Study of genetic diversity of sugarcane (Saccharum) species and commercial varieties through TRAP molecular markers

Modern Biotechnologies: Innovative and Sustainable Approaches for the Improvement of Sugarcane Tolerance to Environmental Stresses

Sugarcane (Saccharum spp.) is one of the most important industrial cash crops, contributing to the world sugar industry and biofuel production. It has been cultivated and improved from prehistoric times through natural selection and conventional breeding and, more recently, using the modern tools of genetic engineering and biotechnology. However, the heterogenicity, complex poly-aneuploid genome and susceptibility of sugarcane to different biotic and abiotic stresses represent impediments that require us to pay greater attention to the improvement of the sugarcane crop. Compared to traditional breeding, recent advances in breeding technologies (molecular marker-assisted breeding, sugarcane transformation, genome-editing and multiple omics technologies) can potentially improve sugarcane, especially against environmental stressors. This article will focus on efficient modern breeding technologies, which provide crucial clues for the engineering of sugarcane cultivars resistant to environmental stresses.

Suitability of target region amplified polymorphism (TRAP) markers to discern genetic variability in sweet sorghum

Background

Sweet sorghum is an emerging biofuel candidate crop with multiple benefits as a source of biomass energy. Increase of biomass and sugar productivity and quality is a central goal in its improvement. Target region amplified polymorphism (TRAP) is a polymerase chain reaction (PCR) based functional marker system that can detect genetic diversity in the functional region of target genes. Thirty sweet sorghum genotypes were used to study the potential of 24 pairs of TRAP marker system in assessing genetic diversity with regard to three lignin and three sucrose biosynthesis genes.

Results

A total of 1638 bands were produced out of which 1161 (70.88%) were polymorphic at least at one locus. The average polymorphic information content (PIC), resolving power (RP), marker index (MI), Shannon’s diversity index (H), and gene diversity values were 0.32, 8.86, 1.74, 3.25, and 0.329, respectively. Analysis of molecular variance (AMOVA) revealed a highly significant genetic variation both within and among accessions studied (P = 0.01). However, the variation within the population was higher than among the populations (accessions). Bootstrap analysis showed that the number of loci amplified using this marker system is sufficient to estimate the available genetic diversity. The thirty genotypes were categorized into five clusters using a similarity matrix at 0.72 coefficient of similarity. The genotypes were also grouped mostly according to their geographic origin where the Ethiopian and Egyptian genotypes tend to fall in specific clusters. Moreover, the genotypes reflected the same pattern of distribution when ordinated using principal coordinate analysis.

Conclusions

In conclusion, TRAP marker can be used as a powerful tool to study genetic diversity in sweet sorghum.

Genetic divergence in Tunisian castor bean genotypes based on trap markers

In the present study, the representatives of the genus Ricinus communis collected from 12 different parts of Tunisia were differentiated by the DNA fingerprinting patterns using 30 TRAP primers. The efficacy of the TRAP technique in this study is further supported by the obtained PIC values of the primers used in the analysis. PCR amplification of DNA using 30 primers for TRAP analysis produced 490 DNA fragments that could be scored in all 56 genotypes of Tunisian castor. The number of amplified fragments varied from 3 (TRAP 04 x arb 1, TRAP 22 x arb 3 and TRAP 23 x arb 3) to 13 (TRAP 56 x arb 2), and the amplicon size ranged from 100 to 1600 bp. Of the 490 amplified bands, 377 were polymorphic, with an average of 5.71 polymorphic bands per primer. To determine the level of polymorphism in the analysed group of Tunisian castor genotypes polymorphic information content (PIC) was calculated. The lowest values of polymorphic information content were recorded for TRAP 10 x arb 1 (0.555) and the highest PIC values were detected for TRAP 44 x arb 2 (0.961) with an average of 0.770. A dendrogram was constructed from a genetic distance matrix based on profiles of the 30 TRAP primers using the unweighted pair-group method with the arithmetic average (UPGMA). According to analysis, the collection of 56 Tunisian castor genotypes were clustered into five main clusters. Moreover, functional TRAP markers would be efficiently useful in genetic studies for castor genetic improvement.

Assessing genetic diversity and population structure of sugarcane cultivars, progenitor species and genera using microsatellite (SSR) markers

Sugarcane is one among the most important commercial crops used to produce sugar, ethanol, and other byproducts, which significantly contributes in the GDP of India and many other countries around the world. Genetic diversity is a platform for any breeding program of a plant species. Estimation of the genetic variability and population structure play a vital role for conservation planning and management of plant genetic resources. Genetic variability serves as a source of noble alleles responsible for key agronomic and quality traits, which ultimately form basis for identification and selection of promising parents for breeding programs. In the present study genetic diversity and population structure of 139 accessions of the genus Saccharum, allied genera of family Poaceae and cultivars were assessed using informative microsatellite (SSR) markers. A sum of 427 alleles was produced using 61 polymorphic primers and number of alleles generated was ranged from 2 to 13 with an average of 7 alleles per locus. PIC values were ranged from 0.35 to 0.90, with a mean value of 0.66 for all the markers evaluated. Cluster analysis based on UPGMA method revealed three major clusters which were further subdivided into nine subclusters. Population structure analysis also established three subpopulations of used accession set, however there were no correlation of sub-groupings with that of place of origin. AMOVA analysis also confirmed that 83% and 17% of total variations were attributed to the within- and between-populations, correspondingly, demonstrating greater exchange of gene pool across places of origin. The principal component analysis (PCA) demonstrated the distribution of accessions in the scatter-plot was substantially dispersed, revealing rich genetic diversity among accessions of different species. The findings from this study will be useful in breeding programs for introgression of noble alleles into modern cultivars by exploiting natural genetic variation existing in sugarcane genetic resources.

Molecular diversity and genetic structure of Saccharum complex accessions

Sugarcane is an important crop for food and energy security, providing sucrose and bioethanol from sugar content and bioelectricity from lignocellulosic bagasse. In order to evaluate the diversity and genetic structure of the Brazilian Panel of Sugarcane Genotypes (BPSG), a core collection composed by 254 accessions of the Saccharum complex, eight TRAP markers anchored in sucrose and lignin metabolism genes were evaluated. A total of 584 polymorphic fragments were identified and used to investigate the genetic structure of BPSG through analysis of molecular variance (AMOVA), principal components analysis (PCA), a Bayesian method using STRUCTURE software, genetic dissimilarity and phylogenetic tree. AMOVA showed a moderate genetic differentiation between ancestors and improved accessions, 0.14, and the molecular variance was higher within populations than among populations, with values of 86%, 95% and 97% when constrasting improved with ancestors, foreign with ancestors and improved with foreign, respectively. The PCA approach suggests clustering in according with evolutionary and Brazilian breeding sugarcane history, since improved accessions from older generations were positioned closer to ancestors than improved accessions from recent generations. This result was also confirmed by STRUCTURE analysis and phylogenetic tree. The Bayesian method was able to separate ancestors of the improved accessions while the phylogenetic tree showed clusters considering the family relatedness within three major clades; the first being composed mainly by ancestors and the other two mainly by improved accessions. This work can contribute to better management of the crosses considering functional regions of the sugarcane genome.