Each plant head was assigned a random identification number, threshed by hand, and all seed from each individual head was planted in randomized plots in two rows of a larger barley field.
In a larger barley study, Wenzl et al.[ 41] produced a 2935 loci composite map from ten mapping populations using JoinMap 3.0 [ 51] in combination with specially built Perl scripts and reported that the project required several months of semi-manual data processing [ 41].
Results of this study indicate a large variability in barley DE content between barley sources that was predicted more accurately by starch and ADF than bulk density.
Finally, association analysis using the haplotypes, parsimony tree edges, and single SNPs was conducted on heading date data collected on a large set of barley germplasm from the Barley CAP.
This means disproportionately large decreases in barley for brewing, "ultimately resulting in dramatic regional decreases in beer consumption and increases in beer prices".
In barley, large differences are observed in the LD decay pattern among cultivated accessions, landraces, and wild accessions (Caldwell et al. 2006).
Large genomes like barley and wheat show a gene density of about 5 genes per 23 kb [ 44] as it was suggested that the larger genomes would have accumulated non-coding sequences between the single-copy genes [ 45].
The focus of this study was to evaluate the potential of short read sequencing (SRS) in combination with mathematically defined repeat (MDR) analysis for surveying and draft annotating repetitive DNA in the large and complex barley genome.
Second, as large amounts of barley SNPs are becoming available [ 22], the number of genetically mapped genes will increase in the coming years, therefore improving the efficiency of the anchoring strategy.
For example, the large genome of barley (5,428 Mb) comprises up to 70% retrotransposons [ 47], while in the small rice genome (489 Mb) these elements represent only 17% of its total composition [ 48].
