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A genome sequence is a powerful resource, but it is not a direct list of every active protein in every cell. Explain what sequence data can reveal and what additional evidence is needed.
What you'll be able to do
Genome projects determine the order of bases across an organism’s genetic material. Automated sequencing and computational analysis allow comparison of many regions and identification of candidate genes. A DNA sequence is evidence about potential information, not direct observation of every gene being active.
For a relatively simple genome, identifying coding regions and applying the genetic code can help predict polypeptide sequences and a potential protein complement. Annotation still requires interpretation: a predicted sequence and an experimentally demonstrated protein function are different levels of evidence.
In more complex organisms, substantial non-coding DNA and regulatory sequences make a simple translation of the entire genome inappropriate. Introns must be distinguished from retained transcript sequence, and regulatory processes determine which messages are produced in each cell and condition.
RNA processing and subsequent protein processing can also create differences between a simple coding prediction and the proteins actually present. Two tissues can share broadly the same genome but have different expressed proteomes. Knowing a sequence does not by itself reveal expression level, location, folding or activity.
Pathogen genome data can identify potential antigenic proteins for vaccine research. A useful candidate must be produced, accessible to the immune response in a relevant way and capable of contributing to protection; a predicted gene alone does not demonstrate these properties.
Compare sequence conservation among strains, expression measurements and functional tests. A conserved target may be attractive, but its role and accessibility still matter. Sequencing generates hypotheses and resources that need biological validation rather than replacing experiments or guaranteeing a successful application.
Try each question before opening the worked response. Use precise biological terms, connect each cause to its effect, and check units and assumptions when interpreting data.
Common mistakes to avoid
Key takeaways
Test yourself
Answer a few questions, then review anything you missed.
Start with the quiz above to check the key ideas. You can also choose another topic from the practice library.