New mathematical model to add rigor to studies of disease genetics and evolution

USC College computational biologist Peter Calabrese has developed a new model to simulate the evolution of so-called recombination hotspots in the genome.

Published March 5 in the early online edition of the Proceedings of the National Academy of Sciences, the mathematical model and its associated software bring much-needed rigor to evolutionary investigations of how natural selection acts on individual genes, said Calabrese, a research assistant professor of biological sciences.

And, they may also aid the search for disease-associated genes within the human genome.

The new tools "are more rigorous and less time-consuming than previous, simpler models," Calabrese said.

Recent interest in genetic recombination hotspots has been fueled partly by the promise of genome association studies, which aim to locate the chromosomal regions responsible for genetic diseases. Analyzing such studies to understand the inheritance of genes associated with disease requires an understanding of genetic recombination at a very fine scale.

Genes are packaged in larger structures called chromosomes. Humans have 23 pairs of matching chromosomes, one inherited from each parent. In almost every cell in the body, the maternal and paternal chromosomes stay separated in these pairs. But the sex cells (sperm and egg) each carry only one copy of each chromosome, a mix of the two inherited chromosomes produced by genetic recombination.

During the creation of new sperm or egg cells, paired chromosomes line up and exchange stretches of DNA before dividing into four cells, each with its own singular and completely new chromosome, which will be passed on to offspring.

This genetic re-arrangement and re-shuffling is a major source of genetic diversity, and so is considered the primary benefit of sexual reproduction. It's the biological process that makes each individual (save identical twins) unique, even from close relatives

Contact: Eva Emerson
University of Southern California

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