Evolution of time-keeping mechanisms: early emergence and adaptation to photoperiod

Abstract

Virtually all species have developed cellular oscillations and mechanisms that synchronize these cellular oscillations to environmental cycles. Such environmental cycles in biotic (e.g. food availability and predation risk) or abiotic (e.g. temperature and light) factors may occur on a daily, annual or tidal time scale. Internal timing mechanisms may facilitate behavioural or physiological adaptation to such changes in environmental conditions. These timing mechanisms commonly involve an internal molecular oscillator (a 'clock') that is synchronized ('entrained') to the environmental cycle by receptor mechanisms responding to relevant environmental signals ('Zeitgeber', i.e. German for time-giver). To understand the evolution of such timing mechanisms, we have to understand the mechanisms leading to selective advantage. Although major advances have been made in our understanding of the physiological and molecular mechanisms driving internal cycles (proximate questions), studies identifying mechanisms of natural selection on clock systems (ultimate questions) are rather limited. Here, we discuss the selective advantage of a circadian system and how its adaptation to day length variation may have a functional role in optimizing seasonal timing. We discuss various cases where selective advantages of circadian timing mechanisms have been shown and cases where temporarily loss of circadian timing may cause selective advantage. We suggest an explanation for why a circadian timing system has emerged in primitive life forms like cyanobacteria and we evaluate a possible molecular mechanism that enabled these bacteria to adapt to seasonal variation in day length. We further discuss how the role of the circadian system in photoperiodic time measurement may explain differential selection pressures on circadian period when species are exposed to changing climatic conditions (e.g. global warming) or when they expand their geographical range to different latitudes or altitudes.

Figure 1.

Postulated temporal patterns of phosphorylation and dephosphorylation of KaiC in (a) summer and (b) winter. The phosphorylation phase is hypothesized to be stimulated by KaiA, starting with dephosphorylated KaiC hexamers at dawn and reaching fully phosphorylated hexamers at dusk.

Figure 2.

Proposed role of the Kai proteins in evolutionary adaptation to photoperiod. Both in short and in long days, the number of phosphorylated KaiC hexamers decreases at about the same constant low rate. In short days this process lasts longer, so more hexamers must be formed in the day, requiring more KaiC production per hour than in long days and more phosphorylation. Since phosphorylation of KaiC must be complete at the end of the shorter day, KaiA is expected to be present at an even higher concentration in short days. If KaiB signals the dephosphorylation status of the hexamer complexes, this will happen during the night, both in short and in long days.

Figure 3.

The dual role of the SCN in daily and annual rhythms as illustrated by its input and output pathways. Arrow connection ends indicate stimulatory pathways, flat connection ends indicate inhibitory pathways. SCN, suprachiasmatic nucleus; PVN, paraventricular nucleus; IML, intermediolateral column of the spinal cord; SCG, superior cervical ganglion.

Figure 4.

Oscillator speed affects photoperiodic time measurement: differences between external (a) and internal (b) coincidence timings. (a) In an external coincidence timing model, longer circadian periods (slower speed) will generate larger phase angle differences with morning light (grey triangle) owing to a lagging phase angle of the circadian oscillator relative to the light–dark cycle. Short circadian periods (faster speed) will generate smaller phase angle differences with morning light owing to the leading phase angle of the circadian oscillator relative to the light–dark cycle. Hence, internal representation of day length will be longer in slower pacemakers (the reverse being true when evening light induces the photoperiodic response). (b) In an internal coincidence timing model, the circadian oscillator is composed of (at least) two oscillators, a morning (light grey curve) and an evening (dark grey curve) oscillator. The phase angle difference of these two oscillators determines the internal photoperiod representation. Intrinsic period of the combined system will generate leading and lagging properties of both oscillators causing a compression of the phase angle difference when intrinsic period deviates from 24 h. Hence, internal representation of day length will be longer when pacemaker period approaches 24 h.

Figure 5.

External (a,b) and internal (c,d) coincidence timing models lead to different predictions for directional selection pressure on circadian period. As follows from figure 4, the relationship between internal and external photoperiods will be differentially affected by circadian period when external (a) or internal (c) coincidence timing is assumed. Plotting internal photoperiod (for a given external photoperiod) against circadian period (τ) yields different curves for external (b) and internal (d) coincidence timing. For external coincidence timing, morning light would generate an inverse relationship between τ and internal photoperiod (b, continuous curve) compare with evening light (b, dashed curve). The curves in (b) and (d) enable predictions on how selection pressure would act on τ when an earlier long-day response is favoured during spring (e.g. at lower latitudes or warmer climatic conditions) for external (b) coincidence and internal (d) coincidence timing. For this example, the directional selection pressures on τ are indicated for both models (black arrows).