Abstract
1 min readGenetic exchange, henceforth recombination, is a widespread evolutionary force. Natural populations of many organisms experience significant amounts of recombination, sometimes with markedly different underlying molecular mechanisms. Although mutation is the ultimate source of genetic variation, recombination can easily introduce allelic variation into different chromosomal backgrounds, generating new genetic combinations. This genetic mixing can result in major evolutionary leaps, for example, allowing pathogens to acquire resistance against drugs, and ensures, as part of meiosis in eukaryotes, that offspring inherit different combinations of alleles from their parents. Indeed, when organisms exchange genetic information they are also swapping their evolutionary histories, and because of this, ignoring the presence of recombination can also mislead the evolutionary analysis. Because of its fundamental role in genomic evolution and its potential confounding effect in many evolutionary inferences, it is not surprising that numerous bioinformatic approaches to detect the molecular footprint of recombination have been developed. While the next chapter discusses methods to detect and characterize individual recombination events with a particular focus on genetically diverse viral populations, the aim of this chapter is to briefly introduce different concepts in recombination analysis and to position the approaches discussed in Chapter 16 in the large array of currently available recombination detection tools.
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