SNP genotyping
- Our original intent was to
genotype 1,536 of the highest priority SNPs.
- We established the feasibility
of using higher throughput technologies offered by Illumina (Figure
4).
- Given the cost per data point
of ~$0.05 USD for this new technology, we genotyped all three association
populations plus ~90 samples from two three-generation loblolly pine
pedigrees for 7,600 SNPs.
- The results established the
feasibility of the InfiniumTM technology within a conifer
species, were consistent with those from the GoldenGateTM
platform and yielded data sets ~3-fold greater in coverage of the functional
gene space of loblolly pine than those proposed originally (Table 4).
We have also placed ~2,000 of the candidate genes on the consensus linkage
map of loblolly pine.
| Population |
Purpose |
n |
No. SNPs |
No. CGs |
| QTL |
linkage |
91 |
1908 |
1749 |
| Base |
linkage |
94 |
1296 |
1644 |
| WeyCo |
association |
464 |
3952 |
3346 |
| NCSU |
association |
437 |
3938 |
3347 |
| FBRC |
association |
1003 |
in progress |
in progress |
Table
1. A summary of genotyping results by population. Only 493 SNPs
are shared between the two pedigrees (QTL and Base), thus allowing for
the potential of 2,711 SNPs to be placed on a linkage map. CG = candidate
gene.
Figure 1. A summary
of the pilot study used to assess the applicability of the Illumina
InfiniumTM platform to loblolly pine. (A) An exemplar example
of a high quality result. The test panel consisted of 24 individuals,
22 progeny and 2 parents from the QTL pedigree. Each point represents
a sample, with ovals enclosing samples within the same genotypic class.
Yellow points represent the genotypes of the parents. Since both parents
are heterozygous, the expected segregation pattern is 1:2:1. (B) A comparison
of the distribution of quality scores between the InfiniumTM
(green) and GoldenGateTM (red) platforms for the same samples.
Population structure analysis
- We chose 23 nuclear microsatellite
(SSR) markers within the loblolly pine genome that cover all 12 chromosomes.
- Genotyping was conducted for
907 individual trees comprising the WeyCo and NCSU populations.
- Using these data we employed
two different Bayesian clustering algorithms to identify structure:
1) STRUCTURE and 2) TESS. The reason for using two different algorithms
is that the one implemented in TESS is better at detecting clinal variation
rather than discrete clustering.
- The results indicate that
subtle, yet significant, amounts of population structure exist across
the range of loblolly pine. Most of this structure appears clinal in
nature (Figure 5A). However, it also appears that the levels of admixture
are highest on the southeastern flank of the Atlantic coastal plain.
This is consistent with expansion from Pleistocene refugia in southern
Florida and Mexico (Figure 5B).
- The levels of admixture (i.e.
the Q-values) have been supplied to all collaborators for use
as covariates in the linear models used for association mapping.
Figure
2. Patterns of population structure in loblolly pine. (A) An illustration
of STRUCTURE results in two dimensions, which were smoothed using universal
Kriging and general linear surface interpolation. (B) Patterns of population
structure as obtained using TESS. The upper graph is a Dirichlet tessellation
of the range map of loblolly pine, with polygons colored by inferred
membership in one of five clusters. The bottom graph is a stacked barplot
showing the membership of each sample in the five inferred clusters.
Those samples with the most admixture (i.e. colors) are those from the
southeastern portion of the Atlantic coastal plain.
