Integrating Molecular and Phenotypic Approaches to Assess Genetic Diversity in Heliconia Genotypes

doi:10.21203/rs.3.rs-5282628/v1

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Integrating Molecular and Phenotypic Approaches to Assess Genetic Diversity in Heliconia Genotypes

https://doi.org/10.21203/rs.3.rs-5282628/v1

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The genus Heliconia exhibits remarkable diversity, particularly in the morphological traits of its plants. Notable variations in the color and size of inflorescence bracts, along with differences in flower type and size, are key markers for distinguishing species and genotypes. This extensive morphological diversity, observed at both interspecies and intraspecific levels, prompted the present study, which aims to assess genetic variability among 28 Heliconiagenotypes using molecular markers. We employed Sequence-Related Amplified Polymorphism (SRAP) and Inter-Simple Sequence Repeat (ISSR) markers to analyze genetic diversity. The Jaccard similarity coefficient indicated considerable genetic variation among the genotypes, with pairwise values ranging from 0.302 to 0.943, leading to the clustering of the genotypes into two major groups at a similarity coefficient of 0.59. Furthermore, multifactorial analysis (MFA) was conducted on agro-morphological traits, revealing leaf morphology and plant height as the most significant contributors to phenotypic variation. Hierarchical cluster analysis based on phenotypic data also divided the genotypes into two main clusters, corresponding to the groupings identified by molecular data. These findings highlight the value of integrating molecular and phenotypic analyses to comprehensively evaluate genetic diversity and characterize Heliconia populations. This approach not only aids in the conservation and management of Heliconia genetic resources but also supports future breeding programs aimed at developing improved cultivars with desirable ornamental and commercial traits.

Genetic diversity

Heliconia

hierarchical cluster analysis

SRAP

multifactorial analysis

Phylogenetic relationship

Polymorphism

ISSR

The genus Heliconia has garnered considerable horticultural interest due to its striking inflorescences. Initially misclassified as banana species due to their similar foliage, Heliconia was established as a distinct genus by Linnaeus in 1771. The name originates from the Greek term "helikonios," referencing Mount Helicon, a site associated with Apollo and the muses. Heliconia derives its name from the flower’s enduring beauty and ornamental appeal. Belonging to the family Heliconiaceae, these plants are native to South and Central America and the islands of the South Pacific, with approximately 250-300 species distributed primarily across the Neotropics, from northern Mexico to southern Brazil (Malakar & Biswas, 2022; Malakar et al., 2019). Commonly referred to as "wild bananas" or "false birds of paradise," Heliconia species are renowned for their exotic appearance, making them highly valued in tropical gardens and floral arrangements.

Heliconia species are perennial plants characterized by rhizomatous roots and an upright, sympodial growth habit. They form pseudostems composed of tightly clustered petioles and leaf sheaths, and their height varies from 1 to 7 meters depending on the species. The leaves are arranged in two opposite rows with elongated basal sheaths and petioles (Cronquist, 1981). The inflorescences, either upright or pendulous, consist of colorful bracts arranged in single planes or spirals, each enclosing clusters of flowers. These bracts display variation in shape, size, arrangement, color, texture, and number, traits often used to classify subgenera within the genus (Cronquist, 1981; Berry & Kress, 1991; Andersson, 1992). Heliconia is widely appreciated for its exceptional cut flowers, distinguished by their unique shapes, vivid colors, long-lasting vase life, and abundant flower production. Significant morphological diversity is observed within and between species, populations, and varieties (Janakiraman & Kumar, 2011).

The genus Heliconia includes a wide range of species, varieties, hybrids, and cultivars of both ornamental and commercial importance. However, uncertainty persists regarding the exact number of species and their relationships, highlighting the need for molecular studies to elucidate the genetic variability and speciation processes within the genus (Marouelli et al., 2010). Despite their horticultural appeal and favorable postharvest characteristics, much remains unknown about the genetics of these plants, emphasizing the necessity for precise species and cultivar identification. Heliconia's diverse colors and forms offer great potential in the commercial cut flower market, with their vibrant hues, exotic shapes, long peduncles, and robust postharvest traits (Malakar, 2020). Nevertheless, substantial morphological variation within and among species, influenced by factors such as geographic isolation, environmental conditions, and nutrient availability, has led to confusion among both enthusiasts and commercial growers. As the genus garners increasing attention from taxonomists and horticulturists, the need for reliable identification methods becomes crucial, with color photographs of inflorescences currently serving as the most practical tool (Thangam et al., 2016).

Molecular markers based on polymerase chain reaction (PCR) with nonspecific primers have gained popularity due to their utility in species lacking prior sequence information. These markers have proven valuable for research involving genetically uncharacterized species, offering a large array of potential markers. In ornamental plants, DNA markers have been widely used to identify genotypes and analyze genetic diversity. Molecular techniques such as Amplified Fragment Length Polymorphism (AFLP) (Isaza et al., 2012), Random Amplified Polymorphic DNA (RAPD) (Thangam et al., 2016; Marouelli et al., 2010; Sheela et al., 2006), and Inter-Simple Sequence Repeat (ISSR) markers (Pereira et al., 2016) have been applied to study the genetic diversity of Heliconia. These methods offer valuable insights into the genetic structure and variability of ornamental plant species like Heliconia.

Both ISSR and Sequence-Related Amplified Polymorphism (SRAP) markers are PCR-based dominant markers extensively used in genetic diversity studies. ISSRs, which target regions between simple sequence repeats (SSR), are known for their simplicity, rapidity, cost-effectiveness, and high reproducibility. They are widely used to assess genetic diversity, examine cultivar relationships, and explore evolutionary processes (Liao et al., 2012; Liu et al., 2013). SRAP markers, introduced by Li and Quiros (2001), have become valuable tools in plant genetic research due to their simplicity, reproducibility, and informativeness. SRAP markers target open reading frames (ORFs), amplifying exonic regions using a forward primer and noncoding regions with a reverse primer. These markers have been successfully used to investigate genetic diversity and relationships in various plant species (Budak et al., 2004). SRAP markers are particularly useful for species with limited genomic information and can facilitate hybridization programs and the development of variety-specific markers for identification purposes. This study marks the first application of SRAP markers in analyzing genetic variation in Heliconia.

Previous research has combined botanical, morphological, and agronomic assessments of Heliconia germplasm, providing valuable insights into the genetic and phenotypic diversity of this genus (Criley, 1999; Castro et al., 2006, 2007; Loges et al., 2006; Costa et al., 2007 I, II; Rocha et al., 2010). The objective of the present study is to evaluate the genetic divergence among Heliconia accessions by integrating agro-morphological traits and molecular markers (ISSR and SRAP).

Plant materials:

Twenty-eight genotypes of Heliconia, representing the majority of those cultivated under the agro-climatic conditions of Maharashtra, were collected from the Heliconia germplasm block at ICAR-DFR, Pune, and used as experimental material for this study (Table 1). These genotypes were analyzed using morphological traits, and reproducible polymorphic primer combinations were selected for further genetic polymorphism analysis (Table 2).

DNA extraction:

Genomic DNA was extracted from leaf samples using a modified CTAB-based method as described by Doyle and Doyle (1987). DNA quality was evaluated via electrophoresis on 0.8% agarose gels stained with ethidium bromide (EtBr), while DNA quantity was measured using a Nanodrop spectrophotometer (Thermo Scientific). The extracted genomic DNA was stored at -20ºC for future use.

PCR amplification of SRAP and ISSR markers:

For SRAP-PCR amplification, the reaction mixture contained 20-40 ng of template DNA, 0.05–1 μM of primer, 2.5 mM MgCl₂, 200 μM of each dNTP, 1.0 U of Taq DNA polymerase, and 1× assay buffer, in a final volume of 20 µL. The thermal cycling program included an initial denaturation at 94°C for 4 min, followed by 10 cycles of 94°C for 1 min, 35°C for 1 min, and 72°C for 1 min. This was followed by 30 cycles at 94°C for 1 min, 50°C for 1 min, and 72°C for 1 min, with a final extension at 72°C for 5 min (Liu et al. 2012).

For ISSR-PCR, the reaction mixture was similar to the SRAP-PCR, with the same primer concentration, MgCl₂, dNTPs, and Taq DNA polymerase in a final volume of 20 µL. The thermal cycling program consisted of an initial denaturation at 94°C for 5 min, followed by 35 cycles at 94°C for 1 min, 50°C for 1 min, and 72°C for 2 min, with a final extension at 72°C for 10 min, and holding at 4°C indefinitely.

The PCR products from both SRAP and ISSR amplifications were separated on 2.0% agarose gels in Tris-Borate-EDTA (TBE) buffer and stained with 0.5 μg/mL ethidium bromide. Gel patterns were visualized using a Chemi Documentation System (BioZen Laboratories), and the images were recorded using GelProKEMI software.

Data analysis:

The amplified bands were scored as present (1) or absent (0), and binary data were subjected to analysis using NTSYS-pc version 2.02i. Pairwise genetic similarities between Heliconia genotypes were calculated using Jaccard’s similarity coefficient (Rohlf 1998), and clustering analysis was conducted using the Unweighted Pair-Group Method with Arithmetic Mean (UPGMA) to generate a dendrogram. Additionally, Polymorphism Information Content (PIC) (Botstein et al. 1980), Marker Index (MI) (Milbourne et al. 1997), and Resolving Power (Rp) (Prevost and Wilkinson 1999) were calculated.

Morphological evaluation:

The morphological evaluation of Heliconia genotypes was conducted at the ICAR-Directorate of Floricultural Research, Pune, India, from 2017 to 2020. The plants were established in a randomized block design (RBD) with three replications, with suckers of each genotype planted at a spacing of 1.5 × 1.5 meters. Standard cultural practices were followed throughout the experiment. Data were recorded for seven quantitative traits, including leaf length (cm), leaf width (cm), plant height (cm), spike length (cm), petiole length (cm), rachis length (cm), bract length (cm), bract width (cm), the number of flowering shoots per plant, the number of bracts per spike, and internodal length between florets per bract (Safeena et al. 2023). The recorded data were subjected to analysis of variance (ANOVA) to test the significance of genotypic differences (Panse and Sukhatme 1954).

Multifactorial and Cluster analysis:

Multifactorial analysis (MFA) was performed using XLSTAT statistical software (version 2023.3.1) to examine the agro-morphological differentiation and identify traits contributing to variability among the accessions (Dube et al. 2019; Gonne et al. 2013). Hierarchical cluster analysis was then conducted to group the 28 genotypes into distinct clusters based on their similarities. Pearson correlation was computed to evaluate interrelationships among the various descriptors (Pipan et al. 2023).

Molecular profiling of Heliconia genotypes using SRAP and ISSR markers

The use of SRAP and ISSR markers effectively demonstrated genetic diversity among the 28 Heliconia genotypes. Morphological analysis further corroborated these findings, underscoring the utility of both molecular and phenotypic data in assessing genetic variation.

SRAP marker analysis

Nine SRAP primer combinations were selected for their reproducibility and clarity in amplification, yielding a total of 38 alleles across the 28 Heliconia genotypes (Table 4; Fig. 1). The number of alleles per primer combination ranged from 2 to 7, with an average of 4.22 alleles per primer. Of the 38 alleles, 37 were polymorphic, resulting in a polymorphism rate of approximately 98%, highlighting the high efficacy of SRAP markers in capturing genetic variability. This level of polymorphism exceeds previously reported values, such as the 88% observed in Magnolia wufengensis (Chen et al., 2014), indicating that SRAP markers are highly informative for Heliconia species. The amplified fragment sizes ranged between 100 bp and 800 bp, suggesting that both small and large genomic regions were targeted.

The polymorphic information content (PIC) values for the SRAP markers ranged from 0.52 (SRAP m2e7) to 0.87 (SRAP m5e3), with an average of 0.74, indicating moderate to high levels of informativeness. The marker index (MI), which reflects the discriminative power of the markers, ranged from 1.56 (SRAP m2e5) to 6.14 (SRAP m5e3), with an average of 3.02. The resolving power (RP) of the primers, a measure of their ability to differentiate closely related genotypes, ranged from 15.42 (m5e3) to 39.5 (m2e7), with an average of 24.44 (Table 4). These parameters collectively suggest that SRAP markers are robust tools for distinguishing between diverse Heliconia genotypes.

ISSR marker analysis

Amplification using two ISSR primers selected from an initial screening of 25 ISSR primers yielded 15 polymorphic alleles across the 28 Heliconia genotypes, with a 100% polymorphism rate (Table 5). The polymorphic rate observed here is notably higher than the 63.64% reported by Pereira et al. (2016) for Heliconia. The allele sizes ranged from 300 bp to 800 bp, and the ISSR 811 primer generated the highest number of alleles (11), while ISSR 809 generated 4 alleles.

The PIC values for ISSR markers ranged from 0.56 (ISSR 809) to 0.85 (ISSR 811), with an average of 0.71, indicating moderate informativeness. The marker index ranged from 2.26 (ISSR 809) to 9.40 (ISSR 811), with an average of 5.83, reflecting the high discriminatory capacity of ISSR markers. The resolving power ranged from 14.90 (ISSR 811) to 38 (ISSR 809), with an average of 26.45 (Table 5), demonstrating their utility in differentiating closely related genotypes.

Comparative analysis of SRAP and ISSR markers

Despite a higher polymorphic band percentage with ISSR markers, SRAP markers exhibited a higher average PIC value (0.74) compared to ISSR (0.71), suggesting greater overall informativeness in distinguishing between Heliconia genotypes. This discrepancy may be attributed to the different genomic regions targeted by the two marker systems, with SRAP markers primarily amplifying functional regions, such as open reading frames (ORFs), and ISSR markers focusing on non-coding regions between simple sequence repeats (SSRs). These differences align with previous studies, where varying levels of marker informativeness were observed across different species and marker systems (Liu et al., 2012; Wu et al., 2014).

Pairwise Jaccard similarity coefficient values for the 28 Heliconia genotypes ranged from 0.302 to 0.943, reflecting substantial genetic variability within the species. The highest similarity (0.943) was observed between H. chartaceae ‘Temptress’ and H. angusta ‘Red Christmas’, suggesting close genetic relatedness. Conversely, the lowest similarity (0.302) was found between H. stricta ‘Lobster Claw’ and H. angusta ‘Red Christmas’, indicating significant genetic divergence (Table 6).

Cluster analysis, performed using the UPGMA method based on SRAP and ISSR marker data, revealed two main clusters (Cluster A and Cluster B) at a similarity coefficient of 59% (Fig. 2). Cluster A comprised seven genotypes, which were further subdivided into two subclusters, A1 and A2. Subcluster A1 included four genotypes: Fire Flash, Guyana 2, Golden Torch, and Alan Carle. The latter three genotypes (Golden Torch, Alan Carle, and Guyana 2) clustered closely together, sharing a common parental lineage of H. psittacorum x H. spathocircinata. In contrast, Fire Flash, which has a distinct parental background of H. densiflora, was placed further apart within this subcluster.

Subcluster A2 contained three genotypes: Temptress, Red Christmas (which shared 94% similarity), and Distans. These genotypes have diverse parental origins, including H. chartaceae, H. angusta, and H. latispatha.

Cluster B, consisting of 21 genotypes, was further divided into two subclusters, B1 and B2. Subcluster B1 was split into two groups: B1.1 and B1.2. Group B1.1 was divided into two subgroups: Group a and Group b. Within Group a, subgroups a1 and a2 were identified. Subgroup a1 contained Meccas Pink and Pedro Ortiz, which are closely related despite having different parental lineages: H. orthotricha and H. collisiana × bourgeana, respectively. Subgroup a2 included four genotypes (Tropics, Kathy, Lady Di, and Kenya Red), which are closely related, with Kathy, Lady Di, and Kenya Red sharing the common parent H. psittacorum, and Tropics being a cross of H. psittacorum x H. spathocircinata.

Group B1.2 contained two subgroups: Group b1 and Group b2. Group b1 consisted of four genotypes: Red, Jacquinii, Prince of Darkness, and Caribea, all sharing a common parental lineage of H. caribaea. Additionally, Red, Jacquinii, and Prince of Darkness share the parental cross H. caribaea x H. bihai. Group b2 comprised seven genotypes, including Ten Days, Jamaican Dwarf, and Parrot’s Beak, which are closely related and clustered with Iris and Guyana. Ten Days and Parrot’s Beak share common parents H. rostrata and H. stricta, while Jamaican Dwarf and Iris share parents H. bihai. Additionally, Dwarf and Schaefer, both sharing the common parent H. bihai, were placed together in Group B1.2.

Cluster B2 included two genotypes, Lobster Claw and Upright, which share a genetic similarity of 0.83, despite having different parental origins: H. stricta and H. rauliniana.

Implications for genetic diversity and conservation

The high levels of polymorphism and genetic diversity observed using SRAP and ISSR markers highlight the extensive genetic variability within Heliconia genotypes. This genetic diversity underscores the need for conservation efforts to preserve Heliconia genetic resources. The results of this study provide valuable insights into the genetic structure of Heliconia, which will be crucial for breeding programs aimed at enhancing the species’ genetic pool, adaptability, and resilience in changing environmental conditions.

In conclusion, both SRAP and ISSR markers have proven to be powerful tools for assessing genetic diversity and population structure in Heliconia genotypes. These findings contribute to a better understanding of the genetic resources available, facilitating the development of effective conservation and breeding strategies for the sustainable management of Heliconia species.

Patterns of agro-morphological differentiation among genotypes

To investigate the patterns of agro-morphological traits and identify the major sources of variation among Heliconia genotypes, a Multifactorial analysis (MFA) was conducted using quantitative data. Descriptive statistics, including the maximum, minimum, mean values, and standard deviations for the estimated traits, are presented in Table 7.

The correlation between variables and factors grouped the 28 genotypes into several distinct factors, with the first four factors accounting for approximately 85.02% of the total variation observed (Table 8). Factor 1 (F1) explained the largest portion of the variation, approximately 47.7%, and was primarily associated with agronomic traits such as plant height, leaf length, leaf width, and leaf petiole length. Factor 2 (F2), which explained 15% of the variation, was closely linked to rachis length, bract length, and the number of flowering shoots per plant. Factor 3 (F3), accounting for 13.2% of the variation, was predominantly influenced by bract width. The final factor, Factor 4 (F4), explained 9.2% of the variation and was mainly associated with spike length.

The MFA plot (Fig. 3) visually represents the relationships between different genotypes based on various agro-morphological attributes, including leaf length, leaf width, plant height, spike length, leaf petiole length, rachis length, bract length, bract width, flowering shoots per plant, bracts per floret per spike, and internodal length between florets per bract. Genotypes with similar traits clustered together, while those exhibiting contrasting traits were positioned further apart.

In the first and second quadrants of the MFA plot, genotypes such as Upright, Temptress, Lobster Claw, Alan Carle, Iris, H-25, H. Red, Jacquinii, Parrot’s Beak, Ten Days, Tropics, Guyana 2, Metallica, and Caribea clustered closely together. These genotypes shared common traits related to leaf morphology (length and width), plant height, leaf petiole length, bract length, rachis length, bract width, spike length, bracts per floret per spike, and internodal length between florets per bract. Notably, Lobster Claw, Alan Carle, and H-25 were closely positioned in the first quadrant, sharing attributes such as bract length, rachis length, spike length, and internodal length between florets. Additionally, H-Red and Jacquinii formed a close cluster due to similarities in bract width. In quadrant two, Ten Days and Guyana 2 were closely associated, exhibiting similarities in leaf length, leaf width, plant height, and leaf petiole length.

On the opposite side of the MFA plot, genotypes such as Guyana, Kenya Red, Lady Di, Kathy, Meccas Pink, Red Christmas, Schaefer, Golden Torch, Dwarf, Fire Flash, Jamaican Dwarf, Distans, Prince of Darkness, and Pedro Ortiz were characterized by traits related to the number of flowering shoots per plant (Fig. 3 and 4). This provided a clear visualization of the differentiation and relationships between the genotypes based on their agro-morphological attributes, revealing specific patterns of association.

To further examine agro-morphological differentiation, hierarchical cluster analysis was performed, estimating dissimilarity among genotypes using distance to centroid based on phenotypic data (Fig. 5). The dendrogram divided the genotypes into two major clusters: Cluster 1 and Cluster 2.

Cluster 1 contained 17 genotypes, including Fire Flash, Pedro Ortiz, Tropics, Distans, Temptress, Lobster Claw, Upright, H. Red, Jacquinii, Caribea, Ten Days, Parrot’s Beak, Iris, Guyana 2, H-25, Metallica, and Alan Carle. Within this cluster, Alan Carle and Guyana 2 exhibited close genetic similarity due to their shared parental lineage of H. psittacorum x H. spathocircinata. Similarly, Ten Days and Parrot’s Beak showed a close relationship, sharing the same parent (H. rostrata). Additionally, H. Red, Jacquinii, and Caribea were grouped together, sharing a common parental background of H. caribaea x H. bihai.

Cluster 2 included 11 genotypes: Meccas Pink, Guyana, Red Christmas, Kathy, Lady Di, Kenya Red, Dwarf, Schaefer, Prince of Darkness, Jamaican Dwarf, and Golden Torch. Among these, Kathy and Lady Di were closely related, having the same parental lineage of H. psittacorum. These results were consistent with molecular analysis, further supporting the relationships observed in the agro-morphological data.

The hierarchical clustering and MFA provided a detailed understanding of the agro-morphological differentiation among Heliconia genotypes. The observed groupings were largely influenced by shared parental lineages and specific trait characteristics. This analysis is crucial for guiding breeding programs and conservation efforts, as it highlights the genetic diversity and potential for selective improvement within the Heliconia genotypes studied.

This study assessed genetic divergence in Heliconia genotypes using agro-morphological traits and molecular markers (ISSR and SRAP). Both marker systems revealed high polymorphism and genetic variation, effectively uncovering genetic relationships. The analysis provided critical insights for breeding programs and conservation, facilitating the selection of diverse genotypes to enhance Heliconia populations' variability and resilience.

Key agro-morphological traits like leaf morphology and plant height significantly contributed to phenotypic variation. Multifactorial and hierarchical cluster analyses clarified genotype relationships based on these traits. The integration of molecular and phenotypic approaches is essential for characterizing genetic diversity, supporting the development of improved Heliconia cultivars.

Author contribution statement

Jagtap AY: Writing-original draftWriting-review and editing and data analysis; Jadhav PR: Methodology, Formal analysis, Writing-original draft, final editing. Safina SA: Formal analysis, Investigation, Writing-editing. Solanke AU: Conceptualization, Methodology, formal analysis. Pagariaya MC: data analysis and editing of draft. Prasad KV: Resources, Supervision. Kawar PG: Conceptualization, Methodology, Formal analysis, Writing - review and final editing; Supervision & coordination.

Acknowledgement

The authors gratefully acknowledge the DG ICAR & Secretary DARE, New Delhi, India DDG (HS) ICAR, New Delhi ADG (HS) ICAR, New Delhi India. Director, ICAR-IIHR, Bengaluru and Director, ICAR-NIPB, New Delhi India, for financial and research support. The authors whose work formed the basis for this work and anonymous reviewers for critically reviewing and suggestions are also acknowledged.

*Conflict of Interest/ Competing interests:

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

*Funding: Institute funded.

*Ethics approval: NA

*Consent to participate (include appropriate consent statements): NA
*Consent for publication (appropriate statements regarding publishing an individual’s data or image): NA
*Availability of data and material - (data transparency):

Data will be made available on reasonable request.

*Code availability - (software application or custom code): NA

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work the author(s) used chat.opeanai.com in order to proof read the contents of manuscript. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

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Tables 1 to 9 are available in the Supplementary Files section.

No competing interests reported.

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Integrating Molecular and Phenotypic Approaches to Assess Genetic Diversity in Heliconia Genotypes

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Abstract

Figures

INTRODUCTION

MATERIALS AND METHODS

RESULTS AND DISCUSSION

CONCLUSION

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1