Genetic variability evaluation and cultivar identification of tetraploid annual ryegrass using SSR markers

Abstract

Annual ryegrass (Lolium multiflorum) is a widely used cool-season turf and forage grass with high productivity and ornamental characteristics. However, the abundant intra-cultivar genetic variability usually hampers the application of conventional techniques for cultivar identification. The objectives of this study were to: (1) describe an efficient strategy for identification of six tetraploid annual ryegrass cultivars and (2) investigate the genetic diversity based on SSR markers. A total of 242 reliable bands were obtained from 29 SSR primer pairs with an average of 8.3 bands for each primer pair and the average value of polymorphic information content (PIC) was 0.304. The result of analysis of molecular variance (AMOVA) revealed that 81.99% of the genetic variation occurred in within-cultivars and 18.01% among-cultivars. The principal coordinate analysis (PCoA) showed that the first two principal axes explain 8.57% (PC1) and 6.05% (PC2) of total variation, respectively. By using multi-bulk strategy based on different filtering thresholds, the results suggested that bands frequency of 40% could be used as a reliable standard for cultivar identification in annual ryegrass. Under this threshold, 12 SSR primer pairs (00-04A, 02-06G, 02-08C, 03-05A, 04-05B, 10-09E, 12-01A, 13-02H, 13-12D, 14-06F, 15-01C and 17-10D) were detected for direct identification of six tetraploid annual ryegrass cultivars, which could be incorporated into conservation schemes to protect the intellectual property of breeders, ensure purity for consumers, as well as guarantee effective use of cultivars in future.

RAD-seq as an effective strategy for heterogenous variety identification in plants—a case study in Italian Ryegrass (Lolium multiflorum)

“…In contrast, high-resolution and high-throughput approach sequencing methods are more convenient and reliable for this task. In our previous study, SSR markers were used to distinguish 6 Italian ryegrass varieties [ 12 ]. We found that 17 out of 29 polymorphic SSR markers could not completely distinguish the 6 tested Italian ryegrass varieties.…”

“…Traditional molecular markers are basically limited to dozens of pairs of primers, of which only a few hundred bands can be amplified based on PCR amplification [ 1 , 8 , 12 ]. In contrast, 18,558,247 SNP markers were detected in this study, which proves that RAD-seq could detect far more sites than traditional molecular markers.…”

“…In addition to optimal high-throughput sequencing, a suitable sampling strategy was also essential for the success of variety identification of OPVs. Previous studies [ 1 , 12 , 42 ] used mixed samples for variety distinction to keep track of the genetic diversity, and these could greatly facilitate evaluating their performance [ 43 ], however, there were only 10–30 individuals for a bulked sample, which did not sufficiently represent all variation in the population. In addition, for a traditional molecular marker, the amount of DNA template used is insufficient if there are too many individuals in a mixed sample, and the lower DNA content of each individual might lead to weak PCR amplification patterns inadequately representing the whole sample.…”

“…However, for a single bulked sample, the limited number of individuals is insufficient to represent the genetic integrity of a heterogeneous population [ 4 ]. For a large number of OPVs, it is sensible to use multiple mixed samples instead of single samples [ 12 ]. In fact, researchers have reached a consensus on using mixed samples for the variety identification of cross-pollinated species [ 4 ].…”

Genetic diversity and population structure analysis in a large collection of white clover (Trifolium repens L.) germplasm worldwide

“…The markers associate with the non-repetitive regions of the genome and exhibit high mutation rates ( Kalia et al, 2011 ; Morgante, Hanafey & Powell, 2002 ). SSR markers have been widely used to evaluate the genetic variation for various plants, e.g., Medicago truncatula ( Eujayl et al, 2004 ), Lolium multiflorum ( Nie et al, 2019 ), Rhdodendron arboretum ( Sharma et al, 2020 ), Pteroceltis tatarinowii ( Zhang et al, 2020 ).…”