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Printable Handouts
Navigable Slide Index
- Introduction
- What is animal breeding?
- Proposition 1
- A "complex" trait: many metabolic pathways
- Proposition 2
- Enzymes in the Krebs cycle
- Coping with complexity
- The Victorians
- Galton’s regression of offspring on parent
- Galton did not “see” concealed heterogeneity
- Pearson: ratio of forehead to body length in crabs
- Founders of modern genetics
- Systems of mating
- Fisher's influence
- “Micro-evolution” due to artificial selection
- Towards multivariate analysis
- The beginning of multi-trait quantitative genetics
- The genetic correlation (Hazel, 1943)
- Partition of non-additive variance
- Best linear unbiased prediction and MMM
- Gaussian mixed linear model
- Henderson's MME
- The "n smaller than p" era
- Good variance component estimates needed
- Historical progression: from simple to fancy
- Bayesian inference
- Bayesian inference and MCMC
- Bayesian methods in genetics: today
Topics Covered
- What is animal breeding?
- Quantitative traits are complex
- Epistasis is pervasive
- The Victorians
- Towards multivariate analysis
- The n<<p era
Links
Series:
Categories:
Talk Citation
Gianola, D. (2017, January 31). A brief history of statistical developments in animal breeding 1 - from Galton to Bayes [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved December 5, 2024, from https://doi.org/10.69645/TTJA9785.Export Citation (RIS)
Publication History
Financial Disclosures
- Prof. Daniel Gianola has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.
A brief history of statistical developments in animal breeding 1 - from Galton to Bayes
Published on January 31, 2017
29 min
Other Talks in the Series: Statistical Genetics
Transcript
Please wait while the transcript is being prepared...
0:00
Hello, my name is Daniel Gianola.
I'm a Professor
at the University of Wisconsin-Madison,
and I'm also
a Hans Fischer Senior Fellow
at the Technical University of Munich,
in Germany.
And today, I will be talking
about "A Brief History
of some Statistical Developments
in Animal Breeding".
I will cover about
100 years of developments.
0:24
So the first question is,
"What is animal breeding?"
By this, we mean the genetic improvement
of farm animals mostly,
animals that serve and enrich mankind.
The question is,
"What individual is best?"
For that, we need to define
some "merit function",
which typically will depend
on several traits.
The same happens in plant breeding.
For example, some variety of wheat
will depend not only on grain yield
but also on dry matter content,
resistance to disease,
resistance to wind,
and some other attributes.
In order to decide what animals
or individuals are best,
we take measurements,
such as milk production in dairy cows,
growth rates in animals.
We have genealogies or pedigrees
that trace animals
according to lines of descent.
More recently, molecular markers
that we know as SNPs, S-N-Ps,
single nucleotide polymorphisms.
In the future,
full DNA sequences,
and also post-genomic data,
such as gene expression,
level of methylation,
which are now available
for experimental purposes;
but have not been used
for predicting breeding value
of animals, yet.
Now, the data that we work with
in animal breeding
are largely observational
and retrospective.
They consist of farm records
that have been collected
directly on the farm.
And there is a notorious absence
of randomized experiments,
as in human medicine,
mostly because it's impossible
to carry out large animal experiments,
as it is impossible or very difficult
to randomize patients
into clinical trials.
Then, the question of evaluating
the merit of animals
becomes largely a statistical one.
And then, once we have evaluation
of the genetic merit of the candidates.
We decide, which will be selected?
How we are going to be mating
the selected animals?
Are we are going to be mating
relatives with relatives?
Or we are going to avoid
mating relatives?
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