Distinct subnetworks of the thalamic reticular nucleus

Abstract

The thalamic reticular nucleus (TRN), the major source of thalamic inhibition, regulates thalamocortical interactions that are critical for sensory processing, attention and cognition1,2,3,4,5. TRN dysfunction has been linked to sensory abnormality, attention deficit and sleep disturbance across multiple neurodevelopmental disorders6,7,8,9. However, little is known about the organizational principles that underlie its divergent functions. Here we performed an integrative study linking single-cell molecular and electrophysiological features of the mouse TRN to connectivity and systems-level function. We found that cellular heterogeneity in the TRN is characterized by a transcriptomic gradient of two negatively correlated gene-expression profiles, each containing hundreds of genes. Neurons in the extremes of this transcriptomic gradient express mutually exclusive markers, exhibit core or shell-like anatomical structure and have distinct electrophysiological properties. The two TRN subpopulations make differential connections with the functionally distinct first-order and higher-order thalamic nuclei to form molecularly defined TRN–thalamus subnetworks. Selective perturbation of the two subnetworks in vivo revealed their differential role in regulating sleep. In sum, our study provides a comprehensive atlas of TRN neurons at single-cell resolution and links molecularly defined subnetworks to the functional organization of thalamocortical circuits.

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Fig. 1: snRNA-seq reveals transcriptomic gradient of TRN neurons.
Fig. 2: Ecel1+ and Spp1+ neurons show distinct spatial distribution across the TRN.
Fig. 3: Topographical map of TRN-thalamus projections.
Fig. 4: Spp1+ and Ecel1+ TRN subpopulations show distinct electrophysiological signatures.
Fig. 5: Selective perturbation of the firing properties of Spp1+ or Ecel1+ neurons in vivo reveals their differential participation in thalamocortical rhythms.

Data availability

Sequencing data for this study is available through the Gene Expression Omnibus GSE145273. All additional data, and plasmids are available from the authors upon reasonable request.

Code availability

Code for the snRNA-seq analyses and the associated t-SNE mappings are available at https://github.com/yinqingl. Any additional code used is available from the authors upon reasonable request.

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Acknowledgements

We thank all members of the G.F., Z.F. and J.Z.L. laboratories for discussions and support; R. Kast for helpful comments on this manuscript; M. Fleishman and M. Palomero-Rivero for technical support; the Broad Flow Cytometry Facility for nucleus sorting; and F. Zhang for CRISPR–Cas9 constructs. The work in the laboratory of G.F. was supported by the Simons Center for the Social Brain at MIT, the Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard, Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, James and Patricia Poitras Center for Psychiatric Disorders Research at MIT, the McGovern Institute for Brain Research at MIT and NIH/NIMH grant R01NS098505, R01NS113245. The work in the laboratory of Z.F. was supported by the Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard. The work in the laboratory of J.Z.L. was supported by the Stanley Center for Psychiatric Research and the Klarman Cell Observatory at the Broad Institute of MIT and Harvard. The work in the laboratory of M.M.H. was supported by the Simons Center for the Social Brain at MIT, the Stanley Center for Psychiatric Research at the Broad Institute, the McGovern Institute for Brain Research at MIT, the Pew Foundation, the Human Frontiers Science Program and NIH grants R01NS098505, R01MH107680. Y.L. was supported by the McGovern–IDG Institute for Brain Research at Tsinghua University.

Author information

Affiliations

Authors

Contributions

Y.L., V.G.L.-H., J.Z.L., Z.F. and G.F. provided overall design and oversight of the project. snRNA-seq experiments were designed, performed, analysed or supervised by Y.L., V.G.L.-H., X.A., C.C.H., S.K.S. and T.L. A modified protocol for Smart-seq2 library construction was contributed by M.K. Viral injections and collection of non-TRN Pvalb+ neuronal nuclei was performed by R.S. and V.G.L.-H. RNA FISH experiments were designed, performed, analysed or supervised by Y.L., K.L., A.Y.Y., T.R.B., A.A., M.G. and J.P. EEG recording and analyses were designed and performed by S.C., R.D.W., V.G.L.-H., B.G., T.N., X.S., D.B., E.H., G.P. and M.M.H. Electrophysiology, patch–seq and morphology experiments were designed, performed, analysed or supervised by V.G.L.-H., M.A.A.-G., Y.L. and Z.F. Retrograde tracing experiments were performed by V.G.L.-H., Y.L., A.Y.Y., A.A., K.L. and A.K. CRISPR-knockout experiments were designed and performed by Y.L., V.G.L.-H., X.A., T.A., A.Y.Y., A.A. and D.M. The manuscript was written by Y.L., V.G.L.-H., Z.F., G.F., J.Z.L. and M.M.H. with inputs from all authors.

Corresponding authors

Correspondence to Joshua Z. Levin or Zhanyan Fu or Guoping Feng.

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The authors declare no competing interests.

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Peer review information Nature thanks Ed S. Lein, Karel Svoboda and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Expression patterns of Gad2 and Pvalb across TRN.

a, Schematic of positions of coronal sections shown along the anterior to posterior axis (indicated by numbers). bd, RNA-FISH co-staining of Gad2 and Pvalb in anterior (b), medial (c), and posterior (d) coronal sections. For each position: Left: overview of the RNA-FISH co-staining in TRN; Right: Zoom-in view of the boxed area in the left panel. For bd, repeated with n = 2. e, Representative FACS plot showing gating strategy used in sorting single nuclei for RNA sequencing. Repeated with n = 53 plate-based sorting.

Extended Data Fig. 2 Identification of Gad2+ cell types.

a, t-SNE embedding of 1,687 single nuclei as in Fig. 1a. Single nuclei are coloured by dissection sources as indicated by the colour bar on the right. Different batches of dissections from the external part of globus pallidus (GPE) are coloured differently. n = 1,687 nuclei. b, t-SNE embedding of nuclei showing expression levels (pseudo-colour) of marker genes for each cluster. The three small clusters exhibiting markedly less Pvalb expression, but enriched with a combination of markers including Gabra1, Fxyd6, Tac1. n = 868 nuclei. c, ISH image in sagittal view of selected markers shown in b. Images obtained from Allen Brain Atlas (https://portal.brain-map.org/). Dashed lines indicate boundaries of TRN and the neighbouring GABAergic nuclei. GP: globus pallidus; ZI: zona incerta; BNST: bed nucleus of the stria terminalis.

Extended Data Fig. 3 Binarized expression pattern of Spp1 and Ecel1 represents transcriptomic gradient.

a, Expression levels of Spp1 and Ecel1 (top) and log(Spp1/Ecel1) (bottom) in individual cells along the transcriptomic gradient, showing binary pattern of Spp1 and Ecel1 correlated with the gradient score. b, Number of genes detected for the major cell types and TRN subpopulations, showing that the Spp1+Ecel1+ (DP) and Spp1Ecel1 (DN) are of quality comparable to other cell populations. nASC = 124, nGlut = 226, nGABA = 868, nODC = 388, nGad1+Cck+ = 9, nOPC = 23, nMCG = 28, nEbf2+ = 21 nuclei. Between Spp1+ and DP, P = 0.1787; DN and Ecel1+, P = 0.2897, two-sided ranksum test. n.s.: not significant. No adjustment for multiple testing was applicable. Box plots shows 25th, 50th, 75th percentiles, and the whiskers extend to the most extreme data points, ‘+’ are taken as outliers. c, Schematics of naive Bayes classifiers to assign Spp1+, Ecel1+, DP and DN neurons into segments of the transcriptomic gradient. d, Classification accuracy of the naive Bayes classifiers. Shown are the probability of assigning Spp1+ to ‘Spp1’ segment, DP and DN neurons to the intermediate segment, and Ecel1+ to ‘Ecel1’ segment, respectively. n = 671 nuclei total, nSpp1+ = 264, nDP+DN = 195, nEcel1+ = 212 neurons. e, Schematics for normalization of medial–lateral position of individual neurons in FISH images. Blue line: TRN boundary; Red dots: Pvalb+Spp1+ neurons; Green dots: Pvalb+Ecel1+ neurons; Yellow dots: DP neurons; DN are not shown in the schematics. f, Scatter plots showing log(Spp1/Ecel1) in individual Pvalb+ neurons at normalized medial-lateral position in selected tFISH images along anterior to posterior TRN, corresponding to Fig. 2c. m-l: medial–lateral position; Blue dots: individual cells; Solid red line: smooth fitting of blue data points, showing inverted-‘U’ shape; Dashed blue line: mean of blue data points, indicating the difference in the FISH background of Spp1 and Ecel1 channel in different images.

Extended Data Fig. 4 Injection sites in distinct thalamic relay nuclei and corresponding cortical projections.

a, The positions of retrogradely labelled neurons traced from different thalamic relay nuclei indicated by different colours are shown in the coronal view of TRN section series arranged from anterior to posterior. The light green and the magenta shaded areas indicate the distribution of typical Ecel1+ and Spp1+ neurons, respectively. VPM, ventral posterior medial; dLGN, lateral geniculate nucleus (dorsal part); POm, posterior-medial; LP, lateral posterior-lateral part; dMGN, medial geniculate-dorsal part; vMGN, medial geniculate-ventral part; VM, ventromedial; VL, ventrolateral. n = 3 mice per region. b, Panoramic view of coronal sections showing the injection sites and cortical projection for each FO and HO thalamic nuclei. V1: primary visual cortex; V2L: secondary visual cortex lateral part; V2ML: secondary visual cortex medial-lateral part; S1BF: primary somatosensory cortex barrel field; S1DZ: primary somatosensory cortex dysgranular zones; S1FL: primary somatosensory cortex forelimb; S1HL: primary somatosensory cortex hindlimb; S2: secondary somatosensory cortex; AuV: secondary auditory cortex ventral area; Au1: primary auditory cortex; AuD: secondary auditory cortex dorsal area; MGD: medial geniculate nuclei dorsal part; MGM: medial geniculate nuclei medial part; TeA: temporal cortex, association area. n = 3 mice per region. c, Quantification of the projection ratio between the primary and higher-order secondary/tertiary cortical areas for different thalamic injection sites. ndLGN = 12 slices/2 mice, nLP = 12 slices/2 mice, nMGV = 15 slices/2 mice, nMGD/MGM = 12 slices/2 mice, nVPM = 12 slices/2 mice, nPOm = 12 slices/2 mice. Bars represent mean ± s.e.m. and raw data points.

Extended Data Fig. 5 Distribution of TRN neurons according to molecular gradient score.

a, The anatomical distribution of Patch-seq recorded neurons in coronal sections of TRN along the anterior-posterior axis. The cells were labelled with different coloured numbers as indicated (Spp1+, magenta, Ecel1+, green, DP, black and DN, blue). Numbers indicate cell ID. Shown are n = 76 cells/5 mice, data collected by 2 experimenters. b, biSNE embedding of the collected TRN neurons for Patch-seq showing molecular gradient pattern with Spp1+ (magenta), Ecel1+ (green), and the intermediate sub-populations DP (blue) and DN (black). Shown are subset of neurons from a batch of n = 68 neurons/5 mice. c, Representative voltage changes in response to hyperpolarizing current step injections. Spp1+ neurons (magenta) show robust rebound burst firings elicited by hyperpolarization with high firing frequencies within a burst. When a similar protocol is applied, most of the Ecel1+ neurons (green) show only one rebound burst with lower firing frequencies within a burst than Spp1+ neurons. DN (blue) and DP (black) neurons present intermediate properties. nEcel1+ = 15, nSpp1+ = 29, nDN = 9, nDP = 10 neurons.

Extended Data Fig. 6 TRN neurons exhibit difference in action potential properties and morphology.

a, Zoom-in view of a representative single action potential traces of Spp1+ and Ecel1+ neurons. b, Summary of action potential (AP) threshold (P = 0.015, two-sided unpaired t-test) and half-width of AP (APhw) (P = 7.08 × 105, two-sided unpaired t-test). For a, b, nSpp1 = 12, nEcel1 = 13, nDP = 6, nDN = 7 neurons from 5 mice. Plots represent mean ± s.d. and raw data points. c, Example of Spp1+ like (‘Spp1’) (magenta) and Ecel1+ like (‘Ecel1’) (green) neuron morphology. d, Sholl analysis of the dendritic complexity. e, Summary of the soma length and width, total dendritic length and maximum number of intersections in Spp1+ like (‘Spp1’) and Ecel1+ like (‘Ecel1’) neurons (Mean ± s.d. Dendritic length, P = 0.0014. Number of intersections, P = 0.0004, two-sided unpaired t-test). For ce, n’Spp1’ = 11 neurons/4 mice, n’Ecel1’ = 10 neurons/4 mice.

Extended Data Fig. 7 AAV-mediated pooled in vivo CRISPR screening.

a, Schematics of the AAV-mediated pooled CRISPR–Cas9 in vivo screen. b, List of pools and genes selected for knockout in the CRISPR–Cas9 screening. TRN enriched refers to genes differentially expressed between Pvalb+ neurons from TRN and from M2 cortex, somatosensory cortex, striatum, and hippocampus. c, A heat map showing the expression pattern of the selected genes in the TRN neurons. The selected disease-risk genes are labelled on the right side. d, A heat map showing the differentially expressed disease-risk genes in Spp1+ versus Ecel1+ neurons: autism spectrum disorder (ASD, purple) and schizophrenia (orange). e, Violin plots showing a list of genes differentially expressed between Pvalb+ neurons in TRN compared and Pvalb+ neurons in the four other brain regions including hippocampus (HP), secondary motor cortex (M2), somatosensory cortex (SCX), and striatum (STR). f, Violin plots confirming the TRN-enriched gene list as shown in e in additional brain regions using the mousebrain.org datasets. CB: cerebellum; Hypoth: hypothalamus; MBd: medial basal nucleus dorsal part; MBV: medial basal nucleus ventral part; SC: spinal cord; Thal: thalamus. g, Violin plots showing selected differentially expressed disease-risk genes compared to the Pvalb+ neurons in the other four brain regions as indicated. HP: hippocampus; M2: secondary motor cortex; SCX: somatosensory cortex; STR: striatum. For e and g, nHP = 90, nM2 = 97, nSCX = 116, nSTR = 13, nTRN = 671 cells; For (f), nCA1 = 136, nCB = 477, nHypoth = 156, nMBb = 331, nMBv = 209, nMedulla = 121, nPons = 199, nSC = 69, nThal = 54, nTRN = 501 cells. The violin plots width is based off of a Gaussian kernel density estimate of the data (estimated by the standard density function in R with default parameters), scaled to have maximum width equal to 1.

Extended Data Fig. 8 Pooled in vivo CRISPR–Cas9 screening reveals gene sets contributing to TRN bursting firing properties.

a, Representative current-clamp recording traces of Spp1+ like (‘Spp1’, magenta) and Ecel1+ like (‘Ecel1’, green) neurons held at different membrane potentials. The trace with the maximum number of bursts was selected for measuring different burst properties and calculating the Z-score (shown in the right). b, Plot showing confidence interval ellipses for classifying Spp1+ like (‘Spp1’) and Ecel1+ like (‘Ecel1’) neurons based on the AHP and the number of rebound bursts. c, Representative rebound burst traces of recorded neurons after knocking out different sets of genes via CRISPR–Cas9 gene editing. Traces show rebound bursting activity changes in response to hyperpolarizing current step injections. TRN neurons exhibited distinct changes in their firing patterns after knockout of different gene groups. d, Radar plots of 5 electrophysiological parameters illustrated in a, showing the deviation of perturbed group to the control after knocking out sets of genes in the pooled approach. Positive changes show an increase towards a parameter, while negative changes show a decrease when compared to control. Green line indicates deviations in Ecel1+ like neurons and colour shades indicates deviations in Spp1+ like neurons. e, Summary of the maximum number of rebound bursts of TRN neurons elicited by comparable hyperpolarizing current step injection as described in Fig. 4b after different sets of genes were knocked out in the pooled approach in Spp1+ like (‘Spp1’) vs Ecel1+ like (‘Ecel1’) neurons (‘Spp1’ Pool1, P = 4.8742 × 107; Pool3, P = 0.0033; Pool5, P = 0.0088; Pool7, P = 0.0065. ‘Ecel1’ Pool3, P = 0.0081; Pool7, P = 0.023, two-sided unpaired t-test). Bars represent the mean ± s.e.m. For ae: ‘Spp1’ Ighe n = 12, Pool1 n = 12, Pool2 n = 9, Pool3 n = 13, Pool4 n = 9, Pool5 n = 10, Pool6 n = 9, and Pool7 n = 10 cells; ‘Ecel1’ Ighe n = 9, Pool1 n = 12, Pool2 n = 13, Pool3 n = 10, Pool4 n = 8, Pool5 n = 10, Pool6 n = 8, and Pool7 n = 9 cells from 24 mice (3 mice per pool).

Extended Data Fig. 9 Characterization and validation of in vivo CRISPR–Cas9 screening reveals key genes contributing to TRN bursting firing properties.

a, Representative rebound burst traces of recorded neurons after knocking out different individual genes from Pool3 via CRISPR–Cas9 gene editing. Knocking out of Kcnd2 recapitulates the effects of Pool#3. b, Radar plots for Pool3 individual gene. Top: Changes in Spp1+ like (‘Spp1’) neurons, pink line showing the effect of the Pool3 gene knock out and colour shades showing the effect produced by individual gene knock out. Bottom: Changes in Ecel1+ like (‘Ecel1’) neurons, green line showing the Pool3 gene radar plot and colour shades showing the changes produced by individual gene knockout. Kcnd2 knockout closely recapitulates the effect of Pool3 in both populations. c, Summary of the maximum number of rebound bursts of TRN neurons elicited by comparable protocols after individual genes from Pool3 were knockout in Spp1+ like (‘Spp1’) vs Ecel1+ like (‘Ecel1’) neurons (‘Spp1’ Kcnd2, P = 0.0095. ‘Ecel1’ Kcng1, P = 0.0088; Kcnd2, P = 0.019, two-sided unpaired t-test). Bars represent the mean ± s.e.m. For ac, ‘Spp1’ Kcng1 n = 6, Kcnc3 n = 6, Kcng4 n = 5, Kcnip1 n = 7, Kcnd2 n = 7; ‘Ecel1’ Kcng1 n = 10, Kcnc3 n = 8, Kcng4 n = 9, Kcnip1 n = 11, Kcnd2 n = 11. d, Schematics of the analysis for on-target and off-target efficiency. Upper: analysis flowchart. WGA: whole genome amplification; NGS: next generation sequencing. Lower: schematics of sgRNA design and primers for on-target analysis for Kcnd2 knockout. Five sgRNA were designed in Exon2, Exon3, and Exon4. As the length spanned by the leftmost sgRNA and the rightmost sgRNA exceeds the NGS analysis limit, nested PCR combined with Sanger sequencing was used for on-target efficiency analysis. Primers for the nested PCR are shown as black arrows in Exon1 and Exon5. e, Bar chart showing the on-target efficiency (5 sgRNA pooled) analysed by nested PCR and Sanger sequencing (control: n = 96 nuclei, viral injected: n = 384 nuclei) and off-target rate for the top predicted (Methods) off-target loci of each sgRNA analysed by NGS (n = 1,600 cells and 72,000 nuclei). Predicted off-target sequences are shown with mismatched bases in lower case. Bar plots represent maximum likelihood estimation (MLE) and upper Wilson score intervals, no raw data point applicable64 (Supplementary Information).

Extended Data Fig. 10 γ6 expression and its perturbation effect in the TRN cells.

a, Calcium currents measured in control (black traces) and with γ6 expression (red traces). b, Summarized current density versus voltage relations showing that γ6 expressing TRN neurons exhibit smaller calcium current densities than controls (P = 0.02, two-sided unpaired t-test, data presented as mean ± s.e.m.). For a, b, n = 6 neurons/3 mice. c, d, Quantification of retrogradely labelled cells (c; P = 0.6170, n.s, not significant, two-sided unpaired t-test) and their percentage of total PV+ neurons (d) in the series of coronal slices from injected mice. L: left hemisphere; R: right hemisphere; g6: γ6; FO: first order; HO: higher order. For c, d, n = 7 for each experimental condition, data presented as mean ± s.e.m. For c, plots are overlaid with raw data points. e, Scatter plots showing γ6 expressing percentage and the effect size for individual mice. Top row: delta power percentage; middle row: number of spindles per minutes in NREM; bottom row: median length of sleep bout in NREM in seconds; dots: animals with retrograde γ6 injection in FO (Red) and HO (Green) somatosensory thalamic nucleus. n = 6 for each conditions. f, Cumulative distribution of sleep spindle length for each individual mouse with retrograde γ6 injection in FO (upper) and HO (lower) somatosensory thalamic nuclei, corresponding to Fig. 5h. g, h, Summary of median length of NREM sleep bouts with retrograde γ6 injection in FO (g) and HO (h) somatosensory thalamic nuclei. Right: two-sided Wilcoxon rank-sum test; Left: Kolmogorov–Smirnov test. For data in fh, ncontrol (FO) = 8, nγ6 (FO) = 8, ncontrol (HO) = 7, nγ6 (HO) = 8. Box plots represent minima, 25th, 50th, 75th percentiles, maxima.

Supplementary information

Supplementary Information

This file contains a Supplementary Discussion, Supplementary Methods and Supplementary Tables 1-5.

Reporting Summary

Supplementary Table 6

Primer sequences.

Supplementary Table 7

Design of sgRNA targets.

Supplementary Table 8

CRISPR screen efficiency and specificity.

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Li, Y., Lopez-Huerta, V.G., Adiconis, X. et al. Distinct subnetworks of the thalamic reticular nucleus. Nature 583, 819–824 (2020). https://doi.org/10.1038/s41586-020-2504-5

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