Evaluation of genetic diversity in wild orchardgrass (Dactylis glomerata L.) based on AFLP markers

Abstract

Studnicki M., Mądry W., Schmidt J. (2013): Comparing the efficiency of sampling strategies to establish a representative in the phenotypic-based genetic diversity core collection of orchardgrass (Dactylis glomerata L.). Czech J. Genet. Plant Breed., 49: 36-47. Establishing a core collection that represents the genetic diversity of the entire collection with a minimum loss of its original diversity and minimal redundancies is an important problem for gene bank curators and crop breeders. In this paper, we assess the representativeness of the original genetic diversity in core collections consisting of one-tenth of the entire collection obtained according to 23 sampling strategies. The study was performed using the Polish orchardgrass Dactylis glomerata L. germplasm collection as a model. The representativeness of the core collections was validated by the difference of means (MD%) and difference of mean squared Euclidean distance (d-D%) for the studied traits in the core subsets and the entire collection. In this way, we compared the efficiency of a simple random and 22 (20 cluster-based and 2 direct cluster-based) stratified sampling strategies. Each cluster-based stratified sampling strategy is a combination of 2 clusterings, 5 allocations and 2 methods of sampling in a group. We used the accession genotypic predicted values for 8 quantitative traits tested in field trials. A sampling strategy is considered more effective for establishing core collections if the means of the traits in a core are maintained at the same level as the means in the entire collection (i.e., the mean of MD% in the simulated samples is close to zero) and, simultaneously, when the overall variation in a core collection is greater than in the entire collection (i.e., the mean of d-D% in the simulated samples is greater than that obtained for the simple random sampling strategy). Both cluster analyses (unweighted pair group method with arithmetic mean UPGMA and Ward) were similarly useful in constructing those sampling strategies capable of establishing representative core collections. Among the allocation methods that are relatively most useful for constructing efficient samplings were proportional and D2 (including variation). Within the Ward clusters, the random sampling was better than the cluster-based sampling, but not within the UPGMA clusters.

Diversity comparison and phylogenetic relationships of cocksfoot (Dactylis glomerata L.) germplasm as revealed by SSR markers

“…A total of 143 polymorphic alleles was generated from 21 primer pairs, with an average of 6.8 alleles per locus, which were sufficient to detect variation and to differentiate D. glomerata accessions from different geographical origins. Based on our SSR data set, the polymorphic rate (P) over 16 accessions of D. glomerata was 90.7%, which was higher than reports of AFLP variation (P: 84.0%) (Peng et al 2008) and ISSR variation (P: 86.3%) ), yet much higher than SRAP variation (P: 84.38%) (Zeng et al 2008) in D. glomerata. The present study found the polymorphic rate was 78.85% in accession PI308794, which means this accession had a higher degree of polymorphism than other accessions.…”

“…Variations in cocksfoot morphological features, distributional patterns, adaptive, agronomic characters and allozymes have been well documented (Lumaret et al 1987;Sahuquillo and Lumaret 1995;Volaire and Thomas 1995;Gauthier et al 1998;Gauthier and Lumaret 1999;Tosun et al 2002). More recently, a number of molecular genetic marker systems have been developed for use in cocksfoot breeding, including random amplified polymorphic DNA (RAPD) markers (Kolliker et al 1999;Tuna et al 2004;, amplified fragment length polymorphism (AFLP) (Reeves et al 1998;Peng et al 2008), inter-simple sequence repeat (ISSR) markers ) and sequence-related amplified polymorphism (SRAP) markers (Zeng et al 2008). These studies demonstrated the usefulness of DNA profiling in accessing genetic differences of cocksfoot and revealed a high degree of genetic diversity of cocksfoot accessions.…”

Identification of orchardgrass (Dactylis glomerata L.) cultivars by using simple sequence repeat markers

“…In the current study, a total of 29 SSR primer pairs were used to estimate the genetic diversity of a collection of orchardgrass cultivars. The P value of the 32 orchardgrass cultivars studied was 92.1%, which was higher compared to that reported for expressed sequence tag-simple sequence repeat (EST-SSR) variation (P = 74.1%) (Xie et al, 2010), SRAP variation (P = 84.38%) (Zeng et al, 2008), AFLP variation (P = 84.0%) (Peng et al, 2008), or ISSR variation (P = 86.3%) (Zeng et al, 2006) in orchardgrass. The average allele of each marker was 7.9, which was higher compared to previous research on 74 accessions (6.3 alleles per locus) of Dactylis species (Xie et al, 2010).…”

“…To overcome these limitations, a number of molecular markers in orchardgrass have been employed for genetic diversity assessments, genetic mapping, and quantitative trait loci (QTL) analysis, because these traits are not influenced by variable environmental conditions with similar phenotype or plant phenology (Belaj et al, 2002). These markers include sequence-related amplified polymorphism (SRAP) (Zeng et al, 2008;Xie et al, 2011), random amplified polymorphic DNA (RAPD) (Kolliker et al, 1999;Tuna et al, 2004), amplified fragment length polymorphism (AFLP) (Peng et al, 2008), inter-simple sequence repeat (ISSR) (Zeng et al, 2006), and simple sequence repeats (SSR) (Xie et al, 2010;Bushman et al, 2011).…”

Orchardgrass (Dactylis glomerata L.) EST and SSR marker development, annotation, and transferability

“…Previous studies have used a variety of tools: chloroplast and ITS sequences have been used to describe phylogenetic relationships (Lumaret et al 1989;Catalan et al 2004;Stewart and Ellison 2010), dominant markers (e.g., RAPD, ISSR, SRAP) used in discreet studies (Koelliker et al 1999;Tuna et al 2004;Peng et al 2008;Zeng et al 2008), and heterologous markers tested from other forage grass species Litrico et al 2009), However, the openplatform dominant markers generally have the inability to add samples to a study without re-analyzing all previous samples due to the large number of bands genotyped per primer. Heterologous marker transferability also decreases as species diverge (Thiel et al 2003;Zhang et al 2005;Litrico et al 2009), and are accompanied by higher likelihood of homoplasy and polymorphism due to mutations that exist among the species (Thiel et al 2003;Saha et al 2004;Zhang et al 2006).…”