Literature DB >> 33694043

Performance comparison: exome sequencing as a single test replacing Sanger sequencing.

Hila Fridman1,2, Concetta Bormans3, Moshe Einhorn4, Daniel Au3, Arjan Bormans3, Yuval Porat4, Luisa Fernanda Sanchez3, Brent Manning3, Ephrat Levy-Lahad5,6, Doron M Behar3.   

Abstract

Next generation sequencing tests are used routinely as first-choice tests in the clinic. However, systematic performance comparing the results of exome sequencing as a single test replacing Sanger sequencing of targeted gene(s) is still lacking. Performance comparison data are critically important for clinical case management. In this study, we compared Sanger-sequencing results of 258 genes to those obtained from next generation sequencing (NGS) using two exome-sequencing enrichment kits: Agilent-SureSelectQXT and Illumina-Nextera. Sequencing was performed on leukocytes and buccal-derived DNA from a single individual, and all 258 genes were sequenced a total of 11 times (using different sequencing methods and DNA sources). Sanger sequencing was completed for all exons, including flanking ± 8 bp regions. For the 258 genes, NGS mean coverage was > 20 × for > 98 and > 91% of the regions targeted by SureSelect and Nextera, respectively. Overall, 449 variants were identified in at least one experiment, and 407/449 (90.6%) were detected by all. Of the 42 discordant variants, 23 were determined as true calls, summing-up to a truth set of 430 variants. Sensitivity of true-variant detection was 99% for Sanger sequencing and 97-100% for the NGS experiments. Mean false-positive rates were 3.7E-6 for Sanger sequencing, 2.5E-6 for SureSelect-NGS and 5.2E-6 for Nextera-NGS. Our findings suggest a high overall concordance between Sanger sequencing and NGS performances. Both methods demonstrated false-positive and false-negative calls. High clinical suspicion for a specific diagnosis should, therefore, override negative results of either Sanger sequencing or NGS.

Keywords:  Comparison; Next generation; Performance; Sanger; Sequencing

Year:  2021        PMID: 33694043     DOI: 10.1007/s00438-021-01772-3

Source DB:  PubMed          Journal:  Mol Genet Genomics        ISSN: 1617-4623            Impact factor:   3.291


  23 in total

1.  Distinct DNA methylation patterns characterize differentiated human embryonic stem cells and developing human fetal liver.

Authors:  Alayne L Brunner; David S Johnson; Si Wan Kim; Anton Valouev; Timothy E Reddy; Norma F Neff; Elizabeth Anton; Catherine Medina; Loan Nguyen; Eric Chiao; Chuba B Oyolu; Gary P Schroth; Devin M Absher; Julie C Baker; Richard M Myers
Journal:  Genome Res       Date:  2009-03-09       Impact factor: 9.043

2.  Genome sequencing identifies major causes of severe intellectual disability.

Authors:  Christian Gilissen; Jayne Y Hehir-Kwa; Djie Tjwan Thung; Maartje van de Vorst; Bregje W M van Bon; Marjolein H Willemsen; Michael Kwint; Irene M Janssen; Alexander Hoischen; Annette Schenck; Richard Leach; Robert Klein; Rick Tearle; Tan Bo; Rolph Pfundt; Helger G Yntema; Bert B A de Vries; Tjitske Kleefstra; Han G Brunner; Lisenka E L M Vissers; Joris A Veltman
Journal:  Nature       Date:  2014-06-04       Impact factor: 49.962

Review 3.  Towards precision medicine.

Authors:  Euan A Ashley
Journal:  Nat Rev Genet       Date:  2016-08-16       Impact factor: 53.242

Review 4.  Coming of age: ten years of next-generation sequencing technologies.

Authors:  Sara Goodwin; John D McPherson; W Richard McCombie
Journal:  Nat Rev Genet       Date:  2016-05-17       Impact factor: 53.242

Review 5.  Recent advances in the genetics of autism spectrum disorder.

Authors:  Silvia De Rubeis; Joseph D Buxbaum
Journal:  Curr Neurol Neurosci Rep       Date:  2015-06       Impact factor: 5.081

6.  A comprehensive genomic approach for neuromuscular diseases gives a high diagnostic yield.

Authors:  Arunkanth Ankala; Cristina da Silva; Francesca Gualandi; Alessandra Ferlini; Lora J H Bean; Christin Collins; Alice K Tanner; Madhuri R Hegde
Journal:  Ann Neurol       Date:  2014-12-17       Impact factor: 10.422

7.  Comprehensive comparison of three commercial human whole-exome capture platforms.

Authors:  Yu Xu; Hui Jiang; Chris Tyler-Smith; Yali Xue; Tao Jiang; Jiawei Wang; Mingzhi Wu; Xiao Liu; Geng Tian; Jun Wang; Jian Wang; Huangming Yang; Xiuqing Zhang
Journal:  Genome Biol       Date:  2011-09-28       Impact factor: 13.583

8.  Performance comparison of exome DNA sequencing technologies.

Authors:  Michael J Clark; Rui Chen; Hugo Y K Lam; Konrad J Karczewski; Rong Chen; Ghia Euskirchen; Atul J Butte; Michael Snyder
Journal:  Nat Biotechnol       Date:  2011-09-25       Impact factor: 68.164

9.  Domain of dentine sialoprotein mediates proliferation and differentiation of human periodontal ligament stem cells.

Authors:  Alkan Ozer; Guohua Yuan; Guobin Yang; Feng Wang; Wentong Li; Yuan Yang; Feng Guo; Qingping Gao; Lisa Shoff; Zhi Chen; Isabel C Gay; Kevin J Donly; Mary MacDougall; Shuo Chen
Journal:  PLoS One       Date:  2013-12-03       Impact factor: 3.240

10.  Performance comparison of four exome capture systems for deep sequencing.

Authors:  Chandra Sekhar Reddy Chilamakuri; Susanne Lorenz; Mohammed-Amin Madoui; Daniel Vodák; Jinchang Sun; Eivind Hovig; Ola Myklebost; Leonardo A Meza-Zepeda
Journal:  BMC Genomics       Date:  2014-06-09       Impact factor: 3.969

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  1 in total

1.  Performance comparison of Agilent new SureSelect All Exon v8 probes with v7 probes for exome sequencing.

Authors:  Vera Belova; Anna Shmitko; Anna Pavlova; Robert Afasizhev; Valery Cheranev; Anastasia Tabanakova; Natalya Ponikarovskaya; Denis Rebrikov; Dmitriy Korostin
Journal:  BMC Genomics       Date:  2022-08-12       Impact factor: 4.547

  1 in total

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