Term
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Definition
*the value of an ind gen o fron how it influences their own pheno
*diff then how it influences progeny pheno |
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Term
| trait w/ no env influence (single- locus) |
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Definition
STEPS:
*replace one random allele for e. ind w/ a B allele and the 2nd w/ a random draw
*try to quantify the effect of B |
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Term
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Definition
*(pop pheno after you swap in an allele) - (pop pheno original)
*how much does swapping cause mean pheno (P-bar) to deviate
BV = Σ IGE |
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Term
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Definition
| BV = Σ IGE(A1,L) + Σ IGE(A2,L) n: total # loci that influence pheno L: locus A1,2: allele 1,2 for any particular locus |
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Term
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Definition
*sum of the effects of all alleles an ind has that influences a particular trait
*if know IGE, sum them up to get BV
*additive effect transmitted to next gen b/c parents pass alleles |
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Term
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Definition
BV-cap(o) = 1/2BV(sire) + 1/2BV(dam)
*each parent only passes 1/2 alleles so expected BV-cap should be average of parent 1 + parent 2
*works b/c BVs additive properties |
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Term
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Definition
*gene combination value
*non-additive effect from a combo of alleles in an ind so influences own P
*not transmitted to next gen |
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Term
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Definition
PROBLEM
*G is insufficient description of genetic merit b/c doesnt tell us how well an ind will breed for a partic trait
*we want to know how G influences progeny, but only tells us own |
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Term
| P = M + BV + GCV + E(P) + E(T) |
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Definition
PROBLEM
*some traits are not affected by yearly fluctuations and some traits dont have repeated performances
IMPORTANT
*for traits w/ repeated performance records |
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Term
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Definition
*an ind will only have a single performance
*have some narrow and broad sense herit |
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Term
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Definition
E(p)
*EX: developmental conditions
E(t)
*explains why the same animal can have diff productions per year
*EX: conditions during L1 |
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Term
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Definition
*PA
*ability of an ind to prod for a particular trait
*sum of genetics and perm env effects
PA = G + E(P) |
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Term
| Breeding goal and equations |
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Definition
*which equation to use depends on breeding objective
BV
*good for breeding
G
*good for production of non-repeated traits
PA
*good for production of repeated traits |
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Term
| purpose of genetic models |
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Definition
HWE MODEL (used for SIT)
1 = p^2 + 2pq + q^2
1) PREDICTION
*predicts the outcome of an experiment to see if breeding strategy will work
2) REVEAL WAYS TO ACHIEVE BREEDING OBJECTIVE
*helps find a relationship between allele and geno freq
*test crosses or genotyping ==> in order to cull carriers
GENETIC MODEL (used for quant)
P = M + BV + GCV + E
1) MAKE PREDICTIONS RELATED TO QUANT TRAITS
2) REVEAL FACTORS THAT INFLUENCE BREEDING FOR QUANT TRAITS
3) REVEAL OPTIMAL WAYS TO ACHIEVE BREEDING OBJECTIVES |
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Term
| heritability (general def) |
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Definition
*pheno resemblance between relatives; relatives have same P
*pheno values are passed on
*the extent to which relatives resemble one another
*relatives can look like e.other b/c share alleles @ higher rate as opposed to random memb of pop
-b/c relatives share alleles, they have correlated BVs
(sum of allelic effects)
↑ h^2 = ↑ pheno resemblance
*parents and offspring share strong resemblance
*assuming no assortitative mating (EX:not considering inc height mated w/ inc height)
*max slope is 0.5 b;c only half come from 1 parent
↓ h^2 = ↓ pheno resemblance
*parent and offspring don't resemble e. other |
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Term
| heritability (math def #1) |
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Definition
*h^2 = (correlation coeff,r)^2
-RANGE: 0 ≤ x ≤ 1
--> r=1: perfect correlation between BV and P (so
E=0, etc.)
-[COV(BV,P) / (σbv)(σP)]^2
*a pop measure of the strength/correlation of the relationship between P and BVs for a trait in a pop
-BV (determined at fert) predicts P
*explains general def b/c in high heritability(↑ h^2), relatives have same alleles so have correlated BVs ==> BV is strong predict P |
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Term
| heritability and selection |
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Definition
*if an ind has ↑ h^2, strong correlation between BV and P
*so if pick ind w/ best pheno values, they should also have best BV
*pheno is a good indicator of BV for selection |
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Term
| factors that influence pheno variation |
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Definition
PHENO VARIANCE
*variance- used to quantify amount of variation in values for a pop
*what influence the amount of σ^2(P) in a pop: the higher the σ^2(G) OR σ^2(E) in a pop means more P |
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Term
| heritability (math def #2) |
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Definition
*the proportion (ratio) of pheno variance in a trait that is attributable to variation in BVs for that trait
h^2 = σ^2(BV) / σ^2(P)
RANGE: 0 ≤ x ≤ 1
*H^2 cant be - b/c variance is always +
*BV is a component of pheno, so BV cant be greater than P
↑ h^2
*components of the pheno variance are low b/c the ratio will be close to 1
*ret of pheno variation for a trait is due to ind diff in BV as opposed to E or GCV |
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Term
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Definition
*equations equal e.other mathematically if components are independent
*equations are diff logically and give diff understanding of herit in genetics
*if given h^2, can predict the behavior of a trait in a pop |
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Term
| heritability (math def #3) |
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Definition
h^2 = b(BV,P) = COV(BV,P) / σ^2(P)
READ AS: of BV(y axis) on P(x axis)
*slope of the relationship between BV and pheno values
*used to make predictions
*use h^2 to predict an ind BV from P
-use prediction equation
-mean BV, G, GCV etc = 0 b/c are expressed as
deviations from mean
-we expect ___% of pheno deviations to be from BV |
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Term
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Definition
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Term
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Definition
FOR A SING IND
P = M + BV + GCV + E(P) + E(T)
P: the pheno value of 1 ind for 1 trait
FOR A POPULATION
σ^2(P) = σ^2(BV) + σ^2(GCV) + σ^2(EP) + σ^2(ET)
P: the amount of pheno variation in a pop |
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Term
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Definition
*e. ratio tells us something diff about a particular trait
*if know h^2, H^2, and rep: can predict how a trait behaves in a pop
NARROW SENSE HERITABILITY
h^2 = σ^2(BV)/ σ^2(P) = r(BV,P)^2 = b(BV,P)
*represents the extexnt to which reatives resemble e.other
*inc resemblance = ↑ h^2 (relatives share alleles -> same BV -> sim P)
BROAD SENSE HERITABILITY
H^2 = σ^2(G) / σ^2(P) = r(G,P)^2 = b(G,P)
*represents the total amount of pheno variation due to genetics as opposed to env effects
*NATURE VS NURTURE- to what extent is the P of an ind due to genetics (nature) or env (nurture)
REPEATABILITY
rep = σ^2(PA) / σ^2(P) = r(PA,P)^2 = b(PA,P)
*amount of pheno variation due to diff in PA
*↑ rep = not much variation in E(T) so have repeated performances for a trait
RANGE: 0 ≤ x ≤ 1
0 ≤ h^2 ≤ H^2 ≤rep ≤ 1 |
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Term
predicting behavior
GIVEN: low h^2, high H^2 |
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Definition
*lots of variation due to genetic effects, env has small influences
*BUT relatives would not have strong resemblance b/c combo of alleles is not passed on
-trait is still strong genetically determined |
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Term
predicting behavior
GIVEN: low h^2, mod H^2, high rep |
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Definition
*mostly influenced by env
*trait should behave
- relatives mot resemble b/c additive effects that are passed to next
gen are a minor contrib
- repeated performances for the same ind would be very similar b/c the
ind PAs would be primarily determined by E(P) (trait is highly
repeatable) |
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Term
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Definition
↑ REP
*repeated performances for a trait will be very similar to e.other
*single pheno record is a good indicator of future pheno records
↓ REP
*doesnt tell much about what subsequent performances would be like |
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Term
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Definition
1) strength of the relationship between sing pheno records and PAs
- if strong correlation (PA good
predictor of P) theres very little
E(T)
2)slop of relationship between single pheno records and PAs
*can predict PA from a single P (pheno
record)
3) proportion of pheno variation due to variatio in PAs
* ↑ ratio means most pheno variation is
due to ind PAs, and not due to E(T) |
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