblathon have concluded that there is no single best approach to genome assembly. Instead, it is preferable to generate multiple assemblies and validate them to determine which is most useful for the desired analysis; this is a labor-intensive process that is often impossible or unfeasible.\n\nResultsTo encourage best practices supported by the community, we present iMetAMOS, an automated ensemble assembly pipeline; iMetAMOS encapsulates the process of running, validating, and selecting a single assembly from multiple assemblies. iMetAMOS packages several leading open-source tools into a single binary that automates parameter selection and execution of multiple assemblers, scores the resulting assemblies based on multiple validation metrics, and annotates the assemblies for genes and contaminants. We demonstrate the utility of the ensemble process on 225 previously unassembled Mycobacterium tuberculosis genomes as well as a Rhodobacter sphaeroides benchmark dataset. On these real data, iMetAMOS reliably produces validated assemblies and identifies potential contamination without user intervention. In addition, intelligent parameter selection produces assemblies of R. sphaeroides that exceed the quality of those from the GAGE-B evaluation, affecting the relative ranking of some assemblers.\n\nConclusionsEnsemble assembly with iMetAMOS provides users with multiple, validated assemblies for each genome. Although computationally limited to small or mid-sized genomes, this approach is the most effective and reproducible means for generating high-quality assemblies and enables users to select an assembly best tailored to their specific needs.

Bioinformatics↗