Int. J. of Computational Biology and Drug Design   »   2018 Vol.11, No.1/2

 

 

Title: Evaluation of biological and technical variations in low-input RNA-Seq and single-cell RNA-Seq

 

Authors: Fan Gao; Jae Mun Kim; JiHong Kim; Ming-Yi Lin; Charles Y. Liu; Jonathan J. Russin; Christopher P. Walker; Reymundo Dominguez; Adrian Camarena; Joseph D. Nguyen; Jennifer Herstein; William Mack; Oleg V. Evgrafov; Robert H. Chow; James A. Knowles; Kai Wang

 

Addresses:
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA

 

Abstract: Background: Low-input or single-cell RNA-Seq are widely used today, but two technical questions remain: 1) in technical replicates, what proportion of noises comes from input RNA quantity rather than variation of bioinformatics tools?; 2) In single neurons, whether variation in gene expression is attributable to biological heterogeneity or just random noise? To examine the sources of variability, we have generated RNA-Seq data from low-input (10/100/1000pg) reference RNA samples and 38 single neurons from human brains. Results: For technical replicates, the quantity of input RNA is negatively correlated with expression variation. For genes in the medium- and high-expression groups, input RNA amount explains most of the variation, whereas bioinformatic pipelines explain some variation for the low-expression group. The t-distributed stochastic neighbour embedding (t-SNE) method reveals data-inherent aggregation of low-input replicate data, and suggests heterogeneity of single pyramidal neuron transcriptome. Interestingly, expression variation in single neurons is biologically relevant. Conclusions: We found that differences in bioinformatics pipelines do not present a major source of variation.

 

Keywords: RNA-Seq; single-cell sequencing; bioinformatics; TopHat; RNA-Seq by expectation maximisation; RSEM; t-distributed stochastic neighbour embedding; t-SNE; principal component analysis; PCA; annotate variation; ANNOVAR; variance.

 

DOI: 10.1504/IJCBDD.2018.090839

 

Int. J. of Computational Biology and Drug Design, 2018 Vol.11, No.1/2, pp.5 - 22

 

Submission date: 04 Mar 2017
Date of acceptance: 04 Aug 2017
Available online: 23 Mar 2018

 

 

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