​Genetic Diversity Analysis in Extra Early Pigeonpea [Cajanus cajan (L.)] Genotypes using SSR Markers

Pigeonpea is an often cross-pollinated diploid (2n=2X=22) crop with 833.07 Mb genome size (Varshney et al., 2012a). Pigeonpea plays an important role in sustainable agriculture, because of its multiple usages in food, fodder, soil conservation, crop-livestock integrated systems, reclaiming of degraded pastures, symbiotic nitrogen fixation and has an important role in vegetarian diet in developing countries by ensuring high supply of vitamin B carotene, ascorbic acid and rich protein (22%) (Varshney et al., 2013). Desirable level of productivity in pigeonpea can be exploited by selecting the existing variability among indigenous germplasm of pigeonpea. However, to attain further breakthrough in increasing yield and improving stability in future cultivars, new variability needs to be tapped and incorporated into cultivars. Using crop wild relatives in breeding programme is a long and laborious process that is typically much more difficult than breeding with cultivated crop varieties. Many plant breeders avoid the use of crop wild relatives for this reason. The first step towards using crop wild relatives in breeding is prebreeding, an essential component for this purpose 43 extra early genotypes are utilized in this research work.
               
Assessment of genetic diversity has traditionally been made through morphological characters that are often limited in number, have complex inheritance and vulnerable to environmental conditions. DNA marker overcome this ill effect as they are abundant in nature, stable and not influenced by environmental fluctuations. Among the DNA markers, simple sequence repeat (SSR) or microsatellite marker is one of the most useful genetic marker systems that use PCR technique to identify differences in microsatellite repeat units. SSR markers are widely used because of its co-dominant, multi allelic, high polymorphism, reproducibility, abundant informativeness, convenience of assay by PCR and distribution throughout the genome, independent of environments, independent of tissue effects and providing more precise characterization of genotypes and measurement of genetic relationships  than other  markers (Gupta and Varshney, 2000; Hari et al., 2017). SSRs with ≥20 nucleotides and <20 nucleotides are referred to as Class I (hypervariable) and Class II, respectively. The significance of hyper-variable SSRs in pigeonpea has been established owing to their ease of scoring in simple agarose gel (Bohra et al., 2017). Keeping these points in view, the present investigation was carried out with an objective of understanding the genetic diversity among 43 pigeonpea accessions using hyper variable SSR markers.

Collection of plant material
 
A set of 43 pigeonpea genotypes were obtained from ICRISAT, Patancheru and these genotypes were raised during 2016-17 following standard Agronomic Practices at Regional Agricultural Research Station, Waragal, PJTSAU, Telangana. Leaf samples were collected from all the genotypes at 30 Days after sowing (DAS) for DNA isolation (Table 1).
 

 
DNA isolation and PCR analysis
 
Genomic DNA from leaf samples was isolated by following the standard protocol as per the procedure described by Murray and Thompson (1986), with few modifications. Final concentration of 30 ng/µl of genomic DNA was used for PCR (Eppendorf) amplification. PCR was performed using 1 U of Taq DNA polymerase (Fermentas, Lithuania) and 1x PCR buffer (Genei, India) in 10-µl reaction volume with a thermal profile of 94°C for 5 min (initial denaturation), followed by 35 cycles of denaturation at 94°C for 1 minute, annealing temperature (Table 2) for 1 min, extension at 72°C for 2 min and a final extension of 7 min at 72°C. The amplified products were electrophoretically resolved on 4% Seakem LE® Agarose (Lonza, USA), containing 0.5 mg/ml of ethidium bromide in 0.5x TBE buffer and visualized under UV.
 

 
Data analysis
 
Allele number was given and scored according to its presence or absence, based on difference in molecular weight. Only the clear and unambiguous bands were scored. 41 markers were scored for the presence (1) and absence (0) of the corresponding band among the genotypes. Consequently, a data matrix comprising ‘1’ and ‘0’ was formed and subjected to further analysis. Further processing of data was done by carrying out sequential agglomerative hierarchical non-overlapping clustering (SAHN), on squared Euclidean distance matrix. Similarity matrix was done using Jaccard’s coefficient, in which similarity matrices were utilized to construct the UPGMA (Unweighted Pair Group Method with Arithmetic average) dendrogram. Data analysis was done using NTSYs PC (Rohlf, 1998).

The  present  investigation  envisaged  the  degree  of  genetic diversity  based  on  marker  data  in  forty three genotypes of pigeonpea (Fig 1). Genetic diversity/relatedness among the genotypes was assessed on the basis of Polymorphic information content (PIC) value. Out of 41 HASSR markers (Table 2), 21 markers (Table 3) were completely amplified and a total of 193 alleles were found. In the remaining markers, some were amplified and some were not amplified. Polymorphic information content (PIC Value) of SSR markers was calculated (Table 2). It ranged from 0.87 (HASSR 116) to 0.60 (HASSR-22, HASSR-29 and HASSR-68) with an average of 0.74. Molecular polymorphism was 58.8% with 21 HASSR primers indicating the low level of genetic variation among the varieties (Table 3). The polymorphic bands were scored visually as present (1) or absent (0) on a binary matrix. Genetic similarity between the varieties was estimated using Jaccards Coefficient of similarity index. Dendrogram was performed using the Unweighted Pair Group Method with an Arithmetic mean (UPGMA) algorithm and the NTSYS software (Fig 2).
 



 

 

 
Cluster analysis
 
Cluster analysis of the genotypes is depicted in Fig 2. The genotypes were grouped into two main clusters i.e. cluster A cluster and cluster B. Cluster A consists of only one genotype viz., ICPL 87119 and it showed 28% of similarity with Cluster B. Cluster B is further divided into sub clusters i.e. sub cluster B₁ and B₂ at 30% of similarity. The sub cluster B₁ is further divided into sub cluster B_1.1 and sub cluster B_1.2 at 35% of similarity. The sub cluster B_1.1 had 5 genotypes viz., UPAS 190, ICPL 11155, ICPL11161, ICPL11151 and ICPL11156. The sub cluster B_1.2 had 32 genotypes viz., ICPL11159, ICPL10140, ICPL11100, ICPL1116, ICPL10116, ICPL11151, ICPL11158, ICPL11160, ICPL11111, ICPL11199, ICPL11106, ICPL 11174, ICPL11198, ICPL11176, ICPL11118, ICPL10118, ICPL11111, ICPL11191, ICPL 10115, ICPL11114, ICPL10111, ICPL10119, ICPL10115, ICPL11165, ICPL11154, ICPL11185, ICPL11101, ICPL87, ICPL88019 and ICPL11141, while, sub cluster B2 had 5 genotypes viz., ICPL84031, ICPL88034, ICPL161, ICPL87091 and CORG9701. In sub cluster B2, the pigeonpea genotypes ICPL 84031and ICPL 88014 showed 68% of similarity, while the pigeonpea genotypes ICPL 87091 and CORG 9701were also showed 68% of similarity and in combination showed 50% of similarity. In Dendrogram the pigeonpea genotypes present in sub cluster B1.1 viz., ICPL 10118 and ICPL 11111 were showed highest percent (91%) of similarity.
       
It is observed from the study that the genotype ICPL 87119 was found to be the most diverse as it occupied a single cluster. It is also interesting to observe that it is resistant to wilt. Hence based on cluster analysis, the identified diverse pigeonpea genotypes can be effectively selected for carrying out various breeding and crop improvement programmes. The study clearly indicated that SSR marker profiles were best-suitable for assessing genetic relationships among pigeonpea genotypes. Based on similarity coefficients and cluster analysis pigeonpea genotypes ICPL 84031, ICPL88034, ICPL161, ICPL87091 and CORG9701 were genetically more distant from other pigeonpea genotypes and these varieties can be used for their desirable characteristics in breeding programs for Pigeonpea improvement (Fig 2).
               
Earlier, assessment of the genetic variation in pigeonpea has been carried out using different types of molecular markers including random amplified polymorphic DNA (RAPD) (Shende and Raut, 2013), Resistance gene analog (RGA)-anchored amplified fragment length polymorphism (AFLP-RGA) (Patil et al., 2014) and simple sequence repeat (SSR) (Bohra et al., 2017, Suman et al., 2019 and Sharma et al., 2020). Similar to our results, the narrow genetic base of the domesticated pigeonpea was also evident from analyses based on other DNA marker systems such as RAPD (Ratnaparkhe et al., 1995), RFLP (Nadimpalli et al., 1993), AFLP (Panguluri et al., 2006), DArT (Yang et al., 2006), ISR (Kudapa et al., 2012) and SNP (Kassa et al., 2012). As compared to the earlier successful reports, the number of polymorphic and informative markers used for genetic diversity analysis in the present investigation is more.

 In the present investigation, we have successfully assessed the levels of inter and intraspecific diversity relationships among 43 exra early pigeonpea genotypes. Pigeonpea genotype ICPL87119 is wilt resistant and also genetically more distant from other pigeonpea genotypes viz., ICPL84031, ICPL88014, ICPL161, ICPL87091 and CORG9701. Hybridization among these diverse parents may helpful to obtain better extra early genotypes with wilt resistance. Results obtained from the present investigation would be highly useful in Pigeonpea breeding programs and may be used for further crop improvement using advance marker systems.

The authors gratefully acknowledge the EXTRAMURAL RESEARCH (EMR) fund of Indian Council of Agricultural Research (ICAR) for providing funding and Professor Jayashankar Telangana State Agricultural University (PJTSAU) for providing facilities to carry out the Research work and for ICRISAT for providing the material.