Neuroblast-specific open chromatin allows the temporal transcription factor, Hunchback, to bind neuroblast-specific loci
The generation of neuronal diversity in mammals and Drosophila is a multi-step process . The initial step is the production of the neuroectoderm ( ventral in Drosophila , dorsal in mammals ) that gives rise to neural progenitors . In both systems , the neuroectoderm and neural progenitor population acquire regional differences due to the action of Hox genes and spatial patterning genes ( Jessell , 2000 ) . Although spatial patterning generates diversity within the neural progenitor population , it is insufficient to account for the neuronal diversity in the mature nervous system . Expanding neural diversity requires a second step called temporal patterning , where individual neural progenitors produce a sequence of distinct neurons and glia ( Doe , 2017 ) . In both Drosophila and mammals , this process appears to be regulated , in part , by temporal transcription factors ( TTFs ) that are sequentially expressed within individual neural progenitors ( Kohwi and Doe , 2013 ) . Although a great deal is known about how spatial factors generate regional diversity , and much has recently been learned about temporal patterning mechanisms , virtually nothing is known about how spatial factors and TTFs are integrated to specify distinct neuronal identities in spatially distinct progenitor populations . Drosophila is an excellent model system to investigate how spatial and temporal factors are integrated during neurogenesis , due to a deep understanding of neural progenitor ( neuroblast ) lineages , and the molecular mechanisms involved in both spatial and temporal patterning during neurogenesis . The Drosophila neuroectoderm produces a bilateral array of 30 neuroblasts in each segment , named according to their row and columnar position within the two dimensional neuroblast array ( Figure 1A , left ) . Each neuroblast has a unique identity based on its distinct molecular profile and each neuroblast produces a unique and stereotyped family of neurons . Spatial patterning factors that specify neuroblast identity have been characterized , and all of them are transcription factors or signalling pathways with transcription factor effectors . Henceforth we refer to these spatial factors as ‘spatial transcription factors’ or STFs , paralleling the naming of temporal transcription factors as TTFs . The Gooseberry ( Gsb ) Pax-3 family transcription factor is expressed in row 5 neuroblasts; loss of Gsb transforms row 5 neuroblasts into row 3/4 identity , and misexpression of Gsb transforms row 3/4 neuroblasts into row 5 identity . Importantly , transient misexpression of Gsb in the neuroectoderm , prior to neuroblast formation , is sufficient to generate ectopic row 5 neuroblasts , suggesting that neuroblast identity is determined in the neuroectoderm and maintained during the subsequent neuroblast lineage ( Skeath et al . , 1995; Bhat , 1996 ) . Thus , Gsb is one of the best characterized STFs . Similarly , the secreted Wingless ( Wg ) protein is produced by row 5 neuroectoderm , where it is required to specify the adjacent row 4 and 6 neuroblast identity that is maintained in the row 4 and 6 neuroblasts ( Chu-LaGraff and Doe , 1993 ) . Precise inactivation of a temperature-sensitive Wg protein showed that loss of Wg activity in the neuroectoderm resulted in loss of neuroblast identity , whereas inactivation of Wg after neuroblast formation had no effect , showing that transient Wg generates row 4 and 6 neuroblast identity ( Chu-LaGraff and Doe , 1993 ) . In addition , Hedgehog ( Hh ) expression in row 6/7 neuroectoderm is required to specify neuroblast identity in adjacent rows 1/2 ( McDonald and Doe , 1997 ) . Finally , Engrailed expression in the neuroectoderm is required for the proper development of row 6/7 neuroblasts , and transient Engrailed misexpression generates ectopic row 7 neuroblast identity ( Deshpande et al . , 2001 ) . Taken together , these spatial patterning experiments show that neuroblast spatial identity is specified in the neuroectoderm by the transient action of STFs expressed in different neuroblast rows . Spatial patterning does not only generate distinct rows of neuroblasts , but also distinct neuroblast columns . During the first stages of neuroblast formation there are three distinct columns of neuroblasts , each specified by a conserved homeodomain protein . Vnd is expressed in a medial column of neuroectoderm , Ind is expressed in an intermediate column , and Msh ( Flybase: Drop ) is expressed in the lateral column ( Figure 1A , left ) ( Isshiki et al . , 1997; McDonald et al . , 1998; Weiss et al . , 1998 ) . Loss of function and misexpression studies show that each is necessary and partially sufficient for specifying columnar neuroblast identity ( Isshiki et al . , 1997; McDonald et al . , 1998; Weiss et al . , 1998 ) . It is likely that these columnar factors function in the neuroectoderm , like spatial row factors , because they do not persist throughout neuroblast lineages . All three of these STFs have conserved mammalian orthologs with similar medial-lateral expression in the neuroectoderm ( Weiss et al . , 1998 ) . Overall , the combination of row and columnar STFs are likely to generate the observed 30 distinct neuroblast identities . Hox factors provide an additional spatial cue that distinguishes segmental differences in neuroblast identity ( Prokop and Technau , 1994 ) . Whereas spatial patterning generates 30 different neuroblast identities , temporal patterning is required to generate different progeny within each neuroblast lineage . Most neuroblasts sequentially express a series of four TTFs as they divide to generate ganglion mother cell ( GMC ) progeny , and the specific TTF inherited by each GMC determines its identity ( Kohwi and Doe , 2013; Li et al . , 2013; Doe , 2017 ) . Embryonic ventral nerve cord ( VNC ) neuroblasts undergo a TTF cascade that progresses from Hunchback ( Hb; Ikaros zinc finger family ) to Krüppel ( zinc finger family ) to the redundant Nubbin/Pdm2 ( Pdm ) to Castor ( Cas; Casz1 zinc finger family ) ( Figure 1A , middle ) . Other neuroblasts in the larval VNC , brain , and optic lobes undergo a similar TTF cascade to increase neuronal diversity , although the identity of the TTFs differs in each region ( Li et al . , 2013; Doe , 2017 ) . The Hb-Kr-Pdm-Cas TTF cascade has been particularly well-characterized , with each factor being necessary and sufficient to specify the neuronal identity produced during its window of expression ( Isshiki et al . , 2001; Novotny et al . , 2002; Kanai et al . , 2005; Grosskortenhaus et al . , 2006; Tran and Doe , 2008; Kohwi et al . , 2013 ) . Importantly , each TTF specifies a different type of neuron in each neuroblast lineage , showing that spatial identity provides a different context for Hb function in each neuroblast ( Figure 1A , right ) . Understanding this ‘context’ at a mechanistic level is the goal of our experiments below . The role of TTFs is best exemplified by Hb , the first TTF in the cascade . Loss of Hb results in absence of the first-born neuron identities in all neuroblast lineages assayed to date ( 1-1 , 3-1 , 3-5 , 7-1 , 7-3 ) . Conversely , driving prolonged Hb expression in neuroblasts results in ectopic first-born neurons in all lineages tested ( Isshiki et al . , 2001; Novotny et al . , 2002; Kanai et al . , 2005; Kohwi et al . , 2013 ) . For example , prolonged expression of Hb in NB7-1 produces ectopic U1 motor neurons , whereas prolonged expression of Hb in NB7-3 produces ectopic EW1 serotonergic interneurons . Note that these misexpression experiments further confirm the neuroblast-specific effect of Hb , showing that the spatial identity of the neuroblast determines the effect of Hb . Importantly , Hb can induce early-born neuronal identity throughout a ‘competence window’ of ~5 neuroblast divisions ( from embryonic stage 9–12 ) . The length of the competence window is defined by expression of Distal antenna ( Dan ) , a nuclear Pipsqueak domain protein present in all neuroblast nuclei until stage 12 ( about five divisions for most neuroblasts ) ; Dan is downregulated in all neuroblasts at the end of stage 12 , and this closes the Hb competence window ( Kohwi et al . , 2013 ) . Hb can induce first-born neuronal identity at any point during this competence window , showing that Hb binding sites are accessible throughout the competence window; this is important to consider for the experiments described here , where we have restricted our Hb binding and chromatin accessibility profiling experiments to the stage 9–12 competence window in individual neuroblast lineages ( see below ) . It is clear that spatial and temporal cues are integrated to generate lineage-specific neuronal diversity , both in Drosophila embryonic neuroblasts and optic lobe neuroblasts ( Erclik et al . , 2017 ) , and likely in mammalian progenitor lineages . Yet in no case , mammals or Drosophila , is it known how spatial and TTFs are integrated . Here we hypothesise two mechanisms by which this integration could occur . ( 1 ) Independent specification ( Figure 1B ) . In this scenario , spatial and temporal transcription factors bind their genomic targets independently , and the combinatorial actions of these factors and their downstream gene regulatory networks results in unique gene expression and therefore unique neural identities . ( 2 ) Sequential specification ( Figure 1C ) . In this scenario , early expression of STFs in the neuroectoderm ( where they are known to act ) biases the subsequent DNA-binding profile of the later expressed TTFs . This could happen via STFs generating different chromatin landscapes in each neuroblast , or via STFs promoting the persistent expression of TTF cofactors that result in neuroblast-specific TTF DNA-binding . While both scenarios would result in the specification of distinct neural identities in spatially distinct NBs , in the independent specification model , TTF binding will be identical in all neuroblasts whereas in the sequential specification model , TTF binding will occur at different loci in each neuroblast . To discriminate between these models , we sought to determine Hb genomic targets in NB5-6 versus NB7-4 . If independent specification is used , we expect to find similar Hb occupancy in each neuroblast ( Figure 1B ) , whereas if sequential specification is used , we expect to find different Hb genomic binding in each neuroblast ( Figure 1C ) . Our goal was to identify Hb occupancy within the early NB5-6 and NB7-4 lineages during the Hb competence window , when Hb retains the ability to generate ectopic early-born neuronal identities , and thus presumably can still bind its normal genomic targets . To identify Hb occupancy in these two neuroblast lineages , we adapted the previously described Targeted DamID ( TaDa ) method ( Southall et al . , 2013; Marshall et al . , 2016 ) . TaDa relies on an attenuated expression of the DNA adenosine methyltransferase ( Dam ) enzyme ( Figure 1D ) , which binds genomic DNA and methylates adenosine at GATC sites . This covalent DNA mark can be used to determine Dam binding sites , due to the very low level of endogenous DNA methylation in Drosophila . Expression of Dam alone can be used to detect open chromatin ( Aughey et al . , 2018 ) ( Figure 1E ) or Dam can be fused to a transcription factor such as Hb , which provides a read-out of Hb genomic occupancy ( Figure 1F ) . Here we characterize two Gal4 lines that are specific for NB5-6 and NB7-4 lineages in the embryo . We use these lines to obtain NB-specific expression of Dam:Hb ( to identify Hb genomic occupancy ) and Dam alone ( to detect open chromatin ) . We demonstrate that Hb has differential targets in NB5-6 and NB7-4 lineages , which correspond to differentially open chromatin in each lineage . Importantly , our observation that Hb-bound loci specific to NB5-6 have open chromatin , but the same loci in NB7-4 have closed chromatin , shows that Hb is not sufficient to create open chromatin . Rather , Hb binding in each neuroblast is likely restricted to a subset of neuroblast-specific open chromatin domains . In support of this model , the Gsb STF , required to specify NB5-6 but not NB7-4 , shows enriched occupancy at open chromatin and Hb enriched loci in NB5-6 , but not in NB7-4 , consistent with a role for Gsb in generating neuroblast-specific open chromatin organization . Our findings support a sequential specification model in which STFs create neuroblast-specific chromatin organization , leading to neuroblast-specific Hb DNA-binding .
Here we characterize two Gal4 lines that label either the NB5-6 or the NB7-4 lineages , which is a prerequisite for profiling neuroblast-specific Hb binding sites . NB5-6 forms in the Gsb domain , whereas NB7-4 forms in the Engrailed domain ( Figure 2A ) . To label NB5-6 and its lineage we used ladybird early ( lbe ) -Gal4 , which is reported to specifically label NB5-6 and its progeny ( Urbach and Technau , 2003; Baumgardt et al . , 2009 ) . We confirmed that lbe-Gal4 expression was highly specific to the NB5-6 and its lineage from stage 10 through stage 12 , the time frame of our experiments ( Figure 2B–D’; Figure 2—figure supplement 1A ) , although by stage 17 it has expression in the non-neuronal salivary gland ( Figure 2—figure supplement 1A ) . Henceforth we call this line ‘NB5-6-Gal4 . ’ To label NB7-4 and its lineage , we used the previously described R19B03AD R18F07DBD split-Gal4 line ( Lacin and Truman , 2016 ) . We confirmed that this line labels NB7-4 and its lineage from stage 10 until the end of stage 17 ( Figure 2E–G’; Figure 2—figure supplement 1B ) ; the only off-target expression is in the adjacent NB5-6 lineage in 6% of hemisegments ( n = 1176 ) . Henceforth we call this line ‘NB7-4-Gal4 . ’ Both NB5-6-Gal4 and NB7-4-Gal4 lines are first expressed after Hb expression in the NB , but during the ‘Hb competence window’ defined by the presence of Distal antenna ( Dan ) nuclear protein in stage 9–12 neuroblasts ( Figure 2C’ and F’ ) ( Kohwi et al . , 2013 ) . Importantly , ectopic Hb can induce early-born neuronal identity throughout the Hb competence window , and thus the relevant Hb DNA-binding sites are still accessible . We conclude that NB5-6-Gal4 and NB7-4-Gal4 lines are each expressed in a single neuroblast and its progeny during the Hb competence window and thus are ideal tools for expressing Dam or Dam:Hb in specific neuroblast lineages . We next identified the early-born Hb+ progeny from both lineages , to ensure that each neuroblast lineage makes different Hb+ progeny . DiI clonal analyses show that both NB5-6 and NB7-4 make distinct populations of interneurons , but also similar populations of subperineurial glia , and their birth-order in the lineage has not been determined ( Schmidt et al . , 1997; Schmid et al . , 1999 ) . Therefore , we used NB5-6-Gal4 to generate MultiColorFlipOut ( MCFO; Nern et al . , 2015 ) single neuron labelling among NB5-6 progeny . We repeatedly ( n = 31 ) identified a Hb+ neuron that had a characteristic ipsilateral ascending projection , which we name the Chaise Lounge neuron due to its distinctive morphology; two segmentally repeated Chaise Lounge neurons are shown in Figure 2H; inset shows a Chaise Lounge neuron expressing Hb . We searched the EM reconstruction ( Ohyama et al . , 2015 ) and identified an identical Chaise Lounge neuron ( Figure 2I ) . Thus , NB5-6 makes a distinctive ipsilateral neuron during its Hb expression window . Similarly , we used NB7-4-Gal4 to generate MCFO single cell labelling , but could not directly identify a Hb+ neuron either due to loss of Hb from early-born neurons prior to neuronal differentiation , or due to lack of Gal4 expression in these neurons . Instead , we used multiple criteria to identify a putative early-born neuron , the G neuron , using MARCM clones ( Figure 2J ) , and EM reconstruction ( Figure 2K ) . Our criteria for assigning this neuron as early-born include ( i ) presence of the neuron in full NB7-4 clones ( Figure 2J ) but not in the NB7-4-Gal4 pattern ( Figure 2—figure supplement 1 ) , which misses early-born neurons; ( ii ) cell body position next to the neuropil , where most Hb+ neurons are located ( Kambadur et al . , 1998 ) ; and ( iii ) close morphological match to the grasshopper G neuron , an early-born neuron from NB7-4 , including ascending and descending projections in the most lateral connective tract ( Raper et al . , 1983 ) . Finally , we note that all NB7-4 neuronal progeny have contralateral axons ( Schmidt et al . , 1997; Schmid et al . , 1999 ) , whereas the NB5-6 early-born Chaise Lounge neuron has ipsilateral projections . Thus , we conclude that NB5-6 and NB7-4 produce different neurons during the Hb expression window . This makes NB5-6 and NB7-4 an appropriate model system to characterize how different spatial patterning cues produce distinct Hb+ early born cell types . The first step in using the TaDa method to map Hb occupancy in the NB5-6 and NB7-4 lineages is to generate a functional , non-toxic Dam:Hb fusion protein . Although other Dam constructs have been shown to be non-toxic ( Southall et al . , 2013; Marshall et al . , 2016; Aughey et al . , 2018 ) , this is the first use of Dam:Hb and its toxicity is unknown . We used standard methods to generate a UAS-LT3-Dam:hb transgene where the first open reading frame ( ORF ) encodes Cherry and the second ORF encodes Dam:Hb ( see Figure 1D , F ) ; placing the Dam fusion protein in the second ORF is important to keep both Dam and Hb levels extremely low , which reduces toxicity and increases specificity of DNA binding ( Southall et al . , 2013 ) . To determine if Dam:Hb is toxic , we expressed the fusion protein throughout the nervous system ( sca-Gal4 UAS-Dam:Hb ) and ubiquitously ( Da-Gal4 UAS-Dam:Hb ) , and observed no effect on embryonic viability ( Figure 3A ) . To determine whether the Hb portion of the Dam:Hb fusion protein was functional , we assayed for its ability to generate ectopic Eve+ U neurons , despite being expressed at very low levels . In wild type , NB7-1 generates five Eve+ U neurons , including the Hb+ early born U1 and U2 neurons , and extending neuroblast expression of Hb produces many ectopic Eve+ U1/U2 neurons ( Isshiki et al . , 2001; Pearson and Doe , 2003 ) . We observed that expression of Dam:Hb was capable of inducing a small number of ectopic Eve+ neurons ( Figure 3B ) , despite the low levels of Dam:Hb , showing that Dam:Hb is functional . We conclude that Dam:Hb is non-toxic in embryos , and that it is functional for inducing early-born neuronal identity . The fact that Dam:Hb can induce early-born neuronal identity suggests that it can bind the same genomic targets as Hb , but we wanted to determine this important point experimentally . The TaDa method involves comparing Dam genomic binding to Dam:Hb genomic binding , with a normalised ratio used to identify sites preferentially bound by the Dam:Hb fusion protein ( Southall et al . , 2013; Marshall and Brand , 2015 ) . We expressed Dam or Dam:Hb in all cells throughout embryogenesis , measured the quantile normalised ratio between them to identify Dam:Hb binding sites ( see Materials and methods ) , and performed three biological replicates at embryonic stage 17 . We found that the biological replicates showed high Pearson correlation coefficients ( Figure 3C , left ) , and were qualitatively very similar along the entire fourth chromosome ( Figure 3C , right ) . Most importantly , we compared Dam:Hb genomic occupancy with published Hb genomic occupancy determined by chromatin immunoprecipitation ( ChIP ) ( Li et al . , 2008; Bradley et al . , 2010 ) . A comparison over 700 kb of genomic DNA on chromosome 3R showed qualitatively similar Dam:Hb and Hb ChIP binding profiles ( Figure 3D ) . Indeed , enriched Dam:Hb binding was detected at eight of the nine known Hb target genes ( Lyne et al . , 2007 ) ( Figure 3E , Figure 3—figure supplement 1 ) . We next compared the similarities in Hb occupancy as reported by these two techniques at the genomic level . To do this , we ran the MACS2 peak caller ( Zhang et al . , 2008 ) on the two datasets and identified 6597 and 6656 regions significantly enriched for Dam:Hb and Hb ChIP respectively ( see Materials and methods ) . We found that 1972 regions were shared between the two ( 29 . 89% of ChIP peaks and 29 . 62% of Dam:Hb peaks ) . When broad peaks were used for this analysis , 2394 regions were shared between the two , or 33 . 74% of ChIP peaks and 45 . 13% of Dam:Hb peaks; and when the narrow peaks were extended to 2 kb on either side of the peak summit , 2207 regions were shared between the two , or 57 . 53% of ChIP peaks and 60 . 37% of Dam:Hb peaks . A Monte Carlo analysis on the narrow peak overlap showed this was highly significant , detecting only 6 . 16% overlap with a set of random peaks ( 100 iterations , p-value < 1 e−300 , see Materials and methods ) . Correspondingly , we found high ChIP signals at the Dam:Hb binding sites and vice versa ( Figure 3F , G , Figure 3—figure supplement 2 ) . Importantly , this overlap in occupancy was not seen when the Dam:Hb data were compared with the ChIP-seq data of any other transcription factor , such as Ftz or Bcd ( Figure 3G ) , demonstrating the specificity of the method . Additional support for the accuracy of Dam:Hb binding is that the known Hb DNA-binding motif is the most enriched motif at Dam:Hb binding sites ( Figure 3—figure supplement 3 ) . Taken together , these results show that Dam:Hb binding closely mimics endogenous Hb binding . At this point we have validated two neuroblast-specific Gal4 lines , as well as shown that Dam:Hb genomic binding is both reproducible and matches published Hb ChIP data in stage nine whole embryos . However , to test the two models of spatial and temporal integration we had to use Dam:Hb in the NB5-6 or NB7-4 lineages – much smaller pools of cells – to determine whether Hb genomic targets were the same or different in these spatially distinct NB lineages . Therefore , our next step was to determine if we could get reproducible Dam:Hb binding data from this small pool of cells , and with shorter Dam:Hb exposure than previously reported ( Southall et al . , 2013; Erclik et al . , 2017; Widmer et al . , 2018 ) . For this purpose , we modified the published protocol to allow processing of more starting material ( see Materials and methods ) . We expressed Dam:Hb in a single neuroblast lineage in each hemisegment ( about 200 cells in the ~50 , 000 cell embryo ) and for five hours ( from embryonic stage 9–12 ) . Previous experiments had expressed Dam constructs in a higher fraction of cells and for ≥12 hr ( Southall et al . , 2013; Cheetham et al . , 2018; Widmer et al . , 2018 ) . We expressed Dam:Hb using each of two neuroblast-specific Gal4 lines ( NB5-6-Gal4 and NB7-4-Gal4 ) and purified DNA from stage 12 embryos , near the end of the Hb competence window ( see Materials and methods ) . We performed three biological replicates for each neuroblast and observed excellent reproducibility across all replicates ( Figure 4A ) . We conclude that we can get a reproducible Dam:Hb signal from a single neuroblast lineage during the Hb competence window . Next , we wanted to determine whether Dam:Hb binds the same or different loci in the two different neuroblasts . The high correlation between biological replicates for each neuroblast , plus the lack of correlation between the two neuroblasts , provided a gross indication that Dam:Hb has unique binding sites in each neuroblast lineage ( Figure 4A ) . We expected the number of differentially bound loci to be relatively small , because most genes are not predicted to regulate NB5-6/NB7-4 differences , and indeed , comparing Hb binding along the entire fourth chromosome shows qualitative similarities between the two NB lineages ( Figure 4B ) . This is also evident at genes known to be expressed in and regulated by Hb across many neuroblast lineages – for example Kr , pdm2 and zfh2 ( Isshiki et al . , 2001 ) ( Figure 4—figure supplement 1 ) . These similarities confirm the reproducibility of Dam:Hb binding in two distinct neuroblast lineages . To begin our analysis of differential Dam:Hb binding between NB5-6 lineage and NB7-4 lineages , we first ran the MACS2 peak caller ( Zhang et al . , 2008 ) on the six datasets – three replicates of NB5-6 lineage and three replicates of NB7-4 lineage – to identify regions significantly bound by Hb in each sample . The rest of our analyses focussed on the significantly bound Hb loci in the two NB lineages . We used the R Bioconductor package DiffBind ( Ross-Innes et al . , 2012 ) to identify 4224 differentially bound loci in the two NB lineages: 2007 that were enriched for Dam:Hb binding in the NB5-6 lineage , and 2217 that were enriched for Dam:Hb binding in the NB7-4 lineage ( Figure 4C; Supplementary file 1 ) . In addition , there were 2860 loci occupied by Dam:Hb in both neuroblast lineages ( Supplementary file 1 ) . Importantly , while the read densities at individual loci are similar between replicates , they are strikingly different between the two neuroblast lineages . Next we represented the differentially bound loci using a volcano plot , where the magenta dots highlight the most significantly differential loci with more than 2-fold change and an FDR of ≤0 . 01 ( Figure 4D ) . This threshold corresponds to 718 Hb enriched loci in NB5-6 lineage and 504 Hb enriched loci in NB7-4 lineage ( Supplementary file 1 ) , which is what we use for all subsequent analyses . The genes closest to the top five differentially occupied loci in each neuroblast are marked in this plot , and shown in Figure 4E , F . Based on these results , we conclude that Dam:Hb binds different loci in different neuroblasts . This clearly rules out the independent specification model where Hb has identical binding sites in different neuroblasts . We next wanted to understand how STFs might influence TTF genomic binding . Given the order of their action – STFs acting early in the neuroectoderm , and TTFs acting later in the delaminated NB – one possibility is that STFs generate different open/closed chromatin landscapes in each neuroblast such that TTFs have access to different loci in each neuroblast . This would predict that spatially distinct NBs would have different open/closed chromatin landscapes . To determine if this were indeed true , we performed chromatin accessibility profiling by Dam only ( CaTaDa ) , which exploits the ability of the Dam protein to bind open chromatin domains ( Aughey et al . , 2018 ) . We first expressed Dam in all cells throughout embryogenesis using Da-Gal4 and observed excellent reproducibility between biological replicates both qualitatively and quantitatively ( Figure 5A , red tracks in C ) . We next wanted to confirm that Dam only binding in the embryo correlates with open chromatin domains , as has been shown in other cell types ( Aughey et al . , 2018 ) . To do this , we analysed the Dam only signal around the DNase I hypersensitive sites ( peaks ) made available by the BDTNP consortium ( Thomas et al . , 2011 ) and found enriched Dam signals around the DNaseI peaks , as well as qualitative similarities between the two ( Figure 5B , compare red and ochre tracks in C ) . We observed 6 , 708 Dam only peaks were aligned with DNase I hypersensitive peaks ( 44 . 6% of all Dam only peaks; 33 . 9% of all DNaseI peaks ) . A Monte Carlo analysis showed this was highly significant , detecting only 18 . 14% overlap with a set of random peaks ( 100 iterations , p-value < 1 e−300 , see Materials and methods ) . These data suggest that Dam only can be used to detect open chromatin in embryos . We next sought to determine whether Dam only could be used to assay open chromatin in small pools of cells over a short period of time – for example in NB5-6 and NB7-4 lineages at stage 12 . We performed three biological replicates of Dam only for each neuroblast , and observed excellent reproducibility in all but one replicate , so we used the two best replicates henceforth ( Figure 5D ) . The reproducibility of the method can also be observed in the similar Dam binding patterns seen at representative control genes that are equally expressed in NB5-6 and NB7-4 lineages ( e . g . Kr , pdm2 and zfh2 ) , or along a large stretch of chromosome 4 ( Figure 5—figure supplement 1 ) . Next , we investigated whether there were global differences in chromatin states between the two neuroblast lineages . To do this , we first determined regions of significantly open chromatin in the two neuroblast lineages by running the MACS2 peak caller ( Zhang et al . , 2008 ) on the four best replicates , which gave us a ‘peakset’ of significantly open chromatin in NB5-6 and NB7-4 lineages . We used these regions of open chromatin in both NB5-6 and NB7-4 lineages to conduct a differential analysis using the DiffBind package ( Ross-Innes et al . , 2012 ) and identified a total of 8 , 740 Dam only differentially bound loci , including 3656 loci in the NB5-6 lineage and 5084 loci in the NB7-4 lineage . These regions of differential chromatin accessibility have been represented as an ‘MA plot’ with the NB5-6 differential open chromatin loci at the top and the NB7-4 differential open chromatin loci at the bottom ( Figure 5E ) . We conclude that there are global differences in the open chromatin landscape between the NB5-6 and NB7-4 lineages . Chromatin accessibility has been shown to be the strongest determinant of TF occupancy on the genome ( Li et al . , 2008; Kaplan et al . , 2011; Guertin et al . , 2012 ) . We wanted to determine if Dam:Hb binding was similarly responsive to the state of the chromatin in the NB5-6 and NB7-4 lineages . To do this , we took all Dam:Hb-bound loci – both those specific for each neuroblast as well as those shared by both neuroblasts – and queried the state of the chromatin at these loci in each NB lineage . We found that Dam:Hb-bound loci in the NB5-6 lineage were enriched for open chromatin in that lineage ( Figure 6—figure supplement 1A ) , and similarly , Dam:Hb-bound loci in the NB7-4 lineage were enriched for open chromatin in that lineage ( Figure 6—figure supplement 1B ) . This suggests that Dam:Hb binding is indeed correlated with chromatin accessibility domains in both NB lineages ( Figure 6—figure supplement 1C ) . If Dam:Hb preferentially occupies regions of open chromatin , we reasoned that the differentially occupied Dam:Hb loci in each NB lineage ( lineage-specific Hb loci ) must be correlated with differentially open chromatin in that neuroblast lineage ( lineage-specific open chromatin ) . Indeed , NB5-6-specific Dam:Hb bound loci showed a strong enrichment for open chromatin ( Figure 6A , blue lines ) ; strikingly , these same loci had closed chromatin in NB7-4 ( Figure 6A , green lines ) . Similarly , NB7-4-specific Dam:Hb bound loci showed strong enrichment for open chromatin ( Figure 6B , green lines ) , while these same loci had closed chromatin in NB5-6 lineage ( Figure 6B , blue lines ) . Corresponding to this , we found 364 peaks , or 50 . 76% of the differential Dam:Hb peaks in NB5-6 overlapped with differentially open chromatin peaks in that lineage; and 164 peaks or 32 . 74% of the differential Dam:Hb peaks in NB7-4 overlapped with differentially open chromatin peaks in that lineage . A Monte Carlo analysis showed these overlaps to be highly significant , detecting 5 . 23% overlap with a set of random peaks in NB5-6% and 6 . 75% in NB 7–4 ( 100 iterations , p-value < 1 e−300 for NB 5–6 and 8 . 9 e−133 for NB 7–4 , see Materials and methods ) . As a control , we assayed loci bound by Dam:Hb in both neuroblast lineages and found that there was no difference between lineages in open chromatin at these sites ( Figure 6C ) . We confirmed these findings at the top five differentially bound Dam:Hb loci in the two neuroblast lineages . All but two of these differentially bound loci were also identified in the differential chromatin analysis; even the two that were not picked up in the analysis ( sqz and mspo ) were qualitatively different between the two neuroblast lineages ( Figure 6D , E ) . We conclude that neuroblast-specific Dam:Hb binding occurs within neuroblast-specific accessible chromatin domains . This correlation suggests that either Hb binds where chromatin is open , or that Hb binding opens chromatin . The latter model seems unlikely , because both NB5-6 and NB7-4 are exposed to Hb expression , yet each neuroblast has specific open chromatin domains ( see Discussion ) . We favor a model in which STFs generate neuroblast-specific open chromatin domains , leading to neuroblast-specific Hb occupancy . If spatial factors generate lineage-specific chromatin landscapes as the sequential specification model proposes , then it’s likely that lineage-specific STF occupancy will correspond to lineage specific chromatin accessibility . Gsb is one of the best studied STFs in the embryonic VNC . It has been shown to be both necessary and sufficient to determine the identity of the row 5 NBs ( Skeath et al . , 1995; Bhat , 1996 ) . Not only is Gsb a functionally validated STF , but Gsb ChIP-chip data from 0 to 12 hr embryos are publicly available ( Bonneaud et al . , 2017 ) . As NB5-6 is a row 5 NB lineage specified by Gsb , it gave us the opportunity to test the sequential specification model more deeply . We asked whether Gsb occupancy was enriched at regions of accessible chromatin in the NB5-6 lineage . We plotted the Gsb ChIP-chip signal around all NB5-6 open chromatin loci and compared this with Gsb ChIP-chip signal around NB7-4 open chromatin loci . Indeed , we found an enrichment of Gsb signal specifically around NB5-6 open chromatin and not NB7-4 open chromatin ( Figure 7A ) . A Monte Carlo analysis found this enrichment to be highly significant ( average real NB5−6/NB7-4 fold change = 2 . 198 , average simulated NB5−6/NB7-4 fold change = 0 . 922 , 100 random iterations , p-value = 1 . 19119 e−62 ) . This supports the hypothesis that lineage-specific STFs generate lineage-specific chromatin landscapes . Finally , we reasoned that if Hb preferentially binds to regions of accessible chromatin , and STF occupancy correlates with open chromatin in a lineage-specific manner , then the lineage-specific Hb occupancy that we observe in NB5-6 should correlate with lineage specific STF occupancy . We therefore plotted Gsb signal around NB5-6-enriched Hb loci and found a corresponding enrichment of Gsb occupancy at these regions ( Figure 7B , blue line ) . In contrast , the NB7-4-enriched Hb loci did not show any such enrichment ( Figure 7B , green line ) . A Monte Carlo analysis found this enrichment to be highly significant ( average real NB5-6/NB7-4 fold change = 2 . 2 , average simulated NB5-6/NB7-4 fold change = 1 . 2 , 1000 random iterations , p-value = 6 . 54 e−10; see Materials and methods ) . Figure 7C represents this analysis graphically: the real signal difference between NB5-6 and NB7-4 ( Figure 7C , red line ) is much greater than the distribution of differences calculated over the 1000 random iterations ( Figure 7C , black line ) . Furthermore , we found that of the 503 Hb enriched loci in NB5-6 , 101 had a Gsb peak within 2 Kb of the centre , whereas this number was 49 for NB7-4 . A Fisher’s exact test on these data found this spatial relationship to be highly significant for NB5-6 ( p = 8 . 78e-19 ) , but not for NB7-4 ( p = 0 . 078 ) . We conclude that loci differentially bound by Hb in NB5-6 are enriched for Gsb occupancy , although we note that occupancy may occur at different times ( Gsb earlier , Hb later ) . Taken together , these data support the sequential specification model , where a transiently expressed STF ( e . g . Gsb ) sculpts a lineage-specific chromatin landscape in NB lineages ( eg . NB5-6 ) , this determines lineage-specific binding of TTFs ( e . g . Hb ) , which can in turn specify different neural fates in different NB lineages ( Figure 8 ) .
Since its first report , Targeted DamID has been used in multiple cell types , in both Drosophila and mammalian embryonic stem cells ( ESCs ) , for mapping transcription factor binding ( Cheetham et al . , 2018; Tosti et al . , 2018 ) , open chromatin domains ( Aughey et al . , 2018 ) , chromatin states ( Bonneaud et al . , 2017 ) , and for mapping paused or transcribed loci ( Southall et al . , 2013; Widmer et al . , 2018 ) . In all cases , the number of cells expressing the Dam constructs are relatively large:~10 , 000 FACS purified ESCs ( Cheetham et al . , 2018 ) and ~5000 mushroom body neurons per brain ( Widmer et al . , 2018 ) . In our study we analyze the smallest percentage of cells to date - we calculate that there are between 8–12 cells in each hemisegment expressing Dam constructs; with a total of 11 segments that would give a maximum of 264 cells per embryo , or about 0 . 5% of the estimated 50 , 000 cells per embryo . Furthermore , we pushed the limits of the technique by allowing just 5 hr of Dam or Dam:Hb expression . It’s likely that this restrictive condition was successful in the case of a transcription factor-DNA interaction , which is stable during the time window; it might not be sufficient for factors such as RNA Pol II that require processivity through a gene . The ability to query transcription factor occupancy in such a precise manner – in a small subsets of cells over short periods of time – will encourage new uses of the method , such as studying the determination of cellular identities during development , upon reprogramming , or even in response to stimuli . We propose that the spatial factor Gsb opens genomic loci in NB5-6 , allowing the temporal factor Hb to bind loci that are not available in the adjacent Gsb-negative NB7-4 . Although nothing is currently known about the role of Gsb in chromatin regulation , the closely related mammalian Pax3 and Pax7 transcription factors can recruit histone methyltransferase to promote open chromatin and increase gene expression ( McKinnell et al . , 2008; Diao et al . , 2012; Kawabe et al . , 2012 ) . Moreover , Pax7 is a pioneer factor during pituitary development , opening ~2500 loci ( Budry et al . , 2012 ) . It would be informative to test whether Gsb can recruit trithorax complex methyltransferase to open genomic loci in row five neuroblasts , and whether this is required for row five neuroblast spatial identity and differential binding of Hb . The specific enrichment of Gsb occupancy at regions of accessible chromatin in NB5-6 is a striking result that supports our model despite different cell populations used for each experiment ( total embryonic vs . single NB lineage ) , different stages assayed ( 0–12 vs . 9–12 ) , and different methods used ( Dam vs . Gsb ChIP ) . Despite these differences , we observed significant enrichment of Gsb-bound loci at open chromatin in a NB-specific manner: NB5-6 shows enrichment , whereas NB7-4 does not . Ideally , similar experiments need to be conducted with Dam:Gsb in NB5-6 and Dam:En in NB7-4 lineage to determine correspondence of STF occupancy and chromatin accessibility , as well as STF and TTF occupancy in the NB lineages . The advantage of the Drosophila model is that these relationships can be rigorously tested . For example , mutational inactivation of the relevant STF , while assaying chromatin accessibility or Hb occupancy in a lineage-specific way could reveal a causal link between the STF and chromatin landscape , and STF and Hb occupancy . Similarly , targeting chromatin modifiers to select loci while assaying Hb occupancy could demonstrate a causal link between chromatin state and Hb occupancy . To definitively rule out the possibility that Hb acts as a pioneer in these lineages , it may be feasible to misexpress or mutate Hb , to determine the effect on chromatin accessibility . These are technically difficult studies , beyond the scope of this paper . We show that ~1200 Hb-bound loci are different in NB5-6 and NB7-4 lineages , and that the chromatin at these sites is preferentially open . In some cases Dam:Hb occupancy is broader than Dam ( open chromatin ) occupancy; this could be due to Dam:Hb maintaining occupancy longer than Dam alone . The strong correlation between Dam:Hb binding and open chromatin could be due to Hb binding to previously opened chromatin domains , or Hb acting as a pioneer factor to open chromatin . We do not favor the latter mechanism because Hb binds some sites in NB5-6 but not in NB7-4 ( and vice versa ) showing that it is not sufficient to open chromatin . NB5-6 and NB7-4 develop adjacent to each other during neuroblast formation . They share a common lateral Msh+ spatial column , but are in different anterior/posterior spatial domains ( NB5-6 is Gsb+ , NB7-4 is En+ ) . Although NB5-6 and NB7-4 make different early-born neurons , they share a common ability to make subperineurial glia and neurons that project through the posterior commissure ( Schmidt et al . , 1997; Schmid et al . , 1999 ) . It is interesting to speculate that their common properties are due to their shared columnar spatial position , whereas their differences are due to different anterior/posterior spatial cues . Although we have provided evidence that Hb-bound loci are chosen from neuroblast-specific open chromatin domains , this does not rule out that sequential specification occurs via lineage-specific STFs/STF-target genes acting as Hb cofactors to bias Hb binding in each lineage . However , we have been unable to find any de novo DNA motif enriched within 1 kb of Hb-bound loci throughout the genome , either neuroblast-specific loci or within all Hb-bound loci . This is consistent with Hb acting independently , but we can’t rule out the possibility of Hb acting with co-factors . Our conclusions are in agreement with studies showing that DNA accessibility , not cooperative or competitive interactions , have the strongest impact on transcription factor binding ( Li et al . , 2008; Kaplan et al . , 2011 ) . Similarly , this model is supported by in vitro protein-DNA studies that eliminate chromatin state contribution to these interactions ( Guertin et al . , 2012 ) . Using traditional methods of studying protein-DNA interactions , Hb targets in early embryogenesis have been well-characterized ( Hoch et al . , 1991; Struhl et al . , 1992; Rivera-Pomar et al . , 1995; Berman et al . , 2002 ) , yet little is known about Hb direct targets in the CNS , and nothing is known about neuroblast lineage-specific targets that specify lineage-specific neuronal identity . Here we’ve reported the first description of Hb occupancy in vivo within the genome of individual neuroblast lineages . Our study identified many loci that were similarly occupied in the two lineages , which are likely to consist of regulatory modules common to both lineages such as pan-neuronal specification or the progression of the temporal series . The latter example consists of Hb activating Kr and repressing pdm2 in most neuroblast lineages . Indeed we find that Hb binds to both loci in NB5-6 and NB7-4 lineages , confirming previous observations that Hb directly represses pdm2 and activates Kr in multiple neuroblast lineages ( Kambadur et al . , 1998; Tran et al . , 2010 ) . Hb is also likely to directly repress zfh2 in most neuroblast lineages ( CQD , unpublished results ) and our data show that the zfh2 locus is indeed equivalently occupied in both neuroblast lineages . Apart from the commonly regulated loci , we identified over 100 loci that are differentially bound by Hb in NB5-6 or NB7-4 . These are excellent candidates for lineage-specific neuronal specification . Our study , coming almost two decades after the first descriptions of spatial and temporal patterning in Drosophila neural stem cells ( Isshiki et al . , 2001 ) , has for the first time explored the mechanism by which spatial and temporal factors could be integrated to generate neuroblast-specific neuronal progeny . Only recently has it been possible to probe TTF DNA-binding and chromatin landscapes within two distinct neuroblast lineages – due to the parallel advances in genetic tools , functional genomics , and our ability to manipulate the genome . Given the conservation of mechanisms in generating neural diversity in vertebrates and invertebrates , and exquisite ways in which the genome can now be manipulated in different organisms , it is now possible to determine if similar mechanisms generate diversity during vertebrate neurogenesis .
Fly stocks were obtained from the Bloomington Drosophila Stock Center ( Bloomington , IN USA ) and , unless otherwise stated , were grown on cornmeal media at 25°C . UAS-LT3-Dam flies were kindly provided by Andrea Brand , R19B03[AD]; R18F07[DBD] was a gift from Gerald Rubin , and Lbe- ( K ) -Gal4 ( called NB5-6-Gal4 here ) was a gift from Stephan Thor . To generate MCFO clones ( Nern et al . , 2015 ) with NB5-6-Gal4 or NB7-4-Gal4 , we crossed hsFLP; UAS-MCFO females to Gal4 line males . 0–1 hr eggs were collected , aged at 25C until stage eight and given a 37°C heat shock for 20 min then aged at 25°C or 18°C until stage 17 . We used MARCM ( Lee and Luo , 1999 ) with engrailed-Gal4 to generate NB7-4 clones , which were unambiguously identified by the presence of channel glia ( Schmidt et al . , 1997; Schmid et al . , 1999 ) . Embryos were dechorionated in bleach for 3 min and fixed in 1:1::4% PFA:Heptane for 20–30 min . Vitteline menbranes were removed by shaking them vigorously in 1:1::heptane:methanol . They were washed with blocking solution ( 1 × PBS with 0 . 3% TritonX and 0 . 1% BSA ) for an hour . Primary antibodies were diluted in blocking solution . The samples were incubated on horizontal shaker at 4°C for 24 hr after which they were washed with 0 . 3% PTX ( 1 × PBS with 0 . 3% TritonX ) and secondary antibody diluted in 0 . 3% PTX was added . The samples were incubated at 4°C overnight , washed 0 . 3% PTX , allowed to settle in 30% glycerol , then allowed to clear in 90% glycerol infused with Vectashield overnight . Primary antibodies used were: chicken anti-GFP ( 1:1000 , abcam ab13970 ) , mouse anti-engrailed ( 1:50 , 4D9 DSHB ) ; rat anti-gooseberry ( 1:10 of equal mix of 10E10 and 16F2 , Holmgren Lab ) , rabbit anti-Hunchback ( 1:400 ) , rabbit anti-Dan ( 1:1000 ) , mouse anti mCherry ( 1:500 , Clonetech 632543 ) , rabbit anti-V5::549 ( 1:400 , Rockland 600-442-378 ) , mouse anti-HA::488 ( 1:200 , Cell signaling 2350S ) , rat anti-Ollas::650 ( 1:200 , Novus NBP1-06713 ) and rabbit anti-Eve ( 1:500 ) . All samples were imaged on ZeissLSM700 or ZeissLSM710 confocal microscope . Optical sections were acquired at 0 . 75 µm intervals with a picture size of 1024 × 1024 pixels . Images were processed in the open source software FIJI ( http://fiji . sc ) . To generate UAS-LT3-Dam:hb , full-length hb CDS was PCR amplified from BACR01F13 and cloned into pUAST-attB-LT3-NDam ( a gift from Andrea Brand ) using NotI and XbaI sites to fuse Dam to the N-terminus of Hb . As spontaneous mutations are known to arise in the Dam sequence upon transformation ( Marshall et al . , 2016 ) , its sequence integrity was tested at each transformation step , and prior to injections , all three elements - Dam , Hb and Cherry sequences were confirmed to be preserved . Transgenic flies with the construct integrated at the attP2 landing site were generated by BestGene Inc . For verifying the Dam:Hb flies , about 1500 females of UAS-LT3-Dam and UAS-LT3-Dam:hb flies were crossed to about 500 males of Da-Gal4 in egg collection cages placed at 25°C . Embryos were collected every two hours and aged for 16 hr at 25°C , then dechorionated with bleach to avoid contaminants , washed thoroughly with de-ionized water and preserved at −20°C until sufficient material was collected - for each replicate , 50 mg of control and experimental embryos . For stage 12 neuroblast TaDa experiments , about 5 , 000–6 , 000 UAS-LT3-Dam and UAS-LT3-Dam:hb flies were crossed to about 3 , 000 Lbe-K-Gal4 or 19B03[AD]/18F07[DBD] flies . Embryos were collected every two hours and aged for 7 . 5 hr at 25°C , and similarly treated until sufficient material was collected - for each replicate , 4 × 1 . 5 µL tubes of 50 mg of control and experimental embryos . The TaDa experimental pipeline was followed according to Marshall et al . ( 2016 ) , with a few alterations to optimize for small cell numbers and short duration of Dam expression . Briefly , the 4 tubes of each replicate were thawed on ice , processed separately and in parallel until the PCR purification step after the DpnI digestion step; subsequently , an additional PCR purification step using standard Qiagen PCR purification columns was used to concentrate the DpnI digested product to 32 µL . Embryos were homogenized with an electric pestle and gDNA was extracted using the DNA Micro Kit ( Qiagen , cat . no . 56304 ) . Extreme care was taken to ensure that the gDNA remained intact – this was done by using wide bore tips to avoid fragmenting the DNA , pipetting deliberately , and avoiding any rough shaking/tipping . gDNA was digested with DpnI for 14–16 hr in a thermocycler then PCR purified . MyTaq HS DNA polymerase kit ( Bioline , cat . no . BIO-21112; not the Advantage 2 cDNA polymerase from Clonetech ) was used for amplification and 21 PCR cycles we used . Sequencing libraries were prepared according to the Illumina TruSeq DNA library protocol . The samples were sequenced on the Illumina HiSeq4000 at 100 base pairs and about 20–60 million single end reads per sample .
Spatial and temporal cues are required to specify neuronal diversity , but how these cues are integrated in neural progenitors remains unknown . Drosophila progenitors ( neuroblasts ) are a good model: they are individually identifiable with relevant spatial and temporal transcription factors known . Here we test whether spatial/temporal factors act independently or sequentially in neuroblasts . We used Targeted DamID to identify genomic binding sites of the Hunchback temporal factor in two neuroblasts ( NB5-6 and NB7-4 ) that make different progeny . Hunchback targets were different in each neuroblast , ruling out the independent specification model . Moreover , each neuroblast had distinct open chromatin domains , which correlated with differential Hb-bound loci in each neuroblast . Importantly , the Gsb/Pax3 spatial factor , expressed in NB5-6 but not NB7-4 , had genomic binding sites correlated with open chromatin in NB5-6 , but not NB7-4 . Our data support a model in which early-acting spatial factors like Gsb establish neuroblast-specific open chromatin domains , leading to neuroblast-specific temporal factor binding and the production of different neurons in each neuroblast lineage .
The human brain is considered to be the most complicated object in the universe , but it only takes a handful of stem cells to make one . The process depends on two types of information: signals separated across space and time . Spatial cues tell a stem cell what type of cell it is going to be , while temporal cues work as molecular clocks to generate a sequence of different neurons over time . Together , these cues generate the large array of cell types in the nervous system . Each stem cell occupies its own space in the developing body and receives its own spatial cues , but they all follow the same timeline . For example , proteins called transcription factors act as molecular clocks and interact with specific genes , telling the cell when to turn them on or off . The same series of transcription factors operates in different stem cells , but they have different effects . So far , it has been unclear whether spatial and temporal signals work independently or sequentially to generate new cell types . To find out , Sen et al . studied two distinct , developing stem cells in fruit flies , which receive different spatial signals . Transcription factors only work if they are able to get to their target genes . Cells can open or close access to different genes by changing the structure of the chromatin wrapping that surrounds the genes . In the experiments , a marker was used to reveal the areas of open chromatin in each of the cells . Another marker was used to track the transcription factors . The results showed that the areas of open chromatin varied between stem cells . Moreover , although both cells used the same transcription factor called Hunchback , it targeted different genes in each stem cell . This was due to changes in the chromatin wrapping: Hunchback only acted in areas where the chromatin was open . This suggests that the spatial cues first sculpt the chromatin , making some genes easier to get to than others . Then , the same transcription factors go to the accessible gene , which will differ from one stem cell to another . These findings help us to understand how different types of brain cells develop , which may also aid us in finding a way how to engineer specific cell types . If we could turn stem cells into different types of brain cells , it might help us to treat brain diseases . This may involve giving the right spatial signal before starting the temporal cues .