Assessment of genetic diversity within and between pearl millet landraces

Abstract

A minimum core subset of pearl millet [ Pennisetum glaucum (L.) R. Br.], which comprised 504 landrace accessions, was recently established from the global pearl millet germplasm collection of ICRISAT. The accessions for this core were selected by a random proportional sampling strategy following stratification of the entire landrace collection (about 16,000 accessions) according to their geographic origin and morpho-agronomic traits. In this study RFLP probes were used to quantify the genetic diversity within and between landrace accessions of this minimum core using a subset comprising ten accessions of Indian origin. Twenty five plants per accession were assayed with EcoRI, EcoRV, HindIII and DraI restriction enzymes, and 16 highly polymorphic RFLP probes, nine associated with a quantitative trait loci (QTLs) for downy mildew resistance, and five associated with a QTL for drought tolerance. A total of 51 alleles were detected using 16 different probe-enzyme combinations. The partitioning of variance components based on the analysis of molecular variance (AMOVA) for diversity analysis revealed high within-accession variability (30.9%), but the variability between accessions was significantly higher (69.1%) than that within the accessions. A dendrogram based on the dissimilarity matrix obtained using Ward's algorithm further delineated the 250 plants into ten major clusters, each comprised of plants from a single accession (with the exception of two single plants). A similar result was found in an earlier study using morpho-agronomic traits and geographic origin. This study demonstrated the utility of RFLP markers in detecting polymorphism and estimating genetic diversity in a highly cross-pollinated species such as pearl millet. When less-tedious marker systems are available, this method could be further extended to assess the genetic diversity between and within the remaining accessions in the pearl millet core subset.

Molecular Markers for the Classification of Switchgrass (Panicum virgatum L.) Germplasm and to Assess Genetic Diversity in Three Synthetic Switchgrass Populations

“…AFLP analyses of genetic variation within and among South American hexaploid accessions and taxa of Bromus section Ceratochloa showed a diversity of 94% among accessions and an average diversity of 47% within taxonomic groups of hexaploid accessions (Massa et al 2001). Assessment of genetic diversity in pearl millet using RFLP revealed 30.9% variability within accessions and 69.1% between accessions (Bhattacharjee et al 2002).…”

“…In the present study, heterologous RFLP markers were used to estimate polymorphism and genetic diversity within and between three synthetic cultivars, 'Alamo', 'Kanlow', and 'Summer' widely used in biomass-energy breeding programs. RFLP markers have been used in studies of genetic diversity in several grasses including rice (Oryza sativa L.) (Zhang et al 1992), maize (Gauthier et al 2002), and pearl millet (Pennisetum glaucum L.) (Bhattacharjee et al 2002). Even though they are more laborious and time consuming compared to RAPD and AFLP (Karp et al 1996), RFLPs are locus specific and more repeatable.…”

Development of a molecular linkage map of pearl millet integrating DArT and SSR markers

“…Such genetic differences in pearl millet have been studied previously by morphological and isozyme analysis (Tostain et al 1987;Tostain and Marchais, 1989;Tostain, 1992). Subsequently, RAPDs (Chowdari et al 1998), RFLPs (Bhattacharjee et al 2002), and SSRs (Budak et al 2003;Kapila et al 2008) and combinations of SSRs with other PCR-compatible markers (Thudi et al 2010) have been used to estimate pearl millet genetic diversity. The power of DArT fingerprinting method lies in its ability to compare different genomes at a large number of loci in a single assay, at an average cost per marker locus that is very low compared with PCR-compatible markers.…”

II.1.5 Phenotyping pearl millet for adaptation to drought

“…These genetic tools have been used to develop a DNA marker-based linkage map for pearl millet (Liu et al, 1994), and to map quantitative trait loci (QTLs) conferring resistance to biotic stresses (Jones et al, 1995, 2002; Morgan et al, 1998) and tolerance to terminal drought stress (Yadav et al, 2002b). They have also been used for: (1) identification of QTLs for flowering time, that appear to be largely responsible for genotype-by-environment interaction (GEI) for grain and stover yield under favorable growing conditions (Yadav et al, 2002a); (2) diversity assessment (Liu et al, 1992; Bhattacharjee et al, 2002); (3) studies of recombination rates (Busso et al, 1995; Liu et al, 1996); (4) analysis of the domestication syndrome (Poncet et al, 2000, 2002); and (5) comparative genomics (Devos et al, 1998; Devos and Gale, 2000). …”