These sequences can serve as markers or tags for transcripts, and have been used in the development of markers for reference genetic map and recovery of full-length cDNA and genomic sequences.
On the final map each GBS marker was mapped to a recombination interval defined by two markers of the reference genetic map.
Some contigs containing candidate genes for resistance to pathogens were a ssigned to chromosomes by the SSR markers of the reference genetic map.
Contigs containing genes relevant to this work and not tagged by the markers of the reference Vitis map were anchored by SSR markers positioned in other genetic maps [ 34], by newly developed SSR markers, and by SSCP markers [see Additional file 1].
Population-based methods are highly accurate, if both number of markers and number of reference individuals are high enough, but they are computationally intensive.
Map position of each new marker was also assigned on the Vitis reference map of Doligez et al [ 30] by comparing the position of the pair of reference markers flanking a new marker in 'Chardonnay', 'Cabernet Sauvignon', 'Bianca', and/or '20/3' with the same reference markers placed on the integrated map.of Doligez et al [ 30].
However, in the absence of reference marker order, the use and imputation of GBS markers is challenging.
In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi.
Using both simulated and real data sets, we determined that factors such as LD level, MAF of untyped SNPs, marker density and size of reference haplotypes have varying effects on imputation accuracy rates.
Under a medium LD level and medium marker density as size of reference samples increased from 90 to 540, for example, the running time for MACH, IMPUTE, fastPHASE, PLINK and Beagle increased from 0.6 min to 15.5 min, from 0.50 min to 13.2 min, from 1.6 min to 6.5 min, from 0.15 min to 0.2 min and from 0.6 min to 0.7 min, respectively.
