Comparison of Exome and Genome Sequencing Technologies for the Complete Capture of Protein‐Coding Regions

For next‐generation sequencing technologies, sufficient base‐pair coverage is the foremost requirement for the reliable detection of genomic variants. We investigated whether whole‐genome sequencing (WGS) platforms offer improved coverage of coding regions compared with whole‐exome sequencing (WES) platforms, and compared single‐base coverage for a large set of exome and genome samples. We find that WES platforms have improved considerably in the last years, but at comparable sequencing depth, WGS outperforms WES in terms of covered coding regions. At higher sequencing depth (95x–160x), WES successfully captures 95% of the coding regions with a minimal coverage of 20x, compared with 98% for WGS at 87‐fold coverage. Three different assessments of sequence coverage bias showed consistent biases for WES but not for WGS. We found no clear differences for the technologies concerning their ability to achieve complete coverage of 2,759 clinically relevant genes. We show that WES performs comparable to WGS in terms of covered bases if sequenced at two to three times higher coverage. This does, however, go at the cost of substantially more sequencing biases in WES approaches. Our findings will guide laboratories to make an informed decision on which sequencing platform and coverage to choose.

[1]  Xin Jin,et al.  Detecting novel genetic mutations in Chinese Usher syndrome families using next-generation sequencing technology , 2015, Molecular Genetics and Genomics.

[2]  Giuliana Silvestri,et al.  Next-generation sequencing-based molecular diagnosis of 82 retinitis pigmentosa probands from Northern Ireland , 2014, Human Genetics.

[3]  Xuan Yuan,et al.  Effectiveness of exome and genome sequencing guided by acuity of illness for diagnosis of neurodevelopmental disorders , 2014, Science Translational Medicine.

[4]  G. Xing,et al.  Targeted genomic capture and massively parallel sequencing to identify novel variants causing Chinese hereditary hearing loss , 2014, Journal of Translational Medicine.

[5]  Yuan Xue,et al.  Solving the molecular diagnostic testing conundrum for Mendelian disorders in the era of next-generation sequencing: single-gene, gene panel, or exome/genome sequencing , 2014, Genetics in Medicine.

[6]  Alison M. Meynert,et al.  Variant detection sensitivity and biases in whole genome and exome sequencing , 2014, BMC Bioinformatics.

[7]  L. Vissers,et al.  Genome sequencing identifies major causes of severe intellectual disability , 2014, Nature.

[8]  T. Haaf,et al.  Targeted next-generation sequencing of deafness genes in hearing-impaired individuals uncovers informative mutations , 2014, Genetics in Medicine.

[9]  Erika Check Hayden,et al.  Technology: The $1,000 genome , 2014, Nature.

[10]  Euan A Ashley,et al.  Clinical interpretation and implications of whole-genome sequencing. , 2014, JAMA.

[11]  J. Zook,et al.  Integrating human sequence data sets provides a resource of benchmark SNP and indel genotype calls , 2013, Nature Biotechnology.

[12]  Byung-Ok Choi,et al.  Comprehensive Analysis to Improve the Validation Rate for Single Nucleotide Variants Detected by Next-Generation Sequencing , 2014, PloS one.

[13]  E. Hayden Is the $1,000 genome for real? , 2014 .

[14]  Eric Vilain,et al.  Assessing the necessity of confirmatory testing for exome sequencing results in a clinical molecular diagnostic laboratory , 2014, Genetics in Medicine.

[15]  Daniel R. Zerbino,et al.  Ensembl 2014 , 2013, Nucleic Acids Res..

[16]  Melissa J. Landrum,et al.  RefSeq: an update on mammalian reference sequences , 2013, Nucleic Acids Res..

[17]  P. Stenson,et al.  The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine , 2013, Human Genetics.

[18]  Joel Gelernter,et al.  Variant Callers for Next-Generation Sequencing Data: A Comparison Study , 2013, PloS one.

[19]  S. Scherer,et al.  Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing. , 2013, American journal of human genetics.

[20]  Marc S. Williams,et al.  ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing , 2013, Genetics in Medicine.

[21]  M. Spielmann,et al.  CNVs of noncoding cis-regulatory elements in human disease. , 2013, Current opinion in genetics & development.

[22]  N. Lennon,et al.  Characterizing and measuring bias in sequence data , 2013, Genome Biology.

[23]  Anh-Dao Nguyen,et al.  Clinical Genomic Database , 2013, Proceedings of the National Academy of Sciences.

[24]  E. Zrenner,et al.  Panel-based next generation sequencing as a reliable and efficient technique to detect mutations in unselected patients with retinal dystrophies , 2013, European Journal of Human Genetics.

[25]  P. Sullivan,et al.  Improving detection of copy-number variation by simultaneous bias correction and read-depth segmentation , 2012, Nucleic acids research.

[26]  Y. Benjamini,et al.  Summarizing and correcting the GC content bias in high-throughput sequencing , 2012, Nucleic acids research.

[27]  Euan A Ashley,et al.  Performance comparison of whole-genome sequencing platforms , 2011, Nature Biotechnology.

[28]  Hugo Y. K. Lam,et al.  Performance comparison of exome DNA sequencing technologies , 2011, Nature Biotechnology.

[29]  M. Spector,et al.  A comparative analysis of exome capture , 2011, Genome Biology.

[30]  Heikki Joensuu,et al.  Comparison of solution-based exome capture methods for next generation sequencing , 2011, Genome Biology.

[31]  Stephen C. J. Parker,et al.  Accurate and comprehensive sequencing of personal genomes. , 2011, Genome research.

[32]  R. Gibbs,et al.  Targeted enrichment beyond the consensus coding DNA sequence exome reveals exons with higher variant densities , 2011, Genome Biology.

[33]  Misko Dzamba,et al.  Detecting copy number variation with mated short reads. , 2010, Genome research.

[34]  P. Stankiewicz,et al.  Whole-genome sequencing in a patient with Charcot-Marie-Tooth neuropathy. , 2010, The New England journal of medicine.

[35]  Christian Gilissen,et al.  Massively parallel sequencing of ataxia genes after array‐based enrichment , 2010, Human mutation.

[36]  Edwin Cuppen,et al.  Accurate SNP and mutation detection by targeted custom microarray-based genomic enrichment of short-fragment sequencing libraries , 2010, Nucleic acids research.

[37]  Gonçalo R. Abecasis,et al.  The Sequence Alignment/Map format and SAMtools , 2009, Bioinform..

[38]  K. Fliessbach,et al.  Human Mutation , 2017 .

[39]  Ira M. Hall,et al.  BEDTools: a flexible suite of utilities for comparing genomic features , 2010, Bioinform..

[40]  Claude-Alain H. Roten,et al.  Fast and accurate short read alignment with Burrows–Wheeler transform , 2009, Bioinform..

[41]  Geoffrey E. Hinton,et al.  Melting of Peridotite to 140 Gigapascals , 2010, Science.

[42]  Terrence S. Furey,et al.  The UCSC Table Browser data retrieval tool , 2004, Nucleic Acids Res..

[43]  Elizabeth M. Smigielski,et al.  dbSNP: the NCBI database of genetic variation , 2001, Nucleic Acids Res..