Biology subjects

Koren, S.

Publications and source records attributed to Koren, S..

16 recordsLinked to original sources

bioRxiv2018

HLA*PRG:LA - HLA typing from linearly projected graph alignments

SummaryHLA*PRG:LA implements a new graph alignment model for HLA type inference, based on the projection of linear alignments onto a variation graph. It enables accurate HLA type inference from whole-genome (99% accuracy) and whole-exome (93% accuracy) Illumina data; from long-read Oxford Nanopore and Pacific Biosciences data (98% accuracy for whole-genome and targeted data); and from genome assemblies. Computational requirements for a typical sample vary between 0.7 and 14 CPU hours per sample.\n\nAvailability and ImplementationHLA*PRG:LA is implemented in C++ and Perl and freely available from https://github.com/DiltheyLab/HLA-PRG-LA (GPL v3).\n\nContactalexander.dilthey@med.uni-duesseldorf.de\n\nSupplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2018

Leveraging evolutionary relationships to improve Anopheles genome assemblies

While new sequencing technologies have lowered financial barriers to whole genome sequencing, resulting assemblies are often fragmented and far from finished. Subsequent improvements towards chromosomal-level status can be achieved by both experimental and computational approaches. Requiring only annotated assemblies and gene orthology data, comparative genomics approaches that aim to capture evolutionary signals to predict scaffold neighbours (adjacencies) offer potentially substantive improvements without the costs associated with experimental scaffolding or re-sequencing. We leverage the combined detection power of three such gene synteny-based methods applied to 21 Anopheles mosquito assemblies with variable contiguity levels to produce consensus sets of scaffold adjacency predictions. Three complementary validations were performed on subsets of assemblies with additional supporting data: six with physical mapping data; 13 with paired-end RNA sequencing (RNAseq) data; and three with new assemblies based on re-scaffolding or incorporating Pacific Biosciences (PacBio) sequencing data. Improved assemblies were built by integrating the consensus adjacency predictions with supporting experimental data, resulting in 20 new reference assemblies with improved contiguities. Combined with physical mapping data for six anophelines, chromosomal positioning of scaffolds improved assembly anchoring by 47% for A. funestus and 38% A. stephensi. Reconciling an A. funestus PacBio assembly with synteny-based and RNAseq-based adjacencies and physical mapping data resulted in a new 81.5% chromosomally mapped reference assembly and cytogenetic photomap. While complementary experimental data are clearly key to achieving high-quality chromosomal-level assemblies, our assessments and validations of gene synteny-based computational methods highlight the utility of applying comparative genomics approaches to improve community genomic resources.

genomics↗

bioRxiv2018

MetaMaps - Strain-level metagenomic assignment and compositional estimation for long reads

Metagenomic sequence classification should be fast, accurate and information-rich. Emerging long-read sequencing technologies promise to improve the balance between these factors but most existing methods were designed for short reads. MetaMaps is a new method, specifically developed for long reads, that combines the accuracy of slower alignment-based methods with the scalability of faster k-mer-based methods. Using an approximate mapping algorithm, it is capable of mapping a long-read metagenome to a comprehensive RefSeq database with >12,000 genomes in <30 GB or RAM on a laptop computer. Integrating these mappings with a probabilistic scoring scheme and EM-based estimation of sample composition, MetaMaps achieves >95% accuracy for species-level read assignment and r2 > 0.98 for the estimation of sample composition on both simulated and real data. Uniquely, MetaMaps outputs mapping locations and qualities for all classified reads, enabling functional studies (e.g. gene presence/absence) and the detection of novel species not present in the current database.\n\nAvailability and ImplementationMetaMaps is implemented in C++/Perl and freely available from https://github.com/DiltheyLab/MetaMaps (GPL v3).

bioinformatics↗

bioRxiv2018

De Novo assembly of the goldfish (Carassius auratus) genome and the evolution of genes after whole genome duplication

For over a thousand years throughout Asia, the common goldfish (Carassius auratus) was raised for both food and as an ornamental pet. Selective breeding over more than 500 years has created a wide array of body and pigmentation variation particularly valued by ornamental fish enthusiasts. As a very close relative of the common carp (Cyprinus carpio), goldfish shares the recent genome duplication that occurred approximately 14-16 million years ago (mya) in their common ancestor. The combination of centuries of breeding and a wide array of interesting body morphologies is an exciting opportunity to link genotype to phenotype as well as understanding the dynamics of genome evolution and speciation. Here we generated a high-quality draft sequence of a \"Wakin\" goldfish using 71X PacBio long-reads. We identified 70,324 coding genes and more than 11,000 non-coding transcripts. We found that the two sub-genomes in goldfish retained extensive synteny and collinearity between goldfish and zebrafish. However, \"ohnologous\" genes were lost quickly after the carp whole-genome duplication, and the expression of 30% of the retained duplicated gene diverged significantly across seven tissues sampled. Loss of sequence identity and/or exons determined the divergence of the expression across all tissues, while loss of conserved, non-coding elements determined expression variance between different tissues. This draft assembly also provides an important resource for comparative genomics with the very commonly used zebrafish model (Danio rerio), and for understanding the underlying genetic causes of goldfish variants.

genomics↗

bioRxiv2018

Amycomicin: a potent and specific antibiotic discovered with a targeted interaction screen

The rapid emergence of antibiotic-resistant pathogenic bacteria has accelerated the search for new antibiotics. Many clinically used antibacterials were discovered through culturing a single microbial species under nutrient-rich conditions, but in the environment, bacteria constantly encounter poor nutrient conditions and interact with neighboring microbial species. In an effort to recapitulate this environment we generated a nine-strain Actinomycete community and used 16S rDNA sequencing to deconvolute the stochastic production of antimicrobial activity that was not observed from any of the axenic cultures. We subsequently simplified the community to just two strains and identified Amycolatopsis sp. AA4 as the producing strain and Streptomyces coelicolor M145 as an inducing strain. Bioassay-guided isolation identified amycomicin, a highly modified fatty acid containing an epoxide isonitrile warhead as a potent and specific inhibitor of Staphylococcus aureus. Amycomicin targets an essential enzyme in fatty acid biosynthesis (FabH) and reduces S. aureus infection in a mouse skin infection model. The discovery of amycomicin demonstrates the utility of screening complex communities against specific targets to discover small-molecule antibiotics.\n\nSignificanceBacteria, especially actinomycetes, produce the majority of our clinically useful small-molecule antibiotics. Genomic analyses of antibiotic-producing strains indicate that earlier discovery efforts found only a fraction of the likely antibiotic candidates. In an effort to uncover these previously missed candidates we developed an approach that utilizes the ability of microbial communities to produce antibiotics that are not produced by any single member in isolation. Successful communities were established and deconvoluted to identify both producers and inducers of antibiotic activity. One inducer-producer pair made amycomicin, a potent and specific antibiotic against Staphylococcus aureus, an important human pathogen. Amycomicin targets fatty acid biosynthesis and exhibits in vivo efficacy against skin infections in a mouse model.

microbiology↗

bioRxiv2018

RefSeq database growth influences the accuracy of k-mer-based species identification

Accurate species-level taxonomic classification and profiling of complex microbial communities remains a challenge due to homologous regions shared among closely related species and a sparse representation of non-human associated microbes in the database. Although the database undoubtedly has a strong influence on the sensitivity of taxonomic classifiers and profilers, to date, no study has carefully explored this topic on historical RefSeq releases and explored its impact on accuracy. In this study, we examined the influence of the database, over time, on k-mer based sequence classification and profiling. We present three major findings: (i) database growth over time resulted in more classified reads, but fewer species-level classifications and more species-level misclassifications; (ii) Bayesian re-estimation of abundance helped to recover species-level classifications when the exact target strain was present; and (iii) Bayesian reestimation struggled when the database lacked the target strain, resulting in a notable decrease in accuracy. In summary, our findings suggest that the growth of RefSeq over time has strongly influenced the accuracy of k-mer based classification and profiling methods, resulting in different classification results depending on the particular database used. These results suggest a need for new algorithms specially adapted for large genome collections and better measures of classification uncertainty.

bioinformatics↗

bioRxiv2018

Complete assembly of parental haplotypes with trio binning

Reference genome projects have historically selected inbred individuals to minimize heterozygosity and simplify assembly. We challenge this dogma and present a new approach designed specifically for heterozygous genomes. \"Trio binning\" uses short reads from two parental genomes to partition long reads from an offspring into haplotype-specific sets prior to assembly. Each haplotype is then assembled independently, resulting in a complete diploid reconstruction. On a benchmark human trio, this method achieved high accuracy and recovered complex structural variants missed by alternative approaches. To demonstrate its effectiveness on a heterozygous genome, we sequenced an F1 cross between cattle subspecies Bos taurus taurus and Bos taurus indicus, and completely assembled both parental haplotypes with NG50 haplotig sizes >20 Mbp and 99.998% accuracy, surpassing the quality of current cattle reference genomes. We propose trio binning as a new best practice for diploid genome assembly that will enable new studies of haplotype variation and inheritance.

genomics↗

bioRxiv2018

Integrating Hi-C links with assembly graphs for chromosome-scale assembly

Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, there are limited open-source tools available. Errors, particularly inversions and fusions across chromosomes, remain higher than alternate scaffolding technologies. We present a novel open-source Hi-C scaffolder that does not require an a priori estimate of chromosome number and minimizes errors by scaffolding with the assistance of an assembly graph. We demonstrate higher accuracy than the state-of-the-art methods across a variety of Hi-C library preparations and input assembly sizes. The Python and C++ code for our method is openly available at https://github.com/machinegun/SALSA\n\nAuthor summaryHi-C technology was originally proposed to study the 3D organization of a genome. Recently, it has also been applied to assemble large eukaryotic genomes into chromosome-scale scaffolds. Despite this, there are few open source methods to generate these assemblies. Existing methods are also prone to small inversion errors due to noise in the Hi-C data. In this work, we address these challenges and develop a method, named SALSA2. SALSA2 uses sequence overlap information from an assembly graph to correct inversion errors and provide accurate chromosome-scale assemblies.

bioinformatics↗

bioRxiv2018

A Fast Adaptive Algorithm for Computing Whole-Genome Homology Maps

MotivationWhole-genome alignment is an important problem in genomics for comparing different species, mapping draft assemblies to reference genomes, and identifying repeats. However, for large plant and animal genomes, this task remains compute and memory intensive.\n\nResultsWe introduce an approximate algorithm for computing local alignment boundaries between long DNA sequences. Given a minimum alignment length and an identity threshold, our algorithm computes the desired alignment boundaries and identity estimates using kmer-based statistics, and maintains sufficient probabilistic guarantees on the output sensitivity. Further, to prioritize higher scoring alignment intervals, we develop a plane-sweep based filtering technique which is theoretically optimal and practically efficient. Implementation of these ideas resulted in a fast and accurate assembly-to-genome and genome-to-genome mapper. As a result, we were able to map an error-corrected whole-genome NA12878 human assembly to the hg38 human reference genome in about one minute total execution time and < 4 GB memory using 8 CPU threads, achieving more than an order of magnitude improvement in both runtime and memory over competing methods. Recall accuracy of computed alignment boundaries was consistently found to be > 97% on multiple datasets. Finally, we performed a sensitive self-alignment of the human genome to compute all duplications of length [≥] 1 Kbp and [≥] 90% identity. The reported output achieves good recall and covers 5% more bases than the current UCSC genome browsers segmental duplication annotation.\n\nAvailabilityhttps://github.com/marbl/MashMap\n\nContactadam.phillippy@nih.gov, aluru@cc.gatech.edu

bioinformatics↗

bioRxiv2017

Improved Aedes aegypti mosquito reference genome assembly enables biological discovery and vector control

Female Aedes aegypti mosquitoes infect hundreds of millions of people each year with dangerous viral pathogens including dengue, yellow fever, Zika, and chikungunya. Progress in understanding the biology of this insect, and developing tools to fight it, has been slowed by the lack of a high-quality genome assembly. Here we combine diverse genome technologies to produce AaegL5, a dramatically improved and annotated assembly, and demonstrate how it accelerates mosquito science and control. We anchored the physical and cytogenetic maps, resolved the size and composition of the elusive sex-determining \"M locus\", significantly increased the known members of the glutathione-S-transferase genes important for insecticide resistance, and doubled the number of chemosensory ionotropic receptors that guide mosquitoes to human hosts and egg-laying sites. Using high-resolution QTL and population genomic analyses, we mapped new candidates for dengue vector competence and insecticide resistance. We predict that AaegL5 will catalyse new biological insights and intervention strategies to fight this deadly arboviral vector.

genomics↗

bioRxiv2017

MetaCompass: Reference-guided Assembly of Metagenomes

Metagenomic studies have primarily relied on de novo approaches for reconstructing genes and genomes from microbial mixtures. While database driven approaches have been employed in certain analyses, they have not been used in the assembly of metagenomes. Here we describe the first effective approach for reference-guided metagenomic assembly of low-abundance bacterial genomes that can complement and improve upon de novo metagenomic assembly methods. When combined with de novo assembly approaches, we show that MetaCompass can generate more complete assemblies than can be obtained by de novo assembly alone, and improve on assemblies from the Human Microbiome Project (over 2,000 samples).

bioinformatics↗

bioRxiv2017

De novo long-read assembly of a complex animal genome

Eukaryotic genome assembly remains a challenge in part because of the prevalence of complex DNA repeats. This is a particularly acute problem for holocentric nematodes because of the large number of satellite DNA sequences found throughout their genomes. These have been recalcitrant to most genome sequencing methods. At the same time, many nematodes are parasites and some represent a serious threat to human health. There is a pressing need for better molecular characterization of animal and plant parasitic nematodes. The advent of long-read DNA sequencing methods offers the promise of resolving complex genomes. Using Nippostrongylus brasiliensis as a test case, applying improved base-calling algorithms and assembly methods, we demonstrate the feasibility of de novo genome assembly matching current community standards using only MinION long reads. In doing so, we uncovered an unexpected diversity of very long and complex DNA repeat sequences, including massive tandem repeats of tRNA genes. The method has the added advantage of preserving haplotypic variants and so has the potential to be used in population analyses.

genomics↗

bioRxiv2017

Analysis of the Aedes albopictus C6/36 genome provides insight into cell line adaptations to in vitro viral propagation

BackgroundThe 50-year old Aedes albopictus C6/36 cell line is a resource for the detection, amplification, and analysis of mosquito-borne viruses including Zika, dengue, and chikungunya. The cell line is derived from an unknown number of larvae from an unspecified strain of Aedes albopictus mosquitoes. Toward improved utility of the cell line for research in virus transmission, we present an annotated assembly of the C6/36 genome.\n\nResultsThe C6/36 genome assembly has the largest contig N50 (3.3 Mbp) of any mosquito assembly, presents the sequences of both haplotypes for most of the diploid genome, reveals independent null mutations in both alleles of the Dicer locus, and indicates a male-specific genome. Gene annotation was computed with publicly available mosquito transcript sequences. Gene expression data from cell line RNA sequence identified enrichment of growth-related pathways and conspicuous deficiency in aquaporins and inward rectifier K+ channels. As a test of utility, RNA sequence data from Zika-infected cells was mapped to the C6/36 genome and transcriptome assemblies. Host subtraction reduced the data set by 89%, enabling faster characterization of non-host reads.\n\nConclusionsThe C6/36 genome sequence and annotation should enable additional uses of the cell line to study arbovirus vector interactions and interventions aimed at restricting the spread of human disease.

genomics↗

bioRxiv2017

Nanopore sequencing and assembly of a human genome with ultra-long reads

Nanopore sequencing is a promising technique for genome sequencing due to its portability, ability to sequence long reads from single molecules, and to simultaneously assay DNA methylation. However until recently nanopore sequencing has been mainly applied to small genomes, due to the limited output attainable. We present nanopore sequencing and assembly of the GM12878 Utah/Ceph human reference genome generated using the Oxford Nanopore MinION and R9.4 version chemistry. We generated 91.2 Gb of sequence data ([~]30x theoretical coverage) from 39 flowcells. De novo assembly yielded a highly complete and contiguous assembly (NG50 [~]3Mb). We observed considerable variability in homopolymeric tract resolution between different basecallers. The data permitted sensitive detection of both large structural variants and epigenetic modifications. Further we developed a new approach exploiting the long-read capability of this system and found that adding an additional 5x-coverage of ultra-long reads (read N50 of 99.7kb) more than doubled the assembly contiguity. Modelling the repeat structure of the human genome predicts extraordinarily contiguous assemblies may be possible using nanopore reads alone. Portable de novo sequencing of human genomes may be important for rapid point-of-care diagnosis of rare genetic diseases and cancer, and monitoring of cancer progression. The complete dataset including raw signal is available as an Amazon Web Services Open Dataset at: https://github.com/nanopore-wgs-consortium/NA12878.

genomics↗

bioRxiv2017

A fast approximate algorithm for mapping long reads to large reference databases

Emerging single-molecule sequencing technologies from Pacific Biosciences and Oxford Nanopore have revived interest in long read mapping algorithms. Alignment-based seed-and-extend methods demonstrate good accuracy, but face limited scalability, while faster alignment-free methods typically trade decreased precision for efficiency. In this paper, we combine a fast approximate read mapping algorithm based on minimizers with a novel MinHash identity estimation technique to achieve both scalability and precision. In contrast to prior methods, we develop a mathematical framework that defines the types of mapping targets we uncover, establish probabilistic estimates of p-value and sensitivity, and demonstrate tolerance for alignment error rates up to 20%. With this framework, our algorithm automatically adapts to different minimum length and identity requirements and provides both positional and identity estimates for each mapping reported. For mapping human PacBio reads to the hg38 reference, our method is 290x faster than BWA-MEM with a lower memory footprint and recall rate of 96%. We further demonstrate the scalability of our method by mapping noisy PacBio reads (each [≥] 5 kbp in length) to the complete NCBI RefSeq database containing 838 Gbp of sequence and > 60, 000 genomes.

bioinformatics↗

bioRxiv2016

Scaffolding of long read assemblies using long range contact information

MotivationLong read technologies have made a revolution in de novo genome assembly by generating contigs of size orders of magnitude more than that of short read assemblies. Although the assembly contiguity has increased, it still does not span a chromosome or an arm of the chromosome, resulting in an unfinished chromosome level assembly. To address this problem, we develop a scalable and computationally efficient scaffolding method that can boost the contiguity of the assembly by a large extent using genome wide chromatin interaction data such as Hi-C. Particularly, we demonstrate an algorithm that uses Hi-C data for longer-range scaffolding of de novo long read genome assemblies.\n\nResultsWe tested our methods on two long read assemblies of different organisms. We compared our method with previously developed method and show that our approach performs better in terms of accuracy of scaffolding.\n\nAvailabilityThe software is available for free use and can be downloaded from here: https://github.com/machinegun/hi-c-scaffold\n\nContactjchin@pacificbiosciences.com

genomics↗