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0:00
I'm Fred van Eeuwijk,
and I'm working
at the Statistics Department
of Wageningen University
in the Netherlands.
And I will tell you today about
statistical genetical principles
that are useful
for plant breeders.
0:14
An overview of topics that
we'll be dealing with today,
at first I have a few slides
as a general introduction
to the topic,
then I will talk about
what I will call genotype
to phenotype models,
which we will see formed
as the major tool
in plant breeding.
And important parts, lets say,
of genotype by phenotype models
is actually the part
of the deals of the so called
the genotype
by environment interaction.
And we will be talking
a little bit about that.
Then, of course,
in plant breeding,
we use phenotypic data
for our modeling.
And I will say
a little bit about
how we get
those phenotypic data,
which experimental designs
we use,
and how we elaborate
those into statistical models.
Then, I will say
a few things about causal
and observational parameters
in statistics,
while we estimate
certain parameters
using our statistical models.
But in genetics,
we use sometimes
slightly different parameters
that are based on our IDs
about gene transmission,
how alleles are transmitted
through pedigrees
from parents to off spring.
Then, I will summarize
what we have done,
that's Intermezzo that you see.
We continue in deeper view
on what genotype
to phenotype models are,
and then we get two examples
of these genotype
to phenotype models.
We will talk about QTL mapping,
QTL mapping strategies
as an example of how to you use
genotype to phenotype models.
We will look at
an analysis of genotype
by environment interaction
by a model
that is called
Finlay Wilkinson model,
Finlay Wilkinson regression.
And then we will finish
with an example
of what we call
multi-environment trial
QTL mapping in which we use
a rather advanced
statistical model to find out
which genes and QTLs are driving
our phenotypic variation.
