Alternative pre-mRNA splicing in breast cancer is known to affect genes responsible for cell cycle and apoptosis through the creation of alternate mRNA isoforms. Several of these events have been characterized as breast cancer-specific and are linked with disease progression. Previous studies of alternative splicing in breast cancer have focused on characterizing specific genes and gene families and do not address the co- transcriptional nature of these events. Here, we propose experiments that will generate genome-wide profiles of breast cancer-specific alternative splicing that will address this knowledge gap. First, we will address the question which alternative mRNA isoforms are created by splicing. The first specific aim will identify and verify breast cancer-specific changes in alternative splicing. Expression profiles will be generated using computational analyses of high throughput data for breast cancer cell lines, tumor tissue, normal cell lines, and non-tumor tissue. Aberrations in alternative splicing will be verified using quantitative PCR and western blo analysis. Given the proposal that pre-mRNA splicing may occur co-transcriptionally, decisions dictating how genes are differentially spliced in breast cancer may be accomplished during this same window. In the second specific aim we will determine the extent to which alternative splicing decisions are made co-transcriptionally. The extent of splicing of nascent mRNA will be determined through high throughput sequencing. Chromatin- bound RNA will be isolated using a technique recently established in our lab. In order to investigate the time associated properties of splicing, we will use a reversible transcription initiation inhibitor to synchronize transcriptin in breast cancer cell lines. Nascent mRNAs will then be extracted at biologically relevant time points and subjected to high throughput sequencing. Computational analyses of these outputs will generate comprehensive snap shots of splicing events such as alternative splice site selection or exon skipping events. Understanding both the consequences and the mechanisms of alternative splicing is vital to developing the next generation of breast cancer therapies and screenings.
Breast cancer-specific alternative splicing has been linked to disease progression. This study will generate genome-wide profiles of aberrant alternative splicing events in breast cancer by combining experimental analyses with bioinformatics. These profiles will be used to test the hypothesis that breast cancer-specific alternative splicing occur co-transcriptionally.
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