Best Practices

Enhancing Research Reproducibility with Biomaterials Characterized by Next-generation Sequencing

It is estimated that 50% of biological research data is irreproducible, and a significant portion of this irreproducibility is associated with research methodology, data analysis, gaps in data provenance, and poor biological materials.^1-3

In the scientific field, ensuring reproducibility is vital for maintaining integrity and reliability, especially given the heavy reliance of biomedical research on biological materials. Thus, prioritizing the quality and accuracy of these materials is crucial. Authenticated, well-characterized models significantly enhance reproducibility, leading to greater productivity and success in life science research, which is crucial in today's rapidly evolving technological landscape.⁴

When selecting biological models for study, understanding their inherent genomic diversity becomes essential as it directly shapes biological traits and phenotypes.⁵ The revolutionary advancement of next-generation sequencing (NGS) technology has made it possible for life science research to shift its focus from studying single genes to the entire genome over the past two decades. NGS not only addresses specific inquiries but also shapes and directs future research activities. Integration of various genomic data types (multi-omics) further aids in comprehending complex and core problems in biology.⁶ This amalgamation accelerates discovery and opens the door to personalized and precision medicine, ultimately advancing human health and well-being. However, NGS applications flood the public domain with enormous amounts of genomic data that frequently lack a consensus or standardized workflow for harmonizing data curation and analysis, often resulting in irreproducibility.^7-9

To address the inherent issues with public data, such as gaps in data provenance and ambiguity in the data harmonization process, ATCC has begun to define its biomaterials via NGS in order to ensure repeatability of data derived from these authenticated biomaterials in any independent setting.^1,^10,¹¹ While ATCC primarily focuses on collecting, preserving, and distributing biological materials, the organization also dedicates its efforts to meticulously characterizing the genetic and molecular attributes of these materials.¹² Recently, ATCC introduced two innovative new platforms: (1) the ATCC Genome Portal (AGP), which offers comprehensive data on microbial genomes; and (2) the ATCC Cell Line Land (ACLL), which offers comprehensive data on the transcriptomes and exomes of human and mouse cell lines. These initiatives underscore ATCC’s commitment to deepening its understanding of the genetic intricacies of its biomaterials. Through the AGP and the ACLL, ATCC delivers transparent and end-to-end solutions for reproducibility, exemplifying the necessity of including accurately curated research data with the biomaterials on offer.¹³ Explore the AGP and ACLL to stay up-to-date on the latest genomic advancements in characterizing the microorganisms and cell lines you currently use or plan to use and be part of the journey toward unlocking new biological dimensions by establishing scientific rigor and data reproducibility.

Did you know?

Our data adhere to F.A.I.R. data principles in that we deliver Findable, Accessible, Interoperable, and Reusable data that can significantly improve the quality of your research.

Meet the authors

Ajeet Singh, PhD

Senior Scientist, ATCC

Dr. Ajeet Singh is Senior Scientist at ATCC where he is focused on providing reference-grade whole transcriptome data that is authenticated, standard, and traceable to physical source materials available in ATCC’s biorepository. Prior to joining ATCC, Dr. Singh received his PhD in Agricultural Plant Pathology where he performed research focused on epidemiology and integrated management of plants pests and diseases. He then performed postdoctoral research at the National Institute of Environmental Health Sciences and subsequently worked as a Senior Staff Scientist at the National Cancer Institute. Dr. Singh has extensive experience in biomedical research with his research career expanding an array of interrelated disciplines exploring epigenetics, chromatin and gene expression in reproductive developmental toxicology, stem cell biology, and cancer.

Amy L. Reese, MS

Bioinformatician, Sequencing and Bioinformatics Center, ATCC

Amy Reese is a Bioinformatician with the Sequencing and Bioinformatics Center at ATCC. She has played a vital role in ATCC’s RNA sequencing collaboration with QIAGEN to create the ATCC Cell Line Land, an RNA-seq reference database for authenticated materials. Amy’s primary responsibility is to oversee and analyze all data for this collaboration; over 900 datasets have been shared with QIAGEN to-date. Amy’s other responsibilities include developing novel internal pipelines for the analysis of microorganisms for publication to the ATCC Genome Portal and performing additional RNA-seq analyses for other external collaborators, such as the NIH’s National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and Virginia Tech’s Center for Emerging, Zoonotic, and Arthropod-borne Pathogens (CEZAP).

Before joining ATCC in 2021, Amy held a position as a Virology Senior Research Associate at the National Biological Threat Characterization Center (NBTCC) of the National Biodefense Analysis and Countermeasures Center (NBACC). There, Amy worked as technical lead on projects working directly with high containment pathogens such as Ebola virus and SARS-CoV-2, and trained new employees in the BSL-2, 3, and 4 laboratories. Amy holds a Bachelor of Science in Biology, a Master of Science in Biology, and a Master of Science in Bioinformatics.

Jonathan Jacobs, PhD

Senior Director of Bioinformatics, ATCC

Dr. Jonathan Jacobs leads ATCC’s Sequencing & Bioinformatics Center and the development of the ATCC Genome Portal. He has over 20 years of experience in molecular genetics, bioinformatics, and microbial genomics, and he has worked throughout his career at the interface of academia, government, and industry. He holds a joint Research Professor appointment at Syracuse University’s Forensic & National Security Sciences Institute in support of microbial forensics graduate student training and research, and he actively collaborates with several US public health laboratories involved in pathogen genomics research and surveillance. Dr. Jacobs is also certified in Product Management from Pragmatic Institute, and he has led successful commercial launches of several bioinformatics products into the market.

Learn more about our reference-quality 'omics data

Discover ATCC's Transcriptomics Data

Learn more about our standardized workflow for producing transcriptomics data from the authenticated cell lines within our collection.

Concentric circles with purple, orange and yellow markers for DNA sequencing.

Discover the ATCC Genome Portal

The ATCC Genome Portal is a rapidly growing ISO 9001–compliant database of high-quality reference genomes from authenticated microbial strains in the ATCC collection. Through this cloud-based platform, you can easily access and download meticulously curated whole-genome sequences from your browser or our secure API. With high-quality, annotated data at your fingertips, you can confidently perform bioinformatics analyses and make insightful correlations.

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Baker M. Irreproducible biology research costs put at $28 billion per year. Nature doi:10.1038/nature.2015.17711, 2015.
Raphael MP, Sheehan PE, Vora GJ. A controlled trial for reproducibility. Nature 579(7798): 190-192, 2020. PubMed: 32157231
Geraghty RJ, et al. Guidelines for the use of cell lines in biomedical research. Br J Cancer 111(6): 1021-1046, 2014. PubMed: 25117809
Luh F, Yen Y. FDA guidance for next generation sequencing-based testing: balancing regulation and innovation in precision medicine. NPJ Genom Med 3: 28, 2018. PubMed: 30302274
Flier JS. Irreproducibility of published bioscience research: Diagnosis, pathogenesis and therapy. Mol Metab 6(1): 2-9, 2017. PubMed: 8123930
Stephens ZD, et al. Big Data: Astronomical or Genomical? PLoS Biol 13(7): e1002195, 2015. PubMed: 26151137
Endrullat C, et al. Standardization and quality management in next-generation sequencing.Appl Transl Genom 10: 2-9, 2016. PubMed: 27668169
Macleod M. Improving the reproducibility and integrity of research: what can different stakeholders contribute? BMC Res Notes 15(1): 146, 2022. PubMed: 35468858
Wallach JD, Boyack KW, Ioannidis JPA. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015-2017. PLoS Biol 16(11): e2006930, 2018. PubMed: 30457984
Riss TL, et al. Treating Cells as Reagents to Design Reproducible Assays. SLASDiscov 23(10): 1256-1267, 2021. PubMed: 34530643
Yarmosh DA, et al. Comparative Analysis and Data Provenance for 1,113 Bacterial Genome Assemblies. mSphere 7(3): e0007722, 2022. PubMed: 35491842

Enhancing Research Reproducibility with Biomaterials Characterized by Next-generation Sequencing

It is estimated that 50% of biological research data is irreproducible, and a significant portion of this irreproducibility is associated with research methodology, data analysis, gaps in data provenance, and poor biological materials.^1-3

Did you know?

Our data adhere to F.A.I.R. data principles in that we deliver Findable, Accessible, Interoperable, and Reusable data that can significantly improve the quality of your research.