Download Phenotypic Variance

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Dual inheritance theory wikipedia , lookup

Genetically modified food wikipedia , lookup

Fetal origins hypothesis wikipedia , lookup

Medical genetics wikipedia , lookup

Tag SNP wikipedia , lookup

Site-specific recombinase technology wikipedia , lookup

Gene expression programming wikipedia , lookup

Group selection wikipedia , lookup

Inbreeding wikipedia , lookup

Artificial gene synthesis wikipedia , lookup

Public health genomics wikipedia , lookup

Dominance (genetics) wikipedia , lookup

Polymorphism (biology) wikipedia , lookup

Genetic drift wikipedia , lookup

Genetic engineering wikipedia , lookup

Genome (book) wikipedia , lookup

Koinophilia wikipedia , lookup

History of genetic engineering wikipedia , lookup

Designer baby wikipedia , lookup

Human genetic variation wikipedia , lookup

Population genetics wikipedia , lookup

Behavioural genetics wikipedia , lookup

Twin study wikipedia , lookup

Microevolution wikipedia , lookup

Quantitative trait locus wikipedia , lookup

Heritability of IQ wikipedia , lookup

Transcript
Quantitative Genetics
and Multifactorial Traits
A field of pumpkins,
where size is under
the influence of
additive alleles
I. Quantitative Characteristics Vary
Continuously and Many Are
Influenced by Alleles at Multiple Loci
Qualitative characteristics
Quantitative characteristics
2
Quantitative (polygenic) traits whose
phenotypes result from both gene action
and environmental influences are often
termed multifactorial or complex traits
3
Not All Polygenic Traits Show
Continuous Variation

Meristic traits: the phenotypes are described
by whole numbers


The number of seeds in a pod, eggs laid by a chicken
Threshold traits: present or absent
4
The Multiple Gene
Hypothesis for
Quantitative
Inheritance
P1
F1
Nilsson-Ehle , 1909
Kernel Color in Wheat
The results of crossing
individuals heterozygous for
different numbers of loci
affecting a characteristic
6
Determining Gene Number for
a Polygenic Characteristic
Assumption:
• All the alleles
contribute equally
and additively;
• Phenotypes of F2 is
not affected
significantly by
environments.
7
II. Statistical Methods Are
Required for Analyzing
Quantitative Characteristics
8
Relations among
the methods of
studying quantitative
genetics.
9
Distribution

Phenotypic variation in a group can be
conveniently represented by a frequency
distribution
Numbers or
proportions
of individuals
phenotypic classes
10
Distributions of phenotypes can assume
several different shapes
Normal distribution
Skewed (不对称) and bimodal (双峰)
11
Samples and Populations

Samples


Be representative of the whole population
Be large enough
12
The Mean

The mean (average) provides information
about the center of the distribution
13
The Variance and Standard Deviation

Variance (方差)

The variability of a group of measurements
The variance (s2) is
defined as the average
squared deviation from
the mean.
14

Standard deviation (s) (标准差)
The standard deviation is often
preferred for describing the variability of
a measurement.
The proportions of a normal
distribution occupied by plus
or minus one, two, and three
standard deviations from the mean
15
Analysis of a quantitative character
• One of the tomato homozygous varieties produces fruit averaging 18 oz.
in weight, whereas fruit from the other averages 6 oz.
• Crossed these two homozygous varieties.
F1
Distribution of tomato weight
F2
626/52=12.04
872/72=12.11
1.29
4.27
1.13
2.06
12.04±1.13
12.11±2.06
The number of genes that control fruit:
F2: 1/4n=1/72, n=3~4
Correlation


The relation between two characteristics is
called a correlation
Correlations between characteristics are
measured by a correlation coefficient (r )
Covariance (cov)
(协方差)
17
The correlation coefficient describes the relation
between two or more variables
18
19
Regression (回归)
The regression
line can be
represented by
a is the y intercept of the line, which is the expected
value of y when x is 0.
b is the slope of the regression line, also called the
regression coefficient (回归系数)
20
The regression equation (y = a + bx ) can be used
to predict the value of any y given the value of x.
21
III. Heritability Is Used to Estimate
the Proportion of Variation in a
Trait That Is Genetic
The proportion of the total phenotypic
variation that is due to genetic differences
is known as the heritability
22
Phenotypic Variance (VP)

Components of phenotypic variance



Genetic variance: VG
Environmental variance:
VE
Genetic−environmental
interaction variance: VGE
23

Components of genetic variance



Additive genetic variance: V A
Dominance genetic variance:V D
Genic interaction variance:V I
24
Types of Heritability (遗传率)

Broad-sense heritability (H 2):

Narrow-sense heritability (h 2):
25
Calculating Heritability

Heritability by elimination of variance
components


In theory, we can make V E = 0 by raising all
individuals in exactly the same environment, then
VGE=0, VP=VG
Instead, we can make V G = 0 by raising genetically
identical individuals, then VGE=0, VP=VE
26
Ex am ple:
Estimate the heritability of white spotting in guinea pigs


Measured the phenotypic variance for white spotting in a
genetically variable population and found that VP= 573
Inbred the guinea pigs for many generations to get
homozygous and genetically identical individuals.
measured their phenotypic variance and got VP=340=VE.
27

Heritability by parent–offspring regression

Heritability and degrees of relatedness

…….
28
Artificial Selection



Artificial selection is the process of
choosing specific individuals with preferred
phenotypes from an initially heterogeneous
population for future breeding purposes.
Alleles that generate dominance effects (V D )
or interact epistatically (V I ) are less
responsive to artificial selection.
Narrow-sense heritability,h 2 , can be used to
predict the impact of selection
29
How to calculate narrow-sense heritability h 2 ?
The simplest approach is to select individuals with superior
phenotypes for the desired quantitative trait from a heterogeneous
population and breed offspring from those individuals.
selection response (R)
selection differential (S)
M : mean score for the trait of the original
population
M1: mean score of the selected individuals
used as parents
M2: mean score of those offspring
Realized
heritability
30
孵化率
受孕率
31
Theoretically, the
process will continue
until all individuals in
the population
possess a uniform
genotype that
includes all the
additive alleles
responsible for high
oil content. At that
point, h 2 →0
Response of corn selected for high and low oil
content over 76 generations.
The numbers in parentheses at generations 9, 25, 52, and 76 for the "high
oil line” indicate the calculation of heritability at these points in the
continuing experiment.
32
Artificial selection has produced
the tremendous diversity of
shape, size, color, and behavior
seen today among breeds of
domestic dogs.
33
Prediction Phenotypes
Ex am ple :
IQ score prediction
• Mother: 110
• Father: 120
• Mean of population: 100
IQs of their offsprings?
Narrow-sense heritability
(h2) of IQ=0.4
The predicted IQ value will be:
106 if h2 =0.4
115 if h2 =1
34
The Limitations of Heritability





Heritability does not indicate the degree to
which a characteristic is genetically determined
An individual does not have heritability
There is no universal heritability for a
characteristic
Even when heritability is high, environmental
factors may influence a characteristic
Heritabilities indicate nothing about the nature
of population differences in a characteristic
35
IV. Quantitative Trait Loci
(QTLs)

A chromosome region is identified as
containing one or more genes
contributing to a quantitative trait is
known as a quantitative trait locus (QTL)
36
A generic case of QTL mapping
•
Individuals from highly divergent lines created
by artificial selection are chosen as parents
•
These individuals are crossed to produce F1
and F2 generations. F2 generations carry
different portions of the P1 genome with
different QTL genotypes and associated
phenotypes. The F2 is known as the QTL
mapping population.
•
Measure phenotype of the trait among
individuals and identify genomic differences
among individuals by using DNA markers.
•
Computer-based statistical analysis is used to
search for linkage between the markers and a
phenotypic variation.
•
If a DNA marker is linked to a QTL, the marker
locus and the QTL are cosegregate.
•
When numerous QTLs for a given trait have
been located, a genetic map is created.
37
Annual Review of Genetics,
Vol . 27:205-233,1993
38
Methods to identify QTLs for fruit weight in tomatoes
Ancestral and modern-day tomato
39
RFLP and QTLs for fruit weight on four chromosomes in the tomato genome
40
• QTL mapping has identified more than 28 QTLs related to
this variation in fruit weight
• One QTL, called fw2.2 (on chromosome 2), was identified
accounting for about 30% of the variation in fruit weight
• A specific gene, ORFX, was identified within this QTL. A
cloned ORFX gene from small-fruited varieties is transferred
to a normally large tomatoes, the transgenic plant produces
fruits with reduced weight.
• ORFX gene encodes a protein
that negatively regulates cell
division during fruit development
• Yet ORFX and other related genes
cannot account for all the observed
variation in tomato size
-: control;
+: transgenic
41