Virtually all multi-exon genes undergo alternative splicing (AS) to generate multiple protein isoforms. Alternative splicing is regulated by splicing factors, such as the serine/arginine rich (SR) protein family and the heterogeneous nuclear ribonucleoproteins (hnRNPs). Splicing factors are essential and highly conserved. It has been shown that splicing factors modulate alternative splicing of their own transcripts and of transcripts encoding other splicing factors. However, the extent of this alternative splicing regulation has not yet been determined. I hypothesize that the splicing factor network extends to many SR and hnRNP proteins, and is regulated by alternative splicing coupled to the nonsense mediated mRNA decay (NMD) surveillance pathway.
The NMD pathway has a role in preventing accumulation of erroneous transcripts with dominant negative phenotypes. During the pioneer round of translation, NMD recognizes mRNA transcripts with in-frame premature termination codons (PTCs) and degrades them. Generally, NMD is thought to play a protective role by degrading transcripts that may generate truncated proteins that can be non-functional or deleterious. The NMD pathway also has physiological targets: it impacts gene expression through alternative splicing coupled with NMD. In this mode of regulation, high levels of one splicing factor cause target pre-mRNAs to be spliced into unproductive isoforms and degraded, resulting in lower levels of the spliced RNAs. Interestingly, many splicing factors undergo this mode of regulation. For example, SR proteins SRSF1, SRSR2, SRSF3, and SRSF7 are known to auto-regulate their own expression by coupling alternative splicing and NMD. In addition, splice factors hnRNP L and PTB are regulated in the same manner. Evidence also exists that splicing factors cross regulate each other via NMD. Since all 12 canonical human SR factors and many hnRNP factors have at least one isoform that contains evolutionarily conserved in-frame PTC, it is possible that this mode of gene regulation extends to all SR splicing factors, many hnRNP factors, and even beyond, forming a regulatory network that is dependent upon NMD.
Approximately 18% of expressed genes are reported to be natural targets of NMD, yet it still remains unclear why the human genome would express mRNAs that are immediately degraded by the NMD pathway. It is especially intriguing that splicing factors, which are responsible for the entire proteomic diversity, are enriched in this pool of natural NMD targets. To date, there has been no comprehensive and systematic study of human splicing factors and their role in genome wide gene regulation via NMD.
Regulation via alternative splicing coupled to NMD requires binding of a splicing factor to the regulated mRNA. CLIP-seq and related studies reveal that splicing factors bind abundantly to all transcripts of our selected 100 splicing factors. In collaboration with Arun Desai, I characterized the network of protein-RNA interactions between splicing factors. I find that splicing factors form a highly-connected network, where 30–60% of all possible interactions between splicing factors and the transcripts encoding splicing factors are observed. Dr. Zhiqiang Hu and I compared the hierarchy of splicing factors to the hierarchy of transcription factors. Dr. Hu calculated hierarchies of transcription and splicing factors using ENCODE ChIP-seq and eCLIP data, applying a hierarchy metric described in Gerstein et al. (Nature 2012 489:91–100). . Our limited data show that the hierarchy among splicing regulators is different from that of transcription factors. Gerstein et al. plot networks in 3 layers, with a top “executive” layer, the bottom under-regulation layer, and a middle layer in between. Unlike transcription factors which concentrate at the extremes of hierarchy metric, splicing factors form a hierarchical network that has nearly uniform distribution of proteins across the hierarchy metric and thus less clearly defined separation into the three distinct layers. Nearly all splicing factors that bind their own transcripts are found in the middle layer.
Dr. Courtney French, Dr. Hu, and I combined experimental data and a model for NMD mechanism to identify targets of NMD. I inhibited NMD in HeLa and GM12878 cells via knockdown of UPF1 and SMG6, two core NMD factors, and by exposure to cycloheximide (CHX). Dr. French and Dr. Hu performed RNA-seq data analysis for targets of NMD. We observed that NMD factor knockdown is likely a better method to identify NMD targets than the CHX treatment. We found that approximately 30% of NMD isoforms are shared between HeLa and GM12878, while the reminder are not substantially expressed in the other cell line.
|Advisor:||Brenner, Steven E.|
|Commitee:||He, Lin, Rio, Donald|
|School:||University of California, Berkeley|
|School Location:||United States -- California|
|Source:||DAI-B 79/08(E), Dissertation Abstracts International|
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