DNA Fingerprinting and Genetic Diversity Analysis in Advanced Clones of Sugarcane (Saccharum sp. complex) Using STMS MarkersAbstract
The objective of this study was to analyze genetic diversity between nine advanced sugarcane clones and five commercial cultivars using 15 STMS markers. Out of these markers, three were genomic-SSR, eleven were EST-SSR, and one marker (NKS69) was recommended by ICAR-Sugarcane Breeding Institute (SBI) for molecular profiling of sugarcane clones. All the molecular markers exhibited distinct bands, that could be utilized for the identification of different varieties based on their presence or absence. The PIC values among these markers ranged from 0.60 to 0.92. The marker NKS9 displayed the highest PIC value of 0.92, closely followed by NKS17 with a value of 0.91. Additionally, markers NKS6, NKS11, NKS17, and NKS34 showed the highest percentage of polymorphic bands, reaching 100%. As per the analysis of genetic diversity, the similarity coefficients ranged from 0.43 to 0.96, indicating significant genetic variability among the clones. When the similarity coefficient was 0.64, the clones were categorized into two main clusters. Notably, the sister lines CoPant 12226 and CoPant 13224 exhibited the highest similarity coefficient of 0.96, placing them in the same cluster. The greatest genetic diversity, with a similarity coefficient of 0.43, was observed between CoPant 12226 and Co 05011, as well as between CoPant 16222 and CoPant 17224. In view of the above, the DNA fingerprinting of these advanced clones during the present investigation proves to be valuable for plant variety protection, and the identified diverse clones can be utilized in future breeding programs.
Keywords:
Sugarcane; DNA fingerprinting; Genetic diversity; STMS; Molecular marker
HIGHLIGHTS
The highest PIC value for marker NKS9 followed by for NKS17
Highest genetic similarity between CoPant 12226 and CoPant 13224
Highest genetic diversity between CoPant 12226 and Co 05011, and between CoPant 16222 and CoPant 17224
INTRODUCTION
Sugarcane (Saccharum sp. complex) is one of the major industrial crops grown globally in tropical and subtropical regions. It has been used as a source of sweetener for centuries, with byproducts such as molasses and bagasse used in ethanol production and the paper industry, respectively. Sugarcane is categorized under the genus Saccharum and the family Poaceae. It predominantly consists of hybrids derived from a combination of S. officinarum, S. spontaneum, and S. barberi. As a result of this multi-species ancestry, sugarcane exhibits extensive size, intricate polyploidy, and varying numbers of somatic chromosomes, contributing to its genetic complexity [25, 31]. As a result, sugarcane has received little attention in genetic studies compared to other diploid crops [18]. Additionally, the restricted use of a small number of parental clones in the genetic composition of contemporary cultivars has led to a narrow genetic base, leading to deaccelerated developments in new sugarcane clones [31]. Hence, it is imperative to incorporate germplasm that possesses substantial genetic variability, particularly in relation to important agronomic traits. This approach is vital for widening genetic base of sugarcane [1].
Presently, the identification of sugarcane varieties is based on morpho-molecular descriptors involve observation on morphological characteristics and genotyping through DNA fingerprinting [22]. However, phenotypic traits are often influenced by various environmental and geographical factors, making a strong molecular base is essential for cultivar identification, intellectual property rights protection, paternity testing of released varieties, germplasm conservation, and early plantlet evaluation [16, 34, 21, 30]. In view of this, molecular markers have arisen as effective tools for accurate identification of germplasm lines, conservation and management under various environmental conditions [33, 21]. There are numerous different types of molecular markers available today, among these microsatellites or simple sequence repeat (SSR) markers are used extensively due to their reproducibility, relative abundance, ability to exhibit multiple alleles, co-dominant inheritance, and suitability for Comprehensive genotyping in sugarcane and grasses [35]. As a result of their exceptional specificity, sequence-tagged microsatellite markers (STMS) are capable of distinguishing the closely related germplasm lines [22].
Given that the creation and utilization of new breeding materials can expedite sugarcane improvement, we employed 15 sugarcane-specific STMS markers for molecular profiling and to estimate the genetic divergence within genotypes and combinations. Out of the fifteen STMS markers used during the present investigation, three of which were EST-SSR, and eleven were genomic-SSR [20, 28] one additional marker was recommended by ICAR-SBI. EST-SSR markers were linked to a diverse array of gene functions, including transmembrane glycoprotein (NKS1), cytochrome P450 (NKS2) [7], and acid invertase (NKS3) [8]. Various researchers have constructed the molecular profile of different sugarcane genotypes using both genomic SSR and EST SSR markers [41, 28, 24, 42]. Because the EST-SSR markers were functional and with low level of polymorphism, it was thought that the genetic variability they showed was promising. However, when it comes to tasks such as DNA fingerprinting, assessing genetic diversity, choosing real hybrids, and identifying variety-specific markers, SSR markers prove to be more valuable due to their pronounced polymorphism and lower genetic similarity values. It has been demonstrated in some previous researches that the markers used in this study are efficient for carrying out genetic diversity analysis and DNA fingerprinting in sugarcane [20]. Microsatellites have emerged as the preferred marker type, and the outcomes of microsatellite analysis in sugarcane underscore the significance of this marker system in characterizing sugarcane clones [15, 17, 29]. The diverse clones identified through genetic analysis may be used for broadening the genetic base of sugarcane by using these clones in hybridization programme.
MATERIAL AND METHODS
Plant material
The plant material comprised of nine advanced generation clones of sugarcane and five commercial cultivars i.e. Co 0238 (S1), CoPant 12221 (S2), CoPant 16221 (S3), CoJ 64 (S4), CoPant 17221 (S5), CoPant 97222 (S6), CoPant 12226 (S7), CoPant 13224 (S8), CoPant 16222 (S9), CoS 767 (S10), CoPant 16223 (S11), CoPant 17224 (S12), CoPant 17223 (S13) and Co 05011 (S14). The nine advanced clones, namely S2, S3, S5, S7, S8, S9, S11, S12, and S13, were derived from a selection process conducted at G.B. Pant University of Agriculture & Technology, Pantnagar. These selections were made in progenies derived from crossing or selfing of parental lines (Table 1). Hybridization work took place at the National Hybridization Garden of the Sugarcane Breeding Institute in Coimbatore.
DNA extraction and quality check
Genomic DNA was obtained from 2 g of young leaves of all fourteen sugarcane clones. To preserve the samples, they were instantly frozen in liquid nitrogen and afterward disrupted using a mortar and pestle. The DNA extraction procedure followed the Cetyltrimethyl ammonium bromide (CTAB) method, which was described by Doyle and Doyle in 1990 [13], with minor modifications. The isolated DNA was purified followed by RNase treatment and phenol:chloroform extraction. The quality check of purified DNA was performed through electrophoresis. Following electrophoresis, the purified genomic DNA was subjected to quantification by measuring UV absorbance at 260nm using a UV spectrophotometer (Eppendrof, BioPhotometer®D30).
Molecular characterization and Data analysis
For the molecular characterization of the aforementioned sugarcane clones, 15 STMS markers were employed (Supplementary Table 1). The reaction mixture of 20 μl, consisted of a final concentration of 50 ng/µl template DNA, 20 ng/µl each of forward and reverse primers, 1 unit Taq polymerase, 10X Reaction buffer, and 100 mM dNTPs mix. The PCR procedure comprised of three main steps. Firstly, an initial heating step where the reaction mix was exposed to 94°C for five minutes. Thereafter the second step involved a standard cycling profile, which included 36 cycles. Each cycle consisted of denaturation at 94°C for one minute, annealing at a specific temperature tailored to each primer (ranging from 53.4-64°C) for one minute, and extension at 72°C for one minute. Upon completion of these cycles, the third and final step was a prolonged extension phase at 72°C for seven minutes, ensuring complete extension of all DNA fragments. For the visualization of PCR products, 8% non-denaturing polyacrylamide gels were employed and ran them in a vertical electrophoresis apparatus (CBS Scientific). Following electrophoresis, the gels were stained with a solution of Ethidium bromide (0.5 µg/ml). To estimate the size of the amplified DNA fragments, a comparison was made with a 100bp DNA ladder. The DNA bands were visualized using an UV trans-illuminator, and a photograph of the gel was captured using a gel documentation unit.
The amplified bands were assessed for their presence (1) or absence (0) in all the fourteen sugarcane clones. Subsequently, the data were employed to compute the Jaccard’s similarity coefficient (JSCs) utilizing NTSYS-pc software (Version 2.0) [26] for genetic diversity analysis. To perform this analysis, the SIMQUAL program utilized Jaccard's coefficient (1908). The pairwise Jaccard index was determined using the formula: GSxy = Nxy / [Nx + Ny + Nxy], where Nxy represents the total number of bands shared between lines x and y, and Nx and Ny are the counts of bands unique to x and y, respectively. These similarity coefficients were then utilized to construct a dendrogram through the un-weighted pair group method with arithmetic average (UPGMA) using the NTSYS program. To calculate the polymorphic information content (PIC), the following formula was used: PIC = 1 - ΣPij 2 [6], where Pij signifies the frequency of the jth allele of the ith locus summed across all alleles for the locus.
RESULTS AND DISCUSSION
Sugarcane cultivars of modern times exhibit a sizable genome, with a 2C value of 11pg DNA, approximately equal to 10,000 Mbp [11]. The analysis of this extensive genome, employing reliable marker systems, has unveiled substantial allelic diversity, facilitating the discrimination of genotypes. DNA-based markers are widely acknowledged as highly versatile tools for investigating genetic phenomena. To effectively utilize the existing genetic resources and develop promising cultivars, it is essential to comprehend genetic divergence as a fundamental requirement [23]. An accurate assessment of genetic diversity is vital as it enables populations and species to adapt and thrive in response to changing environments over evolutionary periods. Molecular markers provide a means to analyze the various alleles at different gene loci, allowing for the estimation of genetic variability within a population [37]. This approach serves as a valuable tool for evaluating and understanding genetic variation. In this study, the genetic diversity and DNA fingerprinting of 14 sugarcane clones were investigated using both genomic and EST-based STMS markers. The molecular profiles of these clones were generated using these markers, Figure 1 displays the profiles obtained with NKS3 (M3), NKS8 (M5), NKS31 (M10), NKS48 (M13), NKS57 (M14), and NKS69 (M15) markers. The detection of multiple alleles using these SSR markers can be explained by the factors like, polyploidy, aneuploidy, and the large genome size of sugarcane [32]. The presence of multiple bands per marker validates the suitability of these markers for evaluating genetic diversity [31, 19, 41, 28, 24, 42].
DNA fingerprinting
The count of discernible bands varied between 4 in NKS24 to 15 in NKS2 and NKS9 with a total of 143 bands amplified from 15 markers of which 111 were polymorphic accounting to 77.62%. This reflects the genetic complexity and polyploid nature of the sugarcane genome. The amplified fragment varied in size, ranging from 102bp (NKS57) to 725bp (NKS1). The lowest range of fragment size was found in NKS24 (151bp to 192bp), while widest range was found in NKS1 (221bp to 725bp). The highest percentage of polymorphic bands was observed with the markers NKS6, NKS11, NKS17 and NKS34 (100%), whereas the lowest percentage was found with NKS1 and NKS69 (50%). Compared to genomic SSRs, EST-SSR markers are typically moderately polymorphic due to the higher specificity of DNA sequences in transcribed regions ([14], [24]). So, in the present finding, it was observed that EST-SSR markers (NKS1, NKS2 and NKS3) showed lesser polymorphic percent in comparison to the rest of the genomic-SSR markers.
The PIC value is the discriminating power of the primer used i.e. it describes the capacity of a primer to express polymorphism. In other words, PIC values indicated the effective number of alleles that can be detected per primer in a set of individuals [2]. The PIC values among the markers varied from 0.60 to 0.92, with a mean of 0.79. The highest PIC value of 0.92 was observed for the most informative marker NKS9 followed by NKS17 (0.91), while NKS38 was found to be the least informative marker with the lowest PIC value (0.60) (Table 2). Significant variation in PIC values, spanning from 0.12 [36] to 0.96 [12], has been reported, and this variability is contingent on the specific SSRs used and the genetic characteristics of the studied genotypes.
In research conducted by You and coauthors, in 2016 [41], which encompassed 181 sugarcane clones and utilized 15 SSR markers, they reported remarkably elevated PIC values of 0.94 (for genomic SSR) and 0.93 (for EST-SSR). Singh and coauthors (2019) [35] reported a PIC value of 1.00 by using the EST-SSR marker for DNA fingerprinting in elite Indian sugarcane varieties. Higher PIC values of the SSR markers lead to a greater possibility of identifying genetic variance [9]. Although, PIC values may differ in various test populations, they are helpful in determining the practicality of a molecular marker [4]. The present study employed 15 STMS primer pairs, revealing high PIC values, distinctive fragments and successful recognition of genetic differences in the 14 sugarcane clones.
The 128bp-sized DNA fragment of NKS6 identified the clones CoPant 12226 and CoPant 13224. While, 224bp fragment of NKS9 identified the clones CoPant 17221 and CoPant 97222. The 172bp DNA fragment of NKS11 was specifically present in CoPant 12221, while the 213bp fragment of this marker distinguished the clones CoPant 12221 and Co 05011. The NKS17 (206bp fragment) marker identified CoPant 97222 and CoPant 17223. The 257bp DNA fragment of NKS31 identified the clones CoPant 17224 and Co 05011. NKS38 amplified fragment of 212bp found only in CoJ64. 240bp DNA fragment of this marker was found in Co 0238 and CoPant 17221. A 165bp amplified fragment of NKS48 was uniquely present in CoPant 16222. The different sizes of bands obtained by the STMS markers used in sugarcane genotyping reported by Hemaprabha and Simon (2012) [19], Arora and coauthors (2018) [5], Sarath Padmanabhan and Hemaprabha (2018) [28], Parthiban and coauthors (2018) [24], and Appunu and coauthors (2020) [3] are also comparable.
Representative molecular profiles of fourteen sugarcane clones for NKS3 (A), NKS8 (B), NKS31 (C), NKS48 (D), NKS57 (E) and NKS69 (F) STMS markers. = Co238, 2= CoPant12221, 3= CoPant16221, 4= CoJ64, 5= CoPant17221, 6= CoPant97222, 7= CoPant12226, 8= CoPant13224, 9= CoPant16222, 10= CoS767, 11= CoPant16223, 12= CoPant17224, 13= CoPant17223 and 14=Co5011
The absence of 196bp band of NKS3 identified the clones CoPant 16223 and Co 05011. The 220bp fragment of NKS17 identified the clones CoJ 64 and CoPant 16223 by their absence. Similarly, 192bp fragment of NKS69 identified the clones CoPant 16223 and Co 05011 due to their absence. The absence of markers could be explained by the possibility of null alleles, which fail to amplify due to primer site variation and tend to occur in large populations due to high mutation rates [10]. The clonal propagation and polyploidy of sugarcane, an ancient crop, retain all genetic changes over generation, but null alleles can result in failed amplification and mimic homozygous individuals. This could explain the absence of band in some genotypes and may be useful for clonal identification and hybridity analysis. Sarath Padmanabhan and Hemaprabha (2018) [28] also performed genotype identification based on the absence of a band.
DNA fingerprinting is a reliable method for accurately identifying and maintaining plant varieties, ensuring their authenticity and conserving and utilizing germplasm. It can also assist in quality assurance for the release of new varieties [36, 33]. Molecular characterization using DNA profiling is useful in various applications like DUS testing, variety registration, and settling disputes [21]. It is also beneficial for breeding as it aids in identifying duplicates in germplasm collections and selecting parents for hybridization programmes leading to better breeding outcome [27]. In particular, polymorphic microsatellites can generate unique molecular profiles that assist in the identification of individual genotypes and facilitate the protection of new sugarcane varieties [21, 38, 30]. Hence, DNA fingerprinting proves to be a valuable tool in both establishment and protection of newly developed plant varieties across diverse breeding programs.
Genetic diversity
Determining true genetic dissimilarity between genotypes is an important and decisive point for clustering and analyzing diversity within the population. For this purpose, the genetic similarity matrix between fourteen sugarcane clones was generated by calculating Jaccard’s similarity coefficients using a data set of 15 STMS markers (Table 3). This similarity coefficient ranged from 0.43 to 0.96, with an average of 0.54. It indicated that variability is present among the studied clones. The highest similarity (0.96) was found between CoPant 12226 and CoPant 13224 followed by 0.63 between CoPant 12221 and CoPant 13224 studied clones. The highest similarity (0.96) was found between CoPant 12226 and CoPant 13224, followed by 0.63 between CoPant 12221 and Co Pant13224. Whereas, highest variability (0.43 similarity coefficient) was found between CoPant 12226 and Co 05011, CoPant 16222 and CoPant 17224 (0.43) followed by among the clones CoPant 97222 and Co 05011 (0.44). The highest similarity among CoPant 12226 and CoPant 13224 may be due to the common parentage of these two clones; they are progeny of the cross Co 1158 x CoPant 90223. The clone CoPant 17224 was the general cross of CoPant 97222; CoPant 17224 and CoPant 97222 exhibited a similarity coefficient of 0.57. Ali and coauthors (2017) [2] similarly studied the genetic diversity among 91 Chinese sugarcane varieties and identified the pair-wise similarity coefficients as ranging from 0.58 to 0.95. [24] examined diversity in 59 sugarcane accessions using SSR and EST-SSR markers and found a 0.70 mean genetic similarity value using EST-SSR and 0.63 using genomic SSR. In addition, Zeni Neto and coauthors (2020) [42] conducted a genetic diversity analysis among sugarcane accessions and revealed that the similarity coefficient ranged from 0.47 to 0.95.
Cluster analysis of these 14 sugarcane clones was carried out based on the genetic similarity matrix generated from the genotypic data by 15 STMS markers and a dendrogram was constructed (Figure 2). The separation distance between two clusters serves as a measure of the extent of diversification. A larger distance between two clusters indicates a higher degree of divergence, while a smaller distance suggests greater similarity. In simpler terms, clones grouped within a single cluster are less dissimilar than those distributed across distinct clusters. When a similarity coefficient of 0.64 was selected as a value for classification, the clones were categorized into two primary clusters. Cluster I consisted of the three clones namely Co 0238, CoPant 17221 and CoPant 16222 with similarity coefficient 0.50 to 0.61 while cluster II consisted of rest of the eleven genotypes. The cluster II was divided into two subgroups, the first of which included seven genotypes with genetic similarity coefficients ranging from 0.52 to 0.96: CoPant 12221, CoPant 17224, CoPant 12226, CoPant 13224, CoS 767, CoPant 16221 and CoJ 64. While second subgroup of cluster II consist of four genotypes viz. CoPant 97222, CoPant 17223, CoPant 16223 and Co 05011 with similarity coefficient 0.44 to 0.57. The clustering of sugarcane genotypes based on similarity coefficient was also carried out by Ali and coauthors (2017) [2], Parthiban and coauthors (2018) [24], Zeni Neto and coauthors (2020) [42], Wang and coauthors [39] and Xiong and coauthors (2022) [40]. Finally, it can be concluded that the extensive diversity observed in the analyzed sugarcane clones can be attributed to the genetic enhancement program that relies on clustering patterns. This finding also lends support to the process of selecting cross-combinations from parental genotypes and expanding the genetic foundation of breeding initiatives.
Pair wise genetic similarity matrix between 14 sugarcane clones based on Jaccard’s similarity coefficients
Dendrogram showing genetic relationship among 14 sugarcane clones. Dendrogram is based on 15 polymorphic STMS markers. The scale indicates Jaccard’s similarity coefficient.
CONCLUSIONS
In this particular study, clones were distinguished based on the presence or absence of distinct genetic markers. The markers NKS6, NKS11, NKS17, and NKS34 exhibited the highest percentage of variable genetic markers, indicating significant genetic variation. Notably, the marker NKS9 displayed the highest Polymorphic Information Content (PIC) value, closely followed by NKS17. The utilization of these molecular profiles can greatly aid in accurate identification of plant varieties, ensuring proper plant variety protection and purity testing. When assessing genetic diversity, the clones CoPant 12226 and Co 05011, as well as CoPant 16222 and CoPant 17224, demonstrated the lowest similarity coefficient. This implies that they possess the greatest genetic dissimilarity and exhibit maximum diversity among the studied clones. These diverse clones hold promising potential for utilization in sugarcane hybridization and can effectively contribute to broadening the genetic foundation of breeding programs. In summary, the identification of clones based on unique genetic markers, the discovery of high levels of genetic variability using specific markers, and the generation of molecular profiles all play crucial roles in facilitating accurate identification of plant varieties for protection and purity testing. Additionally, the identification of genetically diverse clones provides valuable opportunities for their utilization in sugarcane hybridization and the expansion of genetic resources in future breeding programs.
Acknowledgements
The authors are thankful to Director, Experiment Station, GBPUAT, Pantnagar for providing the facilities to undertake the present study. Thanks are due to Department of Genetics and Plant Breeding (GPB) and Department of Molecular biology and Genetic Engineering (MBGE) for providing the lab and computational facilities. DC is highly grateful to Council of Scientific and Industrial Research (CSIR) for providing research fellowship.
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