Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.; Yang, Xiaohan; Guo, Hong

doi:10.1155/2018/9784161

Title: Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

Journal Article · Mon Jan 01 00:00:00 EST 2018 · International Journal of Genomics

DOI:https://doi.org/10.1155/2018/9784161· OSTI ID:1423699

^[1]; Ma, Yue ^[1]; Tuskan, Gerald A. ^[2];

^[2];

^[1]

Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 3783, USA

Here, the existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here) from the protein distribution densities in the LD space defined by ln(L) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0008834; AC05-00OR22725

OSTI ID:: 1423699

Alternate ID(s):: OSTI ID: 1468038

Journal Information:: International Journal of Genomics, Journal Name: International Journal of Genomics Vol. 2018; ISSN 2314-436X

Publisher:: Hindawi Publishing CorporationCopyright Statement

Country of Publication:: Egypt

Language:: English

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Cited by: 3 works

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