Allelic variation for meiosis related genes in Brassica juncea and its diploid progenitors
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Date
2016
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Punjab Agricultural University, Ludhiana
Abstract
Patterns of allelic differentiation were investigated for meiotic genes in natural and resynthesized B. juncea allotetraploids as well as their progenitors. Pollen fertility was wide-ranging, with B. juncea showing the maximum variation. A representative set of 96 lines was then genotyped with 70 STS markers. Fifty five polymorphic markers amplified 137 alleles. Within population differences (76%) accounted for maximum variation, followed by variation among species (19%). Population structure analysis largely reflected the ploidy boundaries. Diploids were grouped together, but B. juncea formed two major subgroups. Linkage disequilibrium (LD) deviated significantly between species and subpopulations as well. Large LD block with MMD1 was observed for B. juncea. For diploids, MRE11 and TES spanned major LD blocks. Markers based on two candidate genes, SCC3 and BRCA2b showed significant association with pooled pollen fertility. These explained 11-14 % of the trait variation. For B. juncea, only MS5b provided evidence of directional selection using softwares Arlequin and LOSITAN. Tajima’s D values were negatively significant for RAD51C, ZYP1a and ZYP1b for A homolog, indicating balancing selection. B homolog of SWI1 showed evidence of positive selection. Hierarchical clustering analysis based on gene expression indicated diverse meiotic machinery in B. juncea as compared to progenitor species. MEI1, ZYP1a, ZYP1b were transgressively over expressed in B. juncea. In contrast; SPO11-1, DMC1, BRCA2a, MSH2, MSH4, MMD1 and TES were distinctly down regulated in B. juncea. There seemed to be a distinct balance between co-upregulation or –down regulation of identified meiotic genes in both natural and freshly resynthesized allopolyploids, suggesting that changes in gene expression regulation may occur in the early aftermath of genome merger.
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Keywords
Meiotic genes, Brassica juncea, Transcriptome