The usefulness of sex, according to an intriguing new theory of evolutionary biology, may be its ability to promote genes that play well with many other partners, rather than just those that shine with one specific set of genes.

This idea of genetic mixability, described in the journal Proceedings of the National Academy of Sciences hits on the difficulties that Evolutionary biologists have had in understanding the role of sex in population genetics and Darwin’s survival-of-the-fittest mantra.

Lead author Adi Livnat, a Miller Institute post-doctoral fellow based at UC Berkeley’s Department of Electrical Engineering and Computer Sciences said:

During the past century, it has often been assumed that sexual reproduction should somehow facilitate the increase in fitness under natural selection, leading to the ‘best’ combinations of genes. But no agreement has been reached on whether and how this could really work. One might think, for example, that by bringing together genes from different individuals, sexual reproduction could create a very successful combination of genes. But just as sexual reproduction will create that very successful combination of genes, it could also break it down in the next generation.

That sex can actually impede the increase in the fitness of the population raises the question of how it could remain the dominant form of reproduction across all manner of species, when the fact remains that sexual reproduction (the merging of genes from different individuals to create genetically unique offspring) is the reproductive method of choice from humans to plants to many fungi. So, this form of reproduction must be doing something right in terms of evolution.

Thinking laterally, instead of making the standard assumption that sexual reproduction increases the average fitness of a population, the researchers came up with a new measure they call “mixability” to represent a gene’s ability to perform well across many different combinations.

They tested the mixability measure in a number of scenarios, within a well-established population-genetic framework and found that if the goal is to maximize fitness by finding a particularly good combination of genes, asexual reproduction – which increases a population’s numbers at a much faster rate than sexual reproduction – works very well.

In contrast, sexual reproduction, through the process of recombination and segregation of chromosomes, strongly favours genes that work well in many different variations rather than any one good combination. In that view, the authors wrote, alleles of the same gene compete with each other based upon how well they perform on average rather than how well they perform in any one specific combination.

Co-author Marcus Feldman, Professor of Biology at Stanford University, and a world-renowned theorist in evolutionary biology said:

It’s important to note that during the process of evolution, the mixability value increases, though it doesn’t increase all the time. The approach we take is different from usual because we’re interested in Evolutionary transience, and in the long run, our mixability value may actually decrease because too much variability is lost from the population.

Even so, sexual reproduction has a great advantage for mixability compared with asexual reproduction, according to the models used in the paper.

Livnat started thinking about this problem in discussions with co-author Christos Papadimitriou, Professor of computer sciences at the University of California, Berkeley, and a leading computer theorist whose research includes optimization algorithms. Such programming is widely used to find best outcomes in applications such as computer networks, transportation planning and financial models.

The researchers explained that of the two main techniques for optimization programming, the first, known as simulated annealing, solves problems using a process analogous to asexual reproduction, whilst the second, known as genetic algorithms, is inspired by sexual reproduction. Genetic algorithms should theoretically be the more efficient of the two techniques for finding the best solutions to a problem because they mimic an approach that is so dominant in nature. However, it turns out that genetic algorithms often perform no better than simulated annealing.

Professor Papadimitriou said:

We were trying to figure out why an algorithm that mimics a good idea in nature was not coming up with better results. It dawned on us that what sexual reproduction is doing is not maximizing fitness, but doing something more subtle. It is bringing about genetic variants that perform well across many possibilities in connection with a great variety of genetic partners. If a particular gene variant can do well with many other alleles, not just a highly specialized variant, evolution is advanced.

The researchers noted that when the human genome was sequenced in 2003, there was surprise that humans didn’t possess far more genes than other species. It turns out that how those genes are combined may be a critical factor in distinguishing humans from other species, supporting the importance of flexibility over fitness.

Feldman, who has studied the evolution of sex and recombination for more than three decades, said he expects this new theory to trigger much debate among his peers, adding:

This problem of understanding sex will go on being one of the central issues in evolution.

You might also enjoy reading:-

• The first sexual experience – 570 million years ago
• Scientists find men and women really do think differently
• Sex is Essential, Kids Aren’t
• Male dominance no guarantee of genetic success
• A royal scandal in the world of ants

Posted by Jonathan in Biology, Sociobiology

No Comments »