Aryal Sandeep, Anand Deepti, Huang Hongzhan, Reddy Ashok P, Wilmarth Phillip A, David Larry L, Lachke Salil A
Department of Biological Sciences, University of Delaware, Newark, DE 19716 USA.
Center for Bioinformatics & Computational Biology, University of Delaware, Newark, DE 19713 USA.
Res Sq. 2023 Mar 17:rs.3.rs-2652395. doi: 10.21203/rs.3.rs-2652395/v1.
To expedite gene discovery in eye development and its associated defects, we previously developed a bioinformatics resource-tool iSyTE (integrated Systems Tool for Eye gene discovery). However, iSyTE is presently limited to lens tissue and is predominantly based on transcriptomics datasets. Therefore, to extend iSyTE to other eye tissues on the proteome level, we performed high-throughput tandem mass spectrometry (MS/MS) on mouse embryonic day (E)14.5 retina and retinal pigment epithelium combined tissue and identified an average of 3,300 proteins per sample (n=5). High-throughput expression profiling-based gene discovery approaches-involving either transcriptomics or proteomics-pose a key challenge of prioritizing candidates from thousands of RNA/proteins expressed. To address this, we used MS/MS proteome data from mouse whole embryonic body (WB) as a reference dataset and performed comparative analysis-termed "in silico WB-subtraction"-with the retina proteome dataset. In silico WB-subtraction identified 90 high-priority proteins with retina-enriched expression at stringency criteria of ³2.5 average spectral counts, ³2.0 fold-enrichment, False Discovery Rate <0.01. These top candidates represent a pool of retina-enriched proteins, several of which are associated with retinal biology and/or defects (e.g., Aldh1a1, Ank2, Ank3, Dcn, Dync2h1, Egfr, Ephb2, Fbln5, Fbn2, Hras, Igf2bp1, Msi1, Rbp1, Rlbp1, Tenm3, Yap1, etc.), indicating the effectiveness of this approach. Importantly, in silico WB-subtraction also identified several new high-priority candidates with potential regulatory function in retina development. Finally, proteins exhibiting expression or enriched-expression in the retina are made accessible in a user-friendly manner at iSyTE (https://research.bioinformatics.udel.edu/iSyTE/), to allow effective visualization of this information and facilitate eye gene discovery.
为了加快在眼睛发育及其相关缺陷方面的基因发现，我们之前开发了一种生物信息学资源工具iSyTE（用于眼睛基因发现的集成系统工具）。然而，iSyTE目前仅限于晶状体组织，并且主要基于转录组学数据集。因此，为了在蛋白质组水平上将iSyTE扩展到其他眼睛组织，我们对小鼠胚胎第14.5天（E14.5）的视网膜和视网膜色素上皮联合组织进行了高通量串联质谱分析（MS/MS），每个样本平均鉴定出3300种蛋白质（n = 5）。基于高通量表达谱的基因发现方法——涉及转录组学或蛋白质组学——面临着从数千种表达的RNA/蛋白质中对候选基因进行优先级排序的关键挑战。为了解决这个问题，我们使用来自小鼠全胚胎体（WB）的MS/MS蛋白质组数据作为参考数据集，并与视网膜蛋白质组数据集进行了比较分析——称为“虚拟WB减法”。在严格标准为平均光谱计数≥2.5、富集倍数≥2.0、错误发现率<0.01的情况下，虚拟WB减法鉴定出90种具有视网膜富集表达的高优先级蛋白质。这些顶级候选蛋白代表了一组视网膜富集蛋白，其中一些与视网膜生物学和/或缺陷相关（例如，Aldh1a1、Ank2、Ank3、Dcn、Dync2h1、Egfr、Ephb2、Fbln5、Fbn2、Hras、Igf2bp1、Msi1、Rbp1、Rlbp1、Tenm3、Yap1等），表明了这种方法的有效性。重要的是，虚拟WB减法还鉴定出了几种在视网膜发育中具有潜在调节功能的新的高优先级候选蛋白。最后，在iSyTE（https://research.bioinformatics.udel.edu/iSyTE/）上以用户友好的方式提供了在视网膜中表现出表达或富集表达的蛋白质，以便有效地可视化这些信息并促进眼睛基因的发现。
