articles Functional imaging with cellular resolution reveals precise microarchitecture in visual cortex Kenichi Ohki , Sooyoung Chung * , Yeang H. Ch ` ng * , Prakash Kara * & R. Clay Reid Department of Neurobiology , Harvard Medical School , Boston , Massachusetts 02115 , USA * These middle authors contributed equally to this work ... . Neurons in the cerebral cortex are organized into anatomical columns , with ensembles of cells arranged from the surface to the white matter . Within a column , neurons often share functional properties , such as selectivity for stimulus orientation ; columns with distinct properties , such as different preferred orientations , tile the cortical surface in orderly patterns . This functional architecture was discovered with the relatively sparse sampling of microelectrode recordings . Optical imaging of membrane voltage or metabolic activity elucidated the overall geometry of functional maps , but is averaged over many cells -LRB- resolution > 100 mm -RRB- . Consequently , the purity of functional domains and the precision of the borders between them could not be resolved . Here , we labelled thousands of neurons of the visual cortex with a calcium-sensitive indicator in vivo . We then imaged the activity of neuronal populations at single-cell resolution with two-photon microscopy up to a depth of 400 mm . In rat primary visual cortex , neurons had robust orientation selectivity but there was no discernible local structure ; neighbouring neurons often responded to different orientations . In area 18 of cat visual cortex , functional maps were organized at a fine scale . Neurons with opposite preferences for stimulus direction were segregated with extraordinary spatial precision in three dimensions , with columnar borders one to two cells wide . These results indicate that cortical maps can be built with single-cell precision . One of the hallmarks of cortical functional architecture1 ,2 is that maps vary continuously across the cortical surface , but are punctuated by occasional jumps or discontinuities . Optical imaging of either metabolically related intrinsic signals or voltage-sensitive dyes3 5 has shown the two-dimensional structure of functional maps , including discontinuities in orientation6 and direction7 ,8 maps in visual cortex . Even in combination with electrophysiology9 , however , it has been difficult to determine whether neurons of different functional types are mixed or kept separate near discontinuities . More generally , previous methods have been unable to examine whether there is any fine-scale organization -- a functional micro-architecture -- either near discontinuities or in cortical areas that lack functional architecture , such as rat visual cortex10 ,11 . As an alternative to optical imaging of intrinsic signals or voltagesensitive dyes , calcium-sensitive indicators12 can be used to measure activity in single neurons with very high signal-to-noise ratios . When two-photon microscopy13 is used to image intracellularly loaded neurons in the cerebral cortex in vivo14 ,15 calcium signals in cell bodies and dendrites can be imaged with submicrometre resolution . Earlier experiments in vitro16 ,17 showed that bulk loading of neocortical cells with cell-permeant forms of calcium-sensitive indicators allows the activity of hundreds of neuronal cell bodies to be observed in parallel . We adapted a recent protocol for bulk loading in vivo18 to study the functional micro-architecture of visual cortex . same duration . We imaged cells at a single focal plane continuously during multiple repetitions of the stimulus protocol . We repeated this protocol at multiple depths , 10 20 mm apart , to study the threedimensional functional architecture of layer 2/3 at single-cell resolution . At the end of these experiments , we often performed an anatomical reconstruction with 1-mm spacing in depth -LRB- Fig. 1a , top panel -RRB- . In rat primary visual cortex -LRB- n = 9 animals -RRB- , we found that 25 75 % of stained cells at a given depth in layer 2/3 responded to at least one stimulus with a significant change in fluorescence -LRB- P , 0.01 , analysis of variance -LRB- ANOVA -RRB- across blank and eight direction periods ; see Methods -RRB- . Of the visually responsive cells , 61 % on average were selective for the orientation and/or direction of the stimulus -LRB- P , 0.01 , ANOVA across eight directions -RRB- . We found a smaller proportion of visually responsive cells compared with previous electrophysiological studies10 ,11,19 . This might be explained by our optimization of stimulus parameters for populations rather than individual neurons , and by our far more complete sampling of neurons -LRB- see Supplementary Discussion and Supplementary Fig. 1 -RRB- , some of which might not have been detected with electrophysiology . As demonstrated elsewhere18 ,20 , somatic calcium signals reflect action potential activity , rather than subthreshold depolarizations . Our measurements were therefore sufficient to examine the relative selectivity of cells for different stimuli -LRB- see Supplementary Discussion -RRB- . Because the drifting stimuli that we used typically evoke prolonged electrophysiological responses from layer 2/3 cortical neurons -LRB- see below -RRB- , we could sample the calcium signal at a slow rate -LRB- ,1 frame s21 -RRB- . The visually evoked calcium transients were analysed in several ways . First , we calculated single-condition maps of the change in fluorescence -LRB- DF -RRB- by averaging the images collected during each of the eight visual stimuli and subtracting the average baseline between stimuli -LRB- Fig. 1b , outer panels ; see also Supplementary Fig. 2 for DF/F maps -RRB- . The maps show cells -LRB- seen as light spots -RRB- that were active with specific orientations of visual stimuli . These data were com597 Functional architecture in rat visual cortex We first examined the functional architecture of orientation selectivity in layer 2/3 of rat primary visual cortex . Several thousand layer 2/3 cells were loaded with a calcium indicator -LRB- Fig. 1a and Methods -RRB- injected into a region 200 400 mm in diameter . Responses of labelled cells to visual stimuli were studied with gratings -LRB- light and dark bars -RRB- at four different orientations , each drifted in two opposite directions . These eight patterns were presented sequentially for 4 8 s each , interspersed with blank -LRB- uniform -RRB- stimuli of the NATURE | VOL 433 | 10 FEBRUARY 2005 | www.nature.com/nature 2005 Nature Publishing Group articles bined into a single , colour-coded orientation map -LRB- Fig. 1c -RRB- , in which the hue of each pixel is determined by the best orientation and the colour saturation is proportional to the sharpness of orientation tuning21 . A cell-based analysis of our images allowed us to examine stimulus selectivity more quantitatively for individual neurons . First , cells in the anatomical image -LRB- Fig. 1a -RRB- were identified and outlined with a semi-automated algorithm . Next , all the pixels within a cell outline were summed to give a single time course -LRB- DF/F -RRB- over the entire duration of the visual stimulation protocol -LRB- eight directions of motion -RRB- . Single-cell averaged responses showed clear peaks in fluorescence -LRB- up to 30 % -RRB- during visual stimulation -LRB- Fig. 1d , grey regions -RRB- and returned to baseline in the intervals between stimuli -LRB- Fig. 1d , white regions -RRB- . These time courses are consistent with the sustained electrophysiological responses evoked by drifting-grating stimuli -LRB- see below -RRB- and the calcium kinetics of neurons -LRB- see Supplementary Discussion and Supplementary Fig. 1 -RRB- . The responses were often selective for stimulus orientation -LRB- Fig. 1d , cells 1 4 -RRB- and sometimes for direction -LRB- cell 3 -RRB- . Selective responses could often be discerned in single trials -LRB- Fig. 1d -RRB- . Neighbouring cells , for example cells 1 3 in Fig. 1e , were often highly tuned to different orientations . Their responses were entirely uncorrelated -LRB- Fig. 1d -RRB- , confirming that two-photon calcium imaging has singlecell resolution with little or no cross talk -LRB- see Supplementary Discussion -RRB- . The orientation maps generated by the pixel-based and cell-based analyses are similar -LRB- Fig. 1c , e -RRB- . The cell-based analysis allowed us to examine population statistics and is thus used in all subsequent figures . Functional architecture in cat visual cortex Previous single-unit electrophysiological studies have failed to discern any order in the orientation preference of nearby neurons in rat visual cortex10 ,11 . Even with our far more complete sampling at single-cell resolution , we found no discernible local structure -LRB- see Supplementary Discussion -RRB- . By contrast , in cat visual cortex the overall functional architecture is exquisitely organized . For example , intrinsic-signal optical imaging has shown that area 18 of the cat visual cortex has regions with roughly constant orientation6 and direction preferences7 -LRB- for ferret , see ref . 8 -RRB- . These regions are punctuated by singularities in the orientation map -LRB- pinwheels6 -RRB- and reversals in the direction map7 ,8 . The low resolution of optical imaging , however , could not show the degree of Figure 1 Functional maps of selective responses in rat visual cortex with single-cell resolution . a , In vivo images of cortical cells stained with a calcium indicator , OGB-1 AM . The top panel shows a volume of stained cells -LRB- depth of 85 400 mm including .3,000 cells -RRB- reconstructed from images obtained with 1 mm spacing in depth ; the bottom panel is an anatomical image at 290 mm below the pia , averaged over all frames during the visual stimulation protocol . b , Single-condition maps -LRB- DF -RRB- for eight directions of visual stimuli -LRB- outer panels ; the arrows indicate stimulus direction -RRB- . Each map is the average of eight repeats . In this and subsequent figures , the scale bar -LRB- DF -RRB- only applies to the outer 598 panels . The central panel is re-drawn from a. c , Pixel-based orientation map , in which hue is determined by the best orientation -LRB- see text and Methods -RRB- , overlaid with the anatomical image in a. d , Time courses of four orientation-selective cells -LRB- 1 4 -RRB- in e . The upper traces show the average response to eight repeats -LRB- ^ s.e.m. in grey -RRB- ; lower traces show three individual repeats . Visual stimulation periods for eight directions are indicated by grey bars . e , Cell-based orientation map . Visually responsive cells -LRB- P , 0.01 , ANOVA ; 45/115 -RRB- are coloured according to their preferred orientation . Scale bars , 100 mm . 2005 Nature Publishing Group NATURE | VOL 433 | 10 FEBRUARY 2005 | www.nature.com/nature articles uniformity of iso-direction or iso-orientation domains . It was therefore unknown whether all the neurons in a domain had similar responses , or some interspersed cells were tuned to very different orientations or directions . Furthermore , optical imaging could not be used to determine the spatial scale of either orientation singularities or the boundaries between directional domains , although electrophysiological studies have given some hints9 ,22,23 . We therefore studied the functional micro-architecture of layer 2/3 in cat visual cortical area 18 -LRB- n = 10 animals -RRB- . Out of 6,734 cells identified , 63 % were visually responsive -LRB- P , 0.01 ; ANOVA across blank and eight direction periods -RRB- . Of the responsive cells , 97 % were selective for orientation and/or direction -LRB- P , 0.01 ; ANOVA across eight directions -RRB- . Of these , 86 % were direction selective -LRB- direction index .0.33 ; see Methods for definition -RRB- . One possible reason for the unresponsive cells -LRB- 37 % -RRB- is low signal-to-noise ratio in some dimly stained cells , particularly at the edges of the stained region . Another factor is that the stimulus parameters -LRB- bar size and drift velocity -RRB- were not optimized for all cells . However , it should be noted that in some cases , 100 % of identified cells were responsive and tuned to orientation and/or direction . In two out of ten experiments , we found regions where orientation and direction selectivity varied slowly over the entire field of view -LRB- a square region 240 300 mm on a side : smaller than the 400-mm spatial scale of direction or orientation domains6 ,7 -RRB- . In one of these cases , single-condition maps -LRB- Fig. 2a , eight outer panels -RRB- showed that responses to 908 or 1358 predominated . Of the 65 cells with statistically significant tuning for orientation or direction -LRB- P , 0.01 -RRB- , all had similar direction selectivity : no cells responded better to the opposite directions -LRB- 2708 and 3158 ; Fig. 2b -RRB- . Furthermore , the transition of the preferred direction from 908 to 1358 was smooth and ordered ; each cell responded similarly to its nearest neighbours -LRB- Fig. 2b , c -RRB- . This uniformity and smoothness of direction maps leads to the question : what is the fine-scale structure near borders or discontinuities in the map ? Because orientation pinwheels are sparsely scattered over cat visual cortical area 18 -LRB- refs 6 , 24 -RRB- , we chose to examine the transition zones between regions of opposite direction preferences . The strict dichotomy between opposite directions offered an ideal opportunity to study the precision of a columnar border in the cerebral cortex . Optical imaging demonstrated overlap between regions that respond to opposite directions7 ,8 , but it could neither determine the spatial scale of the boundary between regions , nor indicate whether cells with opposite direction preferences are mixed together . In eight out of ten experiments , our images included boundaries between regions of opposite direction selectivity . In one such case , single-condition direction maps -LRB- Fig. 3a -RRB- showed activation of cells -LRB- and neuropil to a lesser extent , see Supplementary Fig. 2 -RRB- almost exclusively to stimuli of one orientation moving in either direction -LRB- 458 and 2258 -RRB- . More importantly , the clusters of cells that were activated by opposite directions were highly segregated . To quantify the spatial scale of the direction border at single-cell resolution , we identified cells that were selective to orientation and colour coded them for their preferred direction -LRB- Fig. 3b -RRB- . The time courses of single-cell responses -LRB- Fig. 3c -RRB- illustrate the reproducibility between individual trials and also the degree of direction tuning on both sides of the direction border . Cells closer to the direction border were progressively less directionally selective . Nonetheless , almost all of these cells had a measurable bias so that a preferred direction could be assigned -LRB- Fig. 3b , grey green and grey red cells -RRB- . The border between cells that were biased for opposite directions was so sharp that a straight line perfectly segregated them -LRB- vertical line in Fig. 3b -RRB- . A second example from a different animal also shows a precise direction fracture -LRB- Fig. 3d -RRB- . The degree of segregation on either side of the direction border in Fig. 3b was quantified for three depths separated by 20 mm -LRB- Fig. 4 ; see also Supplementary Fig. 3 -RRB- to examine the columnar border in three dimensions . At all three depths , the direction discontinuities -LRB- or fracture lines -RRB- were found to be precise at the scale of neighbouring cells : ,10 20 mm -LRB- Fig. 4a c -RRB- . As noted , neurons were progressively less directional -LRB- with direction index ,0.33 -RRB- in a transition zone 30 50 mm wide -LRB- Fig. 4d f -RRB- , but even the weakly biased cells had the same preferred direction as their neighbours on the same side of the border . The scales of the transition zone -LRB- 30 50 mm -RRB- and particularly of the direction discontinuity -LRB- 10 20 mm -RRB- are surprising given the 250 400-mm width of dendritic trees of neurons in cortical layer 2/3 -LRB- refs 25 27 -RRB- . As a control , the direction tuning of calcium signals was compared with single-unit electrophysiology in two additional experiments . Calcium signals were imaged briefly at low laser power , followed by extensive electrophysiological recordings . In one of these experiments , calcium images showed both smoothly changing orientation domains and a direction discontinuity -LRB- Fig. 5a -RRB- . Multiple penetrations with tungsten microelectrodes were made in different direction domains . Four representative cells responded in a sustained fashion to the drifting gratings for the entire period of stimulation -LRB- Fig. 5b , histograms -RRB- . The direction selectivity of the electrophysiological responses matched the selectivity seen with calcium imaging in all four sites -LRB- Fig. 5b , polar plots -RRB- , 599 Figure 2 Smoothly changing direction map in cat visual cortex . a , Single-condition maps -LRB- DF -RRB- imaged 200 mm below the pia are shown in the outer panels . The central panel shows the anatomical image as in Fig. 1 . Because of the wide brightness range , some stained cells are not discernible in this image . b , Vector map of preferred direction , calculated from cells with significant visual response and selectivity -LRB- per cent change .5 % and P , 0.01 , ANOVA -RRB- . Red and green vectors indicate the magnitudes of the preferred and null responses , respectively . Preferred direction of identified cells changes smoothly -LRB- in a down and rightward direction -RRB- with no cells preferring upward motion . c , Colour-coded direction map , according to the colour keys in a. Scale bars , 100 mm . NATURE | VOL 433 | 10 FEBRUARY 2005 | www.nature.com/nature 2005 Nature Publishing Group articles including smoothly changing orientation domains -LRB- sites 1 and 3 -RRB- , weakly directional responses near the border -LRB- site 4 -RRB- , and opposite direction tuning across the border -LRB- site 2 -RRB- . ordinarily sharp -LRB- Figs 3 and 4 -RRB- . In maps with discontinuities , cell pairs separated by any given distance have relative directional preferences that are bi-modally distributed -LRB- Fig. 6c -RRB- . This bimodal distribution follows from the sharp fracture between cells with opposite direction preferences -LRB- Fig. 4a c -RRB- . The differences between the visual cortex in cats and rats raise the question of the role of functional architecture in cortical computations28 . As we have confirmed , cells in the rat can be orientation selective although there is no apparent functional architecture11 ; however , cats29 have narrower orientation and direction tuning than rats11 . One might therefore speculate that well-ordered cortical maps may provide an advantage in the sharpening of visual responses by connections between neighbouring neurons with similar stimulus selectivity . Three regimes of functional micro-organization We have demonstrated three qualitatively different regimes of functional micro-organization in the visual cortex . The differences between these three regimes are illustrated in Fig. 6 for single experiments , but similar results were obtained for our entire sample -LRB- see Supplementary Discussion -RRB- . First , in rat visual cortex the distance between cells had no relationship to their relative direction preferences -LRB- Fig. 6a ; r 2 = 0.005 , P . 0.1 -RRB- or orientation preferences -LRB- not shown -RRB- : highly tuned cells were distributed across the cortex with no apparent local structure -LRB- as in Fig. 1 ; but see also Supplementary Discussion -RRB- . Second , in cat visual cortical area 18 , direction domains are quite uniform ; there are no interspersed cells tuned to the opposite directions -LRB- Fig. 2 -RRB- . Furthermore , the preferred direction varies smoothly at the level of neighbouring cells . Consequently , differences between preferred directions are positively correlated with the distance between cells -LRB- Fig. 6b ; r 2 = 0.16 , P , 10210 -RRB- . Third , we have found that when there are direction discontinuities in cat area 18 , the borders are extra - Discussion The ability to examine the receptive-field properties of almost every neuron in a local volume opens up a new realm of experimental investigations of the cerebral cortex . As illustrated in this study , it can show the degree of homogeneity and precision in cortical maps . Maps that are locally disordered , such as the orientation map of rat visual cortex -LRB- Fig. 1 -RRB- , seem inconsistent with the theory that Figure 3 Direction discontinuity in cat visual cortex . a , Single-condition maps -LRB- DF -RRB- imaged 180 mm below the pia are shown in the outer panels . The central panel shows the anatomical image as in Fig. 1 . Cells were activated almost exclusively by stimuli of one orientation moving in either direction -LRB- 458 and 2258 -RRB- . To the non-preferred stimuli , such as 908 , the calcium responses were so small and the noise was so low that the singlecondition maps are almost indistinguishable from zero . b , Cell-based direction map ; 100 % of cells had significant responses . Colour specifies preferred direction -LRB- green , 600 2258 ; red , 458 -RRB- . The cells responding to both 458 and 2258 are displayed as grey , according to their direction index -LRB- see colour scale on right -RRB- . The vertical white line below the arrow indicates approximate position of the direction discontinuity . The discontinuity was curved in the upper right of the panel -LRB- see Supplementary Fig. 3 -RRB- , so we excluded the neurons above the arrow from quantitative analysis . c , Single-trial time courses of six cells , numbered -LRB- 1 6 -RRB- as in b. Five trials -LRB- out of ten -RRB- are superimposed . d , Direction discontinuity from another animal , imaged 240 mm below the pia . Scale bars , 100 mm . NATURE | VOL 433 | 10 FEBRUARY 2005 | www.nature.com/nature 2005 Nature Publishing Group articles Figure 4 Sharpness of direction discontinuity at multiple depths . a c , Preferred direction of each cell plotted against the distance from the direction discontinuity -LRB- vertical white line below arrow in Fig. 3b ; see Supplementary Fig. 3 -RRB- . Single-cell precision was observed at three depths -LRB- a , 180 mm ; b , 200 mm ; c , 220 mm -RRB- . The three discontinuity lines were shifted by 6 mm between sections , so they all fell in a near-vertical plane . d f , The signed direction index -LRB- SDI , negative for 2258 ; positive for 458 -RRB- plotted against the distance from the direction discontinuity . Between two regions of high selectivity , the transition -LRB- jSDIj , 0.33 ; bounded by grey lines -RRB- was very rapid , in the range of 30 50 mm . Figure 6 Three regimes of functional organization . For all pairs of cells , the difference in preferred direction is plotted against distance between them . a , Rat visual cortex -LRB- from Fig. 1e -RRB- . b , A smoothly changing direction map in cat visual cortex -LRB- from Fig. 2c -RRB- . c , A direction discontinuity in cat visual cortex -LRB- from Fig. 3b -RRB- . cortical connections are determined solely by the spatial extent of dendritic and axonal arborizations30 . Instead , connections onto cells with overlapping dendritic arborizations might be selective , as in the case of thalamic inputs to cat visual cortex31 . For instance , groups of layer 2/3 neurons with similar orientation preferences might be selectively interconnected to form partially isolated subnetworks . If maps are structured at a finer spatial scale than the dendritic trees of local neurons , as seen in the borders between direction columns in cat area 18 , then what are the mechanisms driving this precision ? There are several possibilities : -LRB- 1 -RRB- that selective connections between individual neurons with similar tuning dictate the receptive-field properties on either side of the border ; -LRB- 2 -RRB- that smaller anatomical features , such as bundles of apical dendrites32 , are functionally important ; or -LRB- 3 -RRB- that precise inhibitory circuits might dominate neuronal response properties . Single-cell calcium Figure 5 Correspondence of direction tuning obtained by calcium imaging and single-unit electrophysiology in cat visual cortex . a , Calcium imaging at 160 mm from the pia . Singlecondition maps -LRB- DF -RRB- are shown in the outer panels . The central image is a hue-lightnesssaturation map , in which preferred direction is colour coded according to the key shown as arrows in outer panels . b , Histograms are post-stimulus time histograms -LRB- PSTHs -RRB- of four single-unit responses , showing the average spike rates in response to the visual NATURE | VOL 433 | 10 FEBRUARY 2005 | www.nature.com/nature stimuli . Polar plots -LRB- to the right of PSTHs -RRB- show the normalized magnitude of responses to eight stimulus directions , obtained from calcium imaging -LRB- red -RRB- and single-unit activity -LRB- blue -RRB- . Responses of single units were obtained from the PSTHs by summing firing during the stimulus period . Calcium signals were summed over a square region , 40 mm on a side -LRB- white boxes in a -RRB- , which were selected to match the electrode positions , but not necessarily at the same depth . 601 2005 Nature Publishing Group articles imaging combined with other techniques might address these different possibilities . For example , stronger correlations between anatomy and physiology could be achieved by labelling cells to reveal their transmitters or other molecular markers , their projection patterns , or their detailed dendritic and axonal morphology . From its inception , the idea of functional architecture has been considered both at a macroscopic scale , hundreds of micrometres to several millimetres , and at a microscopic scale , mini-columns ,50 mm wide32 ,33 . Until now , the microscopic scale could only be studied with microelectrodes , which typically sample neurons sparsely and without precise localization . Single-cell calcium imaging in vivo promises to elucidate the relationship between anatomy and physiology in neuronal ensembles at an unprecedented level of completeness . Combined with a characterization of the sensory or motor function of single neurons , it could permit the study of micro-functional architecture throughout the cerebral cortex and reveal other examples of maps that have single-cell precision . A 6,734 cells from cats -RRB- through a series of morphological filters that identified the contours of cell bodies based on intensity , size and shape . Cell outlines were visually inspected and the rare but clear errors were corrected manually . Time courses of individual cells were extracted by summing pixel values within cell contours . Occasionally , slow drift of the baseline signal over minutes was removed by a low-cut filter -LRB- cut-off , 2 4 min -RRB- . Visually responsive cells were defined by ANOVA across blank and eight direction periods -LRB- P , 0.01 ; 737 cells from rats , 37 % ; 4,246 cells from cats , 63 % -RRB- . Of these , selective cells to orientation/direction were defined by ANOVA across eight direction periods -LRB- P , 0.01 ; 452 cells from rats , 61 % ; 4,113 cells from cats , 97 % -RRB- . In cell maps -LRB- Figs 2b , c and 3b , d -RRB- , only selective cells are colour coded . For selective cells , the direction index was defined as 1 2 -LRB- response to null direction -RRB- / -LRB- response to preferred direction -RRB- . If the direction index was larger than 0.33 -LRB- ref . 36 -RRB- , the cell was considered to be direction selective -LRB- 3,522 cells from cats , 86 % of the total of orientation-selective cells -RRB- . Preferred orientation was obtained by vector averaging23 . Preferred direction was defined as the angle that showed maximum response in the interpolated tuning curve37 . For pixel-based analysis , images were averaged over stimulus repetitions , and spatially smoothed -LRB- gaussian , j = 1 mm -RRB- . Fluorescence change -LRB- DF -RRB- maps were obtained by subtracting images during the blank period from images during which one of eight directions was presented . In Fig. 1c , a huelightness-saturation orientation map21 was overlaid on the anatomical image . Received 19 October ; accepted 14 December 2004 ; doi : 10.1038 / nature03274 . Published online 19 January 2005 . 1 . Mountcastle , V. B. Modality and topographic properties of single neurons of cat 's somatic sensory cortex . J. Neurophysiol . 20 , 408 434 -LRB- 1957 -RRB- . 2 . Hubel , D. H. & Wiesel , T. N. Receptive fields , binocular interaction and functional architecture in the cat 's visual cortex . J. Physiol . -LRB- Lond . -RRB- 160 , 106 154 -LRB- 1962 -RRB- . 3 . Grinvald , A. , Anglister , L. , Freeman , J. A. , Hildesheim , R. & Manker , A. 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Morphology and intracortical projections of functionally characterised neurones in the cat visual cortex . Nature 280 , 120 125 -LRB- 1979 -RRB- . 26 . Martin , K. A. & Whitteridge , D . The relationship of receptive field properties to the dendritic shape of neurones in the cat striate cortex . J. Physiol . -LRB- Lond . -RRB- 356 , 291 302 -LRB- 1984 -RRB- . 27 . Hirsch , J. A. Synaptic physiology and receptive field structure in the early visual pathway of the cat . Cereb . Cortex 13 , 63 69 -LRB- 2003 -RRB- . 28 . Adams , D. L. & Horton , J. C. Capricious expression of cortical columns in the primate brain . Nature Neurosci . 6 , 113 114 -LRB- 2003 -RRB- . 29 . Rose , D. & Blakemore , C . An analysis of orientation selectivity in the cat 's visual cortex . Exp . Brain Res . 20 , 1 17 -LRB- 1974 -RRB- . 30 . Braitenberg , V. & Schuz , A. Anatomy of the Cortex : Statistics and Geometry -LRB- Springer , Berlin , 1991 -RRB- . 31 . Reid , R. C. & Alonso , J. M. Specificity of monosynaptic connections from thalamus to visual cortex . Nature 378 , 281 284 -LRB- 1995 -RRB- . Methods Animal preparation Long Evans rats -LRB- postnatal days 27 31 -RRB- and cats -LRB- postnatal days 19 40 -RRB- were prepared for in vivo two-photon imaging . Rats were anaesthetized with urethane -LRB- 1.5 g kg21 , intraperitoneally -RRB- , supplemented by ketamine -LRB- 20 mg kg21 -RRB- during surgery . In cats , anaesthesia was induced with a mixture of ketamine -LRB- 20 mg kg21 -RRB- and acepromazine -LRB- 0.2 mg kg21 , intramuscularly -RRB- , and continued with isoflurane -LRB- 1 2 % in surgery , 0.25 1 % during imaging -RRB- . Cats were paralysed with vecuronium bromide -LRB- 0.2 mg kg21 h21 , intravenously -RRB- and expired CO2 regulated at 3.5 4.5 % via mechanical ventilation . In rats and cats , a small craniotomy was made over the visual cortex , the dura reflected and the underlying cortex covered with agarose -LRB- 3 % in artificial cerebrospinal fluid , ACSF -RRB- . Dye loading and in vivo two-photon imaging We modified the protocol of ref . 18 to load cortical neurons with a calcium-sensitive dye under continuous visual guidance through the two-photon microscope . A total of 0.8 mM Oregon Green 488 BAPTA-1 AM -LRB- OGB-1 AM -RRB- was dissolved in DMSO with 20 % pluronic acid and mixed in ACSF containing 40 mM Alexa Fluor 594 -LRB- all from Molecular Probes -RRB- . A patch pipette -LRB- tip diameter of 1 mm for rats , 4 6 mm for cats -RRB- was filled with this solution and inserted into the cortex to a depth of 200 370 mm from the surface . OGB-1 AM and Alexa Fluor 594 were pressure-ejected from the pipette -LRB- 5 10 p.s.i. for 40 80 s -RRB- . On the basis of the calibrations in ref . 18 , we estimate our injection to be ,1 pl , although we did not measure this directly . Because OGB-1 AM is weakly fluorescent before it becomes internalized in cells , the amount of OGB-1 AM ejection was inferred from Alexa Fluor 594 , as visualized through the two-photon microscope . Full loading of the OGB-1 AM dye by cortical somata took 0.5 1 h in rats and 1.5 3 h in cats . After confirming loading , the pipette was withdrawn and the craniotomy sealed with a glass coverslip . Two-photon imaging of changes in calcium fluorescence in cortical cells was monitored with a custom-built microscope and a Tsunami -LRB- Spectra Physics -RRB- mode-locked Ti : sapphire laser -LRB- 810 nm -RRB- or on a Leica TCS SP2 microscope coupled with a Mira 900 -LRB- Coherent Systems -RRB- mode-locked Ti : sapphire laser -LRB- 810 nm -RRB- . All of the cat data and some of the rat data were collected on the Leica system ; the remaining rat data -LRB- including Fig. 1 -RRB- were collected on the custom-built system . Excitation light was focused by 40 immersion objectives -LRB- 0.8 numerical aperture -RRB- . The average power delivered to the brain was ,45 mW . Visual stimulation , image data acquisition and electrophysiology Drifting square-wave gratings -LRB- 100 % contrast , 1 2 Hz -RRB- were presented on a 14-inch LCD monitor at eight directions of motion in 458 steps . Spatial frequency was set at 0.025 0.05 cycles per degree in rats and 0.11 0.33 cycles per degree in cats . Each stimulus started with a blank period of uniform grey -LRB- 4 8 s -RRB- followed by the same period of visual stimulation . The eight stimuli were presented sequentially and repeated five to ten times . Great care was taken to shield the microscope objective and the photomultipliers from stray light . Our observation that even neighbouring neurons responded to different orientations makes it unlikely that there were artefacts caused by stray light from the stimulus . Images were obtained by Leica software or the software developed by ref . 34 . A square region of cortex 150 300 mm on a side was imaged at either 256 256 or 512 512 pixels at 0.81 1.63 s per frame . In all experiments , images were obtained at least from three depths separated by 10 or 20 mm . In some experiments , multiple images were obtained at 1-mm spacing for three-dimensional anatomical reconstruction . In two additional cats , we performed extracellular single-unit recordings with tungsten microelectrodes35 , after calcium imaging . Data analysis Images were analysed in Matlab -LRB- Mathworks -RRB- and ImageJ -LRB- National Institutes of Health -RRB- . When the brain was drifting slowly , more than 2 mm -LRB- but not more than several micrometres -RRB- over .10 min of scanning time , images were realigned by maximizing the correlation between frames . Cells were automatically identified -LRB- 1,992 cells from rats , 602 2005 Nature Publishing Group NATURE | VOL 433 | 10 FEBRUARY 2005 | www.nature.com/nature articles 32 . Peters , A. & Yilmaz , E. Neuronal organization in area 17 of cat visual cortex . Cereb . Cortex 3 , 49 68 -LRB- 1993 -RRB- . 33 . Mountcastle , V. B. Perceptual Neuroscience : the Cerebral Cortex -LRB- Harvard University , Cambridge , 1998 -RRB- . 34 . Pologruto , T. A. , Sabatini , B. L. & Svoboda , K. ScanImage : flexible software for operating laser scanning microscopes . Biomed . Eng . Online 2 , 13 khttp : / / www.biomedical-engineering-online.coml -LRB- 2003 -RRB- . 35 . Kara , P. & Reid , R. C. Efficacy of retinal spikes in driving cortical responses . J. Neurosci . 23 , 8547 8557 -LRB- 2003 -RRB- . 36 . Berman , N. E. , Wilkes , M. E. & Payne , B. R. Organization of orientation and direction selectivity in areas 17 and 18 of cat cerebral cortex . J. Neurophysiol . 58 , 676 699 -LRB- 1987 -RRB- . 37 . Kim , D. S. , Matsuda , Y. , Ohki , K. , Ajima , A. & Tanaka , S. Geometrical and topological relationships between multiple functional maps in cat primary visual cortex . Neuroreport 10 , 2515 2522 -LRB- 1999 -RRB- . Acknowledgements We thank E. Takahashi for involvement in the first set of experiments ; B. Sabatini , W. Regehr , R. Yuste and F. Engert for discussions and technical advice ; S. Yurgenson for technical support and programming ; A. Kerlin and J. Leong for programming ; A. Vagodny for surgical assistance ; and R. Yuste and J. Pezaris for comments on the manuscript . This work was supported by grants from the NEI and fellowships from the Uehara Foundation -LRB- K.O. -RRB- , the Goldenson Fund -LRB- S.C. -RRB- and HHMI -LRB- Y.H.C. -RRB- . Authors ' contributions K.O. started this work and played the major role in the project ; S.C. , Y.H.C. and P.K. contributed equally to its completion . Competing interests statement The authors declare that they have no competing financial interests . Correspondence and requests for materials should be addressed to R.C.R. -LRB- clay_reid@hms.harvard.edu -RRB- . Supplementary Information accompanies the paper on www.nature.com/nature . NATURE | VOL 433 | 10 FEBRUARY 2005 | www.nature.com/nature 2005 Nature Publishing Group 603

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Gene

Regulatory

Networks

and

the

Evolution

of

Animal

Body

Plans

Eric

H.

Davidson

et

al.

Science

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Gene

Regulatory

Networks

and

the

Evolution

of

Animal

Body

Plans

Eric

H.

and

Douglas

H.

Development

of

the

animal

body

plan

is

controlled

by

large

gene

regulatory

networks

-LRB-

GRNs

-RRB-

and

hence

evolution

of

body

plans

must

depend

upon

change

in

the

architecture

of

developmental

GRNs

However

these

networks

are

composed

of

diverse

components

that

evolve

at

different

rates

and

in

different

ways

Because

of

the

hierarchical

organization

of

developmental

GRNs

some

kinds

of

change

affect

terminal

properties

of

the

body

plan

such

as

occur

in

speciation

whereas

others

affect

major

aspects

of

body

plan

morphology

A

notable

feature

of

the

paleontological

record

of

animal

evolution

is

the

establishment

by

the

Early

Cambrian

of

virtually

all

phylum-level

body

plans

We

identify

a

class

of

GRN

component

the

kernels

of

the

network

which

because

of

their

developmental

role

and

their

particular

internal

structure

are

most

impervious

to

change

Conservation

of

phyletic

body

plans

may

have

been

due

to

the

retention

since

pre-Cambrian

time

of

GRN

kernels

which

underlie

development

of

major

body

parts

arge

gene

regulatory

networks

-LRB-

GRNs

-RRB-

that

determine

the

course

of

animal

development

are

now

being

decoded

experimentally

Ee.g.

-LRB-

-RRB-

These

networks

consist

largely

of

the

functional

linkages

among

regulatory

genes

that

produce

transcription

factors

and

their

target

cis-regulatory

modules

in

other

regulatory

genes

together

with

genes

that

express

spatially

important

signaling

components

They

have

a

modular

structure

consisting

of

assemblies

of

multigenic

subcircuits

of

various

forms

Each

such

subcircuit

performs

a

distinct

regulatory

function

in

the

process

of

development

-LRB-

-RRB-

GRN

structure

is

inherently

hierarchical

because

each

phase

of

development

has

beginnings

middle

stages

and

progressively

more

fine-scale

terminal

processes

so

that

network

linkages

operating

earlier

have

more

pleiotropic

effects

than

those

controlling

terminal

events

The

earlier

stages

of

formation

of

every

body

part

involve

specification

of

the

domain

of

the

developing

organism

that

will

become

that

part

followed

by

pattern

formation

which

determines

its

morphological

structure

Only

at

the

end

of

this

process

are

deployed

the

differentiation

gene

batteries

that

encode

the

detailed

functional

properties

of

the

body

part

-LRB-

-RRB-

The

structure/function

properties

of

developmental

GRNs

provide

an

approach

to

an

old

and

general

problem

in

animal

evolution

What

mechanisms

account

for

the

fact

that

has

there

GRN

the

sea

urchin

endomesodermal

GRN

in

fig

Five

properties

can

be

used

to

define

GRN

kernels

First

these

are

network

subcircuits

that

consist

of

regulatory

genes

-LRB-

i.e.

genes

encoding

transcription

factors

-RRB-

Second

they

execute

the

developmental

patterning

functions

required

to

specify

the

spatial

domain

of

an

embryo

in

which

a

given

body

part

will

form

Third

kernels

are

dedicated

to

given

developmental

functions

and

are

not

used

elsewhere

in

development

of

the

organism

-LRB-

though

individual

genes

of

the

kernel

are

likely

used

in

many

different

contexts

-RRB-

Fourth

they

have

a

particular

form

of

structure

in

that

the

products

of

multiple

regulatory

genes

of

the

kernel

are

required

for

function

of

each

of

the

participating

cis-regulatory

modules

of

the

kernel

-LRB-

recursive

wiring

-RRB-

Hence

the

fifth

property

of

the

kernel

is

that

interference

with

expression

of

any

one

kernel

gene

will

destroy

kernel

function

altogether

and

is

likely

to

produce

the

catastrophic

phenotype

of

lack

of

the

body

part

The

result

is

extraordinary

conservation

of

kernel

architecture

Two

examples

of

kernels

illustrate

many

of

these

points

-LRB-

Fig.

-RRB-

Both

display

detailed

conservation

of

complex

subcircuit

architectural

structure

across

immense

periods

of

evolutionary

time

and

both

are

surrounded

by

other

network

linkages

that

are

not

conserved

The

first

-LRB-

Fig.

-RRB-

includes

a

gene

regulatory

feedback

loop

required

for

endoderm

specification

in

echinoderms

that

has

existed

at

least

since

divergence

at

the

end

of

the

Cambrian

half

a

billion

years

ago

-LRB-

-RRB-

and

could

of

course

be

much

older

The

second

-LRB-

Fig.

-RRB-

is

a

heart-field

specification

kernel

-LRB-

-RRB-

that

must

be

even

more

ancient

as

it

is

used

in

both

Drosophila

and

vertebrate

development

These

subcircuits

operate

to

specify

the

cellular

populations

where

respectively

the

gut

and

the

heart

will

form

and

to

set

up

the

regulatory

states

on

which

subsequent

developmental

processes

will

depend

In

the

echinoderm

endoderm

network

five

of

the

six

genes

in

the

kernel

-LRB-

all

except

delta

-RRB-

encode

DNA-recognizing

transcription

factors

that

is

they

are

regulatory

genes

and

this

is

true

of

all

the

genes

in

the

conserved

circuitry

in

the

heart

network

In

both

kernels

the

linkages

are

highly

recursive

For

example

in

the

endoderm

kernel

the

cis-regulatory

module

of

the

otx

gene

receives

input

from

three

of

the

five

genes

the

foxa

gene

from

three

of

the

five

and

the

gatae

foxa

and

bra

genes

from

two

of

the

same

five

genes

similarly

in

the

vertebrate

heart

network

the

tbx

and

genes

all

receive

inputs

from

multiple

other

genes

of

the

kernel

as

do

the

tin

doc

mid

pnr

and

genes

of

the

Drosophila

network

It

is

also

the

case

that

loss

of

expression

of

any

of

these

genes

in

either

kernel

has

a

catastrophic

effect

on

development

of

the

respective

body

parts

-LRB-

-RRB-

There

are

a

number

of

additional

L

has

been

so

little

change

in

phylum

and

superphylum-level

body

plans

since

the

Early

Cambrian

Ee.g.

the

Chengjiang

fauna

-LRB-

-RRB-

-LRB-

Fig.

-RRB-

though

on

the

other

hand

great

changes

have

subsequently

occurred

within

phyla

and

classes

-LRB-

e.g.

the

advent

of

tetrapod

vertebrates

insects

dinosaurs

modern

forms

of

echinoids

and

cephalopods

-RRB-

Furthermore

continuous

modification

characterizes

the

process

of

speciation

Classic

evolutionary

theory

based

on

selection

of

small

incremental

changes

has

sought

explanations

by

extrapolation

from

observed

patterns

of

adaptation

Macroevolutionary

theories

have

largely

invoked

multilevel

selection

among

species

and

among

clades

But

neither

class

of

explanation

provides

an

explanation

of

evolution

in

terms

of

mechanistic

changes

in

the

genetic

regulatory

program

for

development

of

the

body

plan

where

it

must

lie

Functional

Properties

of

Diverse

GRN

Components

Change

in

the

structure

of

the

diverse

kinds

of

subcircuits

of

which

GRNs

are

constructed

will

have

different

consequences

for

the

outcome

of

the

developmental

process

and

therefore

for

evolution

as

well

Here

we

consider

the

following

classes

of

GRN

component

-LRB-

i

-RRB-

evolutionarily

inflexible

subcircuits

that

perform

essential

upstream

functions

in

building

given

body

parts

which

we

term

the

kernels

of

the

GRN

-LRB-

ii

-RRB-

certain

small

subcircuits

the

plug-ins

of

the

GRN

that

have

been

repeatedly

coopted

to

diverse

developmental

purposes

-LRB-

iii

-RRB-

switches

that

allow

or

disallow

developmental

subcircuits

to

function

in

a

given

context

and

so

act

as

input/output

-LRB-

I/O

-RRB-

devices

within

the

GRN

and

-LRB-

iv

-RRB-

differentiation

gene

batteries

These

parts

are

illustrated

in

a

real

developmental

VOL

SCIENCE

Division

of

Biology

California

Institute

of

Technology

Pasadena

CA

USA

of

Paleobiology

National

Museum

of

Natural

History

Post

Office

Box

Washington

DC

and

Santa

Fe

Institute

Hyde

Park

Road

Santa

Fe

NM

USA

To

whom

correspondence

should

be

addressed

E-mail

davidson@caltech.edu

FEBRUARY

Downloaded

from

on

May

REVIEW

Fig.

Examples

of

Cambrian

body

plans

from

the

Early

Cambrian

-LRB-

million

years

ago

-RRB-

Chengjiang

Fauna

of

Yunnan

Province

China

-LRB-

D

to

I

-RRB-

and

the

Middle

Cambrian

Burgess

Shale

Fauna

of

British

Columbia

Canada

-LRB-

A

to

C

J

-RRB-

These

fossils

are

the

remains

of

animals

all

of

which

have

body

plans

that

can

immediately

be

related

to

those

of

modern

phyla

as

indicated

For

instance

the

bilateral

anterior-posterior

organization

and

position

of

the

appendages

in

the

arthropod

examples

resemble

those

of

the

modern

counterparts

in

addition

the

chordate

has

a

segmented

dorsal

muscular

column

and

a

notochord

as

do

modern

chordates

-LRB-

A

-RRB-

Onycophoran

Aysheaia

pedunculata

-LRB-

B

-RRB-

arthropod

Waptia

fieldensis

-LRB-

C

-RRB-

arthropod

Marrella

splendens

-LRB-

D

-RRB-

possible

ascidian

Phlogites

-LRB-

E

-RRB-

priapulid

Maotianshania

cylindrica

-LRB-

F

-RRB-

pan-arthropod

Opabinia

regalis

-LRB-

G

-RRB-

arthropod

Leanchoilia

illecebrosa

-LRB-

H

-RRB-

arthropod

Jianfengia

multisegmentalis

-LRB-

I

-RRB-

arthropod

Fuxianjuia

protensa

-LRB-

J

-RRB-

chordate

Haikouella

lanceolata

-LSB-

-LRB-

A

-RRB-

to

-LRB-

C

-RRB-

-RSB-

and

-LRB-

F

-RRB-

are

from

D.

H.

Erwin

Smithsonian

Institution

-LRB-

D

-RRB-

-LRB-

E

-RRB-

and

-LSB-

-LRB-

G

-RRB-

to

-LRB-

J

-RRB-

-RSB-

are

courtesy

of

J.-Y

Chen

Nanjing

Institute

of

Geology

and

Palaeontology

China

-LRB-

-RRB-

examples

for

which

there

is

persuasive

evidence

for

the

existence

of

GRN

kernels

awaiting

discovery

of

the

direct

genomic

regulatory

code

Prospective

examples

include

kernels

common

to

all

members

of

a

given

phylum

or

superphylum

required

for

the

following

anterior

to

posterior

-LRB-

-RRB-

and

midline

to

lateral

-LRB-

-RRB-

specification

of

the

nervous

system

-LRB-

in

deuterostomes

and

possibly

across

Bilateria

-RRB-

eyefield

specification

-LSB-

in

arthropods

-LRB-

-RRB-

-RSB-

gut

regionalization

-LSB-

in

chordates

-LRB-

-RRB-

-RSB-

development

of

immune

systems

-LSB-

across

Bilateria

-LRB-

-RRB-

-RSB-

and

regionalization

of

the

hindbrain

and

specification

of

neural

crest

-LSB-

in

chordates

-LRB-

-RRB-

-RSB-

Plug-ins

also

consist

of

structurally

conserved

GRN

subcircuits

but

as

they

are

used

for

many

diverse

developmental

functions

within

and

among

species

these

network

subcircuits

are

not

dedicated

to

formation

of

given

body

parts

Instead

they

are

inserted

in

many

different

networks

where

they

provide

inputs

into

a

great

variety

of

regulatory

apparatus

The

best

examples

are

signal

transduction

systems

of

which

a

small

set

each

affecting

a

confined

repertoire

of

transcription

factors

are

used

repeatedly

often

acting

as

dominant

spatial

repressors

in

the

absence

of

ligand

and

as

facilitators

of

spatially

confined

expression

in

its

presence

-LRB-

-RRB-

In

Bilateria

Wnt

-LRB-

-RRB-

transforming

growth

SCIENCE

VOL

factor

b

-LRB-

TGF-b

-RRB-

-LRB-

-RRB-

fibroblast

growth

factor

-LRB-

-RRB-

Hedgehog

-LRB-

-RRB-

Notch

-LRB-

-RRB-

and

epidermal

growth

factor

-LRB-

-RRB-

signaling

systems

are

used

for

myriad

purposes

during

development

Their

deployment

is

very

flexible

and

even

in

homologous

processes

in

related

animals

these

plug-ins

may

be

used

differently

-LRB-

-RRB-

Consider

for

example

the

several

dozen

different

TGF-b

genes

in

amniote

vertebrates

expressed

differentially

in

the

-LRB-

species-specific

-RRB-

terminal

phases

of

development

-LRB-

-RRB-

It

follows

that

their

connections

into

the

network

are

evolutionarily

very

labile

Differentiation

gene

batteries

are

defined

as

groups

of

protein-coding

genes

under

common

regulatory

control

the

products

of

which

exe

FEBRUARY

Downloaded

from

on

May

REVIEW

Fig.

Examples

of

putative

GRN

kernels

Networks

were

constructed

and

portrayed

using

BioTapestry

software

-LRB-

-RRB-

-LRB-

A

-RRB-

Endomesoderm

specification

kernel

common

to

sea

urchin

and

starfish

the

last

common

ancestor

of

which

lived

about

half

a

billion

years

ago

The

relevant

area

of

the

sea

urchin

network

is

shown

at

the

top

-LSB-

-LRB-

-RRB-

for

currently

updated

version

details

and

supporting

data

see

-LRB-

-RRB-

-RSB-

the

corresponding

starfish

network

-LRB-

-RRB-

is

shown

in

the

middle

and

the

network

architecture

which

has

been

exactly

conserved

since

divergence

i.e.

the

kernel

is

shown

at

the

bottom

Horizontal

lines

denote

cis-regulatory

modules

responsible

for

the

pregastrular

phase

of

expression

considered

in

endoderm

-LRB-

yellow

-RRB-

mesoderm

-LRB-

gray

-RRB-

or

both

endoderm

and

mesoderm

-LRB-

striped

gray

and

yellow

-RRB-

The

inputs

into

the

cis-regulatory

modules

are

denoted

by

vertical

arrows

and

bars

The

gray

box

surrounding

the

foxa

input

indicates

that

this

repression

occurs

exclusively

in

mesoderm

-LRB-

B

-RRB-

Possible

heart

specification

kernels

assembled

from

many

literature

sources

-LRB-

-RRB-

Dashed

lines

show

possible

interactions

Some

aspects

of

the

GRN

that

may

underlie

heart

specification

in

Drosophila

are

shown

at

the

top

the

approximately

corresponding

vertebrate

relationships

are

shown

in

the

middle

and

shared

linkages

are

shown

at

the

bottom

Absence

of

a

linkage

simply

means

that

this

linkage

is

not

known

to

exist

not

that

it

is

known

not

to

exist

Many

regulatory

genes

participate

in

vertebrate

heart

formation

for

which

orthologous

Drosophila

functions

have

not

been

discovered

and

the

hearts

themselves

are

of

very

different

structure

However

as

pointed

out

by

many

authors

-LSB-

see

-LRB-

-RRB-

for

reviews

of

earlier

references

-RSB-

a

core

set

of

regulatory

genes

are

used

in

common

and

are

now

known

to

be

linked

in

a

similar

way

in

a

conserved

subcircuit

of

the

gene

network

architecture

as

shown

The

gray

boxes

represent

in

each

case

different

ways

that

the

same

two

nodes

of

the

network

are

linked

in

Drosophila

and

vertebrates

A

PMC/micomere

GRN

Sea

urchin

Tbr

Otx

Delta

Bra

Foxa

Gatae

Starfish

Tbr

Otx

Delta

Bra

Foxa

Gatae

Common

Otx

Delta

Bra

Foxa

Gatae

cute

cell

type

specific

functions

Such

functions

contrast

with

those

of

kernels

and

plug-ins

the

significance

of

which

is

entirely

regulatory

Differentiation

gene

batteries

build

muscle

cells

and

make

skeletal

biominerals

skin

synaptic

transmission

systems

etc.

The

structure

of

differentiation

gene

batteries

has

been

discussed

at

the

network

level

elsewhere

-LRB-

-RRB-

as

an

example

see

the

skeletogenic

and

pigment

cell

differentiation

gene

batteries

in

fig

Differentiation

gene

batteries

display

inherent

evolutionary

lability

and

undergo

continuous

renovation

Numerous

examples

can

be

found

in

studies

of

speciation

-LSB-

e.g.

-LRB-

-RRB-

-RSB-

Internal

changes

occur

in

differentiation

gene

batteries

in

various

ways

Any

of

the

tens

or

hundreds

of

structural

genes

constituting

their

working

components

may

alter

functionally

by

incremental

changes

in

their

protein-coding

sequences

new

genes

may

be

added

to

them

if

they

acquire

cis-regulatory

modules

targeting

members

of

the

given

small

set

of

transcriptional

regulators

to

which

that

battery

responds

or

similarly

they

may

lose

genes

But

differentiation

gene

batteries

reside

at

the

periphery

of

developmental

GRNs

-LRB-

-RRB-

because

their

outputs

terminate

the

network

They

are

expressed

in

the

final

stages

of

given

developmental

processes

They

do

not

regulate

other

genes

and

they

do

not

control

the

progressive

formation

of

spatial

patterns

of

gene

expression

that

underlies

the

building

of

the

body

plan

in

short

they

do

not

make

body

parts

They

receive

rather

than

generate

developmental

instructions

Cis-regulatory

linkages

that

may

be

considered

as

I/O

switches

regulating

other

network

subcircuits

appear

to

be

responsible

for

many

kinds

of

evolutionary

change

in

developmental

process

For

example

a

common

form

of

variation

which

must

be

trivial

at

the

regulatory

VOL

SCIENCE

level

because

it

occurs

even

within

genera

and

species

is

in

size

of

homologous

body

parts

We

can

easily

imagine

that

this

parameter

depends

only

on

the

input

linkage

between

a

regulatory

gene

of

the

network

controlling

the

patterning

of

the

body

part

and

a

cell

cycle

cassette

indeed

such

linkages

are

explicitly

known

for

instance

in

the

gene

network

regulating

pituitary

development

where

the

target

is

the

cell

cycle

control

genes

-LRB-

-RRB-

Here

the

regulatory

gene

specifically

activates

the

cell

cycle

control

genes

cyclin

cyclin

and

c-myc

Many

hox

gene

functions

are

also

in

this

class

They

act

to

permit

or

prohibit

patterning

subcircuits

from

acting

in

given

regions

of

an

animal

Examples

include

the

direct

repressive

effects

of

the

Ubx

gene

product

on

expression

of

wing-patterning

genes

in

the

Drosophila

haltere

-LRB-

-RRB-

the

role

of

group

and

hox

genes

in

specification

of

vertebral

morphol

FEBRUARY

Downloaded

from

on

May

REVIEW

B

Dpp

Mid

-LRB-

-RRB-

Mad

Med

Tin

Wg

Hand

Drosophila

Pnr

Toll

Sur

tubulin

Contractile

proteins

Srf

and

myocardin

Bmp

Smad

Contractile

proteins

Ehand

Dhand

Anf

Dpp/BMP

Feedback

from

to

Dros

Tin

Vert

Mid

Pnr

Common

Mad

Med/SMAD

T-box

genes

establish

mutually

exclusive

domains

Dros

Mid

Tin

Vert

Pnr

linkage

to

Dros

Tin

Vert

Hand/Ehand

Dhand

ogy

in

vertebrates

-LRB-

-RRB-

and

in

beetles

the

function

of

Ubx

to

allow

the

wing-pattern

network

to

operate

in

the

forewings

preventing

expression

of

a

different

program

expressed

normally

in

the

hindwing

-LRB-

-RRB-

Predicted

Evolutionary

Consequences

of

Changes

in

GRN

Architecture

Viewed

in

this

way

it

is

apparent

that

the

effects

of

changes

in

different

component

classes

will

be

qualitatively

distinct

causing

disparate

kinds

of

effect

on

body

plan

and

on

adaptive

organismic

functionality

Furthermore

there

emerges

a

relation

between

the

network-component

class

in

which

changes

might

occur

and

the

taxonomic

level

of

morphogenetic

effects

-LRB-

Fig.

-RRB-

The

most

frequent

and

least

constrained

kinds

of

change

will

occur

in

the

peripheral

regions

of

the

GRN

i.e.

within

differentiation

gene

batteries

themselves

and

the

apparatus

that

SCIENCE

VOL

Reinterpreting

the

Evolutionary

Record

We

propose

that

architectural

changes

in

animal

body

plans

have

been

produced

over

the

past

million

years

by

changes

in

GRNs

of

at

least

three

general

classes

with

extremely

different

developmental

consequences

and

rates

of

occurrence

This

challenges

the

generally

time

FEBRUARY

Downloaded

from

on

May

Vertebrate

controls

their

deployment

This

is

for

the

simple

reason

that

there

are

no

downstream

consequences

in

cis-regulatory

wiring

elsewhere

in

the

network

if

peripheral

input

linkages

change

as

will

commonly

result

from

change

in

more

internal

locations

Such

peripheral

small

changes

are

just

what

is

observed

in

the

countless

processes

of

speciation

They

account

for

many

adaptive

properties

of

the

organism

for

instance

different

properties

of

the

integument

the

repertoire

of

digestive

enzymes

the

positioning

of

peripheral

sensory

elements

etc.

At

the

other

extreme

-LRB-

Fig.

-RRB-

are

the

kernels

of

the

network

They

operate

the

peculiarly

crucial

step

of

specifying

the

domain

for

each

body

part

in

the

spatial

coordinate

system

of

the

postgastrular

embryo

We

think

that

change

in

them

is

prohibited

on

pain

of

developmental

catastrophe

both

because

of

their

internal

recursive

wiring

and

because

of

their

roles

high

in

the

developmental

network

hierarchy

We

predict

that

when

sufficient

comparative

network

data

are

available

there

will

be

found

conserved

network

kernels

similar

in

complexity

and

character

to

those

of

Fig.

which

program

the

initial

stages

of

development

of

every

phylum-specific

body

part

and

perhaps

of

superphylum

and

pan-bilaterian

body

parts

as

well

It

would

follow

that

these

kernels

must

have

been

assembled

during

the

initial

diversification

of

the

Bilateria

and

have

retained

their

internal

character

since

Critically

these

kernels

would

have

formed

through

the

same

processes

of

evolution

as

affect

the

other

components

but

once

formed

and

operating

to

specify

particular

body

parts

they

would

have

become

refractory

to

subsequent

change

Molecular

phylogeny

places

this

evolutionary

stage

in

the

late

Neoproterozoic

when

Bilateria

begin

to

appear

in

the

fossil

record

-LRB-

-RRB-

between

the

end

of

the

Marinoan

glaciation

at

about

million

years

ago

and

the

beginning

of

the

Cambrian

Therefore

the

mechanistic

explanation

for

the

surprising

fact

that

essentially

no

major

new

phylum-level

body

parts

have

evolved

since

the

Cambrian

may

lie

in

the

internal

structural

and

functional

properties

of

GRN

kernels

Once

they

were

assembled

they

could

not

be

disassembled

or

basically

rewired

only

built

on

to

Between

the

periphery

of

developmental

GRNs

and

their

kernels

lies

the

bulk

of

the

network

architecture

Here

we

see

skeins

of

special

cross-regulatory

circuitry

plug-ins

and

I/O

connections

and

here

is

where

have

occurred

the

changes

in

network

architecture

that

account

for

the

evolutionary

novelties

attested

in

the

fossil

record

of

animals

REVIEW

the

underlying

GRNs

Following

the

early

assembly

of

kernels

the

varying

effects

of

plug-in

redeployment

changes

in

I/O

linkages

and

Phylum

and

superphylum

piecemeal

alterations

in

differentiaKernels

characters

tion

gene

batteries

provide

a

basis

for

mechanistic

analysis

of

subphyletic

animal

evolution

To

the

exElaborations

in

tent

that

kernel

formation

underlies

morphological

pattern

critical

morphological

innovations

some

kernels

must

indirectly

be

responsible

for

major

events

in

Alterations

in

Class

order

family

Neoproterozoic

niche

construction

deployment

Motility

predation

digestion

and

characters

of

plug-ins

and

other

canonical

features

of

the

I/O

switches

Bilateria

followed

from

the

evoluSize

of

body

parts

tionary

appearance

of

the

genetic

programs

for

the

respective

body

parts

These

innovations

became

an

engine

of

change

that

irreverFunctional

capabilities

Alterations

in

sibly

altered

the

Earth

's

environof

body

parts

differentiation

gene

ment

and

thus

the

probability

of

batteries

and

their

success

of

subsequent

evolutiondeployment

ary

changes

We

believe

that

exSpeciation

perimental

examination

of

the

Fig.

Diverse

kinds

of

change

in

GRNs

and

their

diverse

evo

conserved

kernels

of

extant

devellutionary

consequences

The

left

column

shows

changes

in

network

opmental

GRNs

will

illuminate

components

the

right

column

shows

evolutionary

consequences

the

widely

discussed

but

poorly

expected

which

differ

in

their

taxonomic

level

-LRB-

red

-RRB-

understood

problem

of

the

origination

of

animal

body

plans

in

the

homogeneous

view

of

most

evolutionary

biolo

late

Neoproterozoic

and

Cambrian

and

their

gists

Current

microevolutionary

thinking

assumes

remarkable

subsequent

stability

that

observed

types

of

genetic

change

-LRB-

from

sinReferences

and

Notes

gle

base

substitutions

to

gene

duplications

-RRB-

are

M.

Levine

E.

H.

Davidson

Proc

Natl.

Acad

Sci

U.S.A.

sufficient

to

explain

all

evolutionary

events

past

-LRB-

-RRB-

and

present

Such

changes

are

considered

as

A.

Ochoa-Espinosa

et

al.

Proc

Natl.

Acad

Sci

U.S.A.

having

occurred

during

evolution

in

a

-LRB-

-RRB-

T.

Koide

T.

Hayata

K.

Cho

Proc

Natl.

Acad

Sci

U.S.A.

rally

homogeneous

way

Microevolution

does

-LRB-

-RRB-

intersect

with

mechanisms

of

GRN

change

H.

Singh

K.

Medina

Proc

Natl.

Acad

Sci

U.S.A.

at

the

level

of

change

within

cis-regulatory

-LRB-

-RRB-

ules

But

attempting

to

explain

an

aspect

of

T.

Inoue

M.

Wang

T.

Ririe

J.

Fernandes

P.

Sternberg

Proc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

animal

evolution

that

depends

on

one

kind

of

M.

F.

Maduro

J.

H.

Rothman

Dev

Biol

-LRB-

-RRB-

network

alteration

by

adducing

evidence

from

R.

M.

Cripps

E.

N.

Olson

Dev

Biol

-LRB-

-RRB-

an

aspect

that

depends

on

another

can

be

I.

Reim

J.

P.

Mohler

M.

Frasch

Mech

Dev

damentally

misleading

Comparative

molecular

-LRB-

-RRB-

dissection

of

GRNs

should

allow

identification

P.

Oliveri

E.

H.

Davidson

Curr

Opin

Genet

Dev

-LRB-

-RRB-

of

the

evolutionary

point

of

origin

of

each

E.

H.

Davidson

Gene

Regulatory

Systems

Development

circuit

and

linkage

in

the

network

and

hence

and

Evolution

-LRB-

Academic

Press

San

Diego

-RRB-

each

morphological

character

of

the

body

plan

J.

W.

Valentine

On

the

Origin

of

Phyla

-LRB-

Univ.

of

Chicago

If

the

early

assembly

of

kernels

underlies

the

Press

Chicago

-RRB-

D.

H.

Erwin

J.

W.

Valentine

J.

J.

Sepkoski

Jr.

Evolution

phyletic

conservation

of

body

parts

since

the

Int

J.

Org

Evolution

-LRB-

-RRB-

Cambrian

then

the

position

in

GRNs

of

J.-Y

Chen

The

Dawn

of

Animal

World

-LRB-

Jiangsu

Science

quent

adaptational

change

is

forced

to

lower

and

Technology

Publishing

House

Nanjing

-RRB-

levels

in

the

network

hierarchy

The

result

is

V.

F.

Hinman

A.

Nguyen

R.

A.

Cameron

E.

H.

Davidson

what

has

been

termed

developmental

or

phyloProc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

For

sources

of

each

linkage

shown

see

-LRB-

-RRB-

and

supporting

genetic

constraints

-LRB-

-RRB-

The

different

levels

online

material

of

change

that

have

occurred

in

evolution

are

E.

H.

Davidson

et

al.

Science

-LRB-

-RRB-

imperfectly

reflected

at

different

levels

of

C.

J.

Lowe

et

al.

Cell

-LRB-

-RRB-

nean

classification

and

we

think

that

these

R.

Lichtneckert

H.

Reichert

Heredity

-LRB-

-RRB-

homogeneous

events

have

been

caused

by

F.

Hirth

L.

Kammermeirt

E.

Frei

U.

Walldorf

M.

Reichert

Development

-LRB-

-RRB-

architectural

alterations

in

different

locations

in

Network

functions

affected

Evolutionary

consequences

D.

Arendt

K.

Nubler-Jung

Development

-LRB-

-RRB-

R.

A.

Cornell

T.

Von

Ohlen

Curr

Opin

Neurobiol

-LRB-

-RRB-

C.

Punzo

M.

Seimiya

S.

Flister

W.

J.

Gehring

S.

Plaza

Development

-LRB-

-RRB-

S.

J.

Silver

I.

Rebay

Development

-LRB-

-RRB-

B.

A.

Afouda

A.

Cia-Uitz

R.

Patient

Development

-LRB-

-RRB-

R.

A.

Shivdasani

Dev

Biol

-LRB-

-RRB-

J.

A.

Hoffmann

F.

C.

Kafatos

C.

A.

Janeway

Jr.

R.

A.

B.

Ezekowitz

Science

-LRB-

-RRB-

E.

V.

Rothenberg

E.

H.

Davidson

in

Innate

Immunity

R.

A.

B.

Ezekowitz

J.

A.

Hoffman

Eds

-LRB-

Humana

Totowa

NJ

-RRB-

pp.

H.

Wada

P.

W.

H.

Holland

S.

Sato

H.

Yamamoto

N.

Satoh

Dev

Biol

-LRB-

-RRB-

D.

Meulemans

M.

Bronner-Fraser

Dev

Cell

-LRB-

-RRB-

S.

Barolo

J.

W.

Posakony

Genes

Dev

-LRB-

-RRB-

K.

M.

Cadigan

R.

Nusse

Genes

Dev

-LRB-

-RRB-

D.

M.

Kingsley

Genes

Dev

-LRB-

-RRB-

G.

Szebenyi

J.

F.

Fallon

Int

Rev.

Cytol

-LRB-

-RRB-

A.

P.

McMahon

P.

W.

Ingham

C.

J.

Tabin

Curr

Top

Dev

Biol

-LRB-

-RRB-

S.

Artavanis-Tsakonis

K.

Matsuno

M.

E.

Fortini

Science

-LRB-

-RRB-

B.-Z

Shilo

Exp

Cell

Res

-LRB-

-RRB-

M.

Tokuoka

K.

S.

Imai

Y.

Satou

N.

Satoh

Dev

Biol

-LRB-

-RRB-

B.

L.

M.

Hogan

Genes

Dev

-LRB-

-RRB-

J.

C.

Avise

Phylogeography

The

History

and

Formation

of

Species

-LRB-

Harvard

Univ.

Press

Cambridge

MA

-RRB-

H.

Bolouri

E.

H.

Davidson

Dev

Biol

-LRB-

-RRB-

X.

Zhu

M.

G.

Rosenfeld

Curr

Opin

Genet

Dev

-LRB-

-RRB-

S.

D.

Weatherbee

G.

Halder

J.

Kim

A.

Hudson

S.

Carroll

Genes

Dev

-LRB-

-RRB-

B.

M.

Hersch

S.

B.

Carroll

Development

-LRB-

-RRB-

R.

Galant

C.

M.

Walsh

S.

B.

Carroll

Development

-LRB-

-RRB-

D.

M.

Wellik

M.

R.

Capecchi

Science

-LRB-

-RRB-

Y.

Tomoyasu

S.

R.

Wheller

R.

E.

Denell

Nature

-LRB-

-RRB-

K.

J.

Peterson

et

al.

Proc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

S.

Aris-Brosou

Z.

Yang

Syst

Biol

-LRB-

-RRB-

E.

J.

Douzery

E.

A.

Snell

E.

Bapteste

F.

Delsuc

H.

Philippe

Proc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

D.

H.

Erwin

E.

H.

Davidson

Development

-LRB-

-RRB-

D.

Condon

et

al.

Science

-LRB-

-RRB-

J.

Maynard

Smith

et

al.

Q.

Rev.

Biol

-LRB-

-RRB-

K.

Schwenk

Zoology

-LRB-

-RRB-

P.

Alberch

in

Evolution

and

Development

J.

T.

Bonner

Ed

-LRB-

Springer-Verlag

Berlin

-RRB-

pp.

W.

J.

R.

Longabaugh

E.

H.

Davidson

H.

Bolouri

Dev

Biol

-LRB-

-RRB-

I.

Reim

M.

Frasch

Development

-LRB-

-RRB-

E.H.D.

acknowledges

support

from

NASA

grant

U.S.

Department

of

Energy

grant

and

NIH

grant

D.H.E.

acknowledges

the

Packard

Foundation

and

the

Santa

Fe

Institute

We

thank

A.

H.

Knoll

D.

Krakauer

E.

V.

Rothernberg

M.

Levine

and

four

anonymous

reviewers

for

useful

comments

on

earlier

drafts

of

the

manuscript

Supporting

Online

Material

SOM

Text

Fig

References

and

Notes

science

FEBRUARY

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B O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O B O O B O O O O O O O O O B O O O B B O O O O B O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O B B O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O B O O B O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O B B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O B B O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O B O O O O B O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

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