Defining the p63 regulatory network driving periderm development in the mouse

定义驱动小鼠周皮发育的 p63 调控网络

• 批准号: BB/V011626/1
• 负责人: Michael Dixon
• 金额: $ 76.34万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FV011626%2F1
• 关键词: Defining; p63; regulatory; network; driving

How cells transition between different cellular states is a fundamental biological question. In this context, the simple ectoderm passes through a dynamic series of cell states to produce a self-replenishing, multi-layered epidermis that protects the organism from dehydration, mechanical trauma, and microbial invasion. The first stratification event results in the formation of a layer of flattened periderm cells. Periderm development commences on the tail and limbs before spreading over the torso and face so that the embryo is covered by embryonic day (E)14; all stages of periderm development are therefore present in individual E11.5 embryos.Periderm functions as an embryonic barrier that prevents pathological adhesion between epithelia during development. Failure of periderm formation underlies several birth defects that are characterised by webbing of the skin across the major joints, cleft lip and/or palate, fusion of the fingers and/or toes, and genital malformations.While we have demonstrated that the transcription factor DeltaNp63Alpha (DNp63A) is a key regulator of periderm development, the regulatory networks controlling this fundamentally important cell layer are poorly characterised; this is a barrier to understanding a major event in epidermal development and in dissecting disease pathogenesis.We have assembled a team of investigators with expertise in developmental biology, gene regulation, and computational biology with the aim of delineating the regulatory interactions that drive cells to delaminate from the ectoderm to form periderm. Two objectives will be addressed:1. Predicting the regulatory networks driving mouse periderm formation at single-cell (sc) resolution: We will define the transcriptome of the developing periderm by performing scRNA-seq analysis of skin dissected from E11.5 wild-type mice in which all stages of periderm development are present. Clustering algorithms will be used to identify sub-populations of cells and expression of their 'marker genes' will be analysed to reconstruct the populations into a tissue context. Developmental trajectories will be inferred computationally allowing us to study the relationships of the clusters during development.To identify regulatory elements, we will perform scATAC-seq analysis and infer the interactions of transcription factors and their target genes. We will link open regulatory regions to their target genes and use the scATAC-seq data to infer potential upstream regulators through differential enrichment of transcription factor binding motifs. Evolution of the regulatory networks driving periderm development will be analysed computationally.Deliverables: We will predict the regulatory networks driving periderm development at single-cell resolution allowing us to formulate hypotheses about the DNp63A regulatory cascade.2. Dissecting the molecular cascade downstream of the transcription factor DNp63A: We will use the data generated in Objective 1 to extend the DNp63A regulatory network. We will perform scRNA-seq and scATAC-seq analyses of skin dissected from E11.5 Tp63-null mice and perform computational analyses to investigate how the predicted regulatory networks are perturbed.The inferred regulatory interactions will be verified experimentally. Direct transcriptional targets of DNp63A will be confirmed by ChIP-qPCR analysis of E11.5 skin. Subsequently, we will extend the ChIP-qPCR analyses to the second layer of network regulation. To analyse whether the transcription factors act as activators or repressors, we will perform luciferase reporter assays and deadCas9-mediated CRISPR activation/inhibition studies.Deliverables: We will validate the DNp63A regulatory network driving periderm development at single-cell resolution.The data will provide mechanistic insights into cell state transitions during development and will have potential impact in determining the pathogenesis of a series of congenital disorders.

细胞如何在不同的细胞状态之间转换是一个基本的生物学问题。在这种情况下，简单的外胚层通过一系列动态的细胞状态产生自我补充的多层表皮，保护生物体免受脱水，机械创伤和微生物入侵。第一个分层事件导致形成一层扁平的围壁细胞。胚胎发育开始于尾部和四肢，然后扩展到躯干和面部，因此胚胎在胚胎第14天被覆盖;因此，胚胎发育的所有阶段都存在于E11.5胚胎中。牙周膜形成的失败是几种出生缺陷的基础，其特征在于主要关节上的皮肤蹼、唇和/或腭裂、手指和/或脚趾融合以及生殖器畸形。虽然我们已经证明转录因子DeltaNp 63 α（DNp 63 A）是牙周膜发育的关键调节因子，但控制这一根本性重要细胞层的调节网络的特征很差;这是理解表皮发育和解剖疾病发病机制中的主要事件的障碍。2我们已经组建了一个具有发育生物学、基因调控和计算生物学专业知识的研究小组，目的是描述驱动细胞从外胚层脱层形成外胚层的调控相互作用。将解决两个目标：1。以单细胞（sc）分辨率预测驱动小鼠牙周膜形成的调控网络：我们将通过对从E11.5野生型小鼠解剖的皮肤进行scRNA-seq分析来定义发育中牙周膜的转录组，其中存在牙周膜发育的所有阶段。聚类算法将用于识别细胞亚群，并分析其“标记基因”的表达，以将群体重建为组织背景。发育轨迹将通过计算推断，使我们能够研究发育过程中簇的关系。为了确定调控元件，我们将进行scATAC-seq分析，并推断转录因子及其靶基因的相互作用。我们将开放的调控区域连接到它们的靶基因，并使用scATAC-seq数据通过转录因子结合基序的差异富集来推断潜在的上游调控因子。可计算性：我们将预测在单细胞分辨率下驱动periodontal发展的调控网络，从而使我们能够制定关于DNp 63 A调控级联的假设。剖析转录因子DNp 63 A下游的分子级联：我们将使用目标1中产生的数据来扩展DNp 63 A调控网络。我们将对E11.5 Tp 63基因敲除小鼠的皮肤进行scRNA-seq和scATAC-seq分析，并进行计算分析，以研究预测的调控网络是如何受到干扰的。推断的调控相互作用将通过实验进行验证。DNp 63 A的直接转录靶标将通过E11.5皮肤的ChIP-qPCR分析来确认。随后，我们将ChIP-qPCR分析扩展到网络调节的第二层。为了分析转录因子是作为激活因子还是阻遏因子，我们将进行荧光素酶报告基因测定和deadCas 9介导的CRISPR激活/抑制研究。我们将验证DNp 63 A监管网络，推动单倍周皮发育这些数据将为发育过程中的细胞状态转变提供机制性见解，并将对确定一系列先天性免疫缺陷的发病机制产生潜在影响。紊乱

项目成果

PEGS: An efficient tool for gene set enrichment within defined sets of genomic intervals.

• DOI: 10.12688/f1000research.53926.2
• 发表时间: 2021
• 期刊: F1000Research
• 作者: Briggs P;Hunter AL;Yang SH;Sharrocks AD;Iqbal M
• 通讯作者: Iqbal M

Revisiting the embryogenesis of lip and palate development.

• DOI: 10.1111/odi.14174
• 发表时间: 2022-07
• 期刊: ORAL DISEASES
• 影响因子: 3.8
• 作者: Hammond, Nigel L.;Dixon, Michael J.
• 通讯作者: Dixon, Michael J.