1. Mapping Quantitative Trait Loci
Two approaches
Biparental mapping populations
Linkage analysis in unselected progeny of a cross
Genome wide association studies (GWAS)
Search for associations between markers and phenotypes in a panel of individuals that represent the gene pool of interest

2. Why map QTL?
Understand how genes control quantitative traits (trait dissection)
To aid in selection for a phenotype (Marker Assisted Selection = MAS)
Starting point for map-based cloning of genes
Conifer Genomics Learning Modules
Developed by Nicholas Wheeler and David Harry for the CTGN

3. QTL mapping – linkage analysis
Select two parents that are genetically diverse for the trait(s) of interest
Cross parents and develop a population of segregating progeny
Measure phenotypes
Score molecular markers
Construct a linkage map for the markers
Identify QTL that are linked to the markers
Observe segregation of genetic markers
See if individuals with different marker genotypes have different phenotypes
Oregon Wolfe Barley
Dom Rec

4. Advantages of biparental mapping populations
Derived from an F1 population, so for unlinked loci, “linkage” equilibrium is obtained with one generation of recombination
Effects of QTL are not correlated (confounded) with the effects of unlinked genes in the population
Simplicity
No more than two alleles per locus
For polymorphic loci, p = q = 0.5 (no minor alleles)
Note:
Other types of pedigreed populations can also be used for linkage mapping
Results from multiple mapping populations may be pooled together
These approaches may provide additional benefits, but analysis may be more complex

5. Disadvantages of linkage analysis approach
There is often only one opportunity for recombination, so estimates of map distances are imprecise
Large populations are needed to obtain rare recombinants (in practice, existing populations are often too small)
Alternatively, can random-mate the F2 for several generations before extracting lines, but this requires more time and expense
Must develop and maintain mapping populations that are often used solely for experimental purposes
e.g., resistant x susceptible (rather than resistant x resistant)
additional time and expense
Results are specific for each mapping population
only 2 alleles per locus are sampled

6. Common types of mapping populations
F2 population
Individual plants
F2:3 or F2:4 families
– families of F3 or F4 plants that trace back to an F2 individual
Backcross population
Recombinant inbred lines (RILs)**
Inbred lines obtained from an F2 population through single seed descent (without selection)  F6 or later generation
Doubled haploids (DH)**
Derived from male or female gametes of an F1 plant
F2 and backcross – advantage is simplicity and short time-frame for development; disadvantage is that they are heterozygous and subject to sampling variation
RILs – takes longer, but haplotypes are permanently fixed.
DH – system for production in tissue culture must exist. Haplotypes, with no residual variation.
**Populations of fixed haplotypes can be efficiently genotyped and permanently maintained

7. Linkage mapping - steps
Genotype the mapping population and prepare data
Calculate recombination fractions (RFs)
Maximum likelihood estimates of pairwise RFs
Group loci into linkage groups
Based on maximum allowable RF threshold
Apply LOD threshold (e.g., LOD > 3 indicates linkage)
Locus ordering
Begin with smallest RFs, and add others to minimize total size
Highest multipoint LOD among possible orders
Computer intensive
Multilocus estimation of map distances
Apply appropriate mapping function (Haldane, Kosambi)

8. Mapping functions When RF is small (≤ 15%), RF~cM
When RF is larger (>15%), then cM ≥ RF
Most mapping software includes map function adjustments
Haldane accounts for double crossovers
Kosambi also accounts for interference, which reduces chances of double crossovers
Source: Conifer Genomics Learning Modules

9. Software
>100 genetic analyses software packages (linkage analysis and QTL mapping)
Distinguishing features
Computer platform
Types of populations that can be handled
Mapping methods
Price
Common examples for linkage maps
Mapmaker/EXP
JoinMap
Common examples for QTL analysis
QTL Cartographer
R/qtl

10. Linkage map Oregon Wolfe Barley 175 DH lines 1328 SNP markers
1H H H H H H H
Linkage map
Oregon Wolfe Barley
175 DH lines
1328 SNP markers
Same map order with
82 maternal DH
93 paternal DH
Cistué et al Theoretical and Applied Genetics 122: 1399–1410.

11. QTL detection methods Single-marker analysis (SMA)
Consider one marker at a time
Simple statistical tests are used to compare phenotypes of marker classes (e.g. AA, Aa, aa)
Need to make adjustments for multiple tests
Does not require a linkage map
Can’t tell how close the marker is to the QTL
Observed phenotypes for marker classes will depend on the extent of recombination as well as the genotypic effect of the QTL
Can’t evaluate interactions among QTLs

12. QTL detection methods Simple interval mapping (SIM) – most common
Test for likelihood of a QTL at many positions (“sliding window”) between two mapped markers
Options to use a likelihood approach (best) or regression (faster)
Composite interval mapping (CIM)
Also uses a “sliding window”
QTL in other regions of the genome are used as covariates, so the effects of the QTL of interest can be estimated more precisely

13. Cercospora zeae-maydis
Y Q
161 F2:3 families
2 replicates, 2 locations
183 polymorphic SSR markers
Constructed linkage map
4 QTL identified using CIM
15 F2 recombinants within a major QTL were used for fine mapping
Gray leaf spot causes serious yield losses (20 – 60% or up to 100%) in maize worldwide
Y32 – resistant tropical inbred form Suwan1
Q11 – susceptible inbred derived from temperate hybrid
For fine mapping, selfed and backcrossed progeny of the 15 recombinants were phenotyped
Used mapmaker for linkage map (Kosambi mapping function)
Used QTL cartographer for QTL analysis, using composite interval mapping

14. QTL mapping of resistance to gray leaf spot in maize
Zhang et al., 2012
From Q11(S)
From Y32(R)
Disease ratings for GLS disease in four replicates for three genotype classes at the umc1913 marker
H2 for GLS resistance = 0.85
QTL-qRgls1 could enhance resistance by %