title: Identification of SNP and SSR Markers in Finger Millet Using Next Generation Sequencing Technologies.
abstract: Finger millet is an important cereal crop in eastern Africa and southern India with excellent grain storage quality and unique ability to thrive in extreme environmental conditions. Since negligible attention has been paid to improving this crop to date, the current study used Next Generation Sequencing (NGS) technologies to develop both Simple Sequence Repeat (SSR) and Single Nucleotide Polymorphism (SNP) markers. Genomic DNA from cultivated finger millet genotypes KNE755 and KNE796 was sequenced using both Roche 454 and Illumina technologies. Non-organelle sequencing reads were assembled into 207 Mbp representing approximately 13% of the finger millet genome. We identified 10,327 SSRs and 23,285 non-homeologous SNPs and tested 101 of each for polymorphism across a diverse set of wild and cultivated finger millet germplasm. For the 49 polymorphic SSRs, the mean polymorphism information content (PIC) was 0.42, ranging from 0.16 to 0.77. We also validated 92 SNP markers, 80 of which were polymorphic with a mean PIC of 0.29 across 30 wild and 59 cultivated accessions. Seventy-six of the 80 SNPs were polymorphic across 30 wild germplasm with a mean PIC of 0.30 while only 22 of the SNP markers showed polymorphism among the 59 cultivated accessions with an average PIC value of 0.15. Genetic diversity analysis using the polymorphic SNP markers revealed two major clusters; one of wild and another of cultivated accessions. Detailed STRUCTURE analysis confirmed this grouping pattern and further revealed 2 sub-populations within wild E. coracana subsp. africana. Both STRUCTURE and genetic diversity analysis assisted with the correct identification of the new germplasm collections. These polymorphic SSR and SNP markers are a significant addition to the existing 82 published SSRs, especially with regard to the previously reported low polymorphism levels in finger millet. Our results also reveal an unexploited finger millet genetic resource that can be included in the regional breeding programs in order to efficiently optimize productivity.
authors.affiliation: Kenyatta University, P.O. Box 43844-00100, Nairobi, Kenya.
authors.forename: Davis
authors.initials: D
authors.lastname: Gimode
authors.affiliation: ICRISAT-Nairobi, P.O. Box 39063-00623, Nairobi, Kenya.
authors.forename: Damaris A
authors.initials: DA
authors.lastname: Odeny
authors.affiliation: Center for Tropical Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom.
authors.forename: Etienne P
authors.initials: EP
authors.lastname: de Villiers
authors.affiliation: University of Eldoret, P.O. Box 1125-30100, Eldoret, Kenya.
authors.forename: Solomon
authors.initials: S
authors.lastname: Wanyonyi
authors.affiliation: Maseno University, Private Bag, Maseno, Kenya.
authors.forename: Mathews M
authors.initials: MM
authors.lastname: Dida
authors.affiliation: Mikocheni Agricultural Research Institute, P.O. Box 6226, Dar-Es-Salaam, Tanzania.
authors.forename: Emmarold E
authors.initials: EE
authors.lastname: Mneney
authors.affiliation: Kenyatta University, P.O. Box 43844-00100, Nairobi, Kenya.|ICRAF-Nairobi, P.O Box 30677, Nairobi, Kenya.
authors.forename: Alice
authors.initials: A
authors.lastname: Muchugi
authors.affiliation: Kenyatta University, P.O. Box 43844-00100, Nairobi, Kenya.
authors.forename: Jesse
authors.initials: J
authors.lastname: Machuka
authors.affiliation: Pwani University, PO Box 195-80108, Kilifi, Kenya.
authors.forename: Santie M
authors.initials: SM
authors.lastname: de Villiers
mesh_terms: D019295:Computational Biology / Q000379:methods; D057225:Data Mining; D030541:Databases, Genetic; D031748:Eleusine / Q000235:genetics*; D014644:Genetic Variation; D005828:Genetics, Population; D005838:Genotype; D059014:High-Throughput Nucleotide Sequencing; D018895:Microsatellite Repeats; D058977:Molecular Sequence Annotation; D010802:Phylogeny; D020641:Polymorphism, Single Nucleotide; D015203:Reproducibility of Results