Application of Genomic and Unigene-based Microsatellite markers in Conservation and Management of Genetic Resources of Some Iranian Crops

Today with appropriate understanding of economical, ecological, cultural and social importance of biodiversity, significant progresses have been made toward identification, quantification, finding distribution patterns and genetic relationships of this diversity. In addition, analysis of genetic variation of various aspects such as distribution of allelic diversity, genetic structure and kinship relationships between and within populations, individuals and species is one of the main concerns in biological sciences. In this regard, and with respect to the importance of identification, preservation and maintenance of these genetic pools, to ensure the permanent existence of them and using those resources as a tool for facilitating management strategies and breeding processes, the efficiency of some different genetic and genomic methods including genome and transcriptome based microsatellites have been evaluated in some crop plants, i.e. saffron, and some species belonging to genus Prunus and Punica. Through the development of different molecular markers used in the above-mentioned studies, genome-based microsatellite markers have significantly improved our knowledge on the processes related to habitat segmentation and small populations, distribution of allelic diversity, patterns of germplasm management and finally genetic relationships in the field of genetic conservation. Recently, availability of next generation sequencing tools provided access to huge amount of transcriptomic and genomic sequences. This has allowed us to, a) investigate the diversity of gene functions caused by habitat segmentation, b) assess diversity of responses to biotic and abiotic stresses as well as environmental changes and, c) identify suitable markers to be used in studies such as marker-assisted selection. Here we discuss how the integration of genomic and transcriptomic variations backed up with new bioinformatic tools could  improve the identification of relative influences of genetic and environmental threats and open up new frontiers in conservation studies.