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The leader—an enthusiastic champion—can 1 drum up support from their collaborators; 2 fuse community expertise with resources; 3 oversee the project; and 4 act as a liaison between new members wanting to join, the infrastructure provider, and existing annotators. Considering that the collective expertise within a group may be extensive but diverse, it is necessary to standardize the curation for quality control of annotations.

To minimize any conflicts that may arise during the annotation process, it is important 1 to have the initial training webinar by laying out clear rules and guidelines; 2 to select a small subset of genes and ask a group of experienced curators to evaluate whether the decisions taken in each case were uniform and sensible; 3 to record webinar training and comments regarding consensus or disagreements for reporting back to the curation team and to edit the tutorial and guidelines; 4 to address this by automated checks and controls Apollo does not allow this for now or makes it extremely difficult ; and 5 to ask multiple reviewers to check each region by reviewing the annotation history in Apollo labor-intensive method.

Pooling the expertise, resources, and time of active communities could enable a wide range of geographically distance members to participate in a common process, to share and validate the identification of contradictions and the misrepresentation of data on the genomes [ ].

After corrections, the datasets manually verified gene sets that emerge from these projects can be used to improve the gene sets for closely related genomes and downstream analysis. Dialog and collaboration between community members have an enormous impact. The result of an entire community agreeing on and taking ownership of a single gene set is a major stepping-stone to accelerating the field.

Handling the mammoth task of manual gene annotation in the absence of dedicated funding or teams is a great challenge. However, our guidelines could provide a manageable solution for the prospect of this approach becoming commonplace and will continue to engage in community-driven curation efforts. For a complete novice, our recommendation would be as below not recommended starting from Illumina only short reads assembly. There are no gold standards for genome assembly and annotation.

However, the availability of NGS data particularly TGS data and their analytical tools has enabled the sequencing of several high-quality genomes of species of importance in aquaculture in recent years. The recommendations addressed here are broad guidelines that could be considered to avoid common pitfalls throughout the whole-genome assembly and annotation process.

However, the comprehensive features e. Finally, newly emerging technologies and analytical tools could dramatically improve end-to-end genome assemblies and annotations in the future by replacing the years-long efforts of the past with rapid and low-cost solutions. Meanwhile, emphasis should be placed upon the following: First, define the achievable research aim. Third, perform assembly and annotation to gain firsthand experience, including in bioinformatics.

Fourth, seek internal and external help and advice from experts. Lastly, be open to sharing genomic data to both increase research productivity and promote public awareness. 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.

Download: PPT. Table 1. Summary of recently published chromosome-level genome assemblies in aquaculture species using long-read sequences a , b. Step 1: Build a wide community for the project if possible All genome projects have a common but monumental goal: sequencing the entire target genome for a wide range of genomics applications. Step 3: Design the best experimental workflow To meet the experimental goals and answer various biological questions, each application must come with different experimental designs.

Table 2. Commonly used tools and programs for genome assembly. Step 7: Choose the best computational design and pipeline Optimizing a computational design and securing sufficient computer resources are essential steps to succeed in a genome assembly and annotation project. Fig 1. Recommended flowchart for genome assembly and annotation.

Step 9: Check the assembly quality before annotation In the shotgun sequencing era, assembling a new genome mostly relies on computational algorithms and experimental designs see Steps 6 and 7. Step Genome annotation Unlike advanced and revolutionized genome sequencing and assembly, getting genome annotation correct remains a challenge.

Step Build a searchable and sharable output format Research papers and data products researchers are usually required to submit raw sequencing data to appropriate repositories such as Sequence Read Archive [SRA] are key outcomes of the scientific enterprise, including most successful genome projects.

Step Reach out to the community to refine the assembly and annotation Dropping whole-genome shotgun sequencing costs and improvements in bioinformatics pipelines and computer capabilities have resulted in the situation where a small lab can undertake genome projects assembly and annotation , and any organism can become a model species. Advice for new genomic users to select a basic assembly and annotation pipeline For a complete novice, our recommendation would be as below not recommended starting from Illumina only short reads assembly.

Conclusions There are no gold standards for genome assembly and annotation. References 1. Long walk to genomics: History and current approaches to genome sequencing and assembly. Comput Struct Biotec. Nanopore sequencing and the Shasta toolkit enable efficient de novo assembly of eleven human genomes. Nat Biotechnol. Is it time to change the reference genome? Genome Biol.

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