Biology subjects

Phillippy, A. M.

Publications and source records attributed to Phillippy, A. M..

10 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

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

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

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

High-throughput ANI Analysis of 90K Prokaryotic Genomes Reveals Clear Species Boundaries

A fundamental question in microbiology is whether there is a continuum of genetic diversity among genomes or clear species boundaries prevail instead. Answering this question requires robust measurement of whole-genome relatedness among thousands of genomes and from diverge phylogenetic lineages. Whole-genome similarity metrics such as Average Nucleotide Identity (ANI) can provide the resolution needed for this task, overcoming several limitations of traditional techniques used for the same purposes. Although the number of genomes currently available may be adequate, the associated bioinformatics tools for analysis are lagging behind these developments and cannot scale to large datasets. Here, we present a new method, FastANI, to compute ANI using alignment-free approximate sequence mapping. Our analyses demonstrate that FastANI produces an accurate ANI estimate and is up to three orders of magnitude faster when compared to an alignment (e.g., BLAST)-based approach. We leverage FastANI to compute pairwise ANI values among all prokaryotic genomes available in the NCBI database. Our results reveal a clear genetic discontinuity among the database genomes, with 99.8% of the total 8 billion genome pairs analyzed showing either >95% intra-species ANI or <83% inter-species ANI values. We further show that this discontinuity is recovered with or without the most frequently represented species in the database and is robust to historic additions in the public genome databases. Therefore, 95% ANI represents an accurate threshold for demarcating almost all currently named prokaryotic species, and wide species boundaries may exist for prokaryotes.

bioinformatics↗

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↗