FaceBase: A Community-Driven Hub for Data-Intensive Research

Abstract

The FaceBase Consortium, funded by the National Institute of Dental and Craniofacial Research of the National Institutes of Health, was established in 2009 with the recognition that dental and craniofacial research are increasingly data-intensive disciplines. Data sharing is critical for the validation and reproducibility of results as well as to enable reuse of data. In service of these goals, data ought to be FAIR: Findable, Accessible, Interoperable, and Reusable. The FaceBase data repository and educational resources exemplify the FAIR principles and support a broad user community including researchers in craniofacial development, molecular genetics, and genomics. FaceBase demonstrates that a model in which researchers "self-curate" their data can be successful and scalable. We present the results of the first 2.5 y of FaceBase's operations as an open community and summarize the data sets published during this period. We then describe a research highlight from work on the identification of regulatory networks and noncoding RNAs involved in cleft lip with/without cleft palate that both used and in turn contributed new findings to publicly available FaceBase resources. Collectively, FaceBase serves as a dynamic and continuously evolving resource to facilitate data-intensive research, enhance data reproducibility, and perform deep phenotyping across multiple species in dental and craniofacial research.

Keywords: craniofacial abnormalities; data curation; developmental biology; genomics; molecular genetics; morphogenesis.

Figure 1.

Growth and diversification of the FaceBase hub data collection. (A) Contributing research projects that have joined FaceBase and released data sets since the second half of 2019; (B) data sets released through FaceBase from new projects; (C) new experiment or assay types now being reported in data sets as a count of the distinct “experiment type” vocabulary terms used to label data sets; (D) biosample characteristics being reported in data sets as a count of the distinct “gene,” “genotype,” and developmental “stage” vocabulary terms used to label data sets; and (E) new data files across all newly released data sets.

Figure 2.

Online visualization capabilities in the FaceBase repository. (A) High-resolution histological data with built-in annotation editing and display, (B) image volumes with orthogonal slice and 3-dimensional rendering, (C) surface meshes with landmarks and measurements between pairwise combinations of landmarks, (D) genome annotation track visualization, and (E) interactive single-cell visualization through integration with the UCSC Cell Browser.

Figure 3.

Overview of the FaceBase data analysis and integration with current knowledge of craniofacial anomalies. To identify spatiotemporal expression and role of genes and noncoding RNAs, FaceBase data were analyzed with various bioinformatic tools and methodologies. In addition, the genes and noncoding RNAs predicted through these bioinformatic analyses were cross-referenced with genes and microRNAs reported in craniofacial anomalies (e.g., cleft lip, cleft palate) in humans and mice. The regulatory networks and functions of the candidate genes and microRNAs were further experimentally validated. Some of these findings have been stored at our database, CleftGeneDB, which is publicly available at https://bioinfo.uth.edu/CleftGeneDB/, and the processed data were also deposited into FaceBase (10.25550/1-YPS4 and 10.25550/1-F5A6).