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

被引:0
作者
K. H. Moumouni
B. A. Kountche
M. Jean
C. T. Hash
Y. Vigouroux
B. I. G. Haussmann
F. Belzile
机构
[1] Université Laval,Département de Phytologie, Faculté des Sciences de l’Agriculture et de l’Alimentation and Institut de Biologie Intégrative et des Systèmes
[2] International Crops Research Institute for the Semi-Arid Tropics (ICRISAT),Faculté d’Agronomie
[3] Institut de Recherche pour le Développement (IRD),Institute of Plant Breeding, Seed Science and Population Genetics (350a)
[4] Université Abdou Moumouni,undefined
[5] University of Hohenheim,undefined
来源
Molecular Breeding | 2015年 / 35卷
关键词
Pearl millet; Genetic map; SNP; Genotyping-by-sequencing;
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学科分类号
摘要
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 F2 population 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 F2 individuals 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.
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