Application of a bioinformatic pipeline to RNA-seq data identifies novel virus-like sequence in human blood

Author:

Melnick Marko1ORCID,Gonzales Patrick1,LaRocca Thomas J2,Song Yuping3,Wuu Joanne4,Benatar Michael4,Oskarsson Björn5,Petrucelli Leonard36,Dowell Robin D7,Link Christopher D18,Prudencio Mercedes36

Affiliation:

1. Department of Integrative Physiology, University of Colorado, Boulder, CO 80303, USA

2. Department of Health and Exercise Science, Center for Healthy Aging, Colorado State University, Fort Collins, CO 80523, USA

3. Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA

4. Department of Neurology, University of Miami, Miami, FL 33136, USA

5. Department of Neurology, Mayo Clinic, Jacksonville, FL 32224, USA

6. Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL 32224, USA

7. BioFrontiers Institute and Department of Molecular, Cellular and Developmental Biology, University of Colorado, Boulder, CO 80303, USA

8. Institute for Behavioral Genetics, University of Colorado, Boulder, CO 80303, USA

Abstract

Abstract Numerous reports have suggested that infectious agents could play a role in neurodegenerative diseases, but specific etiological agents have not been convincingly demonstrated. To search for candidate agents in an unbiased fashion, we have developed a bioinformatic pipeline that identifies microbial sequences in mammalian RNA-seq data, including sequences with no significant nucleotide similarity hits in GenBank. Effectiveness of the pipeline was tested using publicly available RNA-seq data and in a reconstruction experiment using synthetic data. We then applied this pipeline to a novel RNA-seq dataset generated from a cohort of 120 samples from amyotrophic lateral sclerosis patients and controls, and identified sequences corresponding to known bacteria and viruses, as well as novel virus-like sequences. The presence of these novel virus-like sequences, which were identified in subsets of both patients and controls, were confirmed by quantitative RT-PCR. We believe this pipeline will be a useful tool for the identification of potential etiological agents in the many RNA-seq datasets currently being generated.

Funder

NIH

ALS Association

NINDS

Mayo Clinic Foundation

Neuroscience Focused Research Team Mayo Clinic

Association of Frontotemporal Dementia

Alzheimer’s Association-AD Strategic Fund

Muscular Dystrophy Association

ALS Recovery Fund

Department of Defense

Publisher

Oxford University Press (OUP)

Subject

Genetics(clinical),Genetics,Molecular Biology

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