Investigating associations between biting time in the malaria vector Anopheles arabiensis Patton and single nucleotide polymorphisms in circadian clock genes: support for sub-structure among An. arabiensis in the Kilombero valley of Tanzania.

BACKGROUND: There is growing evidence that the widespread use of Long-Lasting Insecticidal Nets (LLINs) is prompting malaria vectors to shift their biting towards times and places where people are not protected, such as earlier in the evening and/or outdoors. It is uncertain whether these behavioural shifts are due to phenotypic plasticity and/or ecological changes within vector communities that favour more exophilic species, or involve genetic factors within vector species to limit their contact with LLINs. Possibly variation in the time and location of mosquito biting has a genetic basis, but as yet this phenomenon has received little investigation. Here we used a candidate gene approach to investigate whether polymorphisms in selected circadian clock genes could explain variation in the time and location of feeding (indoors versus outside) within a natural population of the major African malaria vector Anopheles arabiensis. METHODS: Host-seeking An. arabiensis were collected from two villages (Lupiro and Sagamaganga) in Tanzania by Human Landing Catch (HLC) technique. Mosquitoes were classified into phenotypes of "early" (7 pm-10 pm) or "late" biting (4 am -7 am), and host-seeking indoors or outdoors. In these samples we genotyped 34 coding SNPs in 8 clock genes (PER, TIM, CLK, CYC, PDP1, VRI, CRY1, and CRY2), and tested for associations between these SNPs and biting phenotypes. SNPs in 8 mitochondrial genes (ATP6, ATP8, COX1, COX2, COX3, ND3, ND5 and CYTB) were also genotyped to test population subdivision within An. arabiensis. RESULTS: The candidate clock genes exhibited polymorphism within An. arabiensis, but it was unrelated to variation in the timing and location of their biting activity. However, there was evidence of strong genetic structure within An. arabiensis populations in association with the TIM, which was unrelated to geographic distance. Substructure within An. arabiensis was also detected using mitochondrial markers. CONCLUSIONS: The variable timing and location of biting in An. arabiensis could not be linked to candidate clock genes that are known to influence behaviour in other Diptera. This finding does not rule out the possibility of a genetic basis to biting behaviour in this malaria vector, but suggests these are complex phenotypes that require more intensive ecological, neuronal and genomic analyses to understand.

Evolution of biological complexity.

To make a case for or against a trend in the evolution of complexity in biological evolution, complexity needs to be both rigorously defined and measurable. A recent information-theoretic (but intuitively evident) definition identifies genomic complexity with the amount of information a sequence stores about its environment. We investigate the evolution of genomic complexity in populations of digital organisms and monitor in detail the evolutionary transitions that increase complexity. We show that, because natural selection forces genomes to behave as a natural "Maxwell Demon," within a fixed environment, genomic complexity is forced to increase.

Genome complexity, robustness and genetic interactions in digital organisms.

Digital organisms are computer programs that self-replicate, mutate and adapt by natural selection. They offer an opportunity to test generalizations about living systems that may extend beyond the organic life that biologists usually study. Here we have generated two classes of digital organism: simple programs selected solely for rapid replication, and complex programs selected to perform mathematical operations that accelerate replication through a set of defined 'metabolic' rewards. To examine the differences in their genetic architecture, we introduced millions of single and multiple mutations into each organism and measured the effects on the organism's fitness. The complex organisms are more robust than the simple ones with respect to the average effects of single mutations. Interactions among mutations are common and usually yield higher fitness than predicted from the component mutations assuming multiplicative effects; such interactions are especially important in the complex organisms. Frequent interactions among mutations have also been seen in bacteria, fungi and fruitflies. Our findings support the view that interactions are a general feature of genetic systems.