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1. A diploid assembly-based benchmark for variants in the major histocompatibility complex

Author

Chen-Shan Chin, Justin Wagner, Qiandong Zeng, Erik Garrison, Shilpa Garg, Arkarachai Fungtammasan, Mikko Rautiainen, Sergey Aganezov, Melanie Kirsche, Samantha Zarate, Michael C. Schatz, Chunlin Xiao, William J. Rowell, Charles Markello, Jesse Farek, Fritz J. Sedlazeck, Vikas Bansal, Byunggil Yoo, Neil Miller, Xin Zhou, Andrew Carroll, Alvaro Martinez Barrio, Marc Salit, Tobias Marschall, Alexander T. Dilthey, and Justin M. Zook

Subjects
Science
Abstract

Accurate, phased assemblies are a key tool in understanding the human genome, particularly in highly polymorphic regions like the medically important MHC. Here the authors provide an assembly-based benchmark for this difficult-to-characterize region.

Published
2020
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2. A crowdsourced set of curated structural variants for the human genome.

Author

Lesley M Chapman, Noah Spies, Patrick Pai, Chun Shen Lim, Andrew Carroll, Giuseppe Narzisi, Christopher M Watson, Christos Proukakis, Wayne E Clarke, Naoki Nariai, Eric Dawson, Garan Jones, Daniel Blankenberg, Christian Brueffer, Chunlin Xiao, Sree Rohit Raj Kolora, Noah Alexander, Paul Wolujewicz, Azza E Ahmed, Graeme Smith, Saadlee Shehreen, Aaron M Wenger, Marc Salit, and Justin M Zook

Subjects
Biology (General), QH301-705.5
Abstract

A high quality benchmark for small variants encompassing 88 to 90% of the reference genome has been developed for seven Genome in a Bottle (GIAB) reference samples. However a reliable benchmark for large indels and structural variants (SVs) is more challenging. In this study, we manually curated 1235 SVs, which can ultimately be used to evaluate SV callers or train machine learning models. We developed a crowdsourcing app-SVCurator-to help GIAB curators manually review large indels and SVs within the human genome, and report their genotype and size accuracy. SVCurator displays images from short, long, and linked read sequencing data from the GIAB Ashkenazi Jewish Trio son [NIST RM 8391/HG002]. We asked curators to assign labels describing SV type (deletion or insertion), size accuracy, and genotype for 1235 putative insertions and deletions sampled from different size bins between 20 and 892,149 bp. 'Expert' curators were 93% concordant with each other, and 37 of the 61 curators had at least 78% concordance with a set of 'expert' curators. The curators were least concordant for complex SVs and SVs that had inaccurate breakpoints or size predictions. After filtering events with low concordance among curators, we produced high confidence labels for 935 events. The SVCurator crowdsourced labels were 94.5% concordant with the heuristic-based draft benchmark SV callset from GIAB. We found that curators can successfully evaluate putative SVs when given evidence from multiple sequencing technologies.

Published
2020
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3. Cell-based reference samples designed with specific differences in microRNA biomarkers

Author

P. Scott Pine, Steven P. Lund, Sanford A. Stass, Debra Kukuruga, Feng Jiang, Lynn Sorbara, Sudhir Srivastava, and Marc Salit

Subjects
Reverse transcription PCR (RT-PCR), microRNA (miRNA), Reference samples, Biomarkers, Performance assessment, Measurement assurance, Biotechnology, TP248.13-248.65
Abstract

Abstract Background We demonstrate the feasibility of creating a pair of reference samples to be used as surrogates for clinical samples measured in either a research or clinical laboratory setting. The reference sample paradigm presented and evaluated here is designed to assess the capability of a measurement process to detect true differences between two biological samples. Cell-based reference samples can be created with a biomarker signature pattern designed in silico. Clinical laboratories working in regulated applications are required to participate in proficiency testing programs; research laboratories doing discovery typically do not. These reference samples can be used in proficiency tests or as process controls that allow a laboratory to evaluate and optimize its measurement systems, monitor performance over time (process drift), assess changes in protocols, reagents, and/or personnel, maintain standard operating procedures, and most importantly, provide evidence for quality results. Results The biomarkers of interest in this study are microRNAs (miRNAs), small non-coding RNAs involved in the regulation of gene expression. Multiple lung cancer associated cell lines were determined by reverse transcription (RT)-PCR to have sufficiently different miRNA profiles to serve as components in mixture designs as reference samples. In silico models based on the component profiles were used to predict miRNA abundance ratios between two different cell line mixtures, providing target values for profiles obtained from in vitro mixtures. Two reference sample types were tested: total RNA mixed after extraction from cell lines, and intact cells mixed prior to RNA extraction. MicroRNA profiling of a pair of samples composed of extracted RNA derived from these cell lines successfully replicated the target values. Mixtures of intact cells from these lines also approximated the target values, demonstrating potential utility as mimics for clinical specimens. Both designs demonstrated their utility as reference samples for inter- or intra-laboratory testing. Conclusions Cell-based reference samples can be created for performance assessment of a measurement process from biomolecule extraction through quantitation. Although this study focused on miRNA profiling with RT-PCR using cell lines associated with lung cancer, the paradigm demonstrated here should be extendable to genome-scale platforms and other biomolecular endpoints.

Published
2018
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5. Synthetic spike-in standards improve run-specific systematic error analysis for DNA and RNA sequencing.

Author

Justin M Zook, Daniel Samarov, Jennifer McDaniel, Shurjo K Sen, and Marc Salit

Subjects
Medicine, Science
Abstract

While the importance of random sequencing errors decreases at higher DNA or RNA sequencing depths, systematic sequencing errors (SSEs) dominate at high sequencing depths and can be difficult to distinguish from biological variants. These SSEs can cause base quality scores to underestimate the probability of error at certain genomic positions, resulting in false positive variant calls, particularly in mixtures such as samples with RNA editing, tumors, circulating tumor cells, bacteria, mitochondrial heteroplasmy, or pooled DNA. Most algorithms proposed for correction of SSEs require a data set used to calculate association of SSEs with various features in the reads and sequence context. This data set is typically either from a part of the data set being "recalibrated" (Genome Analysis ToolKit, or GATK) or from a separate data set with special characteristics (SysCall). Here, we combine the advantages of these approaches by adding synthetic RNA spike-in standards to human RNA, and use GATK to recalibrate base quality scores with reads mapped to the spike-in standards. Compared to conventional GATK recalibration that uses reads mapped to the genome, spike-ins improve the accuracy of Illumina base quality scores by a mean of 5 Phred-scaled quality score units, and by as much as 13 units at CpG sites. In addition, since the spike-in data used for recalibration are independent of the genome being sequenced, our method allows run-specific recalibration even for the many species without a comprehensive and accurate SNP database. We also use GATK with the spike-in standards to demonstrate that the Illumina RNA sequencing runs overestimate quality scores for AC, CC, GC, GG, and TC dinucleotides, while SOLiD has less dinucleotide SSEs but more SSEs for certain cycles. We conclude that using these DNA and RNA spike-in standards with GATK improves base quality score recalibration.

Published
2012
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7. The Coronavirus Standards Working Group’s roadmap for improved population testing

Author

Tim Mercer, Neil Almond, Michael A. Crone, Patrick S. G. Chain, Alina Deshpande, Deepa Eveleigh, Paul Freemont, Sebastien Fuchs, Russell Garlick, Jim Huggett, Martin Kammel, Po-E Li, Mojca Milavec, Elizabeth M. Marlowe, Denise M. O’Sullivan, Mark Page, Gary A. Pestano, Sara Suliman, Birgitte Simen, John J. Sninsky, Lynne Sopchak, Cristina M. Tato, Peter M. Vallone, Jo Vandesompele, Thomas J. White, Heinz Zeichhardt, and Marc Salit

Subjects
Biomedical Engineering, Molecular Medicine, Bioengineering, Applied Microbiology and Biotechnology, Biotechnology
Published
2022

9. Benchmarking challenging small variants with linked and long reads

Author

Justin Wagner, Nathan D. Olson, Lindsay Harris, Ziad Khan, Jesse Farek, Medhat Mahmoud, Ana Stankovic, Vladimir Kovacevic, Byunggil Yoo, Neil Miller, Jeffrey A. Rosenfeld, Bohan Ni, Samantha Zarate, Melanie Kirsche, Sergey Aganezov, Michael C. Schatz, Giuseppe Narzisi, Marta Byrska-Bishop, Wayne Clarke, Uday S. Evani, Charles Markello, Kishwar Shafin, Xin Zhou, Arend Sidow, Vikas Bansal, Peter Ebert, Tobias Marschall, Peter Lansdorp, Vincent Hanlon, Carl-Adam Mattsson, Alvaro Martinez Barrio, Ian T. Fiddes, Chunlin Xiao, Arkarachai Fungtammasan, Chen-Shan Chin, Aaron M. Wenger, William J. Rowell, Fritz J. Sedlazeck, Andrew Carroll, Marc Salit, and Justin M. Zook

Abstract

Genome in a Bottle benchmarks are widely used to help validate clinical sequencing pipelines and develop variant calling and sequencing methods. Here we use accurate linked and long reads to expand benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are challenging for short reads. These benchmarks add more than 300,000 SNVs and 50,000 insertions or deletions (indels) and include 16% more exonic variants, many in challenging, clinically relevant genes not covered previously, such as

Published
2022

12. Single cell quantification of ribosome occupancy in early mouse development

Author

Tori Tonn, Hakan Ozadam, Crystal Han, Alia Segura, Duc Tran, David Catoe, Marc Salit, and Can Cenik

Abstract

Technological limitations precluded transcriptome-wide analyses of translation at single cell resolution. To solve this challenge, we developed a novel microfluidic isotachophoresis approach, named RIBOsome profiling via IsoTachoPhoresis (Ribo-ITP), and characterized translation in single oocytes and embryos during early mouse development. We identified differential translation efficiency as a key regulatory mechanism of genes involved in centrosome organization and N6-methyladenosine modification of RNAs. Our high coverage measurements enabled the first analysis of allele-specific ribosome engagement in early development and led to the discovery of stage-specific differential engagement of zygotic RNAs with ribosomes. Finally, by integrating our measurements with proteomics data, we discovered that ribosome occupancy in germinal vesicle stage oocytes is the predominant determinant of protein abundance in the zygote. Taken together, these findings resolve the long-standing paradox of low correlation between RNA expression and protein abundance in early embryonic development. The novel Ribo-ITP approach will enable numerous applications by providing high coverage and high resolution ribosome occupancy measurements from ultra-low input samples including single cells.

Published
2021

13. MAQC and the era of genomic medicine

Author

Marc, Salit and Janet, Woodcock

Subjects
Quality Control, United States Food and Drug Administration, International Cooperation, Humans, Genomics, United States, Oligonucleotide Array Sequence Analysis
Published
2021

14. COVID-19 Testing R&D (Final Report)

Author

Rebecca Abergel, Parul Adams, Dion Antonopoulos, Gyorgy Babnigg, Scott Baker, Daniel Bedinger, Monica Borucki, Steven Bradfute, Thomas Bunt, Chris Daum, Joseph Fitch, Vince Gerbasi, Paul Gilna, David Graham, Michael Guarnieri, Sally Hall, Nathan Hillson, Elizabeth Hong-Geller, Greg Hura, Crystal Jaing, Ramesh Jha, Andrzej Joachimiak, Bishoy Kamel, Jeff Kimbrel, Antonietta Lillo, Betty Mangadu, Robert Meagher, Joseph Moon, Nigel Mouncey, Michael Morrison, Nisha Mulakken, Hau Nguyen, Marit Nilsen-Hamilton, Kristin Omberg, Hugh O'Neal, Jerry Parks, Lili Pasa-Tolic, Christa Pennacchio, Dave Rakestraw, Scott Retterer, Marc Salit, Blake Simmons, Anup Singh, Jess Sustarich, James Thissen, Nileena Velappan, Geoffrey Waldo, Kelly Williams, Jesse Wilson, Chunyan Ye, Malin Young, Yuko Yoshinaga, and Mowei Zhou

Published
2021

15. Benchmarking challenging small variants with linked and long reads

Author

Justin Wagner, Nathan D Olson, Lindsay Harris, Jennifer McDaniel, Ziad Khan, Jesse Farek, Medhat Mahmoud, Ana Stankovic, Vladimir Kovacevic, Byunggil Yoo, Neil Miller, Jeffrey A. Rosenfeld, Bohan Ni, Samantha Zarate, Melanie Kirsche, Sergey Aganezov, Michael Schatz, Giuseppe Narzisi, Marta Byrska-Bishop, Wayne Clarke, Uday S. Evani, Charles Markello, Kishwar Shafin, Xin Zhou, Arend Sidow, Vikas Bansal, Peter Ebert, Tobias Marschall, Peter Lansdorp, Vincent Hanlon, Carl-Adam Mattsson, Alvaro Martinez Barrio, Ian T Fiddes, Chunlin Xiao, Arkarachai Fungtammasan, Chen-Shan Chin, Aaron M Wenger, William J Rowell, Fritz J Sedlazeck, Andrew Carroll, Marc Salit, and Justin M Zook

Subjects
Structural variation, Computer science, Centromere, Benchmark (computing), PMS2, Computational biology, Benchmarking, Copy-number variation, Indel, Genome, Gene, Segmental duplication
Abstract

Genome in a Bottle (GIAB) benchmarks have been widely used to help validate clinical sequencing pipelines and develop new variant calling and sequencing methods. Here we use accurate long and linked reads to expand the prior benchmark to include difficult-to-map regions and segmental duplications that are not readily accessible to short reads. Our new benchmark adds more than 300,000 SNVs, 50,000 indels, and 16 % new exonic variants, many in challenging, clinically relevant genes not previously covered (e.g., PMS2). We increase coverage of the autosomal GRCh38 assembly from 85 % to 92 %, while excluding problematic regions for benchmarking small variants (e.g., copy number variants and assembly errors) that should not have been in the previous version. Our new benchmark reliably identifies both false positives and false negatives across multiple short-, linked-, and long-read based variant calling methods. As an example of its utility, this benchmark identifies eight times more false negatives in a short read variant call set relative to our previous benchmark, mostly in difficult-to-map regions. To enable robust small variant benchmarking, we still exclude 3.6% of GRCh37 and 5.0% of GRCh38 in (1) highly repetitive regions such as large, highly similar segmental duplications and the centromere not accessible to our data and (2) regions where our sample is highly divergent from the reference due to large indels, structural variation, copy number variation, and/or errors in the reference (e.g., some KIR genes that have duplications in HG002). We have demonstrated the utility of this benchmark to assess performance in more challenging regions, which enables benchmarking in more difficult genes and continued technology and bioinformatics development. The v4.2.1 benchmarks are available under ftp://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/AshkenazimTrio/.

Published
2020

16. Reproducible integration of multiple sequencing datasets to form high-confidence SNP, indel, and reference calls for five human genome reference materials

Author

Justin M. Zook, Jennifer McDaniel, Hemang Parikh, Haynes Heaton, Sean A. Irvine, Len Trigg, Rebecca Truty, Cory Y. McLean, Francisco M. De La Vega, Chunlin Xiao, Stephen Sherry, and Marc Salit

Subjects
0303 health sciences, Computer science, Genomics, Single-nucleotide polymorphism, Context (language use), Computational biology, Genome, Personal Genome Project, 03 medical and health sciences, 0302 clinical medicine, 030220 oncology & carcinogenesis, Human genome, International HapMap Project, Indel, 030304 developmental biology, Reference genome
Abstract

Benchmark small variant calls from the Genome in a Bottle Consortium (GIAB) for the CEPH/HapMap genome NA12878 (HG001) have been used extensively for developing, optimizing, and demonstrating performance of sequencing and bioinformatics methods. Here, we improve and simplify the methods we use to integrate multiple sequencing datasets, with the intention of deploying a reproducible cloud-based pipeline for application to arbitrary human genomes. We use these reproducible methods to form high-confidence calls with respect to GRCh37 and GRCh38 for HG001 and 4 additional broadly-consented genomes from the Personal Genome Project that are available as NIST Reference Materials. Our new methods produce 17% more SNPs and 176% more indels than our previously published calls for HG001. We also phase 99.5% of the variants in HG001 and call about 90% of the reference genome with high-confidence, increased from 78% previously. Our calls only contain 108 differences from the Illumina Platinum Genomes calls in GRCh37, only 14 of which are ambiguous or likely to be errors in our calls. By comparing several callsets to our new calls, our previously published calls, and Illumina Platinum Genomes calls, we highlight challenges in interpreting performance metrics when benchmarking against imperfect high-confidence calls. Our new calls address some of these challenges, but performance metrics should always be interpreted carefully. Benchmarking tools from the Global Alliance for Genomics and Health are useful for stratifying performance metrics by variant type and genome context to elucidate strengths and weaknesses of a method. We also explore differences between comparing to high-confidence calls for the 5 GIAB genomes, and show that performance metrics for one pipeline are largely similar but not identical when comparing to the 5 genomes. Finally, to explore applicability of our methods for genomes that have fewer datasets, we form high-confidence calls using only Illumina and 10x Genomics, and find that they have more high-confidence calls but have a higher error rate. These newly characterized genomes have a broad, open consent with few restrictions availability of samples and data, enabling a uniquely diverse array of applications.

Published
2018

17. List of Contributors

Author

Haley Abel, Shankar Ajay, Hussam Al-Kateb, Sami S. Amr, Andrew J. Bredemeyer, Fengqi Chang, Elizabeth C. Chastain, Deanna M. Church, Paul Cliften, Catherine E. Cottrell, Andrew Drury, Eric Duncavage, Birgit Funke, Amy S. Gargis, Ian S. Hagemann, Tina M. Hambuch, Madhuri R. Hegde, Michelle Hogue, Vanessa L. Horner, Lisa Kalman, Shamika Ketkar, Roger D. Klein, Shashikant Kulkarni, William A. LaFramboise, Marilyn M. Li, Cindy J. Liu, Geoffrey L. Liu, Ira M. Lubin, Elaine Lyon, Donna R. Maglott, Rong Mao, John Mayfield, Carri-Lyn Mead, Rakesh Nagarajan, Yuri E. Nikiforov, Marina N. Nikiforova, Alex Nord, Brendan D. O’Fallon, John Pfeifer, Colin Pritchard, Erica Ramos, Kris Rickhoff, Kristina A. Roberts, Wendy S. Rubinstein, Stephen J. Salipante, Marc Salit, Jennifer K. Sehn, Benjamin D. Solomon, Stephanie Solomon, David H. Spencer, Bin Zhang, and Justin Zook

Published
2015

18. Standards in gene expression microarray experiments

Author

Marc, Salit

Subjects
Gene Expression Profiling, Animals, Gene Expression, Humans, Reference Standards, Oligonucleotide Array Sequence Analysis
Abstract

The use of standards in gene expression measurements with DNA microarrays is ubiquitous--they just are not yet the kind of standards that have yielded microarray gene expression profiles that can be readily compared across different studies and different laboratories. They also are not yet enabling microarray measurements of the known, verifiable quality needed so they can be used with confidence in genomic medicine in regulated environments.

Published
2006

19. Peritoneal dialysis solution calcium concentration regulates peritoneal fibroblast proliferation in CAPD

Author

Silvia Carozzi, Marc Salit, M. G. Nasini, and Alberto Cantaluppi

Subjects
Male, medicine.medical_specialty, Lymphocyte, medicine.medical_treatment, Biomedical Engineering, Biophysics, chemistry.chemical_element, Bioengineering, Calcium, In Vitro Techniques, Peritoneal dialysis, Biomaterials, Peritoneal cavity, Interferon-gamma, Peritoneal Dialysis, Continuous Ambulatory, Internal medicine, Dialysis Solutions, medicine, Humans, Lymphocytes, Fibroblast, Peritoneal Fibrosis, business.industry, Macrophages, Continuous ambulatory peritoneal dialysis, General Medicine, Fibroblasts, Middle Aged, Fibrosis, In vitro, Surgery, medicine.anatomical_structure, Endocrinology, chemistry, Female, Peritoneum, business, Cell Division, Interleukin-1
Abstract

Peritoneal fibrosis remains one of the major causes of dropout in continuous ambulatory peritoneal dialysis (CAPD), by reducing ultrafiltration capacity. Since studies in vitro have shown that cytoplasmic Ca2+ regulates the proliferation of most cell lines and the release of cytokines from immune cells, eight uremics and four controls at the start of CAPD were evaluated for the in vitro effects of different peritoneal dialysis solution (PDS) Ca2+ concentrations (1, 1.25, 1.75, and 2 mmol/L) on: 1) peritoneal fibroblast (PF) proliferation; 2) peritoneal macrophage (PM) and peritoneal lymphocyte (PL) release of interleukin-1 (IL-1) and interferon-gamma (IFN-gamma)--cytokines that are known to induce PF proliferation; and 3) cytoplasmic Ca2+ concentrations in PF, PM, and PL. Results showed that in both the uremics and controls, increasing the dose of Ca2+ in the medium induced a dose-dependent rise in PF proliferation, and in the release of IL-1 and IFN-gamma from PM and PL. Meanwhile, the cytoplasmic Ca2+ concentration of PF, PM, and PL also increased. With a PDS containing 1 mmol/L of Ca2+ in the uremics, these parameters were below normal; they exceeded the norm with a Ca2+ concentration of 1.75 and 2 mmol/L, and were normal with a Ca2+ concentration of 1.25 mmol/L. These data suggest that in CAPD patients, the use of a low Ca2+ PDS (1 and 1.25 mmol/L) may be useful in reducing the proliferation of PF and the production of IL-1 and IFN-gamma from PM and PL, thereby preventing peritoneal sclerosis.

Published
1992

21. Reproducibility of Fluorescent Expression from Engineered Biological Constructs in E. coli

Author

Jacob, Beal, Trac Haddock Angellii, Markus, Gershater, Kim de Mora, Meagan, Lizarazo, Jim, Hollenhorst, Randy, Rettberg, Philipp, Demling, Rene, Hanke, Michae, Osthegel, Anna, Schechtel, Suresh, Sudarsan, Arne, Zimmermann, Bartosz, Gabryelczyk, Martina, Ikonen, Minnamari, Salmela, Muradıye, Acar, Muhammed Fatih Aktas, Furkan, Bestepe, Furkan Sacit Ceylan, Sadık, Cigdem, Mikail, Dohan, Mustafa, Elitok, Mehmet, Gunduz, Esra, Gunduz, Omer Faruk Hatipoglu, Turan, Kaya, Orhan, Sayin, Safa, Tapan, Osman Faruk Tereci, Abdullah, Uçar, Mustafa, Yilmaz, Jeffrey, Barrick, Alex, Gutierrez, Dennis, Mishler, Jordan, Monk, Kate, Mortensen, Nathan, Shin, Ella, Watkins, Yintong, Chen, Yuji, Jin, Yuanjie, Shi, Haoqian Myelin Zhang, Bruno, Ono, Ieda Maria Martinez Paino, Lais, Ribovski, Ivan, Silva, Danilo Keiji Zampronio, Nils, Birkholz, Rudiger Frederik Busche, Oliver, Konzock, Steffen, Lippold, Carsten, Ludwig, Melanie, Philippi, Lukas, Platz, Christian, Sigismund, Susanne, Weber, Maren, Wehrs, Niels, Werchau, Anna, Wronska, Zen Zen Yen, Yash, Agarwal, Evan, Appleton, Douglas, Densmore, Ariela, Esmurria, Kathleen, Lewis, Alan, Pacheco, Marcel, Bruchez, Danielle, Peters, Cheryl, Telmer, Lena, Wang, Silvia Canas Duarte, Daniel Giraldo Perez, Camilo Gomez Garzon, Jorge Madrid Wolff, Nathaly Marin Medina, Valentina, Mazzanti, Laura Rodriguez Forero, Eitan, Scher, Robin, Dowell, Samantha, O’Hara, Cloe Simone Pogoda, Kendra, Shattuck, Ali, Altintas, Anne Pihl Bali, Rasmus, Bech, Anne, Egholm, Anne Sofie Laerke Hansen, Kristian, Jensen, Kristian Barreth Karlsen, Caroline, Mosbech, Sophia, Belkhelfa, Noemie, Berenger, Romain, Bodinier, Cecile, Jacry, Laura Matabishi Bibi, Pierre, Parutto, Julie, Zaworski, Andries de Vries, Freek de Wijs, Rick, Elbert, Lisa, Hielkema, Chandhuru, Jagadeesan, Bayu, Jayawardhana, Oscar, Kuipers, Anna, Lauxen, Thomas, Meijer, Sandra, Mous, Renske van Raaphorst, Aakanksha, Saraf, Otto, Schepers, Oscar, Smits, Jan Willem Veening, Ruud Detert Oude Weme, Lianne, Wieske, Catherine, Ainsworth, Xenia Spencer Milnes, Alejandro, Gómezávila, Eddie Cano Gamez, Ana Laura Torres Huerta, Carlos Alejandro Meza Ramirez, Philipp, Popp, Jara, Radeck, Anna, Sommer, Xiangkai, Li, Qi, Wu, Hongxia, Zhao, Ruixue, Zhao, Irem, Bastuzel, Yasemin, Ceyhan, Mayda, Gursel, Burak, Kizil, Ilkem, Kumru, Yasemin, Kuvvet, Helin, Tercan, Seniz, Yuksel, Luiza, Niyazmetova, Timothy, Ang, Lucas, Black, Ciaran, Kelly, George, Wadhams, Clovis, Basier, Urszula, Czerwinska, Cindy Suci Ananda, Muhammad Al Azhar, Adelia, Elviantari, Maya, Fitriana, Arief Budi Witarto, Yuliant, Jia Fangxing, Qingfeng, Hou, Wan, Pei, Chen, Rifei, Wang, Rong, Huang, Wei, Zhang, Yushan, Jianguo, He, Dengwen, Lai, Pai, Li, Jianheng, Liu, Chunyang, Ni, Qianbin, Zhang, Cinthya, Cadenas, Zardain Canabal, Eduardo J., Claudia Nallely Alonso Cantu, Mercedes Alejandra Vazquez Cantu, Eduardo Cepeda Canedo, Cesar Miguel Valdez Cordova, Jose Alberto de la Paz Espinosa, Carlos Enrique Alavez Garcia, Ana Laura Navarro Heredia, Adriana, Hernandez, Sebastian Valdivieso Jauregui, Eduardo Ramirez Montiel, Eduardo Serna Morales, Yamile Minerva Castellanos Morales, Omar Alonso Cantu Pena, Ramirez Rodríguez, Eduardo A., Elizabeth Vallejo Trejo, Jesus Gilberto Rodriguez Ceja, Jesus Eduardo Martinez Hernandez, Mario Alberto Pena Hernandez, Enrique Amaya Perez, Rebeca Paola Torres Ramirez, Cla, J., Martin, Hanzel, Sarah Mohand Said, Shihab, Sawar, Dylan, Siriwardena, Alex, Tzahristos, Nils, Anlind, Martin, Friberg, Erik, Gullberg, Stephanie, Herman, Dallin, Christensen, Sara, Gertsch, Cody, Maxfield, Charles, Miller, Ryan, Putman, Christine, Bauerl, Estelles Lopez, Lucia T., Estefania Huet Trujillo, Marta Vazquez Vilar, Marlène Sophie Birk, Nico, Claassens, Walter de Koster, Rik van Rosmalen, Wen Ying Wu, Sian, Davies, Dan, Goss, William, Rostain, Chelsey, Tye, Waqar, Yousaf, Natalie, Farny, Chloe, Lajeunesse, Alex, Turland, Chen, An, Jielin, Chen, Yahong, Chen, Zehua, Che, Baishan, Fang, Xiaotong, Fu, Xifeng, Guo, Yue, Jiang, Yiying, Lei, Jianqiao, Li, Zhe, Li, Chang, Liu, Weibing, Liu, Yang, Li, Yizhu, Lv, Qingyu, Ruan, Yue, Su, Chun, Tang, Yushen, Wang, Fan, Wu, Xiaoshan, Yan, Ruihua, Zhang, Tangduo, Zhang, Farren, Isaacs, Ariel Leyva Hernandez, Natalie, Ma, Stephanie, Mao, Yamini, Naidu, Tuukka, Miinalainen, Marion Aruann, Daniel Calendini, Yoann Chabert, Gael Chambonnier, Myriam, Choukour, Ella de Gaulejac, Camille, Houy, Axel, Levier, Loreen, Logger, Sebastien, Nin, Valerie, Prima, Sturgis, James N., Beibei, Fang, Sadik, Cigdem, Abdullah, Ucar, Alejandro, Gutierrez, Revanth, Poondla, Sanjana, Reddy, Tyler, Rocha, Natalie, Schulte, Devin, Wehle, Marta Eva Jackowski, Sean Ross Craig, Ariana Mirzarafie Ahi, Elliott, Parris, Luba, Prout, Barbara, Steijl, Rachel, Wellman, Zhao, Fan, Zhang, Jing, Yang, Wei, Yang, Yuanzhan, Wen, Zhaosen, Evan, Appletion, Jeffrey, Chen, Abha, Patil, Shaheer, Priracha, Kate, Ryan, Nick, Salvador, John, Viola, Boralli, Camila Maria S., Camila Barbosa Bramorski, Juliana Cancino Bernardi, Ana Laura de Lima, Paula Maria Pincela Lins, Cristiane Casonato Melo, Deborah Cezar Mendonca, Thiago, Mosqueiro, Everton, Silva, Graziele, Vasconcelos, Ruchi, Asthana, Donna, Lee, Michelle, Yu, Peter, Choi, Effie, Lau, Kenneth, Lau, Oscar, Ying, Brandon, Malone, Paul, Young, Aidan, Ceney, Dakota, Hawthorne, Sharon, Lian, Sam, Mellentine, Dylan, Miller, Barbara Castro Moreira, Christie, Peebles, Olivia, Smith, Kevin, Walsh, Allison, Zimont, Michael, Brasino, Michael, Donovan, Hannah, Young, Jan, Bejvl, Daniel, Georgiev, Hynek, Kasl, Katerina Pechotova, Vaclav Pelisek, Anna, Sosnova, Pavel, Zach, Anthony, Ciesla, Benjamin, Hoover, Elliott, Chapman, Jon Marles Wright, Vicky, Moynihan, Liusaidh, Owen, Brooke Rothschild Mancinelli, Emilie, Cuillery, Joseph, Heng, Vincent, Jacquot, Paola, Malsot, Rocco, Meli, Cyril, Pulver, Ari, Sarfatis, Loic, Steiner, Victor, Steininger, Nina van Tiel, Gregoire, Thouvenin, Axel, Uran, Lisa, Baumgartner, Anna, Fomitcheva, Daniel, Gerngross, Verena, Jagger, Michael, Meier, Anja, Michel, Jasmine, Bird, Bradley, Brown, Todd, Burlington, Daniel, Herring, Joseph, Slack, Georgina, Westwood, Emilia, Wojcik, Julian, Bender, Julia, Donauer, Ramona, Emig, Rabea, Jesser, Julika, Neumann, Lara, Stuhn, Takema, Hasegawa, Tomoya, Kozakai, Haruka, Maruyama, Sean, Colloms, Charlotte, Flynn, Vilija, Lomeikaite, James, Provan, Kang, Ning, Shuyan, Tang, Guozhao, Wu, Yunjun, Yang, Zhi, Zeng, Zhan, Yi, Pan, Chu, Jun, Li, Keji, Yan, Athale, Chaitanya A., Swapnil, Bodkhe, Manasi, Gangan, Harsh, Gakhare, Yash, Jawale, Snehal, Kadam, Prachiti, Moghe, Gayatri, Mundhe, Neha, Khetan, Ira, Phadke, Prashant, Uniyal, Siddhesh, Zadey, Ines, Cottignie, Eline, Deprez, Astrid, Deryckere, Jasper, Janssens, Frederik, Jonnaert, Katarzyna, Malczewska, Thomas, Pak, Johan, Robben, Ovia Margaret Thirukkumaran, Vincent Van Deuren, Laurens, Vandebroek, Laura Van Hese, Laetitia Van Wonterghem, Leen, Verschooten, Moritz, Wolter, Joss, Auty, Richard, Badge, Liam, Crawford, Raymond, Dalgleish, Amy, Evans, Cameron, Grundy, Charlie, Kruczko, Payal, Karia, Graeme, Glaister, Rhys, Hakstol, Seme, Mate, Karin, Otero, Dustin, Smith, Jeff, Tingley, Hans Joachim Wieden, Haotian, Wang, Ningning, Yao, Matthias, Franz, Anna, Knoerlein, Nicolas, Koutsoubelis, Loechner, Anne C., Max, Mundt, Alexandra, Richter, Oliver, Schauer, Marjorie, Buss, Sivateja, Tangirala, Brian, Teague, Tianyi, Huang, Xinhao, Song, Yibing, Wei, Zhaoran, Zhang, Longzhi, Cao, Cheng Li, Kang Yang, Zhiqin, Chen, Yuxing, Fang, Libo, Sun, Weiyi, Wang, Yang, Yang, David, Adams, Joshua, Colls, Joshua, Timmons, David, Urick, Julia Anna Adrian, Madina, Akan, Youssef, Chahibi, Rahmi, Lale, Typhaine Le Doujet, Marit Vaagen Roee, Altynay, Abdirakhmanova, Askarbek, Orakov, Azhar, Zhailauova, Jinyang, Liang, Yu, Ma, Qikai, Qin, Yetian, Su, Ju Yeon Han, Raphaella, Hull, Wei Chung Kong, Li Chieh Lu, Duke, Quinton, Pauline, Aubert, Johan, Bourdarias, Olivier, Bugaud, Coralie Demon Chaine, Isabelle, Hatin, Ibtissam Kaid Slimane, Seong Koo Kang, Audrey, Moatti, Cheikh Fall Ndiaye, Mathilde, Ananos, Alexander, Arkhipenko, Valentin, Bailly, Jules, Caput, Javier, Castillo, Alma Chapet Batlle, Floriane, Cherrier, Claudia Demarta Gatsi, Deshmukh, Gopaul, Muriel, Gugger, Caroline, Lambert, Lucas, Krauss, Amelie, Vandendaele, Xiaojing, Li, Lin, Xiaomei, Luo Xunxun, Anders C. h. r. Hansen, Tina, Kronborg, Pettersen, Jens S., Charles, Calvet, Tyler Dae Devlin, Kosuke, Fujishima, Danny, Greenberg, Tina, Ju, Ryan, Kent, Daniel, Kunin, Erica, Lieberman, Griffin, Mccutcheon, Thai, Nguyen, Lynn, Rothschild, Shih, Joseph D., Jack, Takahashi, Kirsten, Thompson, Forrest, Tran, Daniel, Xiang, Felix, Richter, Yang, Xiaoran, Xiangyue, Hu, Changyuan, Deng, Shuyu, Hua, Yumeng, Li, Xinyu, Meng, Boxiang, Wang, Yingqi, Wang, Xuan, Wang, Zixuan, Xu, Jieyu, Yan, Ming, Yan, Yineng, Zhou, Edgar Alberto Alcalá Orozco, José Alberto Cristerna Bermúdez, Daniela Flores Gómez, José Ernesto Hernández Castañeda, Diana Clarisse Montaño Navarro, Juana Yessica PérezÁvila, María Fernanda Salazar Figueroa, María Fernanda Sánchez Arroyo, Oliva Angélica Sánchez Montesinos, Ángel Farid Rojas Cruz, Carlos Ramos Gutiérrez, Alonso Pérez Lona, Carlos Alejandro Meza Ramírez, Fernanda Sotomayor Olivares, Jorge Sebastián Rodríguez Iniesta, Juan Carlos Rueda Silva, Shotaro, Ayukawa, Takahiro, Kashiwagi, Daisuke, Kiga, Misa, Minegishi, Riku, Shinohara, Hiraku, Tokuma, Yuta, Yamazaki, Shuhei, Yasunishi, Erinn Sim Zixuan, Remsha, Afzal, Matthew, Carrigan, Barry, Moran, Marlena, Mucha, Arnas, Petrauskas, Stefan, Marsden, Michelle, Post, Anne, Rodenburg, Hector, Sanguesa, Marit van der Does, Erwin van Rijn, Max van’t Hof, Yeshi de Bruin, Hans de Ferrante, Elles, Elschot, Laura, Jacobs, Jan Willem Muller, Sjoerd, Nooijens, Femke, Vaassen, Cas van der Putten, Esther van Leeuwen, Laura van Smeden, Kwan Kwan Zhu, Kevin, Sabath, Katharina, Sporbeck, Nicolai von Kügelgen, Lisa, Wellinger, Stefanie, Braun, Jack, Ho, Yash, Mishra, Mariola, Sebastian, Lucas von Chamier, Ahsan, Fasih M., Satyadi, Megan A., Vivienne, Gunadhi, Phillip, Kyriakakis, Jenny, Lee, Walter, Thavarajah, Kimia, Abtahi, Robert, Hand, Chun Mun Loke, Adam, Wahab, Iowis, Zhu, Del Bianco, Cristina, Chizzolini, Fabio, Elisa, Godino, Lentini, Roberta, Mansy, Sheref Samir, Yeh Martin, Noel, Claudio Oss Pegorar, Alexander, Cook, Timothy, Kerns, Chad, Nielsen, Michael, Paskett, Alexander, Torgesen, Stephen, Lee, Ophir, Ospovat, Sikandar, Raza, Daniel, Shaykevich, Jarrod, Shilts, Barbora, Bajorinaite, Mykolas, Bendorius, Ieva, Rauluseviciute, Ieva, Savickyte, Sarunas, Tumas, William, Buchser, Elli, Cryan, Caroline, Golino, Andrew, Halleran, Taylor, Jacobs, Michael, Lefew, Joe, Maniaci, John, Marken, Margaret, Saha, Panya, Vij, Kayla, Desanty, Julie, Mazza, Raytheon BBN Technologies, iGEM Foundation, Synthace, Agilent Technology [Santa Clara], Raytheon BBN Technologies, Synthace, and Agilent provided support in the form of salaries for authors JB, MG, and JH, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the author contributions section, The authors wish to thank Sarah Munro and Marc Salit of NIST for help in designing this study. Consortium authors include all persons self-identified by contributing teams as deserving co-authorship credit. Contributors are listed alphabetically within team, and teams alphabetically and by year. Note that some persons may be credited as contributing in both years. Team names are given as identified in iGEM records: full details of each team’s institution and additional members may be found online in the iGEM Foundation archives at:http://year.igem.org/Team:name e.g.: full information on the 2015 ETH_Zurich team may be found at: http://2015.igem.org/Team:ETH_Zurich, BBN Technologies, IGEM Foundation, Synthace Ltd., Agilent Technologies, Department of Biotechnology and Chemical Technology, Helsinki Institute for Information Technology HIIT, ATOMS Turkiye, Boston University, Carnegie Mellon University, Technical University of Denmark, Ludwig Maximilian University of Munich, Middle East Technical University, Sumbawa University of Technology, Southern University of Science and Technology, Sun Yat-Sen University, Tecnológico de Monterrey, Universidad Autonoma de Nuevo Leon, University of Ottawa, Universitat Politècnica de València, Wageningen University and Research Centre, Worcester Polytechnic Institute, Xiamen University, University of Texas at Austin, Bielefeld University, Birkbeck University of London, USP-Brazil, City University of Hong Kong, Colorado State University, CU Boulder, Swiss Federal Institute of Technology Lausanne, Swiss Federal Institute of Technology Zurich, University of Exeter, Indian Institute of Science Education and Research, KU Leuven, Massachusetts Institute of Technology, Northeast Agricultural University, Nanjing Agricultural University, Norwegian University of Science and Technology, Ocean University of China, University of Southern Denmark, Shenzhen Middle School - SZMS 15, Tokyo Institute of Technology, Trinity College Dublin, Delft University of Technology, Eindhoven University of Technology, Tuebingen, University of California Los Angeles, University of California San Diego, University of Maryland, University of Trento, Vanderbilt University, College of William and Mary, Department of Bioproducts and Biosystems, Aalto-yliopisto, Aalto University, Jones, D Dafydd, Discrete Technology and Production Automation, and ​Robotics and image-guided minimally-invasive surgery (ROBOTICS)

Subjects
0106 biological sciences, 0301 basic medicine, green fluorescent protein, Laboratory Proficiency Testing, Transcription, Genetic, International Genetically Engineered Machine, [SDV]Life Sciences [q-bio], lcsh:Medicine, Protein Engineering, 01 natural sciences, Infographics, Synthetic biology, genetics, lcsh:Science, Promoter Regions, Genetic, Macromolecular Engineering, transcription initiation, Measurement, Multidisciplinary, Chemistry, Strain (biology), gene expression regulation, good laboratory practice, Research Assessment, Fluorescence, Reproducibility, 3. Good health, Bioassays and Physiological Analysis, Engineering and Technology, Educational Status, Synthetic Biology, Genetic Engineering, Transcription, Graphs, Research Article, Biotechnology, Transcriptional Activation, Computer and Information Sciences, General Science & Technology, Green Fluorescent Proteins, Bioengineering, Computational biology, iGEM Interlab Study Contributors, Research and Analysis Methods, Promoter Regions, 03 medical and health sciences, promoter region, Genetic, 010608 biotechnology, Escherichia coli, ta215, business.industry, Data Visualization, lcsh:R, Fluorescence Competition, genetic transcription, DNA structure, Reproducibility of Results, Biology and Life Sciences, protein engineering, 030104 developmental biology, Good Health and Well Being, 7 INGENIERÍA Y TECNOLOGÍA, Synthetic Bioengineering, People and Places, lcsh:Q, Population Groupings, biosynthesis, business, metabolism, Undergraduates
Abstract

We present results of the first large-scale interlaboratory study carried out in synthetic biology, as part of the 2014 and 2015 International Genetically Engineered Machine (iGEM) competitions. Participants at 88 institutions around the world measured fluorescence from three engineered constitutive constructs in E. coli. Few participants were able to measure absolute fluorescence, so data was analyzed in terms of ratios. Precision was strongly related to fluorescent strength, ranging from 1.54-fold standard deviation for the ratio between strong promoters to 5.75-fold for the ratio between the strongest and weakest promoter, and while host strain did not affect expression ratios, choice of instrument did. This result shows that high quantitative precision and reproducibility of results is possible, while at the same time indicating areas needing improved laboratory practices. Copyright: © 2016 Beal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Published
2016

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