Diving, and even digging, into the wild jungle of annotation pathways for non-vertebrate animals
A deep dive into genome assemblies of non-vertebrate animals
Recommendation: posted 21 April 2022, validated 06 May 2022
In their paper, Guiglielmoni et al. propose we pick up our snorkels and palms and take "A deep dive into genome assemblies of non-vertebrate animals" (1). Indeed, while numerous assembly-related tools were developed and tested for human genomes (or at least vertebrates such as mice), very few were tested on non-vertebrate animals so far. Moreover, most of the benchmarks are aimed at raw assembly tools, and very few offer a guide from raw reads to an almost finished assembly, including quality control and phasing.
This huge and exhaustive review starts with an overview of the current sequencing technologies, followed by the theory of the different approaches for assembly and their implementation. For each approach, the authors present some of the most representative tools, as well as the limits of the approach.
The authors additionally present all the steps required to obtain an almost complete assembly at a chromosome-scale, with all the different technologies currently available for scaffolding, QC, and phasing, and the way these tools can be applied to non-vertebrates animals. Finally, they propose some useful advice on the choice of the different approaches (but not always tools, see below), and advocate for a robust genome database with all information on the way the assembly was obtained.
This review is a very complete one for now and is a very good starting point for any student or scientist interested to start working on genome assembly, from either model or non-model organisms. However, the authors do not provide a list of tools or a benchmark of them as a recommendation. Why? Because such a proposal may be obsolete in less than a year.... Indeed, with the explosion of the 3rd generation of sequencing technology, assembly tools (from different steps) are constantly evolving, and their relative performance increases on a monthly basis. In addition, some tools are really efficient at the time of a review or of an article, but are not further developed later on, and thus will not evolve with the technology. We have all seen it with wonderful tools such as Chiron (2) or TopHat (3), which were very promising ones, but cannot be developed further due to the stop of the project, the end of the contract of the post-doc in charge of the development, or the decision of the developer to switch to another paradigm. Such advice would, therefore, need to be constantly updated.
Thus, the manuscript from Guiglielmoni et al will be an almost intemporal one (up to the next sequencing revolution at last), and as they advocated for a more informed genome database, I think we should consider a rolling benchmarking system (tools, genome and sequence dataset) allowing to keep the performance of the tools up-to-date, and to propose the best set of assembly tools for a given type of genome.
1. Guiglielmoni N, Rivera-Vicéns R, Koszul R, Flot J-F (2022) A Deep Dive into Genome Assemblies of Non-vertebrate Animals. Preprints, 2021110170, ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.20944/preprints202111.0170
2. Teng H, Cao MD, Hall MB, Duarte T, Wang S, Coin LJM (2018) Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning. GigaScience, 7, giy037. https://doi.org/10.1093/gigascience/giy037
3. Trapnell C, Pachter L, Salzberg SL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics, 25, 1105–1111. https://doi.org/10.1093/bioinformatics/btp120
Francois Sabot (2022) Diving, and even digging, into the wild jungle of annotation pathways for non-vertebrate animals. Peer Community in Genomics, 100016. https://doi.org/10.24072/pci.genomics.100016
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.
Reviewed by Cécile Monat, 23 Mar 2022
Reviewed by Yann Bourgeois, 11 Apr 2022
Reviewed by Benjamin Istace, 15 Mar 2022
Evaluation round #1
DOI or URL of the preprint: 10.20944/preprints202111.0170.v1
Version of the preprint: 1
Author's Reply, 07 Mar 2022
Decision by Francois Sabot, posted 06 Jan 2022
Dear Dr Guiglielmoni,
I have been through your manuscript, as well as 4 independent reviewers, and we all agree that the manuscript is of high interest.
They all, however, highlighted minor comments before acceptance of the manuscript, that I encourage you to perform quite fastly before I can accept if.
In addition, Dr Bourgeois discussed a lot on different aspects of the manuscript that in my opinion are of great interest. Indeed, proposing specific tools for each step would be of great help for non-specialists and beginners...
However, based on my own experience, such recommendations, while of high quality at the given time of the publication and on some specific genomes, would be quite fastly outdated and may be misleading to readers.
Thus, these comments, while very interesting, are for me to be the subject of an online list that can be quickly updated. I would then propose that you discuss them in the manuscript in this way.
Dr Francois Sabot