Background: In order to assess genetic diversity of a set of 41 Caricaceae accessions, this study used 34 primer pairs designed from the conserved domains of bacterial leaf blight resistance genes from rice, in a PCR based approach, to identify and analyse resistance gene analogues from various accessions of Carica papaya, Vasconcellea goudotiana, V. microcarpa, V. parviflora, V.
View Article and Find Full Text PDFBackground: Bacterial leaf blight (BLB) caused by the vascular pathogen Xanthomonas oryzae pv. oryzae (Xoo) is one of the most serious diseases leading to crop failure in rice growing countries. A total of 37 resistance genes against Xoo has been identified in rice.
View Article and Find Full Text PDFA preliminary survey of genetic diversity among 34 commercially popular Carica papaya cultivars from India and abroad, 6 accessions of Vasconcellea species and 1 accession of Jacaratia spinosa, was done using 20 simple sequence repeat (SSR) markers. The SSR profiles were used to find out total number of alleles, null and rare alleles, Polymorphism Information Content (PIC) values and to calculate similarity matrix using Jaccard's coefficient. The subsequent dendrogram was made by unweighted pair-group method of arithmetic average (UPGMA) and neighbor-joining method.
View Article and Find Full Text PDFBackground: Adaptations to different habitats across the globe and consequent genetic variation within rice have resulted in more than 120,000 diverse accessions including landraces, which are vital genetic resources for agronomic and quality traits. In India the rice landraces of the states West Bengal, Assam, Mizoram, Manipur and Nagaland are worthy candidates for genetic assessment. Keeping the above in view, the present study was conducted with the aim to (i) calculate the genetic distances among the accessions of 83 landraces collected from these states along with 8 check accessions (total 91 accessions) using 23 previously mapped SSR markers and (ii) examine the population structure among the accessions using model-based clustering approach.
View Article and Find Full Text PDF