ABSTRACT
Cotton is the world's leading fiber crop and the second important oil seed crop. Recent advances in genomics research have provided new tools, such as molecular markers, that will assist breeders in the improvement of this important crop. Use of molecular markers in genome analysis, mapping of agriculturally important traits and marker-assisted selection have been greatly advanced by the development of PCR-based markers. The present study is a part of a cotton genomics project that addresses the use of different PCR-based molecular markers [RAPD, ISSRI and SSR] for germplasm characterization, fingerprinting and assessing the genetic diversity among some of the accessions available at the Cotton Research Institute, ARC, and Egypt. Twenty one cotton accessions were assayed using 28 RAPD and 12 ISSR primers, in addition to 24 SSR specific primer pairs. The total number of amplicons detected by RAPD, ISSR and SSR was 323, 125 and 62, respectively. While, the number of polymorphic amplicons was 191, 62 and 39 respectively. Thus, the level of polymorphism among the 21 accessions as revealed by RAPD, ISSR and SSR was 59.1%, 49.6 and 62.9 respectively. The genetic relationships among the 21 accessions were estimated in terms of similarity using the Dice coefficient. The topology of the dendrograms derived from the different marker types was unique, however, with evident similarities. All dendrograms clearly clustered the accessions belonging to G. hirsutum in one group and those of G. barbadense, expect Pima Early American, in another group. One out of the 28 RAPD primers produced 21 different banding patterns, thus, identifying each of the 21 accessions by a unique banding profile. Two ISSR primers [SI and S2] revealed 18 banding patterns each and together made it possible the identification of all the genotypes. Moreover, accession-specific DNA markers characterized different genotypes and therefore were used to generate unique fingerprint for each genotype. The RAPD, ISSR and SSR detected 4, 8 and 5 unique positive and/or negative markers characterizing 3, 4 and 4 accessions, respectively. Furthermore, five SSR alleles [M8 280, M8 290, C11 250, C11 260 and M13 150] could the discriminate between accessions belonging to the species G. barbadense and those of G. hirsutum. Thus, they were considered as species-specific markers
ABSTRACT
The genetic variability and relationships among 14 date pain [Phoenix dactylifera L.] accessions representing six Egyptian cultivars were assayed using 27 RAPD and 10 ISSR primers. The level of polymorphism among the 14 accessions as revealed by RAPD and ISSR was 25.2% and 28.6%, respectively. These low levels of polymorphism reflect the narrow genetic background of these accessions. The genetic relationships among the 14 accessions were estimated in terms of similarity using Dice coefficients. The genetic similarity ranged from 96.1% to 99, 5% and from 91.2% to 100% for RAPD and ISSR, respectively. The inter-cultivar relationships among the six date palm cultivars based on RAPD and ISSR revealed the highest genetic similarity between the cultivar Bertmoda and each of the cultivars Malkaby and Sakkoty. The RAPD and ISSR based dendrograms clustered the accessions belonging to each of the 3 cultivars Frailty, Siwi and Gandila in separate groups. However, the reshuffling in the position of some of the accessions belonging to the other cultivars in the different dendro grams revealed that they share common gnenetic background. Cultivar-specific DNA markers characterized different genotypes and therefore, were used to generate unique fingerprint for each genotype. The RAPD and ISSR revealed 17 and 5 cultivar unique DNA markers, characterizing 4 and 5 cultivars, respectively. Moreover, each of the RAPD and ISSR was successful in identifying accession-specific markers characterizing five accessions
ABSTRACT
Fourteen date palm [Phoenix dactylifera L.] accessions collected from different locations in Egypt representing six Egyptian cultivars: Sakkoty, Bertmoda, Malkaby, Gandila, Fraihy and Siwi were assayed using 16 AFLP primer combinations. AFLP analysis generated a total of 657 amplicons representing a level of polymorphism of 45.8%. The genetic similarity and relationships were estimated among the 14 accessions and among the six cultivars according to Dice coefficient. The AFLP-based dendrograms clustered the genotypes of some cultivars together, i.e. Fraihy and Gandila. The genotypes of Siwi cultivar were clustered together also, but they exhibited some degree of intravarietal variation. The other three cultivars [Sakkoty, Bertmoda, and Malkaby] showed higher degree of intravarietal variation. Moreover, at the intervarietal level, the AFLP assay separated the oases cultivars i.e., Siwi and Fraihy, from the cultivars from Aswan, i.e. Sakkoty, Bertmoda, Malkaby and Gandila. AFLP analysis permitted the characterization of each cultivar by specific unique markers. Data from RAPD's and ISSR's, previously obtained on the same 14 accessions were combined with AFLP's to generate more accurate relationships based on large and versatile genome coverage. The dendrogram based on the combined data from the different types of markers [RAPD, ISSR and AFLP] was closest to the AFLP-based dendrogram. To evaluate the efficiency of the different marker systems, the sum effective number of alleles [SENA], the average expected heterozygosity for polymorphic markers [Hav[p]], the effective multiplex ratio [E] and marker index [MI] were calculated. The AFLP exhibited considerably high sum effective number of alleles [205.7] compared to RAPD and ISSR [45.1 and 17.8, respectively]. The average heterozygosity was also higher in AFLP [0.39] than in RAPD and ISSR [0.36 and 0.35, respectively]. The MI was 117.3 in AFLP while it was 95.9 and 10.4 in RAPD and ISSR, respectively. Thus, the results indicated that AFLP is more effective in detecting high level of polymorphism. The correlation coefficient was considerably high between RAPD and ISSR [0.68], and it was lower between RAPD and AFLP [0.23] than that between AFLP and ISSR [0.34]. The results confirmed that different marker systems differ in the mechanism of detecting polymorphism, genome coverage and the ease of application. Therefore, they could complement each other 10 draw more accurate conclusions