Accessible Research: How 1000 genomes can inform on male driving habits

Okay, so not really driving habits, but male driven evolution. Male driven evolution, also referred to as male mutation bias, describes the phenomenon whereby males contribute more mutations than females to offspring (because sperm experience more rounds of replication, and so have the change to incorporate more mutations, than do eggs).

Ideally, we could measure mutations directly in sperm and eggs, but it is very invasive to collect eggs from female mammals, and so we need to find alternative ways.

In the recently released 1000 genomes pilot project, they briefly talk about a very exciting potential dataset. Currently there are two trios (a mother, father and daughter) that were sequenced. The benefit of this dataset is that, with completely sequenced genomes from each of these, scientists can determine which mutations are new in the daughter (i.e. occurred in the germ cells of the mother or father), and can compute a human mutation rate per generation time.

It isn't discussed in the paper, but these kinds of datasets (genomic sequences of both genetic parents and one or more offspring) are ideal for determining the strength of male mutation bias, because the number of mutations can be partitioned into those that came from the paternal germline and which came from the maternal germline. But, in order to do this, I think, one must also sequence the germ cells from at least one of the parents (it would be much easier to sequence some sperm). This is because, in order to be identified as a new mutation in the offspring, by definition, it will not exist in the somatic tissues of the mother or father. So, although we aren't there yet, we are very close to being able to directly measure the male (and then compute the female) mutation rates in human.

Some potential conflicting factors to keep in mind are that: 1) we don't want to confuse somatic mutations in the offspring with parentally-inheirited mutations, so many tissues should be sampled to determine which mutations are shared across all tissues, and which are tissue-specific; and 2) there is likely a lot of statistical fluctuation in mutation rates between individuals, so any one set of trios may not accurately represent the majority. Thus, many families, and ideally families with many children, should be included in such an analysis.

Nature

 

467,

 

1061–1073

 

(28 October 2010)

 

doi:10.1038/nature09534