AFLP-based molecular characterization of an elite germplasm collection of Jatropha curcas L., a biofuel plant

Amplified fragment length polymorphism (AFLP) was employed to assess the diversity in the elite germplasm collection of Jatropha curcas, which has gained tremendous significance as a biofuel plant in India and many other countries recently. Forty-eight accessions, collected from six different states of India, were used with seven AFLP primer combinations that generated a total of 770 fragments with an average of 110 fragments per primer combination. A total of 680 (88%) fragments showed polymorphism in the germplasm analyzed, of which 59 (8.7%) fragments were unique (accession specific) and 108 (15.9%) fragments were rare (present in less than 10% accessions). In order to assess the discriminatory power of seven primer combinations used, a variety of marker attributes like polymorphism information content (PIC), marker index (MI) and resolving power (RP) values were calculated. Although the PIC values ranged from 0.20 (E-ACA/M-CAA) to 0.34 (E-ACT/M-CTT) with an average of 0.26 per primer combination and the MI values were observed in the range of 17.60 (E-ACA/M-CAA) to 32.30 (E-ACT/M-CTT) with an average of 25.13 per primer combination, the RP was recognized the real attribute for AFLP to determine the discriminatory power of the primer combination. The RP values for different primer combinations varied from 23.11 (E-ACA/M-CAA) to 46.82 (E-ACT/M-CTT) with an average of 35.21. Genotyping data obtained for all 680 polymorphic fragments were used to group the accessions analyzed using the UPGMA-phenogram and principal component analysis (PCA). Majority of groups obtained in phenogram and PCA contained accessions as per geographical locations. In general, accessions coming from Andhra Pradesh were found diverse as these were scattered in different groups, whereas accessions coming from Chhattisgarh showed occurrence of higher number of unique/rare fragments. Molecular diversity estimated in the present study combined with the datasets on other morphological/agronomic traits will be very useful for selecting the appropriate accessions for plant improvement through conventional as well as molecular breeding approaches.