Describe the Key Differences in Gene Finding and Gene Function Prediction in Prokaryotes Compared to Eukaryotes

Introduction

Bioinformatics based tools are essential to the design of experiments in the post-genomic age. They allow scientists to manipulate the large datasets gained from genome sequencing efforts to identify potential research targets; analyse target sequences to predict protein characteristics; and to share annotated data through simple, on demand interfaces. This gives researchers more information to use when creating a hypothesis, which saves time and money that would have been spent of failed experiments.

Informed use of these tools is required to avoid false-positive and negative results. This requires knowledge of the tools limits, parameter adjustments and biological considerations to ensure a confident hypothesis when using bioinformatics. Additionally, strong fundamental knowledge of these techniques will increase their accuracy and efficiency, leading to better initial experiments.

An important biological consideration that dictates which bioinformatics tools should be used is whether sequence data is taken from a prokaryotic or eukaryotic organism. Many tools will have options to select what classification your sequence comes from and some will only work with a certain classification. This is because there are major differences in the organisation and processing of genetic information between prokaryotes and eukaryotes.

However, only certain differences between the two classifications are important; depending on what data you’re analysing and what information you hope to extract. This creates two stages of analysis take that place during experimental design using bioinformatics tools. These are gene finding and gene function prediction; together, they can identify potential targets for research and elicit imp...

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...d to consider these differences when identifying genes and predicting their function. Prokaryotic genomes also possess synteny, which makes comparative genomics a useful tool in identifying small genes that would be overlooked in more stringent gene finding tools such as ORF scanning.

Predicting gene function revolves around predicting protein localisation and defining conserved functional domains. These are both dependant on whether the target sequence is prokaryotic or eukaryotic in origin, as different signalling peptides, possibilities for localisation and useful domains exist for each classification. However, gene expression data has been overlooked as a method of functional analysis as analysis of either classification follows a similar method. Gene expression data is useful as it further narrows the ambiguity of protein function to specific cellular events.