BBSRC-NSF/BIO: Integrative analysis and Visualisation of Fly Cell Atlas datasets to enable cross-species comparisons

果蝇（Drosophila melanogaster）在上个世纪一直是遗传学研究的基础。它在许多研究领域被用作选择的模式生物，因为它提供了在实验室研究遗传学并将研究结果应用于人类遗传学的能力。它作为模型的使用是由于两个因素：首先，它的遗传密码可以在实验室中相对容易地操作，再加上生命周期短，提供了一种可以快速研究基因或途径功能的手段。其次，绝大多数基本的生化机制和途径在苍蝇和人类之间是保守的。事实上，导致人类疾病的基因中有75%在苍蝇身上发现，因此，在苍蝇身上收集的数据可用于深入了解人类体内的相同过程。单细胞RNA测序（scRNA-seq）新技术的出现，提供了关于单细胞中哪些基因是开启的或最活跃的信息。在果蝇群落中，这提供了快速绘制细胞群和细胞类型到整个解剖结构的能力，并将其与表型和功能联系起来。来自不同物种的scRNA-seq数据集的增加导致了单细胞表达图谱（scEA）的发展。这是一个门户网站，使用户能够更容易地可视化和解释这些数据。预计到2020年，苍蝇单细胞数据将从10个数据集增加到100个，到2021年将进一步增加两倍。科学利用这些数据的关键将是用户不仅能够有效地分析果蝇数据，而且能够检查果蝇数据与人类或小鼠数据集之间的相互联系。该项目将提供方法，使苍蝇数据集可以很容易地解释，并通过scEA链接到小鼠和人类数据集。scEA目前拥有超过500K次分析的scRNA-seq数据，其中包括人类细胞图谱（HCA）和小鼠细胞图谱（MCA）等数据。将开发分析管道，以结合现有的和新兴的数据集，以及必要的计算基础设施来托管蝇细胞图谱（FCA）数据集。ScEA将为用户提供具有探索性查询功能的易于导航的web服务，以及用于进一步数据分析的数据下载功能。该服务将与已建立的果蝇资源，Flybase， Virtual fly Brain和哈佛大学果蝇资源充分整合。该项目还将开发数据集注释的流程。这一注释步骤为数据增加了额外的科学信息，为用户提供了更高水平的生物学理解，从而有助于解释和分析。该注释将扩展现有的FlyBase解剖本体，该本体是一种用于描述苍蝇解剖结构的受控词汇表结构，这将确保在新的和现有资源之间具有完全的兼容性。scEA将开发并提供方法，使数据可以很容易地可视化和挖掘细胞类型，同时也为苍蝇社区提供贡献科学专业知识的能力。scEA用户界面将进一步开发，以提供更高水平的跨物种查询能力，因为由此产生的FCA将在scEA内与HCA， MCA和任何进一步的数据集相关联，从而实现跨物种比较，这将有助于发现新的生物学见解。该项目旨在为果蝇社区提供连接、再利用和重新分析数据集的实用解决方案，从而缩小将模式生物（如果蝇）的生物学发现转化为人类的差距，反之亦然。这个项目将使这种比较分析的结果迅速提供给不断增长的用户群体。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The fruit fly, Drosophila melanogaster, has for the last century been fundamental to the study of genetics. It is used in many areas of research as the model organism of choice, as it provides the ability to study genetics in the laboratory and apply findings to human genetics. Its use as a model is due to two factors: First, its genetic code can be relatively easily manipulated in the laboratory and this coupled with a short life cycle, provides a means by which a gene or pathway function can be rapidly studied. Secondly, the vast majority of the fundamental biochemical mechanisms and pathways are conserved between fly and humans. Indeed, 75% of the genes that cause human disease are found in fly and, thus, the data collected in the fly can be used to provide insights into the same processes within humans. The emergence of a new technology, single cell RNA sequencing (scRNA-seq), has provided information as to which genes are switched on or most active from a single cell. Within the fly community this provides the ability to quickly map clusters of cells and cell types to the whole anatomy and link this to both phenotype and function. The increasing number of scRNA-seq datasets from different species has resulted in the development of the Single Cell Expression Atlas (scEA). This is a web portal which enables users to more easily visualize and interpret this data. It is anticipated that the level of fly single cell data will increase from 10 datasets to ~100 in 2020 and further two-fold increase in 2021. Key to the scientific exploitation of this data will be the ability of users to not only effectively analyze the fly data but also to examine the interconnections between fly data and human or mouse datasets. This project will provide the means by which fly datasets can be easily interpreted and also linked to mouse and human datasets via scEA. The scEA currently hosts scRNA-seq data for over 500K assays and this includes data for the Human Cell Atlas (HCA) and Mouse Cell Atlas (MCA), amongst others. Analysis pipelines will be developed to combine the available and emerging datasets, alongside the necessary computational infrastructure to host the Fly Cell Atlas (FCA) datasets. ScEA will provide users with an easy to navigate web service with exploratory querying capability, in addition to data download capabilities for further data analysis. The service will be fully integrated with the established fly resources, Flybase, Virtual Fly Brain and the Drosophila Resources at Harvard University. This project will also develop a process for annotation of the datasets. This annotation step adds additional scientific information to the data which provides the user with a greater level of biological understanding and so aids the interpretation and analysis. This annotation will expand on the existing FlyBase anatomy ontology which is a structure of controlled vocabularies used to describe the anatomy of the fly this will ensure that there is full compatibility across new and existing resources. The scEA will develop and provide the means by which the data can be easily visualized and mined for cell types, while also providing the fly community with the ability to contribute their scientific expertise to the annotation. The scEA user interface will be further developed to provide a greater level of cross species query ability as the resulting FCA will be linked within scEA to the HCA, MCA and any further datasets enabling cross species comparisons which will aid in the discovery of novel biological insights. This project aims to provide the fly community with practical solutions for connecting, re-using and reanalyzing datasets and so will close the gap in translating biological discoveries in model organisms, such as the fruit fly, to humans and vice versa. This project will make the results of this comparative analysis rapidly available to the growing user community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.