Gene Calling and Functional Annotation I

Overview

Teaching: 180 min
Exercises: 60 min

Objectives

• Understand what gene calling and functional annotation are, and how together they turn a raw viral genome sequence into an interpretable one

• Explain what ORFs are, describe phage-specific genomic features that make gene calling harder, and how tools like Phanotate are designed to handle them

• Describe three complementary strategies for functional annotation (Pharokka, Phold and Phynteny)

• Explain why these different strategies are required for functional annotation.

From assembled contigs to interpretable viral genomes

We have now identified viral contigs in our metagenomic data. But a DNA sequence by itself tells us very little about that virus. In this lesson, we will learn how to turn a (putative) viral genome sequence into an annotated genome.

This involves two main steps:

1. Gene calling: predicts the coordinates and strand of likely genes and their corresponding protein sequences.

2. Functional annotation: predicts what those proteins might do based on comparisons with known proteins and other sources of evidence.

The resulting information can then be presented in a gene table or as a genome figure, providing a more interpretable view of the viral genome.

In this lesson, you will learn about the principles behind gene calling and functional annotation. You will then apply these concepts in a practical annotation exercise.

Gene calling

The first step in annotating a viral genome is to identify where the genes are located.

Exercise

1. What is the difference between an ORF and a gene?
2. Why do we need specialised gene callers for phages?
3. Name 3 features of phages that make gene calling challenging.
4. Briefly describe the main idea behind the Phanotate algorithm.
5. Malte and Jeroen made a new gene calling program called AwesomeGeneCaller. They ran Phanotate and AwesomeGeneCaller on a few viral genomes and compared the results. AwesomeGeneCaller predicts ten times more genes per viral sequence than Phanotate. Should Malte and Jeroen be happy? Why or why not?

Use the resources below to answer the questions. You are free to decide which resource(s) you use for each question. You do not need to use all of them.

• Lecture (~18 minutes). This lecture by Dr. Robert Edwards gives an introduction to phages and discusses Phanotate, a gene-calling program developed in his lab. Stop at 18:14, when the lecture moves on to functional annotation.

• Research paper: The phanotate paper describes the motivation and algorithm behind Phanotate.

• This video by Dr. Katelyn McNair, the main developer of Phanotate, provides a more detailed explanation of how the algorithm works.

Functional annotation

Once we have identified the genes in a phage genome, we would like to know what those genes might do. This process is called functional annotation and can provide insights into phage biology, including its lifestyle, interactions with its host, and other potential functions encoded in its genome.

Note: For clarity we treat gene calling and functional annotation as two separate steps. In practice they are often performed together by a single tool. For example, Pharokka performs both gene calling (using Phanotate) and functional annotation.

In this part of the lesson, you will learn about three tools that use different types of evidence to predict the functions of phage proteins: Pharokka, Phold, and Phynteny.

You will first learn how these approaches work by reading parts of the corresponding papers. You will then use the Phage Annotation Server, which runs these three tools together, to annotate your own viral contigs.

1. Sequence-based annotation with Pharokka

Read Sections 1–2.4 of the Pharokka paper.

Answer the following questions:

Exercise

1. What does Pharokka do, and which steps of the genome annotation process does it perform?
2. What genomic features are taken into account when predicting genes?
3. How does Pharokka assign functional annotations to predicted proteins?
4. What is an HMM? Why are they useful for annotating phage proteins? What is a PHROG?

The PHROG paper and PHROGs database can be used as additional resources.

2. Phold

Sequence similarity is not the only source of information that can be used to predict protein function. Phold uses a different approach.

Read the abstract and introduction of the Phold paper, and/or watch this short video (5:53 min) where Phold is briefly explained.

Exercise

1. Why might a sequence-based approach fail to assign a function to some phage proteins?
2. What is the basic idea behind Phold?
3. Why can Phold predict the function for more proteins than Pharokka?

3. Phynteny

Finally, read the abstract and introduction of Phynteny paper, to answer the following questions:

Exercise

1. What is meant by synteny?
2. How can Phynteny predict the function of a gene, when Phold and Pharokka cannot?

Key Points

• Genome annotation gives meaning to genomic sequences

• ORFs can be predicted from start and stop codons in the genomic sequences

• Phages have different genomic features than prokaryotes, which influences the design of algorithms

• Gene calling predicts the coordinates, strand, and protein sequence of candidate genes

• Phage genomes have distinctive features (e.g. dense/overlapping genes, atypical start codon usage) that differ from prokaryotic genomes, requiring specialized tools like Phanotate

• Sequence-based annotation (e.g. Pharokka) assigns function by comparing predicted proteins against known viral genes

• Sequence similarity alone often fails on divergent phage proteins.