Home > Bioinformatics, QTL > Finding QTLs with EXPLoRA

Finding QTLs with EXPLoRA

EXPLoRA is a Hidden Markov Model  (HMM) capable of finding Quantitative Trait Loci (QTL) using Bulk Segregant Analysis experiments.

A few days ago, our new version of the algorithm was made available thru a web server. You can find it following this link (here a link to the paper)

The idea behind the method is to use prediction of natural selection and linkage disequilibrium to detect the regions in the DNA responsible for the trait (i.e. find the QTL). Sexual reproduction involve two parents contributing one gamete each. Gametes are produced during meiosis: chromosomes are duplicated and then the cells are divided twice, ending in sexual cells with half the number of chromosomes of a normal cell. One key feature in this process is recombination or crossover.

Recombination is a fundamental source of genomic variation. It has a huge impact on the life cycle of mutations. Recombination cause the offspring to inherit a completely new combination of parental DNA. From the point of view of the dynamics of evolution this would allow a beneficial mutation to be selected independently of the rest of the ancestor’s mutations to some degree. This independence of mutations is not complete because the frequency of crossover events between two mutations is proportional to their physical distance in the chromosomes. Mutations close to each other are less likely to suffer a crossover event that separate them.

The degree to which mutations are separated is related to the recombination rate (i.e. the average number of recombination events that happen in a chromosome). The more recombination events in a chromosome, the easier it becomes for a beneficial mutation to be selected alone, just for the fitness advantage it confers. But this also implies that mutations in close vicinity tend to be inherited together, and therefore “linked”. The link between two mutations is known as linkage disequilibrium.

When observing the genomes of descendants that are selected for the traits of their parents, independent of the reason behind the selection the effect is that the causal mutation become more common in the population. Interestingly, this does not only happen to the responsible mutation, it also happen to those mutation in close proximity to the causal mutation. The closer a neutral mutation is to the causal mutation the less likely is that a recombination event happen in the area. If a neutral mutation is in very close proximity to the causal mutation, the chance that a recombination event happens in the region between them becomes very low.

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Categories: Bioinformatics, QTL
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