- Email: [email protected]
Temporal Coding of Sleep
Leading Edge
Previews Temporal Coding of Sleep Christopher S. Colwell1,* and Jeffrey Donlea2,* 1Department
of Psychiatry and Biobehavioral Sciences, Semel Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA of Neurobiology, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA 90095, USA *Correspondence: [email protected] (C.S.C.), [email protected] (J.D.) https://doi.org/10.1016/j.cell.2018.10.047 2Department
In Drosophila, well-delineated circuits control circadian rhythms, but the electrophysiological patterns that occur within these circuits are not well understood. In this issue, Tabuchi et al. clarify the temporal coding within a circuit, linking patterns of neural activity to sleep behavior. One of the fundamental concepts of neuroscience is that the frequency of action potentials encodes information—i.e., rate coding. When teaching, we may illustrate this relationship by using the example of a sensory neuron, where the intensity of the stimuli is directly related to the frequency of the action potentials generated, or perhaps in a motor neuron, where the frequency of firing is directly related to the force generated by the muscle under its regulation. While these examples are certainly valid, those of us who record the electrical activity of neurons appreciate that firing patterns are rarely as monotonic as would be implied from a simple rate-coding algorithm. Instead, many measurements reveal that the intervals between action potentials (the interspike intervals) are variable, with many cells exhibiting bursts of discharges. For many years, more computationally minded neuroscientists have suggested that this variability in interspike intervals is not just noise but is a highly regulated physiological process that conveys information—i.e., temporal coding. In this issue of Cell, Tabuchi et al. (2018) provide a timely example of how temporal coding works, with a particularly convincing link between sleep regulation and the patterns of discharge from a specific cell population (Figure 1). In Drosophila, well-delineated circuits control circadian rhythms, but the electrophysiological patterns that occur within these circuits are not well understood. The authors demonstrated the presence of naturally occurring temporal spiking patterns associated with day and night in the posterior dorsal neurons. During the day, these neurons are likely to fire in irregular bursts and then switch to a regular cadence at night. Importantly, these
daily changes in firing patterns exhibit circadian rhythmicity and require known clock genes. Next, the authors optogenetically imposed either day (irregular) or night (regular) activity patterns on posterior dorsal neurons and measured their effects on sleep. In the absence of changes in firing rate, posterior dorsal neuron spike timing serves as a temporal code to signify state-dependent arousal and impact sleep behavior—sleep episodes last longer when these neurons fire regularly and are more likely to be fragmented when these cells fire in irregular bursts (Figure 1A). Using a genetic screen, they identified a class of voltage-gated K+ currents (KCa, Slo1) along with a pump (Na+/ K+ ATPase) as critical drivers of the day/ night differences in electrical discharge. The KCa channels are responsible for the after-spike hyperpolarization, while Na+/ K+ ATPase activity alters the threshold for generation of, as well as repolarization after, the action potential. The authors used electrophysiological and computational analyses to show that the rhythmic regulation of these two biophysical processes can drive the daily changes in posterior dorsal neuron firing (Figure 1B). Within each posterior dorsal neuron, the circadian clock, working through the rhythmic output gene WAKE, appears to control the subcellular localization of these membrane proteins. Through WAKE, the molecular clock targets the proteins to the membrane at night and thus alters the membrane properties of these neurons. The posterior dorsal neurons directly project to a cell population that controls arousal (Dilp2+ neurons of the pars intercerebralis) (Barber et al, 2016). In the final set of experiments, the authors examined how the temporal patterning of discharge
in the posterior dorsal neurons impacts the Dilp2+ neurons. They first confirmed that these target cells (Dilp2+ neurons) exhibit a higher firing rate during the day than during the night. Next, they recorded from the target cells while simultaneously optogenetically activating the posterior dorsal clock neurons using day (irregular) or night (regular) temporal codes. They found that the irregular code leads to an increase in firing in the arousal-promoting output neurons. This potentiation took minutes to develop, persisted after the stimulation ended, and was dependent upon NMDA receptor signaling. This plasticity in firing in the Dilp2+ neurons was driven by the regularity, but not the rate, of firing in the presynaptic posterior dorsal neuron and represents a form of spike-timing plasticity. Future work will need to uncover the mechanism underlying the firing-rate plasticity in the pars intercerebralis (PI) neurons. Interestingly, two recent publications have also mapped connections from posterior dorsal neurons to visual neurons projecting from the anterior optic tubercle (Guo et al, 2018; Lamaze et al, 2018). If posterior dorsal neurons convey sleep-regulatory signals to multiple synaptic partners, then are all targets sensitive to temporal coding like the Dilp2+ neurons? Or might rate and temporal coding information be multiplexed in posterior dorsal neuron activity? The firing pattern of posterior dorsal neurons is governed only by the KCa and Na+/K+ pump and certainly involves other currents. For example, prior work from the Allada laboratory (Flourakis et al., 2015) demonstrated that the circadian clock regulates excitability via a Na+ leak conductance providing a concrete mechanism by which the molecular
Cell 175, November 15, 2018 ª 2018 Elsevier Inc. 1177
Figure 1. Proposed Model for How Clock-Dependent Temporal Coding Regulates Sleep Fragmentation (A) During the day (ZT6–8, yellow), DN1p clock neurons exhibit irregular firing with coefficient of variation (CV) of z1.2. Irregular firing of the DN1p triggers NMDA receptor-dependent plastic changes in the downstream arousal-promoting pars intercerebralis (PI, Dilp2+) neurons. While the mechanisms are not clear, this plasticity leads to an increase in firing rate of the PI neurons, and arousal is increased. Consequently, the sleep behavior exhibits increased fragmentation. During the night (ZT18–20, blue), DN1p clock neurons exhibit regular firing (CV z 0.3). The PI neurons are silent under this synaptic input, and sleep is consolidated. Optogenetic-driven changes in the firing pattern of the DN1p neurons can mimic the diurnal regulation. Regardless of the time of day, driving the DN1p neurons to fire regularly (CV of 0.3) leads to consolidated sleep, while irregular firing (CV of 1.2) leads to fragmented sleep. (B) At night, the circadian clock acts via WAKE to upregulate SLOB and NaKb to increase the KCa2+ current and Na+/K+ ATPase activity, respectively. These transcriptional/translational changes rhythmically alter the biophysical properties of action potentials to promote regular firing during the night. The regular pattern of action potentials does not trigger changes in firing in the PI neurons and these neurons fall silent.
clock can regulate membrane excitability. In addition, KCa currents would normally work in partnership with an L-type Ca2+ current, and the channels may even be in close physical proximity. In many spontaneously active pacemaker cells, the L-type Ca2+ channels open during membrane depolarization and allow Ca2+ to enter the cell. This Ca2+, as well as the membrane depolarization, would activate the KCa currents, which in turn repolarize the membrane. This feedback loop underlies a number of physiological oscillations. At the transcriptional level, the genes coding for these ion channels are under circadian control (Allen et al., 2017). For example, in mammals, the expression of one of the genes coding for L-type Ca2+ channels is rhythmic (peaking during the late night) and is regulated by the circadian clock component REV-ERBa (Schmutz et al., 2014). Therefore, when considering how the circadian rhythms in 1178 Cell 175, November 15, 2018
the temporal patterns of firing are generated, it is likely that more currents will be found to be critically involved. The present findings implicating a pivotal role of KCa or the so-called big potassium (BK) currents resonates with work done in the central circadian clock in mammals (suprachiasmatic nucleus). These neurons also exhibit a daily rhythm in electrical activity, with higher discharge during the day. Work from the Meredith laboratory indicates that the kinetic properties of the BK currents (slo1) shifts from day to night (Whitt et al., 2016). These channels are the mammalian homologs of the KCa described in the present work. During the day, the BK currents are inactivated with the net result of a more sustained BK current and membrane hyperpolarization during the night. This work implicated the regulation of the b2 subunit as a driver of the rhythm in suprachiasmatic nucleus firing. However, the
levels of the b2 subunit appeared to be stable through time, suggesting that the circadian clock regulation of this subunit is through posttranslational regulation. Interestingly, recent work in mouse models of Huntington’s Disease suggests that disruption of the BK current may underlie disturbed rhythms in suprachiasmatic nucleus neural activity reported in these models of neurodegeneration (Kuljis et al., 2018). The study by Tabuchi et al. (2018) comprises a technically demanding set of experiments that demonstrate a causal role for temporal coding in sleep regulation. These data show that downstream targets are regulated by an NMDA-dependent form of synaptic plasticity triggered solely by temporal patterns of synaptic inputs and provide an example of how Drosophila can be used to probe the molecular and neurophysiological basis of behavioral regulation. Rapid development
of optogenetic tools to define sleep and arousal circuits in mammals (Weber and Dan, 2016) may open the opportunity for testing whether similar coding also underlies sleep regulation in vertebrates. Hopefully, this work will lead to a better understanding of the spatiotemporal dynamics of neural activity that drives sleep in us all. REFERENCES Allen, C.N., Nitabach, M.N., and Colwell, C.S. (2017). Membrane Currents, Gene Expression, and Circadian Clocks. Cold Spring Harb. Perspect. Biol. 9, a027714. Barber, A.F., Erion, R., Holmes, T.C., and Sehgal, A. (2016). Circadian and feeding cues integrate to drive rhythms of physiology in Drosophila insulinproducing cells. Genes Dev. 30, 2596–2606.
Flourakis, M., Kula-Eversole, E., Hutchison, A.L., Han, T.H., Aranda, K., Moose, D.L., White, K.P., Dinner, A.R., Lear, B.C., Ren, D., et al. (2015). A Conserved Bicycle Model for Circadian Clock Control of Membrane Excitability. Cell 162, 836–848. Guo, F., Holla, M., Dı´az, M.M., and Rosbash, M. (2018). A Circadian Output Circuit Controls Sleep-Wake Arousal in Drosophila. Neuron. Published online September 22, 2018. https://doi.org/ 10.1016/j.neuron.2018.09.002. Kuljis, D., Kudo, T., Tahara, Y., Ghiani, C.A., and Colwell, C.S. (2018). Pathophysiology in the suprachiasmatic nucleus in mouse models of Huntington’s disease. J. Neurosci. Res. 96, 1862–1875. Lamaze, A., Kra¨tschmer, P., Chen, K.-F., Lowe, S., and Jepson, J.E.C. (2018). A Wake-Promoting Circadian Output Circuit in Drosophila. Curr. Biol. 28, 3098–3105.
Schmutz, I., Chavan, R., Ripperger, J.A., Maywood, E.S., Langwieser, N., Jurik, A., Stauffer, A., Delorme, J.E., Moosmang, S., Hastings, M.H., et al. (2014). A specific role for the REV-ERBa-controlled L-Type Voltage-Gated Calcium Channel CaV1.2 in resetting the circadian clock in the late night. J. Biol. Rhythms 29, 288–298. Tabuchi, M., Monaco, J.D., Duan, G., Bell, B., Liu, S., Liu, Q., Zhang, K., and Wu, M.N. (2018). ClockGenerated Temporal Codes Determine Synaptic Plasticity to Control Sleep. Cell 175, this issue, 1213–1227. Weber, F., and Dan, Y. (2016). Circuit-based interrogation of sleep control. Nature 538, 51–59. Whitt, J.P., Montgomery, J.R., and Meredith, A.L. (2016). BK channel inactivation gates daytime excitability in the circadian clock. Nat. Commun. 7, 10837.
Non-mendelian Inheritance in Mammals Is Highly Constrained Luke Isbel1,* and Dirk Schu¨beler1,2,* 1Friedrich
Miescher Institute for Biomedical Research, Basel, Switzerland of Basel, Faculty of Sciences, Basel, Switzerland *Correspondence: [email protected] (L.I.), [email protected] (D.S.) https://doi.org/10.1016/j.cell.2018.10.046 2University
In this issue, Kazachenka, Bertozzi, and colleagues identify elements in the mouse genome with epigenetic variability between littermates, a phenomenon linked to transmission of phenotypes over generations. This addresses two questions that remained unanswered despite intense speculation: how prevalent are these alleles, and what is their effect, within and across generations? The vast majority of heritable sources of phenotypic variation are of course genetic in origin; however, rare instances of trait variation in the absence of DNA mutation (i.e., within inbred colonies) are known to exist and are of great interest to the fields of genetics and development (Daxinger and Whitelaw, 2012; Heard and Martienssen, 2014). These inherited phenotypes can have profound effects over multiple generations, and there is speculation that this can be used to provide advantage while environmental conditions fluctuate without the need to acquire permanent genetic changes (Jablonka and Lamb, 1989). This could also account for some of the complexity in human pheno-
types, and the epigenetic factors involved are potential therapeutic targets. Critically, few established mammalian models exist in the literature, with limited evidence of the epigenetic mechanisms underlying phenotypic variation (Daxinger et al., 2016). While limited in number, these examples have been regarded as the ‘‘tip of the iceberg’’ by many scientists who consider epigenetic inheritance as a likely explanation of unknown phenotypic variance. It is thus essential to comprehensively define the frequency of such loci and the magnitude of their effect size. While several examples exist of nonmendelian inheritance in plants and worms,
there are relatively few in mammals. The best characterized of these are the Avy and AxinFu alleles that arose spontaneously within inbred mouse colonies; littermates display variable expression of these alleles and offspring tend to have expression states similar to the parents (Morgan et al., 1999; Rakyan et al., 2003). Avy results in varied pigmentation from yellow, mottled to pseudoagouti (brown) coat coloring (Figure 1), and AxinFu results in a normal or kinked tail. In both cases, the genetic basis of variation, or metastability, results from the insertion nearby a gene of an intracisternal A-particle (IAP), a relatively evolutionary young long terminal repeat element. Notably, while the DNA
Cell 175, November 15, 2018 ª 2018 Elsevier Inc. 1179
Previews Temporal Coding of Sleep Christopher S. Colwell1,* and Jeffrey Donlea2,* 1Department
of Psychiatry and Biobehavioral Sciences, Semel Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA of Neurobiology, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA 90095, USA *Correspondence: [email protected] (C.S.C.), [email protected] (J.D.) https://doi.org/10.1016/j.cell.2018.10.047 2Department
In Drosophila, well-delineated circuits control circadian rhythms, but the electrophysiological patterns that occur within these circuits are not well understood. In this issue, Tabuchi et al. clarify the temporal coding within a circuit, linking patterns of neural activity to sleep behavior. One of the fundamental concepts of neuroscience is that the frequency of action potentials encodes information—i.e., rate coding. When teaching, we may illustrate this relationship by using the example of a sensory neuron, where the intensity of the stimuli is directly related to the frequency of the action potentials generated, or perhaps in a motor neuron, where the frequency of firing is directly related to the force generated by the muscle under its regulation. While these examples are certainly valid, those of us who record the electrical activity of neurons appreciate that firing patterns are rarely as monotonic as would be implied from a simple rate-coding algorithm. Instead, many measurements reveal that the intervals between action potentials (the interspike intervals) are variable, with many cells exhibiting bursts of discharges. For many years, more computationally minded neuroscientists have suggested that this variability in interspike intervals is not just noise but is a highly regulated physiological process that conveys information—i.e., temporal coding. In this issue of Cell, Tabuchi et al. (2018) provide a timely example of how temporal coding works, with a particularly convincing link between sleep regulation and the patterns of discharge from a specific cell population (Figure 1). In Drosophila, well-delineated circuits control circadian rhythms, but the electrophysiological patterns that occur within these circuits are not well understood. The authors demonstrated the presence of naturally occurring temporal spiking patterns associated with day and night in the posterior dorsal neurons. During the day, these neurons are likely to fire in irregular bursts and then switch to a regular cadence at night. Importantly, these
daily changes in firing patterns exhibit circadian rhythmicity and require known clock genes. Next, the authors optogenetically imposed either day (irregular) or night (regular) activity patterns on posterior dorsal neurons and measured their effects on sleep. In the absence of changes in firing rate, posterior dorsal neuron spike timing serves as a temporal code to signify state-dependent arousal and impact sleep behavior—sleep episodes last longer when these neurons fire regularly and are more likely to be fragmented when these cells fire in irregular bursts (Figure 1A). Using a genetic screen, they identified a class of voltage-gated K+ currents (KCa, Slo1) along with a pump (Na+/ K+ ATPase) as critical drivers of the day/ night differences in electrical discharge. The KCa channels are responsible for the after-spike hyperpolarization, while Na+/ K+ ATPase activity alters the threshold for generation of, as well as repolarization after, the action potential. The authors used electrophysiological and computational analyses to show that the rhythmic regulation of these two biophysical processes can drive the daily changes in posterior dorsal neuron firing (Figure 1B). Within each posterior dorsal neuron, the circadian clock, working through the rhythmic output gene WAKE, appears to control the subcellular localization of these membrane proteins. Through WAKE, the molecular clock targets the proteins to the membrane at night and thus alters the membrane properties of these neurons. The posterior dorsal neurons directly project to a cell population that controls arousal (Dilp2+ neurons of the pars intercerebralis) (Barber et al, 2016). In the final set of experiments, the authors examined how the temporal patterning of discharge
in the posterior dorsal neurons impacts the Dilp2+ neurons. They first confirmed that these target cells (Dilp2+ neurons) exhibit a higher firing rate during the day than during the night. Next, they recorded from the target cells while simultaneously optogenetically activating the posterior dorsal clock neurons using day (irregular) or night (regular) temporal codes. They found that the irregular code leads to an increase in firing in the arousal-promoting output neurons. This potentiation took minutes to develop, persisted after the stimulation ended, and was dependent upon NMDA receptor signaling. This plasticity in firing in the Dilp2+ neurons was driven by the regularity, but not the rate, of firing in the presynaptic posterior dorsal neuron and represents a form of spike-timing plasticity. Future work will need to uncover the mechanism underlying the firing-rate plasticity in the pars intercerebralis (PI) neurons. Interestingly, two recent publications have also mapped connections from posterior dorsal neurons to visual neurons projecting from the anterior optic tubercle (Guo et al, 2018; Lamaze et al, 2018). If posterior dorsal neurons convey sleep-regulatory signals to multiple synaptic partners, then are all targets sensitive to temporal coding like the Dilp2+ neurons? Or might rate and temporal coding information be multiplexed in posterior dorsal neuron activity? The firing pattern of posterior dorsal neurons is governed only by the KCa and Na+/K+ pump and certainly involves other currents. For example, prior work from the Allada laboratory (Flourakis et al., 2015) demonstrated that the circadian clock regulates excitability via a Na+ leak conductance providing a concrete mechanism by which the molecular
Cell 175, November 15, 2018 ª 2018 Elsevier Inc. 1177
Figure 1. Proposed Model for How Clock-Dependent Temporal Coding Regulates Sleep Fragmentation (A) During the day (ZT6–8, yellow), DN1p clock neurons exhibit irregular firing with coefficient of variation (CV) of z1.2. Irregular firing of the DN1p triggers NMDA receptor-dependent plastic changes in the downstream arousal-promoting pars intercerebralis (PI, Dilp2+) neurons. While the mechanisms are not clear, this plasticity leads to an increase in firing rate of the PI neurons, and arousal is increased. Consequently, the sleep behavior exhibits increased fragmentation. During the night (ZT18–20, blue), DN1p clock neurons exhibit regular firing (CV z 0.3). The PI neurons are silent under this synaptic input, and sleep is consolidated. Optogenetic-driven changes in the firing pattern of the DN1p neurons can mimic the diurnal regulation. Regardless of the time of day, driving the DN1p neurons to fire regularly (CV of 0.3) leads to consolidated sleep, while irregular firing (CV of 1.2) leads to fragmented sleep. (B) At night, the circadian clock acts via WAKE to upregulate SLOB and NaKb to increase the KCa2+ current and Na+/K+ ATPase activity, respectively. These transcriptional/translational changes rhythmically alter the biophysical properties of action potentials to promote regular firing during the night. The regular pattern of action potentials does not trigger changes in firing in the PI neurons and these neurons fall silent.
clock can regulate membrane excitability. In addition, KCa currents would normally work in partnership with an L-type Ca2+ current, and the channels may even be in close physical proximity. In many spontaneously active pacemaker cells, the L-type Ca2+ channels open during membrane depolarization and allow Ca2+ to enter the cell. This Ca2+, as well as the membrane depolarization, would activate the KCa currents, which in turn repolarize the membrane. This feedback loop underlies a number of physiological oscillations. At the transcriptional level, the genes coding for these ion channels are under circadian control (Allen et al., 2017). For example, in mammals, the expression of one of the genes coding for L-type Ca2+ channels is rhythmic (peaking during the late night) and is regulated by the circadian clock component REV-ERBa (Schmutz et al., 2014). Therefore, when considering how the circadian rhythms in 1178 Cell 175, November 15, 2018
the temporal patterns of firing are generated, it is likely that more currents will be found to be critically involved. The present findings implicating a pivotal role of KCa or the so-called big potassium (BK) currents resonates with work done in the central circadian clock in mammals (suprachiasmatic nucleus). These neurons also exhibit a daily rhythm in electrical activity, with higher discharge during the day. Work from the Meredith laboratory indicates that the kinetic properties of the BK currents (slo1) shifts from day to night (Whitt et al., 2016). These channels are the mammalian homologs of the KCa described in the present work. During the day, the BK currents are inactivated with the net result of a more sustained BK current and membrane hyperpolarization during the night. This work implicated the regulation of the b2 subunit as a driver of the rhythm in suprachiasmatic nucleus firing. However, the
levels of the b2 subunit appeared to be stable through time, suggesting that the circadian clock regulation of this subunit is through posttranslational regulation. Interestingly, recent work in mouse models of Huntington’s Disease suggests that disruption of the BK current may underlie disturbed rhythms in suprachiasmatic nucleus neural activity reported in these models of neurodegeneration (Kuljis et al., 2018). The study by Tabuchi et al. (2018) comprises a technically demanding set of experiments that demonstrate a causal role for temporal coding in sleep regulation. These data show that downstream targets are regulated by an NMDA-dependent form of synaptic plasticity triggered solely by temporal patterns of synaptic inputs and provide an example of how Drosophila can be used to probe the molecular and neurophysiological basis of behavioral regulation. Rapid development
of optogenetic tools to define sleep and arousal circuits in mammals (Weber and Dan, 2016) may open the opportunity for testing whether similar coding also underlies sleep regulation in vertebrates. Hopefully, this work will lead to a better understanding of the spatiotemporal dynamics of neural activity that drives sleep in us all. REFERENCES Allen, C.N., Nitabach, M.N., and Colwell, C.S. (2017). Membrane Currents, Gene Expression, and Circadian Clocks. Cold Spring Harb. Perspect. Biol. 9, a027714. Barber, A.F., Erion, R., Holmes, T.C., and Sehgal, A. (2016). Circadian and feeding cues integrate to drive rhythms of physiology in Drosophila insulinproducing cells. Genes Dev. 30, 2596–2606.
Flourakis, M., Kula-Eversole, E., Hutchison, A.L., Han, T.H., Aranda, K., Moose, D.L., White, K.P., Dinner, A.R., Lear, B.C., Ren, D., et al. (2015). A Conserved Bicycle Model for Circadian Clock Control of Membrane Excitability. Cell 162, 836–848. Guo, F., Holla, M., Dı´az, M.M., and Rosbash, M. (2018). A Circadian Output Circuit Controls Sleep-Wake Arousal in Drosophila. Neuron. Published online September 22, 2018. https://doi.org/ 10.1016/j.neuron.2018.09.002. Kuljis, D., Kudo, T., Tahara, Y., Ghiani, C.A., and Colwell, C.S. (2018). Pathophysiology in the suprachiasmatic nucleus in mouse models of Huntington’s disease. J. Neurosci. Res. 96, 1862–1875. Lamaze, A., Kra¨tschmer, P., Chen, K.-F., Lowe, S., and Jepson, J.E.C. (2018). A Wake-Promoting Circadian Output Circuit in Drosophila. Curr. Biol. 28, 3098–3105.
Schmutz, I., Chavan, R., Ripperger, J.A., Maywood, E.S., Langwieser, N., Jurik, A., Stauffer, A., Delorme, J.E., Moosmang, S., Hastings, M.H., et al. (2014). A specific role for the REV-ERBa-controlled L-Type Voltage-Gated Calcium Channel CaV1.2 in resetting the circadian clock in the late night. J. Biol. Rhythms 29, 288–298. Tabuchi, M., Monaco, J.D., Duan, G., Bell, B., Liu, S., Liu, Q., Zhang, K., and Wu, M.N. (2018). ClockGenerated Temporal Codes Determine Synaptic Plasticity to Control Sleep. Cell 175, this issue, 1213–1227. Weber, F., and Dan, Y. (2016). Circuit-based interrogation of sleep control. Nature 538, 51–59. Whitt, J.P., Montgomery, J.R., and Meredith, A.L. (2016). BK channel inactivation gates daytime excitability in the circadian clock. Nat. Commun. 7, 10837.
Non-mendelian Inheritance in Mammals Is Highly Constrained Luke Isbel1,* and Dirk Schu¨beler1,2,* 1Friedrich
Miescher Institute for Biomedical Research, Basel, Switzerland of Basel, Faculty of Sciences, Basel, Switzerland *Correspondence: [email protected] (L.I.), [email protected] (D.S.) https://doi.org/10.1016/j.cell.2018.10.046 2University
In this issue, Kazachenka, Bertozzi, and colleagues identify elements in the mouse genome with epigenetic variability between littermates, a phenomenon linked to transmission of phenotypes over generations. This addresses two questions that remained unanswered despite intense speculation: how prevalent are these alleles, and what is their effect, within and across generations? The vast majority of heritable sources of phenotypic variation are of course genetic in origin; however, rare instances of trait variation in the absence of DNA mutation (i.e., within inbred colonies) are known to exist and are of great interest to the fields of genetics and development (Daxinger and Whitelaw, 2012; Heard and Martienssen, 2014). These inherited phenotypes can have profound effects over multiple generations, and there is speculation that this can be used to provide advantage while environmental conditions fluctuate without the need to acquire permanent genetic changes (Jablonka and Lamb, 1989). This could also account for some of the complexity in human pheno-
types, and the epigenetic factors involved are potential therapeutic targets. Critically, few established mammalian models exist in the literature, with limited evidence of the epigenetic mechanisms underlying phenotypic variation (Daxinger et al., 2016). While limited in number, these examples have been regarded as the ‘‘tip of the iceberg’’ by many scientists who consider epigenetic inheritance as a likely explanation of unknown phenotypic variance. It is thus essential to comprehensively define the frequency of such loci and the magnitude of their effect size. While several examples exist of nonmendelian inheritance in plants and worms,
there are relatively few in mammals. The best characterized of these are the Avy and AxinFu alleles that arose spontaneously within inbred mouse colonies; littermates display variable expression of these alleles and offspring tend to have expression states similar to the parents (Morgan et al., 1999; Rakyan et al., 2003). Avy results in varied pigmentation from yellow, mottled to pseudoagouti (brown) coat coloring (Figure 1), and AxinFu results in a normal or kinked tail. In both cases, the genetic basis of variation, or metastability, results from the insertion nearby a gene of an intracisternal A-particle (IAP), a relatively evolutionary young long terminal repeat element. Notably, while the DNA
Cell 175, November 15, 2018 ª 2018 Elsevier Inc. 1179