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      YaHS: yet another Hi-C scaffolding tool

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      Author(s): , ,
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      Publication date (Electronic):
      Journal: Bioinformatics
      Publisher: Oxford University Press

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          Abstract

          Summary

          We present YaHS, a user-friendly command-line tool for the construction of chromosome-scale scaffolds from Hi-C data. It can be run with a single-line command, requires minimal input from users (an assembly file and an alignment file) which is compatible with similar tools and provides assembly results in multiple formats, thereby enabling rapid, robust and scalable construction of high-quality genome assemblies with high accuracy and contiguity.

          Availability and implementation

          YaHS is implemented in C and licensed under the MIT License. The source code, documentation and tutorial are available at https://github.com/sanger-tol/yahs.

          Supplementary information

          Supplementary data are available at Bioinformatics online.

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          Most cited references17

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          Comprehensive mapping of long-range interactions reveals folding principles of the human genome.

          Erez Lieberman-Aiden, Nynke van Berkum, Louise Williams … (2009)
          We describe Hi-C, a method that probes the three-dimensional architecture of whole genomes by coupling proximity-based ligation with massively parallel sequencing. We constructed spatial proximity maps of the human genome with Hi-C at a resolution of 1 megabase. These maps confirm the presence of chromosome territories and the spatial proximity of small, gene-rich chromosomes. We identified an additional level of genome organization that is characterized by the spatial segregation of open and closed chromatin to form two genome-wide compartments. At the megabase scale, the chromatin conformation is consistent with a fractal globule, a knot-free, polymer conformation that enables maximally dense packing while preserving the ability to easily fold and unfold any genomic locus. The fractal globule is distinct from the more commonly used globular equilibrium model. Our results demonstrate the power of Hi-C to map the dynamic conformations of whole genomes.
          Article 0 comments Cited 1814 times – based on 0 reviews     Review now
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            De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds.

            Olga Dudchenko, Sanjit Batra, Arina Omer … (2017)
            The Zika outbreak, spread by the Aedes aegypti mosquito, highlights the need to create high-quality assemblies of large genomes in a rapid and cost-effective way. Here we combine Hi-C data with existing draft assemblies to generate chromosome-length scaffolds. We validate this method by assembling a human genome, de novo, from short reads alone (67× coverage). We then combine our method with draft sequences to create genome assemblies of the mosquito disease vectors Aeaegypti and Culex quinquefasciatus, each consisting of three scaffolds corresponding to the three chromosomes in each species. These assemblies indicate that almost all genomic rearrangements among these species occur within, rather than between, chromosome arms. The genome assembly procedure we describe is fast, inexpensive, and accurate, and can be applied to many species.
            Article 0 comments Cited 973 times – based on 0 reviews     Review now
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              Towards complete and error-free genome assemblies of all vertebrate species

              Arang Rhie, Shane A. McCarthy, Olivier Fedrigo … (2021)
              High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species 1 – 4 . To address this issue, the international Genome 10K (G10K) consortium 5 , 6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences. The Vertebrate Genome Project has used an optimized pipeline to generate high-quality genome assemblies for sixteen species (representing all major vertebrate classes), which have led to new biological insights.
              Article 0 comments Cited 823 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Chenxi Zhou:
                ORCID: https://orcid.org/0000-0002-1735-2630
                Shane A McCarthy:
                ORCID: https://orcid.org/0000-0002-2715-4187
                Richard Durbin:
                ORCID: https://orcid.org/0000-0002-9130-1006
                Can Alkan: Role: Associate Editor
                Journal
                Journal ID (nlm-ta): Bioinformatics
                Journal ID (iso-abbrev): Bioinformatics
                Journal ID (publisher-id): bioinformatics
                Title: Bioinformatics
                Publisher: Oxford University Press
                ISSN (Print): 1367-4803
                ISSN (Electronic): 1367-4811
                Publication date Collection: January 2023
                Publication date (Electronic): 16 December 2022
                Publication date PMC-release: 16 December 2022
                Volume: 39
                Issue: 1
                Electronic Location Identifier: btac808
                Affiliations
                Department of Genetics, University of Cambridge , Cambridge CB2 3EH, UK
                Wellcome Sanger Institute, Wellcome Genome Campus , Cambridge CB10 1SA, UK
                Department of Genetics, University of Cambridge , Cambridge CB2 3EH, UK
                Wellcome Sanger Institute, Wellcome Genome Campus , Cambridge CB10 1SA, UK
                Department of Genetics, University of Cambridge , Cambridge CB2 3EH, UK
                Wellcome Sanger Institute, Wellcome Genome Campus , Cambridge CB10 1SA, UK
                Author notes
                To whom correspondence should be addressed. rd109@ 123456cam.ac.uk
                Author information
                https://orcid.org/0000-0002-1735-2630
                https://orcid.org/0000-0002-2715-4187
                https://orcid.org/0000-0002-9130-1006
                Article
                Publisher ID: btac808
                DOI: 10.1093/bioinformatics/btac808
                PMC ID: 9848053
                PubMed ID: 36525368
                SO-VID: a4be23b5-60d7-4728-a212-bd2ddab27907
                Copyright © © The Author(s) 2022. Published by Oxford University Press.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 30 June 2022
                Date revision received : 09 December 2022
                Date: 12 December 2022
                Date accepted : 15 December 2022
                Date: 27 December 2022
                Page count
                Pages: 3
                Funding
                Funded by: Wellcome, DOI 10.13039/100010269;
                Award ID: 207492
                Award ID: 218328
                Award ID: 220540
                Categories
                Subject: Applications Note
                Subject: Genome Analysis
                Subject: AcademicSubjects/SCI01060

                ScienceOpen disciplines: Bioinformatics & Computational biology
                Data availability:
                ScienceOpen disciplines: Bioinformatics & Computational biology

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