Agricultural Science Digest

  • Chief EditorArvind kumar

  • Print ISSN 0253-150X

  • Online ISSN 0976-0547

  • NAAS Rating 5.52

  • SJR 0.156

Frequency :
Bi-monthly (February, April, June, August, October and December)
Indexing Services :
BIOSIS Preview, Biological Abstracts, Elsevier (Scopus and Embase), AGRICOLA, Google Scholar, CrossRef, CAB Abstracting Journals, Chemical Abstracts, Indian Science Abstracts, EBSCO Indexing Services, Index Copernicus
Agricultural Science Digest, volume 44 issue 1 (february 2024) : 81-87

Phenotypic Evaluation of Traits and Barcode Identification using Plastid-specific Ribulose Bisphosphate Carboxylase (Rbcl) Analysis on Lablab Beans [Lablab purpureus (L.) Sweet]

Agbolade James Oludare1,*, Idowu Jeremiah Adebare1,*, Isiaka Abiodun Ibrahim1, A. Adekoya Modinat1, Ikenna Odoh2, Adepeju Adefisola Bola3, Joseph Ivala Kioko4
1Department of Plant Science and Biotechnology, Federal University Oye-Ekiti, Ekiti State, Nigeria.
2Medical Centre, Federal University Oye-Ekiti, Ekiti State, Nigeria.
3Department of Food Science and Technology, Federal University Oye-Ekiti, Ekiti State, Nigeria.
4Department of Biodiversity and Conservation, Cape Peninsula University of Science and Technology, Cape Town, South Africa.
Cite article:- Oludare James Agbolade, Adebare Jeremiah Idowu, Ibrahim Abiodun Isiaka, Modinat Adekoya A., Odoh Ikenna, Bola Adefisola Adepeju, Kioko Ivala Joseph (2024). Phenotypic Evaluation of Traits and Barcode Identification using Plastid-specific Ribulose Bisphosphate Carboxylase (Rbcl) Analysis on Lablab Beans [Lablab purpureus (L.) Sweet] . Agricultural Science Digest. 44(1): 81-87. doi: 10.18805/ag.AF-729.
Background: The importance of grain legumes in world food sustainability cannot be overemphasized. Minor legumes on the other hand, contribute to agricultural strengthening, especially in the context of sustainable crop and livestock production systems. In the context of assessing different legume species for crop improvement and identification, twenty (20) accessions of Lablab purpureus (L.) Sweet collected to determine the degree of trait variability and to identify accessions with potentials, which can contribute to grain and forage production.

Methods: The present study involved the evaluation of twenty (20) accessions of Lablab purpureus (L.) Sweet from IITA, Ibadan. The accessions were grown in the experimental plot and DNA from young and healthy leaves were isolated for determination of genetic diversity using ribulose bisphosphate carboxylase (rbcL). The accessions were also categorized into groups based on the performances and the highest discriminating traits that accounted for greater variability using principal component analysis (PCA) and cluster analysis (CA) respectively. 

Result: Cluster analysis grouped all the twenty accessions into three clusters, where cluster I, cluster II and cluster III comprised of eight, seven and five accessions respectively. The PCA revealed hundred seed-weights, number of pod per plant and seed length as the most discriminating trait that accounted for greater variability in the Lablab accessions considered and they should be considered in the hyacinth bean improvement programs. Based on diverse level of phenotypic traits, accessions from each cluster were selected for barcode identification and comparison with other cultivars from other region. Results of the molecular analysis showed two clusters and authenticated the use of universal primers, ribulose bisphosphate carboxylase (rbcL) for DNA barcoding for successful amplification, identification and discrimination of Lablab purpureus (L). This revealed diversity of the considered accessions and provided information on relatedness to other accessions from other region of the world.
Legumes are plants belonging to the family Fabaceae and are known to produce seeds within a pod (Agbolade et al., 2019). On the basis of usefulness and economy of plant, legumes are divided into major and minor species (Assogba et al., 2015). Major legumes are well-liked and widespread with well-established domestication and cultivation, agronomic practices, utilization and conservation (Popoola et al., 2019). Minor legumes on the other hand are underutilized species commonly identified as a result of their local worth, poor breeding, variation together with general withdrawal by established agricultural researchers, extension services, donors, technology providers, plant breeders, policy and decision makers, as well as consumers (Singh et al., 2018). Nevertheless, minor grain legumes have diverse potentials and promising as the conventional staple crops. Minor or orphan legumes are often linked to the cultural heritage of their places of origin, well adapted to diverse agro-ecological conditions with wide range resilience to different stresses. (Narasimhulu et al., 2018). Lablab (Lablab purpureus) is one of the minor legumes or orphan legume crops; also known as the hyacinth bean in English speaking and Dolich in French speaking countries. It is an African species, commonly flourishes in wet tropical regions than in dry regions like Sahel, regardless of its consideration to be more drought tolerant plant than cowpea (Patricia et al., 2019). Success of any a breeding programme and crop improvement of specific trait through selection in particular, solely rest on the available genetic variability in the available germplasm of a particular crop (Pitil et al., 2017, Patricia et al., 2019). This study was mainly focused on investigating genetic diversity among twenty Lablab purpureus accessions and assessment of morphological and molecular studies using vegetative characters, sequence analysis, calculation of genetic distance, molecular weight of bases, amplified polymorphism, barcode development of multiple sequence alignment, use of a neighbor-joining algorithm and tree construction analysis. This result will help to develop an accurate species identification method for the selected five L. purpureus genotypes with the desired traits through developing potential DNA barcodes to support conservation efforts of the genus.
Sample site
 
Twenty genotypes of selected Lablab beans [Lablab purpureus (L.) Sweet] were collected from International Institute of Tropical Agriculture (IITA), Ibadan and experiment was carried out at Teaching and Research Farm of Federal University, Oye-Ekiti, Ekiti State, Nigeria and at the Bioscience Research Laboratory, IITA, Ibadan, Nigeria; during 2020/2021 academic session/year. The genotypes were evaluated in an Alpha lattice design with two replications using R package “Agricolae” for the randomization. Sowing, spacing, field maintenance and data gathering was in accordance with Popoola et al., (2019). Some accessions were selected for the plastid-specific ribulose biphosphate carboxylase (rbcL) study, based on morphological cluster analysis.
 
Genomic DNA isolation
 
Total genomic DNA was isolated using a modified CTAB protocol  according to Fatima et al., (2018b).
 
DNA quantification
 
This was carried out in accordance with Jiao et al., (2013).
 
PCR amplification through universal barcode primers (rbcL)
 
PCR amplification through universal barcode primers (rbcL) was in line with the procedure of CBOL Plant Working Group (2009).
 
Nucleotide sequencing
 
The nucleotide sequencing was according to Fatima et al., (2018b).
 
Statistical analysis
 
The data collected from the experimental field were subjected to analyses using the R software version 4.2 (R Core Team, 2019). Mean average for all characters were computed for Analysis of variance (ANOVA) to detect the variability present among the twenty-five genotypes of Lablab purpureus. Pearson’s correlation test was conducted to detect the positive and negative correlation among the characters observed. The variables generated were then subjected to principal component analysis (PCA) which revealed the variables that contributed mainly to the variation observed among accessions used in this study. This was generated using packages such as ‘FactoMineR’, ggplot2 and FactoExtra to group accessions into different categories. Hierarchical clustering was adopted for the grouping based on the performance of the accessions on the field and Student Newman Keuls (SNK) was adopted for the mean separation of traits across the clusters formed.
 
Barcodes and phylogenetic analysis
 
This was in accordance with Hollingsworth et al., (2011).
Variability of traits across hyacinths beans accessions
 
Analysis of variance of variable observed among accessions of Lablab purpureus exhibited minor significant differences (P<0.05) for different vegetative and yield-related traits. It was found that five (5) of the 16 observed variables showed degree range of variation across the twenty accessions studied (Table 1). The table below showed that stem girth, days to flowering and one hundred seed-weight showed significant variability between the twenty accessions of hyacinth bean (P<0.05) Table 1.

Table 1: Analysis of variance of variables observed among Lablab purpureus accessions.



Other variables studied like plant height, petiole length, stem girt, number of pods per plants, pod weight and pod length showed no variation across the accessions of hyacinth beans studied (Table 1). Analysis of variance results revealed 20% of variables observed contributed to the diversity across the accessions of lablab in this study. The descriptive statistics of variables observed among Lablab purpureus accessions revealed the mean value, standard deviation, minimum and maximum values for all traits.

Correlation matrix between the studied variables of hyacinth bean revealed significant association between many traits (Fig 1). High significant and positive correlation was observed between leaf girth and leaf length. Leaf girth also showed positive and significant correlation with stem girth only. Relationship with other variables were not significantly correlated (Fig 1). Plant height showed no significant correlation with any of the observed variables. Moderate positive correlation was observed between seed weight and 100-seed weight, number of seeds per pod with pod length and pod width. Pod length exhibited positive and significant correlation with hundred-seed weight. This correlation between pod length and hundred-seed weight can be utilized during selection for improvement of yield traits in Lablab purpureus.  However, no significant correlation was observed for petiole length with all evaluated variables (Fig 1). 

Fig 1: Correlation matrix among traits of Lablab purpureus.


 
Principal component analysis
 
The first four Principal Components with Eigen values >1 explained 69% of variation among the accessions of Lablab purpureus evaluated in this study. The first PC contributed 26.3% of the variation (Fig 2 and Table 2).  PC2 accounted for 17.5%, 14.49% for PC3 and 10.35 for PC 4. The significant variables in each PC was determined using >±0.5 significant correlation (Akohoue et al., 2019). Days to 50% flowering, number of pod per plant, pod length, hundred-seed weight and seed length showed high contribution to first principal component (Table 2). Petiole length, pod length, pod width and Number of pod per plant (NPP) contributed most to PC 2 as in Table 2.

Fig 2: Cluster plot (a) and phylogenetic representation (b) of Lablab purpureus accessions using phenotypic traits.



Table 2: Contribution of principal component axes to the variation among accessions studied.



Significant negative correlation was also observed in principal component 1 where leaf girth exhibited high degree of negative contribution. Principal component 2 also showed negative contribution of leaf girth. Principal component revealed the most significant positive correlation for days of germination and leaf girth (Table 2). Negative correlation was also observed for Days to 50% flowering.
 
Phylogenic pattern
 
Fig 2 (b) also revealed the phylogenic root of Lablab purpureus accessions in this study. This shows discriminating arrangement when morphometric traits are adopted for the grouping. The accessions in this study were grouped into three phylogenic clusters based on the linkage, each cluster containing accessions that are highly similar in terms of the morphological attributes they possess. Cluster 1 consisted of accessions with the accession codes- TLn37, TLn39, TLn43, TLn19, TLn45, TLn36, TLn48 and TLn44; which are further separated into two sub groups. Cluster 2 contains TLn59, TLn 57, TLn6, TLn55, TLn13 TLn57 and TLn70; which are also separated into two subgroups as it happened in cluster 1. Finally, the cluster 3 also consists of TLn12, TLn5, TLn7, TLn49 and TLn46. Accessions in cluster 3 are also further grouped based on the level of similarities between their descriptive variables (Fig 2).

Accessions cluster mean values of the studied traits revealed considerable variation among different groups. Clusters were differentiated using Student Newman Keuls (SNK) test, accessions with the highest days to maturity are embedded in cluster 3 and cluster 2. Cluster with early 50% flowering are found in cluster 1. Performance of most variables showed that all these traits have high degree of similarities in the performance. Therefore, showed low discriminating attributes for all the accessions in this study. Traits such as number of pod per plant (NPP), pod length (PODL), pod width (PODW), seed weight (SW), leaf length (LL) cannot be used to characterize the accessions evaluated in the study due to low diversity attributed to those traits in Lablab purpureus. This could attributed to the influence of environmental factors of where the experiment was undertaken. This study suggests more multi-locational trial of all the considered accession in this region. Additionally, Fig 3 showed a total of five individuals representing the three clusters from the morphological data and the electropherogram results.

Fig 3: Electropherogram results of rbcL gene amplification in Lablab beans.


 
Nucleotide sequence statistics
 
Table 2 shows the sequence characteristics of the studied barcodes. The total sequences obtained from the ribulose bisphosphate carboxylase (rbcL) region of the selected species were aligned using CLC Sequence Viewer 8.The final aligned partial sequences of rbcL in TLn 12 had a length of 153 bp, 158 bp for TLn 13, 162 bp for TLn 45 and TLn 46 and 159 bp for TLn 57 with the variable single stranded weights of 47.654 kDa for TLn 12, 49.208 kDa for TLn 13, 50.483 kDa for TLn 45, 50.134 kDa for TLn 46 and 49.386 kDa for TLn 57. For the double strands, there are variable weights ranging between 94.56kDa for TLn 12, 97.653kDa for TLn 13, 100.12kDa for TLn 45, 100.125kDa for TLn 46 and 98.277kDa for TLn 57 (Table 3).

Table 3: Nucleotide sequence statistics for the selected accessions of lablab.



Multiple sequence alignment
 
We analyzed the selected L. purpureus genotypes from International Institute for Tropical Agriculture, Ibadan and the sequences of the examined region of plastid DNA (rbcL) was utilized. Multiple sequence alignment of the selected three species sequences was carried out by using the online software Clustal W (v1.2.4). We found unique nucleotide sites between TLn 12 and TLn 45, also throughout the selected genotypes. These were the 79th to 80th sites of the rbcL sequences at which A were present throughout the genotypes and at the 53rd and 54th sites, 118 to 119 CC, TA were present respectively (Fig 4).

Fig 4: Multiple sequence alignment illustration of the sequences of lablab accessions.


 
Bioinformatics analyses of sequences and barcode generation
 
The rbcL sequences from TLn 46 and TLn 12 were identical (accession number MN966634.1, KF724319.1) with other sequences of the selected species. BLAST search in the NCBI nucleotide database was done using the sequences of all L. purpureus genotypes deposited in the GenBank showing 99.23% homology with the nuclear DNA regions. Comparison of the detected sequences with entries in the database finally provided the plant species identification. The developed barcodes for the L. purpureus by using rbcL are shown in Fig 5.

Fig 5: DNA Barcodes representation for Lablab purpureus accessions. a- TLn 12, b- TLn 13, c- TLn 45, d- TLn 46, e- TLn 57.


 
Phylogenetic analysis
 
Total aligned molecular sequences from the selected L. purpureus by rbcL were used to generate a dendrogram which represented the genetic relationship among the selected species in comparison to the NCBI nucleotide sequences. Similar sequences were found to link the accessions considered with the existing accessions of lablab achieved in the NCBI database. This serves as identification insight to the accessions considered as lablab (Fig 6).

Fig 6: Phylogenetic tree of Lablab purpureus accessions compared with known Lablab on NCBI database.



Understanding genetic diversity between accessions requires a proper molecular characterization of the germplasm evaluated so as to be able to ascertain the phenotyping findings (Assogba et al., 2015). The primers gave sharp bands that were required for reliable DNA sequencing. This is in line with the observation of Hollingsworth et al., 2009 where the amplification of the rbcl gene using one or two universal primer types had a high success rate. Thus, using DNA barcodes primers systems is reliable, fast and cheap system for amplification, identification and discrimination of Lablab purpureus (L). The results revealed that all single barcodes could be easily amplified and sequenced with the selected primers. Besides, rbcL marker is individually able to discriminate species of Lablab purpureus accessions investigated and the result corroborates the phylogenic illustration of the accessions using phenotypic traits.
Knowledge of phenotyping in variability study is paramount to making a better selection of genotypes during breeding program. This finding revealed the need for molecular improvement of Lablab purpureus and the need to breed with cultivars from other developed countries due to low variability observed among the accessions. Of all accessions of Lablab beans evaluated in this study, accessions TLn-12, TLn-13, TLn-36, TLn-45, TLn-46, TLn-57 and TLn-70 showed great potential in the morphological traits. Therefore, genetic compatibility study is required among these accessions and most importantly with other cultivars from other developed countries.

DNA-based barcoding is a vital tool for detecting errors in identifications of minor and underutilized grain legumes such as Lablab purpureus. From the sequences, DNA barcodes and distances within the phylogenetic revealed close proximity and indicated their closeness. The present study provides barcodes with DNA sequences for the identification of the selected accessions.

The DNA barcoding established a shared community resource of DNA sequences that can be used for organismal identification and taxonomic clarification of Lablab purpureus.
We appreciate International Institutes of Tropical Agriculture for providing the planting materials and their contribution in the molecular analysis of this research work.
Agbolade James Oludare, Idowu Jeremiah Adebare, Isiaka Abiodun Ibrahim designed the research. Isiaka Abiodun Ibrahim and Idowu Jeremiah Adebare performed the field experiments and analyzed the data. Idowu Jeremiah Adebare, Isiaka Abiodun Ibrahim, Agbolade James Oludare and Ikenna Odoh conducted laboratory tests. Agbolade James Oludare, Idowu Jeremiah Adebare wrote the article. Agbolade James Oludare, Idowu Jeremiah Adebare, Isiaka Abiodun Ibrahim and A. Adekoya Modinat revised the article, JIK edited and proofread the article. All authors read and approved the final manuscript.
All authors declare that they have no conflict of interest.

  1. Agbolade, J.O., Popoola, J.O., Kioko, K.I., Adewale, B.D., Ajiboye, A.A., Ajewole, T.O. and David O.A. (2019). Comparative genetic variability and trait’s heritability in vegetative and floral characters in accessions of two minor legumes. Indian Journal of Agricultural Research. 53(37): 1-6. doi: 10.18805/IJARe.A-374.

  2. Akohoue, F., Achigan-Dako, E.G., Coulibaly, M., and Sibiya, J. (2019). Correlations, path coefficient analysis and phenotypic diversity of a West African germplasm of Kersting’s groundnut [Macrotyloma geocarpum (Harms) Maréchal and Baudet]. Genetic Resources and Crop Evolution. 66(8): 1825-1842. https://doi.org/10.1007/s10722-019- 00839.

  3. Assogba, P., Ewedje E.E.B.K., Dansi A., Loko, Y.L., Adjatin, A., Dansi, M. and Sanni, A. (2015). Indigenous knowledge and agro-morphological evaluation of the minor crop Kersting’s groundnut [Macrotyloma geocarpum (Harms) Maréchal et Baudet] cultivars of Benin. Genetic Resources and Crop Evolution.  63: 513-529.

  4. CBOL Plant Working Group (2009). A DNA Barcode for Land Plants. Proceedings of the National Academy of Sciences of the USA. 106(31): 12794-12797.

  5. Hollingsworth, P.M., Forrest, L.L., Sponge, J.L., Hajibabaei, M., Ratnasingham, S. van der Bank, M., Chase, M.W., Cowan, R.S., Erickson, D.L. and Little, D.P. (2009). A DNA barcode for land plants. Proceedings of the National Academy of Sciences,CBOL Plant Working Group. 106(31): 12794- 12797.

  6. Fatima, T. (2018b). Optimization of genomic DNA extraction routine from ROSEWOOD (Dalbergia latifolia) and BEN TEAK (Lagerstroemia lanceolata). International Journal of Genetics. 10(6): 446-451. ISSN. 0975-2862.

  7. Jiao, L., Yin Y, Cheng, Y., Jiang, X. (2013). DNA barcoding for identification of the endangered specie Aquilaria sinensis: comparison of data from heated or aged wood samples. J Holzforschung. 4: 487-494

  8. Narasimhulu, R.,Naidu, N.V. and Ready, K.H.P. (2018). Genetic analysis for yields and yield attributes in green gram [Vigna radiata (L.) Wilizek]. Legume Res. 41: 349-355. doi: 10.18805/LR-3768.

  9. Patil, B.T, Bachkar, C.B, Handal, B.B, and Shinde, K.G. (2017). Character association and path analysis studies in pole type dolichos bean (Lablab Purpureus L.). Advances in Plants and Agriculture Research. 7(5): 388-390. DOI: 10.15406/apar.2017.07.00271.

  10. Patricia Vidigal, Maria Manuel Romeiras and Filipa Monteiro (2019). Crop Diversification and the Role of Orphan Legumes to Improve the Sub-Saharan Africa Farming Systems. Sustainable Crop Production. DOI:10.5772/intechopen. 88076. 

  11. Popoola, J., Ojuederie, O., Omonhinmin, C., and Adegbite, A. (2019). Neglected and underutilized legume crops: Improvement and future prospects. In Recent advances in grain crops reseach. Intech Open.

  12. Shilpa, M.L., Srinivasa, V., Devaraju, Gangaprasad, S., Ganapathi, M. and Akshay, A. (2020). Variability, heritability and genetic advance for yield and yield attributing characters in dolichos bean (Dolichos lablab L.) Genotypes under hill zone of Karnataka. International Journal of Current Microbiology and Applied Sciences. 9(10): 201-207. doi:https://doi.org/10.20546/ijcmas.2020.910.026.

  13. Singh, S.P., Yadav, R.S., Amit, K. and Jakhar, R.R. (2018).Productivity augumentation of green gram (Vigna radiata) through weed management. Legume Res. 41: 410-415. doi: 10.18805/LR-3793.

Editorial Board

View all (0)