Research indicates children and young people in care have a high prevalence of Developmental Language Disorder (DLD) as part of a complex set of vulnerabilities. This study describes the profile of language, literacy and communication abilities of a cohort of care leavers. The language, literacy and communication abilities of 44 young people leaving care between the ages of 16 and 26 years were assessed using standardized measures. Demographic data about the young people was collected along with a survey to key staff to capture their perceptions and experiences of the language and communication abilities of these young people. Ninety percent of the care leavers’ language abilities were below average and over 60% met criteria for DLD in combination with literacy difficulties, developmental disorders and social, emotional and mental health difficulties (SEMH). The implications of unidentified DLD on the lives of young people leaving care is discussed. Earlier identification of DLD is advocated to enable services to intervene to facilitate more positive outcomes and life chances for this very vulnerable population.  In 2018, there were 75,429 looked after children in England [Children in looked after care are very vulnerable with poor life chances across educational attainment, employment, independence and social, emotional and mental health (SEMH) ,3,4. TheResearch investigating the language, literacy and communication profiles of children and young people in care is preliminary . A recenThe term DLD refers to children who have significant developmental difficulties in their language and communication abilities. The term DLD has recently been revised and is used to refer to children who show difficulties across many modalities of language and communication (including speech). These difficulties cannot be best explained by intellectual disabilities, other neuro-developmental disorders, hearing loss or other neuro-biological reasons . There iThis current study builds on previous research ,6,7 by pThe aims of the study were to (1) describe the profile of language, literacy and communication abilities of a cohort of care leavers aged 16 to 25 years; (2) determine if this profile of abilities is self-reported by the care leavers themselves and the key staff working with them and: (3) understand how these key staff perceive and experience the language and communication abilities of the young people they work with.What is the language, literacy and communication profile as measured by standardised assessments of care leavers aged between 16 and 25 years? How do care leavers report their own language and communication abilities and does this align with the profile of language and communication ability described by the assessments? Can key staff working with care leavers describe their language and communication abilities and does this align with the profile of language and communication ability described by the assessments?How do key staff perceive and experience the language and communication abilities of care leavers? The study asked the following research questions: This is a cross sectional study using standardised assessments to describe the profile of language, literacy and communication abilities of care leavers aged between 16 years to 26 years. The study employs an online survey to capture the perspectives and experiences of key staff about the language and communication abilities of the young people they work with. Participants were 44 young people aged between 16 and 26 years with a mean age of 20 years and 9 months (SD 2.20). Thirty were male and 14 were female. Participants were identified through opportunity and voluntary sampling from the council leaving care service in a large city in England. All young people in the service were eligible to participate . Study information was sent to all the Personal Advisors (PAs) in the service to explain the study and the potential involvement of the young people they work with. PAs are professionals who play a key role in supporting young people with their transition to independence. PAs were asked to discuss the study with all their young people. Where young people indicated they would like to participate, the PA contacted the research team and an assessment was set up. Flyers about the study were also distributed through a venue where the service is based which functions as a drop in-centre for the young people. Interested young people were asked to make contact with the research team. Researchers also attended a young person led support group to tell young people about the study as well as distributing flyers to young people as they came into the venue. If a young person indicated an interest in participating in the study, they received an information sheet (accessible version) and an assessment was set up at a convenient date and time. PAs were also participants in the study. Twenty-three PAs completed an online survey to capture their perspectives and experiences of the language and communication abilities of the young people. Participants completed assessments of language, literacy and communication. 19 is an assessment of language standardised on a UK population aged 5 years to 21 years and 11 months. Four subtests of the CELF-5 UK were administered to form the composite Core Language Score (CLS) [The CELF-5 UKThis subtest measures the ability to construct grammatically and semantically correct sentences. The participant is presented with a picture and a spoken word and then asked to create a spoken sentence about the picture using the word. A score of two is given for a grammatically, semantically and syntactically correct sentence. A score of one is given where there is a complete sentence but there are one or two syntactic or semantic errors. A score of zero is given where there is an incomplete sentence, the sentence does not make sense or there are multiple errors. This subtest measures listening, specifically verbal working memory. The participant is asked to immediately repeat a sentence spoken by the examiner. The sentences increase progressively in length and complexity. A score of three is gained where no errors are made and gradually decrease to zero, when four or more errors are made. This subtest measures language understanding where participants answer questions relating to novel, factual information heard in a spoken paragraph. The examiner reads out written paragraphs of increasing length and complexity, and the participant is then asked to answer questions about the information they listened to. A score of 1 is awarded for each correct answer. This subtest measures the ability to correctly understand sentences where a range of semantic relationships are expressed including comparison, locations and directions, time relationships, serial order and tenses. For each item, a maximum score of 1 is available. Raw scores were converted into scaled scores using the UK standardised norms of the CELF-5-UK enabling comparisons with UK age norm scores. A scaled score of 10 describes the mean score; scaled scores of 7 and 13 are one standard deviation (SD) below and above the mean. Scores lower than 7 are indicative of significant difficulties. The mean of the standard core raw score is 100. The CELF-5 UK has high reliability and validity.This  is a staThe Communication Checklist  is a 70-In both the CC-SR and the CC-A, language and communication ability is rated across three domains of (1) Structural language ; (2) Pragmatic skills  and; (3) Social engagement . A scaled score of 6 or less is taken as a cut off score indicating a difficulty. The participants were given the choice to complete the CC-SR independently or to have the researcher read out each statement and record their score. The majority of participants asked the researcher to read the statements aloud to them and record their score. The CC-A was completed by the participant’s PA. PAs completed this measure independently but were able to ask the researcher questions on certain items if needed. The PA may have completed this measure multiple times if they had more than one young person on their caseload participating in the study. Due to ethical issues, it was not feasible to access participants’ demographic data about the participants held by the service. A questionnaire was designed to capture data pertaining to current vocation (employment/studying/other), current living circumstances, number and type of care placements experienced, age entered and left care, diagnoses received, in receipt of a Statement of Special Educational Needs/Education, Care and Health Plan (EHCP), qualifications, physical health needs and criminal convictions. Where participants needed support, the researcher read out the questions and recorded their responses. A short online survey was designed to capture the perspectives and experiences of PAs. The survey consisted of ten questions see  and 23 PAt the assessment, the participants received the information sheet (accessible version) again to read through or the researcher talked through the information. If the participant agreed to take part, he/she gave their written consent. Assessments were either conducted at the city council venue or externally at the young person’s home with the PA present. The assessments completed by the young people were the CELF-5 UK, TOWRE-2, CC-SR and the demographic questionnaire. All assessments were conducted in English and the order in which the assessments were completed was varied. The assessment session was approximately one hour in duration.The majority of the assessments were carried out in the city council venue. It was not possible to use an individual room unless a PA was present . Therefore, some assessments may have been impacted by background noise. Participants received a £20 gift voucher for their time. PAs completed the CC-A in their own time and returned these to the researcher in person or by post. The CELF-5 UK, TOWRE and CC-SR and CC-A data was examined for normality. Shapiro Wilks tests confirmed significance of non-normal distribution for the CELF-5UK data only. Therefore, the medians and inter-quartile ranges (IQR) are reported for the CELF-5 UK data. Means, standard deviations and ranges are reported for the TOWRE and CC-SR and CC-A. Due to the variation in the sample, a descriptive analysis was conducted. Non-parametric correlational analysis was also completed. SPSS-Version 21 was used to conduct all analyses. Of the 44 participants, 30 were male and 14 were female with a mean age of 20 years and 9 months (SD 2.20) (range 16 to 26 years). It was noted that one participant was 26 years old and so beyond the age range of the Leaving Care Service. Twenty-three (52.3%) participants (aged between 18 and 25 years) were living independently. Seven participants (15.9%) (aged 16 to 26 years) were in supported living making the transition into independent living. Six participants (13.6%) (aged 18 to 20 years) were still in foster care and 4 participants (9%) (aged 16 to 21 years) were categorised as ‘other’ . Forty participants (91%) reported experience of foster care and 4 (9%) experience of foster and residential care. The mean age of entering care was 10 years and 9 months (range 2 years to 18 years). Of the 29 participants (66%) who had left care, the mean age of leaving was 17 years and 6 months (range 15 to 19 years). Fifteen participants (34.1%) reported still being in care and four (9%) were not sure/did not respond to this question. Five participants (11.4%) reported speaking English as an Additional Language (EAL) These participants were aged between 18 and 21 years and had entered care when they came to England as unaccompanied asylum seekers at the age of 16 years or under. Four participants came to England from Eritrea and spoke Tigrinya as their first language. The fifth participant did not report which country he had travelled from and/or his first language. At the time of the study, twenty-three participants (52.3%) (aged 16 to 26 years) were not in employment, education or training (NEET), nine participants (20.5%) were in paid employment (aged 18 to 25 years), ten (22.7%) in education (17 to 24 years) and two (4.5%) in volunteer roles (aged 20 to 23 years). Educational qualifications were categorised as highest educational qualification achieved ever. GCSEs were attained by 16 participants (36.3%), NVQs by 18 participants (40.9%), BTECs by 5 participants (11.4%) and A levels by 1 participant (2.3%). No participants in this sample had gained a higher education/University qualification. Nineteen participants (43.2%) reported receipt of either a Statement of Special Education Need (SEN) and/or an Education and Health Care Plan (EHCP). Twelve of these 19 participants (27.3%) were unable to report why they had received additional education support. Seven participants (15.9%) did report reasons across learning difficulties (n = 3), social, emotional and mental health difficulties (n = 1), reading and/or dyslexia (n = 2), physical/mobility/hearing (n = 1). Fourteen participants (31.8%) reported receipt of a developmental disorder diagnosis ever across Attention Deficit Hyperactivity Disorder (ADHD) (n = 8), Autism Spectrum Disorder (ASD) (n = 5), learning difficulties (n = 4), dyslexia (n = 4) and dyspraxia (n = 1). Ten participants (22.7%) reported physical health needs including hearing difficulties (n = 3), epilepsy (n = 1), mobility needs (n = 4) and cardiac needs (n = 2). In terms of mental health difficulties, 29 participants (65.9%) reported mental health difficulties across depression (n = 13), anxiety (n = 15), bi-polar (n = 1), conduct disorders (n = 1), obsessive compulsive disorder (n = 2), borderline personality disorder (n = 2) and post-traumatic stress disorder (n = 1). Fifteen participants (34.1%) reported receipt of a criminal conviction. Four received a referral or community order and four received a custodial sentence. One was not sure and six participants chose not to disclose the type of sentence received. Complete CELF-5 UK scores were available for 42 of the 44 participants (Thirty-nine participants completed the TOWRE-2 see . The meaAll 44 participants completed the CC-SR see . The meaComplete data was available for 21 of the 44 participants see . The meap = 0.45), There was a negative non-significant correlation for Language Structure , a positive non-significant correlation for Social Engagement  and a negative, non-significant correlation for the total score .Comparison of the CC-SR and CC-A data was completed using the same 21 participants who had complete data for both scales see . All 21 The profile of the 26 participants with CELF-5 UK scores in the very low/severe range (−2 SD and below) was examined with respect to EAL, receipt of a Statement of SEN/EHCP, diagnoses of developmental disorders and mental health difficulties and scores of 6 or below on the CC-A and CC-SR see . Of the Importantly, the five participants who were unaccompanied asylum seekers with EAL were in this sample. These five participants with EAL were removed to describe the profile of language, literacy and communication of the 21 participants with CELF 5UK scores (−2 SD and below) see . DescripThe survey to the PAs was completed by 23 participants. The findings are presented for each of the questions. Question 1.What is your staff role in the Children Looked After and Leaving Care Service, Sheffield City? (n = 23/23 responses)The majority of respondents were PAs (n = 20), with two as Senior PAs. One was a Senior Field Work Manager and the other two were from the Business Support Team who worked with care leavers in these roles. Question 2.How long have you been in this role? (n = 23/23 responses)Six respondents had been in post for more than five years and ten respondents had been in post for less than a year. Of the remaining seven respondents, five had been in post between one and three years and two between three and five years. Question 3.Do you experience difficulties in communicating effectively with the care leavers you work with? (n = 21/23 responses)Six respondents reported they do experience difficulties and seven reported they do not. One respondent was not sure, and seven selected other and responded with comments making reference to (1) care leavers changing their mobile numbers frequently; (2) variation across care leavers with some care leavers being effective communicators and others not; (3) English as an additional language and 4) avoidance of communication initiated by the care leavers. Question 4.If there are care leavers with communication difficulties in your service, how are these communication difficulties documented? (n = 20 responses)The majority of respondents reported communication difficulties are documented in the Service Needs Assessment/Pathway Plans (n = 17) followed by SEN Statement/EHCP Plan (n = 9) and Case Files (n = 8). Question 5.What types of communication difficulties do care leavers have? Respondents ranked 9 options from 1–9 where 1 represented the type of need most prevalent and 9 the type of need the least prevalent (n = 20/23 responses)The median ranks were calculated for the 9 options see . AttentiQuestion 6.What support is available in your service for care leavers with communication difficulties? (n = 21/23 responses)No respondents reported being able to access a speech and language therapist (SLT) employed in the service whereas 11 respondents reported being able to access a SLT through another service. This was where care leavers were also involved in the Youth Justice Service which employs a SLT. One respondent was able to access support from staff who had received training about speech, language and communication needs (SLCN). Nine respondents reported not being able to access any support. Question 7.Do you consider that having communication difficulties makes it more difficult for a care leaver to engage effectively in the service and their transition? (n = 22/23 responses).Twenty respondents reported yes and two reported no. Question 8.If yes, please rank the following reasons from 1–5, where 1 represents the most common reason and 5, the least common reason (n = 16/23 responses).The median ranks were calculated for the 5 options see . Giving Question 9.How effective do you consider communication between staff and care leavers is? (n = 20/23 responses)Communication between staff and care leavers is perceived as very effective by one respondent, effective by 12 respondents, medium effectiveness by six respondents and some effectiveness by one respondent. Question 10.How could staff be supported to communicate more effectively with care leavers? (n = 23/23)Participating in training both to understand SLCN (n = 15) and to communicate more effectively with care leavers (n = 9) along with accessing speech and language therapy services (n = 14) and accessing resources to increase the accessibility of information for care leavers (n = 13) were all selected The study conducted a descriptive analysis of the language, literacy and communication profiles of 44 young people leaving care, aged between 16 and 26 years. Young people rated their own language and communication abilities and PAs also rated the language and communication abilities of these young people. PAs completed a survey to understand their perspectives and experiences of the language and communication abilities of the young people they work with. The demographic data confirmed the poor psycho-social experiences and outcomes of young people in care ,3,4. ForThe PAs were uncertain about developmental language and communication abilities and difficulties. There was agreement language and communication difficulties impede a young person’s transition and accessing appropriate support is challenging. Interestingly, if the young person was also involved in the youth justice service, they were able to access speech and language therapy services. Despite the variation in responses, there was confirmation language and communication difficulties make it harder for care leavers to engage in their transition to independence. Further training, access to speech and language therapy services and resources were all considered necessary. This study confirms the findings of the few previous studies identifying similar profiles of language, literacy and communication abilities and prevalence of DLD ,6,7 in yThe findings are relevant to other vulnerable populations ,26. YounThere are several methodological limitations to highlight. The self-report demographic data and analysis confirms this sample is very heterogenous. Variation is evident across all the measures employed. The inclusion of participants who entered looked after provision as asylum seekers with EAL and the high rate of self report of Statements for SEN/EHCP, developmental disorders and mental health difficulties is further evidence of this. The sample of 44 participants  is a small proportion of all the young people in the leaving care service at the time of the study and therefore may be biased. The study may have attracted those young people who were interested in receiving a gift voucher and/or actively seeking more support than other young people in the service. Furthermore, since the PAs knew the study was about language, literacy and communication, they may have been more likely to identify young people they considered could benefit from participating although measures were taken to prevent this. There are issues around the assessments and measures used. There is a dearth of language and communication assessments standardised for young people with potential developmental as opposed to acquired language and communication disorders. The CELF-5 UK is standardised up to 21 years and not 25 years. Although the TOWRE-2 is standardized to 25 years, it only provided a measure of single word reading and not more functional literacy skills. There is incomplete data, specifically for the PA completed CC-A assessment and some of the survey questions. It was challenging to ensure PAs completed the CC-A for their young people. For some young people, there were distractions in the venue where the assessments were completed which may have impacted on their scores. Indeed, many young people needed reassurance to complete the assessments. The CELF-5 UK employs a discontinuation rule where a young person has to continue attempting items before the stop rule is reached even though the young person is aware, they are failing. This is an uncomfortable experience and may have stopped young people engaging fully.An important part of the study was to identify how young people perceive their own language and communication abilities and if this aligned with their CELF-5 UK scores. Some young people self-reported language and communication difficulties but there was no clear alignment between the self-reporting on the CC-SR with the PA completed CC-A and the standardised assessments. The CC-SR and CC-A did not correlate nor align with the CELF-5 UK. This is clearly an area for future research to consider how best to gain a more functional measure of language and communication ability from the perspective of the young person and those who work closely with him/her. The incomplete responses for some of the survey questions indicates the survey design not fully appreciating the limited knowledge and understanding of the PAs leading to potential mis-understanding and non-completion. The demographic data collected was via self-report as it was not possible to access participant data from the service due to ethical issues. The self-report demographic data may not be accurate. Indeed, several participants were unable to recall important historical information, e.g., reasons for having a Statement of SEN/EHCP plan. Nevertheless, the high proportion of young people identified with severe language and communication difficulties meeting criteria for DLD in this sample warrants further consideration.Ninety percent of the care leavers had below average language abilities and over 60% met criteria for DLD in combination with literacy difficulties, developmental disorders and SEMH. Earlier identification of DLD is advocated to enable services to intervene to facilitate more positive outcomes and life chances for this very vulnerable population. All children and young people in care should be able to access speech and language therapy services to identify their language and communication needs and to support these effectively through childhood and into adult life.


Pax7 contribute to multiple lineages, and a subset of premigratory neural crest cells shares a transcriptional signature with their border precursors. Together, our results suggest that cells at the neural plate border remain heterogeneous until early neurulation, at which time progenitors become progressively allocated toward defined neural crest and placode lineages. The data also can be mined to reveal changes throughout the developing epiblast.The epiblast of vertebrate embryos is comprised of neural and non-neural ectoderm, with the border territory at their intersection harboring neural crest and cranial placode progenitors. Here, we a generate single-cell atlas of the developing chick epiblast from late gastrulation through early neurulation stages to define transcriptional changes in the emerging ‘neural plate border’ as well as other regions of the epiblast. Focusing on the border territory, the results reveal gradual establishment of heterogeneous neural plate border signatures, including novel genes that we validate by fluorescent in situ hybridization. Developmental trajectory analysis infers that segregation of neural plate border lineages only commences at early neurulation, rather than at gastrulation as previously predicted. We find that cells expressing the prospective neural crest marker  During gastrulation, the ectoderm layer of the chordate embryo becomes segregated into the neural plate and the surrounding non-neural ectoderm. The neural plate ultimately generates the central nervous system (CNS), whereas the surrounding non-neural ectoderm forms the epidermis of the skin as well as the epithelial lining of the mouth and nasal cavities. At the interface of these tissues is a territory referred to as the ‘neural plate border’ which in vertebrates contains precursors of neural crest, neural, and placodal lineages . Neural An ongoing question is whether individual neural plate border cells are specified toward a particular lineage  or if they have the potential to become any cell type that arises from the border. It has been suggested that progenitors of these different lineages may be regionalized within the neural plate border, with the more lateral cells contributing to the placodes and the more medial region giving rise to neural and neural crest cells . Such seOne study using an ex ovo culturing method of explants from the chicken embryos proposed that a pre-neural plate border region is established as early as stage Hamburger and Hamilton (HH) 3 . In addiPax7+ cells are not restricted to a neural crest fate but rather are capable of giving rise to all derivatives of the neural plate border. The data also reveal numerous novel factors dynamically expressed across the developing epiblast as well as indicating putative drivers of neural plate border trajectories. Taken together, the data reveal dynamic changes in an emerging neural plate border that becomes progressively segregated into defined lineages, that is complete only late in neurulation. Furthermore, the data can be further interrogated to examine transcriptional changes in other regions emerging from the epiblast.Single-cell RNA-sequencing (scRNA-seq) provides a unique platform to address the intriguing question of when a neural plate border transcriptional signature arises in an in vivo context. To this end, we examined single-cell transcriptomes from the epiblast of gastrulating to neurulating chick embryos to determine the time course of emergence of the neural plate border. The chick represents an ideal system for these studies since avian embryos develop as a flat blastodisc at the selected time points, highly reminiscent of human development at comparable stages. Interestingly, our results show that the border is not transcriptionally distinct until the beginning of neurulation (HH7), when neural plate border markers define a discrete subcluster of the ectoderm. Furthermore, RNA velocity measurements imply that segregation of the neural plate border commences at HH6, but is more profoundly underway at HH7, with definitive neural crest clusters only emerging in the elevating neural folds. Velocity analysis also suggests that Pax7 and Tfap2A transcription factors, both of which are well-established early markers of the neural plate border , and featured low levels of Tfap2A and Dlx5  were enriched in HH4-Cl4   yielding Xenopus . While n Xenopus  suggestsPax7 was detectable but low during gastrulation stages (HH4/5), its expression is strongly enhanced by HH6/7 ; posterior lateral neural plate . Cardiac mesoderm markers were enriched in HH6-Cl4 (Tcf21 and Gata5) and HH6-Cl11 . HH6-Cl1 and HH6-Cl3 represented paraxial mesoderm . Endoderm cells formed HH6-Cl6 . Hensen’s node and primitive streak markers  were identified in HH6-Cl7 and HH6-Cl9, respectively. We also detected a cluster of cells (HH6-Cl5) with high levels of mitochondrial genes (Cox1/3), this cluster was also enriched for factors associated with highly proliferative cells   .Pax7, Tfap2A, Dlx5, Bmp4, and Msx1  also emerged in these cells , other neural/neural crest genes featured in HH7-Cl3, including Zeb2 and Zic2 , while mesoendodermal cells ingress and internalize at the primitive streak and Hensen’s node. To further resolve the transcriptional complexity of the developing neural plate border, we extracted and subclustered the ectodermal clusters at stages HH5, HH6, and HH7. These are designated HH5-Cl4, HH6-Cl8/10, and HH7-Cl3/9 .Sox2, Otx2, Sox21, Six3) subcluster (HH5-sub-1) versus the non-neural ectoderm  subcluster (HH5-sub-2)  and caudal epiblast genes  but a small portion of HH5-sub-2  cells also expressed Pax7   were clesed Pax7 . HH5-subclusters .Sox2, Otx2, Six3; Tfap2A, Dlx5) were enriched in HH6-sub-0   ; howeverclusters . These Pis stage .Irf6 which was broadly present across HH5 subclusters, was now enriched in HH6-sub-0 , along with Grhl3 which was present in a small portion of HH5-sub-2  but was clearly enriched in HH6-sub-1  , while Znf703 was restricted to more caudal epiblast cells (HH5-sub-0 and HH6-sub-2)  . Gbx2 wa6-sub-2) . Gata2 aH6-sub-0 . The plaor niche .Pax7, Msx1 and Bmp4 were found in a niche of cells within HH7-sub-1, which broadly expressed Tfap2A and other non-neural ectoderm markers  were arising in the Pax7+ domain  but these cells did not co-express Pax7 (Pax7+) and lateral (Tfap2A+) regions, as well as highlighting the overlap and combination of genes co-expressed across these regions. HH7-sub-1 also featured Irf6 expression, and Grhl3 was present in a subset of cells which co-expressed Irf6 and Tfap2A  to observe co-expression in this region. Embryos from HH4 through HH10 were screened to glean the time course of gene expression.We validated the in vivo expression pattern of intriguing genes identified in our single-cell datasets, using fluorescent in situ hybridization  , which eIng5, Astacin-like metalloendopeptidase, Astl, and neuronal navigator 2, Nav2 were enriched in the ectoderm cluster (HH4-Cl0) /HH6-Cl8 (Ing5). Astl was seen in HH7-Cl9, Ing5 was not differentially expressed at this stage but was present in HH7-Cl3  . At stage border . While bectoderm . At HH8-al plate . Ing5 waal folds . By HH8,indbrain . Ing5 wae at HH8 ; howeverplacodes . Consist HH7-Cl3 .Nav2, detected in ectoderm clusters HH4-Cl0, HH5-Cl4, HH6-Cl10, and HH7-Cl9 was expressed across the ectoderm and neural plate at HH5–HH7, where it over-lapped with the neural marker Sox21  and HH6-Cl10 . The latter was characterized by and Irf6 . In situand HH8- . Irf6 waand HH8- . Furtherand HH8- . At HH8+ placode . By HH9+ placode .Wnt5A, Wnt5B, Wnt8A , in vivo we found Sp8 expression commenced from HH7 in the neural plate border, partially overlapping with Tfap2A    and was l plate)  as previl plate) . This ex at HH8- . Sp8 expaterally . At HH9,n region  but largn region . Dlx6 was at HH9 , as wells at HH9 .Sp5 was enriched in HH6-sub-2 , this work also defined distinct clusters of neural crest cells characterized by marker genes representing their likely potential; neural-neural crest  and mesenchymal-neural crest .To assess the progression of ectodermal progenitors across time-points from epiblast to onset of neural crest emigration, we first integrated the ectoderm clusters from each stage namely; HH5-Cl4, HH6-Cl3 + 9 and HH7-Cl8 + 10. Here, we also included 10 X scRNA-seq data obtained from premigratory neural crest cells (HH8+) , such thCdh1, Epcam, and FoxG1 expression. Interestingly these cells grouped with the non-neural ectoderm clusters from HH6 and HH7, including neural plate border cells  defined one distinct trajectory, whereas the other trajectory was less well defined but could be distinguished by posterior epiblast markers   . The neux1, Bmp4 . Early ning here . While ting here . Neural and Zic1  which arand Zic1 . Some neSix1, Dlx5  were found in the non-neural ectoderm and some neuroepithelial-like cells, as well as extending into the interface of neural plate and neural-neural crest populations . To this end, we extracted the ectoderm clusters (HH7-Cl3+ Cl9) and combined these cells with the premigratory neural crest data set from HH8+ embryos  and usedx1, Dlx5 . While Tal crest . Other nulations .Taken together, combining our 10X data-sets from all stages reinforced the notion that the neural plate border territory is not specified to a neural crest fate until HH7 since scVelo analysis on the entire dataset (including HH5 and HH6 data) generated ambiguous and non-contiguous developmental trajectories . While nPax7, Bmp4, Tfap2A, Msx1, Dlx5, and Six3) were co-expressed  initiated a separate trajectory. However, cells located centrally, including neural plate border cells, contributed to all three subclusters .At HH6 the trajectories were more distinct. Caudal epiblast cells (HH6-sub-2) contributed to both neural plate and non-neural ectoderm populations. Within the neural plate cluster (HH6-sub-1) some cells were directed toward the non-neural ectoderm and others followed a separate trajectory. Likewise, the non-neural ectoderm cluster was subdivided between two parallel pathways with some mutual cross-over. Neural plate border cells found across all three clusters and at their interface largely joined the non-neural ectoderm clusters .Pax7+ neural plate border cells  were engaged in a separate trajectory; these cells were enriched for Dlx5 . Whereas Ing5 expression correlated with Pitx1 (WGCNA cluster-x), which we identified here as a putative driver of neuro-epithelial neural crest lineage. Another example is Irf6 which has previously been described in craniofacial development  characteristic of Van der Woude syndrome  (HH4 data was obtained using v2 chemistry) as per the manufacturers protocol. Libraries were quantified using Qubit (Life Tech Qubit high sensitivity DNA kit Cat. #Q32854) and Kapa . scRNA-seq libraries were sequenced on Illumina HiSeq2500 platform in rapid run mode with on-board clustering and sequencing depth of 300 million reads. The run type was: paired end 28(read1)–8(index)–91(read2). HH4 10 X scRNA-seq library was sequenced on Illumina NextSeq500 platform using high output v2.5 150-cycle kit in 26 × 8 x 0 x 98 mode.Fastq files were generated using cellranger v3.1.0 mkfastq . CellranFrom HH4 embryos 2398 cells were recovered with 144,605 mean reads/cell, 1836 median genes/cell, 6,180 median UMI counts/cell and 15,370 total genes. From HH5 embryos 6723 cells were recovered with 44,343 mean reads/cell, 3,659 median genes/cell, 14,229 median UMI counts/cell and 18,916 total genes. From HH6 embryos 4553 cells were recovered with 30,466 mean reads/cell, 3396 median genes/cell, 13,309 median UMI counts/cell and 17,828 total genes. From HH7 embryos 6585 cells were recovered with 20,044 mean reads/cell, 2696 median genes/cell, 8821 median UMI counts/cell and 17,873 total genes. Count matrices were generated using the cellranger count function and exported to R-studio for downstream analysis using Seurat-v3 . MatriceFluorescent in situ hybridization chain reaction was performed using the v3 protocol . BrieflyFollowing HCR and whole mount imaging, selected embryos were prepared for cyrosectioning Embryos were placed in a 15% sucrose solution at 4 °C overnight then 15% sucrose / 7.5% Gelatin overnight at 37 °C. Embryos were transferred to 20% gelatin and incubated at 37 °C for 4 hr then mounted in 20% gelatin, snap frozen in liquid nitrogen and stored at –80 °C. Sections were taken at 10 µm intervals. In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Decision letter after peer review:[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting the paper "Segregation of neural crest specific lineage trajectories from a heterogeneous neural plate border territory only emerges at neurulation" for consideration by eLife. While this manuscript has not reached the benchmark of a Research Article, on noting the potential value of the dataset for future study of the development of the neuroectoderm, the neural crest cells and the ectodermal placode, we are keen to provide the opportunity for publishing this paper as Resource Article. Resubmission of a new manuscript would require addressing the critiques raised by the reviewers in this round of review, which are paraphrased below and outlined in the three reviewer reports.We are sorry to say that, after consideration of the reviewers' feedback and following further consultation with the reviewers, we have decided that this work will not be considered for publication by The reviewers recognised that this study has collated a potentially useful dataset of the stage-resolved single-cell transcriptome of chick epiblast/ectoderm cells that may inform the development of the epiblast to neural folds and the molecular characteristics of the neural plate border cell population from which neuroepithelium, ectodermal neural placode and neural crest cells emerge. The findings reiterate the concept of lateral neural plate border harbours a heterogenous population of ectoderm cells and members of this population are precursors of the neural crest cell lineage during neurulation. The new knowledge gleaned from the transcriptome data is that the neural plate border cells are specified  progressively/dynamically during neurulation, but no insight is provided on how the neural border cells establish multipotency . The data further showed that the segregation of the neural crest cell lineage and the placodal ectoderm lineage from the neural plate borders cells may occur at early neurulation, which is later than previously anticipated. Mining the transcriptome data of the emerging cell lineages has inferred the putative molecular drivers of the trajectory of neural plate border cells to neural crest cell lineage and placodal ectoderm lineage. There is no follow-up verification of the functional attributes of these drivers or the molecular network in the development of these two lineages. The merit of this study would be enhanced if functional analysis has been undertaken to identify which are the key drivers and their functional role in the segregation of the two divergent neural border cell lineages and the early steps of differentiation of the neural crest cells.Re-submission as a resource report will require provision of the missing detail of the experimental design of the single-cell transcriptome analysis and the data analytics pipeline, improving the style of presentation to allow a better comprehension of the important novel findings of data mining. addressing the utility and limitation of the transcriptome dataset to gains knowledge that enables the formulation of testable hypothesis on the molecular activity driving neural plate development. emergence of the neural plate border cell lineages.Reviewer #1:The work by Williams et al. represents a significant effort to understand the lineages that emerge from the epiblast, which is the layer of cells that will give rise to the chick embryo, during the period from gastrulation through neurulation. Previously published work has addressed the question of when and where cells in the epiblast at the neural plate border become specified, but the authors strive to refine such data further and more precisely by using single-cell RNA-sequencing to characterize the signatures of these lineages in vivo. The authors focus on identifying cells that generate the placodes, neural crest, and neural tissues. Studying these populations of cells is well justified because of their relevance to human disease phenotypes particularly in the craniofacial complex, heart, gut, and malignancies more broadly. Another important contribution of the work is the descriptions of novel markers, which may ultimately result in identifying new genes associated with human disease.A strength is that the manuscript is concise, clear, and well-written. Additionally, the figures are nicely organized and easy to follow. The images of embryonic gene expression  are excellent in terms of tissue quality and confocal microscopy, and they provide robust support for the conclusions. The strategies employed for single-cell RNA-seq analysis represent a technical advance, and the results generated by this study will be of broad interest to the community. The use Hybridization Chain Reaction (HCR) with multiplexed probes to validate the RNA-seq dataset adds significant depth to the analysis.A weakness is that the study is primarily descriptive with no experimental test of a hypothesis. For example, the work could benefit from some loss-of-function analyses for any of the novel genes identified. On this point, the authors have an excellent track record using high-throughput screening with chick embryos and morpholinos either in terms of characterizing gene regulatory networks (GRNs) or assaying for developmental phenotypes related to the neural crest. Moreover, work from the Bronner and Sauka-Spengler labs has previously contributed much in the way of our understanding of the GRNs that direct the delineation of the neural and non-neural lineages in the ectoderm. A discussion of how the current results fit into the larger framework of GRNs (both for known and novel genes) would provide a more complete context for the work. A schematic figure that maps these genes onto a GRN could be quite informative and clarifying.Nonetheless, the results are significant in that they advance our understanding of the spatial and temporal expression of genes that are associated with cell specification and lineage restriction during the embryonic time course from gastrulation to neurulation. The conclusions are further supported by a modified RNA velocity analysis that reconstructs the temporal sequence of transcriptional steps and resolves gene-specific transcriptional dynamics over time. Importantly, based on this analysis, the authors find that cells from the emerging neural plate border are more heterogeneous than previously believed and they do not see the emergence of neural crest cells as a distinct lineage until later than what has been suggested by other studies.Overall, the authors could do more in both the Introduction and the Discussion to emphasize exactly how their current study advances the field beyond simply describing the timing of specification and lineage restriction. This would be especially helpful since the authors cite earlier work from the Bronner lab , which demonstrates that significant co-expression of neural crest, placode, and CNS markers persists in the neural plate border from gastrulation through neurulation. In fact, this earlier work has a similar conclusion that cells at the neural plate border contribute to multiple ectodermal lineages throughout neurulation and even after neural tube closure.The sample sizes of embryos and numbers of cells collected are unclear. For example, the authors state that they isolate 2398 cells from 8 embryos  at stage HH4. Does this total number consist of approximately 300 cells per embryo? The authors should explain why this number is sufficient as a representative and unbiased sample size in light of some reports that estimate up to 50,000 epithelial cells in the epiblast at this stage . In the Methods section they state that "approximately 10,000 cells/stage were collected" and so it is hard to make sense of the sample sizes, etc. The authors should include the total number of embryos (n) for each RNA-seq analysis performed along with the number of cells .Moreover, how can the authors claim with certainty that they are "profiling the majority of neural plate border cells" ? Could there be other cells in the neural plate border that do not express Pax7 and Tfap2A? For each experiment, the authors should try to estimate how many cells (or what percentage) are not included in their analyses and discuss what the implications are for the interpretation of their results. A supplemental data table with total number of cells collected for each embryo at each stage in each experiment, would be helpful.Given that HCR is also a quantitative technique and given that the authors use words like "stronger" or "decreased" to describe spatial and temporal changes in gene expression, the authors should try to measure levels  of expression among these markers and novel genes either relative to one another and/or over time.Although the authors generate an intriguing list of genes that are co-expressed at the right time and place, they should refrain from equating "expression" with "function"  given that the authors have not tested a role for any of the new genes that they have identified in their dataset. Also, the authors spend much of the Discussion describing previous experimental work for some of the genes included in their dataset. Here too, the authors should temper and contextualize their conclusions taking into account the fact that the presence of a specific transcript does not always correspond to actual gene function and protein activity, especially since there are numerous examples of post-transcriptional  regulation for many of these genes.Reviewer #2:This study performs single-cell transcriptome analysis of chicken embryos from gastrulation to neurulation stages (HH4-HH7) with the goal of understanding the emergence and transition of the neural plate border domain to placodal and neural crest lineages. The main impact of the study is the first detailed single-cell analysis of early chick embryos, which should complement similar studies in human, mouse, and other vertebrates. Major cell types are described at each stage, and this is coupled with in situ hybridization for a set of known and novel genes, as well as RNA velocity to deduce cell trajectories (based on the ratio of old cytoplasmic to new nuclear transcripts). Based on the absence of a distinct Pax7/Tfap2a cluster during gastrulation stages, the authors make an argument that the neural plate border and placode/neural crest does not emerge until later stages (i.e. neurulation), later than previously reported. However, the study largely falls short of making significant new insights into the timing and lineage trajectories of placodes and neural crest. The manuscript is very dense with descriptive data of gene expression in numerous clusters, which makes it difficult to extract big picture messages about lineage emergence. There are also numerous typos and figure errors that make the reading difficult. The RNA velocity analysis is not particularly convincing as to lineage emergence, and there are numerous overstatements about the ability of such single-cell genomics approaches to define in vivo lineages in the absence of experimental confirmation. While some new genes with neural plate border expression are presented, others are already well known or are shown to have very broad expression, thus limiting their utility in defining domains. There is a feeling that this work is quite preliminary in terms of its analysis of neural plate border lineages, though it is clearly an important resource for the chick embryology community.1. Several statements are made as to lineage analysis, e.g. with relation to Pax7+ cells. Single-cell analysis can only make predictions about lineages, which need to be experimentally confirmed. These statements should therefore be removed or more carefully explained. For example, lines 51-52  : "We further demonstrate that Pax7+ cells are not restricted to a neural crest fate and are capable of giving rise to all derivatives of the neural plate border."2. In the Intro, it stated that the study identifies numerous novel factors, but the in situs presented show a combination of novel factors and many known factors , with several of the "novel" genes (e.g. Ing5) being much broader than just prospective NPB territory. Similarly in Figure 4, many of the in situ markers are quite broad and therefore it is hard to determine their utility in defining specific domains (e.g. Gbx2 and Znf703). It is also an overstatement to say the study has identified key drivers of NPB trajectories in the absence of functional assays.3. The known roles of Irf6 and Grhl3 in driving periderm fate should be better integrated in the single-cell analysis. The in situs confirm that these are expressed quite broadly and mainly in the overlying periderm.4. The scVelo in Figure 5 is not particularly informative. From the various arrows and UMAPs shown, its hard to distill a clear theme of cell transitions. For example in panel F, how does the data specifically inform bifurcation of placodal and neural crest ectoderm?5. What is "neural-neural crest"?6. There appears to be an error in Figure 6A preventing the top left of the plot from being visualized. An image from panel D seems to be pasted by mistake. In general, there are many typos/errors in the manuscript that further make it difficult to follow.7. It is unclear what the colors mean in Figure 6E,F. Figure S5I – the legend is similarly insufficient to understand the panels, e.g. no description of what colors means.8. What is the evidence that mitochondrial genes at HH4 indicative of highly active migrating cells?9. HH6-Cl2 is stated to be anterior lateral plate mesoderm, but Pitx2 and Alx1 are also markers of frontonasal neural crest mesenchyme. How do the authors distinguish between these possibilities?10. In Figure S1B, ElalL1 and Tgfi1 are used as epiblast stem cell markers but appear to be very broadly expressed. Also in Figure S1F, the genes used to define the Node are not very specific.11. The in situ in Figure S4D is not described in legend or annotated in actual panel.Reviewer #3:In this study, Williams and colleagues use single cell transcriptomics to describe the cell fates and lineages in the dorsal ectoderm of chick embryos taken from gastrula to early neurula stage. Specifically, they provide an atlas of whole embryo epiblast at stages 4,HH, 5HH, 6HH and 7H. They further subcluster the ectoderm cells and use cVelo algorithm (based on velocity of RNA splicing) to infer trajectories and lineages in this dataset.Description of each stage and each cluster of cells is carefully done and retrieves the canonical markers for each territory. The neural plate border is found expressing pax7 early on, as previously described in chick embryos  but a specific clustering of these cells is not found, suggesting that the identity of the neural plate border is rather the overlap of gene signatures from adjacent tissues and that the neural crest and the placode signatures arise at the early neurula stage, in the elevating neural folds of the embryo.From previous lineage tracing studies done at the gastrula stage, it was shown that the border between the prospective neural plate and the future non-neural ectoderm gives rise to four main cell fates: dorsal neural tube cells, neural crest cells, posterior placodal cells and non-neural ectoderm cells . Genetically, this territory has previously been defined by the overlap between gene expressions defining the non-neural ectoderm and the neural ectoderm Previous transcriptomic studies have pointed out the high similarity of the neural plate border territory compared to adjacent ectoderm regions, the failure of "classical" biostatistics tools to evidence a specific signature and the need for tailored strategies to do so . Using those, the neural plate border could be defined from gastrula stage by its expression of pax3/pax7 ortholog and a couple of other genes, then by a more extended signature at neurulation stage.In conclusion, although this study explores the same question with the latest tools of single cell transcriptomics, it is mostly descriptive and brings little novel insight into the biology of neural and neural plate border induction. However, it highlights a series of additional genes that could be of interest for further functional study.In order to increase the impact of this study, functional analysis of some key genes should be added. Previous works from the same authors have elegantly shown how various regulators influence cell fates in the neural crest gene regulatory network.eLife. Your revised article has been evaluated by Kathryn Cheah (Senior Editor) and a Reviewing Editor.Thank you for resubmitting your work entitled "Segregation of neural crest specific lineage trajectories from a heterogeneous neural plate border territory only emerges at neurulation" for further consideration by The feedback of the reviewers indicate that the revision addresses most of original concerns and now fits better as a Resources paper. While the manuscript has been improved, there are some remaining issues that need to be addressed, as outlined below:Consider modifying the title and summary to broaden the coverage of subject beyond the neural plate border cell populationTake into consideration of that the inference of molecular trajectory of cell population and the transcriptional network/s driving lineage development are hypothetical in the context of the origin of the neural crest cells at this juncture and tune the Discussion accordingly.Address the critique of the data presented in Figures 5 and 6:The computational results on the developmental trajectory  purportedly showed the connectivity of cell types at four developmental stages separately. As these are snapshots of the "transcriptome proximity" between cell types (whole epiblast/extracted ectoderm sub-clusters) at a single timepoint, it is not biological meaningful for inferring a developmental trajectory of cell population in time. These results (and the accompanying description of the data in Results) may be provided as supplementary information.Enhance the visibility of the findings of scRNA velocity : The RNA velocity measurement across the four stages may be more appropriate for inferring the developmental trajectory of cell types across HH6-HH7. For more clarity, it may be helpful to highlight the predominant velocity vectors between the cell types, as some individual vectors appeared to be outliers .Please provide information on the development of the web portal and its state of accessibility. If possible, provide user feedback on a trial run to evaluate the utility and effectiveness of the web interface, which may be presented as supplementary information of revised manuscript. [Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.][…] There is no follow-up verification of the functional attributes of these drivers or the molecular network in the development of these two lineages. The merit of this study would be enhanced if functional analysis has been undertaken to identify which are the key drivers and their functional role in the segregation of the two divergent neural border cell lineages and the early steps of differentiation of the neural crest cells.Thank you for the useful comments. We agree that functional experiments would be very valuable and we have initiated some of these, but we also feel that given the myriad of new genes, finding the essential drivers will not be an easy task and would likely take an enormous amount of time execute in a controlled and validated fashion. Given the pandemic, we feel that these experiments would not be feasible in a reasonable amount of time. Moreover, the present manuscript is already overly long. We have endeavoured to make it clearer and more concise in the revised version. Therefore, we agree with the idea presented by the Senior Editor that the present dataset would make a very valuable Resource paper without adding functional data.Re-submission as a resource report will require provision of the missing detail of the experimental design of the single-cell transcriptome analysis and the data analytics pipeline, improving the style of presentation to allow a better comprehension of the important novel findings of data mining. addressing the utility and limitation of the transcriptome dataset to gains knowledge that enables the formulation of testable hypothesis on the molecular activity driving neural plate development. emergence of the neural plate border cell lineages.We thank the editor and reviewers for giving us the option to resubmit the paper as a Resource. Accordingly, we have amended the manuscript to address the very useful comments of the reviewers as described below. We are also in the process of uploading all our data sets to a web-based user interface such that readers can explore the data in its entirety.Reviewer #1:[…] A discussion of how the current results fit into the larger framework of GRNs (both for known and novel genes) would provide a more complete context for the work. A schematic figure that maps these genes onto a GRN could be quite informative and clarifying.We thank the reviewer for this insightful comment. To address this, we have added discussion of how some of the genes identified here fit into the broader neural crest gene regulatory network using previously published data  (lines 384-386 and 392-394). While the idea of putting some of the novel genes described here into a GRN is very attractive, it is premature in the absence of functional data since it is not possible to construct a GRN on expression data alone; this would require epistatic/regulatory data which is outside the scope of the current work.Overall, the authors could do more in both the Introduction and the Discussion to emphasize exactly how their current study advances the field beyond simply describing the timing of specification and lineage restriction. This would be especially helpful since the authors cite earlier work from the Bronner lab , which demonstrates that significant co-expression of neural crest, placode, and CNS markers persists in the neural plate border from gastrulation through neurulation. In fact, this earlier work has a similar conclusion that cells at the neural plate border contribute to multiple ectodermal lineages throughout neurulation and even after neural tube closure.Thank you for noting this lack of information. To address this point, we have amended parts of the introduction and discussion as suggested. In particular we emphasize how our analysis expands on previous work (lines 38-41) and how our whole epiblast sc-RNA-seq data sets provide a contextual environment for understanding how the neural plate border emerges during early neurulation and diverges from the surrounding neural and non-neural ectoderm (line 381). We also further discuss how the genes identified here might fit into the broader neural crest GRN (lines 382-394) and we highlight the notion that neural plate border cells are not a unique population characterized by an exclusive gene expression signature, but rather that they share features with the surrounding tissues (lines 409-415).The sample sizes of embryos and numbers of cells collected are unclear. For example, the authors state that they isolate 2398 cells from 8 embryos  at stage HH4. Does this total number consist of approximately 300 cells per embryo? The authors should explain why this number is sufficient as a representative and unbiased sample size in light of some reports that estimate up to 50,000 epithelial cells in the epiblast at this stage . In the Methods section they state that "approximately 10,000 cells/stage were collected" and so it is hard to make sense of the sample sizes, etc. The authors should include the total number of embryos (n) for each RNA-seq analysis performed along with the number of cells .Moreover, how can the authors claim with certainty that they are "profiling the majority of neural plate border cells" ? Could there be other cells in the neural plate border that do not express Pax7 and Tfap2A? For each experiment, the authors should try to estimate how many cells (or what percentage) are not included in their analyses and discuss what the implications are for the interpretation of their results.We apologize for this lack of clarity. We have now added the number of embryos and cells used in the analysis to the text  and also provide a supplemental table detailing the number of embryos/cells used at each stage. Along with the CellRanger output.It is likely that the epiblast contains up to 50,000 cells; however approximately 50% of cells may be lost during the dissociation/FACS process. Furthermore, the 10X Chromium platform has limited loading capacity (46.6ul), and as it is not advisable to spin down cells and resuspend in a smaller volume, the number cells loaded is restricted. Moreover, the 10X Chromium platform can only recover up to 10,000 cells, so overloading is not advantageous. The percentage of cells we recover is largely within the 10X guidelines of 45-60%, the exception was HH4 (30%) however this was performed with v2 10X chemistry.Given that we resolve numerous clusters that clearly represent each germ layer and sub-divisions thereof, we believe these are sufficient numbers of cells to construct an unbiased single-cell atlas at each stage. Moreover, we record high quality gene expression metrics indicating the cells were of good quality . We have now clarified these points in the text and apologize that this was not clearer in the first version of the manuscript.A supplemental data table with total number of cells collected for each embryo at each stage in each experiment, would be helpful.Thank you for this excellent suggestion. This is now provided in the supplemental section.Given that HCR is also a quantitative technique and given that the authors use words like "stronger" or "decreased" to describe spatial and temporal changes in gene expression, the authors should try to measure levels  of expression among these markers and novel genes either relative to one another and/or over time.We appreciate the reviewers point here. While HCR can be quantitative if performed at nonsaturating levels, embryos must be processed concomitantly and under exactly the same conditions to make accurate comparisons. As we did not prepare the whole mount embryos in this way, it would be no trivial undertaking to repeat all the HCR’s, imaging and quantification. Furthermore, in the broader context of this work, the HCR analysis was done to provide validation of novel genes identified in the sc-RNA-seq data sets, and to uncover putative candidates for further investigation. However, we recognize the need for quantification here, as such we now provide the fold change values where applicable from the sc-RNA-seq data for genes shown in HCR. This information has been added on the relevant feature plots in figures 3 and 4. We have also altered our wording accordingly such that our description refers to qualitative rather than quantitative changes in gene expression levels .Although the authors generate an intriguing list of genes that are co-expressed at the right time and place, they should refrain from equating "expression" with "function"  given that the authors have not tested a role for any of the new genes that they have identified in their dataset. Also, the authors spend much of the Discussion describing previous experimental work for some of the genes included in their dataset. Here too, the authors should temper and contextualize their conclusions taking into account the fact that the presence of a specific transcript does not always correspond to actual gene function and protein activity, especially since there are numerous examples of post-transcriptional  regulation for many of these genes.We thank the reviewer for raising this concern. We have now modified the text  to be more circumspect. We have also added references here to support our discussion of previous work .Reviewer #2:[…]1. Several statements are made as to lineage analysis, e.g. with relation to Pax7+ cells. Single-cell analysis can only make predictions about lineages, which need to be experimentally confirmed. These statements should therefore be removed or more carefully explained. For example, lines 51-52  : "We further demonstrate that Pax7+ cells are not restricted to a neural crest fate and are capable of giving rise to all derivatives of the neural plate border."We thank the reviewer for this comment and agree that it is important to distinguish between gene expression and lineage relationships. Accordingly, we have adjusted the text to dampen down these claims . Indeed, this was a most interesting finding which we intend to follow up experimentally and include in future publications.2. In the Intro, it stated that the study identifies numerous novel factors, but the in situs presented show a combination of novel factors and many known factors , with several of the "novel" genes (e.g. Ing5) being much broader than just prospective NPB territory. Similarly in Figure 4, many of the in situ markers are quite broad and therefore it is hard to determine their utility in defining specific domains (e.g. Gbx2 and Znf703). It is also an overstatement to say the study has identified key drivers of NPB trajectories in the absence of functional assays. genes together with novel genes to observe co-expression in this region. We have now added this information in the text (line 170-171). We appreciate that the expression pattern of some of the genes shown here have previously been described, but not in the context of neural plate border development. We have attenuated the text accordingly and added citations (line 207 and 225).The reviewer raises an interesting point. Indeed, we believe it is a combination of transcription and signaling factors (both novel and known), that are involved in refinement of the neural plate border. For our in situ analysis, we combined probes to known neural plate border genes Indeed, many of the genes explored in this study are expressed more broadly than the neural plate border, in keeping with the notion that the neural plate border is not defined by an exclusive set of genes. Rather, it is the combination of genes co-expressed across this region that are differentially shared with surrounding tissues. We have reinforced this point in the text line (lines 409-415). We have also toned down the text regarding key drivers of specific trajectories .3. The known roles of Irf6 and Grhl3 in driving periderm fate should be better integrated in the single-cell analysis. The in situs confirm that these are expressed quite broadly and mainly in the overlying periderm.Irf6 and Grhl3 in periderm formation and indeed Van der Woude syndrome. We thank the reviewer for bringing this information to our attention (lines 388-391).We now mention the roles of 4. The scVelo in Figure 5 is not particularly informative. From the various arrows and UMAPs shown, its hard to distill a clear theme of cell transitions. For example in panel F, how does the data specifically inform bifurcation of placodal and neural crest ectoderm?Pax7 expression is demonstrated in the feature plots shown alongside . We hope this makes this point clearer. We have also further clarified this in the text (lines 279-281).Thank you for pointing out that this was not sufficiently clear. We have attempted to improve the visualisation of scVelo analysis by showing alternative plots in Figures 5 and 6. In these the arrows represent an average velocity across given clusters such that fewer but bolder arrows are shown. We have also removed the shading around the Pax7+ zone in Figure 5F as 5. What is "neural-neural crest"?We apologise for not making this description clear. The split in neural crest cells between neural potential and mesenchymal potential has previously been described in this way  and we now clarify this in the text (line 293-296).6. There appears to be an error in Figure 6A preventing the top left of the plot from being visualized. An image from panel D seems to be pasted by mistake. In general, there are many typos/errors in the manuscript that further make it difficult to follow.We apologise for this problem which we failed to notice in the previous submission. Similarly, we have endeavoured to identify and correct other typos and figure errors. We thank the reviewer for pointing out this problem.7. It is unclear what the colors mean in Figure 6E,F. Figure S5I – the legend is similarly insufficient to understand the panels, e.g. no description of what colors means.Thank you for pointing out this lack of clarity here. We now describe this better and define the meaning of the colors in the figure legends. We have also added scale bars on the figures and describe the color correlation in the figure legends.8. What is the evidence that mitochondrial genes at HH4 indicative of highly active migrating cells?The reviewer raises a good point. There is no evidence that mitochondrial genes indicate active migration, but since we also detected cell migration genes in the same cluster, we thought the high levels of mitochondrial activity may represent highly active migrating cells. However, we recognize this is an over-interpretation and have removed this statement (line 445-446).9. HH6-Cl2 is stated to be anterior lateral plate mesoderm, but Pitx2 and Alx1 are also markers of frontonasal neural crest mesenchyme. How do the authors distinguish between these possibilities?ShisA2, Sfrp1, OlfmL3, Six1 and Twist1. While some of these genes are indeed expressed in other tissues, collectively their shared expression is most dominant in the LPM. We have now added these examples to the text in the supplementary Results section (line 450). If the reviewers and editor so desire, we could add HCR of Pitx2 and Alx1 to clarify their location at HH6.Interesting point. We now clarify that HH6-Cl2 is also enriched for other lateral plate mesoderm (LPM) genes, including; 10. In Figure S1B, ElalL1 and Tgfi1 are used as epiblast stem cell markers but appear to be very broadly expressed. Also in Figure S1F, the genes used to define the Node are not very specific.Elav1 and Tgif are broadly expressed, but they are enriched 0.479 and 0.472 average fold change, respectively, in HH4-Cl2. We now include this information on the feature plots in Figure. S1B. We had difficultly annotating HH5-Cl7  and we agree the genes shown on the heatmap are not indicative of the node. We originally assigned this cluster as node based on less enriched genes not shown here. We have now relabeled this cluster as ‘Miscellaneous’ since the top enriched genes represent a myriad of cellular processes.We agree that 11. The in situ in Figure S4D is not described in legend or annotated in actual panel.We thank the reviewer for noting this over sight. We have now annotated the in situ image and describe it in the legend.Reviewer #3:[…]In order to increase the impact of this study, functional analysis of some key genes should be added. Previous works from the same authors have elegantly shown how various regulators influence cell fates in the neural crest gene regulatory network.We thank the reviewer for their comments and appreciate the fact that it would be ideal to include functional experiments. That said, the manuscript is already overly long. More importantly, it would take us +1 year to test the new transcription factors described here and assemble them into a meaningful gene regulatory network. Thus, we would prefer to publish the paper as a Resource (as suggested) and follow-up with detailed functional analysis at a later time.ReferencesDev Cell, 51, 255-276 e7.Williams, R. M., Candido-Ferreira, I., Repapi, E., Gavriouchkina, D., Senanayake, U., Ling, I. T. C., Telenius, J., Taylor, S., Hughes, J. and Sauka-Spengler, T. 2019. Reconstruction of the Global Neural Crest Gene Regulatory Network in vivo. [Editors’ note: what follows is the authors’ response to the second round of review.]The feedback of the reviewers indicate that the revision addresses most of original concerns and now fits better as a Resources paper. While the manuscript has been improved, there are some remaining issues that need to be addressed, as outlined below:Consider modifying the title and summary to broaden the coverage of subject beyond the neural plate border cell populationWe have now changed the title and edited the text in the abstract and introduction to describe this study more broadly.Take into consideration of that the inference of molecular trajectory of cell population and the transcriptional network/s driving lineage development are hypothetical in the context of the origin of the neural crest cells at this juncture and tune the Discussion accordingly.We have adjusted the text accordingly to reflect the hypothetical nature of lineage trajectory analysis.Address the critique of the data presented in Figures 5 and 6:The computational results on the developmental trajectory  purportedly showed the connectivity of cell types at four developmental stages separately. As these are snapshots of the "transcriptome proximity" between cell types (whole epiblast/extracted ectoderm sub-clusters) at a single timepoint, it is not biological meaningful for inferring a developmental trajectory of cell population in time. These results (and the accompanying description of the data in Results) may be provided as supplementary information.We have now moved this data and accompanying text to the supplemental section, this now makes supplemental figure 6. The main manuscript is now 5 figures and we have adjusted the figure citations throughout.Enhance the visibility of the findings of scRNA velocity : The RNA velocity measurement across the four stages may be more appropriate for inferring the developmental trajectory of cell types across HH6-HH7.We have included scVelo data from stages HH5/6/7/8. We did not find that including HH4 and excluding HH8 was useful.For more clarity, it may be helpful to highlight the predominant velocity vectors between the cell types, as some individual vectors appeared to be outliers .We appreciate the reviewers remark however, having already changed the velocity plots here (now figure 5) to the big, bold, averaged arrows to be clearer, we feel adding any more annotation will only further complicate the results as there is already lots of colour and arrows we don’t feel more annotation would help.Please provide information on the development of the web portal and its state of accessibility. If possible, provide user feedback on a trial run to evaluate the utility and effectiveness of the web interface, which may be presented as supplementary information of revised manuscript.All the data from this study is now available on the Single Cell Portal. This has been trialed by colleagues and corrected accordingly. This will be made publicly available once the paper is formally accepted.