> Recombination makes new combinations, but does not create new sex alleles, nor allelic variation.
New work on recombination paints a different picture (
Evolution results from changes in allele frequencies in populations. The main forces that
cause such changes are natural selection and random genetic drift. However, an additional
process, GC-biased gene conversion (gBGC), associated with meiotic recombination, affects
the probability that alleles are passed from one generation to the next.
The honeybee, Apis
mellifera, has extremely high recombination rates—more than 20 times to those observed in
humans. However, the reason for this is unknown and the effects of such high recombination
rates on evolution are not well understood.
The strong skews in site frequency spectrum and fixation biases are incompatible with a
standard model of population genetics whereby the fate of alleles is determined by genetic
drift and selection. The process of gBGC has a major influence on probability of fixation of an
allele in honeybee populations. This has major implications for molecular evolution, as it can
interfere with the removal of harmful alleles and fixation of beneficial alleles by natural selection
and cause fixation of weakly deleterious mutations.
Recombination, via gBGC, therefore appears to have profound consequences on genome
evolution in honeybees and interferes with the process of natural selection. These findings
have important implications for our understanding of the forces driving molecular evolution.
Wallberg, et al. PLOS Genetics (2015) DOI:10.1371/journal.pgen.1005189
Comment:
Recombination _appears_ to be at odds with natural selection, and hence, human guided selection. Most probably, natural selection has produced this high level of recombination in the honey bee as a consequence of the weeding out of strains that had lower rates of recombination. The reason for this high recombination rate may be to create variation for some necessary function. The following work suggests an explanation:
Abstract
Background: Social hymenoptera, the honey bee (Apis mellifera) in particular, have ultra-high crossover rates and a
large degree of intra-genomic variation in crossover rates. Aligned with haploid genomics of males, this makes
them a potential model for examining the causes and consequences of crossing over. To address why social insects
have such high crossing-over rates and the consequences of this, we constructed a high-resolution recombination
atlas by sequencing 55 individuals from three colonies with an average marker density of 314 bp/marker.
Results: We find crossing over to be especially high in proximity to genes upregulated in worker brains, but see no
evidence for a coupling with immune-related functioning. We detect only a low rate of non-crossover gene conversion,
contrary to current evidence. This is in striking contrast to the ultrahigh crossing-over rate, almost double that
previously estimated from lower resolution data. We robustly recover the predicted intragenomic correlations between
crossing over and both population level diversity and GC content, which could be best explained as indirect and direct
consequences of crossing over, respectively.
Conclusions: Our data are consistent with the view that diversification of worker behavior, but not immune function,
is a driver of the high crossing-over rate in bees. While we see both high diversity and high GC content associated with
high crossing-over rates, our estimate of the low non-crossover rate demonstrates that high non-crossover rates are
not a necessary consequence of high recombination rates.
Liu et al. Genome Biology (2015) 16:15 DOI 10.1186/s13059-014-0566-0
Comment:
It _appears_ that recombination combined with multiple mating is geared toward producing the maximum variation in behavioral characteristics, while conserving immune function, which is known to be somewhat basic in the honey bee. This variation may be producing a synergy which in turn increases the adaptability of the superorganism to the extreme variability which the colony encounters in the real world (e.g., constantly changing resources, conditions, etc.)
PLB
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