Twelve quick steps for genome assembly and annotation in the classroom

PLoS Comput Biol. 2020 Nov 12;16(11):e1008325. doi: 10.1371/journal.pcbi.1008325. eCollection 2020 Nov.

Abstract

Eukaryotic genome sequencing and de novo assembly, once the exclusive domain of well-funded international consortia, have become increasingly affordable, thus fitting the budgets of individual research groups. Third-generation long-read DNA sequencing technologies are increasingly used, providing extensive genomic toolkits that were once reserved for a few select model organisms. Generating high-quality genome assemblies and annotations for many aquatic species still presents significant challenges due to their large genome sizes, complexity, and high chromosome numbers. Indeed, selecting the most appropriate sequencing and software platforms and annotation pipelines for a new genome project can be daunting because tools often only work in limited contexts. In genomics, generating a high-quality genome assembly/annotation has become an indispensable tool for better understanding the biology of any species. Herein, we state 12 steps to help researchers get started in genome projects by presenting guidelines that are broadly applicable (to any species), sustainable over time, and cover all aspects of genome assembly and annotation projects from start to finish. We review some commonly used approaches, including practical methods to extract high-quality DNA and choices for the best sequencing platforms and library preparations. In addition, we discuss the range of potential bioinformatics pipelines, including structural and functional annotations (e.g., transposable elements and repetitive sequences). This paper also includes information on how to build a wide community for a genome project, the importance of data management, and how to make the data and results Findable, Accessible, Interoperable, and Reusable (FAIR) by submitting them to a public repository and sharing them with the research community.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computational Biology
  • Gene Library
  • Genome*
  • Genomics / education
  • Genomics / methods*
  • Genomics / statistics & numerical data
  • High-Throughput Nucleotide Sequencing / methods
  • High-Throughput Nucleotide Sequencing / statistics & numerical data
  • Humans
  • Molecular Sequence Annotation / methods*
  • Molecular Sequence Annotation / statistics & numerical data
  • RNA-Seq / methods
  • RNA-Seq / statistics & numerical data
  • Sequence Analysis, DNA / methods
  • Sequence Analysis, DNA / statistics & numerical data

Grants and funding

This work was supported by the Korean Ministry of Agriculture, Food, and Rural Affairs (918010042HD030, Strategic Initiative for Microbiomes in Agriculture and Food) to SE. This work was also supported by a grant from the National Institute of Fisheries Science (R2020001) to WK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.