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Logo of bmcgenoBioMed Centralsearchsubmit a manuscriptregisterthis articleBMC Genomics
 
BMC Genomics. 2009; 10: 582.
Published online Dec 4, 2009. doi:  10.1186/1471-2164-10-582
PMCID: PMC2797026
Development and implementation of high-throughput SNP genotyping in barley
Timothy J Close,corresponding author1 Prasanna R Bhat,1,12 Stefano Lonardi,2 Yonghui Wu,2,13 Nils Rostoks,3,14 Luke Ramsay,3 Arnis Druka,3 Nils Stein,4 Jan T Svensson,1,15 Steve Wanamaker,1 Serdar Bozdag,2,16 Mikeal L Roose,1 Matthew J Moscou,1,17 Shiaoman Chao,5 Rajeev K Varshney,4,18 Péter Szűcs,6 Kazuhiro Sato,7 Patrick M Hayes,6 David E Matthews,8 Andris Kleinhofs,9 Gary J Muehlbauer,10 Joseph DeYoung,11 David F Marshall,3 Kavitha Madishetty,1 Raymond D Fenton,1 Pascal Condamine,1,19 Andreas Graner,4 and Robbie Waugh3
1Department of Botany & Plant Sciences, University of California (UCR), Riverside, CA, 92521, USA
2Department of Computer Sciences, University of California (UCR), Riverside, CA, 92521, USA
3Scottish Crop Research Institute (SCRI), Invergowrie, Dundee, DD2 5DA, UK
4Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstrasse 3, D-06466, Gatersleben, Germany
5USDA-ARS Biosciences Research Lab, Fargo, ND, 58105-5674, USA
6Department of Crop and Soil Science, Oregon State University, Corvallis, OR, 97331, USA
7Research Institute for Bioresources, Okayama University, Kurashiki, 710-0046, Japan
8USDA-ARS, Cornell University, Ithaca, NY, 14853, USA
9Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99164, USA
10Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
11Southern California Genotyping Consortium, University of California, Los Angeles, CA, 90095, USA
12Monsanto Research Centre, Bangalore, 560092, India
13Google, Mountain View, CA, 94043, USA
14Faculty of Biology, University of Latvia, 4 Kronvalda Boulevard, Riga, LV-1586, Latvia
15University of Copenhagen, Frederiksberg C, DK-1871, Denmark
16NIH National Cancer Institute, Neuro-Oncology Branch, Bethesda, MD, 20892, USA
17Department of Plant Pathology, Iowa State University, Ames, Iowa, 50011, USA
18International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru - 502 324, Andhra Pradesh, India
19NetSocial Marketing, Le Puech, 15600 Montmurat, France
corresponding authorCorresponding author.
Timothy J Close: timothy.close/at/ucr.edu; Prasanna R Bhat: prasannarb/at/gmail.com; Stefano Lonardi: stelo/at/cs.ucr.edu; Yonghui Wu: yonghui/at/cs.ucr.edu; Nils Rostoks: nrostoks/at/latnet.lv; Luke Ramsay: Luke.Ramsay/at/scri.ac.uk; Arnis Druka: arnisdruka/at/aol.com; Nils Stein: stein/at/ipk-gatersleben.de; Jan T Svensson: jsv/at/life.ku.dk; Steve Wanamaker: steve.wanamaker/at/ucr.edu; Serdar Bozdag: sbozdag/at/cs.ucr.edu; Mikeal L Roose: mikeal.roose/at/ucr.edu; Matthew J Moscou: moscou/at/iastate.edu; Shiaoman Chao: Shiaoman.Chao/at/ars.usda.gov; Rajeev K Varshney: r.k.varshney/at/cgiar.org; Péter Szűcs: Peter.Szucs/at/oregonstate.edu; Kazuhiro Sato: kazsato/at/rib.okayama-U.ac.jp; Patrick M Hayes: hayesp/at/css.orst.edu; David E Matthews: Matthews/at/greengenes.cit.cornell.edu; Andris Kleinhofs: andyk/at/wsu.edu; Gary J Muehlbauer: Gary.J.Muehlbauer-1/at/tc.umn.edu; Joseph DeYoung: Jdeyoung/at/mednet.ucla.edu; David F Marshall: D.F.Marshall/at/scri.sari.ac.uk; Kavitha Madishetty: kavithavcs/at/yahoo.com; Raymond D Fenton: raymond.fenton/at/ucr.edu; Pascal Condamine: pascalcondamine/at/yahoo.fr; Andreas Graner: a_graner/at/IPK-Gatersleben.de; Robbie Waugh: rwaugh/at/scri.sari.ac.uk
Received July 31, 2009; Accepted December 4, 2009.
Abstract
Background
High density genetic maps of plants have, nearly without exception, made use of marker datasets containing missing or questionable genotype calls derived from a variety of genic and non-genic or anonymous markers, and been presented as a single linear order of genetic loci for each linkage group. The consequences of missing or erroneous data include falsely separated markers, expansion of cM distances and incorrect marker order. These imperfections are amplified in consensus maps and problematic when fine resolution is critical including comparative genome analyses and map-based cloning. Here we provide a new paradigm, a high-density consensus genetic map of barley based only on complete and error-free datasets and genic markers, represented accurately by graphs and approximately by a best-fit linear order, and supported by a readily available SNP genotyping resource.
Results
Approximately 22,000 SNPs were identified from barley ESTs and sequenced amplicons; 4,596 of them were tested for performance in three pilot phase Illumina GoldenGate assays. Data from three barley doubled haploid mapping populations supported the production of an initial consensus map. Over 200 germplasm selections, principally European and US breeding material, were used to estimate minor allele frequency (MAF) for each SNP. We selected 3,072 of these tested SNPs based on technical performance, map location, MAF and biological interest to fill two 1536-SNP "production" assays (BOPA1 and BOPA2), which were made available to the barley genetics community. Data were added using BOPA1 from a fourth mapping population to yield a consensus map containing 2,943 SNP loci in 975 marker bins covering a genetic distance of 1099 cM.
Conclusion
The unprecedented density of genic markers and marker bins enabled a high resolution comparison of the genomes of barley and rice. Low recombination in pericentric regions is evident from bins containing many more than the average number of markers, meaning that a large number of genes are recombinationally locked into the genetic centromeric regions of several barley chromosomes. Examination of US breeding germplasm illustrated the usefulness of BOPA1 and BOPA2 in that they provide excellent marker density and sensitivity for detection of minor alleles in this genetically narrow material.
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