Abstract
The brain consists of thousands of neuronal types that are generated by stem cells producing different neuronal types as they age. In Drosophila, this temporal patterning is driven by the successive expression of temporal transcription factors (tTFs)1-3 We used single-cell mRNA sequencing to identify the complete series of tTFs that specify most Drosophila optic lobe neurons. We verify that tTFs regulate the progression of the series by activating the next tTF(s) and repressing the previous one(s), and also identify more complex regulations. Moreover, we establish the temporal window of origin and birth order of each neuronal type in the medulla and provide evidence that these tTFs are sufficient to explain the generation of all the neuronal diversity in this brain region. Finally, we describe the first steps of neuronal differentiation. We find that terminal differentiation genes, such as neurotransmitter-related genes, are present as transcripts, but not as proteins, in immature larval neurons; we show that these steps are conserved in humans. This comprehensive analysis of a temporal series of tTFs in the optic lobe offers mechanistic insights into how tTF series are regulated, and how they can lead to the generation of a complete set of neurons.
The brain is the most complex organ of the animal body: the human brain consists of over 80 billion neurons4 that belong to thousands of neuronal types. As neural stem cells age, temporal patterning allows them to generate different neuronal types in the correct order and stoichiometry1-3,5-7. Temporal patterning in neuronal systems was first described in the Drosophila ventral nerve cord (VNC), where a cascade of temporal transcription factors (tTFs) is expressed in embryonic neural stem cells (neuroblasts) as they divide and age8-10. This concept was later expanded to the Drosophila optic lobe, with a different tTF series. It was later suggested that tTFs also contribute to the generation of neuronal diversity in different mammalian neuronal tissues, such as the retina11-14 and the cortex15. However, series of tTFs are incomplete, as they were discovered by relying on existing antibodies. To generate a comprehensive description of the tTFs patterning a neural structure we have used single-cell mRNA sequencing (scRNASeq) of the larval fly optic lobe.
The Drosophila optic lobe is an ideal system to address how neuronal diversity is generated and how neurons proceed to differentiate. It is an experimentally manageable, albeit complex structure, for which we have a very comprehensive catalogue of neuronal cell types. Meticulous work from the last decades has identified multiple cell types in the optic lobes based solely on morphological characters16. Recent work took advantage of elaborate molecular genetic tools, as well as scRNASeq, to expand the number of neuronal cell types to ~200, based on both morphology and molecular identity17-19. Importantly, the neuroblasts that generate the medulla, which is the largest optic lobe neuropil containing ~100 neuronal types, are formed by a wave of neurogenesis over a period of days20,21 and progress through the same tTF temporal series22,23. This means that at any given developmental stage from mid third larval stage (L3) to early pupal stages (P15) the neurogenic region contains neuroblasts at all developmental stages (Figure 1a).
Medulla neuroblast temporal series
To study neuroblast and neuronal trajectories, we performed scRNASeq on the optic lobes. We obtained 49,893 single-cell transcriptomes from 40 L3 optic lobes (Extended Data Figure 1). The Outer Proliferation Center (OPC) neuroepithelium generates two optic lobe neuropils: the medulla from the medial side and the lamina from the lateral side20 (Figure 1a). Medulla neuroepithelium, neuroblasts, intermediate precursors (called GMCs) and neurons were arranged in the UMAP24 following a progression that resembled their differentiation in vivo (Figure 1b - Extended Data Figure 2a). Similarly, lamina neuroepithelium, precursor cells, and neurons were also arranged following a similar differentiation trajectory but in the opposite orientation of that of the medulla. The neuroblasts and the neurons that are generated from the Inner Proliferation Center (IPC) followed a different trajectory in the UMAP plot (Figure 1b).
We then merged the larval single-cell dataset with the annotated early pupal stage 15 (P15) single-cell dataset18. The P15 neurons mapped at the tip of each of the neuronal trajectories (Figure 1c), which allowed us to identify the corresponding neuronal types. We identified neurons from all the neuropils of the optic lobe (lamina, medulla, lobula, and lobula plate), as well as a small number of neuroblasts and neurons from the central brain that were likely retained when microdissecting the optic lobe (Extended Data Figure 2b-c).
We then looked at the expression of the known spatial TFs in the OPC neuroepithelium and tTFs in the neuroblasts:
The spatial TFs Vsx1, Optix, and Rx25, were expressed in largely non-overlapping subsets of neuroepithelial cells (Extended Data Figure 2d-e).
The tTFs Homothorax (Hth), Eyeless (Ey), Sloppy-paired (Slp), D, and Tll22 were expressed in neuroblast subsets that were temporally organized in the UMAP plot (Figure 1d).
Thus, the UMAP plot recapitulated both proliferation and differentiation axes in the developing tissue: the UMAP horizontal axis represents differentiation status, while the vertical axis represents neuroblasts progressing through their tTF series.
The larval scRNASeq dataset gave us the opportunity to look for all potential tTFs in an unbiased way. We isolated the medulla neuroblast cluster from the scRNASeq data and used Monocle26 to reconstruct their developmental trajectory. Hth, Ey, Slp1/2, D and Tll were expressed in the previously described temporal order along the trajectory (Figure 1e). We therefore examined the expression dynamics of all TFs and identified 14 candidate tTFs whose expression was restricted to a specific pseudotime window, including the 6 previously known tTFs (Extended Data Figure 3). Using antibodies or in situ hybridization for the eight newly discovered candidate tTFs and those already known in medulla neuroblasts, we showed that their expression was indeed limited to restricted temporal windows (Figure 1f-l and Extended Data Figure 4), thus defining new temporal windows as the neuroblasts progress through divisions (Figure 1e).
tTFs assume different roles in the series
The previously known tTFs (except Hth) contribute to the progression of the series by activating the next tTF in the cascade and repressing the previous one22. To test which of the newly identified tTFs were involved in the progression of the temporal series (Figure 2a), we generated tTF mutant neuroblast MARCM clones27 or tTF RNAi knockdowns using the MZVUM-Gal4 line that is expressed in the Vsx1 domain28 of the OPC (Figure 2, Extended Data Figures 5-6).
Early unit (Hth, Erm, Opa, Oaz):
Hth is expressed in the neuroepithelium and young neuroblasts, and is not required for Ey activation22. We identified two factors that regulate the expression of Ey in different manners: Erm is required to activate Ey and to inhibit Hth (Figure 2b), while Opa is required for the correct timing of Ey activation (Figure 2c). Opa also activates the expression of Oaz (Extended Data Figure 6b), which does not regulate the expression of any of the tTFs (Extended Data Figure 5f-j). Opa expression is repressed by Erm (Figure 2d). Once Ey expression is initiated at the correct time by the combined action of Erm and Opa, Ey represses the expression of its activators (Figure 2e-f). Therefore, Erm is essential for the progression of the cascade, while Opa contributes to the correct timing of expression of the next tTFs.
Middle unit (Ey, Hbn, Slp, Scro, Opa)
We had previously shown that Ey activates Slp, which in turn inhibits Ey22. However, the developmental trajectory of neuroblasts uncovered a more complex situation. First, Ey activates Hbn (Figure 2g). Hbn then represses Ey and activates Slp (Figure 2h). Hbn also activates Scro and a second wave of Opa expression (Figure 2i-j). Hbn then inhibits the expression of Erm (Figure 2i) and Scro inhibits the expression of Ey (Figure 2k). Finally, Slp inhibits Hbn, Opa, and Oaz (Figure 2l-m, Extended Data Figure 6c).
Late unit: (D, BarH1,Tll)
D expression requires both Slp and Scro. We had previously shown that in slp mutant clones, D is not expressed22. Similarly, when Scro was knocked down by RNAi, D was not activated (Figure 2n). Scro is therefore important for the progression of the series, as it inhibits Ey and activates the expression of D. It remains expressed until the end of the neuroblast life. Once D is activated, it inhibits Slp22 and activates BarH1 (Figure 2o), which in turn activates Tll (Figure 2p). Finally, similar to the inhibitory interaction between Tll and D previously described22, Tll is sufficient but not necessary to inhibit BarH1 (Extended Data Figure 5n, Extended Data Figure 6j).
We have thus identified most, if not all, temporally expressed TFs in a developing neuronal system and show that these tTFs participate in the progression of the temporal series. We also confirmed many of these interactions by analyzing the effect of tTF mis-expression on the temporal cascade (Extended Data Figure 6d-j).
Besides their participation in the progression of the temporal series, tTFs regulate neuronal identity. Some tTFs are maintained in the neuronal subsets that are generated during their temporal window (Extended Data Figure 7a-a'), while others are only maintained in newly born neurons (Extended Data Figure 7a’’-a’’’-b). tTFs activate the expression of downstream neuronal transcription factors22,23 that regulate effector genes in the absence of the tTF. To test how tTFs regulate neuronal identity, we asked whether knocking down the expression of the tTFs in neuroblasts affects the expression of neuronal transcription factors. The loss of hth, ey, and slp in neuroblasts leads to the loss of Bsh-, Vvl-, and Toy-positive neurons, respectively22. We show that Hbn is required for the specification of Toy, Traffic-jam (Tj) and Orthodenticle (Otd)-positive neurons (Extended Data Figure 7c-c’) and Opa is required for the generation of TfAP-2-positive neurons (Extended Data Figure 7d). Therefore, Hbn and Opa, as well as Hth, Ey, and Slp22, regulate neuronal diversity not only by allowing the temporal series to progress, but also by regulating neuronal transcription factor expression.
Temporal window of origin of medulla neurons
The identified tTFs define at least 11 temporal windows, in which different neurons (and glia) are generated (Figure 3a). As they are generated, newly born neurons displace earlier born neurons away from the parent neuroblast29, creating a columnar arrangement of neuronal cell bodies in the medulla cortex that represent birth order: Early born neurons are located close to the emerging medulla neuropil, while late born neurons are closer to the surface of the brain ( Figure 3a’ )29,30. Neurons born in each temporal window express downstream effectors of tTFs (e.g., Bsh, Runt (Run) and Vvl) that were termed “concentric genes” due to their pattern of expression22,29 ( Figure 3a’ ). We used the expression of tTFs in GMCs, and previously described22,29 and new concentric genes (this work) in scRNASeq neuronal clusters, together with their relative proximity in the UMAP plot (Figure 3b, Extended Data Figure 8), to assign the 105 neuronal clusters that comprise the medulla dataset (Extended Data Figure 8d) to their predicted temporal window of origin (Figure 3c and Supplementary Table 1). Proximal medulla (Pm) neurons are generated in the Hth and Hth/Opa temporal windows, while distal medulla (Dm) neurons are generated starting from the Ey temporal window. On the other hand, transmedullary (Tm) neurons are generated throughout most of the neuroblast life (Opa, Ey/Hbn and Slp temporal windows) (Figure 3c and Supplementary Table 1). Importantly, co-expression of some concentric genes is restricted to subregions of the medulla cortex, which allowed us to assign the spatial origin to several medulla neuron clusters (e.g. Extended Data Figure 8a arrowheads and Supplementary Table 1).
To assess the Notch status of all neuronal types, we also looked at the expression of Apterous (Ap), which is expressed in the NotchON progeny of each GMC22. Among the 105 neuronal types, 64 were NotchOFF and 41 NotchON (Extended Data Figure 8c and Supplementary Table 1). Since a given GMC division generates one NotchON and one NotchOFF neuron, Ap+ and Ap− neurons are intermingled in the medulla cortex22. Therefore, the position in the medulla cortex of concentric TFs expressed in NotchON and NotchOFF neurons allows us to infer sister neurons, for instance Run neurons are likely sisters of TfAP-2 neurons, while early born Vvl neurons are likely sisters of Knot (Kn) neurons (Extended Data Figure 8a vii,xi).
Finally, we assigned neurotransmitter identity to all the medulla clusters at L3 and P15 stages (Supplementary Table 1). Ap expression is highly correlated with cholinergic identity17, as nearly all Ap+, i.e. NotchON, clusters in our dataset express ChAT and thus have cholinergic identity, while most of the NotchOFF clusters are either GABAergic (most of them express Lim3)17 or glutamatergic (most of them express Tj or Fd59A)17. Interestingly, all the NotchOFF neurons from the same temporal window express the same neurotransmitter, independently of their spatial origin (Figure 3d and Supplementary Table 1). This suggests that the temporal origin of medulla neurons and their Notch status instructs shared TF expression and neurotransmitter identity, and hence function. In summary, we defined the temporal (and spatial) origin, birth order, and Notch identity of all medulla cell types and highlight the role of tTFs in regulating the generation of neural diversity.
Early commitment to neuronal identity
To study the first steps of neuronal differentiation after specification, we merged the clusters from pupal stages (P15, P30, P40, P50, and P70) corresponding to the Mi1 cells with the L3 scRNASeq cluster and the GMCs most closely linked to them in the UMAP plot (Extended Data Figure 9a). We reconstructed their differentiation trajectory (Extended Data Figure 9b-c), identified groups of genes (modules) that co-vary along the entire trajectory from L3 to P70 and searched for the Gene Ontology (GO) terms enriched in each gene module (Figure 4a). The timing of differentiation appears to follow a specific path: At L3, cell cycle genes and DNA replication genes are first expressed, as expected from the division of GMCs. This is closely followed by genes involved in translation. Then, genes related to dendrite development and axon-guidance are upregulated from late L3 until P30, stages when the neurons direct their neurites to the appropriate neuropils. Genes important for neuronal function, such as neurotransmitter-related genes, synaptic transmission proteins, as well as ion channels start to be expressed as early as L3, reaching a plateau that is maintained until P15. Their expression then increases again until adulthood, when their products support neuronal function (Figure 4a). This timing of differentiation was observed not only for Mi1 but could be generalized to all optic lobe neurons (Figure 4c). These results indicate that not only is neuronal identity specified during the first hours of neuronal development, but their neuronal function (as indicated by the upregulation of chemical synaptic transmission terms) is implemented very early, although it will only be required much later. As this was unexpected, we asked whether neurotransmitter mRNA expression observed as early as late L3 was also translated into protein. Neurotransmitter-related genes, ChAT, VGlut, and Gad1 mRNA are all expressed in the scRNASeq data in non-overlapping neuronal sets (Figure 4d) and are maintained in the adult18 (Supplementary Table 1). However, we did not observe protein expression at L3 (Figure 4e). This suggests that their transcription represents a commitment to a specific neurotransmitter identity early, but that other factors prevent premature translation of these mRNAs until they are needed at later stages of development.
Common trajectory of Drosophila and human neurons
We then asked whether the Drosophila optic lobe neuronal differentiation trajectory was similar to human neuronal differentiation. We generated single-nuclear RNAseq data from the human fetal cortical plate at gestational week 19. We used Monocle3 to reconstruct their developmental trajectory (Extended Data Figure 9d-e) from apical progenitors to intermediate progenitors and postmitotic neurons (Extended Data Figure 9f) and identified gene modules that were co-regulated along the trajectory. GO analysis uncovered a remarkable similarity to Drosophila (Extended Data Figure 9g). We then plotted the expression of the GO terms that were expressed at different stages of the differentiation trajectory in Drosophila on the human cortical differentiation trajectory (Figure 4b). We observed very similar dynamics; the main difference was the absence of enrichment for ribosome assembly and translation-related GO terms at early stages. This could potentially be explained by the slower development of human neurons compared to Drosophila, which leads to a slower increase in size and the fact that the divisions of the radial glia are more symmetric31 than those of optic lobe neuroblasts. Despite this difference, these results show that neurons follow a similar differentiation trajectory in Drosophila and humans.
Drosophila tTFs in mouse progenitors
Although temporal patterning is a universal neuronal specification mechanism32,33, it is unclear how it has evolved6,7. We asked whether the medulla tTFs were conserved in mouse cortical radial glia using a published scRNASeq dataset34. None of the medulla neuroblast tTFs were expressed in strict temporal windows in ageing radial glia, with the exception of Pax6, which was enriched in older progenitors (Extended Data Figure 10a). Reciprocally, the Drosophila orthologs of the mouse temporally expressed TFs33 were not expressed temporally in the developing optic lobe.
The mouse orthologs of Drosophila VNC tTFs Ikzf1, Pou2f1/Pou2f2, and Casz1 are expressed temporally in mouse retinal progenitors11,12,14. We looked at the expression of the optic lobe tTFs in the mouse retina in a published scRNASeq dataset35. Pax6/Ey was constitutively expressed, Meis2/Hth, Zic5/Opa, and Sox12/D were expressed at embryonic stage 12, while Nr2e1, the ortholog of Tll (which is expressed when neuroblasts become gliogenic), was expressed late, when retinal progenitors become gliogenic and start generating Müller glia36 (Extended Data Figure 10d). The lack of a strict conservation of tTFs between flies and mice indicates that the acquisition of the specific temporal series occurred independently in each phylum.
Conclusions
The comprehensive series of transcription factors described in this work and their regulatory interactions temporally pattern a developing neural structure. We show that most tTFs are expressed in overlapping windows, creating combinatorial codes that differentiate neural stem cells of different ages and therefore provide them with the ability to generate diverse neurons after every division. We conservatively assigned them into 11 distinct temporal windows (10 of which generate neurons), which, when integrated with spatial patterning (6 spatial domains) and the Notch binary cell fate decision, can explain the generation of ~120 cell types, which is close to the entire neuronal type diversity of the Drosophila medulla. Moreover, we determined the downstream TFs that were expressed in neurons produced temporally, which allowed us to establish the birth order of all medulla neurons. Additionally, we provide a detailed transcriptomic description of the first steps in the differentiation trajectory of a neuron. Terminal differentiation genes are expressed within the first 20 hours of neuronal life, approximately 2-4 days before their protein products can fulfil their function. Why these genes are expressed so early remains unknown, but we hypothesize that this reflects the commitment of neurons to a specific function. We also show that all neurons follow the same route for differentiation and that this is similar to the differentiation process in developing human cortical neurons. Hence, understanding the mechanisms of neuronal differentiation in flies can generate insight for the equivalent process in humans (see also Supplementary Discussion).
Methods
Genetics
To generate MARCM clones, crosses were kept at 25 °C and were heat-shocked for one hour at 37 °C four days before dissecting wandering L3 larvae. For RNAi experiments, MzVUM-Gal4 (Vsx-Gal4) flies were crossed to flies carrying the RNAi construct; the crosses were kept at 25 °C before dissecting wandering L3 larvae. The crosses are indicated below:
hth RNAi: MzVUM-Gal4; UAS-CD8.GFP; flies were crossed with ;hth-RNAi; flies
Oaz RNAi: MzVUM-Gal4; UAS-CD8.GFP; flies were crossed with yscvsev;; Oaz-RNAi flies
scro RNAi: MzVUM-Gal4; UAS-CD8.GFP; flies were crossed with yv;; scro-RNAi flies
BarH1 RNAi: MzVUM-Gal4; UAS-CD8.GFP; flies were crossed with ;BarH1-RNAi; flies
erm- MARCM clones: ;erm1, FRT40A/CyO,act-GFP; flies were crossed with UAS-CD8GFP, hs-flp; FRT40A, tub-Gal80; tub-Gal4/TM6B flies.
opa- MARCM clones: ;;FRT82B - opa(null)/TM6B flies were crossed with yw, hs-flp, UAS-GFP;; tub-Gal4, FRT82B, tub-Gal80/TM6C flies.
ey- MARCM clones: yw, hs-flp122; +/(Cyo); FRT80B/TM6B; ey[j5.71]/In(4) flies were crossed with yw, hs-flp122; +/cyo; FRT80B ey-rescue (y+) ubiGFP/TM6B; ey [J5.71]/In(4) flies.
D- MARCM clones: yw; If/Cyo; D[87],FRT2A/TM6B flies were crossed with yw, hs-flp; if/cyo; FRT2A, ubi-nlsGFP/TM6B flies.
hbn- MARCM clones: FRT42B(G13), hbn15227 flies were crossed with yw, hs-flp; FRT42B(G13), tub-Gal80/CyO, act-GFP; tub-Gal4, UAS-CD8GFP/TM6,Tb,Hu flies.
slp- MARCM clones: yw, hs-flp122; slp[s37a],FRT40A/SM6~TM6B flies were crossed with UAS-CD8GFP, hs-flp; FRT40A, tub-Gal80; tub-Gal4/TM6B flies.
tll- MARCM clones: w;; FRT82B, tll[I49]/TM3,GFP,Ser flies were crossed with yw, hs-flp, UAS-GFP;; tub-Gal4, FRT82B, tub-Gal80/TM6C flies.
Origin of all individual stocks is detailed in Supplementary Table 2.
Antibody generation
Polyclonal antibodies were generated by Genscript (https://www.genscript.com/). The epitopes used for each immunization are listed below.
Erm
KTFSCLECGKVFNAHYNLTRHMPVHTGARPFVCKVCGKGFRQASTLCRHKIIHTSEKPHKCQTCGKAFNRSSTLNTHSRIHAGYKPFVCEYCGKGFHQKGNYKNHKLTHSGEKAYKCNICNKAFHQVYNLTFHMHTHNDKKPYTCRVCAKGFCRNFDLKKHMRKLHEIGGDLDDLDMPPTYDRRREYTRREPLASGYGQASGQLTPDSSSGSMSPPINVTTPPLSSGETSNPAWPRSAVSQYPPGGFHHQLGVAPPHDYPSGSAFLQLQPQQPHPQSQQHHQQQQRLSETFIAKVF
Ey
MFTLQPTPTAIGTVVPPWSAGTLIERLPSLEDMAHKDNVIAMRNLPCLGTAGGSGLGGIAGKPSPTMEAVEASTASHPHSTSSYFATTYYHLTDDECHSGVNQLGGVFVGGRPLPDSTRQKIVELAHSGARPCDISRILQVSNGCVSKILGRYYETGSIRPRAIGGSKPRVATAEVVSKISQYKRECPSIFAWEIRDRLLQENVCTNDNIPSVSSINRVLRNLAAQKEQQSTGSGSSSTSAGNSISAKVSVSIGGNVSNVASGSRGTLSSSTDLMQTATPLNSSESGGASNSGEGSEQEAIYEKLRLLNTQHAAGPGPLEPARAAPLVGQSPNHLGTRSSHPQLVHGNHQALQQHQQQSWPPRHYSGSWYPTSLSEIPISSAPNIASVTAYASGPSLAHSLSPPNDIESLASIGHQRNCPVATEDIHLKKELDGHQSDETGSGEGENSNGGASNIGNTEDDQARLILKRKLQRNRTSFTNDQIDSLEKEFERTHYPDVFA
Esg
MHTVEDMLVEKNYSKCPLKKRPVNYQFEAPQNHSNTPNEPQDLCVKKMEILEENPSEELINVSDCCEDEGVDVDHTDDEHIEEEDEDVDVDVDSDPNQTQAAALAAAAAVAAAAAASVVVPTPTYPKYPWNNFHMSPYTAEFYRTINQQGHQILPLRGDLIAPSSPSDSLGSLSPPPHHYLHGRASSVSPPMRSEIIHRPIGVRQHRFLPYPQMPGYPSLGGYTHTHHHH
Hbn
MMTTTTSQHHQHHPIMPPAMRPAPVQESPVSRPRAVYSIDQILGNQHQIKRSDTPSEVLITHPHHGHPHHIHHLHSSNSNGSNHLSHQQQQQHSQQQHHSQQQQQQQQLQVQAKREDSPTNTDGGLDVDNDDELSSSLNNGHDLSDMERPRKVRRSRTTFTTFQLHQLERAFEKTQYPDVFTREDLAMRLDLSEARVQVWFQNRRAKWRKREKFMNQDKAGYLLPEQGLPEFPLGIPLPPHGLPGHPGSMQSEFWPPHFALHQHFNPAAAAAAGLLPQHLMAPHYKLPNFHTLLSQYMGLSNLNGIFGAGAAAAAAAASAGYPQNLSLHAGLSAMSQVSPPCSNSSPRESPKLVPHPTPPHATPPAGGNGGGGLLTGGLISTAAQSPNSAAGASSNASTPVSVVTKGED
Scro
MSSHGLAYTTRIERKSYRELQINRDQYFVTAPNEEDLVMSLSPKDTLIHTAISQHHQVDTSTKLNTNETSTQNTVSTAAAAAVAHHHHNLSSIHHLQNLHSQHQSTLFNSNH
Slp2
MVKIEEGLPSSEISAHSLHFQHHHHPLPPTTHHSALQSPHPVGLNLTNLMKMARTPHLKSSFSINSILPETVEHHDEDEEEDVEKKSPAKFPPNHNNNNLNTTNWGSPEDHEAESDPESDLDVTSMSPAPVANPNESDPDEVDEEFVEEDIECDGETTDGDAENKSNDGKPVKDKKGNE
Vvl (rat)
EEDTPTSDDLEAFAKQFKQRRIKLGFTQADVGLALGTLYGNVFSQTTICRFEALQLSFKNMCKLKPLLQKWLEEADSTTGSPTSIDKIAAQGRKRKKRTSIEVSVKGALEQHFHKQPKPSAQEITSLADSLQLEKEVVRVWFCNRRQKEKRMTPPNTLGG
Tll
MQSSEGSPDMMDQKYNSVRLSPAASSRILYHVPCKVCRDHSSGKHYGIYACDGCAGFFKRSIRRSRQYVCKSQKQGLCVVDKTHRNQCRACRLRKCFEVGMNKDAVQHERGPRNSTLRRHMAMYKDAMMGAGEMPQIPAEILMNTAALTGFPGVPMPMPGLPQRAGHHPAHMAAFQPPPSAAAVLDLSVPRVPHHPVHQGHHGFFSPTAAYMNALATRALPPTPPLMAAEHIKETAAEHLFKNVNWIKSVRAFTELPMPDQLLLLEESWKEFFILAMAQYLMPMNFAQLLFVYESENANREIMGMVTREVHAFQEVLNQLCHLNIDSTEYECLRAISLFRKSPPSASSTEDLANSSILTGSGSPNSSASAESRGLLESGKVAAMHNDARSALHNYIQRTHPSQPMRFQTLLGVVQLMHKVSSFTIEELFFRKTIGDITIVRLISDMYSQRKI
Otd
MAAGFLKSGDLGPHPHSYGGPHPHHSVPHGPLPPGMPMPSLGPFGLPHGLEAVGFSQGMWGVNTRKQRRERTTFTRAQLDVLEALFGKTRYPDIFMREEVALKINLPESRVQVWFKNRRAKCRQQLQQQQQSNSLSSSKNASGGGSGNSCSSSSANSRSNSNNNGSSSNNNTQSSGGNNSNKSSQKQGNSQSSQQGGGSSGGNNSNNNSAAAAASAAAAVAAAQSIKTHHSSFLSAAAAAASGGTNQSANNNSNNNNQGNSTPNSSSSGGGGGSQAGGHLSAAAAAAALNVTAAHQNSSPLLPTPATSVSPVSIVCKKEHLSGGYGSSVGGGGGGGGASSGGLNLGVGVGVGVGVGVGVSQDLLRSPYDQLKDAGGDIGAGVHHHHSIYGSAAGSNPRLLQPGGNITPMDSSSSITTPSPPITPMSPQSAAAAAHAAQSAQSAHHSAAHSAAYMSNHDSYNFWHNQYQQYPNNYAQAPSYYSQMEYFSNQNQVNYNMGHSGYTASNFGLSPSPSFTGTVSAQAFSQNSLDYMSPQDKYANMV
Run
MHLPAGPTMVANNTQVLAAAAAAAAAAAAAVAQGPGPQQSSNATTASAIAINPAQSLANTSTHSASSTGSSTPDLSTNNTSSSSNATTSPQNSAKMPSSMTDMFASLHEMLQEYHGELAQTGSPSILCSALPNHWRSNKSLPGAFKVIALDDVPDGTLVSIKCGNDENYCGELRNCTTTMKNQVAKFNDLRFVGRSGRGKSFTLTITIATYPVQIASYSKAIKVTVDGPREPRSKQSYGYPHPGAFNPFMLNPAWLDAAYMTYGYADYFRHQAAAQAAQVHHPALAKSSASSVSPNPNPSVATSSSSAVQPSEYPHPAAAVAAAAGQPAAMMPSPPGAAPATPYAIPQFPFNHVAAAAAAKAATPHAFHPYNFAAAAGLRARNAALHHQSEPVHVSPASSRPSSSSPTQQHVLLKLNTSIETSSIHEQSASDGDSDDEQIDVVKSEFDLDKSLDVAPLRMRCDLKAPSAMKPLYHESGPGAVANSRQPSPETTTKIKSAAVQQKTVWRPY
Kn
TGNTSLSISGHPLAPDSTYDGLYPPLPVATPCIKAISPSEGWTTGGATVIIVGDNFFDGLQVVFGTMLVWSELITSHAIRVQTPPRHIPGVVEVTLSYKSKQFCKGSPGRFVYVSALNEPTIDYGFQRLQKLIPRHPGDPEKLQKEIILKRAADLVEALYSMPRSPGGSTGFNSYAGQLAVSVQDGSGQWTEDDYQRAQSSSVSPRGGYCSSASTPHSSGGSYGATAASAAVAATANGYAPAPNMGTLSSSPGSVFNSTSRVSSLSFNPFALPTCNTQGYSTQLVTSTK
Toy
MRTQRRSADTVDGSGRTSTANNPSGTTASSSVATSNNSTPGIVNSAINVAERTSSALVSNSLPEASNGPTVLGGEANTTHTSSESPPLQPAAPRLPLNSGFNTMYSSIPQPIATMAENYNSSLGSMTPSCLQQRDAYPYMFHDPLSLGSPYVSAHHRNTACNPSAAHQQPPQHGVYTNSSPMPSSNTGVISAGVSVPVQISTQNVSDLTGSNYWPRLQ
Sox102F
MKPPGEDQTNEKEHSDLGMIKQLQLIRNRILSQAHYDSMTDIDASAQQQQQLQNVQRLQHESCLQELHNHLSSQYGAVRFTAANPQHQNQQAVSVSSGNLMPFLPAFLQPPMPNAQQLLQLIPGHENAQSVPTHHHSHPQSEAFSTHKMALAPMWSTAAVAAAHIQAALAAAAVAAANNNKNSSHFSNNTNIVGL
Dll
MDAPDAPHTPKYMDGGNTAASVTPGINIPGKSAFVELQQHAAAGYGGIRSTYQHFGPQGGQDSGFPSPRSALGYPFPPMHQNSYSGYHLGSYAPPCASPPKDDFSISDKCEDSGLRVNGKGKKMRKPRTIYSSLQLQQLNRRFQRTQYLALPERAELAASLGLTQTQVKIWFQNRRSKYKKMMKAAQGPGTNSGMPLGGGGPNPGQHSPNQMHSGELANGRFLWAALETNGTLALVHSTGGNNGGGSNSGSPSHYLPPGHSPTPSSTPVSELSPEFPPTGLSPPTQAPWDQKPHWIDHKPPPQMTPQPPHPAATLHPQTHHHNPPPQMGGYVPQYWYQPETNPSLVT
Oaz
MRTQRRSADTVDGSGRTSTANNPSGTTASSSVATSNNSTPGIVNSAINVAERTSSALVSNSLPEASNGPTVLGGEANTTHTSSESPPLQPAAPRLPLNSGFNTMYSSIPQPIATMAENYNSSLGSMTPSCLQQRDAYPYMFHDPLSLGSPYVSAHHRNTACNPSAAHQQPPQHGVYTNSSPMPSSNTGVISAGVSVPVQISTQNVSDLTGSNYWPRLQ
Ap
MRARNLVFHVNCFCCTVCHTPLTKGDQYGIIDALIYCRTHYSIAREGDTASSSMSATYPYSAQFGSPHNDSSSPHSDPSRSIVPTGIFVPASHVINGLPQPARQKGRPRKRKPKDIEAFTANIDLNTEYVDFGRGSHLSSSSRTKRMRTSFKHHQLRTMKSYFAINHNPDAKDLKQLSQKTGLPKRVLQVWFQNARAKWRRMMMKQDGSGLLEKGEGALDLDSISVHSPTSFILGGPNSTPPLNLD
TfAP-2
CLDKSKIDNEKK
Dpn
HTKLEKADILEMTVKHLQSVQRQQLNMAIQSDPSVVQKFKTGFVECAEEVNRYVSQMDGIDTGVRQRLSAHLNQCANSLEQIGSMSNFSNGYRGGLFPATAVTAAPTPLFPSLPQDLNNNSRTESSAPAIQMGGLQLIPSRLPSGEFALIMPNTGSAAPPPGPFAWPGSAAGVAAGTASAALASIANPTHLNDYTQSFRMSAFSKPVNTSVPANLPENLIHTLPGQTQLPVKNSTSPPLSPISSISSHCEESRAASPTVDVMSKHSFAGVFSTPPPTSAETSFNTSGSLNLSAGSHDSSGCSRPLAHLQQQQVSSTSGIAKRDREAEAESSDCSLDEPSSKKFLAGAIEKSSS
Immunohistochemistry
Wandering third instar larval Drosophila optic lobes were fixed in 4% formaldehyde for 15-20 minutes at room temperature (with the exception of immunostainings using mouse anti-eyeless, rat anti-Oaz and rabbit anti-Opa antibodies, for which fixation was on ice for 30 minutes). After washing, they were incubated for 2 days with primary antibodies at 4 °C. After washing the primary antibody, the brains were incubated with the secondary antibodies overnight at 4 °C. The secondary antibodies were washed, and the brains were mounted in Slowfade and imaged at a confocal microscope (Leica SP8) using a 63x glycerol objective. Images were processed in Fiji and Illustrator.
Origin of all individual antibodies is detailed in Supplementary Table 2.
Statistics and reproducibility
Male and female larvae (stage L3) were selected randomly from the fly vials for all experiments. Blinding across different genotypes was not performed, as the genotype can be distinguished by the experimenter. All immunohistochemistry experiments were performed in at least 3 different biological replicates (brains of different animals) for each genotype, which is sufficient as it is well-established that the structure and composition of the Drosophila brain is very stereotypical. Moreover, all mutant phenotypes were very penetrant. In particular, n = :
Figure 1: (f) 4, (g) 4, (h) 4, (i) 4, (j) 3, (k) 4, (l) 4
Figure 2: (b) 7, (c) 6, (d) 5, (e) 7, (f) 4, (g) 4, (h) 6, (i) 5, (j) 3, (k) 6, (l) 3, (m) 5, (n) 7, (o) 5, (p) 5
Figure 3b: (i) 4, (ii) 7, (iii) 7, (iv) 4, (v) 6, (vi) 24, (vii) 3, (viii) 10, (ix) 3, (x) 4, (xi) 4, (xii) 9, (xiii) 11, (xiv) 6
Figure 4e: 3
Extended Data Figure 3: (c) 5, (d) 2
Extended Data Figure 4: (a) 8, (b) 3, (c) 4, (d) 6, (e) 4, (f) 4, (g) 3, (h) 4, (i) 3
Extended Data Figure 5: (b) 5, (c) 3, (d) 6, (e) 6, (f) 4, (g) 4, (h) 4, (i) 3, (j) 4, (k) 10, (l) 3, (m) 3, (n) 4, (o) 4, (p) 4, (q) 3
Extended Data Figure 6: (b) 6, (c) 7, (d) 7, (e) 4, (f) 4, (g) 4, (h) 4, (i) 4, (j) 6
Extended Data Figure 7: (b) 4, (c) 4, (c’) 4, (d) 6
Extended Data Figure 8a: (i) 4, (ii) 3, (iii) 3, (iv) 6, (v) 4, (vi) 7, (vii) 7, (viii) 4, (ix) 4, (x) 4, (xi) 5, (xii) 3, (xiii) 3, (xiv) 6
Extended Data Figure 8b: (i) 6, (ii) 11, (iii) 11
Extended Data Figure 8c: (i) 5, (ii) 5, (ii’) 3, (ii’’) 3, (ii’’’) 3, (iii) 4, (iii’) 4, (iii’’) 4, (iii’’’) 4, (iii’’’’) 4
Hybridization Chain Reaction-RNA FISH
To perform HCR-RNA FISH, custom probes were designed for BarH1, BarH2, Oaz and dpn coding sequences and sourced from Molecular Instruments. Wash, amplification and hybridization buffers, and fluorophore-labelled amplification hairpins, were obtained from Molecular Instruments. The HCR protocol for Drosophila larval brains used was as specified in: dx.doi.org/10.17504/protocols.io.bzh5p386. Amplification hairpins used were labelled with Alexa Fluor 488, 546, 594 and 647.
Birth order of medulla neurons and temporal window assignment
The current L3-P15 scRNASeq dataset contains some neurons that do not originate from the main OPC neuroepithelium that generates medulla neurons. We removed from the analysis Low Quality (LQ) clusters, clusters containing more than one cell type, glial clusters, clusters with a different origin from the medulla and clusters that were transcriptionally more similar to these than to medulla neurons (see Extended Data Figure 8). Additionally, clusters that express a combination of concentric genes that we do not observe in the medulla cortex by immunostaining were removed, such as 13 (Run+TfAP-2) (Extended Data Figure 8a vii), 114 (Hbn+Ap) (Extended Data Figure 8c ii’’’), and clusters 51 and 169b (Toy+Hbn) (Extended Data Figure 8a xiv). To establish the birth order of all the clusters in the medulla dataset and its predicted temporal window of origin (Figure 3c and Supplementary Table 1), we used the mRNA expression of tTFs in GMCs, and tTFs and concentric genes in medulla neuronal clusters at L3 and P15, together with their relative position in UMAP plot (Extended Data Figure 7a-a’’’’’’ and 3c). To identify medulla clusters expressing a given concentric gene and/or tTF (Supplementary Table 1), we used Mixture Modelling39 at P15 stage from Ozel et al., 202018, and confirmed the results using violin plots for each concentric gene. To define the relative order of concentric gene expression in medulla neurons, we immunostained late L3 brains with these TFs (see Figure 3b) and analyzed the most medial part of the medulla cortex, where neurons are more mature and hence more similar to the P15 dataset. Several criteria were considered to assign a cluster to a given temporal window: tTF expression in GMCs and neuronal clusters, concentric gene expression in neuronal clusters, UMAP position, transcriptional similarity based on hierarchical cluster tree (Extended Data Figure 8) and experimental data from MARCM mutant clones in NB tTFs where a given concentric gene is lost in neurons (Extended Data Figure 7c-d and 22,23,29,40).
Single-cell RNA seq
Drosophila optic lobes sample preparation
The developing central nervous system from male and female flies was dissected from Canton-S wandering third instar larvae in PBS. The optic lobes were separated from the central brain using Vannas Spring Scissors with a 2mm cutting edge (Fine Science Tools Cat no. 15000-04). The optic lobes were dissociated into single cell suspension by incubating in 2mg/mL collagenase and 2mg/mL dispase in PBS for 15 minutes at 25 °C. The enzymes were then carefully removed and replaced with PBS + 0.1% BSA. The brains are soft but remain intact if pipetted slowly. The brains were pipetted up and down many times (> 100) until most large chunks of tissue were dissociated. The cells/tissue were kept cold by putting the tubes on ice. The cells were then filtered using 20 μm cell strainers. The concentration of the cell suspension was then measured staining the cells with 1/2000 Hoechst, using an epifluorescent microscope and a 0.02-mm deep cytometer.
Library preparation and sequencing
Droplet-based purification, amplification and barcoding of single-cell transcriptomes were performed using Chromium Single Cell 3′Reagent Kit v2 (10x Genomics) as described in the manufacturer’s manual (Chromium Single Cell 3′Reagent Kits v2 User Guide – Rev D), with a target recovery of 7,000 cells per experiment. We prepared 10 libraries (biological replicates), which were subjected to paired-end sequencing (26 × 8 × 98) with NovaSeq 6000 (Genome Technology Center at NYU Langone Health) to an average 50,000 reads per cell sequenced (that is, 350,000,000 reads for an experiment with 7,000 cells).
Single-nucleus RNA seq
Human cortical plate sample preparation
Tissue was collected from de-identified prenatal autopsy specimens without neuropathological abnormalities. All autopsies were done with written consent from the legal next-of-kin. The Icahn School of Medicine Institution Review Board considers autopsies as non-human subjects. Utilization of fetal specimens was determined as non-human research by the Icahn School of Medicine Institution Review Board and exemption was provided to Dr. Nadejda Tsankova (HS#: 14-01007). The cortical plate was dissected fresh from the anterior frontal lobe of anatomically intact brain specimens with postmortem time interval less than 24 hours, and immediately fresh-frozen on dry ice.
Isolation and fluorescence-activated nuclear sorting (FANS) with hashing.
All buffers were supplemented with RNAse inhibitors (Takara). 25mg of frozen postmortem human brain tissue was homogenized in cold lysis buffer (0.32M Sucrose, 5 mM CaCl2, 3 mM Magnesium acetate, 0.1 mM EDTA, 10mM Tris-HCl, pH8, 1 mM DTT, 0.1% Triton X-100) and filtered through a 40 μm cell strainer. The flow-through was underlaid with sucrose solution (1.8 M Sucrose, 3 mM Magnesium acetate, 1 mM DTT, 10 mM Tris-HCl, pH8) and centrifuged at 107,000 g for 1 hour at 4 °C. Pellets were re-suspended in PBS supplemented with 0.5% bovine serum albumin (BSA).
Four samples were processed in parallel. 2 million nuclei from each sample were pelleted at 500 g for 5 minutes at 4 °C. Following centrifugation, nuclei were re-suspended in 100 μl staining buffer (2% BSA, 0.02% Tween-20 in PBS) and incubated with 1 μg of a unique TotalSeq-A nuclear hashing antibody (Biolegend) for 30 min at 4 °C. Prior to FANS, volumes were brought up to 250 μl with PBS and DAPI (Thermoscientific) added to a final concentration of 1 μg/ml. DAPI positive nuclei were sorted into tubes pre-coated with 5% BSA using a FACSAria flow cytometer (BD Biosciences).
snRNAseq and library preparation.
Following FANS, nuclei were subjected to 2 washes in 200 μl staining buffer, after which they were re-suspended in 15 μl PBS and quantified (Countess II, Life Technologies). Concentrations were normalized and equal amounts of differentially hash-tagged nuclei were pooled. A total of 40,000 (10,000 each) pooled nuclei were processed using 10x Genomics single cell 3’ v3 reagents. At the cDNA amplification step (step 2.2), 1 μl of 2 μm HTO cDNA PCR “additive” primer was added41. After cDNA amplification, supernatant from 0.6x SPRI selection was retained for HTO library generation. cDNA library was prepared according to 10x Genomics protocol. HTO libraries were prepared as previously described41. cDNA and HTO libraries were sequenced at NYGC using the Novaseq platform (Illumina).
Bioinformatic analyses
Detailed scripts and related R objects can be found here: https://drive.google.com/open?id=12260_PQkmEplL1hNBFbQX9eEpzC4pySy&authuser=nk1845%40nyu.edu&usp=drive_fs
Mapping and integration of larval (L3) and pupal (P15) datasets
We mapped the sequenced libraries to the D. melanogaster genome assembly BDGP6.88 using CellRanger 3.0.1. We kept only genes that were expressed in at least 3 cells across all cells and cells with counts with at least 200 genes for further analysis. After processing, the dataset comprised 49,893 cells passing quality filters, with a median of 3,635 UMIs and 1,343 genes per cell.
We used the procedure implemented in Seurat v.3 to remove batch effects from our sequenced libraries. We used default parameters except for the dimensionality for which we tried the values 100, 150 and 200. We compared the results using the Seurat function LocalStruct with default parameters. The results obtained were 83.7%, 84.9% and 83.6%, respectively. We therefore chose a dimensionality of 150 for the larval dataset.
The dataset was then clustered with a resolution of 2. Notably, in this developing structure, cells are clustered both by identity and by differentiation stage. For example, Mi1 cells fall into 2 clusters, an immature (cluster 23) and a mature cluster (cluster 53).
Larval and pupal datasets were merged using default parameters.150 PCs were used subsequently for generating the UMAP to remain consistent with the integration of the different larval libraries.
Spatial patterning analysis
To focus on the heterogeneity within the neuroepithelial cells, the larval dataset was further subsetted using marker expression with Seurat v3. Expression of neuroepithelial markers shg, tom, and brd were examined for each cluster42. Clusters with average expression higher than 95th percentile of normalized expression of tom and brd were selected as neuroepithelial clusters. DE-Cadherin (Shg) is known to be enriched in neuroepithelial cells43 and is enriched in the selected clusters (logFC = 0.75, adjusted p value = 0).
Principal components were calculated using variable features found in the subsetted neuroepithelial cells. Examination of PC1 revealed that tll, an early marker of lamina precursor cells44, is expressed in a near-mutually exclusive fashion with hth (enriched in neuroepithelium and young medulla neuroblasts), suggesting the subset contained both OPC neuroepithelium and lamina precursor cells. To keep only OPC neuroepithelial cells, we sub-clustered the cells and examined the average expression of hth and tll for each cluster. This process is performed iteratively to keep only hth+/tll− clusters. The remaining cells were assigned as OPC neuroepithelium for further analysis of spatial temporal factors.
Trajectory analysis: identification of candidate tTFs
To study temporal patterning in neuroblasts, we first identified the cluster that corresponded to the medulla neuroblasts (cluster 9) based on the expression of Dpn and Ase, as well as the expression of the known temporal factors. We extracted the counts from these cells and inputted them into Monocle. We used default parameters to order the cells in pseudotime. We used the DDRTree method for dimensionality reduction. The cells were then ordered in pseudotime and the beginning and end of the trajectory were defined based on the expression of the known tTFs (i.e. Hth marked the beginning of the trajectory and Tll marked the end). We then looked at the expression along the pseudotime of 629 genes annotated as transcription factors in FlyBase to identify the candidate tTFs. identified 39 candidate that exhibited temporally restricted expression. These fell into two distinct categories: 14 of them were expressed at relatively high levels and included the 6 known tTFs (Extended Data Figure 3a), while 25 of them were expressed at lower levels along the trajectory (Extended Data Figure 3b). We tested the expression pattern of 4 of the 25 lowly expressed candidates, apterous (ap), cut, gcm, and gemini (gem) in the developing optic lobes. Ap is expressed in neurons22, gem was not expressed in the optic lobe, gcm is expressed in glial cells coming from the Tll temporal window45, and cut was not expressed in a temporal manner (Extended Data Figure 3c-d). We therefore decided not to pursue these candidates further as their fluctuations likely represent noise.
Merging of larval and pupal Mi1 and DE analysis over pseudotime
Larval and pupal (P15, P30, P40, P50, and P70) datasets were merged after cells were batch effect corrected for each stage separately. The standard Monocle workflow was followed to generate trajectories. The L3 and P15 trajectories were ordered manually.
Based on the way the optic lobe develops, there are cells at the same differentiation stage in the L3 and P15 datasets. We therefore decided to align these two datasets in order to get a continuum of expression. We tested different genes and ended up using “Ggamma30A” as a reference gene. Ggamma30A starts increasing in the middle of the L3 trajectory and continues all the way to P15 in a linear manner. We adjusted the expression of Ggamma30A in P15 using linear regression, which was then applied to all genes of P15. This does not change the dynamics of expression, just the relative levels, and serves the purpose of aligning the trajectories over pseudotime of L3 and P15.
To identity differentially expressed genes along the differentiation trajectory from L3 to P70, we used two methods: “principal graph” and “knn”. We selected genes that were identified as differentially expressed with at least one of the two methods. We then used the find_gene_modules function to group the differentially expressed genes into modules of genes that co-vary. These genes were then used for GO analysis.
GO enrichment analysis
We performed GO enrichment analysis and calculated enrichment for ‘Biological Process’ using The Gene Ontology Resource (http://geneontology.org/) using a Fisher's exact test to calculate p-value. Multiple testing correction was performed by calculating the False Discovery Rate.
To find the expression of GO terms over time, we added and normalized the expression of all genes that belong to a specific GO term and plotted it over pseudotime or on the UMAP.
Analysis of human data
We mapped the sequenced libraries to the H. sapiens genome assembly GRCh38 (hg38) using CellRanger 3.1.0. For the hashtag oligos (HTO), we used the CITE-seq-Count 1.4.2 version to align HTO to 10x barcodes using the following command:
CITE-seq-Count -R1 reas1 -R2 read2 -T 1 -t tag -cbf 1 -cbl 16 -umif 17 -umil 26 -cells 40000 -o output --sliding-window # --dense
After processing, the dataset comprised 3,363 cells passing quality filters, with a median of 4,736 UMIs and 2,414 genes per cell.
We selected the radial glia (expressing Pax6), intermediate progenitors (expressing Eomes), and neurons (expressing NeuroD2) that were forming a trajectory in UMAP and imported the data into Monocle and used default parameters to calculate the trajectories. We used the find_gene_modules function to group genes into 6 modules of genes that co-vary. These modules were then used for GO analysis.
Analysis of mouse cortical data
The dataset that was generated by Telley et al.34 was downloaded from GEO (GSE118953). The raw counts were inputted into Seurat and the standard workflow was followed (log-normalization, followed by clustering and UMAP using 25 PCs, and clustering was done with a resolution of 2). The radial glia clusters (clusters 2 and 3) were identified based on the expression of known radial glia markers, such as SOX2 and PAX6. Radial glia from different embryonic days 12, 13, 14, and 15 were used to generate the violin plots of Extended Data Figure 10a.
Analysis of mouse retina data
We downloaded the dataset that was generated by Clark et al.35. We inputted the raw counts into Seurat and the standard workflow was followed (log-normalization, followed by clustering and UMAP using 50 PCs, and clustering was done with a resolution of 0.5). We used the annotation provided by the authors35 to select early and late retinal progenitor cells (RPCs). RPCs from embryonic days 11, 12, 14, 16, and 18 and postnatal day 0 were used to generate the violin plots of Extended Data Figure 10c-d.
Extended Data
Supplementary Material
Acknowledgements
We are indebted to the fly community; Cheng-Yu Lee, Deborah Hursh, John Nambu, Andrew Tomlinson, and Mitshuhiko Kurusu for fly lines, Peter Gergen, Kwangwook Choi, Hermann Aberle, Dorothea Godt, James Skeath, Richard Mann, and Tiffany Cook for antibodies. We thank members of the Desplan lab, and Stein Aerts for constructive feedback on the manuscript, as well as Rosa Mirayes, Tzumin Lee, and three anonymous reviewers for a fruitful reviewing process. Finally, we thank Sergio Córdoba for the optic lobe illustrations and Kazi Hossain and Albert Tadros for help with preliminary experiments. This work was supported by NIH grant EY019716 and EY10312 to C.D. N.K. was supported by the National Eye Institute (K99 EY029356-01). I.H. was supported by an HFSP postdoctoral fellowship (LT000757/2017-L) and by the Kimmel Center for Stem Cell Biology Senior Postdoctoral Fellowship. A.M.R was supported by funding from NIH (T32 HD007520), and by NYU’s Dean’s Dissertation Fellowship. A.M.J. was supported by the NYU SURP program. M.N.O is a Leon Levy Neuroscience Fellow.
Footnotes
Declaration of Interests
Authors declare no conflicts of interest.
Code availability
All related code that was used in this manuscript can be found on Github: https://github.com/NikosKonst/larva_scSeq2022
Data Availability
All Drosophila raw and processed data referenced were uploaded to GEO: accession number GSE167266.
The human source data described in this manuscript are available via the PsychENCODE Knowledge Portal (https://psychencode.synapse.org/). The PsychENCODE Knowledge Portal is a platform for accessing data, analyses, and tools generated through grants funded by the National Institute of Mental Health (NIMH) PsychENCODE program. Data is available for general research use according to the following requirements for data access and data attribution: (https://psychencode.synapse.org/DataAccess). For access to content described in this manuscript see: www.doi.org/10.7303/syn24975927
The publicly available single-cell sequencing datasets that were used can be found in GEO: accession numbers GSE142787 (Drosophila pupal development), GSE118953 (mouse cortical radial glia), and GSE118614 (mouse retinal progenitors).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All Drosophila raw and processed data referenced were uploaded to GEO: accession number GSE167266.
The human source data described in this manuscript are available via the PsychENCODE Knowledge Portal (https://psychencode.synapse.org/). The PsychENCODE Knowledge Portal is a platform for accessing data, analyses, and tools generated through grants funded by the National Institute of Mental Health (NIMH) PsychENCODE program. Data is available for general research use according to the following requirements for data access and data attribution: (https://psychencode.synapse.org/DataAccess). For access to content described in this manuscript see: www.doi.org/10.7303/syn24975927
The publicly available single-cell sequencing datasets that were used can be found in GEO: accession numbers GSE142787 (Drosophila pupal development), GSE118953 (mouse cortical radial glia), and GSE118614 (mouse retinal progenitors).