Stutts - ANSC 4395 Breeding & Genetics - Test 3

Simply-Inherited Traits

traits affected by only a few genes

qualitative or categorical

affected little by environment

Quantitative

measured with numbers

Polygenic Traits

Affected by many genes with no gene having an overriding influence.

- EX: Growth rate, milk production, ribeye area

Typically quantitative or continuous in expression.

- Phenotypes are usually described by numbers

Greatly influenced by environment

Examples of Simply-Inherited Traits

Coat color, horns

Examples of Polygenic Traits

Weaning weights, milk yield, REA... CANT DO TEST MATINGS FOR THIS TYPE OF TRAIT

Threshold Traits

Polygenic traits that have categorical phenotypes

- Pregnancy, dystocia, gait

- Influenced by many genes but have an either/or result

Which traits are more important?

Polygenic traits, traits that determine profitability and productivity

EX) Growth rate, fertility, milk production

Niche markets

markets more sensitive to simply-inherited traits

Simply Inherited

Genetic Defects

Common characteristics of Polygenic and Simply Inherited

1. Both are subject to the same Mendelian Mechanisms: Law of Segregation and Independent Assortment

2. Affected by dominance and epistasis

3. Principles of selection and mating apply to both

- Attempt to increase frequency of desirable alleles

(More difficult to do with polygenic traits)

Function of the Number of genes involved

- The more genes involved, the more DIFFICULT it is to observe the effects of individual genes, and therefore the less specific info we have about those genes

- When a few or one gene affects a trait, the effects of those genes are well understood (Exact genotype may not be known, but a probable genotype may be identified.)

Test Matings

Matings designed to reveal the genotype of an individual for a small number of loci.

- used on simply inherited traits

- Have to characterize the net effect (breeding values, expected progeny differences)

Why test matings cannot be done on polygenic traits

Polygenic traits have so many different genes affecting them

- Cannot observe the effects of specific genes

An individual that is Aa will produce gametes

- Half will contain A, other half will contain a

- When populations are small, there may not be exactly half of each

Three types of test matings to determine if an individual is heterozygous

1. Mating to recessive

2. Mating to heterozygous

3. Mating sire to daughters (last resort)

Method with the highest probability of detection

Mating to recessive

- Probability of siring a recessive offspring is 1/2

If the condition is deleterious

- May be hard to find homozygous recessive

- Use known heterozygotes

- Probability of a recessive offspring is 1/4 or the probability of the offspring showing the dominant phenotype is 3/4

If heterozygous females are hard to find, then mate sire to daughters

- Assume the daughter's dams do not carry the recessive gene

- Probability that a daughter carries the recessive gene is 1/2 if sire is heterozygous

The probability of offspring showing the recessive phenotype is 1/8

- 1/4 is probability of homozygous recessive from mating heterozygotes

- 1/2 comes from half of the daughters of a heterozygous male are expected to carry the recessive gene

- Probability of dominant phenotype from this mating is 7/8

The probability of a heterozygous male having all normal offspring ______ rapidly as the number of matings _______

diminishes ; increases

- When many normal offspring result from these matings, it is said that male is not a carrier of gene

Most economically important traits are

quantitative

Quantitative Traits

- Measured on a numerical scale

- Under the influence of many genes and environment

- Express a continuous distribution from one extreme to another

- No discrete phenotypic classes like qualitative

bell curve (normal distribution)

A statistical distribution that phenotypes will closely approximate

- Allows us to use statistics to describe populations and their genetic makeup

Statistic

estimate of a parameter

Parameter

A value that describes a population (value or statistic)

Population

all the members of a group

sample

subset of a population

variable

whatever trait is measured on a group of individuals

- Generally given an algebraic identification

Why its called a "variable"

Because, in general, different individuals will have different values of measurement for that trait

discrete variable

has distinct classes (whole number)

EX. 3 of lambs born

Continuous Variable

for any 2 values, there is a possible intermediate value

EX. weaning weight and yearling weight

Two basic types of statistics for a single variable:

Measures of 1) central tendency and 2) variability

Mean (average)

main measure of central tendency

Median

- Other measure of central tendency

- Value with the same number of observations with larger values as the number of observations with smaller values

- Number in the middle

Mode

- Other measure of central tendency

-Most frequent value

Measures of variability

Standard deviation

Variance

Coefficient of variation

Standard Deviation

A measure of how widely distributed the observations are around the mean

- Symbolized with a "s" or sigma "o"

variance

Square of the standard deviation

- Symbolized as either s2 or o2

- Relatively little value by itself

- Useful for describing the genetic variability in a population

coefficient of variation

Standard deviation as percentage of the mean

- Useful for comparing the relative amounts of variation for various traits

2 statistics useful for determining if a relationship exists

Correlation and Regression

Correlation coefficient

The measure of the association between two variables (r XY)

VALUES OF R RANGE

-1 - strong negative correlation

0 - no correlation; indicates the 2 variables are unrelated or independent of each other

1 - strong positive correlation

Correlation

Calculation of the correlation coefficient

Terms in the denominator

- Are numerators for the variances of X and Y

- Called the corrected sum of squares of X and Y

Numerator

Called the corrected sum of cross-products

Regression Coefficient

- A measure of the linear relationship between variables x and y.

- Determination of which variable to call Y variable depends on how this is viewed

Y Variable

- Dependent variable whose value is dependent on the value of X

bYX

read as the regression of Y on X

Equation of a straight line:

Y = a + bX

Y = dependent or predicted variable

X = independent or predictor value

b = slope of the line or regression coefficient

a = the intercept, or the value of Y when X = 0

X and Y measurements for 2 traits

Y assigned to trait you wish to predict

X assigned to trait you wish to make the predictions of Y

Calculating the regression coefficient

- The numerator is the same as the numerator in the correlation coefficient

- The denominator is the same as the numerator of the variance of X

- Does make a difference which variable is X and which is Y

Regression Coefficient

Will have the same sign as the correlation coefficient, but is unrestricted in its magnitude

Regression - flat line

regression coefficient of 0

Regression - straight vertical (up and down)

regression coefficient of infinity

Regression intercept

-Represents the value of y when x=0

- Point at which the line crosses the vertical axis when the regression line is plotted

Regression line

Can be plotted by calculating several predicted values of Y using several values of X