The study of the sorghum genetic diversity using the mul¬tiplex microsatellite analysis

Autor: Yu. V. Aniskina, E. V. Malinovskaya, V. S. Mitsurova, N. S. Velishaeva, O. S. Kolobova, I. A. Shilov
Jazyk: English<br />Russian
Rok vydání: 2020
Předmět:
Zdroj: Биотехнология и селекция растений, Vol 2, Iss 3, Pp 20-29 (2020)
Druh dokumentu: article
ISSN: 2658-6266
2658-6258
DOI: 10.30901/2658-6266-2019-3-o1
Popis: This study is focused on evaluation of the genetic structure and diversity of the national sorghum collection. Analyzing the genetic diversity of crop species is of great importance for genetic resources management and food security of any country. Huge genetic diversity of sorghum provides a great opportunity to improve the agronomic characteristics of this crop. The efficiency of microsatellite analysis has been demonstrated in many studies on the genetic diversity of different races and geographical groups of sorghum plants. Development of multiplex PCR analysis systems based on a set of polymorphic microsatellite loci will facilitate genetic tests on a large number of plant samples, thus making the research on sorghum diversity more efficient and comprehensive. A system of multiplex PCR analysis based on 12 polymorphic microsatellite loci was developed to perform single-stage high-throughput screening of cultivated and wild forms preserved in the sorghum germplasm collection. As a result of the microsatellite analysis of 200 sorghum plants, 229 alleles were detected. The studied loci showed high polymorphism. More than 17 alleles were identified in most loci, their polymorphic index content (PIC) ranging from 0.694 to 0.954. The value of the effective multiplex ratio (EMR) in the developed system was estimated at 0.833. The microsatellite analysis of sorghum accessions resulted in obtaining quantized gene expressions profiles, with a DNA profile for each accession, and revealed significant polymorphism among the plants of different sorghum varieties (races). The developed multiplex PCR system was shown to be efficient for evaluation of the genetic diversity and genetic relationships of sorghum plants from different races. The analysis of the obtained data using three bioinformatic techniques, NJ cluster analysis, PCoA, and the Bayesian model-based clustering, helped to classify the analyzed sorghum accessions into cluster groups according to their morphological and agronomic traits.
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