Indiana University-Purdue University Indianapolis (IUPUI) / Several experimental methods has been developed for the study of the central
dogma since late 20th century. Protein mass spectrometry and next generation sequencing
(including DNA-Seq and RNA-Seq) forms a triangle of experimental methods,
corresponding to the three vertices of the central dogma, i.e., DNA, RNA and protein.
Numerous RNA sequencing and protein mass spectrometry experiments has been carried
out in attempt to understand how the expression change of known genes affect biological
functions in various of organisms, however, it has been once overlooked that the result
data of these experiments are in fact holograms which also reveals other delicate
biological mechanisms, such as RNA splicing and the expression of long non-coding
RNAs. In this dissertation, we carried out five studies based on high-throughput
sequencing data, in an attempt to understand how RNA splicing and differential
expression of long non-coding RNAs is associated biological functions.
In the first two studies, we identified and characterized 197 stimulant induced and
477 developmentally regulated alternative splicing events from RNA sequencing data. In
the third study, we introduced a method for identifying novel alternative splicing events
that were never documented. In the fourth study, we introduced a method for identifying
known and novel RNA splicing junctions from protein mass spectrometry data. In the
fifth study, we introduced a method for identifying long non-coding RNAs from poly-A
selected RNA sequencing data. Taking advantage of these methods, we turned RNA
sequencing and protein mass spectrometry data into an information gold mine of splicing
and long non-coding RNA activities. / 2019-05-06
Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/17771 |
Date | 10 1900 |
Creators | Zhou, Ao |
Contributors | Wu, Huanmei, Liu, Yunlong, Janga, Sarath C., Liu, Xiaowen |
Source Sets | Indiana University-Purdue University Indianapolis |
Language | en_US |
Detected Language | English |
Type | Dissertation |
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