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2. A map of human genome variation from population-scale sequencing

Author

Durbin, Richard M., Altshuler, David L., Durbin, Richard M., Abecasis, Gonçalo R., Bentley, David R., Chakravarti, Aravinda, Clark, Andrew G., Collins, Francis S., De La Vega, Francisco M., Donnelly, Peter, Egholm, Michael, Flicek, Paul, Gabriel, Stacey B., Gibbs, Richard A., Knoppers, Bartha M., Lander, Eric S., Lehrach, Hans, Mardis, Elaine R., McVean, Gil A., Nickerson, Debbie A., Peltonen, Leena, Schafer, Alan J., Sherry, Stephen T., Wang, Jun, Wilson, Richard K., Gibbs, Richard A., Deiros, David, Metzker, Mike, Muzny, Donna, Reid, Jeff, Wheeler, David, Wang, Jun, Li, Jingxiang, Jian, Min, Li, Guoqing, Li, Ruiqiang, Liang, Huiqing, Tian, Geng, Wang, Bo, Wang, Jian, Wang, Wei, Yang, Huanming, Zhang, Xiuqing, Zheng, Huisong, Lander, Eric S., Altshuler, David L., Ambrogio, Lauren, Bloom, Toby, Cibulskis, Kristian, Fennell, Tim J., Gabriel, Stacey B., Jaffe, David B., Shefler, Erica, Sougnez, Carrie L., Bentley, David R., Gormley, Niall, Humphray, Sean, Kingsbury, Zoya, Koko-Gonzales, Paula, Stone, Jennifer, McKernan, Kevin J., Costa, Gina L., Ichikawa, Jeffry K., Lee, Clarence C., Sudbrak, Ralf, Lehrach, Hans, Borodina, Tatiana A., Dahl, Andreas, Davydov, Alexey N., Marquardt, Peter, Mertes, Florian, Nietfeld, Wilfiried, Rosenstiel, Philip, Schreiber, Stefan, Soldatov, Aleksey V., Timmermann, Bernd, Tolzmann, Marius, Egholm, Michael, Affourtit, Jason, Ashworth, Dana, Attiya, Said, Bachorski, Melissa, Buglione, Eli, Burke, Adam, Caprio, Amanda, Celone, Christopher, Clark, Shauna, Conners, David, Desany, Brian, Gu, Lisa, Guccione, Lorri, Kao, Kalvin, Kebbel, Andrew, Knowlton, Jennifer, Labrecque, Matthew, McDade, Louise, Mealmaker, Craig, Minderman, Melissa, Nawrocki, Anne, Niazi, Faheem, Pareja, Kristen, Ramenani, Ravi, Riches, David, Song, Wanmin, Turcotte, Cynthia, Wang, Shally, Mardis, Elaine R., Wilson, Richard K., Dooling, David, Fulton, Lucinda, Fulton, Robert, Weinstock, George, Durbin, Richard M., Burton, John, Carter, David M., Churcher, Carol, Coffey, Alison, Cox, Anthony, Palotie, Aarno, Quail, Michael, Skelly, Tom, Stalker, James, Swerdlow, Harold P., Turner, Daniel, De Witte, Anniek, Giles, Shane, Bainbridge, Matthew, Challis, Danny, Sabo, Aniko, Yu, Fuli, Yu, Jin, Fang, Xiaodong, Guo, Xiaosen, Li, Yingrui, Luo, Ruibang, Tai, Shuaishuai, Wu, Honglong, Zheng, Hancheng, Zheng, Xiaole, Zhou, Yan, Marth, Gabor T., Garrison, Erik P., Huang, Weichun, Indap, Amit, Kural, Deniz, Lee, Wan-Ping, Fung Leong, Wen, Quinlan, Aaron R., Stewart, Chip, Stromberg, Michael P., Ward, Alistair N., Wu, Jiantao, Lee, Charles, Mills, Ryan E., Shi, Xinghua, Daly, Mark J., DePristo, Mark A., Ball, Aaron D., Banks, Eric, Browning, Brian L., Garimella, Kiran V., Grossman, Sharon R., Handsaker, Robert E., Hanna, Matt, Hartl, Chris, Kernytsky, Andrew M., Korn, Joshua M., Li, Heng, Maguire, Jared R., McCarroll, Steven A., McKenna, Aaron, Nemesh, James C., Philippakis, Anthony A., Poplin, Ryan E., Price, Alkes, Rivas, Manuel A., Sabeti, Pardis C., Schaffner, Stephen F., Shlyakhter, Ilya A., Cooper, David N., Ball, Edward V., Mort, Matthew, Phillips, Andrew D., Stenson, Peter D., Sebat, Jonathan, Makarov, Vladimir, Ye, Kenny, Yoon, Seungtai C., Bustamante, Carlos D., Clark, Andrew G., Boyko, Adam, Degenhardt, Jeremiah, Gravel, Simon, Gutenkunst, Ryan N., Kaganovich, Mark, Keinan, Alon, Lacroute, Phil, Ma, Xin, Reynolds, Andy, Clarke, Laura, Flicek, Paul, Cunningham, Fiona, Herrero, Javier, Keenen, Stephen, Kulesha, Eugene, Leinonen, Rasko, McLaren, William M., Radhakrishnan, Rajesh, Smith, Richard E., Zalunin, Vadim, Zheng-Bradley, Xiangqun, Korbel, Jan O., Stütz, Adrian M., Humphray, Sean, Bauer, Markus, Cheetham, Keira R., Cox, Tony, Eberle, Michael, James, Terena, Kahn, Scott, Murray, Lisa, Ye, Kai, De La Vega, Francisco M., Fu, Yutao, Hyland, Fiona C. L., Manning, Jonathan M., McLaughlin, Stephen F., Peckham, Heather E., Sakarya, Onur, Sun, Yongming A., Tsung, Eric F., Batzer, Mark A., Konkel, Miriam K., Walker, Jerilyn A., Albrecht, Marcus W., Amstislavskiy, Vyacheslav S., Herwig, Ralf, Parkhomchuk, Dimitri V., Sherry, Stephen T., Agarwala, Richa, Khouri, Hoda M., Morgulis, Aleksandr O., Paschall, Justin E., Phan, Lon D., Rotmistrovsky, Kirill E., Sanders, Robert D., Shumway, Martin F., Xiao, Chunlin, McVean, Gil A., Auton, Adam, Iqbal, Zamin, Lunter, Gerton, Marchini, Jonathan L., Moutsianas, Loukas, Myers, Simon, Tumian, Afidalina, Desany, Brian, Knight, James, Winer, Roger, Craig, David W., Beckstrom-Sternberg, Steve M., Christoforides, Alexis, Kurdoglu, Ahmet A., Pearson, John V., Sinari, Shripad A., Tembe, Waibhav D., Haussler, David, Hinrichs, Angie S., Katzman, Sol J., Kern, Andrew, Kuhn, Robert M., Przeworski, Molly, Hernandez, Ryan D., Howie, Bryan, Kelley, Joanna L., Cord Melton, S., Abecasis, Gonçalo R., Li, Yun, Anderson, Paul, Blackwell, Tom, Chen, Wei, Cookson, William O., Ding, Jun, Min Kang, Hyun, Lathrop, Mark, Liang, Liming, Moffatt, Miriam F., Scheet, Paul, Sidore, Carlo, Snyder, Matthew, Zhan, Xiaowei, Zöllner, Sebastian, Awadalla, Philip, Casals, Ferran, Idaghdour, Youssef, Keebler, John, Stone, Eric A., Zilversmit, Martine, Jorde, Lynn, Xing, Jinchuan, Eichler, Evan E., Aksay, Gozde, Alkan, Can, Hajirasouliha, Iman, Hormozdiari, Fereydoun, Sahinalp, Cenk S., Sudmant, Peter H., Mardis, Elaine R., Chen, Ken, Chinwalla, Asif, Ding, Li, Koboldt, Daniel C., McLellan, Mike D., Wallis, John W., Wendl, Michael C., Zhang, Qunyuan, Albers, Cornelis A., Ayub, Qasim, Balasubramaniam, Senduran, Barrett, Jeffrey C., Chen, Yuan, Conrad, Donald F., Danecek, Petr, Dermitzakis, Emmanouil T., Hu, Min, Huang, Ni, Hurles, Matt E., Jin, Hanjun, Jostins, Luke, Keane, Thomas M., Quang Le, Si, Lindsay, Sarah, Long, Quan, MacArthur, Daniel G., Montgomery, Stephen B., Parts, Leopold, Tyler-Smith, Chris, Walter, Klaudia, Zhang, Yujun, Gerstein, Mark B., Snyder, Michael, Abyzov, Alexej, Balasubramanian, Suganthi, Bjornson, Robert, Du, Jiang, Grubert, Fabian, Habegger, Lukas, Haraksingh, Rajini, Jee, Justin, Khurana, Ekta, Lam, Hugo Y. K., Leng, Jing, Jasmine Mu, Xinmeng, Urban, Alexander E., Zhang, Zhengdong, Lee, Charles, McCarroll, Steven A., DePristo, Mark A., Korbel, Jan O., De La Vega, Francisco M., Blackwell, Tom, Eichler, Evan E., Kidd, Jeffrey M., Hurles, Matt E., Gibbs, Richard A., Coafra, Cristian, Dinh, Huyen, Kovar, Christie, Lee, Sandy, Nazareth, Lynne, Marth, Gabor T., Wilkinson, Jane, Flicek, Paul, Sherry, Stephen T., Abecasis, Gonçalo R., Mardis, Elaine R., Coffey, Allison, Scott, Carol, Gerstein, Mark B., Chakravarti, Aravinda, Knoppers, Bartha M., Bustamante, Carlos D., Gharani, Neda, Jorde, Lynn, Kaye, Jane S., Kent, Alastair, Li, Taosha, McGuire, Amy L., Ossorio, Pilar N., Rotimi, Charles N., Su, Yeyang, Toji, Lorraine H., Brooks, Lisa D., Felsenfeld, Adam L., McEwen, Jean E., Abdallah, Assya, Juenger, Christopher R., Clemm, Nicholas C., Duncanson, Audrey, Green, Eric D., Guyer, Mark S., and Peterson, Jane L.

Published
2010
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3. Accurate whole human genome sequencing using reversible terminator chemistry

Author

Bentley, David R., Balasubramanian, Shankar, Swerdlow, Harold P., Smith, Geoffrey P., Milton, John, Brown, Clive G., Hall, Kevin P., Evers, Dirk J., Barnes, Colin L., Bignell, Helen R., Boutell, Jonathan M., Bryant, Jason, Carter, Richard J., Cheetham, R. Keira, Cox, Anthony J., Ellis, Darren J., Flatbush, Michael R., Gormley, Niall A., Humphray, Sean J., Irving, Leslie J., Karbelashvili, Mirian S., Kirk, Scott M., Li, Heng, Liu, Xiaohai, Maisinger, Klaus S., Murray, Lisa J., Obradovic, Bojan, Ost, Tobias, Parkinson, Michael L., Pratt, Mark R., Rasolonjatovo, Isabelle M. J., Reed, Mark T., Rigatti, Roberto, Rodighiero, Chiara, Ross, Mark T., Sabot, Andrea, Sankar, Subramanian V., Scally, Aylwyn, Schroth, Gary P., Smith, Mark E., Smith, Vincent P., Spiridou, Anastassia, Torrance, Peta E., Tzonev, Svilen S., Vermaas, Eric H., Walter, Klaudia, Wu, Xiaolin, Zhang, Lu, Alam, Mohammed D., Anastasi, Carole, Aniebo, Ify C., Bailey, David M. D., Bancarz, Iain R., Banerjee, Saibal, Barbour, Selena G., Baybayan, Primo A., Benoit, Vincent A., Benson, Kevin F., Bevis, Claire, Black, Phillip J., Boodhun, Asha, Brennan, Joe S., Bridgham, John A., Brown, Rob C., Brown, Andrew A., Buermann, Dale H., Bundu, Abass A., Burrows, James C., Carter, Nigel P., Castillo, Nestor, Catenazzi, Maria Chiara E., Chang, Simon, Cooley, R. Neil, Crake, Natasha R., Dada, Olubunmi O., Diakoumakos, Konstantinos D., Dominguez-Fernandez, Belen, Earnshaw, David J., Egbujor, Ugonna C., Elmore, David W., Etchin, Sergey S, Ewan, Mark R., Fedurco, Milan, Fraser, Louise J., Fuentes Fajardo, Karin V., Furey, W. Scott, George, David, Gietzen, Kimberley J., Goddard, Colin P., Golda, George S., Granieri, Philip A., Green, David E., Gustafson, David L., Hansen, Nancy F., Harnish, Kevin, Haudenschild, Christian D., Heyer, Narinder I, Hims, Matthew M., Ho, Johnny T., Horgan, Adrian M., Hoschler, Katya, Hurwitz, Steve, Ivanov, Denis V., Johnson, Maria Q., James, Terena, Huw Jones, T. A., Kang, Gyoung-Dong, Kerelska, Tzvetana H., Kersey, Alan D., Khrebtukova, Irina, Kindwall, Alex P., Kingsbury, Zoya, Kokko-Gonzales, Paula I., Kumar, Anil, Laurent, Marc A., Lawley, Cynthia T., Lee, Sarah E., Lee, Xavier, Liao, Arnold K., Loch, Jennifer A., Lok, Mitch, Luo, Shujun, Mammen, Radhika M., Martin, John W., McCauley, Patrick G., McNitt, Paul, Mehta, Parul, Moon, Keith W., Mullens, Joe W., Newington, Taksina, Ning, Zemin, Ling Ng, Bee, Novo, Sonia M., O'Neill, Michael J., Osborne, Mark A., Osnowski, Andrew, Ostadan, Omead, Paraschos, Lambros L., Pickering, Lea, Pike, Andrew C., Pike, Alger C., Pinkard, D. Chris, Pliskin, Daniel P., Podhasky, Joe, Quijano, Victor J., Raczy, Come, Rae, Vicki H., Rawlings, Stephen R., Rodriguez, Ana Chiva, Roe, Phyllida M., Rogers, John, Rogert Bacigalupo, Maria C., Romanov, Nikolai, Romieu, Anthony, Roth, Rithy K., Rourke, Natalie J., Ruediger, Silke T., Rusman, Eli, Sanches-Kuiper, Raquel M., Schenker, Martin R., Seoane, Josefina M., Shaw, Richard J., Shiver, Mitch K., Short, Steven W., Sizto, Ning L., Sluis, Johannes P., Smith, Melanie A., Sohna Sohna, Jean Ernest, Spence, Eric J., Stevens, Kim, Sutton, Neil, Szajkowski, Lukasz, Tregidgo, Carolyn L., Turcatti, Gerardo, vandeVondele, Stephanie, Verhovsky, Yuli, Virk, Selene M., Wakelin, Suzanne, Walcott, Gregory C., Wang, Jingwen, Worsley, Graham J., Yan, Juying, Yau, Ling, Zuerlein, Mike, Rogers, Jane, Mullikin, James C., Hurles, Matthew E., McCooke, Nick J., West, John S., Oaks, Frank L., Lundberg, Peter L., Klenerman, David, Durbin, Richard, and Smith, Anthony J.

Published
2008
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4. A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers

Author

Quail Michael A, Smith Miriam, Coupland Paul, Otto Thomas D, Harris Simon R, Connor Thomas R, Bertoni Anna, Swerdlow Harold P, and Gu Yong

Subjects
Next-generation sequencing, Ion torrent, Illumina, Pacific biosciences, MiSeq, PGM, SMRT, Bias, Genome coverage, GC-rich, AT-rich, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background Next generation sequencing (NGS) technology has revolutionized genomic and genetic research. The pace of change in this area is rapid with three major new sequencing platforms having been released in 2011: Ion Torrent’s PGM, Pacific Biosciences’ RS and the Illumina MiSeq. Here we compare the results obtained with those platforms to the performance of the Illumina HiSeq, the current market leader. In order to compare these platforms, and get sufficient coverage depth to allow meaningful analysis, we have sequenced a set of 4 microbial genomes with mean GC content ranging from 19.3 to 67.7%. Together, these represent a comprehensive range of genome content. Here we report our analysis of that sequence data in terms of coverage distribution, bias, GC distribution, variant detection and accuracy. Results Sequence generated by Ion Torrent, MiSeq and Pacific Biosciences technologies displays near perfect coverage behaviour on GC-rich, neutral and moderately AT-rich genomes, but a profound bias was observed upon sequencing the extremely AT-rich genome of Plasmodium falciparum on the PGM, resulting in no coverage for approximately 30% of the genome. We analysed the ability to call variants from each platform and found that we could call slightly more variants from Ion Torrent data compared to MiSeq data, but at the expense of a higher false positive rate. Variant calling from Pacific Biosciences data was possible but higher coverage depth was required. Context specific errors were observed in both PGM and MiSeq data, but not in that from the Pacific Biosciences platform. Conclusions All three fast turnaround sequencers evaluated here were able to generate usable sequence. However there are key differences between the quality of that data and the applications it will support.

Published
2012
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5. Optimizing illumina next-generation sequencing library preparation for extremely at-biased genomes

Author

Oyola Samuel O, Otto Thomas D, Gu Yong, Maslen Gareth, Manske Magnus, Campino Susana, Turner Daniel J, MacInnis Bronwyn, Kwiatkowski Dominic P, Swerdlow Harold P, and Quail Michael A

Subjects
Next-Generation Sequencing, Illumina, Library, Plasmodium falciparum, AT-rich, Malaria, Clinical isolate, PCR, Tetramethyammonium chloride, PCR-free, Isothermal, Linear, Exponential, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background Massively parallel sequencing technology is revolutionizing approaches to genomic and genetic research. Since its advent, the scale and efficiency of Next-Generation Sequencing (NGS) has rapidly improved. In spite of this success, sequencing genomes or genomic regions with extremely biased base composition is still a great challenge to the currently available NGS platforms. The genomes of some important pathogenic organisms like Plasmodium falciparum (high AT content) and Mycobacterium tuberculosis (high GC content) display extremes of base composition. The standard library preparation procedures that employ PCR amplification have been shown to cause uneven read coverage particularly across AT and GC rich regions, leading to problems in genome assembly and variation analyses. Alternative library-preparation approaches that omit PCR amplification require large quantities of starting material and hence are not suitable for small amounts of DNA/RNA such as those from clinical isolates. We have developed and optimized library-preparation procedures suitable for low quantity starting material and tolerant to extremely high AT content sequences. Results We have used our optimized conditions in parallel with standard methods to prepare Illumina sequencing libraries from a non-clinical and a clinical isolate (containing ~53% host contamination). By analyzing and comparing the quality of sequence data generated, we show that our optimized conditions that involve a PCR additive (TMAC), produces amplified libraries with improved coverage of extremely AT-rich regions and reduced bias toward GC neutral templates. Conclusion We have developed a robust and optimized Next-Generation Sequencing library amplification method suitable for extremely AT-rich genomes. The new amplification conditions significantly reduce bias and retain the complexity of either extremes of base composition. This development will greatly benefit sequencing clinical samples that often require amplification due to low mass of DNA starting material.

Published
2012
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6. G&T-seq: parallel sequencing of single-cell genomes and transcriptomes

Author

Macaulay, Iain C., Haerty, Wilfried, Kumar, Parveen, Li, Yang I., Hu, Tim Xiaoming, Teng, Mabel J., Goolam, Mubeen, Saurat, Nathalie, Coupland, Paul, Shirley, Lesley M., Smith, Miriam, Van der Aa, Niels, Banerjee, Ruby, Ellis, Peter D., Quail, Michael A., Swerdlow, Harold P., Zernicka-Goetz, Magdalena, Livesey, Frederick J., Ponting, Chris P., and Voet, Thierry

Abstract

The ability to simultaneously sequence the genome and transcriptome of the same single cell offers a powerful means to dissect functional genetic heterogeneity at the cellular level. Here we describe G&T-seq, a method for separating and sequencing genomic DNA and full-length mRNA from single cells. By applying G&T-seq to over 220 single cells we reveal cellular properties that cannot be inferred from DNA or RNA sequencing alone, including associations between DNA copy number variation and gene expression dosage. We further demonstrate the detection of coding interchromosomal fusions and single nucleotide variants in both the genomes and transcriptomes of individual cells. G&T-seq enables the study of genotype-phenotype associations in single cells, and the investigation of DNA cell lineage trees of healthy and diseased tissues with transcriptome inferred cell types and states.

Published
2015

7. Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low-cost microfluidic instrumentation.

Author

Stephenson, William, Donlin, Laura T., Butler, Andrew, Rozo, Cristina, Bracken, Bernadette, Rashidfarrokhi, Ali, Goodman, Susan M., Ivashkiv, Lionel B., Bykerk, Vivian P., Orange, Dana E., Darnell, Robert B., Swerdlow, Harold P., and Satija, Rahul

Subjects
RHEUMATOID arthritis, TISSUES, BIOLOGY, DROPLETS
Abstract

Droplet-based single-cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While this approach offers the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we developed a 3D-printed, low-cost droplet microfluidic control instrument and deploy it in a clinical environment to perform single-cell transcriptome profiling of disaggregated synovial tissue from five rheumatoid arthritis patients. We sequence 20,387 single cells revealing 13 transcriptomically distinct clusters. These encompass an unsupervised draft atlas of the autoimmune infiltrate that contribute to disease biology. Additionally, we identify previously uncharacterized fibroblast subpopulations and discern their spatial location within the synovium. We envision that this instrument will have broad utility in both research and clinical settings, enabling low-cost and routine application of microfluidic techniques. [ABSTRACT FROM AUTHOR]

Published
2018
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8. G&T-seq: parallel sequencing of single-cell genomes and transcriptomes.

Author

Macaulay, Iain C, Haerty, Wilfried, Kumar, Parveen, Li, Yang I, Hu, Tim Xiaoming, Teng, Mabel J, Goolam, Mubeen, Saurat, Nathalie, Coupland, Paul, Shirley, Lesley M, Smith, Miriam, Van der Aa, Niels, Banerjee, Ruby, Ellis, Peter D, Quail, Michael A, Swerdlow, Harold P, Zernicka-Goetz, Magdalena, Livesey, Frederick J, Ponting, Chris P, and Voet, Thierry

Subjects
NUCLEOTIDE sequencing, RNA sequencing, GENETIC transcription, SINGLE nucleotide polymorphisms, DNA copy number variations, EXONS (Genetics), CELL lines, BREAST cancer
Abstract

The simultaneous sequencing of a single cell's genome and transcriptome offers a powerful means to dissect genetic variation and its effect on gene expression. Here we describe G&T-seq, a method for separating and sequencing genomic DNA and full-length mRNA from single cells. By applying G&T-seq to over 220 single cells from mice and humans, we discovered cellular properties that could not be inferred from DNA or RNA sequencing alone. [ABSTRACT FROM AUTHOR]

Published
2015
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9. DNA Immobilization: Silanized Nucleic Acids and Nanoprinting.

Author

Wittmann, Christine, Du, Quan, Larsson, Ola, Swerdlow, Harold, and Liang, Zicai

Abstract

Over the last decade, the development of DNA microarray technology has allowed the simultaneous analysis of many thousands of different genes in histological or cytological specimens. Although DNA microarrays can also be fabricated by photolithographic synthesis, the current paper focuses mainly on methods of DNA attachment by spotting on solid surfaces. Chemical modifications on solid surfaces (such as glass) and the DNA molecules have been presented with special focus on the approach of silanized nucleic acids, a method of DNA modification that can rid the need of glass surface modifications, and nanoprinting method, a way of producing high-density DNA arrays by a stamping mechanism. Different glass and DNA modifications have been applied to a different extent in the DNA microarray industry, but it is anticipated that, with the application of the DNA chip shifting gradually from large-scale expression profiling to more focused genotyping or diagnostics, the utilization of these methods may also shift according to the needs. [ABSTRACT FROM AUTHOR]

Published
2006
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10. SASI-Seq: sample assurance Spike-Ins, and highly differentiating 384 barcoding for Illumina sequencing.

Author

Quail, Michael A., Smith, Miriam, Jackson, David, Leonard, Steven, Skelly, Thomas, Swerdlow, Harold P., Yong Gu, and Ellis, Peter

Subjects
SEQUENCING batch reactor process, INDEXING, BAR codes, LUMINOUS flux, ASSURANCE (Theology), INDUSTRIAL contamination
Abstract

Background A minor but significant fraction of samples subjected to next-generation sequencing methods are either mixed-up or cross-contaminated. These events can lead to false or inconclusive results. We have therefore developed SASI-Seq; a process whereby a set of uniquely barcoded DNA fragments are added to samples destined for sequencing. From the final sequencing data, one can verify that all the reads derive from the original sample(s) and not from contaminants or other samples. Results By adding a mixture of three uniquely barcoded amplicons, of different sizes spanning the range of insert sizes one would normally use for Illumina sequencing, at a spike-in level of approximately 0.1%, we demonstrate that these fragments remain intimately associated with the sample. They can be detected following even the tightest size selection regimes or exome enrichment and can report the occurrence of sample mix-ups and cross-contamination. As a consequence of this work, we have designed a set of 384 eleven-base Illumina barcode sequences that are at least 5 changes apart from each other, allowing for single-error correction and very low levels of barcode misallocation due to sequencing error. Conclusion SASI-Seq is a simple, inexpensive and flexible tool that enables sample assurance, allows deconvolution of sample mix-ups and reports levels of cross-contamination between samples throughout NGS workflows. [ABSTRACT FROM AUTHOR]

Published
2014
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11. Optimal enzymes for amplifying sequencing libraries.

Author

Quail, Michael A, Otto, Thomas D, Gu, Yong, Harris, Simon R, Skelly, Thomas F, McQuillan, Jacqueline A, Swerdlow, Harold P, and Oyola, Samuel O

Subjects
LETTERS to the editor, ENZYME analysis, GENE amplification
Abstract

A letter to the editor is presented which discusses the identification of optimal enzymes for amplifying high complexity mixtures of DNA fragments.

Published
2012
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13. Efficient depletion of host DNA contamination in malaria clinical sequencing.

Author

Oyola SO, Gu Y, Manske M, Otto TD, O'Brien J, Alcock D, Macinnis B, Berriman M, Newbold CI, Kwiatkowski DP, Swerdlow HP, and Quail MA

Subjects
DNA Methylation, DNA, Protozoan genetics, Humans, Hydrolysis, Molecular Epidemiology methods, Plasmodium falciparum isolation & purification, DNA Contamination, DNA, Protozoan isolation & purification, Malaria, Falciparum parasitology, Molecular Biology methods, Parasitology methods, Plasmodium falciparum genetics
Abstract

The cost of whole-genome sequencing (WGS) is decreasing rapidly as next-generation sequencing technology continues to advance, and the prospect of making WGS available for public health applications is becoming a reality. So far, a number of studies have demonstrated the use of WGS as an epidemiological tool for typing and controlling outbreaks of microbial pathogens. Success of these applications is hugely dependent on efficient generation of clean genetic material that is free from host DNA contamination for rapid preparation of sequencing libraries. The presence of large amounts of host DNA severely affects the efficiency of characterizing pathogens using WGS and is therefore a serious impediment to clinical and epidemiological sequencing for health care and public health applications. We have developed a simple enzymatic treatment method that takes advantage of the methylation of human DNA to selectively deplete host contamination from clinical samples prior to sequencing. Using malaria clinical samples with over 80% human host DNA contamination, we show that the enzymatic treatment enriches Plasmodium falciparum DNA up to ∼9-fold and generates high-quality, nonbiased sequence reads covering >98% of 86,158 catalogued typeable single-nucleotide polymorphism loci.

Published
2013
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14. Optimal enzymes for amplifying sequencing libraries.

Author

Quail MA, Otto TD, Gu Y, Harris SR, Skelly TF, McQuillan JA, Swerdlow HP, and Oyola SO

Subjects
Bordetella pertussis genetics, Genome, Bacterial genetics, Humans, Plasmodium falciparum genetics, Salmonella genetics, Staphylococcus aureus genetics, DNA-Directed DNA Polymerase metabolism, Genomic Library, Nucleic Acid Amplification Techniques methods, Polymerase Chain Reaction methods
Published
2011
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