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. 2021 Dec 13;10:e68224. doi: 10.7554/eLife.68224

Figure 4. Combinatorial transcription factors (TFs) in marking tectal morphological subclasses.

(A) Left: the schematic showing the procedure of collecting single-cell transcriptomes of tectal glutamatergic neurons with fluorescence-activated cell sorting (FACS) using Tg (vglut2a:loxp-DsRed-loxp-GFP) fishline. Right: the t-distributed stochastic neighbor embedding (t-SNE) plot of 3, 883 cells obtained from Tg (vglut2a:loxp-DsRed-loxp-GFP) fishline labelling glutamatergic neurons in the optic tectum showing 11 clusters, each color-coded and marked by a number. (B) Schematic showing the designing of the Gal4FF BAC plasmids for six TF marker genes, covering all 11 clusters of tectal glutamatergic neurons shown in A. (C) Schematic showing the method for single TF-based labeling of tectal glutamatergic neurons. CRE expressed in glutamatergic neurons was used to excise loxp and drive fluorescent tdTomatocaax expression. (D) Representative images of seven subclasses of tectal glutamatergic neurons with distinct morphological subclasses using the method described in (B–C). The number of neurons collected for each subclass was shown. Insets depicted the morphological characteristics. Neurons with ascending and descending projections were those projecting to the forebrain and hindbrain, respectively. Solid lines marked the boundaries between brain regions. Dashed lines marked the boundary of the tectal neuropile. Scale bars: 20 μm. (E) The matrix showing the expressions of six TFs in each of seven morphological subclasses. The black squares represented TFs could label particular morphological subclasses, and no expression was indicated by white squares.

Figure 4—source data 1. The annotation of transcription factors (TFs) expression in each tectal glutamatergic clusters.
Figure 4—source data 2. Gene labeled morphological analysis of tectal glutamatergic neurons.

Figure 4.

Figure 4—figure supplement 1. Combinatorial transcription factors (TFs) in marking tectal morphological subclasses.

Figure 4—figure supplement 1.

(A) Canonical correlation analysis (CCA) of cells from two independent experiments of Tg (vglut2a:loxp-DsRed-loxp-gfp), two rounds overlapping indicated data reproducibility. Two rounds of data were color-coded. (B) Lawson-Hanson algorithm for non-negative least squares (NNLS) analysis showing the relationship of transcriptome-based clusters of tectal glutamatergic neurons from sorted samples with Tg (vglut2a:loxp-DsRed-loxp-gfp) and whole-brain samples. Sorted clusters could cover all clusters from whole-brain sample. The correltion coefficiency was both color-coded and size-coded. (C) t-Distributed stochastic neighbor embedding (tSNE) plots of expression of mab21l2 and vglut2a (shown with slc17a6b) in sorted tectal glutamatergic neurons. Tubb5 and tfap2a are the marker genes of clusters of tectal glutamatergic neurons. (D) The JaccardRainCloundPlot showing the stability of tectal glutamatergic neuronal clusters in Figure 4A. Red line indicated the 0.6 cutoff of Jaccard index to evaluate the cluster stability. Red arrowhead indicated unstable clusters. (E) Left: tSNE plot showing the expression of TF in the clusters of tectal glutamatergic neurons. Right: the percentages of TF-expressed cells in each of 11 clusters (upper) and the averaged UMI of each TF-expressed cell in each cluster (bottom). (F) The matrix showing the expressions of six TFs in each of 11 tectal glutamatergic neurons. The labeled were indicated by black squares and no expression was indicated by white squares. (G) The matrix showing 574 neurons expressing each of six TFs in E. All neurons were categorized into seven morphological subclasses: bi-stratified (n = 36), mono-stratified (n = 71), non-stratified (n = 318), necklace (n = 76), cross-hemisphere (n = 15), ascending projection (n = 18), and descending projection (n = 40). (H) NNLS analysis showing the correlation of morphological subclasses and transcriptome clusters. The correltion coefficiency was both color-coded and size-coded.