Revealing the complex genetic structure of cultivated amaryllis (Hippeastrum hybridum) using transcriptome-derived microsatellite markers

Sci Rep. 2018 Jul 13;8(1):10645. doi: 10.1038/s41598-018-28809-9.

Abstract

Although amaryllis (Hippeastrum hybridum) plants are commonly used in physiological and ecological research, the extent of their genomic and genetic resources remains limited. The development of molecular markers is therefore of great importance to accelerate genetic improvements in Hippeastrum species. In this study, a total of 269 unique genes were defined that might regulate the flower spathe development of amaryllis. In addition, 2000 simple sequence repeats (SSRs) were detected based on 171,462 de novo assembled unigenes from transcriptome data, and 66,4091 single nucleotide polymorphisms (SNPs) were also detected as putative molecular markers. Twenty-one SSR markers were screened to evaluate the genetic diversity and population structure of 104 amaryllis accessions. A total of 98 SSR loci were amplified for all accessions. The results reveal that Nei's gene diversity (H) values of these markers ranged between 0.055 and 0.394, whereas the average values of Shannon's Information index (I) ranged between 0.172 and 0.567. Genetic tree analysis further demonstrates that all accessions can be grouped into three main clusters, which can be further divided into two subgroups. STRUCTURE-based analysis revealed that the highest ΔK values were observed when K = 5, K = 6, K = 7 and K = 8. The results of this study enable large-scale transcriptomics and classification of Hippeastrum genetic polymorphisms and will be useful in the future for resource conservation and production.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amaryllidaceae / genetics*
  • Chromosome Mapping
  • Gardens
  • Gene Expression Profiling
  • Gene Expression Regulation, Plant
  • Genes, Plant / genetics*
  • Genetic Variation
  • Microsatellite Repeats / genetics*
  • Phylogeny*
  • Polymorphism, Genetic
  • Sequence Analysis, DNA
  • Transcriptome / genetics*