Siewert Anna, Reiz Benedikt, Krug Carina, Heggemann Julia, Mangold Elisabeth, Dickten Henning, Ludwig Kerstin U
Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany.
FASTGenomics, Comma Soft AG, Bonn, Germany.
Front Cell Dev Biol. 2023 Apr 24;11:1091666. doi: 10.3389/fcell.2023.1091666. eCollection 2023.
Cleft lip ± cleft palate (CL/P) is one of the most common birth defects. Although research has identified multiple genetic risk loci for different types of CL/P (i.e., syndromic or non-syndromic forms), determining the respective causal genes and understanding the relevant functional networks remain challenging. The recent introduction of single-cell RNA sequencing (scRNA-seq) has provided novel opportunities to study gene expression patterns at cellular resolution. The aims of our study were to: (i) aggregate available scRNA-seq data from embryonic mice and provide this as a resource for the craniofacial community; and (ii) demonstrate the value of these data in terms of the investigation of the gene expression patterns of CL/P candidate genes. First, two published scRNA-seq data sets from embryonic mice were re-processed, i.e., data representing the murine time period of craniofacial development: (i) facial data from embryonic day (E) E11.5; and (ii) whole embryo data from E9.5-E13.5 from the Mouse Organogenesis Cell Atlas (MOCA). Marker gene expression analyses demonstrated that at E11.5, the facial data were a high-resolution representation of the MOCA data. Using CL/P candidate gene lists, distinct groups of genes with specific expression patterns were identified. Among others we identified that a co-expression network including and in the periderm, while it was limited to and in palatal epithelia, cells of the ectodermal surface, and basal cells at the fusion zone. The analyses also demonstrated that additional CL/P candidate genes (e.g., ) were exclusively expressed in + facial epithelial cells (i.e., as opposed to epithelial cells). The MOCA data set was finally used to investigate differences in expression profiles for candidate genes underlying different types of CL/P. These analyses showed that syndromic CL/P genes (syCL/P) were expressed in significantly more cell types than non-syndromic CL/P candidate genes (nsCL/P). The present study illustrates how scRNA-seq data can empower research on craniofacial development and disease.
唇裂±腭裂(CL/P)是最常见的出生缺陷之一。尽管研究已经确定了不同类型CL/P(即综合征型或非综合征型)的多个遗传风险位点,但确定各自的致病基因并理解相关的功能网络仍然具有挑战性。最近引入的单细胞RNA测序(scRNA-seq)为在细胞分辨率下研究基因表达模式提供了新的机会。我们研究的目的是:(i)汇总来自胚胎小鼠的可用scRNA-seq数据,并将其作为颅面研究领域的资源提供;(ii)在研究CL/P候选基因的基因表达模式方面展示这些数据的价值。首先,对来自胚胎小鼠的两个已发表的scRNA-seq数据集进行了重新处理,即代表小鼠颅面发育时间段的数据:(i)胚胎第11.5天(E11.5)的面部数据;(ii)来自小鼠器官发生细胞图谱(MOCA)的E9.5 - E13.5的全胚胎数据。标记基因表达分析表明,在E11.5时,面部数据是MOCA数据的高分辨率表示。使用CL/P候选基因列表,鉴定出具有特定表达模式的不同基因组。其中,我们发现一个共表达网络,包括外胚层表面的周皮中的 和 ,而在腭上皮、外胚层表面细胞和融合区的基底细胞中则限于 和 。分析还表明,其他CL/P候选基因(例如 )仅在 + 面部上皮细胞中表达(即与 上皮细胞相反)。MOCA数据集最终用于研究不同类型CL/P潜在候选基因的表达谱差异。这些分析表明,综合征型CL/P基因(syCL/P)比非综合征型CL/P候选基因(nsCL/P)在更多的细胞类型中表达。本研究说明了scRNA-seq数据如何能够推动颅面发育和疾病的研究。