Chapter 19 (M2) Flashcards
Discontinuous variation
- traits sharply defined and easy to categorize
ex. mendel’s peas, drosophila mutant phenos
Continuous variation
- pheno variation exists on a large numerical scale
Multifactorial trait
Genetic and non genetic variation affect trait
ex. developmental and environmental factors like nutrition
Genetic potential
transmitted by parents
may or may not be met
Polygenetic traits
determined by multiple genes
genes may contribute differently to the phenotype
Human eye colour (polygenetic)
major vs minor (modifier) genes
- OCA2 and HERC2 are two genes with strong influence (major genes)
- Other genes have minor effects on eye colour and are called modifier genes
Additive gene effects
- Multiple genes contribute an incremental amount of phenotypic influence
- Alleles of each additive gene can be assigned a value of contribution
5 questions of quantitative genetics
- How much is the phenotypic variation contributed by genetic
factors? - How many genes influence the specific phenotypic trait?
- How much does each of the genes contribute to the phenotypic
variation? - How do genes interact with each other to influence phenotypic
variation? - How do genes interact with environmental factors to influence phenotypic variation?
Multiple-Gene Hypothesis
think additive
The idea that alleles of multiple genes segregate and assort independently and impart additive effects on phenotype
first done by Hermann Nilsson-Ehle
Model for additive genes
(wheat plant kernel colour)
two genes (A, B)
two alleles (1, 2)
A1A1B1B1
- darkest colour
A2A2B2B2
- lightest colour
Phenotype Distributions with Additive Genes
Number of pheno categories and frequency of extremes
- Number of phenotypic
categories calculated as
2n + 1 where n = number of genes - Frequency of most
extreme phenotypes =
1/4^n
Pascal’s triangle
Number of events = # of alleles
ex. 3 genes x 2 alleles = 6 alleles
on pascal 7 phenotypes
Frequency of most extreme phenotypes
most rare
when they ask frequency of most extreme pheno, do frequency of one
ex. 1/64
Edward East length of corolla in tobacco plants
observations
Tall and short pure-breeding parents
Intermediate height F1
More variant F2
Continued selective breeding = eventually tall and short again
Edward East experiment results
- Trait is based on segregation of alleles from multiple genes
- Phenotypic variance seen in each generation due to environmental factors
Gene-by-Environment Factors on Phenotypic Variation
more gene-environment interaction
= wider distribution but same mean
Threshold traits
continuous distribution but two observed phenotypes
once you reach the threshold of genetic liability, you will be affected
Genetic liability
refers to alleles that push phenotypes towards threshold (affected end of spectrum)
Mean, median, mode
used to analyze distribution of continuous traits
Variance (s^2)
a measure of the spread of distribution around the mean
s^2 = sum (xi - xbar)^2 / df
Sum of square difference between each value and the mean divided by degrees of freedom
(number independent variables)
Standard deviation (s)
s = √ s^2
s = √ variance
Formula for phenotypic variance
Phenotypic variance (VP)
= genetic variance (VG) + environmental
variance (VE)
Genetic variance
genotypic contribution to phenotype
Environmental variance
environmental contribution to
phenotype
Parents, F1, and F2 calculations
- Parental pure-breeding lines:
VP = VE
(VG= 0) - Genetically uniform F1:
VP = VE
(VG= 0) - Genetically diverse F2:
VP = VE + VG
or
VG = VP - VE
2 things that make a wider variance of phenotypic values
- stronger environmental effects
- more diverse populations
Why are model organisms useful for studying in the laboratory
think genetic variation
- Use of inbred populations: VG = 0
(for each population) - Control environment in experiments:
VE approaches 0 - Therefore, phenotypic differences between
populations (strains) are genetic
Formula for genetic variance
VG = VA + VD + VI
Additive variance (VA)
Added effects of all alleles contributing to
trait
Dominance variance (VD)
contributions due to heterozygous individuals not having intermediate phenotype between two homozygous states
Interactive variance (VI)
epistatic interactions between alleles of
different genes
Heritability
The measure of the degree to which genetic differences contribute to phenotypic variation of a trait is called heritability
It’s important to note that heritability does not mean a trait is solely determined by genes, but rather how much genetic differences account for variations in that trait within a population
2 types of heritability and their formulas
significance of 0 to 1
- Broad sense heritability (H^2) = VG/VP
- Narrow sense heritability (h^2) = VA/VP
both expressed as a proportion that ranges from 0 to 1
* 1 = phenotypic variance very strongly explained by genetic variance
* 0 = little or no genetic variance contributes to phenotypic variance
4 caveats with heritability
4. High heritability does not preclude …
- Does not indicate mechanism by which genes control a trait, nor does it
indicate how much of a trait is produced by gene action (just does general genetic differences contribution) - Heritability values are accurate only for the environment and
population in which they are measured (can’t be generalized) - Heritability for a given trait in a population can change
- High heritability does not preclude environmental factors
Broad sense heritability - twin studies (mono vs di)
Identical twins (monozygotic, MZ) share all the same alleles
* Therefore VP = VE
Fraternal or dizygotic twins (DZ) are related like any other sibling
and share on average 50% of their alleles in common
* Therefore VP = VE + ½VG
Twin study H^2 caveats (3)
- Stronger maternal effects in MZ
- Parents treat MZ more similar than DZ
- More similarity in gene-environment interactions for MZ
Narrow sense heritability (h^2)
high h^2 = high or low degree of response to selection
the proportion of phenotypic variation due to additive genetic variation
high h^2 correlates with a greater degree to response of selection
Selection differential (S)
is the difference between the mean of
the whole population and the breeding population
S = x1 - x0
Response to selection (R)
depends on the extent to which the
difference between the population mean and the mean of mating
individuals can be passed on to progeny
x2 - x0
Response to selection formulas
R = S(h^2)
h^2 = R/S
Selection is strongest when h^2 = 1
Variables they use for response to selection
S = Ms – M
R = M’ – M
h^2 = R/S
Quantitative Trait Loci (QTLs)
genes/DNA regions that contribute to phenotypic variation in quantitative traits
QTL mapping - what is it
mapping QTLs to chromosome regions/linkage
groups
Chromosomal regions are identified through the co-occurrence of
a genetic marker (e.g. SNP) with a particular phenotype
QTL mapping - how to do it
- Construct genetic crosses between parental strains with different phenotypes
- Cross parentals to gather F1
- Cross either F1 together or backcross F1 to parentals
- Obtain a phenotype and genotype of all progeny
- Identify associations between phenotype and genotype at
individual loci - Develop DNA markers (eg SNPs) that differ between parental strains (that might be responsible)
Identifying QTL genes using introgression lines (ILs)
- Introgression lines are derived from backcross progeny by selectively
breeding inbred lines together - Carefully planned selective breeding can enable introgression lines to
have a similar genetic background - Most of their genome is similar; differences are at key locations of interest
- Introgression lines are basically recombinants and QTL mapping
uses genetic markers to locate where crossovers occurred to map a
gene - Analyze DNA sequence, SNPs, etc to determine if phenotypic variation correlates with differences in markers
Smallest interval on SNP map that correlates with phenotype
Look at two QTLs with variation in recombination between introgression lines
Relative trait difference
between introgression line and domesticated species (parental)
See map and pheno correlate
Degrees of kevin bacon gene
regulates an ordered social network
Social network tools were developed in 2012 to study how social
interactions are organized in Drosophila
- Two strains studied – Canton-S (CS) and Oregon-R (OR)
- CS and OR consistently differed in a phenotype called betweenness centrality (BC)
- BC is a social network measure that captures hubs in networks
- Higher BC = more individuals in the centre of network;
- BC, scored in social networks of other animals, including
humans, widely reported to be heritable
QTL Mapping Betweenness Centrality
- Years were spent generating introgression lines by crossing the CS
and OR strains together - SNPs used to track “CS-like” genomic regions and “OR-like”
genomic regions - Social behaviour measured for all recombinants, compared to CS
and OR flies in order to map the gene contributing to phenotypic
differences
dokb gene in narrowest interval that correlates
with behavioural data
