Novel approaches for bioinformatic analysis of salivary RNA sequencing data for development

Karolina Elzbieta Kaczor-Urbanowicz; Yong Kim; Feng Li; Timur Galeev; Rob R Kitchen; Mark Gerstein; Kikuye Koyano; Sung-Hee Jeong; Xiaoyan Wang; David Elashoff; So Young Kang; Su Mi Kim; Kyoung Kim; Sung Kim; David Chia; Xinshu Xiao; Joel Rozowsky; David T W Wong

doi:10.1093/bioinformatics/btx504

Novel approaches for bioinformatic analysis of salivary RNA sequencing data for development

Bioinformatics. 2018 Jan 1;34(1):1-8. doi: 10.1093/bioinformatics/btx504.

Authors

Karolina Elzbieta Kaczor-Urbanowicz¹, Yong Kim¹, Feng Li¹, Timur Galeev², Rob R Kitchen², Mark Gerstein^{2

3}, Kikuye Koyano⁴, Sung-Hee Jeong⁵, Xiaoyan Wang⁶, David Elashoff⁶, So Young Kang⁷, Su Mi Kim⁸, Kyoung Kim⁷, Sung Kim⁸, David Chia⁹, Xinshu Xiao⁴, Joel Rozowsky¹⁰, David T W Wong¹

Affiliations

¹ Center for Oral/Head & Neck Oncology Research, School of Dentistry, Division of Oral Biology & Medicine University of California at Los Angeles, Los Angeles, CA 90095, USA.
² Department of Molecular Biophysics and Biochemistry, Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
³ The Department of Computer Science, Yale University, New Haven, CT 06520.
⁴ Department of Integrative Biology and Physiology, University of California at Los Angeles, Los Angeles, CA 90095-1570, USA.
⁵ Department of Oral Medicine, School of Dentistry, Pusan National University, Beomeo-ri, Mulgeum-eup, Yangsan-si, Gyeongsangnam-do 626-770, Korea.
⁶ Department of Biostatistics, University of California at Los Angeles, Los Angeles, CA 90024, USA.
⁷ Department of Pathology & Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Korea.
⁸ Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Korea.
⁹ Department of Pathology & Laboratory Medicine, University of California at Los Angeles, Los Angeles, CA 90095, USA.
¹⁰ Department of Molecular Biophysics and Biochemistry,Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.

Abstract

Motivation: Analysis of RNA sequencing (RNA-Seq) data in human saliva is challenging. Lack of standardization and unification of the bioinformatic procedures undermines saliva's diagnostic potential. Thus, it motivated us to perform this study.

Results: We applied principal pipelines for bioinformatic analysis of small RNA-Seq data of saliva of 98 healthy Korean volunteers including either direct or indirect mapping of the reads to the human genome using Bowtie1. Analysis of alignments to exogenous genomes by another pipeline revealed that almost all of the reads map to bacterial genomes. Thus, salivary exRNA has fundamental properties that warrant the design of unique additional steps while performing the bioinformatic analysis. Our pipelines can serve as potential guidelines for processing of RNA-Seq data of human saliva.

Availability and implementation: Processing and analysis results of the experimental data generated by the exceRpt (v4.6.3) small RNA-seq pipeline (github.gersteinlab.org/exceRpt) are available from exRNA atlas (exrna-atlas.org). Alignment to exogenous genomes and their quantification results were used in this paper for the analyses of small RNAs of exogenous origin.

Contact: dtww@ucla.edu.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Computational Biology / methods*
High-Throughput Nucleotide Sequencing / methods
Humans
RNA
Saliva / chemistry
Sequence Analysis, RNA / methods*
Software*

Substances

RNA

Abstract

Publication types

MeSH terms

Substances

Grants and funding