Molecular genetic diversity and population structure analyses of rutabaga accessions from Nordic countries as revealed by single nucleotide polymorphism markers

被引:12
|
作者
Yu, Zhiyu [1 ]
Fredua-Agyeman, Rudolph [1 ]
Hwang, Sheau-Fang [1 ]
Strelkov, Stephen E. [1 ]
机构
[1] Univ Alberta, Dept Agr Food & Nutr Sci, Edmonton, AB T6G 2P5, Canada
关键词
Brassica; SNP; AMOVA; Population differentiation; PCoA; UPGMA and NJ; BRASSICA-NAPUS; SNP MARKERS; PROGRAM STRUCTURE; SUGAR CONTENT; F-STATISTICS; SOFTWARE; CLUSTERS; SWEDES; TRANSCRIPTOME; ORIGIN;
D O I
10.1186/s12864-021-07762-4
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: Rutabaga or swede (Brassica napus ssp. napobrassica (L.) Hanelt) varies in root and leaf shape and colour, flesh colour, foliage growth habits, maturity date, seed quality parameters, disease resistance and other traits. Despite these morphological differences, no in-depth molecular analyses of genetic diversity have been conducted in this crop. Understanding this diversity is important for conservation and broadening the use of this resource. Results: This study investigated the genetic diversity within and among 124 rutabaga accessions from five Nordic countries (Norway, Sweden, Finland, Denmark and Iceland) using a 15 K single nucleotide polymorphism (SNP) Brassica array. After excluding markers that did not amplify genomic DNA, monomorphic and low coverage site markers, the accessions were analyzedwith 6861 SNP markers. Allelic frequency statistics, including polymorphism information content (PIC), minor allele frequency (MAF) and mean expected heterozygosity (H over bar) and population differentiation statistics such as Wright's F-statistics (F-ST) and analysis of molecular variance (AMOVA) indicated that the rutabaga accessions from Norway, Sweden, Finland and Denmark were not genetically different from each other. In contrast, accessions from these countries were significantly different from the accessions from Iceland (P < 0.05). Bayesian analysis with the software STRUCTURE placed 66.9% of the rutabaga accessions into three to four clusters, while the remaining 33.1% constituted admixtures. Three multivariate analyses: principal coordinate analysis (PCoA), the unweighted pair group method with arithmetic mean (UPGMA) and neighbour-joining (NJ) clustering methods grouped the 124 accessions into four to six subgroups. Conclusion: Overall, the correlation of the accessions with their geographic origin was very low, except for the accessions from Iceland. Thus, Icelandic rutabaga accessions can offer valuable germplasm for crop improvement.
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页数:13
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