6.1.3(b)(i)-(iii) - Uses of gene sequencing and synthetic biology

From Sequence To Meaning

A DNA sequence is a long string of bases. On its own, that string is useful but not enough. To turn sequence data into biological meaning, scientists usually combine three ideas.

[DIAGRAM: sequencing_data_to_applications: Lesson 150: Gene sequencing applications and synthetic biology - diagram 01; asset_slug: 150_m06_1_3_gene_sequencing_applications_and_synthetic_biology__diagram_01; recommended_method: drawn_biology; description: A deterministic 16:9 flow diagram showing gene sequencing producing DNA base-order data, bioinformatics storing and comparing large sequence/protein/pathway datasets, computational biology modelling and predicting from those data, and the OCR-required outputs: genotype-phenotype research, epidemiology, evolutionary relationships, amino-acid prediction and synthetic biology.]

These fields overlap in practice; this useful distinction describes their main contributions rather than mutually exclusive activities. A complete account identifies the data stored, the comparisons made and the predictions tested.

For example, a database may hold DNA sequences, amino-acid sequences, protein structures and metabolic pathway information. Bioinformatics helps scientists search and compare those records. Computational biology then uses algorithms or models to identify patterns, test associations, predict a polypeptide sequence, or model a possible protein's structure and function.

Genome-Wide Comparisons

A genome-wide comparison looks across a large amount of the genome rather than at one isolated gene. Gene sequencing made this possible because many individuals or species can have large parts of their genomes sequenced and compared using software.

Comparisons between individuals can help research into genotype-phenotype relationships. A genotype is the genetic information an organism has; a phenotype is the observable outcome, influenced by genotype and environment. If a particular sequence variant is found more often in individuals with a particular phenotype, that may suggest an association.

This is powerful, but the wording must stay careful. A sequence difference may be associated with a phenotype without directly causing it. Further evidence is needed to test whether the variant affects gene expression, protein structure, enzyme activity, development or another biological process.

Comparisons between species can help search for evolutionary relationships. Closely related species are expected to have more similar DNA sequences because they share a more recent common ancestor. Conserved sequences may also suggest important functions, because harmful changes in those regions are less likely to persist.

In epidemiology, the same comparison idea is used with pathogen genomes. If two bacterial or viral samples have very similar genome sequences, they may belong to the same outbreak or lineage. Sequence data can also show when a new variant has appeared. However, the data must be combined with time, place, sampling and case information before strong conclusions are made about transmission.

Predicting Polypeptides

Gene sequencing can also allow the amino-acid sequence of a polypeptide to be predicted. The key link is the genetic code: triplets of bases in DNA correspond, through mRNA codons, to amino acids or stop signals.

Use this chain:

DNA coding sequence -> mRNA codons -> amino-acid sequence -> primary structure of a polypeptide

Here is a small worked example using a coding DNA sequence. In a coding DNA strand, replace T with U to get the matching mRNA codons.