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1. Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms

Author

Maura Costello, Mark Fleharty, Justin Abreu, Yossi Farjoun, Steven Ferriera, Laurie Holmes, Brian Granger, Lisa Green, Tom Howd, Tamara Mason, Gina Vicente, Michael Dasilva, Wendy Brodeur, Timothy DeSmet, Sheila Dodge, Niall J. Lennon, and Stacey Gabriel

Subjects
Next generation sequencing, Massively parallel sequencing, ILLUMINA sequencing, Index swapping, Index hopping, Multiplexing, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background Here we present an in-depth characterization of the mechanism of sequencer-induced sample contamination due to the phenomenon of index swapping that impacts Illumina sequencers employing patterned flow cells with Exclusion Amplification (ExAmp) chemistry (HiSeqX, HiSeq4000, and NovaSeq). We also present a remediation method that minimizes the impact of such swaps. Results Leveraging data collected over a two-year period, we demonstrate the widespread prevalence of index swapping in patterned flow cell data. We calculate mean swap rates across multiple sample preparation methods and sequencer models, demonstrating that different library methods can have vastly different swapping rates and that even non-ExAmp chemistry instruments display trace levels of index swapping. We provide methods for eliminating sample data cross contamination by utilizing non-redundant dual indexing for complete filtering of index swapped reads, and share the sequences for 96 non-combinatorial dual indexes we have validated across various library preparation methods and sequencer models. Finally, using computational methods we provide a greater insight into the mechanism of index swapping. Conclusions Index swapping in pooled libraries is a prevalent phenomenon that we observe at a rate of 0.2 to 6% in all sequencing runs on HiSeqX, HiSeq 4000/3000, and NovaSeq. Utilizing non-redundant dual indexing allows for the removal (flagging/filtering) of these swapped reads and eliminates swapping induced sample contamination, which is critical for sensitive applications such as RNA-seq, single cell, blood biopsy using circulating tumor DNA, or clinical sequencing.

Published
2018
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2. Neptune: an environment for the delivery of genomic medicine

Author

Venner Eric, Victoria Yi, David Murdock, Sara E. Kalla, Tsung-Jung Wu, Aniko Sabo, Shoudong Li, Qingchang Meng, Xia Tian, Mullai Murugan, Michelle Cohen, Christie Kovar, Wei-Qi Wei, Wendy K. Chung, Chunhua Weng, Georgia L. Wiesner, Gail P. Jarvik, Donna Muzny, Richard A. Gibbs, Debra Abrams, Samuel E. Adunyah, Ladia Albertson-Junkans, Berta Almoguera, Darren C. Ames, Paul Appelbaum, Samuel Aronson, Sharon Aufox, Lawrence J. Babb, Adithya Balasubramanian, Hana Bangash, Melissa Basford, Lisa Bastarache, Samantha Baxter, Meckenzie Behr, Barbara Benoit, Elizabeth Bhoj, Suzette J. Bielinski, Sarah T. Bland, Carrie Blout, Kenneth Borthwick, Erwin P. Bottinger, Mark Bowser, Harrison Brand, Murray Brilliant, Wendy Brodeur, Pedro Caraballo, David Carrell, Andrew Carroll, Lisa Castillo, Victor Castro, Gauthami Chandanavelli, Theodore Chiang, Rex L. Chisholm, Kurt D. Christensen, Wendy Chung, Christopher G. Chute, Brittany City, Beth L. Cobb, John J. Connolly, Paul Crane, Katherine Crew, David R. Crosslin, Jyoti Dayal, Mariza De Andrade, Jessica De la Cruz, Josh C. Denny, Shawn Denson, Tim DeSmet, Ozan Dikilitas, Michael J. Dinsmore, Sheila Dodge, Phil Dunlea, Todd L. Edwards, Christine M. Eng, David Fasel, Alex Fedotov, Qiping Feng, Mark Fleharty, Andrea Foster, Robert Freimuth, Christopher Friedrich, Stephanie M. Fullerton, Birgit Funke, Stacey Gabriel, Vivian Gainer, Ali Gharavi, Andrew M. Glazer, Joseph T. Glessner, Jessica Goehringer, Adam S. Gordon, Chet Graham, Robert C. Green, Justin H. Gundelach, Heather S. Hain, Hakon Hakonarson, Maegan V. Harden, John Harley, Margaret Harr, Andrea Hartzler, M. Geoffrey Hayes, Scott Hebbring, Nora Henrikson, Andrew Hershey, Christin Hoell, Ingrid Holm, Kayla M. Howell, George Hripcsak, Jianhong Hu, Elizabeth Duffy Hynes, Joy C. Jayaseelan, Yunyun Jiang, Yoonjung Yoonie Joo, Sheethal Jose, Navya Shilpa Josyula, Anne E. Justice, Divya Kalra, Elizabeth W. Karlson, Brendan J. Keating, Melissa A. Kelly, Eimear E. Kenny, Dustin Key, Krzysztof Kiryluk, Terrie Kitchner, Barbara Klanderman, Eric Klee, David C. Kochan, Viktoriya Korchina, Leah Kottyan, Emily Kudalkar, Alanna Kulchak Rahm, Iftikhar J. Kullo, Philip Lammers, Eric B. Larson, Matthew S. Lebo, Magalie Leduc, Ming Ta (Michael) Lee, Niall J. Lennon, Kathleen A. Leppig, Nancy D. Leslie, Rongling Li, Wayne H. Liang, Chiao-Feng Lin, Jodell E. Linder, Noralane M. Lindor, Todd Lingren, James G. Linneman, Cong Liu, Wen Liu, Xiuping Liu, John Lynch, Hayley Lyon, Alyssa Macbeth, Harshad Mahadeshwar, Lisa Mahanta, Bradley Malin, Teri Manolio, Maddalena Marasa, Keith Marsolo, Michelle L. McGowan, Elizabeth McNally, Jim Meldrim, Frank Mentch, Hila Milo Rasouly, Jonathan Mosley, Shubhabrata Mukherjee, Thomas E. Mullen, Jesse Muniz, David R. Murdock, Shawn Murphy, Melanie F. Myers, Bahram Namjou, Yizhao Ni, Robert C. Onofrio, Aniwaa Owusu Obeng, Thomas N. Person, Josh F. Peterson, Lynn Petukhova, Cassandra J. Pisieczko, Siddharth Pratap, Cynthia A. Prows, Megan J. Puckelwartz, Ritika Raj, James D. Ralston, Arvind Ramaprasan, Andrea Ramirez, Luke Rasmussen, Laura Rasmussen-Torvik, Soumya Raychaudhuri, Heidi L. Rehm, Marylyn D. Ritchie, Catherine Rives, Beenish Riza, Dan M. Roden, Elisabeth A. Rosenthal, Avni Santani, Schaid Dan, Steven Scherer, Stuart Scott, Aaron Scrol, Soumitra Sengupta, Ning Shang, Himanshu Sharma, Richard R. Sharp, Rajbir Singh, Patrick M.A. Sleiman, Kara Slowik, Joshua C. Smith, Maureen E. Smith, Duane T. Smoot, Jordan W. Smoller, Sunghwan Sohn, Ian B. Stanaway, Justin Starren, Mary Stroud, Jessica Su, Casey Overby Taylor, Kasia Tolwinski, Sara L. Van Driest, Sean M. Vargas, Matthew Varugheese, David Veenstra, Eric Venner, Miguel Verbitsky, Gina Vicente, Michael Wagner, Kimberly Walker, Theresa Walunas, Liwen Wang, Qiaoyan Wang, Scott T. Weiss, Quinn S. Wells, Peter S. White, Ken L. Wiley, Janet L. Williams, Marc S. Williams, Michael W. Wilson, Leora Witkowski, Laura Allison Woods, Betty Woolf, Julia Wynn, Yaping Yang, Ge Zhang, Lan Zhang, and Hana Zouk

Subjects
Computer science, business.industry, Process (engineering), MEDLINE, High-Throughput Nucleotide Sequencing, Genomics, Data science, Article, Personalization, Variety (cybernetics), Workflow, Neptune, Pharmacogenomics, Health care, Electronic Health Records, Humans, business, Software, Genetics (clinical)
Abstract

Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .

Published
2021
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3. Evidence of transmission from fully vaccinated individuals in a large outbreak of the SARS-CoV-2 Delta variant in Provincetown, Massachusetts

Author

Pardis C. Sabeti, Erika Buzby, Stacey Gabriel, Hanna Shephard, Clare Bernard, Petra L. Schubert, Deirdre Arvidson, Anthony A. Philippakis, Stephanie Baez, Christopher Tomkins-Tinch, Faye L. Reagan, Corey M. Nolet, Matthew Defelice, Catherine M. Brown, Kyle Vernest, Lydia A. Krasilnikova, Gabrielle Gionet, Seana Cofsky, John Beauchamp, Nicholas A. Fitzgerald, Maurice Melchiono, Timelia Fink, Taylor Brock-Fisher, Niall J. Lennon, Jessica Brown, Andrew S. Lang, Bradford P. Taylor, Katelyn S. Messer, Nikolaos Barkas, Sushma Chaluvadi, Selina Clancy, William P. Hanage, Katherine C. DeRuff, Vaira Harik, Bryn Loftness, Gordon Adams, Glen R. Gallagher, Christine Loreth, Brendan Blumenstiel, Lisa M. Anderson, Hillary Johnson, Zoe M. Mandese, Gage K. Moreno, Sabrina T. Dobbins, James Meldrim, Amanda Kearns, Heather M. Rooke, Scott Hennigan, Jacob E. Lemieux, Bronwyn MacInnis, Marissa E. Fisher, Rachel Harrington, Joshua Hall, Maesha A. Ulcena, Sandra Smole, Gina Vicente, Matthew D. Lee, Natasha L. Smith, Sean E. English, Stephen F. Schaffner, Luc Gagne, Michelle Cipicchio, Matthew Doucette, Scott Anderson, Daniel J. Park, Stephanie Ash, Ivan Specht, Lawrence C. Madoff, Steven K. Reilly, Theresa Covell, Katie Larkin, Marianne C. Ray, Sarah D. Slack, Megan E. Vodzak, Jillian Silbert, Johanna Vostok, Beau Schaeffer, Jonna Grimsby, Molly Dunn, and Katherine J. Siddle

Subjects
Delta, Adult, Male, medicine.medical_specialty, Adolescent, Population, Genome, Viral, Disease cluster, Article, law.invention, Disease Outbreaks, Young Adult, law, Epidemiology, medicine, Humans, education, Child, Phylogeny, Aged, Aged, 80 and over, education.field_of_study, Molecular Epidemiology, Whole Genome Sequencing, SARS-CoV-2, Public health, Vaccination, Infant, Newborn, Outbreak, COVID-19, Infant, Middle Aged, Geography, Transmission (mechanics), Massachusetts, Child, Preschool, Female, Contact Tracing, Demography
Abstract

Multiple summer events, including large indoor gatherings, in Provincetown, Massachusetts (MA), in July 2021 contributed to an outbreak of over one thousand COVID-19 cases among residents and visitors. Most cases were fully vaccinated, many of whom were also symptomatic, prompting a comprehensive public health response, motivating changes to national masking recommendations, and raising questions about infection and transmission among vaccinated individuals. To characterize the outbreak and the viral population underlying it, we combined genomic and epidemiological data from 467 individuals, including 40% of known outbreak-associated cases. The Delta variant accounted for 99% of sequenced outbreak-associated cases. Phylogenetic analysis suggests over 40 sources of Delta in the dataset, with one responsible for a single cluster containing 83% of outbreak-associated genomes. This cluster was likely not the result of extensive spread at a single site, but rather transmission from a common source across multiple settings over a short time. Genomic and epidemiological data combined provide strong support for 25 transmission events from, including many between, fully vaccinated individuals; genomic data alone provides evidence for an additional 64. Together, genomic epidemiology provides a high-resolution picture of the Provincetown outbreak, revealing multiple cases of transmission of Delta from fully vaccinated individuals. However, despite its magnitude, the outbreak was restricted in its onward impact in MA and the US, likely due to high vaccination rates and a robust public health response.

Published
2021

4. Comparative transmissibility of SARS-CoV-2 variants Delta and Alpha in New England, USA

Author

Rebecca Earnest, Rockib Uddin, Nicholas Matluk, Nicholas Renzette, Sarah E. Turbett, Katherine J. Siddle, Christine Loreth, Gordon Adams, Christopher H. Tomkins-Tinch, Mary E. Petrone, Jessica E. Rothman, Mallery I. Breban, Robert Tobias Koch, Kendall Billig, Joseph R. Fauver, Chantal B.F. Vogels, Kaya Bilguvar, Bony De Kumar, Marie L. Landry, David R. Peaper, Kevin Kelly, Greg Omerza, Heather Grieser, Sim Meak, John Martha, Hannah B. Dewey, Susan Kales, Daniel Berenzy, Kristin Carpenter-Azevedo, Ewa King, Richard C. Huard, Vlad Novitsky, Mark Howison, Josephine Darpolor, Akarsh Manne, Rami Kantor, Sandra C. Smole, Catherine M. Brown, Timelia Fink, Andrew S. Lang, Glen R. Gallagher, Virginia E. Pitzer, Pardis C. Sabeti, Stacey Gabriel, Bronwyn L. MacInnis, Ryan Tewhey, Mark D. Adams, Daniel J. Park, Jacob E. Lemieux, Nathan D. Grubaugh, Ahmad Altajar, Alexandra DeJesus, Anderson Brito, Anne E. Watkins, Anthony Muyombwe, Brendan S. Blumenstiel, Caleb Neal, Chaney C. Kalinich, Chen Liu, Christopher Castaldi, Claire Pearson, Clare Bernard, Corey M. Nolet, David Ferguson, Erika Buzby, Eva Laszlo, Faye L. Reagan, Gina Vicente, Heather M. Rooke, Heidi Munger, Hillary Johnson, Irina R. Tikhonova, Isabel M. Ott, Jafar Razeq, James C. Meldrim, Jessica Brown, Jianhui Wang, Johanna Vostok, John P. Beauchamp, Jonna L. Grimsby, Joshua Hall, Katelyn S. Messer, Katie L. Larkin, Kyle Vernest, Lawrence C. Madoff, Lisa M. Green, Lori Webber, Luc Gagne, Maesha A. Ulcena, Marianne C. Ray, Marissa E. Fisher, Mary Barter, Matthew D. Lee, Matthew T. DeFelice, Michelle C. Cipicchio, Natasha L. Smith, Niall J. Lennon, Nicholas A. Fitzgerald, Nicholas Kerantzas, Pei Hui, Rachel Harrington, Randy Downing, Rashida Haye, Ryan Lynch, Scott E. Anderson, Scott Hennigan, Sean English, Seana Cofsky, Selina Clancy, Shrikant Mane, Stephanie Ash, Stephanie Baez, Steve Fleming, Steven Murphy, Sushma Chaluvadi, Tara Alpert, Trevor Rivard, Wade Schulz, Zoe M. Mandese, and Acibadem University Dspace

Subjects
Delta, 2019-20 coronavirus outbreak, Coronavirus disease 2019 (COVID-19), SARS-CoV-2, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Alpha (ethology), COVID-19, Biology, Transmissibility (vibration), General Biochemistry, Genetics and Molecular Biology, Article, New england, New England, Humans, Viral rna, Public Health, Demography
Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant quickly rose to dominance in mid-2021, displacing other variants, including Alpha. Studies using data from the United Kingdom and India estimated that Delta was 40-80% more transmissible than Alpha, allowing Delta to become the globally dominant variant. However, it was unclear if the ostensible difference in relative transmissibility was due mostly to innate properties of Delta’s infectiousness or differences in the study populations. To investigate, we formed a partnership with SARS-CoV-2 genomic surveillance programs from all six New England US states. By comparing logistic growth rates, we found that Delta emerged 37-163% faster than Alpha in early 2021 (37% Massachusetts, 75% New Hampshire, 95% Maine, 98% Rhode Island, 151% Connecticut, and 163% Vermont). We next computed variant-specific effective reproductive numbers and estimated that Delta was 58-120% more transmissible than Alpha across New England (58% New Hampshire, 68% Massachusetts, 76% Connecticut, 85% Rhode Island, 98% Maine, and 120% Vermont). Finally, using RT-PCR data, we estimated that Delta infections generate on average ∼6 times more viral RNA copies per mL than Alpha infections. Overall, our evidence indicates that Delta’s enhanced transmissibility could be attributed to its innate ability to increase infectiousness, but its epidemiological dynamics may vary depending on the underlying immunity and behavior of distinct populations.

Published
2021

5. Harmonizing Clinical Sequencing and Interpretation for the eMERGE III Network

Author

Ian B. Stanaway, Dan M. Roden, Divya Kalra, Dustin Key, Debra J. Abrams, David Fasel, Victor Castro, Brad Malin, Berta Almoguera, Beenish Riza, Meckenzie A. Behr, Eric Venner, Christine M. Eng, Joy Jayaseelan, Scott J. Hebbring, Michelle L. McGowan, Steven E. Scherer, Theresa L. Walunas, Mark Bowser, James D. Ralston, Wei-Qi Wei, Liwen Wang, David R. Murdock, Wayne H. Liang, Julia Wynn, Nancy D. Leslie, Laura J. Rasmussen-Torvik, Ming Ta (Michael) Lee, Frank D. Mentch, Lan Zhang, Alanna Kulchak Rahm, Josh F. Peterson, Jodell E. Linder, Joshua C. Smith, Soumitra Sengupta, Brendan J. Keating, Gina Vicente, Andrew Carroll, Nora B. Henrikson, Anne E. Justice, Heather S. Hain, Wen Liu, Andrea H. Ramirez, Matthew S. Lebo, Hana Zouk, Georgia L. Wiesner, Andrea L. Hartzler, Cassandra J. Pisieczko, Catherine M. Rives, Jessica Goehringer, Maegan V. Harden, John Lynch, Chiao-Feng Lin, Peter White, Phil Dunlea, Shawn N. Murphy, Mullai Murugan, Harshad Mahadeshwar, Mark Fleharty, Andrea Foster, Arvind Ramaprasan, Christopher A. Friedrich, Justin H. Gundelach, Hayley Lyon, Niall J. Lennon, Eric W. Klee, David R. Crosslin, Ge Zhang, Rongling Li, Ozan Dikilitas, Xiuping Liu, Christin Hoell, Aniwaa Owusu Obeng, Katherine D. Crew, Lisa M. Castillo, Justin Starren, Jonathan D. Mosley, Carrie L. Blout, Himanshu Sharma, Elizabeth M. McNally, Sarah T. Bland, Megan J. Puckelwartz, Matthew Varugheese, Keith Marsolo, Betty Woolf, Sharon Aufox, Janet L. Williams, Kimberly Walker, Murray H. Brilliant, Birgit Funke, Laura Allison Woods, Marylyn D. Ritchie, Brittany City, Todd Lingren, Hila Milo Rasouly, Lawrence J. Babb, Alex Fedotov, Robert C. Onofrio, Margaret Harr, Suzette J. Bielinski, Michael W. Wilson, Shubhabrata Mukherjee, Robert R. Freimuth, Chet Graham, Todd L. Edwards, Quinn S. Wells, Marc S. Williams, Jordan W. Smoller, Wendy K. Chung, Avni Santani, Paul K. Crane, George Hripcsak, QiPing Feng, Ali G. Gharavi, Yizhao Ni, Iftikhar J. Kullo, Michael Wagner, Philip E. Lammers, Michael J. Dinsmore, Thomas N. Person, Victoria Yi, Samuel E. Adunyah, Tim DeSmet, Eric B. Larson, Elizabeth Hynes, David C. Kochan, Eimear E. Kenny, Magalie S. Leduc, Lisa Mahanta, David Carrell, Paul S. Appelbaum, Viktoriya Korchina, Beth L. Cobb, Lynn Petukhova, Jessica De la Cruz, Patrick M. A. Sleiman, Stuart A. Scott, Tsung-Jung Wu, Gail P. Jarvik, Erwin P. Bottinger, Ken Wiley, Josh C. Denny, Melissa A. Basford, Samuel J. Aronson, David L. Veenstra, Yaping Yang, Kayla Marie Howell, John J. Connolly, Jessica Su, Yoonjung Yoonie Joo, Miguel Verbitsky, Sean M. Vargas, Cong Liu, Barbara Benoit, Andrew Hershey, Richard A. Gibbs, Cynthia A. Prows, Hana Bangash, Wendy Brodeur, Gauthami Chandanavelli, Sara L. Van Driest, Kurt D. Christensen, Elizabeth J. Bhoj, Vivian S. Gainer, Adam S. Gordon, Robert C. Green, Hakon Hakonarson, Krzysztof Kiryluk, Elisabeth A. Rosenthal, Rajbir Singh, James G. Linneman, Harrison Brand, Theodore Chiang, Sheila Dodge, Ingrid A. Holm, M. Geoffrey Hayes, Yunyun Jiang, Ning Shang, Samantha Baxter, Noralane M. Lindor, Kathleen A. Leppig, Teri A. Manolio, Sara E. Kalla, Pedro J. Caraballo, Ritika Raj, Aaron Scrol, Jyoti G. Dayal, Richard R. Sharp, Christie Kovar, Soumya Raychaudhuri, Sunghwan Sohn, Emily Kudalkar, Maddalena Marasa, Stacey Gabriel, Dan Schaid, Ladia Albertson-Junkans, Rex L. Chisholm, Maureen E. Smith, Donna M. Muzny, Casey Overby Taylor, Jianhong Hu, Elizabeth W. Karlson, Lisa Bastarache, Darren C. Ames, Joseph T. Glessner, Leora Witkowski, Siddharth Pratap, Qiaoyan Wang, Melissa A. Kelly, Adithya Balasubramanian, Kara Slowik, Terrie Kitchner, Barbara J. Klanderman, Shawn Denson, Mary Stroud, Alyssa Macbeth, Melanie F. Myers, Jesse Muniz, Kasia Tolwinski, Scott T. Weiss, Chunhua Weng, Stephanie M. Fullerton, John B. Harley, Christopher G. Chute, Heidi L. Rehm, Sheethal Jose, Andrew M. Glazer, Navya Shilpa Josyula, Kenneth M. Borthwick, Thomas E. Mullen, Mariza de Andrade, Leah C. Kottyan, Luke V. Rasmussen, James Meldrim, and Bahram Namjou

Subjects
0301 basic medicine, Standardization, Test data generation, business.industry, Computer science, Sequence Analysis, DNA, 030105 genetics & heredity, Precision medicine, Data science, Clinical decision support system, Biobank, Article, 3. Good health, Data sharing, 03 medical and health sciences, 030104 developmental biology, Genetics, Humans, Genetic Testing, Prospective Studies, Sample collection, Personalized medicine, Precision Medicine, business, Genetics (clinical)
Abstract

The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.

Published
2019
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6. Transmission from vaccinated individuals in a large SARS-CoV-2 Delta variant outbreak

Author

Katherine J. Siddle, Lydia A. Krasilnikova, Gage K. Moreno, Stephen F. Schaffner, Johanna Vostok, Nicholas A. Fitzgerald, Jacob E. Lemieux, Nikolaos Barkas, Christine Loreth, Ivan Specht, Christopher H. Tomkins-Tinch, Jillian S. Paull, Beau Schaeffer, Bradford P. Taylor, Bryn Loftness, Hillary Johnson, Petra L. Schubert, Hanna M. Shephard, Matthew Doucette, Timelia Fink, Andrew S. Lang, Stephanie Baez, John Beauchamp, Scott Hennigan, Erika Buzby, Stephanie Ash, Jessica Brown, Selina Clancy, Seana Cofsky, Luc Gagne, Joshua Hall, Rachel Harrington, Gabrielle L. Gionet, Katherine C. DeRuff, Megan E. Vodzak, Gordon C. Adams, Sabrina T. Dobbins, Sarah D. Slack, Steven K. Reilly, Lisa M. Anderson, Michelle C. Cipicchio, Matthew T. DeFelice, Jonna L. Grimsby, Scott E. Anderson, Brendan S. Blumenstiel, James C. Meldrim, Heather M. Rooke, Gina Vicente, Natasha L. Smith, Katelyn S. Messer, Faye L. Reagan, Zoe M. Mandese, Matthew D. Lee, Marianne C. Ray, Marissa E. Fisher, Maesha A. Ulcena, Corey M. Nolet, Sean E. English, Katie L. Larkin, Kyle Vernest, Sushma Chaluvadi, Deirdre Arvidson, Maurice Melchiono, Theresa Covell, Vaira Harik, Taylor Brock-Fisher, Molly Dunn, Amanda Kearns, William P. Hanage, Clare Bernard, Anthony Philippakis, Niall J. Lennon, Stacey B. Gabriel, Glen R. Gallagher, Sandra Smole, Lawrence C. Madoff, Catherine M. Brown, Daniel J. Park, Bronwyn L. MacInnis, and Pardis C. Sabeti

Subjects
Article, General Biochemistry, Genetics and Molecular Biology
Abstract

An outbreak of over one thousand COVID-19 cases in Provincetown, Massachusetts, in July 2021—the first large outbreak mostly in vaccinated individuals in the US—prompted a comprehensive public health response, motivating changes to national masking recommendations and raising questions about infection and transmission among vaccinated individuals. To address these questions, we combined genomic and epidemiological data from 467 individuals, including 40% of known outbreak-associated cases. The Delta variant accounted for 99% of outbreak-associated cases in this dataset; it was introduced from at least 40 sources, but 83% of cases derived from a single source, likely through transmission across multiple settings over a short time rather than a single event. Genomic and epidemiological data supported multiple transmissions of Delta from and between fully vaccinated individuals. However, despite its magnitude, the outbreak had limited onward impact in MA and the US, likely due to high vaccination rates and a robust public health response., Rapid integration of epidemiological and genomic data helped to support public health measures during a recent large outbreak of the SARS-CoV-2 Delta variant. This outbreak stemmed primarily from a single source that spread the virus at multiple locations and frequent transmission between vaccinated individuals was observed and contained with robust intervention and community engagement.

Published
2022
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7. Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms

Author

Brian E. Granger, Steven Ferriera, Stacey Gabriel, Mark Fleharty, Sheila Dodge, Tom Howd, Justin Abreu, Yossi Farjoun, Wendy Brodeur, Lisa Green, Tamara Mason, Niall J. Lennon, Timothy DeSmet, Laurie Holmes, Michael Dasilva, Maura Costello, and Gina Vicente

Subjects
0301 basic medicine, animal structures, Massively parallel sequencing, lcsh:QH426-470, Computer science, lcsh:Biotechnology, Parallel computing, environment and public health, Multiplexing, DNA sequencing, 03 medical and health sciences, Next generation sequencing, lcsh:TP248.13-248.65, Genetics, Humans, Illumina dye sequencing, Gene Library, Exclusion amplification, Massive parallel sequencing, Genome, Human, Flagging, fungi, Search engine indexing, High-Throughput Nucleotide Sequencing, Indexes, DNA, Sequence Analysis, DNA, Sample (graphics), Index hopping, Index, lcsh:Genetics, 030104 developmental biology, Index (publishing), Index swapping, Barcodes, ILLUMINA sequencing, Sequence Analysis, Research Article, Biotechnology
Abstract

Background Here we present an in-depth characterization of the mechanism of sequencer-induced sample contamination due to the phenomenon of index swapping that impacts Illumina sequencers employing patterned flow cells with Exclusion Amplification (ExAmp) chemistry (HiSeqX, HiSeq4000, and NovaSeq). We also present a remediation method that minimizes the impact of such swaps. Results Leveraging data collected over a two-year period, we demonstrate the widespread prevalence of index swapping in patterned flow cell data. We calculate mean swap rates across multiple sample preparation methods and sequencer models, demonstrating that different library methods can have vastly different swapping rates and that even non-ExAmp chemistry instruments display trace levels of index swapping. We provide methods for eliminating sample data cross contamination by utilizing non-redundant dual indexing for complete filtering of index swapped reads, and share the sequences for 96 non-combinatorial dual indexes we have validated across various library preparation methods and sequencer models. Finally, using computational methods we provide a greater insight into the mechanism of index swapping. Conclusions Index swapping in pooled libraries is a prevalent phenomenon that we observe at a rate of 0.2 to 6% in all sequencing runs on HiSeqX, HiSeq 4000/3000, and NovaSeq. Utilizing non-redundant dual indexing allows for the removal (flagging/filtering) of these swapped reads and eliminates swapping induced sample contamination, which is critical for sensitive applications such as RNA-seq, single cell, blood biopsy using circulating tumor DNA, or clinical sequencing. Electronic supplementary material The online version of this article (10.1186/s12864-018-4703-0) contains supplementary material, which is available to authorized users.

Published
2018
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8. Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms

Author

Tom Howd, Yossi Farjoun, Tamara Mason, Niall J. Lennon, Maura Costello, Timothy DeSmet, Michael Dasilva, Stacey Gabriel, Sheila Dodge, Gina Vicente, Wendy Brodeur, Laurie Holmes, Mark Fleharty, Justin Abreu, and Steven Ferriera

Subjects
Massive parallel sequencing, Index (publishing), Data integrity, Search engine indexing, Parallel computing, DUAL (cognitive architecture), Interest rate swap, Sample (graphics), TRACE (psycholinguistics)
Abstract

Here, we present an in-depth characterization of the index swapping mechanism on Illumina instruments that employ the ExAmp chemistry for cluster generation (HiSeqX, HiSeq4000, and NovaSeq). We discuss best practices for eliminating the effects of index swapping on data integrity by utilizing unique dual indexing for complete filtering of index swapped reads. We calculate mean swap rates across multiple sample preparation methods and sequencer models, demonstrating that different methods can have vastly different swap rates, and show that even non-ExAmp chemistry instruments display trace levels of index swapping. Finally, using computational methods we provide a greater insight into the mechanism of index swapping.

Published
2017
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