NASA GeneLab RNA-seq consensus pipeline: standardized processing of short-read RNA-seq data

Eliah G Overbey¹, Amanda M Saravia-Butler^{2

3}, Zhe Zhang⁴, Komal S Rathi⁴, Homer Fogle^{5

3}, Willian A da Silveira⁶, Richard J Barker⁷, Joseph J Bass⁸, Afshin Beheshti^{9

10}, Daniel C Berrios³, Elizabeth A Blaber¹¹, Egle Cekanaviciute³, Helio A Costa¹², Laurence B Davin¹³, Kathleen M Fisch¹⁴, Samrawit G Gebre^{3

9}, Matthew Geniza¹⁵, Rachel Gilbert¹⁶, Simon Gilroy⁷, Gary Hardiman^{6

17}, Raúl Herranz¹⁸, Yared H Kidane¹⁹, Colin P S Kruse²⁰, Michael D Lee^{21

22}, Ted Liefeld²³, Norman G Lewis¹³, J Tyson McDonald²⁴, Robert Meller²⁵, Tejaswini Mishra²⁶, Imara Y Perera²⁷, Shayoni Ray²⁸, Sigrid S Reinsch³, Sara Brin Rosenthal¹⁴, Michael Strong²⁹, Nathaniel J Szewczyk³⁰, Candice G T Tahimic³¹, Deanne M Taylor³², Joshua P Vandenbrink³³, Alicia Villacampa¹⁸, Silvio Weging³⁴, Chris Wolverton³⁵, Sarah E Wyatt^{36

37}, Luis Zea³⁸, Sylvain V Costes³, Jonathan M Galazka³

Affiliations

¹ Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
² Logyx, LLC, Mountain View, CA 94043, USA.
³ Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA 94035, USA.
⁴ Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA 19104, USA.
⁵ The Bionetics Corporation, NASA Ames Research Center, Moffett Field, CA 94035, USA.
⁶ Institute for Global Food Security (IGFS) & School of Biological Sciences, Queen's University Belfast, Belfast, UK.
⁷ Department of Botany, University of Wisconsin, Madison, WI 53706, USA.
⁸ MRC Versus Arthritis Centre for Musculoskeletal Ageing Research, Royal Derby Hospital, University of Nottingham & National Institute for Health Research Nottingham Biomedical Research Centre, Derby DE22 3DT, UK.
⁹ KBR, NASA Ames Research Center, Moffett Field, CA 94035, USA.
¹⁰ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
¹¹ Center for Biotechnology and Interdisciplinary Studies, Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA.
¹² Departments of Pathology, and of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA.
¹³ Institute of Biological Chemistry, Washington State University, Pullman, WA 99164, USA.
¹⁴ Center for Computational Biology & Bioinformatics, Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
¹⁵ Phylos Bioscience, Portland, OR 97214, USA.
¹⁶ NASA Postdoctoral Program, Universities Space Research Association, NASA Ames Research Center, Moffett Field, CA 94035, USA.
¹⁷ Medical University of South Carolina, Charleston, SC, USA.
¹⁸ Centro de Investigaciones Biológicas Margarita Salas (CSIC), Ramiro de Maeztu 9, 28040 Madrid, Spain.
¹⁹ Center for Pediatric Bone Biology and Translational Research, Texas Scottish Rite Hospital for Children, 2222 Welborn St., Dallas, TX 75219, USA.
²⁰ Los Alamos National Laboratory, Bioscience Division, Los Alamos, NM 87545, USA.
²¹ Exobiology Branch, NASA Ames Research Center, Mountain View, CA 94035, USA.
²² Blue Marble Space Institute of Science, Seattle, WA 98154, USA.
²³ Department of Medicine, University of California San Diego, San Diego, CA 92093, USA.
²⁴ Department of Radiation Medicine, Georgetown University Medical Center, Washington, DC 20007, USA.
²⁵ Department of Neurobiology and Pharmacology, Morehouse School of Medicine, Atlanta, GA 30310, USA.
²⁶ Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
²⁷ Department of Plant and Microbial Biology, North Carolina State University, Raleigh, NC 27695, USA.
²⁸ NGM Biopharmaceuticals, South San Francisco, CA 94080, USA.
²⁹ National Jewish Health, Center for Genes, Environment, and Health, 1400 Jackson Street, Denver, CO 80206, USA.
³⁰ Ohio Musculoskeletal and Neurological Institute and Department of Biomedical Sciences, Ohio University, Athens, OH 43147, USA.
³¹ Department of Biology, University of North Florida, Jacksonville, FL 32224, USA.
³² Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia and the Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
³³ Department of Biology, Louisiana Tech University, Ruston, LA 71272, USA.
³⁴ Institute of Computer Science, Martin-Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, Halle 06120, Germany.
³⁵ Department of Botany and Microbiology, Ohio Wesleyan University, Delaware, OH, USA.
³⁶ Department of Environmental and Plant Biology, Ohio University, Athens, OH 45701, USA.
³⁷ Interdisciplinary Program in Molecular and Cellular Biology, Ohio University, Athens, OH 45701, USA.
³⁸ BioServe Space Technologies, Aerospace Engineering Sciences Department, University of Colorado Boulder, Boulder 80303 USA.

PMID: 33870146
PMCID: PMC8044432
DOI: 10.1016/j.isci.2021.102361

NASA GeneLab RNA-seq consensus pipeline: standardized processing of short-read RNA-seq data

Eliah G Overbey et al. iScience. 2021.

. 2021 Mar 26;24(4):102361.

doi: 10.1016/j.isci.2021.102361. eCollection 2021 Apr 23.

Authors

Affiliations

¹ Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
² Logyx, LLC, Mountain View, CA 94043, USA.
³ Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA 94035, USA.
⁴ Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA 19104, USA.
⁵ The Bionetics Corporation, NASA Ames Research Center, Moffett Field, CA 94035, USA.
⁶ Institute for Global Food Security (IGFS) & School of Biological Sciences, Queen's University Belfast, Belfast, UK.
⁷ Department of Botany, University of Wisconsin, Madison, WI 53706, USA.
⁸ MRC Versus Arthritis Centre for Musculoskeletal Ageing Research, Royal Derby Hospital, University of Nottingham & National Institute for Health Research Nottingham Biomedical Research Centre, Derby DE22 3DT, UK.
⁹ KBR, NASA Ames Research Center, Moffett Field, CA 94035, USA.
¹⁰ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
¹¹ Center for Biotechnology and Interdisciplinary Studies, Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA.
¹² Departments of Pathology, and of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA.
¹³ Institute of Biological Chemistry, Washington State University, Pullman, WA 99164, USA.
¹⁴ Center for Computational Biology & Bioinformatics, Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
¹⁵ Phylos Bioscience, Portland, OR 97214, USA.
¹⁶ NASA Postdoctoral Program, Universities Space Research Association, NASA Ames Research Center, Moffett Field, CA 94035, USA.
¹⁷ Medical University of South Carolina, Charleston, SC, USA.
¹⁸ Centro de Investigaciones Biológicas Margarita Salas (CSIC), Ramiro de Maeztu 9, 28040 Madrid, Spain.
¹⁹ Center for Pediatric Bone Biology and Translational Research, Texas Scottish Rite Hospital for Children, 2222 Welborn St., Dallas, TX 75219, USA.
²⁰ Los Alamos National Laboratory, Bioscience Division, Los Alamos, NM 87545, USA.
²¹ Exobiology Branch, NASA Ames Research Center, Mountain View, CA 94035, USA.
²² Blue Marble Space Institute of Science, Seattle, WA 98154, USA.
²³ Department of Medicine, University of California San Diego, San Diego, CA 92093, USA.
²⁴ Department of Radiation Medicine, Georgetown University Medical Center, Washington, DC 20007, USA.
²⁵ Department of Neurobiology and Pharmacology, Morehouse School of Medicine, Atlanta, GA 30310, USA.
²⁶ Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
²⁷ Department of Plant and Microbial Biology, North Carolina State University, Raleigh, NC 27695, USA.
²⁸ NGM Biopharmaceuticals, South San Francisco, CA 94080, USA.
²⁹ National Jewish Health, Center for Genes, Environment, and Health, 1400 Jackson Street, Denver, CO 80206, USA.
³⁰ Ohio Musculoskeletal and Neurological Institute and Department of Biomedical Sciences, Ohio University, Athens, OH 43147, USA.
³¹ Department of Biology, University of North Florida, Jacksonville, FL 32224, USA.
³² Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia and the Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
³³ Department of Biology, Louisiana Tech University, Ruston, LA 71272, USA.
³⁴ Institute of Computer Science, Martin-Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, Halle 06120, Germany.
³⁵ Department of Botany and Microbiology, Ohio Wesleyan University, Delaware, OH, USA.
³⁶ Department of Environmental and Plant Biology, Ohio University, Athens, OH 45701, USA.
³⁷ Interdisciplinary Program in Molecular and Cellular Biology, Ohio University, Athens, OH 45701, USA.
³⁸ BioServe Space Technologies, Aerospace Engineering Sciences Department, University of Colorado Boulder, Boulder 80303 USA.

PMID: 33870146
PMCID: PMC8044432
DOI: 10.1016/j.isci.2021.102361

Abstract

With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab.

Keywords: Omics; Space Sciences.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

**Figure 1**
GeneLab RNA-seq Consensus Pipeline (RCP) (A) The three broad steps of the RCP. The RCP handles (1) data preprocessing to trim sequencing adapters and to provide quality control metrics; (2) data processing to map reads to the reference genome and quantify the number of read counts per gene; and (3) differential gene expression calculation, which will provide a list of differentially expressed genes that can be sorted by adjusted p value and log fold-change. (B) The full RCP annotated with tools, input files, and output files.

**Figure 2**
Data preprocessing (pipeline step 1): quality control and trimming (A) Data preprocessing pipeline. FastQ files from Illumina base-calling software are quality checked using FastQC and MultiQC. Data are then trimmed using TrimGalore and are re-checked for quality; (B) flags used for FastQC program; (C) flags used for MultiQC program; (D) flags used for TrimGalore program; trimmed reads (∗fastq.gz) are then used as input data for FastQC (B) followed by MultiQC (C) to generate trimmed read quality metrics. Tool versions used to process each dataset are included in the RNA-seq processing protocol in the GLDS Repository.

**Figure 3**
Data processing (pipeline step 2A): read mapping (A) Data processing pipeline. Trimmed reads are mapped to their reference genome and transcriptome with STAR. Gene counts are then quantified with RSEM; (B) flags used for generating the indexed STAR reference files; (C) flags used for mapping reads with STAR. Tool versions used to process each dataset are included in the RNA-seq processing protocol in the GLDS Repository.

**Figure 4**
Data processing (pipeline step 2B): gene quantification (A) Data processing pipeline. Mapping results from STAR are quantified by RSEM; (B) parameters for RSEM indexed reference files generation; (C) parameters for quantifying gene and isoform counts with RSEM. Tool versions used to process each dataset are included in the RNA-seq processing protocol in the GLDS repository.

**Figure 5**
Differential gene expression calculation (pipeline step 3) (A) Data processing pipeline. The R program DESeq2 is run in order to determine which genes are differentially expressed between experimental conditions using gene count files from RSEM. (B) Output files generated. The table columns distinguish which script produces each output. The columns distinguish how those output files are used.

**Figure 6**
Global and differential gene expression in spaceflight versus ground control liver samples from GeneLab datasets (A and B) Principal component analysis of global gene expression in spaceflight (FLT) and respective ground control (GC) liver samples from the (A) Rodent Research 1 (RR-1) NASA Validation mission (GLDS-168) and (B) RR-6 ISS-terminal mission (GLDS-245). Plots were generated using data in the normalized counts tables for each respective dataset on the NASA GeneLab Data Repository. (C and D) Heatmaps showing the top 30 differentially expressed genes in spaceflight (FLT) versus ground control (GC) liver samples from the (C) Rodent Research 1 (RR-1) NASA Validation mission (GLDS-168) and (D) RR-6 ISS-terminal mission (GLDS-245). Heatmaps were generated using data in the differential expression tables for each respective dataset on the NASA GeneLab Data Repository and are colored by relative expression. Adj. p value < 0.05 and |log2FC| > 1. All samples included were derived from frozen carcasses post-mission and utilized the ribo-depletion library preparation method.

See this image and copyright information in PMC

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NASA GeneLab RNA-seq consensus pipeline: standardized processing of short-read RNA-seq data

Affiliations

NASA GeneLab RNA-seq consensus pipeline: standardized processing of short-read RNA-seq data

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources