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Sequencing, Assembling, and Correcting Draft Genomes Using Recombinant Populations

Matthew W. Hahn, Simo V. Zhang and Leonie C. Moyle
G3: Genes, Genomes, Genetics April 1, 2014 vol. 4 no. 4 669-679; https://doi.org/10.1534/g3.114.010264
Matthew W. Hahn
Department of Biology, Indiana University, Bloomington, Indiana 47405School of Informatics and Computing, Indiana University, Bloomington, Indiana 47405
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  • For correspondence: mwh@indiana.edu
Simo V. Zhang
School of Informatics and Computing, Indiana University, Bloomington, Indiana 47405
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Leonie C. Moyle
Department of Biology, Indiana University, Bloomington, Indiana 47405
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Abstract

Current de novo whole-genome sequencing approaches often are inadequate for organisms lacking substantial preexisting genetic data. Problems with these methods are manifest as: large numbers of scaffolds that are not ordered within chromosomes or assigned to individual chromosomes, misassembly of allelic sequences as separate loci when the individual(s) being sequenced are heterozygous, and the collapse of recently duplicated sequences into a single locus, regardless of levels of heterozygosity. Here we propose a new approach for producing de novo whole-genome sequences—which we call recombinant population genome construction—that solves many of the problems encountered in standard genome assembly and that can be applied in model and nonmodel organisms. Our approach takes advantage of next-generation sequencing technologies to simultaneously barcode and sequence a large number of individuals from a recombinant population. The sequences of all recombinants can be combined to create an initial de novo assembly, followed by the use of individual recombinant genotypes to correct assembly splitting/collapsing and to order and orient scaffolds within linkage groups. Recombinant population genome construction can rapidly accelerate the transformation of nonmodel species into genome-enabled systems by simultaneously producing a high-quality genome assembly and providing genomic tools (e.g., high-confidence single-nucleotide polymorphisms) for immediate applications. In populations segregating for important functional traits, this approach also enables simultaneous mapping of quantitative trait loci. We demonstrate our method using simulated Illumina data from a recombinant population of Caenorhabditis elegans and show that the method can produce a high-fidelity, high-quality genome assembly for both parents of the cross.

  • genome
  • genetics
  • assembly
  • next-generation sequencing
  • duplication
  • Received October 28, 2013.
  • Accepted February 10, 2014.
  • Copyright © 2014 Hahn et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution Unported License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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PUBLICATION INFORMATION

Volume 4 Issue 4, April 2014

G3: Genes|Genomes|Genetics: 4 (4)

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Investigations
Multiparental Populations
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Sequencing, Assembling, and Correcting Draft Genomes Using Recombinant Populations

Matthew W. Hahn, Simo V. Zhang and Leonie C. Moyle
G3: Genes, Genomes, Genetics April 1, 2014 vol. 4 no. 4 669-679; https://doi.org/10.1534/g3.114.010264
Matthew W. Hahn
Department of Biology, Indiana University, Bloomington, Indiana 47405School of Informatics and Computing, Indiana University, Bloomington, Indiana 47405
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: mwh@indiana.edu
Simo V. Zhang
School of Informatics and Computing, Indiana University, Bloomington, Indiana 47405
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Leonie C. Moyle
Department of Biology, Indiana University, Bloomington, Indiana 47405
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
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Citation

Sequencing, Assembling, and Correcting Draft Genomes Using Recombinant Populations

Matthew W. Hahn, Simo V. Zhang and Leonie C. Moyle
G3: Genes, Genomes, Genetics April 1, 2014 vol. 4 no. 4 669-679; https://doi.org/10.1534/g3.114.010264
Matthew W. Hahn
Department of Biology, Indiana University, Bloomington, Indiana 47405School of Informatics and Computing, Indiana University, Bloomington, Indiana 47405
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: mwh@indiana.edu
Simo V. Zhang
School of Informatics and Computing, Indiana University, Bloomington, Indiana 47405
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Leonie C. Moyle
Department of Biology, Indiana University, Bloomington, Indiana 47405
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site

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  • A Very Oil Yellow1 Modifier of the Oil Yellow1-N1989 Allele Uncovers a Cryptic Phenotypic Impact of Cis-regulatory Variation in Maize
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Multiparental Populations

  • A Statistical Procedure for Genome-Wide Detection of QTL Hotspots Using Public Databases with Application to Rice
  • GAL4 Drivers Specific for Type Ib and Type Is Motor Neurons in Drosophila
  • A Very Oil Yellow1 Modifier of the Oil Yellow1-N1989 Allele Uncovers a Cryptic Phenotypic Impact of Cis-regulatory Variation in Maize
Show more Multiparental Populations
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The Genetics Society of America (GSA), founded in 1931, is the professional membership organization for scientific researchers and educators in the field of genetics. Our members work to advance knowledge in the basic mechanisms of inheritance, from the molecular to the population level.

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