Improving draft assemblies by iterative mapping and assembly of short reads to eliminate gaps.
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ABSTRACT:
SUBMITTER: Tsai IJ
PROVIDER: S-EPMC2884544 | biostudies-literature | 2010
REPOSITORIES: biostudies-literature
Publications
Improving draft assemblies by iterative mapping and assembly of short reads to eliminate gaps.
Tsai Isheng J IJ Otto Thomas D TD Berriman Matthew M
Genome biology 20100413 4
Advances in sequencing technology allow genomes to be sequenced at vastly decreased costs. However, the assembled data frequently are highly fragmented with many gaps. We present a practical approach that uses Illumina sequences to improve draft genome assemblies by aligning sequences against contig ends and performing local assemblies to produce gap-spanning contigs. The continuity of a draft genome can thus be substantially improved, often without the need to generate new data. ...[more]
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Project description:BackgroundClosing gaps in draft genomes is an important post processing step in genome assembly. It leads to more complete genomes, which benefits downstream genome analysis such as annotation and genotyping. Several tools have been developed for gap closing. However, these tools don't fully utilize the information contained in the sequence data. For example, while it is known that many gaps are caused by genomic repeats, existing tools often ignore many sequence reads that originate from a repeat-related gap.ResultsWe compare GAPPadder with GapCloser, GapFiller and Sealer on one bacterial genome, human chromosome 14 and the human whole genome with paired-end and mate-paired reads with both short and long insert sizes. Empirical results show that GAPPadder can close more gaps than these existing tools. Besides closing gaps on draft genomes assembled only from short sequence reads, GAPPadder can also be used to close gaps for draft genomes assembled with long reads. We show GAPPadder can close gaps on the bed bug genome and the Asian sea bass genome that are assembled partially and fully with long reads respectively. We also show GAPPadder is efficient in both time and memory usage.ConclusionIn this paper, we propose a new approach called GAPPadder for gap closing. The main advantage of GAPPadder is that it uses more information in sequence data for gap closing. In particular, GAPPadder finds and uses reads that originate from repeat-related gaps. We show that these repeat-associated reads are useful for gap closing, even though they are ignored by all existing tools. Other main features of GAPPadder include utilizing the information in sequence reads with different insert sizes and performing two-stage local assembly of gap sequences. The results show that our method can close more gaps than several existing tools. The software tool, GAPPadder, is available for download at https://github.com/Reedwarbler/GAPPadder .
| S-EPMC6551238 | biostudies-literature
Project description:The reconstruction of the complete genome sequence of an organism is an important point for comparative, functional and evolutionary genomics. Nevertheless, overcoming the problems encountered while completing the sequence of an entire genome can still be demanding in terms of time and resources. We have developed Enly, a simple tool based on the iterative mapping of sequence reads at contig edges, capable to extend the genomic contigs deriving from high-throughput sequencing, especially those deriving by Newbler-like assemblies. Testing it on a set of de novo draft genomes led to the closure of up to 20% of the gaps originally present. Enly is cross-platform and most of the steps of its pipeline are parallelizable, making easy and fast to improve a draft genome resulting from a de novo assembly.
| S-EPMC4091449 | biostudies-literature
Project description:BACKGROUND:The advent of third-generation sequencing (TGS) technologies opens the door to improve genome assembly. Long reads are promising for enhancing the quality of fragmented draft assemblies constructed from next-generation sequencing (NGS) technologies. To date, a few algorithms that are capable of improving draft assemblies have released. There are SSPACE-LongRead, OPERA-LG, SMIS, npScarf, DBG2OLC, Unicycler, and LINKS. Hybrid assembly on large genomes remains challenging, however. RESULTS:We develop a scalable and computationally efficient scaffolder, Long Reads Scaffolder (LRScaf, https://github.com/shingocat/lrscaf), that is capable of significantly boosting assembly contiguity using long reads. In this study, we summarise a comprehensive performance assessment for state-of-the-art scaffolders and LRScaf on seven organisms, i.e., E. coli, S. cerevisiae, A. thaliana, O. sativa, S. pennellii, Z. mays, and H. sapiens. LRScaf significantly improves the contiguity of draft assemblies, e.g., increasing the NGA50 value of CHM1 from 127.1 kbp to 9.4 Mbp using 20-fold coverage PacBio dataset and the NGA50 value of NA12878 from 115.3 kbp to 12.9 Mbp using 35-fold coverage Nanopore dataset. Besides, LRScaf generates the best contiguous NGA50 on A. thaliana, S. pennellii, Z. mays, and H. sapiens. Moreover, LRScaf has the shortest run time compared with other scaffolders, and the peak RAM of LRScaf remains practical for large genomes (e.g., 20.3 and 62.6 GB on CHM1 and NA12878, respectively). CONCLUSIONS:The new algorithm, LRScaf, yields the best or, at least, moderate scaffold contiguity and accuracy in the shortest run time compared with other scaffolding algorithms. Furthermore, LRScaf provides a cost-effective way to improve contiguity of draft assemblies on large genomes.
| S-EPMC6902338 | biostudies-literature
Project description:MotivationExtra-long tandem repeats (ETRs) are widespread in eukaryotic genomes and play an important role in fundamental cellular processes, such as chromosome segregation. Although emerging long-read technologies have enabled ETR assemblies, the accuracy of such assemblies is difficult to evaluate since there are no tools for their quality assessment. Moreover, since the mapping of error-prone reads to ETRs remains an open problem, it is not clear how to polish draft ETR assemblies.ResultsTo address these problems, we developed the TandemTools software that includes the TandemMapper tool for mapping reads to ETRs and the TandemQUAST tool for polishing ETR assemblies and their quality assessment. We demonstrate that TandemTools not only reveals errors in ETR assemblies but also improves the recently generated assemblies of human centromeres.Availability and implementationhttps://github.com/ablab/TandemTools.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC7355294 | biostudies-literature
Project description:As next-generation sequence (NGS) production continues to increase, analysis is becoming a significant bottleneck. However, in situations where information is required only for specific sequence variants, it is not necessary to assemble or align whole genome data sets in their entirety. Rather, NGS data sets can be mined for the presence of sequence variants of interest by localized assembly, which is a faster, easier, and more accurate approach. We present TASR, a streamlined assembler that interrogates very large NGS data sets for the presence of specific variants by only considering reads within the sequence space of input target sequences provided by the user. The NGS data set is searched for reads with an exact match to all possible short words within the target sequence, and these reads are then assembled stringently to generate a consensus of the target and flanking sequence. Typically, variants of a particular locus are provided as different target sequences, and the presence of the variant in the data set being interrogated is revealed by a successful assembly outcome. However, TASR can also be used to find unknown sequences that flank a given target. We demonstrate that TASR has utility in finding or confirming genomic mutations, polymorphisms, fusions and integration events. Targeted assembly is a powerful method for interrogating large data sets for the presence of sequence variants of interest. TASR is a fast, flexible and easy to use tool for targeted assembly.
| S-EPMC3092772 | biostudies-literature
Project description:Short-read DNA sequencing instruments can yield over 1012 bases per run, typically composed of reads 150 bases long. Despite this high throughput, de novo assembly algorithms have difficulty reconstructing contiguous genome sequences using short reads due to both repetitive and difficult-to-sequence regions in these genomes. Some of the short read assembly challenges are mitigated by scaffolding assembled sequences using paired-end reads. However, unresolved sequences in these scaffolds appear as "gaps". Here, we introduce GapPredict - An implementation of a proof of concept that uses a character-level language model to predict unresolved nucleotides in scaffold gaps. We benchmarked GapPredict against the state-of-the-art gap-filling tool Sealer, and observed that the former can fill 65.6% of the sampled gaps that were left unfilled by the latter with high similarity to the reference genome, demonstrating the practical utility of deep learning approaches to the gap-filling problem in genome assembly.
| S-EPMC8772386 | biostudies-literature
Project description:Next-generation sequencing technologies generate very large numbers of short reads. Even with very deep genome coverage, short read lengths cause problems in de novo assemblies. The use of paired-end libraries with a fragment size shorter than twice the read length provides an opportunity to generate much longer reads by overlapping and merging read pairs before assembling a genome.We present FLASH, a fast computational tool to extend the length of short reads by overlapping paired-end reads from fragment libraries that are sufficiently short. We tested the correctness of the tool on one million simulated read pairs, and we then applied it as a pre-processor for genome assemblies of Illumina reads from the bacterium Staphylococcus aureus and human chromosome 14. FLASH correctly extended and merged reads >99% of the time on simulated reads with an error rate of <1%. With adequately set parameters, FLASH correctly merged reads over 90% of the time even when the reads contained up to 5% errors. When FLASH was used to extend reads prior to assembly, the resulting assemblies had substantially greater N50 lengths for both contigs and scaffolds.The FLASH system is implemented in C and is freely available as open-source code at http://www.cbcb.umd.edu/software/flash.t.magoc@gmail.com.
| S-EPMC3198573 | biostudies-literature
Project description:The Illumina DNA sequencing platform generates accurate but short reads, which can be used to produce accurate but fragmented genome assemblies. Pacific Biosciences and Oxford Nanopore Technologies DNA sequencing platforms generate long reads that can produce complete genome assemblies, but the sequencing is more expensive and error-prone. There is significant interest in combining data from these complementary sequencing technologies to generate more accurate "hybrid" assemblies. However, few tools exist that truly leverage the benefits of both types of data, namely the accuracy of short reads and the structural resolving power of long reads. Here we present Unicycler, a new tool for assembling bacterial genomes from a combination of short and long reads, which produces assemblies that are accurate, complete and cost-effective. Unicycler builds an initial assembly graph from short reads using the de novo assembler SPAdes and then simplifies the graph using information from short and long reads. Unicycler uses a novel semi-global aligner to align long reads to the assembly graph. Tests on both synthetic and real reads show Unicycler can assemble larger contigs with fewer misassemblies than other hybrid assemblers, even when long-read depth and accuracy are low. Unicycler is open source (GPLv3) and available at github.com/rrwick/Unicycler.
| S-EPMC5481147 | biostudies-literature
Project description:BackgroundLong sequencing reads allow increasing contiguity and completeness of fragmented, short-read-based genome assemblies by closing assembly gaps, ideally at high accuracy. While several gap-closing methods have been developed, these methods often close an assembly gap with sequence that does not accurately represent the true sequence.FindingsHere, we present DENTIST, a sensitive, highly accurate, and automated pipeline method to close gaps in short-read assemblies with long error-prone reads. DENTIST comprehensively determines repetitive assembly regions to identify reliable and unambiguous alignments of long reads to the correct loci, integrates a consensus sequence computation step to obtain a high base accuracy for the inserted sequence, and validates the accuracy of closed gaps. Unlike previous benchmarks, we generated test assemblies that have gaps at the exact positions where real short-read assemblies have gaps. Generating such realistic benchmarks for Drosophila (134 Mb genome), Arabidopsis (119 Mb), hummingbird (1 Gb), and human (3 Gb) and using simulated or real PacBio continuous long reads, we show that DENTIST consistently achieves a substantially higher accuracy compared to previous methods, while having a similar sensitivity.ConclusionDENTIST provides an accurate approach to improve the contiguity and completeness of fragmented assemblies with long reads. DENTIST's source code including a Snakemake workflow, conda package, and Docker container is available at https://github.com/a-ludi/dentist. All test assemblies as a resource for future benchmarking are at https://bds.mpi-cbg.de/hillerlab/DENTIST/.
| S-EPMC8848313 | biostudies-literature
Project description:The glycopeptide antibiotic-producing soil actinobacterium Kibdelosporangium philippinense A80407 (=ATCC 49844) was sequenced using Illumina and Nanopore sequencing methodologies, and a hybrid genome assembly was generated for this type strain, with a total predicted genome length of 12,054,556 bp, 10,953 protein-coding sequences, 79 RNAs, 298 pseudogenes, and a G+C content of 65.13%.
| S-EPMC9022495 | biostudies-literature