ABSTRACT
Apple scab instigated by Venturia inaequalis impels remarkable losses to apple fruit production. In an effort to comprehend the key mechanisms of evolutionary potential defining V. inaequalis population, 132 isolates of V. inaequalis from five commercial apple orchards were collected and assayed using 14 microsatellite markers. The average diversity was observed within the individuals of populations based on the Shannon-Wieners index (I) and observed heterozygosity (Ho) was average but considerably lower than expected heterozygosity (He). The genetic differentiation based on FST values was revealed as an average measure of divergence between populations and had varying proportions of gene flow and migration among themselves. Analysis of Molecular Variance (AMOVA) revealed that variance (94%) was dispersed across individuals with a significant (6%) variation between populations from different regions. To examine host specialization within the V. inaequalis population, the assignment approach based on K-means of clustering (an unsupervised machine learning approach), revealed that the clustering method supported three clusters at (K = 3) and three major clusters were also observed in Principle Component Analysis (PCA). Additionally, Nei's genetic distance values, pairwise estimates of genetic differentiation, dendrogram using the neighbor-joining and PCoA revealed the random distribution of V. Inaequalis isolates that depicted a high proportion of genotypic diversity within populations and population genetic structure. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03672-2.
ABSTRACT
BACKGROUND: Characterization and evaluation of plant genetic resources play an important role for their utilization in the crop improvement programmes. METHODS AND RESULTS: This study involves the agro-morphological and cooking quality besides, molecular characterization of 51 genotypes/advance breeding lines of rice from Kashmir Himalayas. Significant variability was observed for all agro-morphological and cooking quality traits among all the studied genotypes. Cluster analysis using UPGMA method divided the genotypes into two major clusters having 15 and 36 genotypes. Thirty eight genotypes screened using 24 SSR markers detected 48 alleles with 2.0 alleles for each locus with average polymorphism information content (PIC) of 0.37. High polymorphism information content (PIC) values was observed for the primers RM263 (0.67), RM159 (0.59) and RM333 (0.50). Furthermore, out of 38 SSR markers screened on 192 temperate rice germpalsm lines, R4M17 accurately differentiated indica and temperate japonica genotypes amplifying 220 bp and 169 bp, respectively. Accordingly, 15 genotypes were reported as indica and 28 temperate japonica in addition to 149 genotypes as intermediate types. CONCLUSION: The information on marker-based diversity and performance based on cooking quality and agronomic traits helped to select the most divergent lines for crossing. Also the analysis was useful to classify the temperate germplasm into indica and temperate japonica. The classification could be helpful to devise a strategy for inter-sub species hybridization to breed for improved rice varieties.
