Alternative splicing (AS) of human genes is pervasive and greatly expands the repertoire of protein and RNA products arising from the human genome. AS is fundamental to gene and genome function, and its dysregulation has been causally linked with a broad and expanding array of both common and rare diseases and cancers. Despite its central importance, we currently have limited insight into the occurrence and regulation of AS at both the local (gene) and global (genome-wide) levels, due chiefly to a lack of tools that provide direct, high-resolution, and quantitative views into the splicing process. This deficit has in turn roadblocked progress in characterizing the wealth of mutations affecting various components of the splicing machinery now emerging from genetic studies of disease. To date, global studies of splicing have relied chiefly on analysis of mature cytosolic RNA isoforms, which represent the combined result of transcription, splicing, nuclear export and degradation and thus a very incomplete view. For example, at least 1/3rd of splicing events are estimated to go undetected since the resulting RNA product is rapidly targeted for nonsense-mediated decay, and many others go undetected due to limited sensitivity of current sequencing-based approaches. Thus, it is critical to map splicing events rapidly when and where they occur. Here we propose to develop a novel approach that will provide a direct, dynamic, and global window into the alternative splicing of human exons. Our approach enables simultaneous determination of RNA polymerase position and the splicing state of individual RNA molecules. This will in turn open a new kinetic window on splicing that will have uniquely powerful utility for basic mapping and mechanistic studies, and for characterization and functional analysis of mutations affecting the splicing machinery.
In Aim 1, we develop an approach that interrogates entire nascent transcripts, to simultaneously map 3' ends as well as the splicing state of the nascent RNA, in a strand-specific manner. We will then develop computational tools to quantify the average distance transcribed by Pol II when splicing occurs, and to integrate these data with average transcription rates and high resolution Pol II mapping to reveal mean splicing times ? thus opening a new and global window into splicing kinetics. This approach has a temporal resolution of tens of milliseconds that greatly eclipses other strategies to measure splicing kinetics, such as metabolic labeling of nascent RNA.
In Aim 2, we apply this approach to characterize the global effects of recurrent mutations in 2 splicing regulators found in malignancies. An unexpected discovery from cancer genome sequencing studies has been the identification of frequent mutations in genes encoding splicing machinery components. As proof-of-principle for complex biological applications, we propose to apply our approach to characterize and gain functional insights into mutations in splicing regulators characteristic of several major malignancies. Our comprehensive approach for measuring global splicing kinetics has the positive impact of enabling rapid discovery and characterization of splicing regulation in health and disease.

Public Health Relevance

The proposed research is relevant to public health, because dysregulated alternative splicing leads to a broad range of diseases, including many cancers and neurological disorders. Developing a novel approach to directly measure splicing kinetics will shed light on how mutations in splicing regulators lead to disease phenotypes and will suggest novel therapeutic approaches.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21HG009264-02
Application #
9360128
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Pazin, Michael J
Project Start
2016-09-28
Project End
2019-07-31
Budget Start
2017-08-01
Budget End
2019-07-31
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Harvard Medical School
Department
Genetics
Type
Schools of Medicine
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
02115