GAPPadder: a sensitive approach for closing gaps on draft genomes with short sequence reads.

Closing 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. We 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. In 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 .

Chu C ，Li X ，Wu Y 《BMC GENOMICS》

LR_Gapcloser: a tiling path-based gap closer that uses long reads to complete genome assembly.

Completing a genome is an important goal of genome assembly. However, many assemblies, including reference assemblies, are unfinished and have a number of gaps. Long reads obtained from third-generation sequencing (TGS) platforms can help close these gaps and improve assembly contiguity. However, current gap-closure approaches using long reads require extensive runtime and high memory usage. Thus, a fast and memory-efficient approach using long reads is needed to obtain complete genomes. We developed LR_Gapcloser to rapidly and efficiently close the gaps in genome assembly. This tool utilizes long reads generated from TGS sequencing platforms. Tested on de novo assembled gaps, repeat-derived gaps, and real gaps, LR_Gapcloser closed a higher number of gaps faster and with a lower error rate and a much lower memory usage than two existing, state-of-the art tools. This tool utilized raw reads to fill more gaps than when using error-corrected reads. It is applicable to gaps in the assemblies by different approaches and from large and complex genomes. After performing gap-closure using this tool, the contig N50 size of the human CHM1 genome was improved from 143 kb to 19 Mb, a 132-fold increase. We also closed the gaps in the Triticum urartu genome, a large genome rich in repeats; the contig N50 size was increased by 40%. Further, we evaluated the contiguity and correctness of six hybrid assembly strategies by combining the optimal TGS-based and next-generation sequencing-based assemblers with LR_Gapcloser. A proposed and optimal hybrid strategy generated a new human CHM1 genome assembly with marked contiguity. The contig N50 value was greater than 28 Mb, which is larger than previous non-reference assemblies of the diploid human genome. LR_Gapcloser is a fast and efficient tool that can be used to close gaps and improve the contiguity of genome assemblies. A proposed hybrid assembly including this tool promises reference-grade assemblies. The software is available at http://www.fishbrowser.org/software/LR_Gapcloser/.

Xu GC ，Xu TJ ，Zhu R ，Zhang Y ，Li SQ ，Wang HW ，Li JT ... -  《GigaScience》

Sealer: a scalable gap-closing application for finishing draft genomes.

While next-generation sequencing technologies have made sequencing genomes faster and more affordable, deciphering the complete genome sequence of an organism remains a significant bioinformatics challenge, especially for large genomes. Low sequence coverage, repetitive elements and short read length make de novo genome assembly difficult, often resulting in sequence and/or fragment "gaps" - uncharacterized nucleotide (N) stretches of unknown or estimated lengths. Some of these gaps can be closed by re-processing latent information in the raw reads. Even though there are several tools for closing gaps, they do not easily scale up to processing billion base pair genomes. Here we describe Sealer, a tool designed to close gaps within assembly scaffolds by navigating de Bruijn graphs represented by space-efficient Bloom filter data structures. We demonstrate how it scales to successfully close 50.8% and 13.8% of gaps in human (3 Gbp) and white spruce (20 Gbp) draft assemblies in under 30 and 27 h, respectively - a feat that is not possible with other leading tools with the breadth of data used in our study. Sealer is an automated finishing application that uses the succinct Bloom filter representation of a de Bruijn graph to close gaps in draft assemblies, including that of very large genomes. We expect Sealer to have broad utility for finishing genomes across the tree of life, from bacterial genomes to large plant genomes and beyond. Sealer is available for download at https://github.com/bcgsc/abyss/tree/sealer-release.

Paulino D ，Warren RL ，Vandervalk BP ，Raymond A ，Jackman SD ，Birol I ... -  《BMC BIOINFORMATICS》

GMcloser: closing gaps in assemblies accurately with a likelihood-based selection of contig or long-read alignments.

Genome assemblies generated with next-generation sequencing (NGS) reads usually contain a number of gaps. Several tools have recently been developed to close the gaps in these assemblies with NGS reads. Although these gap-closing tools efficiently close the gaps, they entail a high rate of misassembly at gap-closing sites. We have found that the assembly error rates caused by these tools are 20-500-fold higher than the rate of errors introduced into contigs by de novo assemblers. We here describe GMcloser, a tool that accurately closes these gaps with a preassembled contig set or a long read set (i.e., error-corrected PacBio reads). GMcloser uses likelihood-based classifiers calculated from the alignment statistics between scaffolds, contigs and paired-end reads to correctly assign contigs or long reads to gap regions of scaffolds, thereby achieving accurate and efficient gap closure. We demonstrate with sequencing data from various organisms that the gap-closing accuracy of GMcloser is 3-100-fold higher than those of other available tools, with similar efficiency. GMcloser and an accompanying tool (GMvalue) for evaluating the assembly and correcting misassemblies except SNPs and short indels in the assembly are available at https://sourceforge.net/projects/gmcloser/. shunichi.kosugi@riken.jp. Supplementary data are available at Bioinformatics online.

Kosugi S ，Hirakawa H ，Tabata S 《-》

An improved approach for reconstructing consensus repeats from short sequence reads.

Repeat elements are important components of most eukaryotic genomes. Most existing tools for repeat analysis rely either on high quality reference genomes or existing repeat libraries. Thus, it is still challenging to do repeat analysis for species with highly repetitive or complex genomes which often do not have good reference genomes or annotated repeat libraries. Recently we developed a computational method called REPdenovo that constructs consensus repeat sequences directly from short sequence reads, which outperforms an existing tool called RepARK. One major issue with REPdenovo is that it doesn't perform well for repeats with relatively high divergence rates or low copy numbers. In this paper, we present an improved approach for constructing consensus repeats directly from short reads. Comparing with the original REPdenovo, the improved approach uses more repeat-related k-mers and improves repeat assembly quality using a consensus-based k-mer processing method. We compare the performance of the new method with REPdenovo and RepARK on Human, Arabidopsis thaliana and Drosophila melanogaster short sequencing data. And the new method fully constructs more repeats in Repbase than the original REPdenovo and RepARK, especially for repeats of higher divergence rates and lower copy number. We also apply our new method on Hummingbird data which doesn't have a known repeat library, and it constructs many repeat elements that can be validated using PacBio long reads. We propose an improved method for reconstructing repeat elements directly from short sequence reads. The results show that our new method can assemble more complete repeats than REPdenovo (and also RepARK). Our new approach has been implemented as part of the REPdenovo software package, which is available for download at https://github.com/Reedwarbler/REPdenovo .

Chu C ，Pei J ，Wu Y 《BMC GENOMICS》