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Functional and Moonlighting Studies of Proteins and RNA based on Network Organization and Cellular Localization Diversity.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Functional and Moonlighting Studies of Proteins and RNA based on Network Organization and Cellular Localization Diversity./
作者:	Cheng, Lixin.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	174 p.
附註:	Source: Dissertations Abstracts International, Volume: 79-12, Section: B.
Contained By:	Dissertations Abstracts International79-12B.
標題:	Cellular biology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10902148
ISBN:	9780438105669

Functional and Moonlighting Studies of Proteins and RNA based on Network Organization and Cellular Localization Diversity.
Cheng, Lixin.

Functional and Moonlighting Studies of Proteins and RNA based on Network Organization and Cellular Localization Diversity. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 174 p.

Source: Dissertations Abstracts International, Volume: 79-12, Section: B.

Thesis (Ph.D.)--The Chinese University of Hong Kong (Hong Kong), 2018.

This item must not be sold to any third party vendors.

Spatial-temporal regulation amongst proteins forms dynamic interaction networks in cells. Protein co-existence in common cell compartments can improve the biological reliability of the protein-protein interactions. However, this is usually overlooked by most current proteomic studies and leads to erroneous discoveries. Chapters 1 and 2 give an overview and background of this thesis respectively. In Chapter 3, we systematically characterize the interaction localization diversity in human protein interactome using localization coefficient, a novel metric we proposed for assessing how diversely the interactions localize among cell compartments. Our analysis reveals that: (1) the subcellular networks of nucleus, cytosol, and mitochondrion are dense but the interactions tend to localize in specific cell compartments, whereas the subnetworks of secretory-pathway, membrane, and extracellular region are sparse but the interactions are diversely and evenly localized; (2) the housekeeping proteins tend to appear in multiple compartments, while the tissue-specific proteins present a relatively flat profile of localization breadth; (3) the autophagy proteins tend to diversely localize in multiple compartments, especially those with high connectivity, compared with the apoptosis proteins; and (4) the proteins targeted by small-molecule drugs show no preference for compartments, whereas the proteins directed by antibody-based drugs tend to belong to transmembrane regions with a strong diversity. To sum up, our analysis provides a comprehensive view of the subcellular localization for interacting proteins, demonstrates localization diversity is an important feature of protein interactions, and shows its ability to highlight meaningful biological functions. Clustering the components in a molecular network is a typical method in systems biology, and is effective in predicting functional modules or protein complexes. However, few studies have realized that biological molecules are spatially regulated to form a dynamic cellular network. This spatial distribution results in subsets of proteins mainly interacting with each other in cell compartments. Also, subcellular localization is crucial for proteins to perform biological functions and each compartment accommodates specific portions of the protein interaction structure. In Chapter 4, we propose a novel procedure, Subcellular Module Identification with Localization Expansion (SMILE), to identify super modules that consist of several subcellular modules performing specific biological functions among cell compartments. These super modules identified by SMILE are more functionally diverse and have been verified to be more associated with known protein complexes and biological pathways compared with the modules identified from the global PPI networks in both the ComPPI and InWeb_InBioMap datasets. The results reveal that subcellular localization is a principal feature of functional modules and offers important guidance in detecting more accurate and biologically meaningful results. The interaction localization diversity has been studied as a crucial feature of proteins. Nevertheless, neither the localization diversity of ncRNAs nor their characteristics in cancers have been systematically studied. In Chapter 5, we provide a new method, non-coding RNA TArget Localization coefficiENT (ncTALENT), to quantify the target localization diversity of ncRNAs based on the ncRNA-protein association and protein subcellular localization data. ncTALENT can be used to calculate the target localization coefficient (TLC) of ncRNAs and measure how diversely their targets are distributed among the subcellular locations. We focus on lncRNAs in this thesis and our findings reveal that the localization diversity is a key feature of lncRNAs subtypes and functions. lncRNAs in multiple cancers, differentially expressed cancer lncRNAs, and lncRNAs with multiple cancer target proteins are prone to have high localization diversity. This method can help us to better understand how the lncRNA work in cancers and it can be easily applied to the other types of ncRNAs and regulatory elements, such as circRNAs, snoRNAs, and transcription factors. Moonlighting proteins are a class of proteins having multiple distinct functions, which play essential roles in a variety of cellular and enzymatic functioning systems. Although there have long been calls for computational algorithms for the identification of moonlighting proteins, research on approaches for identifying moonlighting long non-coding RNAs (lncRNAs) has never been undertaken. In Chapter 6, we introduce a novel methodology, MoonFinder, for the identification of moonlighting lncRNAs. MoonFinder is a statistical algorithm identifying moonlighting lncRNAs without a priori knowledge by the integration of protein interactome, RNA-protein interactions, and functional annotation of proteins. We discovered that the identified moonlighting lncRNA candidates are a distinct class of lncRNAs characterized by specific sequence and cellular localization features. Importantly, we found that the non-coding genes that transcript moonlighting lncRNAs tend to have shorter but more exons and the moonlighting lncRNAs have a localization tendency of residing in cytoplasmic compartment in comparison to the nuclear compartment. Moreover, moonlighting lncRNAs and moonlighting proteins are rather mutually exclusive in terms of both their direct interactions and interacting partners.

ISBN: 9780438105669Subjects--Topical Terms:

3172791
Cellular biology.

Functional and Moonlighting Studies of Proteins and RNA based on Network Organization and Cellular Localization Diversity.
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500 $a Source: Dissertations Abstracts International, Volume: 79-12, Section: B.
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506 $a This item must not be added to any third party search indexes.
520 $a Spatial-temporal regulation amongst proteins forms dynamic interaction networks in cells. Protein co-existence in common cell compartments can improve the biological reliability of the protein-protein interactions. However, this is usually overlooked by most current proteomic studies and leads to erroneous discoveries. Chapters 1 and 2 give an overview and background of this thesis respectively. In Chapter 3, we systematically characterize the interaction localization diversity in human protein interactome using localization coefficient, a novel metric we proposed for assessing how diversely the interactions localize among cell compartments. Our analysis reveals that: (1) the subcellular networks of nucleus, cytosol, and mitochondrion are dense but the interactions tend to localize in specific cell compartments, whereas the subnetworks of secretory-pathway, membrane, and extracellular region are sparse but the interactions are diversely and evenly localized; (2) the housekeeping proteins tend to appear in multiple compartments, while the tissue-specific proteins present a relatively flat profile of localization breadth; (3) the autophagy proteins tend to diversely localize in multiple compartments, especially those with high connectivity, compared with the apoptosis proteins; and (4) the proteins targeted by small-molecule drugs show no preference for compartments, whereas the proteins directed by antibody-based drugs tend to belong to transmembrane regions with a strong diversity. To sum up, our analysis provides a comprehensive view of the subcellular localization for interacting proteins, demonstrates localization diversity is an important feature of protein interactions, and shows its ability to highlight meaningful biological functions. Clustering the components in a molecular network is a typical method in systems biology, and is effective in predicting functional modules or protein complexes. However, few studies have realized that biological molecules are spatially regulated to form a dynamic cellular network. This spatial distribution results in subsets of proteins mainly interacting with each other in cell compartments. Also, subcellular localization is crucial for proteins to perform biological functions and each compartment accommodates specific portions of the protein interaction structure. In Chapter 4, we propose a novel procedure, Subcellular Module Identification with Localization Expansion (SMILE), to identify super modules that consist of several subcellular modules performing specific biological functions among cell compartments. These super modules identified by SMILE are more functionally diverse and have been verified to be more associated with known protein complexes and biological pathways compared with the modules identified from the global PPI networks in both the ComPPI and InWeb_InBioMap datasets. The results reveal that subcellular localization is a principal feature of functional modules and offers important guidance in detecting more accurate and biologically meaningful results. The interaction localization diversity has been studied as a crucial feature of proteins. Nevertheless, neither the localization diversity of ncRNAs nor their characteristics in cancers have been systematically studied. In Chapter 5, we provide a new method, non-coding RNA TArget Localization coefficiENT (ncTALENT), to quantify the target localization diversity of ncRNAs based on the ncRNA-protein association and protein subcellular localization data. ncTALENT can be used to calculate the target localization coefficient (TLC) of ncRNAs and measure how diversely their targets are distributed among the subcellular locations. We focus on lncRNAs in this thesis and our findings reveal that the localization diversity is a key feature of lncRNAs subtypes and functions. lncRNAs in multiple cancers, differentially expressed cancer lncRNAs, and lncRNAs with multiple cancer target proteins are prone to have high localization diversity. This method can help us to better understand how the lncRNA work in cancers and it can be easily applied to the other types of ncRNAs and regulatory elements, such as circRNAs, snoRNAs, and transcription factors. Moonlighting proteins are a class of proteins having multiple distinct functions, which play essential roles in a variety of cellular and enzymatic functioning systems. Although there have long been calls for computational algorithms for the identification of moonlighting proteins, research on approaches for identifying moonlighting long non-coding RNAs (lncRNAs) has never been undertaken. In Chapter 6, we introduce a novel methodology, MoonFinder, for the identification of moonlighting lncRNAs. MoonFinder is a statistical algorithm identifying moonlighting lncRNAs without a priori knowledge by the integration of protein interactome, RNA-protein interactions, and functional annotation of proteins. We discovered that the identified moonlighting lncRNA candidates are a distinct class of lncRNAs characterized by specific sequence and cellular localization features. Importantly, we found that the non-coding genes that transcript moonlighting lncRNAs tend to have shorter but more exons and the moonlighting lncRNAs have a localization tendency of residing in cytoplasmic compartment in comparison to the nuclear compartment. Moreover, moonlighting lncRNAs and moonlighting proteins are rather mutually exclusive in terms of both their direct interactions and interacting partners.
590 $a School code: 1307.
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