Detecting protein-RNA interactions is challenging?both experimentally and computationally? because RNA transcripts are large in number, diverse in cellular location and function. As a result, many RNA-binding proteins (RBPs) and their cognate motifs are likely unknown or uncharacterized in humans as well as other model organisms. With increasing number of RBPs implicated in human diseases, there is an urgent need for identifying and mapping functional and phenotypic information for RBPs as well as to complete a map of the protein-RNA interaction network. The objective here is to establish a robust computational technique that integrates expression associations with sequence as well as several RBP centric features for genome-scale prediction of binding motifs for hundreds of human RBPs to facilitate the elucidation of their tissue-specific post-transcriptional networks. At the completion of this project, we expect to have developed the most advanced tool for predicting human RBP motifs and methods as well as resources which can facilitate the construction of tissue-specific RBP-RNA networks. Our central hypothesis, supported by our initial genome-scale computational study and assessment by comparative analysis of known RBP binding motifs is that, since many RBPs are involved in different stages of RNA metabolism, exon expression level associations with an RBP and other exon related features can be very powerful in identifying the binding motifs of an RBP in a tissue-specific manner. The proposed integrated approach to experimentally validate several binding motifs using CLIP-seq and to deconvolute global posttranscriptional networks in specific cell/tissue types, using genome-wide data from protein protection assays (POP-seq) will significantly enhance our capability of uncovering network dynamics of RBPs in cell types and tissues. Such high-quality predictions based on experimental validations, resulting from all the Aims which will be made public, can become a venue for future experimental follow up to dissect the role of these important regulatory molecules in different tissues and disease states. The proposed studies will make an impact in the field as the first large-scale computational mapping of protein-RNA interaction networks in the human tissues by taking our ability to predict RBP targets to the next level. The complementary experience and expertise of investigators will make this project successful.

Public Health Relevance

RNA-binding proteins (RBPs) play important roles in every biological pathway and cellular process. Elucidation of the RNA recognition motifs of hundreds of RNA-binding proteins discovered in recent years and analysis of dynamic post-transcriptional networks of RBPs across various tissues and disease states will increase our fundamental knowledge about how gene expression is modulated by these important regulatory molecules in living organisms. This knowledge is a critical step towards understanding, diagnosis, and treatment of several human diseases caused by mutation or mis-expression of these proteins.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM123314-01A1
Application #
9398667
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Krasnewich, Donna M
Project Start
2017-09-11
Project End
2022-08-31
Budget Start
2017-09-11
Budget End
2018-08-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Indiana University-Purdue University at Indianapolis
Department
Type
Schools of Arts and Sciences
DUNS #
603007902
City
Indianapolis
State
IN
Country
United States
Zip Code
46202
Neelamraju, Yaseswini; Gonzalez-Perez, Abel; Bhat-Nakshatri, Poornima et al. (2018) Mutational landscape of RNA-binding proteins in human cancers. RNA Biol 15:115-129
Palam, Lakshmi Reddy; Mali, Raghuveer Singh; Ramdas, Baskar et al. (2018) Loss of epigenetic regulator TET2 and oncogenic KIT regulate myeloid cell transformation via PI3K pathway. JCI Insight 3:
Kadumuri, Rajashekar Varma; Janga, Sarath Chandra (2018) Epitranscriptomic Code and Its Alterations in Human Disease. Trends Mol Med 24:886-903
Budak, Gungor; Dash, Soma; Srivastava, Rajneesh et al. (2018) Express: A database of transcriptome profiles encompassing known and novel transcripts across multiple development stages in eye tissues. Exp Eye Res 168:57-68
Srivastava, Rajneesh; Budak, Gungor; Dash, Soma et al. (2017) Transcriptome analysis of developing lens reveals abundance of novel transcripts and extensive splicing alterations. Sci Rep 7:11572
Singh, Deepak K; Gholamalamdari, Omid; Jadaliha, Mahdieh et al. (2017) PSIP1/p75 promotes tumorigenicity in breast cancer cells by promoting the transcription of cell cycle genes. Carcinogenesis 38:966-975
Budak, Gungor; Srivastava, Rajneesh; Janga, Sarath Chandra (2017) Seten: a tool for systematic identification and comparison of processes, phenotypes, and diseases associated with RNA-binding proteins from condition-specific CLIP-seq profiles. RNA 23:836-846