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Open Access Research article

Saturated linkage map construction in Rubus idaeus using genotyping by sequencing and genome-independent imputation

Judson A Ward1*, Jasbir Bhangoo2, Felicidad Fernández-Fernández3, Patrick Moore4, JD Swanson5, Roberto Viola6, Riccardo Velasco6, Nahla Bassil7, Courtney A Weber1 and Daniel J Sargent6

Author affiliations

1 Department of Horticulture, Cornell University, New York State Agricultural Experiment Station, Geneva, New York, 14456, USA

2 Sector 18, Chandigarh, UT, 160018, India

3 East Malling Research (EMR), New Road, East Malling, Kent, ME, 19 6BJ, UK

4 Department of Horticulture and Landscape Architecture, Washington State University Puyallup Research and Extension Center, Puyallup, WA, 98372, USA

5 Department of Biology and Biomedical Sciences, Salve Regina University, 100 Ochre Point Ave, Newport, RI, 02840, USA

6 IASMA Research and Innovation Centre, Foundation Edmund Mach, Via E Mach 1, San Michele all’Adige, (TN), 38010, Italy

7 USDA-ARS National Clonal Germplasm Repository, 33447 Peoria Rd, Corvallis, OR, 97333, USA

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Citation and License

BMC Genomics 2013, 14:2  doi:10.1186/1471-2164-14-2

Published: 16 January 2013

Abstract

Background

Rapid development of highly saturated genetic maps aids molecular breeding, which can accelerate gain per breeding cycle in woody perennial plants such as Rubus idaeus (red raspberry). Recently, robust genotyping methods based on high-throughput sequencing were developed, which provide high marker density, but result in some genotype errors and a large number of missing genotype values. Imputation can reduce the number of missing values and can correct genotyping errors, but current methods of imputation require a reference genome and thus are not an option for most species.

Results

Genotyping by Sequencing (GBS) was used to produce highly saturated maps for a R. idaeus pseudo-testcross progeny. While low coverage and high variance in sequencing resulted in a large number of missing values for some individuals, a novel method of imputation based on maximum likelihood marker ordering from initial marker segregation overcame the challenge of missing values, and made map construction computationally tractable. The two resulting parental maps contained 4521 and 2391 molecular markers spanning 462.7 and 376.6 cM respectively over seven linkage groups. Detection of precise genomic regions with segregation distortion was possible because of map saturation. Microsatellites (SSRs) linked these results to published maps for cross-validation and map comparison.

Conclusions

GBS together with genome-independent imputation provides a rapid method for genetic map construction in any pseudo-testcross progeny. Our method of imputation estimates the correct genotype call of missing values and corrects genotyping errors that lead to inflated map size and reduced precision in marker placement. Comparison of SSRs to published R. idaeus maps showed that the linkage maps constructed with GBS and our method of imputation were robust, and marker positioning reliable. The high marker density allowed identification of genomic regions with segregation distortion in R. idaeus, which may help to identify deleterious alleles that are the basis of inbreeding depression in the species.

Keywords:
Genotyping by sequencing; GBS; RADseq; Imputation; Raspberry; Rubus idaeus; Psuedotestcross; Linkage map; Segregation distortion