The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Methods used to sequence the transcriptome often produce more than 200 million short sequences. We introduce StringTie, a computational method that applies a network flow algorithm originally developed in optimization theory, together with optional de novo assembly, to assemble these complex data sets into transcripts. When used to analyze both simulated and real data sets, StringTie produces more complete and accurate reconstructions of genes and better estimates of expression levels, compared with other leading transcript assembly programs including Cufflinks, IsoLasso, Scripture and Traph. For example, on 90 million reads from human blood, StringTie correctly assembled 10,990 transcripts, whereas the next best assembly was of 7,187 transcripts by Cufflinks, which is a 53% increase in transcripts assembled. On a simulated data set, StringTie correctly assembled 7,559 transcripts, which is 20% more than the 6,310 assembled by Cufflinks. As well as producing a more complete transcriptome assembly, StringTie runs faster on all data sets tested to date compared with other assembly software, including Cufflinks.

StringTie enables improved reconstruction of a transcriptome from RNA-seq reads

Motivation Recent advances in sequencing technologies promise ultra-long reads of ∼100 kb in average, full-length mRNA or cDNA reads in high throughput and genomic contigs over 100 Mb in length. Existing alignment programs are unable or inefficient to process such data at scale, which presses for the development of new alignment algorithms. Results Minimap2 is a general-purpose alignment program to map DNA or long mRNA sequences against a large reference database. It works with accurate short reads of ≥100 bp in length, ≥1 kb genomic reads at error rate ∼15%, full-length noisy Direct RNA or cDNA reads and assembly contigs or closely related full chromosomes of hundreds of megabases in length. Minimap2 does split-read alignment, employs concave gap cost for long insertions and deletions and introduces new heuristics to reduce spurious alignments. It is 3-4 times as fast as mainstream short-read mappers at comparable accuracy, and is ≥30 times faster than long-read genomic or cDNA mappers at higher accuracy, surpassing most aligners specialized in one type of alignment. Availability and implementation https://github.com/lh3/minimap2. Supplementary information Supplementary data are available at Bioinformatics online.

Minimap2: pairwise alignment for nucleotide sequences

Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of “marker” genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities.

/pdf/checkm-assessing-the-quality-of-microbial-genomes-recovered-2792hxp0ce.pdf

CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes

Summary: Limitations of genome sequencing techniques have led to dozens of assembly algorithms, none of which is perfect. A number of methods for comparing assemblers have been developed, but none is yet a recognized benchmark. Further, most existing methods for comparing assemblies are only applicable to new assemblies of finished genomes; the problem of evaluating assemblies of previously unsequenced species has not been adequately considered. Here, we present QUAST—a quality assessment tool for evaluating and comparing genome assemblies. This tool improves on leading assembly comparison software with new ideas and quality metrics. QUAST can evaluate assemblies both with a reference genome, as well as without a reference. QUAST produces many reports, summary tables and plots to help scientists in their research and in their publications. In this study, we used QUAST to compare several genome assemblers on three datasets. QUAST tables and plots for all of them are available in the Supplementary Material, and interactive versions of these reports are on the QUAST website.

QUAST: quality assessment tool for genome assemblies

Animals Male Sprague-Dawley rats (200-250 g) (Charles Rivers, St-Aubin-Lès-Elbeuf, France) were used. After arrival at the laboratory, the animals were allowed to acclimatize for one week in groups of 6 per cage with ad libitum access to food and water. The guidelines of the Committee for Research and Ethical Issue of the I.A.S.P. (Zimmermann, 1983) were followed. Great care was taken, particularly with regard to housing conditions, to avoid or minimise discomfort of the animals.

Online Supplementary Material

MOTIVATION Sequences produced by automated Sanger sequencing machines frequently contain fragments of the cloning vector on their ends. Software tools currently available for identifying and removing the vector sequence require knowledge of the vector sequence, specific splice sites and any adapter sequences used in the experiment-information often omitted from public databases. Furthermore, the clipping coordinates themselves are missing or incorrectly reported. As an example, within the approximately 1.24 billion shotgun sequences deposited in the NCBI Trace Archive, as many as approximately 735 million (approximately 60%) lack vector clipping information. Correct clipping information is essential to scientists attempting to validate, improve and even finish the increasingly large number of genomes released at a 'draft' quality level. RESULTS We present here Figaro, a novel software tool for identifying and removing the vector from raw sequence data without prior knowledge of the vector sequence. The vector sequence is automatically inferred by analyzing the frequency of occurrence of short oligo-nucleotides using Poisson statistics. We show that Figaro achieves 99.98% sensitivity when tested on approximately 1.5 million shotgun reads from Drosophila pseudoobscura. We further explore the impact of accurate vector trimming on the quality of whole-genome assemblies by re-assembling two bacterial genomes from shotgun sequences deposited in the Trace Archive. Designed as a module in large computational pipelines, Figaro is fast, lightweight and flexible. AVAILABILITY Figaro is released under an open-source license through the AMOS package (http://amos.sourceforge.net/Figaro).

Figaro: a novel statistical method for vector sequence removal.

We analyzed the whole genome sequence coverage in two versions of the Bos taurus genome and identified all regions longer than five kilobases (Kbp) that are duplicated within chromosomes with >99% sequence fidelity in both copies. We call these regions High Fidelity Duplications (HFDs). The two assemblies were Btau 4.2, produced by the Human Genome Sequencing Center at Baylor College of Medicine, and UMD Bos taurus 3.1 (UMD 3.1), produced by our group at the University of Maryland. We found that Btau 4.2 has a far greater number of HFDs, 3111 versus only 69 in UMD 3.1. Read coverage analysis shows that 39 million base pairs (Mbp) of sequence in HFDs in Btau 4.2 appear to be a result of a mis-assembly and therefore cannot be qualified as segmental duplications. UMD 3.1 has only 0.41 Mbp of sequence in HFDs that are due to a mis-assembly.

/pdf/mis-assembled-segmental-duplications-in-two-versions-of-the-2ge7wda2i0.pdf

Mis-assembled "segmental duplications" in two versions of the Bos taurus genome.

The assembly methods used for whole-genome shotgun (WGS) data have a major impact on the quality of resulting draft genomes. We present a novel algorithm to generate a set of “reliable” overlaps based on identifying repeat k-mers. To demonstrate the benefits of using reliable overlaps, we have created a version of the Phrap assembly program that uses only overlaps from a specific list. We call this version PhrapUMD. Integrating PhrapUMD and our “reliable-overlap” algorithm with the Baylor College of Medicine assembler, Atlas, we assemble the BACs from the Rattus norvegicus genome project. Starting with the same data as the Nov. 2002 Atlas assembly, we compare our results and the Atlas assembly to the 4.3 Mb of rat sequence in the 21 BACs that have been finished. Our version of the draft assembly of the 21 BACs increases the coverage of finished sequence from 93.4% to 96.3%, while simultaneously reducing the base error rate from 4.5 to 1.1 errors per 10,000 bases. There are a number of ways of assessing the relative merits of assemblies when the finished sequence is available. If one views the overall quality of an assembly as proportional to the inverse of the product of the error rate and sequence missed, then the assembly presented here is seven times better. The UMD Overlapper with options for reliable overlaps is available from the authors at http://www.genome.umd.edu. We also provide the changes to the Phrap source code enabling it to use only the reliable overlaps.

/pdf/improving-phrap-based-assembly-of-the-rat-using-reliable-8ygxpifr99.pdf

Improving Phrap-based assembly of the rat using "reliable" overlaps.

We present an algorithm to generate a set of highly reliable overlaps based on identifying repeat k-mers. This method does not require uniform coverage. We also describe an error correction method based on multi-sequence comparison, that allows extending usable sequence in reads trimmed to 16% error rate. We use a version of the Phrap assembly program that uses only overlaps computed by the UMD overlapper, called PhrapUMD. We integrate the University of Maryland algorithms with Baylor’s ATLAS assembler applied to Rattus norvegicus. Starting with the same data as the Nov. 2002 ATLAS assembly, we compare our results to 4.5 Mbp of rat sequence in 21 BACs that have been finished. We find that after extension and error correction, (i) the reads are up to 30% longer than reads trimmed to 2%; (ii) the average error rate across the extended reads is about 3 in 10,000 bases, with 88% of the extended reads matching finished sequence exactly across their entire length; and (iii) PhrapUMD with these reads and our reliable overlaps produces a draft assembly of the rat which has no misassemblies and increases the coverage of finished sequence from 93.7% to 96.7%, while simultaneously reducing the base error rate from 4.5 to 2.0 errors per 10,000 bases.

http://yorke.umd.edu/papers/genome_papers/Improving%20sequence%20assemble%20rat.pdf

Michael Roberts

Papers

Online Supplementary Material

Figaro: a novel statistical method for vector sequence removal.

Mis-assembled "segmental duplications" in two versions of the Bos taurus genome.

Improving Phrap-based assembly of the rat using "reliable" overlaps.

Improving Sequence Assembly of the Rat Genome Using Reliable Overlaps and Extended Reads