in silico Whole Genome Sequencer & Analyzer (iWGS): A Computational Pipeline to Guide the Design and Analysis of de novo Genome Sequencing Studies
Abstract
The availability of genomes across the tree of life is highly biased toward vertebrates, pathogens, human disease models, and organisms with relatively small and simple genomes. Recent progress in genomics has enabled the de novo decoding of the genome of virtually any organism, greatly expanding its potential for understanding the biology and evolution of the full spectrum of biodiversity. The increasing diversity of sequencing technologies, assays, and de novo assembly algorithms have augmented the complexity of de novo genome sequencing projects in nonmodel organisms. To reduce the costs and challenges in de novo genome sequencing projects and streamline their experimental design and analysis, we developed iWGS (in silico Whole Genome Sequencer and Analyzer), an automated pipeline for guiding the choice of appropriate sequencing strategy and assembly protocols. iWGS seamlessly integrates the four key steps of a de novo genome sequencing project: data generation (through simulation), data quality control, de novo assembly, and assembly evaluation and validation. The last three steps can also be applied to the analysis of real data. iWGS is designed to enable the user to have great flexibility in testing the range of experimental designs available for genome sequencing projects, and supports all major sequencing technologies andmore »
- Authors:
-
[1];
[2];
[2];
[3];
[2];
[1]
- Vanderbilt Univ., Nashville, TN (United States). Dept. of Biological Sciences
- Univ. of Wisconsin, Madison, WI (United States). Wisconsin Energy Inst., J. F. Crow Inst. for the Study of Evolution, Lab. of Genetics, Genome Center of Wisconsin, Dept. of Energy Great Lakes Bioenergy Research Center
- US Dept. of Agriculture (USDA)., Peoria, IL (United States). National Center for Agricultural Utilization Research, Agricultural Research Service, Mycotoxin Prevention and Applied Microbiology Research Unit
- Publication Date:
- Research Org.:
- Argonne National Laboratory (ANL), Argonne, IL (United States). Advanced Photon Source (APS); Univ. of Wisconsin, Madison (United States); Lawrence Berkeley National Laboratory (LBNL), CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); National Institutes of Health (NIH); National Science Foundation (NSF)
- OSTI Identifier:
- 1373365
- Alternate Identifier(s):
- OSTI ID: 1378364
- Grant/Contract Number:
- AC02-06CH11357; AC02-05CH11231; FC02-07ER64494
- Resource Type:
- Accepted Manuscript
- Journal Name:
- G3
- Additional Journal Information:
- Journal Volume: 6; Journal Issue: 11; Journal ID: ISSN 2160-1836
- Publisher:
- Genetics Society of America
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; Genome Sequencing; High-Throughput Sequencing; De Novo Assembly; Experimental Design; Simulation; Nonmodel Organism
Citation Formats
Zhou, Xiaofan, Peris, David, Kominek, Jacek, Kurtzman, Cletus P., Hittinger, Chris Todd, and Rokas, A. in silico Whole Genome Sequencer & Analyzer (iWGS): A Computational Pipeline to Guide the Design and Analysis of de novo Genome Sequencing Studies. United States: N. p., 2016.
Web. doi:10.1534/g3.116.034249.
Zhou, Xiaofan, Peris, David, Kominek, Jacek, Kurtzman, Cletus P., Hittinger, Chris Todd, & Rokas, A. in silico Whole Genome Sequencer & Analyzer (iWGS): A Computational Pipeline to Guide the Design and Analysis of de novo Genome Sequencing Studies. United States. https://doi.org/10.1534/g3.116.034249
Zhou, Xiaofan, Peris, David, Kominek, Jacek, Kurtzman, Cletus P., Hittinger, Chris Todd, and Rokas, A. Fri .
"in silico Whole Genome Sequencer & Analyzer (iWGS): A Computational Pipeline to Guide the Design and Analysis of de novo Genome Sequencing Studies". United States. https://doi.org/10.1534/g3.116.034249. https://www.osti.gov/servlets/purl/1373365.
@article{osti_1373365,
title = {in silico Whole Genome Sequencer & Analyzer (iWGS): A Computational Pipeline to Guide the Design and Analysis of de novo Genome Sequencing Studies},
author = {Zhou, Xiaofan and Peris, David and Kominek, Jacek and Kurtzman, Cletus P. and Hittinger, Chris Todd and Rokas, A.},
abstractNote = {The availability of genomes across the tree of life is highly biased toward vertebrates, pathogens, human disease models, and organisms with relatively small and simple genomes. Recent progress in genomics has enabled the de novo decoding of the genome of virtually any organism, greatly expanding its potential for understanding the biology and evolution of the full spectrum of biodiversity. The increasing diversity of sequencing technologies, assays, and de novo assembly algorithms have augmented the complexity of de novo genome sequencing projects in nonmodel organisms. To reduce the costs and challenges in de novo genome sequencing projects and streamline their experimental design and analysis, we developed iWGS (in silico Whole Genome Sequencer and Analyzer), an automated pipeline for guiding the choice of appropriate sequencing strategy and assembly protocols. iWGS seamlessly integrates the four key steps of a de novo genome sequencing project: data generation (through simulation), data quality control, de novo assembly, and assembly evaluation and validation. The last three steps can also be applied to the analysis of real data. iWGS is designed to enable the user to have great flexibility in testing the range of experimental designs available for genome sequencing projects, and supports all major sequencing technologies and popular assembly tools. Three case studies illustrate how iWGS can guide the design of de novo genome sequencing projects, and evaluate the performance of a wide variety of user-specified sequencing strategies and assembly protocols on genomes of differing architectures. iWGS, along with a detailed documentation, is freely available at https://github.com/zhouxiaofan1983/iWGS.},
doi = {10.1534/g3.116.034249},
journal = {G3},
number = 11,
volume = 6,
place = {United States},
year = {Fri Sep 16 00:00:00 EDT 2016},
month = {Fri Sep 16 00:00:00 EDT 2016}
}
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Figures / Tables:
Figure 1: iWGS workflow. A typical iWGS analysis consists of four steps: (1) data simulation (optional); (2) preprocessing (optional); (3) de novo assembly; and (4) assembly evaluation. iWGS supports both Illumina short reads and PacBio long reads, and a wide selection of assemblers to enable de novo assembly using eithermore »
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QUAST: quality assessment tool for genome assemblies
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GAGE-B: an evaluation of genome assemblers for bacterial organisms
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The MaSuRCA genome assembler
journal, August 2013
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Evaluation and validation of de novo and hybrid assembly techniques to derive high-quality genome sequences
journal, June 2014
- Utturkar, Sagar M.; Klingeman, Dawn M.; Land, Miriam L.
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RAMPART: a workflow management system for de novo genome assembly
journal, January 2015
- Mapleson, Daniel; Drou, Nizar; Swarbreck, David
- Bioinformatics, Vol. 31, Issue 11
Mitochondrial genome evolution in yeasts: an all-encompassing view
journal, May 2015
- Freel, Kelle C.; Friedrich, Anne; Schacherer, Joseph
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Genome 10K: A Proposal to Obtain Whole-Genome Sequence for 10 000 Vertebrate Species
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- Arenas, Miguel; Posada, David
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The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification
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- Nucleic Acids Research, Vol. 43, Issue D1
Contiguous and accurate de novo assembly of metazoan genomes with modest long read coverage
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Metassembler: Merging and optimizing de novo genome assemblies
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- Wences, Alejandro Hernandez; Schatz, Michel C.
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Velvet: Algorithms for de novo short read assembly using de Bruijn graphs
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- Zerbino, D. R.; Birney, E.
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ABySS: A parallel assembler for short read sequence data
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- Simpson, J. T.; Wong, K.; Jackman, S. D.
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Assemblathon 1: A competitive assessment of de novo short read assembly methods
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- Earl, D.; Bradnam, K.; St. John, J.
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Efficient de novo assembly of large genomes using compressed data structures
journal, December 2011
- Simpson, J. T.; Durbin, R.
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GAGE: A critical evaluation of genome assemblies and assembly algorithms
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journal, March 2014
- Zhou, Xiaofan; Rokas, Antonis
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Comparative genomics reveals insights into avian genome evolution and adaptation
journal, December 2014
- Zhang, G.; Li, C.; Li, Q.
- Science, Vol. 346, Issue 6215
The Genome Sequence of Drosophila melanogaster
journal, March 2000
- Adams, M. D.
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Creating a Buzz About Insect Genomes
journal, March 2011
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The Theory and Practice of Genome Sequence Assembly
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text, January 2014
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Extensive Error in the Number of Genes Inferred from Draft Genome Assemblies
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Meraculous: De Novo Genome Assembly with Short Paired-End Reads
journal, August 2011
- Chapman, Jarrod A.; Ho, Isaac; Sunkara, Sirisha
- PLoS ONE, Vol. 6, Issue 8
Pilon: An Integrated Tool for Comprehensive Microbial Variant Detection and Genome Assembly Improvement
journal, November 2014
- Walker, Bruce J.; Abeel, Thomas; Shea, Terrance
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Diverse Lifestyles and Strategies of Plant Pathogenesis Encoded in the Genomes of Eighteen Dothideomycetes Fungi
journal, December 2012
- Ohm, Robin A.; Feau, Nicolas; Henrissat, Bernard
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Finished Genome of the Fungal Wheat Pathogen Mycosphaerella graminicola Reveals Dispensome Structure, Chromosome Plasticity, and Stealth Pathogenesis
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journal, May 2018
- Krassowski, Tadeusz; Coughlan, Aisling Y.; Shen, Xing-Xing
- Nature Communications, Vol. 9, Issue 1
Repeat-aware evaluation of scaffolding tools
journal, March 2018
- Mandric, Igor; Knyazev, Sergey; Zelikovsky, Alex
- Bioinformatics, Vol. 34, Issue 15
Next-generation forward genetic screens: using simulated data to improve the design of mapping-by-sequencing experiments in Arabidopsis
journal, September 2019
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- Nucleic Acids Research, Vol. 47, Issue 21
Solving scaffolding problem with repeats
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Mitochondria-encoded genes contribute to evolution of heat and cold tolerance in yeast
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Evolution of a novel chimeric maltotriose transporter in Saccharomyces eubayanus from parent proteins unable to perform this function
journal, April 2019
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- PLOS Genetics, Vol. 15, Issue 4
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