Construction of a genetic map for pearl millet, Pennisetum glaucum (L.) R. Br., using a genotyping-by-sequencing (GBS) approach

• Published in: Molecular breeding 2015-01, Vol.35 (1), p.1-10, Article 5
• Main Authors: Moumouni, K. H, Kountche, B. A, Jean, M, Hash, C. T, Vigouroux, Y, Haussmann, B. I. G, Belzile, F
• Format: Article
• Language: English
• Subjects: agronomic traits; Biomedical and Life Sciences; Biotechnology; breeding; diet; gene frequency; haplotypes; Life Sciences; linkage groups; microsatellite repeats; parents; Pennisetum glaucum; Plant Genetics and Genomics; Plant Pathology; Plant Physiology; Plant Sciences; polymerase chain reaction; restriction endonucleases; single nucleotide polymorphism; Striga; traditional farming
• ISSN: 1380-3743; 1572-9788
• DOI: 10.1007/s11032-015-0212-x

Pearl millet is the main component of traditional farming systems and a staple grain in the diet of sub-Saharan Africa and India. To facilitate breeding work in this crop, a genetic map consisting of single nucleotide polymorphism (SNP) markers was constructed using an F₂population of 93 progenies, from a wild × cultivated pearl millet cross. We used a modified genotyping-by-sequencing (GBS) protocol involving two restriction enzymes (PstI–MspI) and PCR amplification with primers including three selective bases to generate 3,321 SNPs. Of these, 2,809 high-quality SNPs exhibited a minor allele frequency ≥0.3. In total, 314 non-redundant haplotypes and 85 F₂individuals were used to construct a genetic map spanning a total distance of 640 cM. These SNPs were evenly distributed over seven linkage groups ranging considerably in size (62–123 cM). The average density for this map was 0.51 SNP/cM, and the average interval between SNP markers was 2.1 (±0.6) cM. Finally, to establish bridges between the linkage groups of this and previous maps, 19 SSR markers were examined for polymorphism between the parents of this population. We could only tentatively suggest a correspondence between four of our linkage groups and those of previous maps. Overall, GBS enabled us to quickly produce a genetic map with a density and uniformity of markers greater than previously published maps. The availability of such a map will be useful for the identification of genomic regions associated with Striga resistance and other important agronomic traits.