The number of genomic scaffolds anchored to the perennial grass genome assembly.

<p>The number of genomic scaffolds anchored to the perennial grass genome assembly.</p

Using a Candidate Gene-Based Genetic Linkage Map to Identify QTL for Winter Survival in Perennial Ryegrass

<div><p>Important agronomical traits in perennial ryegrass (<i>Lolium perenne</i>) breeding programs such as winter survival and heading date, are quantitative traits that are generally controlled by multiple loci. Individually, these loci have relatively small effects. The aim of this study was to develop a candidate gene based Illumina GoldenGate 1,536-plex assay, containing single nucleotide polymorphism markers designed from transcripts involved in response to cold acclimation, vernalization, and induction of flowering. The assay was used to genotype a mapping population that we have also phenotyped for winter survival to complement the heading date trait previously mapped in this population. A positive correlation was observed between strong vernalization requirement and winter survival, and some QTL for winter survival and heading date overlapped on the genetic map. Candidate genes were located in clusters along the genetic map, some of which co-localized with QTL for winter survival and heading date. These clusters of candidate genes may be used in candidate gene based association studies to identify alleles associated with winter survival and heading date.</p></div

Details of the SNP-based linkage map.

<p>The F2-type map was built using only the SNPs which showed F2 type segregation. The final map includes all available SNPs, along with 57 previously mapped markers [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152004#pone.0152004.ref031" target="_blank">31</a>].</p

Spearman’s rank correlation coefficient for the traits winter survival (WS) and heading date expressed as growing degree-days to heading (GDDH 2004 and GDDH 2005).

<p>Spearman’s rank correlation coefficient for the traits winter survival (WS) and heading date expressed as growing degree-days to heading (GDDH 2004 and GDDH 2005).</p

Genome Wide Allele Frequency Fingerprints (GWAFFs) of Populations via Genotyping by Sequencing

<div><p>Genotyping-by-Sequencing (GBS) is an excellent tool for characterising genetic variation between plant genomes. To date, its use has been reported only for genotyping of single individuals. However, there are many applications where resolving allele frequencies within populations on a genome-wide scale would be very powerful, examples include the breeding of outbreeding species, varietal protection in outbreeding species, monitoring changes in population allele frequencies. This motivated us to test the potential to use GBS to evaluate allele frequencies within populations. Perennial ryegrass is an outbreeding species, and breeding programs are based upon selection on populations. We tested two restriction enzymes for their efficiency in complexity reduction of the perennial ryegrass genome. The resulting profiles have been termed Genome Wide Allele Frequency Fingerprints (GWAFFs), and we have shown how these fingerprints can be used to distinguish between plant populations. Even at current costs and throughput, using sequencing to directly evaluate populations on a genome-wide scale is viable. GWAFFs should find many applications, from varietal development in outbreeding species right through to playing a role in protecting plant breeders’ rights.</p> </div

Marker density in the candidate gene-based genetic map.

<p>The linkage groups are presented on the <i>x</i> axis. The <i>y</i> axis corresponds to the most plausible positions in cM on the final candidate gene based genetic map. The color scale illustrates the number of candidate genes mapped in intervals of 10 cM.</p

Distinguishing populations based on GWAFFs.

<p>Principle Component Analysis (PCA) of GWAFFs based on SNP positions having a minimum coverage of 5 in all samples. (A) and (C) GWAFFs based on allele frequencies of the variant allele at 21,942 SNP positions in ApeKI, (B) and (D) GWAFFs based on allele frequencies of the variant allele at 10,958 SNP positions in PstI. Colours in A and B correspond to the varieties; Beatrice (black), Chardin (Green), Stolon (grey), Greenway (sky blue), Glenveagh (dark blue), Sponsor (yellow), Mongita (purple), and Bronzyn (red). Colours in C and D correspond to type; forage (black), turf (red).</p

QTL for heading date expressed as growing degree-days to heading (GDDH) and for winter survival (WS).

<p>QTL signals below the genome wide 3.18 LOD value threshold of GDDH 2005 are presented in italics.</p

Perennial ryegrass genetic map consisting of candidate genes for vernalization and cold response.

<p>High confidence F2-type map presenting the F2 type markers (bold italics) based on which the QTL analysis was performed. The remaining markers are presented in bins. Markers underlined are common with the perennial ryegrass genetic map previously developed from a comprehensive Expressed Sequence Tag (EST) collection [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152004#pone.0152004.ref031" target="_blank">31</a>]. Markers presented in blue were positioned on the map based on co-location on the same genomic scaffold with a mapped marker.</p

Correlation between allele frequency estimates.

<p>Scatter plot matrices between ‘sample replicates’ from the variety Beatrice of the frequency of the variant allele at 1000 randomly selected SNP positions from each of three groupings (a) SNPs with coverage between 5 and 10X in all samples, (b) SNPs with coverage between 10 and 20X in all samples, and (c) SNPs with coverage greater than 20X in all samples. The x and y axis show the frequency of the variant allele. Least squares regression line is shown by solid green line, and Loess smooth is shown by broken red line.</p