Association mapping methodology

1. ASSOCIATION MAPPING
WITH TASSEL
VG SHOBHANA

2. Genomics Effective tools
Identify genes in pathways
Alleles of agronomic traits Quite challenging
ASSOCIATION MAPPING
- high resolution
- to evaluate wide range of alelles rapidly

3. Genetic Linkage
 occurs when particular genetic loci or alleles for genes
are inherited jointly
 seen on the same chromosome
 are physically connected
 first discovered - British geneticists William Bateson
and Reginald Punnett
 Sturtvent - possiblility to obtain a measure for the
distance between the genes - linkage map
 A recombinant frequency (RF) of 1% is equivalent to
1 m.u.

4. Quantitative trait loci
 Inheritance of a phenotypic characteristic - varies in
degree - attributed to the interactions between two
or more genes and their environment.
 Stretches of DNA that are closely linked to the genes
that underlie the trait.
 QTLs can be molecularly identified (for
example, with PCR or AFLP) to help map regions of
the genome.
 This can be an early step in identifying and
sequencing these genes.
 Their phenotypes typically vary along a continuous
gradient depicted by a bell curve.

5. Differences: Linkage and Association
Linkage analysis Association mapping
 Recombination is the main
 Co- inheritance of force of elimination of
neighbouring DNA variants linkage.
(in both).  Recombination events occur
 Only few chances for over many generations.
recombination to occur.  Eliminated linkage between
 Low resolution of map. a mutated gene.
 Only very close markers are
in LD with the mutated gene.

6. QTL mapping is the statistical study of the alleles
that occur in a locus and the phenotypes (physical
forms or traits) that they produce.
Limitations of using natural populations:
 It requires the growth of three generations before
linkage analysis is possible.
 Very large segregating populations are needed to
achieve a high resolution map.
 The molecular markers may be specific
(polymorphic) to only one particular crossing family.

7. A complementary approach - to analyse Linkage
Disequilibrium in natural populations.
Successfully in humans - no large mapping families.
LD between two loci in natural populations - affected by
all the recombination events.
Have happened since the two alleles appeared in some
individuals of the population.
LD declines as the number of generations
increases, so that in old populations.
LD is limited to small distances.
This is desirable!!
Since a marker very close to a mutation responsible for
a disease makes it easier to reach the mutated
gene.

8.  Linkage disequilibrium is the correlation between pairs of
polymorphisms.
 One simple way to estimate linkage disequilibrium between pairs of sites
is to calculate r2.
 The average distance between polymorphisms, at which r2 drops below
0.1 - a rough estimate of the resolution.
 The rate of LD decay may also be locus specific as differences in
recombination rate, mutation rate, and selection history can affect LD
patterns.

9. -- LD measures the closeness of the genetic association
between markers and a particular trait.
-- May be used to identify markers in close proximity to
the gene(s) responsible for the trait.

10. Association mapping is good for,
 5000 times higher resolution than using F2 populations
 Surveys tens of alleles – while in standard methods –
only a maximum of two alleles
 Linkage disequilibrium and selection – keys to
association analysis
 Rely on
– the extensive history of mutation
– recombination to dissect a trait

11. Materials
Genotypic data
 100 genotypes from each cluster – no closely related lines.
 One line from one taxon only.
 Has to be as diverse it could be – Extensive recombination
history.
 50 - 150 markers in a non random mated population – Good
statistical power!!
– Modest number of SSRs
– large numbers of SNPs,
– AFLP may provide a good compromise
Phenotypic data?
– Across 2-3 seasons in replications

13. A standard procedure for association analysis on candidate genes:
1. Select positional candidate genes using existing QTL and
positional cloning studies
2. Choose germplasm that will capture the bulk of diversity
present. (When possible, use inbred lines)
3. Score phenotypic traits in replicated trials
4. Amplify and sequence candidate genes
5. Manipulate sequence into valid alignments and identify
polymorphisms
6. Obtain diversity estimates and evaluate patterns of selection
7. Statistically evaluate associations between genotypes and
phenotypes taking population structure into account

14. Sequence Manipulation Softwares
 Phred and Phrap
(http://www.codoncode.com/) - to assess sequence
quality and contig (join) sequences
 Biolign
(http://www.mbio.ncsu.edu/BioEdit/bioedit.html) - to
edit multiple alignments of contigs and evaluate
SNPs (custom software package)
 MegAlign from DNASTAR
 Sequencher from GeneCodes
(http://www.genecodes.com) offer similar features

15. Association Analysis Software
Population Structure: STRUCTURE (http://pritch.bsd.uchicago.edu)
Linkage Disequilibrium:
– Arlequin (http://lgb.unige.ch/arlequin)
– TASSEL (http://www.maizegenetics.net) (ANOVA and
regression analysis)
– PowerMarker (http://www.statgen.ncsu.edu)
– DnaSP (http://www.bio.ub.es/~julio/DnaSP.html)
STRAT
- (http://pritch.bsd.uchicago.edu) - for testing association of binary
traits across structured populations
SAS (http://www.sas.com) carries out a wide range of statistics useful
for association analysis.

16. TASSEL
Trait Analysis by
aSSociation, Evolution
and Linkage

17. Analysis Mode
Result Mode

19. ONLINE TOOL IN TASSEL

22. DATA MODELS IN EXCEL

23. LD Plot

24. DIVERSITY & CLUSTERS

25. Conclusions
1. Mapping with F2 or derived populations is powerful for
evaluating two alleles with low resolution.
2. Association analysis can evaluate numerous alleles at high
resolution.
3. These two approaches are complementary.
4. The successful integration - will allow the rapid dissection of
almost any trait within a few years time.
5. The key to association analysis is the choice of
germplasm, quality of phenotypic data, and use of statistical
analyses to control for population structure.
6. The combination of association mapping and QTL mapping
could make it routine to dissect complex traits.