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Researcher school genetics / Forskarskule genetikk

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1440 Group work Who we are, what we know, and what we want. ... Fanfare!! In comes the clown?? RESEARCH SCHOOL GENETICS. NORWEGIAN UNIVERSITY OF LIFE SCIENCES ... – PowerPoint PPT presentation

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Title: Researcher school genetics / Forskarskule genetikk


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RESEARCH SCHOOL GENETICS / FORSKARSKULE GENETIKK
  • Tormod Ådnøy, leader
  • 5.9.2007

3
Welcome! Program today
  • 1415 On the Research school genetics at UMB.
    Tormod Ådnøy
  • 1438 Lille lørdag Åsmund Bjørnstad
  • 1440 Group work Who we are, what we know, and
    what we want. Groups of 3-5 participants.
  • 1455 Brief summing up by the youngest in every
    group.
  • 1500 Pizza, beer, .. (free) (Husdyrkantina)
  • Discussions over tables, and all together.
    (Genetic small talk permitted)

4
What we are
  • An application for funding (web - in Norwegian) /
    100.000 nok
  • But people and ideas are more important than
    money
  • Email list 42 PhD, 45 Advisors and researchers
  • Web page http//www.umb.no/22912
  • Preliminary board (3 PhD, 2 advisors)
  • Silje Brenna Hansen (PhD Cigene)
  • Marianne Haraldsen (PhD IHA Forskargruppe
    genetikk og avl)
  • Simen Rød Sandve (PhD IPM Genetikk og
    plantebiologi)
  • Morten Lillemo (postdoc IPM)
  • Tormod Ådnøy, leader research school (assoc.prof.
    IHA)
  • A secretary Anne Golten, IHA
  • This gathering today, and first Wednesday every
    month
  • Focus on PhD students

5
What we will be remains to be seen
  • Send an email for new participants to join the
    school
  • So far membership is not exclusive
  • Meetings are open
  • Peer review groups?
  • Reader groups?
  • Nordic collaboration?
  • Research grant applications?
  • Include MSc students?
  • ECTS for some activities?
  • Presentation of own work for others in the
    Research school
  • May help self-image
  • Will give useful training
  • Future courses in the Research school?
  • Summer courses?
  • ...

6
What I will talk about now
  • SCHOOL
  • Institution
  • Knowledge
  • Feeling ok
  • Clowns
  • Paradigms
  • GENETICS
  • Genes
  • DNA, mRNA, ..
  • SNP
  • Genotypes, haplotypes
  • Regulatory nets
  • BREEDING
  • Regression
  • Additive relationship

7
GENETICS
  • Gene
  • Gene maps, DNA, mRNA, , amino acids and
    proteins,
  • SNPs identifying genes in single individuals
  • We know a lot more now than some years ago
  • Molecular lab people have a lot of information
    and will have a lot more!How can it be used?
  • Can it be used to find the best future individual
    for a trait we want to improve?
  • What combination of genes is best?

8
How is the gene expressed in a trait?
  • We dont see a genes value, we see an
    individuals complete genomes value!
  • Genotype value for the trait
  • How do we express a genes value
  • or
  • How do we know which genes to combine to have a
    better individual in the future?

9
If two individuals were the same except two
alleles in a locus
  • We could say that the difference in the two
    individuals genotype values was the difference
    of the two allele effects
  • But the alleles may interact with other genes, or
    the environment
  • And normally we have a lot more differences
    between two individuals than just two different
    alleles

10
Numbers of genotypes
  • ..very many
  • How do we know which individuals/genotypes to
    select for future breeding?
  • What is you answer?
  • May we predict what value a not yet existing
    genotype (of infinitely many) will get for a
    trait?

11
.. to have better individuals in the future ..
  • Select for single gene effects
  • Select for haplotype effects
  • Select for combination of gene effects
    (dominance, epistasis, heterosis)?
  • Select for best genotypes today breeding

12
Casein genes in Norwegian goats
  • DNA from 436 bucks in national breeding scheme
  • Analyzed 39 snps (single nucleotide
    polymorphisms) in 4 casein genes (on same
    chromosome)
  • Haplotypes deduced from snp genotypes and
    relationship
  • Milk (kg), and protein-, fat-, lactose- from
    daughters in Goat dairy control
  • Hayes,Ben Hagesæther,Nina Ådnøy,Tormod
    Pellerud,Grunde Berg,Paul R. Lien,Sigbjørn
    (2006) Haplotype structure of casein genes in
    Norwegian goats and effects on production traits.
    Genetics 174, 455-464.

13
Casein snp genotypes excerpt of the 436 bucks
14
Results haplotypes effects on fat-, protein-
and milk, not significant for lactose
15
Results of single snp not significant
16
Finding gene effects / Number of genotypes
  • We deduced 21 haplotypes on bucks, and found
    additive effects on daughters production.
  • All possible combinations of 39 snps is 339gt1018,
    but number of individuals observed was 436. All
    genotypes may not be modeled, only the ones
    observed.
  • Modeling additive effects of all 39 snp-s
    simultaneously led to collinearity problems, but
    we could analyze for one snp at a time.
  • Even to find all haplotype combinations
    represented in a sample will be difficult
    212120/2231 potential genotypes. (Some
    haplotypes are rare.) How important is haplotype
    dominance?

17
BREEDING
  • To generate the best future individuals We want
    to change the population mean
  • Info used
  • Phenotypic observations
  • Additive relationship
  • ..best genotypes/ population (for a future
    environment)
  • Given
  • Existing populations,
  • Existing knowledge about the populations,
  • Existing techniques for breeding (AI, blup, ..)
  • Focus is on population, less on individuals

18
How do we know which individuals/genotypes to
select for future breeding?
  • Select best phenotypes Mass selection
  • Select individuals with best offspring
  • Other methods
  • Breeders use genes as an alibi they dont need
    them!
  • Statistics linear regression of offspring
    phenotypes on parents phenotypes
  • Additive inheritance of genes is a motive for
    relationship matrix
  • Include info on genes
  • Meuwissen, T. H. E., Hayes, B. J., Goddard, M.
    E. (2001). Prediction of total genetic value
    using genome-wide dense marker maps. Genetics
    157, 1819-1829.

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The infinitesimal model
  • Many genes
  • Small effects
  • Independently distributed
  • No change in gene frequency
  • Equilibrium of gene frequencies
  • All assumptions are violated in breeding
    programs, normally
  • Shaky foundation of Fisherian genetics SWO
  • Why does it work so well?

20
Additivity
  • A crucial question
  • To what extent are gene effects additive?
  • How does deviations from additivity affect the
    Parent-Offspring relationship Cov (P,O)
    0.5Additive variance ?

21
Genotype values
22
Genetic variance pure additive model
  • For two loci with two alleles each (H h K k), and
    only additive gene effects (in figure aH2 aK3,
    while ahak0)
  • Let Hi1 when H-allele is present, Hi0 when
    h-allele
  • Then the genotype value is
  • y(i,j) H(i)H(j)aH K(i)K(j)aK
  • (0, 2, 4, , 10 in figure)
  • The mean genotype value is
  • EY sum p(i,j) y(i,j) 2pHaH 2pKaK
  • The variance of the genotype values, with random
    mating and same disequilibrium in parents
    gametes (D dHKpHK-pHpK)
  • VY E(Y2)(EY)2 2pHphaH22pKpkaK24dHKaHa
    K
  • VY0 VYd
  • Avery, P. J. Hill, W. G. (1978). The effect of
    linkage disequilibrium on the genetic variance of
    a quantitative trait. Adv. Appl. Prob. 4-6. /
  • Ådnøy, T. (1981). Selection in few-locus models /
    Seleksjon i få-lokus modellar. PhD-dissertation
    at Dept Mathem Statist, Agric Univ Norway. 1-218.
  • Even in the additive model, disequilibrium over
    loci will change the variance.Linkage,
    selection, .. may lead to disequilibrium.

23
  • If selection is for an additive trait we should
    expect that the best allele is fixed in every
    locus
  • Should be no genetic variation left
  • This does not happen normally
  • There is genetic variation left for most traits
    even after much selection
  • Why?

24
Bridging the gap genes phenotypes (Cigene in
eVita)
  • Arne Gjuvsland (Cigene) PhD dissertation October
    2
  • linking regulatory gene networks to additivity
    and dominance

25
SCHOOL
  • To learn
  • Something is not known by students
  • It is normal that students dont know thats
    why they attend a school
  • The most important is the process in the
    students heads
  • Transfer of knowledge from lectures, books, ..
  • It helps to know what you already know
  • Generation of knowledge
  • Important science may generate new schools
    (paradigms)
  • The shaky foundations of Fisherian genetics
    SWO
  • Creativeness is good in a research school / new
    ideas

26
To feel OK
  • Emotions are important for learning
  • We learn more when we fell ok
  • We (most of us) need to know if what we are doing
    is good/relevant/useful/
  • We may not always rely on our self-evaluation
  • We need external evaluations
  • Norwegians are good at belittling themselves
  • We need to compare to what others do
  • What do you need to trust that you are doing ok?
  • If I tell you youre clever do you believe me?
  • Others input may correct our learning make us
    better students
  • Dont be afraid to tell what you dont know!
  • Helps other feel helpful / builds their
    self-image
  • Clowns help us relax
  • May help us see ourselves in a new light

27
I have talked about
  • Genetics
  • Breeding
  • School

28
Litle laurdag / Lille lørdag Wednesdaylittle
Saturday
  • Now professor Åsmund Bjørnstad will tell a story?
  • Fanfare!!
  • In comes the clown??

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Groups
  • Divide in groups

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GROUP ASSIGNMENT
  • Who we are
  • Present yourself to the group
  • Name, birth, occupation,
  • What we know
  • What techniques do you use? What courses are you
    taking?
  • Variance components, Linear models, Molecular
    lab, mRNA, micromatrices, HFA401,
  • How does your discipline find the best
    individuals for the future?
  • What we want
  • How can a research school be useful?
  • What can we contribute yourself and what can we
    get/buy from others?
  • Present two topics where you think our school may
    be helpful to the whole group at 1455. (By
    youngest in group.)

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Food and drink
  • Pizza
  • 8 assorted kinds
  • 1 vegetarian
  • 1 muslim
  • Salad with vinaigrette
  • One bottle of drink
  • Apple drink
  • Clausthaler Beer without alcohol
  • Green Tuborg
  • I need two voluntaries to help with the dishes
    afterwards

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