There are important differences between the
latitudinal structure of trends for the second half
of the 20th century and for the 21st century
(2000–2014) (Fig. 3). For example, the Arctic latitudes
have shown strong warming trends both
over the land and ocean since 2000, but during
the latter half of the 20th century, the ocean
trends in this area are near zero. The longer-term
50-year trend has more consistency in the rates
of warming across all latitudes, and this is even
more evident over the full period of record back
to 1880 (fig. S1). There is a distinct Northern
Hemisphere mid-latitude cooling in LST during
the 21st century, which is also showing up in
cooling of the cold extremes, as reported for the
extreme minimum temperatures in this zone in
(27). Atmospheric teleconnections and regional
forcings could be relevant in understanding these
short time-scale zonal trends. It is evident that in
most latitude bands, the global trends in the past
15 years are comparable with trends in the preceding
50 years.
Last, we considered the impact of larger warming
rates in high latitudes (24) on the overall
global trend. To estimate the magnitude of the
additional warming, we applied large-area interpolation
over the poles using the limited observational
data available. Results indicate that, indeed,
additional global warming of a few hundredths of
a degree Celsius per decade over the 21st century
is evident (Fig. 1), providing further evidence
against the notion of a recent warming “hiatus”
(supplementary materials).
Newly corrected and updated global surface
temperature data from NOAA’s NCEI do not
support the notion of a global warming “hiatus.”
As shown in Fig. 1, there is no discernable (statistical
or otherwise) decrease in the rate of
warming between the second half of the 20th
century and the first 15 years of the 21st century.
Our new analysis now shows that the trend over
the period 1950–1999, a time widely agreed as
having significant anthropogenic global warming
(1), is 0.113°C decade−1
, which is virtually
indistinguishable from the trend over the period
2000–2014 (0.116°C decade−1
). Even starting a
trend calculation with 1998, the extremely warm
El Niño year that is often used as the beginning
of the “hiatus,” our global temperature trend
(1998–2014) is 0.106°C decade−1
—and we know
that is an underestimate because of incomplete
coverage over the Arctic. Indeed, according to our
new analysis, the IPCC’s (1) statement of 2 years
ago—that the global surface temperature “has
shown a much smaller increasing linear trend
over the past 15 years than over the past 30 to
60 years”—is no longer valid.
REFERENCES AND NOTES
1. IPCC, Climate Change 2013: The Physical Science Basis.
Contribution of Working Group I to the Fifth Assessment Report
of the Intergovernmental Panel on Climate Change,
T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen,
J. Boschung, A. Nauels, Y. Xia, V. Bex, P.M. Midgley, Eds.
(Cambridge Univ. Press, Cambridge, 2013).
2. G. A. Meehl, H. Teng, J. M. Arblaster, Nature Clim. Change 4,
898–902 (2014).
3. G. A. Meehl, A. Hu, J. M. Arblaster, J. Fasullo, K. E. Trenberth,
J. Clim. 26, 7298–7310 (2013).
4. Y. Kosaka, S.-P. Xie, Nature 501, 403–407 (2013).
5. M. H. England et al., Nature Clim. Change 4, 222–227 (2014).
6. B. D. Santer et al., Nat. Geosci. 7, 185–189 (2014).
7. G. A. Schmidt, D. T. Shindell, K. Tsigaridis, Nat. Geosci. 7,
158–160 (2014).
8. J. Tollefson, Nature 505, 276–278 (2014).
9. M. Watanabe et al., Geophys. Res. Lett. 40, 3175–3179
(2013).
10. J. C. Fyfe, N. P. Gillett, Nature Clim. Change 4, 150–151 (2014).
11. K. E. Trenberth, J. T. Fasullo, M. A. Balmaseda, J. Clim. 27,
3129–3144 (2014).
12. H. Ding, R. J. Greatbatch, M. Latif, W. Park, R. Gerdes, J. Clim.
26, 7650–7661 (2013).
13. B. Huang et al., J. Clim. 28, 911–930 (2015).
14. J. J. Rennie et al., Geosci. Data J. 1, 75–102 (2014).
15. E. C. Kent, J. J. Kennedy, D. I. Berry, R. O. Smith, Clim. Change
1, 718–728 (2010).
16. R. W. Reynolds, N. A. Rayner, T. M. Smith, D. C. Stokes,
W. Wang, J. Clim. 15, 1609–1625 (2002).
17. R. W. Reynolds, D. B. Chelton, J. Clim. 23, 3545–3562 (2010).
18. J. J. Kennedy, N. A. Rayner, R. O. Smith, D. E. Parker,
M. Saunby, J. Geophys. Res. Atmos. 116 (D14), D14104 (2011).
19. J. H. Lawrimore, J. J. Rennie, P. W. Thorne, Eos 94, 61 (2014).
20. M. J. Menne, I. Durre, R. S. Vose, B. E. Gleason, T. G. Houston,
J. Atmos. Ocean. Technol. 29, 897–910 (2012).
21. M. J. Menne, C. N. Williams Jr., J. Clim. 22, 1700–1717 (2009).
22. J. H. Lawrimore et al., J. Geophys. Res. 116 (D19), D19121
(2011).
23. C. N. Williams, M. J. Menne, P. W. Thorne, J. Geophys. Res. 117
(D5), D05116 (2012).
24. K. Cowtan, R. G. Way, Q. J. Roy. Met. Soc. 140, 1935–1944
(2014).
25. B. Santer et al., Int. J. Climatol. 28, 1703–1722 (2008).
26. T. M. Smith, R. W. Reynolds, J. Clim. 16, 1495–1510 (2003).
27. J. Sillman, M. G. Donat, J. C. Fyfe, F. W. Zwiers, Environ. Res.
Lett. 9, 064023 (2014).
ACKNOWLEDGMENTS
We thank the many scientists at NCEI and at other institutions who
routinely collect, archive, quality control, and provide access to the
many complex data streams that go into the computation of the
global surface temperature. In particular, we thank T. Boyer,
B. Gleason, J. Matthews, J. Rennie, and C. Williams for their
contributions to this analysis. We also thank J. Meehl and P. Duffy
for constructive comments on an early version of this manuscript.
SUPPLEMENTARY MATERIALS
www.sciencemag.org/content/348/6242/1469/suppl/DC1
Materials and Methods
Fig. S1
Table S1
References (28–38)
23 December 2014; accepted 21 May 2015
Published online 4 June 2015;
10.1126/science.aaa5632
BRAIN CIRCUITS
A parvalbumin-positive excitatory
visual pathway to trigger fear
responses in mice
Congping Shang,1,2
Zhihui Liu,1
Zijun Chen,1,2
Yingchao Shi,1,2
Qian Wang,1
Su Liu,1
Dapeng Li,1
Peng Cao1
*
The fear responses to environmental threats play a fundamental role in survival. Little is
known about the neural circuits specifically processing threat-relevant sensory information
in the mammalian brain. We identified parvalbumin-positive (PV+
) excitatory projection
neurons in mouse superior colliculus (SC) as a key neuronal subtype for detecting looming
objects and triggering fear responses. These neurons, distributed predominantly in the
superficial SC, divergently projected to different brain areas, including the parabigeminal
nucleus (PBGN), an intermediate station leading to the amygdala. Activation of the PV+
SC-PBGN pathway triggered fear responses, induced conditioned aversion, and caused
depression-related behaviors. Approximately 20% of mice subjected to the fearconditioning
paradigm developed a generalized fear memory.
E
nvironmental threats are detected by different
sensory organs projecting to central
brain areas to trigger fear responses (1, 2).
The superior colliculus (SC) is a retinal recipient
structure (3, 4) composed of different
neuronal subtypes (5, 6), including parvalbuminpositive
(PV+
), somatostatin-positive (SST+
), and
vasoactive intestinal peptide–positive (VIP+
) neurons
(Fig. 1A and fig. S1). In addition to mediating
orienting responses (7), the SC contributes
to avoidance and defense-like behaviors (8–11).
With an optogenetic approach (12–14), we found
that activation of neurons expressing channelrhodopsin-2
(ChR2) in mouse SC triggered freezing
that lasted 52.8 T 5.3 s (n = 5 mice) (movie
S1). This prompted us to systematically identify
the key neuronal subtypes underlying this
behavior.
By crossing Ai32 (15) with different Cre lines
(Fig. 1B) (16, 17), we expressed ChR2–enhanced
yellow fluorescent protein (EYFP) in specific
neuronal subtypes in the SC (Fig. 1C and fig. S1)
and optogenetically elicited spikes in acute slices
(Fig. 1D and fig. S1). Activation of SC PV+
neurons,
but not SST+
or VIP+
neurons, triggered impulsive
escaping (1.18 T 0.09 s) followed by long-lasting
freezing (46.4 T 2.8 s) (Fig. 1, E to G; fig. S1; and
movie S2). To avoid activation of PV+
retinal
1472 26 JUNE 2015 • VOL 348 ISSUE 6242 sciencemag.org SCIENCE
1
State Key Laboratory of Brain and Cognitive Sciences,
Institute of Biophysics, Chinese Academy of Sciences,
Beijing 100101, China. 2
University of Chinese Academy of
Sciences, Beijing 100049, China.
*Corresponding author. E-mail: pcao@ibp.ac.cn
RESEARCH | REPORTS
onJuly14,2015www.sciencemag.orgDownloadedfromonJuly14,2015www.sciencemag.orgDownloadedfromonJuly14,2015www.sciencemag.orgDownloadedfromonJuly14,2015www.sciencemag.orgDownloadedfromonJuly14,2015www.sciencemag.orgDownloadedfromonJuly14,2015www.sciencemag.orgDownloadedfrom
ganglion cells (RGCs) (18) by ferrule light, we injected
adeno-associated virus (AAV) expressing
double-floxed ChR2-mCherry (12) into the SC of
PV-ires-Cre mice, resulting in specific expression
of ChR2-mCherry in SC PV+
neurons but
not in PV+
RGCs (Fig. 2A and fig. S2). The light
triggered spikes from ChR2-mCherry–positive
neurons in SC slices (Fig. 2B and fig. S2), elicited
a similar stereotyped locomotor pattern
(fig. S2 and movie S3), and increased the heart
rate and plasma corticosterone levels that were
not observed in mice with SC PV+
neurons expressing
mCherry (Fig. 2, C and D).
When facing threats, animals can either fight
or flee. To test whether SC PV+
neurons were
involved in this behavioral dichotomy, we measured
the durations of light-induced escaping
(E) and freezing (F) and calculated their ratio
(E/F ratio). We conducted a series of tests spanning
5 days (table S1). First, light stimulations
with higher intensity or longer duration enhanced
E/F ratios in the same male mice by prolonging
escaping more strongly than freezing (Fig. 2, E
and F). Second, light stimulations with higher
frequency but similar total illumination time
prolonged escaping and freezing proportionally
(Fig. 2G). Third, both responses showed strong
adaptation to repetitive light stimulations (every
5 min), with no significant change in E/F ratios
across each stimulation (Fig. 2H). Finally,
the same light stimulations elicited longer escaping
and shorter freezing in female versus
male mice, resulting in higher E/F ratios in females
(Fig. 2I). The origin of these sexually
dimorphic behaviors was further examined (supplementary
text).
We next characterized the morphological and
physiological properties of SC PV+
neurons.
They were predominantly but not exclusively
distributed in the superficial gray (SuG) layer of
the SC (Fig. 3A and fig. S3). Whole-cell recording
of tdTomato-expressing PV+
neurons in SC
slices from PV-ires-Cre; Ai9 mice (19) demonstrated
that, distinct from V1 PV+
interneurons
with slow frequency adaptation (20), the
SuG PV+
neurons responded to depolarizing currents
in a faster adaptation mode (Figs. 3, C
and D, and fig. S3). SuG PV+
neurons labeled
with neurobiotin had parallel dendrites extending
to the SC surface, presumably receiving
inputs from RGCs (Fig. 3B and fig. S3). The
postsynaptic currents from PV-negative neurons
induced by optogenetic activation of PV+
neurons
expressing ChR2-mCherry were blocked by
SCIENCE sciencemag.org 26 JUNE 2015 • VOL 348 ISSUE 6242 1473
9
***
STOP
CAG
promoter
ChR2-EYFPAi32
ires
SST, PV or VIP gene
CreCre lines
EYFP / PV / DAPI
PV-ires-Cre;Ai32SST-ires-Cre;Ai32
0
0.3
0.6
0.9
1.2
Speedoflocomotion(m/sec)
-5 0 5 10 25 30 35
Time relative to light stimulation initiation (sec)
Light stimulation
SST-ires-Cre
PV-ires-Cre
0
0.2
0.4
0.6
0.8
1.0
1.2
0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
Traveldistance(m)
Peakspeed(m/sec)
During Stimulation (5 sec)
After Stimulation (30 sec)
0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Traveldistance(m)
0
0.02
0.04
0.06
0.08
0.10
0.12
Peakspeed(m/sec)
9 7
9 9 99
SST+
PV+
20
During Stimulation (5 sec) After Stimulation (30 sec)Before Stimulation (5 sec)
StartEnd Start
End
StartEnd
Start
End
Start
End
Start/End
7
VIP+
***
99
7
***
7
***
EYFP / SST / DAPI
n.s.
n.s.
n.s. n.s.
SST+
PV+
VIP+
SST+
PV+
VIP+
SST+
PV+
VIP+
PV-ires-Cre;Ai32SST-ires-Cre;Ai32
PV-ires-Cre
SST-ires-Cre
1 mm 20 µm
2 ms 10Hz
20 mV0.1 s
10 cm
2 ms 10Hz
EYFP / DAPI
250 µm
EYFP / DAPI
1 mm 20 µm250 µm
Fig. 1. Neuronal subtypes in the SC to trigger fear responses. (A) Diagram
of different neuronal subtypes in the SC. (B) Ai32 mice were crossed with
different Cre lines. (C) Coronal micrographs showing ChR2-EYFP expressed in
specific neuronal subtypes. DAPI, 4′,6-diamidino-2-phenylindole. (D) Lightinduced
spikes from ChR2-EYFP+
neurons in acute slices. (E) Instantaneous
locomotion speed before, during, and after light stimulation. (Inset)
Locomotion trails from example mice. (F and G) Analyses of peak speed
and travel distance during and after light stimulation. Data in (F) and (G)
are means T SEM (error bars); numbers of mice are in bars. Statistical
analysis is t test (***P < 0.001; n.s. P > 0.1). Dashed lines in (F) and (G)
indicate the control levels measured from behaviors after SC SST+
neuron
activation.
RESEARCH | REPORTS
D-(–)-2-amino-5-phosphonopentanoic acid (APV)
and 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX),
but not by picrotoxin (Fig. 3, E and F, and fig.
S3), suggesting that these neurons were glutamatergic
but did not release g-aminobutyric
acid. The SC PV+
neurons in intermediate and
deep layers of the SC were examined (supplementary
text).
To test whether SC PV+
neurons were involved
in detecting collision threats in the visual field
(21–23), we displayed a virtual soccer ball moving
in controlled velocities and directions to the
anaesthetized mice (Fig. 3J and fig. S4). The singleunit
activity recorded with optrodes was quantitatively
identified (24, 25) as putative SC PV+
neurons expressing ChR2-mCherry (Fig. 3, G to
I). These putative PV+
neurons (n = 9 cells) were
strongly activated by the ball moving toward
the animal but not by the motion in the other
five directions (Fig. 3K). The response onset
time before collision depended on the size and
velocity of the ball (Fig. 3L) and was linearly
correlated with the square root of the diameter/
velocity (Fig. 3M). The response peak was close
to the time to collision and was independent
of the size and velocity of the soccer ball (Fig.
3N). In freely behaving mice, the escaping triggered
by SC PV+
neuron activation pointed to
the side of the SC receiving light stimulation
(movie S4).
We then determined the circuit mechanism
underlying the fear responses mediated by SC
PV+
neurons. By injecting AAV expressing doublefloxed
monomeric green fluorescent protein
(mGFP) into the SC of PV-ires-Cre mice, we specifically
labeled SC PV+
neurons (Fig. 4B and
figs. S5 and S6) and observed axon terminals in
the parabigeminal nucleus (PBGN), the pontine
nucleus (Pn), and the dorsal lateral geniculate
nucleus (DLGN) (Fig. 4, A and C). These projections
were confirmed by retrograde tracing
with cholera toxin B with Alexa Fluor-594 (CTB-
594). CTB-594 injection into the PBGN (Fig. 4D)
retrogradely labeled SC neurons predominantly
in the ipsilateral SuG layer (Fig. 4E and fig. S7).
A considerable proportion of CTB-labeled SC
neurons (SC-PBGN: 52 T 4.3%; SC-Pn: 31 T 4.5%;
SC-DLGN: 33 T 3.8%, n = 3 mice) were positive
for PV (Fig. 4F and fig. S7).
To determine which of these parallel projections
(26) participated in the fear responses, we
injected AAV expressing double-floxed ChR2mCherry
into the SC and implanted optic fibers
in the PBGN or Pn (Fig. 4G) to locally stimulate
the ChR2-mCherry–positive axon terminals. Activation
of the PV+
SC-PBGN pathway, but not the
PV+
SC-Pn pathway, triggered the stereotyped
1474 26 JUNE 2015 • VOL 348 ISSUE 6242 sciencemag.org SCIENCE
8
**
8
ChR2-mCherry/DAPI
Merge
PV
ChR2-mCherry
10 Hz & 2 ms
ChR2-mCherry+
0
0.5
1
1.5
2
1 2 3
0
20
40
60
1 2 3
0
1
2
3
4
5
1 2 3
Adaptation
F
F
Gender
0
1
2
3
0
10
20
30
40
50
0
10
20
30
40
50
M
M
M F
***
***
Escaping(sec)Freezing(sec)
0
0.5
1.0
1.5
2.0
0
20
40
60
80
Intensity
0
1
2
3
4
12 20 mW
***
***
*** **
**
**
Frequency
0
0.3
0.6
0.9
1.2
1.5
1.8
0
10
20
30
40
50
60
0
1
2
3
4
5
10 Hz1.0
***
***
Escaping(sec)Freezing(sec)E/Fratio(%)
Duration
0
10
20
30
40
50
60
70
0
0.4
0.8
1.2
1.6
0
1
2
3
4
5
0.5s 5.0s
***
***
**
Escaping(sec)Freezing(sec)
0.5s 5.0s
0.5s 5.0s
10 Hz1.0
E/Fratio(%)
E/Fratio(%)
Escaping(sec)
Escaping(sec)
Freezing(sec)
Freezing(sec)
E/Fratio(%)
E/Fratio(%)
9 9
9 9
9 9
10 Hz1.0
12 20 mW
12 20 mW
0
40
80
120
160
PlasmaCORT(ng/ml)
0
100
200
300
400
500
HeartRate(beats/min)
**
ECG Waveform
Before20min
1 sec
40min
8 888
Ctrl ChR2
C
trlC
hR
2
600
Stim -
C
trlC
hR
2
C
trlC
hR
2
Before 20 min 40 min
C
trlC
hR
2
Stim +
C
trlC
hR
2
88 88
n.s.n.s.
n.s.
n.s.
n.s.
1 mm
20 µm
PV+ PV-
ChR2-mCherry-
0.2 s
15 mV
0.2 nA
AAV-DIO-ChR2-mCherry
PV-ires-Cre mice
20 µm
20 µm
Fig. 2. Specific activation of SC PV+
neurons induced fear responses.
(A) Specific expression of ChR2-mCherry in SC PV+
neurons of PV-ires-Cre
mice. (B) The light-pulse train triggered spikes (red) from ChR2-mCherry–
positive neurons and postsynaptic currents (black) from adjacent ChR2mCherry–negative
neurons. (C) Electrocardiographic traces and heart rate
analyses from the anaesthetized mice before and after light stimulations.
Ctrl, control. (D) Analyses of plasma corticosterone concentration in
response to light stimulation. (E to I) Durations of escaping, freezing, and
E/F ratios, were plotted as functions of stimulation intensity, duration,
frequency, repetition, and sex in mice with SC PV+
neurons expressing
ChR2-mCherry. Data in (C) to (I) are means T SEM (error bars); numbers
of mice are in bars. Statistical analysis is t test (***P < 0.001; **P < 0.01;
n.s. P > 0.1). Dashed lines indicate the levels measured from control mice.
M, male; F, female.
RESEARCH | REPORTS
escaping-freezing locomotor pattern (Fig. 4, H to
J; fig. S9, and movie S5). We examined whether
PBGN projected to the amygdala by anterograde
and retrograde tracings. Local injection of AAVSynaptoTag
(27) in the PBGN and its adjacent
region strongly labeled axon terminals positive
for synaptobrevin-2–EGFP in the central amygdaloid
nucleus (28, 29), whereas CTB-594 injection
in the amygdala retrogradely labeled neurons in
the PBGN (fig. S8). Finally, the relation between
PV+
SC-PBGN pathway activation and the affective
state of mice was explored (supplementary
text and figs. S10 to S12). Taken together, these
data revealed a PV+
excitatory visual pathway to
trigger stereotyped fear responses in mice.
SCIENCE sciencemag.org 26 JUNE 2015 • VOL 348 ISSUE 6242 1475
Z+
Z-
X+
X-
Y+
Y-5
0 5
Time (ms)
20lightpulsesat10Hz
Before
After
+PTX
Ctrl +APV/CNQX
0
200
400
600
800
+APV/CNQX
EvokedPSC(pA)
Before
After
Ctrl +PTX
EvokedPSC(pA)
PV+ neurons
V1
0.1 nA
0.2 nA
0.3 nA
Spikenumber
0
40
80
120
160
200
0
0.2
0.4
0.6
0.8
1.0
Current injection (nA)
0 0.2 0.4 0.6
Spikingphase(sec)
PV+ neurons
SC-SuG
0
20
40
60
0
20
40
60
0
20
40
60
V= 5 m/s
D= 20 cm
V= 2 m/s
D= 40 cm
V= 5 m/s
D= 40 cm
0
20
40
60
V= 2 m/s
D= 20 cm
Firingrate(spike/sec)
Time before collision (sec)
-3 -2 -1 0 -3 -2 -1 0
-2.0
-1.5
-1
-0.5
0
0.1 0.2 0.3 0.4
Square root of diameter/velocity
V1
Z+ Z-
X-
X+
Y+
Y-
Laser
Recording
ResponseOnset(sec)ResponsePeak(ms)
-300
-200
-100
0
0.1 0.2 0.3 0.4
Square root of diameter/velocity
******
***
SC vs. V1
SC vs. V1
0
200
400
600
800 n.s.
0.4 mm
100 µm
0.5 s 25 mV
25 µV50 ms
25 µV3 ms
40 µV1 s
R = -0.997
R = -0.336
P = 0.003
P = 0.664
n=11
n=10
n=11
n=10
-0.2
0
0.2
0.4
0.6
0.8
1.0
0.01 0.1 1.0 10 100
Waveformcorrelation
Light-evoked energy ( mV x s )2
visual
25 µV3 ms
light
n= 9 units
n= 9 units
n=9
n=10
Onset Onset
Onset Onset
SC-SuG
100 ms 0.1 nA
100 ms 0.1 nA
Fig. 3. Morphological and physiological properties of SC PV+
neurons.
(A) Layer-specific distribution of SC PV+
neurons. (B) Neurobiotin-labeled
PV+
neurons in the SC SuG layer and V1. (C) Spike firings of PV+
neurons in
the SC and V1 to depolarizing currents. (D) Analyses of spike number and
spiking phase as a function of current intensity. n, number of cells. (E and F)
Effects of CNQX (20 mM)/APV (50 mM) (E) and picrotoxin (50 mM) (F) on the
postsynaptic currents (PSC) induced by light stimulation. n, number of cells.
(G) Single-unit activity recorded from a putative SC PV+
neuron triggered by
light pulses (arrows, 1 ms at 10 Hz). (H) Raster plot showing the latency of
light-evoked spikes relative to the light pulses (0 ms). (I) Distributional plot
(left) and example spikes (right) evoked by visual stimuli and light showing
quantitative identification of PV-positive and PV-negative units based on the
waveform correlation and energy of light-evoked spikes. (J) A virtual soccer
ball flying toward the eye of an anaesthetized mouse. (K) Example single-unit
traces from a putative SC PV+
neuron in response to the soccer ball (20 cm
in diameter) moving in six directions at 2 m/s. (L) Peristimulus time histograms
of a PV+
neuron to looming stimuli with controlled velocities (V) (2
and 5 m/sec) and diameters (D) (20 and 40 cm). Arrows indicate response
onset time. (M and N) Correlation analyses of response onset time (M) and
response peak time (N) of SC PV+
neurons and the square root of
diameter/velocity of the looming ball. Data are means T SEM (error bars);
numbers of cells or units are in graphs. Statistical analyses are t test and
one-way analysis of variance (***P < 0.001; n.s. P > 0.1). R, correlation
coefficient.
RESEARCH | REPORTS
Our data lead to the following conclusions.
First, the SC PV+
neurons form a subcortical visual
pathway that transmits threat-relevant visual
information to the amygdala to trigger fear responses.
These data, in alliance with earlier studies
(18, 30, 31), suggest a “retina-SC-PBGN-amygdalahypothalamus”
pathway for vision-induced fear
responses. Second, the SC PV+
neurons in the
SuG layer are predominantly glutamatergic
1476 26 JUNE 2015 • VOL 348 ISSUE 6242 sciencemag.org SCIENCE
PBG
SuG/Zo
Op
InG
DpG InW
CTB-594
Pn
Pn
PBG
AAV
OpticFiber
0
0.2
0.4
0.6
0.8
1.0
1.2
Peakspeed(m/sec)
After Stimulation (30s)
SC
9
PBG
9 10
SC
Ctrl ChR2
During Stimulation (5 sec)
0
0.6
0.8
1.0
1.2
1.4
1.6Traveldistance(m)
11 9 9 10
PnSC PBGSC
Ctrl ChR2
Pn
0
0.02
0.04
0.06
0.08
0.10
0.12
Peakspeed(m/sec)
SC
9
PBG
9
10
SC
Ctrl ChR2
0
0.6
1.2
1.8
2.4
3.0
3.6
Traveldistance(m)
11
9 9
10
PnSC PBGSC
Ctrl ChR2
0
0.2
0.4
0.6
0.8
1.0
1.2
Escapingduration(sec)
9 9
SC PBG
ChR2
0
10
20
30
40
50
Freezingduration(sec)
9 9
SC PBG
ChR2
0
1.0
1.5
2.0
2.5
3.0
3.5
E/Fratio(%)
9 9
SC PBG
ChR2
11
1.4
0.4
0.2
1.4 60
0.5
11
***
***
***
***
*** *** *** ***
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
1 mm
SC: PV / CTB-594 / DAPI
30 µm
1 mm 1 mm
GFP / DAPI
PBG
Pn
SC
1 mm
PBG: GFP / DAPI Pn: GFP / DAPI DLG: GFP / DAPI
30 µm
SC: PV SC: GFP SC: merge
30 µm
30 µm 30 µm
30 µm 30 µm
Fig. 4. PV+
SC-PBGN pathway mediated fear responses. (A to C) Specific
expression of mGFP in SC PV+
neurons (B) of PV-ires-Cre mice resulted in
labeling of their axon terminals in the PBGN, Pn, and DLGN [(A) and (C)].
(D to F) CTB-594 injected in the PBGN (D) retrogradely labeled cells in
the SC (E), a large proportion of which were PV+
(denoted by arrowheads)
(F). DpG, deep gray layer; InW, intermediate white layer; Ing, intermediate
gray layer; Op, optic nerve layer; Zo, zonal layer. (G) Diagrams showing the
optic fibers implanted either above the PBGN or the Pn to stimulate ChR2mCherry–positive
axon terminals. (H and I) Locomotion analyses during
and after the activation of PV+
SC-PBGN and SC-Pn pathways. (J) Analyses
of escaping, freezing, and E/F ratio in mice receiving activation of the PV+
SC-PBGN pathway and SC PV+
neurons. Data in (H) to (J) are means T SEM
(error bars); numbers of mice are in bars. Statistical analysis is t test (***P <
0.001; n.s. P > 0.1).
RESEARCH | REPORTS
projection neurons with spiking patterns distinct
from those of their counterparts in cortical
regions. Thus, this finding broadens the
concept of PV+
neurons (32) and adds another
perspective to understanding their functions.
Third, the SC PV+
neurons may belong to type-r
looming detector, supporting the notion that
mathematically defined computational units
correspond to specific neuronal subtypes (33).
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ACKNOWLEDGMENTS
We thank T. Südhof, K. Deisseroth, Y. Wang, B. Li, and M. Luo for
providing plasmids, instruments, and technical support for this study.
This work was supported by the Thousand Young Talents Program
of China. We declare no conflicts of interest. All data are archived in the
Institute of Biophysics, Chinese Academy of Sciences.
SUPPLEMENTARY MATERIALS
www.sciencemag.org/content/348/6242/1472/suppl/DC1
Materials and Methods
Supplementary Text
Figs. S1 to S12
Table S1 and S2
Reference (34)
Movies S1 to S5
Data S1
6 February 2015; accepted 28 May 2015
10.1126/science.aaa8694
STRUCTURAL BIOLOGY
A Cas9–guide RNA complex
preorganized for target
DNA recognition
Fuguo Jiang,1
Kaihong Zhou,2
Linlin Ma,2
Saskia Gressel,3
Jennifer A. Doudna1,2,4,5,6,7
*
Bacterial adaptive immunity uses CRISPR (clustered regularly interspaced short
palindromic repeats)–associated (Cas) proteins together with CRISPR transcripts for
foreign DNA degradation. In type II CRISPR-Cas systems, activation of Cas9 endonuclease
for DNA recognition upon guide RNA binding occurs by an unknown mechanism. Crystal
structures of Cas9 bound to single-guide RNA reveal a conformation distinct from both
the apo and DNA-bound states, in which the 10-nucleotide RNA “seed” sequence required
for initial DNA interrogation is preordered in an A-form conformation. This segment of
the guide RNA is essential for Cas9 to form a DNA recognition–competent structure
that is poised to engage double-stranded DNA target sequences. We construe this as
convergent evolution of a “seed” mechanism reminiscent of that used by Argonaute
proteins during RNA interference in eukaryotes.
C
RISPR-Cas proteins function in complex
with mature CRISPR RNAs (crRNAs) to
identify and cleave complementary target
sequences in foreign nucleic acids (1). In
type II CRISPR systems, the Cas9 enzyme
cleaves DNA at sites defined by the 20-nucleotide
(nt) guide segment within crRNAs, together with
a trans-activatingcrRNA (tracrRNA) (2) that forms
a crRNA:tracrRNA hybrid structure capable of
Cas9 association (3). Once assembled on target
DNA, the Cas9 HNH and RuvC nuclease domains
cleavethedouble-strandedDNA(dsDNA)sequence
within the strands that are complementary and
noncomplementary to the guide RNA segment,
respectively (3, 4) (Fig. 1A). By engineering a synthetic
single-guide RNA (sgRNA) that fuses the
crRNA and tracrRNA into a single transcript of
80 to 100 nt (Fig. 1B), Cas9:sgRNA has been harnessed
as a two-component programmable system
forgenome engineeringinvarious organisms (5, 6).
The utility of Cas9 for both bacterial immunity
and genome engineering applications relies on
accurate DNA target selection. Target choice relies
on base pairing between the DNA and the 20-nt
guide RNA sequence, as well as the presence of a
2– to 4–base pair (bp) protospacer adjacent motif
(PAM) proximal to the target site (3, 4). The target
complementarity of a “seed” sequence within
the guide segment of crRNAs is critical for DNA
recognition and cleavage (7, 8). In type II CRISPR
systems, Cas9 binds to targets by recognizing a
PAM and searching the adjacent DNA for complementarity
to the 10- to 12-nt “seed” sequence
at the 3′ end of the guide RNA segment (Fig. 1B)
(3, 9–11). Crystal structures of Cas9 bound to
sgRNA and a target DNA strand, with or without
a partial PAM-containing nontarget strand, show
the entire 20-nt guide RNA segment engaged in
an A-form helical interaction with the target
DNA strand (12, 13). How the “seed” region within
the guide RNA specifies DNA binding has remained
unknown.
To determine how Cas9 assembles with and
positions the guide RNA prior to substrate recognition,
we solved the crystal structure of catalytically
active Streptococcus pyogenes Cas9 (SpyCas9)
in complex with an 85-nt sgRNA at 2.9 Å resolution
(Fig. 1 and table S1). The overall structure
of the Cas9-sgRNA binary complex, representing
the pre–target-bound state of the enzyme, resembles
the bilobed architecture of the target DNA–
bound state, as observed in electron microscopic
studies (14), with the guide segment of the sgRNA
positioned in the central channel between the
nuclease and helical recognition lobes (Fig. 1, C
to E). This structural architecture and guide RNA
organization is maintained in the crystal structure
of a widely used nuclease-inactive version of Cas9
(D10A/H840A, referred to as dCas9) in complex
with sgRNA (fig. S1).
Comparison of SpyCas9 crystal structures representing
the protein alone and the RNA-bound
and RNA-DNA–bound states of the enzyme reveals
the nature of Cas9’s conformational flexibility during
sgRNA binding and target DNA recognition
(Fig. 2A and figs. S2 and S3). The helical recognition
lobe undergoes substantial rearrangements
upon sgRNA binding but before DNA association,
especially in helical domain 3, which moves as
a rigid body by ~65 Å into close proximity with
the HNH domain (fig. S2D). Superposition of
the Cas9-sgRNA pre–target-bound complex onto
the target DNA–bound structures reveals further
SCIENCE sciencemag.org 26 JUNE 2015 • VOL 348 ISSUE 6242 1477
1
Department of Molecular and Cell Biology, University of
California, Berkeley, CA 94720, USA. 2
Howard Hughes
Medical Institute, University of California, Berkeley, CA
94720, USA. 3
Max Planck Institute for Biophysical Chemistry,
37077 Göttingen, Germany. 4
California Institute for
Quantitative Biosciences, University of California, Berkeley,
CA 94720, USA. 5
Department of Chemistry, University of
California, Berkeley, CA 94720, USA. 6
Physical Biosciences
Division, Lawrence Berkeley National Laboratory, Berkeley,
CA 94720, USA. 7
Innovative Genomics Initiative, University of
California, Berkeley, CA 94720, USA.
*Corresponding author. E-mail: doudna@berkeley.edu
RESEARCH | REPORTS
DOI: 10.1126/science.aaa8694
, 1472 (2015);348Science
et al.Congping Shang
responses in mice
A parvalbumin-positive excitatory visual pathway to trigger fear
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