Cross transferability and PCR amplification
Molecular markers facilitate precise and quick varietal identification, germplasm characterization and conservation. Microsatellite markers have been most preferred in molecular studies because of their codominance, high discrimination power, multiallelic nature and cross transferability within genera/family. They are easy to use, cost effective and amenable to automation as compared to other markers. Development of novel SSRs for concerned species involves sequencing of targeted genomic regions and is a costly affair with absence of genomic information. Studies on deciphering genomic sequence in flower bulbs particularly in gladiolus is comparatively difficult due to high heterozygosity, polyploidy and huge genome size [17]. Under such circumstances, a common procedure to detect microsatellite loci for a target species is through cross species and cross genera transferability of SSRs [22]. Success of heterologous amplification relies on conserved nucleotide sequence among the flanking regions of phylogenetically similar species. In the present investigation, 17 highly polymorphic SSRs were detected from a set of 65 microsatellites reported within iridaceae family members. The polymorphic microsatellites included seven chloroplast SSRs of gladiolus, five genomic SSRs of Gladiolus palustris and five EST derived SSRs of Iris. Chloroplast SSRs have been widely used to study phylogenetic evolution of plants in recent years. It is established that chloroplast genome is characterized by conserved genic sequences, non-recombination and maternal inheritance in plants [34]. Out of 12 chloroplast SSRs identified by Singh and coworkers [40], seven were polymorphic among gladiolus genotypes. Chloroplast SSRs revealed higher level of diversity in rice and barley species in contrast to chloroplast derived RFLPs [33, 35]. The microsatellites reported for Gladiolus palustris (tetraploid) showed positive cross species transferability (66.66%) in gladiolus cultivars. This indicated presence of conserved genomic regions between Gladiolus palustris and modern gladiolus cultivars. Cross species amplification of these microsatellites has been also studied in individuals of Gladiolus imbricatus and Gladiolus tenuis [20]. In support of our findings, close genetic relationship between modern gladiolus cultivars and Gladiolus palustris was revealed using chloroplast DNA regions [42]. In addition, Iris EST-SSRs also portrayed successful cross genera amplification (48%) in gladiolus. Our findings are consistent with prediction that suggested that cross-transferability of SSRs can vary from 50 to 100 % within a genus, while transferability across genera is generally less than 50% [27]. SSR markers derived from ESTs or transcriptome have high rate of cross transferability as they are located very close to or within functional genes. Therefore, they are highly conserved and often show significant polymorphism among plant species [15]. Possibility of cross transferability is high when the repeat sequences and flanking region consisting selected primer region is conserved across taxa. In a similar line of study, Debener (2012) analyzed genetic diversity of Euphorbia pulcherrima accessions using EST SSRs developed for Euphorbia esula through cross species amplification [7]. In ornamentals, congeneric transferability of microsatellite markers has been investigated in Iris spp. [45], Aspidistra spp. [12] and cacti [2].
Marker efficiency and allelic diversity measures
Molecular profiling of 84 gladiolus genotypes using 17 polymorphic SSRs revealed that all were highly informative. Representative gel electrophoresis profiles for markers G5 and GP13 are presented in Fig. 3. Abundant polymorphism and more genomic coverage of molecular markers increases accuracy in genetic diversity studies. Amount of genotyping required for phylogenetic analysis of crop plants can be reduced with highly informative markers. According to Botstein et al (1980), a DNA marker with PIC value more than 0.5 is said to be highly informative [3]. PIC and Rp (> 0.50 and > 2.0, respectively) values for most of the loci suggested that SSR markers were efficient enough to distinguish gladiolus germplasm in the study. Higher PIC value of SSR markers may be attributed to their codominant and multi allelic nature. Marker indices define total utility of marker system in estimating genetic variation within germplasm pool. GP4 had highest marker index value of 2.38. Estimates of PIC, RP and MI signify overall ability of such markers in detecting polymorphisms in the plant population and between any two genotypes or cultivars taken at random from that population, the overall utility of a marker for detecting genetic variation and infer genetic relationships between accessions [30]. In the current study, SSR markers showed comparatively higher polymorphism against those DNA markers used in earlier reports [36, 23, 4, 43].
Allele wise mean genetic diversity parameters (Na, Ne, I, Ho, He, F, h, Havg & Nm) indicated effectiveness of these SSRs to characterize the gladiolus germplasm used in the present study. Average Nei’s genetic diversity (equivalent to average expected heterozygosity) indicated higher frequency of heterozygotes at single locus when chosen randomly. Average expected heterozygosity was comparatively high than observed heterozygosity for tested SSRs. Inbreeding coefficient values for most of the SSRs were low suggesting less fixation of alleles. Average estimated gene flow revealed high allelic diversity among gladiolus genotypes. Similarly, allelic diversity has been estimated using EST-SSRs in Iris spp. [50, 45, 49] and genomic SSRs in crocus [24], herbertia [10] and gladiolus [20]. Non neutral markers detected based on Ewens Watterson test indicated their possible linkage to phenotypic traits or genes under selection. Kirk and Freeland (2011) suggested that non neutral markers may show unusual genetic divergence for traits under selection [16].
Population structure and cluster analysis
STRUCTURE analysis based on Bayesian approach grouped the overall gladiolus germplasm into two subpopulations however, no clear distinction among the Indian and exotic germplasm was established. Exotic genotypes could not be demarcated from Indian bred genotypes because introduced exotic gladioli have been used as parents in crossing programme and therefore fall within pedigree of Indian genotypes (Table S1). It has been known that no gladiolus species is native to India and it was introduced to India in later part of 19th century. Cultivated gladioli (Gladiolus × grandiflorus) are complex hybrids and have been evolved from interspecific hybridization among wild species viz. Gladiolus cardinalis, Gladiolus daleni, Gladiolus oppositiflorus, Gladiolus papilio, Gladiolus carneus, Gladiolus cruentus, Gladiolus tristis and Gladiolus saundersii [13]. In a similar line of study, Choudhary et al (2018) revealed presence of mixed population among gladiolus germplasm while analyzing STRUCTURE of 53 gladiolus genotypes using ISSR markers [4]. AMOVA results showed minor variation between two subpopulations whereas individuals within total population depicted maximum variance. Wright’s F statistics differentiated whole germplasm into two subdivided population based on level of allele frequencies shared among individuals. According to Vicente et al (2004), if FST value is within the range of 0.05–0.15, then subpopulations are assumed to be moderately differentiated at genetic level [5, 6]. Moderate (FST = 0.10) genetic differentiation of allelic frequencies was observed among two subpopulations. Average heterozygotes in each subpopulation (FIT = 0.41) and among subpopulations (FIT = 0.46) indicated existence of large non-random mating among individuals within subpopulations. This may be attributed to complex ploidy level, high heterozygosity and cross pollination nature of gladiolus. Various factors including pollen movement, germplasm exchange, natural selection, reproduction system and geographical distribution decide the level of variability existing among the populations. Subpopulation 1 was genetically more diverse than subpopulation 2 accounting highest average genetic diversity estimates (Na, Ne, I, Ho, and He).
Genetic relationships
In our study, the grouping pattern arising from STRUCTURE were consistent with those obtained from UPGMA dendrogram and PCoA in terms of genotype number and composition of clusters excluding few admixtures. A detailed insight into genetic relationship among gladiolus varieties was inferred from polymorphic SSR data based on Jaccard’s similarity matrix and UPGMA clustering. Two major clusters containing 42 genotypes each were identified at an average pairwise similarity of 0.49 based on Jaccard’s similarity matrix. Highest degree of similarity for cultivar pairs viz. Dhanvantari - Fire Flame (Jaccard’s coefficient = 0.97) followed by Yellow Star - Neel Rekha (Jaccard’s coefficient = 0.96) was recorded and it was evident from their close presence in Cluster II, while lowest degree of similarity between cultivar pairs viz. Punjab Dawn - Punjab Lemon Delight and Arka Arti - Punjab Lemon Delight was observed and thus their presence in different clusters could be noticed. Based on simple matching dissimilarity matrix, Punjab Lemon Delight - Vicki Lin (coefficient of dissimilarity = 0.89) had highest degree of dissimilarity. Presence of Punjab Lemon Delight - Vicki Lin in cluster I and II respectively, could be justified to their clustering pattern. Punjab Lemon Delight and Vicki Lin were found genetically distinct among gladiolus genotypes used in the study.
Cultivar pairs which shared common parent/s (either male/female or both) in their derivation were found closely spaced in cluster I. Indian bred cultivars namely Arka Amar (Watermelon Pink × Arka Aarti), Arka Darshan (Watermelon Pink × Shirley), Arka Sapna (Green Woodpecker × Friendship), Pusa Chandni (Green Woodpecker × White Butterfly), Punjab Glad 1 (Happy End × True Yellow) and Punjab Glance (Happy End × Yellow Stone) were grouped together owing to common female parent during hybridization. While Punjab Pink Elegance (Suchitra × White Prosperity) and Punjab Lemon Delight (Jacksonville Gold × White Prosperity) were noticed in the same cluster showing similarity in their male parentage. Thus, presence of Suchitra, Jacksonville Gold and Yellow Stone in the same group could be highly obvious. Occurrence of Pusa Sarang (OP seedling obtained from ‘White Oak’), Pusa Shagun (White Oak × Oscar), Pusa Mohini (Ave × Christian Jane) and Pusa Kiran (OP seedling obtained from ‘Ave’) in cluster I was evident showing their affinity towards parentage. However, rest of the genotypes could not share any common parentage but clustered together. This might be attributed to highly heterozygous nature of crop.
Correspondingly, cluster II was also formed by the genotypes sharing common lineage. Presence of Punjab Dawn (Suchitra × Melody), Arka Arti (Shirley × Melody), Amethyst (Lavender Puff × Tropic Sea), Neelima (Snow Princess × Tropic Sea), Arka Naveen (74-39-1 × Tropic Sea), Pusa Sringarika (Mayur × Heady Wine) and Pusa Urmi (Berlew × Heady Wine) in cluster II might be attributed to owing to their common male parentage during crossing. Similarly, Punjab Morning (Sancerre × White Prosperity) and Anjali (Sancerre × Rose Spire) were placed close together with female parent ‘Sancerre’. Malaviya Shatabdi, an induced mutant of Punjab Dawn was also present in this cluster. Kalima and Pusa Suhagin were open pollinated seedlings of Sylvia and found related to each other in this cluster. Even though Pusa Srijana and Pusa Urmi had common parentage i.e., Berlew × Heady Wine, however, their presence in cluster I and II, respectively might be due to chance similarity in their parentage at genotypic level. Few genotypes could not share any common parentage were also grouped together in both the clusters because of greater degree of similarity in genetic constitution of ancestors. It was also suggested that chloroplast SSRs or EST derived SSRs may not differentiate the related species and cultivars due to conserved genome or positions within genic regions in the genome of ancestors. However, pedigree information was not available for some of the genotypes as it is essential for comparative analysis with SSR profiles. In general, our results were more consistent with clustering pattern obtained based on AFLP [36], RAPD [31] and ISSR [4] data. In a similar study, Singh et al analyzed phylogenetic relationship among gladiolus cultivars using sequenced chloroplast DNA regions [42].