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1. Virseqimprover: an integrated pipeline for viral contig error correction, extension, and annotation

   https://doi.org/10.7717/peerj.18515  

   Song, Haoqiu; Tithi, Saima Sultana; Brown, Connor; Aylward, Frank O; Jensen, Roderick; Zhang, Liqing (January 2025, PeerJ)

   Despite the recent surge of viral metagenomic studies, it remains a significant challenge to recover complete virus genomes from metagenomic data. The majority of viral contigs generated from de novo assembly programs are highly fragmented, presenting significant challenges to downstream analysis and inference. To address this issue, we have developed Virseqimprover, a computational pipeline that can extend assembled contigs to complete or nearly complete genomes while maintaining extension quality. Virseqimprover first examines whether there is any chimeric sequence based on read coverage, breaks the sequence into segments if there is, then extends the longest segment with uniform depth of coverage, and repeats these procedures until the sequence cannot be extended. Finally, Virseqimprover annotates the gene content of the resulting sequence. Results show that Virseqimprover has good performances on correcting and extending viral contigs to their full lengths, hence can be a useful tool to improve the completeness and minimize the assembly errors of viral contigs. Both a web server and a conda package for Virseqimprover are provided to the research community free of charge. 

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2. Virseqimprover: An Integrated Pipeline for Viral Contig Error Correction, Extension, and Annotation

   https://doi.org/10.21203/rs.3.rs-3318217/v1  

   Song, Haoqiu; Tithi, Saima; Aylward, Frank; Jensen, Roderick; Zhang, Liqing (September 2023, Research Square)

   Abstract Background:Despite the recent surge of viral metagenomic studies, it remains a significant challenge to recover complete virus genomes from metagenomic data. The majority of viral contigs generated fromde novoassembly programs are highly fragmented, presenting significant challenges to downstream analysis and inference.Methods:We have developed Virseqimprover, a computational pipeline that can extend assembled contigs to complete or nearly complete genomes while maintaining extension quality. Virseqimprover first examines whether there is any chimeric sequence based on read coverage, breaks the sequence into segments if there is, then extends the longest segment with uniform coverage, and repeats these procedures until the sequence cannot be extended. Finally, Virseqimprover annotates the gene content of the resulting sequence.Conclusion:Virseqimprover has good performance on correcting and extending viral contigs to their full lengths, hence can be a useful tool to improve the completeness and minimize the assembly errors of viral contigs. Both a web server and a conda package for Virseqimprover are provided to the research community free of charge. 

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3. The SAMBA tool uses long reads to improve the contiguity of genome assemblies

   https://doi.org/10.1371/journal.pcbi.1009860  

   Zimin, Aleksey V.; Salzberg, Steven L. (February 2022, PLOS Computational Biology)

   Shao, Mingfu (Ed.)

   Third-generation sequencing technologies can generate very long reads with relatively high error rates. The lengths of the reads, which sometimes exceed one million bases, make them invaluable for resolving complex repeats that cannot be assembled using shorter reads. Many high-quality genome assemblies have already been produced, curated, and annotated using the previous generation of sequencing data, and full re-assembly of these genomes with long reads is not always practical or cost-effective. One strategy to upgrade existing assemblies is to generate additional coverage using long-read data, and add that to the previously assembled contigs. SAMBA is a tool that is designed to scaffold and gap-fill existing genome assemblies with additional long-read data, resulting in substantially greater contiguity. SAMBA is the only tool of its kind that also computes and fills in the sequence for all spanned gaps in the scaffolds, yielding much longer contigs. Here we compare SAMBA to several similar tools capable of re-scaffolding assemblies using long-read data, and we show that SAMBA yields better contiguity and introduces fewer errors than competing methods. SAMBA is open-source software that is distributed at https://github.com/alekseyzimin/masurca . 

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4. The revised reference genome of the leopard gecko ( Eublepharis macularius ) provides insight into the considerations of genome phasing and assembly

   https://doi.org/10.1093/jhered/esad016  

   Pinto, Brendan J.; Gamble, Tony; Smith, Chase H.; Keating, Shannon E.; Havird, Justin C.; Chiari, Ylenia; Sethuraman, ed., Arun (March 2023, Journal of Heredity)

   Abstract Genomic resources across squamate reptiles (lizards and snakes) have lagged behind other vertebrate systems and high-quality reference genomes remain scarce. Of the 23 chromosome-scale reference genomes across the order, only 12 of the ~60 squamate families are represented. Within geckos (infraorder Gekkota), a species-rich clade of lizards, chromosome-level genomes are exceptionally sparse representing only two of the seven extant families. Using the latest advances in genome sequencing and assembly methods, we generated one of the highest-quality squamate genomes to date for the leopard gecko, Eublepharis macularius (Eublepharidae). We compared this assembly to the previous, short-read only, E. macularius reference genome published in 2016 and examined potential factors within the assembly influencing contiguity of genome assemblies using PacBio HiFi data. Briefly, the read N50 of the PacBio HiFi reads generated for this study was equal to the contig N50 of the previous E. macularius reference genome at 20.4 kilobases. The HiFi reads were assembled into a total of 132 contigs, which was further scaffolded using HiC data into 75 total sequences representing all 19 chromosomes. We identified 9 of the 19 chromosomal scaffolds were assembled as a near-single contig, whereas the other 10 chromosomes were each scaffolded together from multiple contigs. We qualitatively identified that the percent repeat content within a chromosome broadly affects its assembly contiguity prior to scaffolding. This genome assembly signifies a new age for squamate genomics where high-quality reference genomes rivaling some of the best vertebrate genome assemblies can be generated for a fraction of previous cost estimates. This new E. macularius reference assembly is available on NCBI at JAOPLA010000000. 

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5. HiFine: integrating Hi-C-based and shotgun-based methods to refine binning of metagenomic contigs

   https://doi.org/10.1093/bioinformatics/btac295  

   Du, Yuxuan; Sun, Fengzhu; Birol, ed., Inanc (April 2022, Bioinformatics)

   Abstract MotivationMetagenomic binning aims to retrieve microbial genomes directly from ecosystems by clustering metagenomic contigs assembled from short reads into draft genomic bins. Traditional shotgun-based binning methods depend on the contigs’ composition and abundance profiles and are impaired by the paucity of enough samples to construct reliable co-abundance profiles. When applied to a single sample, shotgun-based binning methods struggle to distinguish closely related species only using composition information. As an alternative binning approach, Hi-C-based binning employs metagenomic Hi-C technique to measure the proximity contacts between metagenomic fragments. However, spurious inter-species Hi-C contacts inevitably generated by incorrect ligations of DNA fragments between species link the contigs from varying genomes, weakening the purity of final draft genomic bins. Therefore, it is imperative to develop a binning pipeline to overcome the shortcomings of both types of binning methods on a single sample. ResultsWe develop HiFine, a novel binning pipeline to refine the binning results of metagenomic contigs by integrating both Hi-C-based and shotgun-based binning tools. HiFine designs a strategy of fragmentation for the original bin sets derived from the Hi-C-based and shotgun-based binning methods, which considerably increases the purity of initial bins, followed by merging fragmented bins and recruiting unbinned contigs. We demonstrate that HiFine significantly improves the existing binning results of both types of binning methods and achieves better performance in constructing species genomes on publicly available datasets. To the best of our knowledge, HiFine is the first pipeline to integrate different types of tools for the binning of metagenomic contigs. Availability and implementationHiFine is available at https://github.com/dyxstat/HiFine. Supplementary informationSupplementary data are available at Bioinformatics online. 

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