Evaluation of microsatellite-based genetic diversity, protein and mineral content in chickpea accessions grown in Kyrgyzstan

The genetic diversity of 23 chickpea accessions representing Kyrgyz landraces and cultivars, ICARDA breeding lines, Spanish and Turkish cultivars was characterized using nine microsatellite (SSR) markers which generated a total of 122 alleles. The number of alleles (Na) per locus varied from 9 to 20. The observed heterozygosity (Ho) ranged between 0.05 and 0.43 (average 0.13) whereas both the expected heterozygosity (He) and polymorphic information content (PIC) ranged from 0.71 to 0.90 (average 0.83). Analysis of molecular variance (AMOVA) showed that 62% of the total genetic variation was found within accessions while the remaining 38% was found among accessions. Principal coordinate analysis (PCoA) indicated the presence of two groups. The two Kyrgyz cultivars were found apart from these groups. Cluster analysis generally confirmed the results of PCoA and also separated the Kyrgyz cultivars from the subcluster formed by Kyrgyz landraces and the subclusters formed by breeding lines from ICARDA along with landraces from Turkey and Spain. In addition, protein content and mineral concentration were determined. Protein content and mineral concentrations for Ca, S, Mg, P, K, Fe, Mn, Cu and Zn varied significantly among accessions. The results show that Kyrgyz germplasm provides a source of diversity for improvement of chickpea

Genotype tables for the "Analysis of microsatellite loci in tree of heaven (Ailanthus altissima (Mill.) Swingle) using SSR-GBS"

Genotypes of 90 individuals of tree of heaven (Ailanthus altissima) at 19 microsatellite loci described in the cited study. Tissue was collected from three forest stands in Eastern Austria

Data from: Analysis of microsatellite loci in tree of heaven (Ailanthus altissima (Mill.) Swingle) using SSR-GBS

Microsatellite markers are still the marker of choice for many research questions in the field of forest genetics. However, the number of available markers is often low for species that have not been studied intensively like the tree of heaven (Ailanthus altissima). During the last decade, next generation sequencing (NGS) has offered advanced techniques for efficiently identifying microsatellite markers and accurately genotyping samples. Here, we identify new microsatellite markers for the tree of heaven by applying an NGS-based method using the Illumina MiSeq platform. NGS technology was proved to be an effective method for fast and cost-efficient identification of microsatellite markers by implementing a genotyping-by-sequencing approach based on Illumina amplicon sequencing (SSR-GBS). We screened three populations from Eastern Austria for genetic variation at 19 newly identified microsatellite loci. We tested two different genotyping approaches: (1) considering only allele lengths (forming a so-called ‘allele length dataset’), (2) taking also single nucleotide polymorphisms (SNPs) within the amplified fragments into account (forming a so-called ‘SNP dataset’). The results revealed higher values for all genetic diversity parameters, as well as a better resolution of genetic assignment, when the latter approach was followed. Thus, by taking advantage of sequence information which is provided by SSR-GBS, one may achieve considerable gains in performance using the same marker set. The developed markers provide a cost-efficient tool for genotyping populations of tree of heaven and the approach presented here promises to be of high value for medium throughput genotyping applications in non-model forest tree species. We will use this method to widen the perspectives for further population genetic investigations of the tree of heaven

Misligholdsbeføyelser ved aksjonæravtaler

Characteristics of the 16 SSR markers used in this study with indication of the corresponding multiplex and dye. Footnotes: a [61]; b [60]; c [59]; d [62]; e Primer concentration within a given multiplex has been adjusted to get more homogeneous SSR marker amplification intensities. (XLSX 10 kb