Targeted DNA-seq and RNA-seq of Reference Samples with Short-read and Long-read Sequencing

Binsheng Gong^#¹, Dan Li^#¹, Paweł P Łabaj^#^{2

3}, Bohu Pan¹, Natalia Novoradovskaya⁴, Danielle Thierry-Mieg⁵, Jean Thierry-Mieg⁵, Guangchun Chen⁶, Anne Bergstrom Lucas⁷, Jennifer S LoCoco⁸, Todd A Richmond⁹, Elizabeth Tseng¹⁰, Rebecca Kusko¹¹, Scott Happe¹², Timothy R Mercer¹³, Carlos Pabón-Peña⁷, Michael Salmans⁸, Hagen U Tilgner^{14

15}, Wenzhong Xiao^{16

17}, Donald J Johann Jr¹⁸, Wendell Jones¹⁹, Weida Tong¹, Christopher E Mason^{20

21

22}, David P Kreil²³, Joshua Xu²⁴

Affiliations

¹ Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA.
² Małopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland.
³ Bioinformatics Research, Institute of Molecular Biotechnology, Boku University Vienna, Vienna, Austria.
⁴ Agilent Technologies, Inc., 11011 N Torrey Pines Rd., La Jolla, CA, 92037, USA.
⁵ National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD, 20894, USA.
⁶ Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, 5323 Harry Hine Blvd., Dallas, TX, 75390, USA.
⁷ Agilent Technologies, Inc., 5301 Stevens Creek Blvd., Santa Clara, CA, 95051, USA.
⁸ Illumina Inc., 5200 Illumina Way, San Diego, CA, 92122, USA.
⁹ Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., 4300 Hacienda Dr., Pleasanton, CA, 94588, USA.
¹⁰ PacBio, San Francisco, USA.
¹¹ Cellino Bio, 750 Main Street, Cambridge, MA, 02143, USA.
¹² Agilent Technologies, Inc., 1834 State Hwy 71 West, Cedar Creek, TX, 78612, USA.
¹³ Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, QLD, Australia.
¹⁴ Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
¹⁵ Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA.
¹⁶ Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA.
¹⁷ Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA.
¹⁸ Winthrop P Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301W Markham St., Little Rock, AR, 72205, USA.
¹⁹ Q squared Solutions Genomics, 2400 Elis Road, Durham, NC, 27703, USA.
²⁰ Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA. chm2042@med.cornell.edu.
²¹ The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA. chm2042@med.cornell.edu.
²² The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA. chm2042@med.cornell.edu.
²³ Bioinformatics Research, Institute of Molecular Biotechnology, Boku University Vienna, Vienna, Austria. David.Kreil@boku.ac.at.
²⁴ Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA. Joshua.Xu@fda.hhs.gov.

^# Contributed equally.

PMID: 39152166
PMCID: PMC11329654
DOI: 10.1038/s41597-024-03741-y

Targeted DNA-seq and RNA-seq of Reference Samples with Short-read and Long-read Sequencing

Binsheng Gong et al. Sci Data. 2024.

. 2024 Aug 16;11(1):892.

doi: 10.1038/s41597-024-03741-y.

Authors

Affiliations

¹ Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA.
² Małopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland.
³ Bioinformatics Research, Institute of Molecular Biotechnology, Boku University Vienna, Vienna, Austria.
⁴ Agilent Technologies, Inc., 11011 N Torrey Pines Rd., La Jolla, CA, 92037, USA.
⁵ National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD, 20894, USA.
⁶ Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, 5323 Harry Hine Blvd., Dallas, TX, 75390, USA.
⁷ Agilent Technologies, Inc., 5301 Stevens Creek Blvd., Santa Clara, CA, 95051, USA.
⁸ Illumina Inc., 5200 Illumina Way, San Diego, CA, 92122, USA.
⁹ Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., 4300 Hacienda Dr., Pleasanton, CA, 94588, USA.
¹⁰ PacBio, San Francisco, USA.
¹¹ Cellino Bio, 750 Main Street, Cambridge, MA, 02143, USA.
¹² Agilent Technologies, Inc., 1834 State Hwy 71 West, Cedar Creek, TX, 78612, USA.
¹³ Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, QLD, Australia.
¹⁴ Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
¹⁵ Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA.
¹⁶ Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA.
¹⁷ Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA.
¹⁸ Winthrop P Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301W Markham St., Little Rock, AR, 72205, USA.
¹⁹ Q squared Solutions Genomics, 2400 Elis Road, Durham, NC, 27703, USA.
²⁰ Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA. chm2042@med.cornell.edu.
²¹ The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA. chm2042@med.cornell.edu.
²² The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA. chm2042@med.cornell.edu.
²³ Bioinformatics Research, Institute of Molecular Biotechnology, Boku University Vienna, Vienna, Austria. David.Kreil@boku.ac.at.
²⁴ Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA. Joshua.Xu@fda.hhs.gov.

^# Contributed equally.

PMID: 39152166
PMCID: PMC11329654
DOI: 10.1038/s41597-024-03741-y

Abstract

Next-generation sequencing (NGS) has revolutionized genomic research by enabling high-throughput, cost-effective genome and transcriptome sequencing accelerating personalized medicine for complex diseases, including cancer. Whole genome/transcriptome sequencing (WGS/WTS) provides comprehensive insights, while targeted sequencing is more cost-effective and sensitive. In comparison to short-read sequencing, which still dominates the field due to high speed and cost-effectiveness, long-read sequencing can overcome alignment limitations and better discriminate similar sequences from alternative transcripts or repetitive regions. Hybrid sequencing combines the best strengths of different technologies for a more comprehensive view of genomic/transcriptomic variations. Understanding each technology's strengths and limitations is critical for translating cutting-edge technologies into clinical applications. In this study, we sequenced DNA and RNA libraries of reference samples using various targeted DNA and RNA panels and the whole transcriptome on both short-read and long-read platforms. This study design enables a comprehensive analysis of sequencing technologies, targeting protocols, and library preparation methods. Our expanded profiling landscape establishes a reference point for assessing current sequencing technologies, facilitating informed decision-making in genomic research and precision medicine.

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Conflict of interest statement

Upon the completion of this study, N.N., A.B.L., S.H., and C.P-P. are affiliated with Agilent Technologies, Inc., J.S.L. is affiliated with Illumina Inc., T.A.R. is affiliated with Roche Sequencing Solutions Inc., E.T. is affiliated with PacBio. Other authors declare no competing interest.

Figures

**Fig. 1**
Illustration of study design. **(a)** To create reference samples C, D, and E: samples A and B were mixed in the ratios of 1:1, 1:4, and 4:1 respectively. **(b)** Three types of libraries were prepared for the reference samples: targeted RNA, targeted DNA, and whole transcriptome RNA. The libraries were sequenced using short-read or long-read sequencing methods, or both. The panel codes are explained in Table 2. The pink “S” represents short-read sequencing, while green “L” represents long-read sequencing. The ILMR3 panel is a whole exome RNA panel, and it was placed under “targeted RNA” for visual simplicity. **(c)** Both targeted DNA and targeted RNA libraries were sequenced with short-read sequencing. For targeted DNA libraries, four library replicates (lib1-4) were prepared for Samples A, B, and C using AGLR1, AGLR2, and ROCR2. * Three library replicates (lib1-3) were prepared using ROCR1. Sample D was sequenced with ROCR1 instead of Sample C. For targeted RNA libraries, four library replicates (lib1-4) were prepared for Samples A, B, C, D, and E using 7 panels. **(d)** Targeted RNA libraries of Sample A, B, and C were made with three panels, each library was split into different fractions (F1, F1 + 2, or F3), and sequenced with both long-read sequencing platforms. **(e)** † ROCR2 was only used for Sample A and the libraries was sequenced only on Nanopore. ‡ Sample B was sequenced by Nanopore Direct RNA protocol only. **(f)** An illustration shows the flexible options for possible comparison analyses for an in-depth study of the impacts of targeting, size selection, and sequencing protocols.

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References

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Targeted DNA-seq and RNA-seq of Reference Samples with Short-read and Long-read Sequencing

Affiliations

Targeted DNA-seq and RNA-seq of Reference Samples with Short-read and Long-read Sequencing

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical