COURSE

GUIDE

ANP 507
ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT
(2 Units)

Course team Dr. C. E. Isidahomen (Writer/Developer)

Ambrose Alli University Ekpoma

NATIONAL OPEN UNIVERSITY OF NIGERIA

ANP 507 COURSE GUIDE

© 2023 by NOUN Press

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Printed 2023

ISBN: 978-978-058-416-2

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ANP 507 COURSE GUIDE

CONTENTS PAGES

Introduction ………………………………………. iv
What You Will Learn in This Course …………… iv
Course Aim ……………………………………… iv

iii
ANP 507 COURSE GUIDE

INTRODUCTION

The course ANP507 (Animal Breeding and Livestock Improvement), is

a two (2) credit unit course designed for 500 level undergraduate
students pursuing a degree in Agricultural Science. The course is
expected to provide a good knowledge base for the future manpower for
genetic improvement of Nigerian livestock resources towards a
sustainable production of livestock. It explains the rudimentary
Production traits, their measurement and evaluation, selection for
breeding for improvement of livestock performance. Breeding
systems and selection methods. Performance testing, progeny testing..
The course also provides basic knowledge for biotechnological.
Identifying and incorporating genetic markers and major genes in
animal breeding programmes. DNA tests and segregation analysis for
genetic disorders. Determining associations between genetic markers
and quantitative test loci (QTL) applications in livestock genetic
improvement and the development of genotypes that are adapted
to Nigerian environment. The course will provide a basic foundation for
students intending to take up Animal breeding and Livestock
Improvement as a Career in the future. The course is divided into seven
(7) units with unit one to seven units. Each unit begins with a clear
introduction and statement of objectives followed by the main content.
The conclusion, summary and references (for further reading) were also
provided for each unit. Tutor marked assignments were provided for
each unit to enable you attempt some questions on the topics treated for
onward submission to your tutor. The Course Guide provides you with
access to brief information and overview of the course content, course
duration, what you are expected to know in each unit, what course
material you need to use and how you can systematically go through
the course materials.. Thus, we intend to achieve the above through the
following broad aim and other specific objectives.

COURSE AIM

The major aim of this course is to treat the fundamental principles of

animal genetics and breeding through the highlights of the basic
knowledge of breeding and livestock improvement. Using Production
traits, their measurement and evaluation, selection for breeding
for improvement of livestock performance. Breeding systems and
selection methods. Performance testing, progeny testing. Identifying
and incorporating genetic markers and major genes in animal
breeding programmes.DNA tests and segregation analysis for
genetic disorders. Determining associations between genetic markers
and quantitative test loci (QTL).

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 MAIN
COURSE

CONTENTS PAGE

Module 1 Production Traits, Their Measurements

and Evaluation…………………………………. 1

Module 2 Selection for Breeding for Improvement

Of Livestock Performance…………………… 2

Module 3 Breeding Systems and Selection Methods…….. 7

Module 4 Performance Testing and Progeny Testing…… 12

Module 5 Identifying And Incorporating Genetic

Markers and Major Genes in Animal
Breeding Programmes………………………. 19

Module 6 Dna Tests……………………………………….. 30

Module 7 Determining Associations Between Genetic

Markers And Quantitative Trait Locus (Qtl)… 40
ANP 507 MODULE 1

MODULE 1 PRODUCTION TRAITS, THEIR

MEASUREMENTS AND EVALUATION

The purpose of animal breeding is not to genetically improve

individual animals once an individual is conceived; it is a bit late
for that-but to improve animal populations, to improve future
generations of animals. To this task breeders bring two basic tools:
selection and mating. Both involve decision making. In selection,
we decide which individuals become parents, how many offspring
they may produce, and how long they remain in the breeding
population. In mating, we decide which of the males we have
selected will be bred to which of the females we have selected.
This chapter examines both kinds of decisions from a broad
perspective. Cattle Beef/milk productions. (Pregnancy, Calving
ease, Birth weight, Weaning weight ,Yearling weight, Mature
weight, Hip height, Pelvic area, Feed conversion (feed per
gain),Scrotal circumference, Breeding soundness, Back fat
thickness, Days dry, Calving interval, Milk yield ,Fat in milk (%)
,Protein in milk (%)) Horses (Wither height, Mature weight, Time to
trot 1 mile Time to run ~ mile Time to run 1 mile Weight started (draft)
Cutting score, Placing (in a race or show) Winnings), Swine (Pregnancy,
Litter size (number born alive) Litter size (number weaned) Weaning
weight, 21-day litter weight Days to 230 lb, Feed conversion (feed per
gain) Loin eye area Back fat thickness),Sheep(Pregnancy, Number born,
Birth weight ,60-day weaning weight Yearling weight, Loin eye area,
Grease fleece weight, Clean fleece weight Staple length, Breeding
soundness, Poultry(Number of eggs in first year (layers) Egg weight
(layers),Hatchability (chickens),Feed conversion ratio (broilers), Hot
carcass weight (broilers), Mature body weight (broilers), Shank length
(turkeys) Breast weight (broilers).

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ANP 507 MODULE 2

MODULE 2 SELECTION FOR BREEDING FOR

IMPROVEMENT OF LIVESTOCK
PERFORMANCE

CONTENTS

1.0 Introduction
2.0 Objectives
3.0 Main Content
4.0 Conclusion
5.0 Summary
6.0 Tutor-marked Assignment
7.0 References/Further Reading

1.0 INTRODUCTION

1 Measuring Performance

In order to select animals, we must first measure performance

(phenotype) on eligible candidates for selection. Systematic
measurement of performance in a population is called performance
testing. Performance testing programs vary among species and
breeders within species. A progressive beef cattle breeder's
program, for example, might include the recording of birth date,
calf birth weight and calving ease score at calving time; weaning
date, calf weaning weight, cow weight, and cow pregnancy status
at weaning time; feed intake from weaning to yearling age; and
weigh date, yearling weight, hip height, pelvic dimensions, back fat
thickness or ultrasound measurements, scrotal circumference, and
breeding soundness score at yearling time.

Performance Testing: Systematic measurement of performance

(phenotype) in a population.

Performance testing programs are widespread in traditional livestock

species (beef and dairy cattle, swine, poultry, and sheep) in
developed countries. Seed stock producers commonly take part in
such programs, reporting the data they record to breed
associations or government agencies. Commercial producers may
do performance testing also. However, because of the labor
and expense involved in recording performance data, commercial
testing programs are typically less elaborate than seed stock
programs. Listed in Table 1.1 are traits commonly measured in
several species?

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

2.0 OBJECTIVES

 You will understand what production traits means

 You will understand their measurement and evaluation

3.0 MAIN CONTENT

3.1 Measuring Performance

In order to select animals, we must first measure performance

(phenotype) on eligible candidates for selection. Systematic
measurement of performance in a population is called performance
testing. Performance testing programs vary among species and
breeders within species. A progressive beef cattle breeder's program,
for example, might include the recording of birth date, calf birth
weight and calving ease score at calving time; weaning date, calf
weaning weight, cow weight, and cow pregnancy status at
weaning time; feed intake from weaning to yearling age; and
weigh date, yearling weight, hip height, pelvic dimensions, back
fat thickness or ultrasound measurements, scrotal circumference,
and breeding soundness score at yearling time.

Performance Testing: Systematic measurement of performance

(phenotype) in a population.

Performance testing programs are widespread in traditional

livestock species (beef and dairy cattle, swine, poultry, and
sheep) in developed countries. Seed stock producers commonly
take part in such programs, reporting the data they record to breed
associations or government agencies. Commercial producers
may do performance testing also. However, because of the
labor and expense involved in recording performance data,
commercial testing programs are typically less elaborate than seed
stock programs. Listed in Table 1.1 are traits commonly measured in
several species?

Selection Using Information on Relatives

Most animal breeders are unlikely to limit themselves to

individual performance information alone in making selection
decisions. They will use information on relatives as well. For
example, when a dog breeder purchases an eight-week-old puppy
from another breeder, she probably does not base her choice on
just the conformation and personality characteristics evident in such
a young puppy. She wants to evaluate those same traits in the

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ANP 507 MODULE 2

littermates, the dam, and the sire. She might want to see a copy of
the puppy's extended pedigree to learn more about its ancestors.
Similarly, when beef cattle breeders evaluate a sire to use via
artificial insemination (A.I.), they look further than the sire's
own performance for growth rate. They want to know something
about the growth performance of his progeny.

Dam: A female parent. Sire: A male parent

The above examples illustrate the use of two different types of

information (data) on relatives: pedigree data and progeny data.
By examining the young puppy's parents, littermates, and
extended pedigree, the dog breeder is using pedigree data. She is
trying to learn something about the genes made available to the
puppy through its parents. Beef cattle breeders, on the other
hand, are using progeny data. They are trying to learn something
about an A.I. sire's genes by evaluating the performance of his
offspring.

Pedigree Data: Information on the genotype or performance

of ancestors and (or) collateral relatives of an individual.

As the above examples should make clear, the information

used to make Selection decisions can be subjective, objective, or
something in between. The pedigree data used by the dog breeder
are, for the most part, subjective. The puppy's Papers may include
some semi objective information on show championships won by
ancestors, but the breeder's observations on conformation and
personality are essentially subjective in nature. In contrast, the
progeny data used by beef cattle breeders are relatively objective.
They consist of carefully measured (we hope) weights of animals
taken at specific ages.

Table 1.1 Commonly Measured Traits

Species Trait
Cattle (beef): Pregnancy
Calving ease
Birth weight(kg)
Weaning weight(kg)
Yearling weight(kg)
Mature weight(kg)
Hip height(cm)
Pelvic area (cm)
Feed conversion (feed per gain)
Scrotal circumference(cm)

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

Breeding soundness
Back fat thickness (cm)

Cattle (dairy) Days dry

Calving interval Milk yield
Fat in milk (%)
Protein in milk (%)

Horses: 1 Wither height

2 Mature weight
3 Time to trot 1 mile
4 Time to run ~ mile
5 Time to run 1 mile
6 Weight started (draft)
7 Cutting score
8 Placing (in a race or show)
9 Winnings
Swine 1 Pregnancy
2 Litter size (number born alive)
3 Litter size (number weaned)
4 Weaning weight
5 21-day litter weight
6 Days to 230 lb
7 Feed conversion (feed per gain)
8 Loin eye area
9 Back fat thickness
Poultry 1 Number of eggs in first year (layers)
2 Egg weight (g) (layers)
3 Hatchability (%) (chickens)
4 Feed conversion ratio (broilers)
5 Hot carcass weight(kg) (broilers)
6 Mature body weight(kg) (broilers)
7 Shank length (cm) (turkeys)
8 Breast weight (kg) (broilers)
Sheep: 1 Pregnancy
2 Number born
2 Birth weight
3 60-day weaning weight
5 Yearling weight
6 Loin eye area
7 Grease fleece weight
8 Clean fleece weight
9 Staple length
10 Breeding soundness

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ANP 507 MODULE 2

6.0 TUTOR MARKED ASSIGNMENT

1. Explain how selection causes changes in the performance of

future generations of a population
2. Why is a selection generally more effective for highly heritable
traits than for lowly heritable ones?

7.0 REFERENCES/FURTHER READING

Richard, M Bourdon (2000).Understanding

Animal Breeding 2ndEdition. Pp 1-538

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

MODULE 3 BREEDING SYSTEMS AND

SELECTION METHODS

CONTENTS

1.0 Introduction
2.0 Objectives
3.0 Main Content
4.0 Conclusion
5.0 Summary
6.0 Tutor-marked Assignment
7.0 References/Further Reading

1.0 INTRODUCTION

Selection: The process that determines which individuals become

parents, how many offspring they produce, and how long they
remain in the breeding population. Selection is the process that
determines which individuals become parents, how many
offspring they produce, and how long they remain in the breeding
population. Most of us are familiar with the term natural
selection. Natural selection is the great evolutionary force that
fuels genetic change in all living things. The term conjures up
visions of fossil records, species creation, gradual anatomical
and physiological changes, and mass extinctions. We
commonly think of natural selection as affecting wild animals
and plants, but in fact it affects both wild and domestic species.
All animals with lethal genetic defects, for example, are naturally
selected against-they never live to become parents. Animal
breeders cannot ignore natural selection, but the kind of selection
of primary interest to them is called artificial selection;
selection that is under human control. Artificial selection has
two aspects: replacement selection and culling. In replacement
selection we decide which individuals will become parents for the
first time. Replacement selection gets its name from the fact that
we select new animals to replaceparents that have been culled.
These new animals are termed replacements.

Animal breeders cannot ignore natural selection, but the kind of

selection of primary interest to them is called artificial
selection; selection that is under human control. Artificial
selection has two aspects: replacement selection and culling. In
replacement selection we decide which individuals will become
parents for the first time. Replacement selection gets its name from
the fact that we select new animals to replace parents that have been
culled. These new animals are termed replacements.

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ANP 507 MODULE 3

Natural Selection: Selection that occurs in nature independent

of deliberate human control.

We normally think of replacements as being young animals. When

you choose the pups in a litter, the lambs in a flock, or the calves
in a herd to be kept for breeding purposes, you practice
replacement selection with young animals. Broadly speaking,
however, replacement selection need not be confined to young
animals. If you were a dairyman and you chose to use for the first
time a well known bull via artificial insemination (A.I.); you would
still be practicing replacement selection. The bull is not young, nor
will he be a parent for the first time, but he will be a parent for the
first time in your herd.

2.0 OBJECTIVES
 You will understand breeding systems
 You will understand the selection methods
 You will understand the merit and demerit breeding systems and
selection methods

3.0 MAIN CONTENT

3.1 Selection methods

This is the methods used by breeders to make

long-term genetic change in animals.

(a) Tandem: is selection for one trait at n time

improved, then for another? This is the most
efficient method if only one trait needs
improvement. With more traits it is inefficient.
(b) Independent culling: can be applied for two or
more characters.
A minimum level is established for each trait
below which animals are culled. Animals which
satisfy requirements for all traits are retained. The
number of animals which can be kept decreases as
the number of traits under consideration increases.

(c) Selection index: is the most efficient method. It

uses one single value for any number of traits,
each of which is weighted by its economic
value. The value I equal the sum of traits
each of which is multiplied by a certain
factor b (regression coefficient).

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 ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

I = b1X1 + h2X2 +…… +1bnXn

To construct a selection index information is needed on
the phenotypic and genotypic covariance) gross and
genetic correlation) between each pair of traits, and
then of course the economic values (b).
All three methods of selection are also called mass or
individual selection because selection is based on the
individuals record. Mass selection is simple, easy and
effective with high heritability.

Selection systems: Besides individual records information

on relatives is used or instead. This applies when
traits are measurable in every individual (growth
rate). Records on relatives must be used in two cases.

(i) For sex-limited traits (milk production, egg

production);
(ii) For data becoming available at slaughter (carcass
traits).
(a) Family selection: Is used when comparing
average performance of families (litters) and
selecting whole families, no matter whether
there are outstanding or poorer individuals in the
group. It is used when heritability of trait (s) is
low, when there is little variation in the
common environment, when families are
large. However, intensity of selection is
lowered, much space is needed for many
animals, and some danger of inbreeding is
involved Figure : shows family selection (From
Johnsson-Rendel, 1968)

Family
Average daily gain in grams x
1 B CD 645
2 G H 675
3 KL 666
4 NOP 680
5 RST 656
„600„625„650„675„700, 725,750 656

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ANP 507 MODULE 3

If 8 animals are selected, the two best families (2

and 4) are taken. Questions: What was the selection
differential?

(b) Within Family Selection: (From Falconer,

1970).If 10 animals are needed, you select the
two top individuals in each family, no matter
how high or low the family average is.
Note: Individual or mass selection would be the
choice or the best performers.
(c) Combined selection: applies both procedures.(d)
Sib selection: uses information from sib
(full brother or sister) average excluding the
individual under consideration, while in family
selection it is included. The above systems are
based on information from contemporaries or
collateral relatives.

(e) Progeny or offering averages: can be used for

selection of a parent. It is widely applied in
progeny testing (to be discussed later). This
system lengthens the generation interval,
involves large numbers of animals and is time –
and space consuming.

(f) Pedigree selection: can only be used

together with other information, or if alone
in the case no other information available.
Ancestors‟ performance records become
less important the farther they are removed in
the pedigree.

(g) Recurrent selection: is a scheme which

selects for combing ability by testing crosses
of individuals form one population (line)
against those forms a tester line which has a
proven combining ability. The tester line is
usually high inbred. Individuals in the line tested
are selected on the basis how well they cross.
Crossbreds, but this will depend on the
purebreds used; some do not combine well.

(h) Reciprocal recurrent selection (RRS): involves

animals of two populations tested against each
other by reciprocal crossing, improving each
line simultaneously on the crossbred

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 ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

performance. There is no tester line. The two lines

need not be highly inbred. But again purebreds
are selected, not crossbreds.

7.0 REFERENCES/FURTHER READING

Falconer, D.S. (1970). Introduction to Quantitative

Genetics. Oliver and Boyd.

Johansson, I. and J. Rendel. (1968). Genetics and

animal Breeding. Oliver and Boyd.

Lerner, I..M. 1958. The Genetic Basis of Selection.

Campanand Hill.

Richard, M Bourdon (2000).Understanding

nd
Animal Breeding 2 Edition. Pp 1-538

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ANP 507 MODULE 4

MODULE 4 PERFORMANCE TESTING AND

PROGENY TESTING

CONTENTS

1.0 Introduction
2.0 Objectives
3.0 Main Content
3.1 Performance testing
3.1.1 Performance Testing Procedure
3.2 Progeny testing
3.2.1: Progeny Testing Procedure
3.2.3: Factors that affect the usefulness of Progeny Testing
4.0 Conclusion
5.0 Summary
6.0 Tutor Marked Assignment
7.0 References/ Further Reading

1.0 INTRODUCTION

The performance test on individuals and on brothers and sisters is

used to determine which animal will be selected for breeding purposes.
These male animals are then progeny tested as the final test of breeding
value. One of the most important consequences of performance testing
is that it leads to the scrutinization of the relative importance of the
different traits for which we select. This not only applies to measurable
but also to immeasurable attributes. In pigs for instance, performance
testing has highlighted the importance of good legs and the enormous
problem the pig industry has in this respect. The same applies to
excessive folds in Merino sheep in harsh environments. Animal
breeding is extremely complex in the sense that different characteristics,
some positively correlated, some negatively correlated and others un-
correlated, some very important, others less important, make up the total
economic and breeding worth of an animal. Without figures it is
virtually impossible to select sensibly for such a very complex
combination. Also bear in mind that the economic value and the
breeding value of an animal is not necessarily the same thing, as some
traits are readily passed on to the offspring while others have a low
heritability.

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

2.0 OBJECTIVES

 You will understand performance testing and procedures

involved
 You will understand the merit and demerit of performance testing
 You will understand progeny testing and its procedures
 You will understand the merit and demerit of performance testing

3.0 MAIN CONTENT

3.1 Performance testing

Performance testing today forms the basis of breed improvement of

nearly all kinds of livestock in all the developed Western countries of
the world. In South Africa, too, performance testing is being accepted
readily as an indispensable aid in animal improvement. In fact, as far as
methods and techniques are concerned, South Africa can be regarded as
a world leader in many aspects.
The obvious reason for the success obtained by using performance
testing is that it leads to more accurate selection of superior breeding
stock. This, however, is only part of the whole story and it must be
stressed that performance testing merely supplies data and that breeders
differ in their ability to utilize these data in the same way that they
differ in their ability to select animals efficiently without objective
measurements. Given the best measuring technique and data processing
system, the incapable breeder could still make a terrible hash of his
breeding enterprise. Performance testing invariably has, as a first
consequence, the formulation of breeding objectives which are
sensible, realistic and based on fact. Without performance testing the
stud breeder could easily fail to appreciate the exact needs of his final
customer, the commercial producer. An example of how easily this can
happen is the fact that many beef cattle breeders insisted on selecting for
traits such as coat colour, shape of horns, etc., while the commercial
producer's needs shifted to economically important properties such as
fertility and growth rate.

3.1.1 Performance Testing Procedure

The performance testing procedure in Irish Cattle Breeding Federation is

as follows;

1. The bulls are made to enter a pre-entry isolation where they are
clipped, dosed, treated for lice and sorted into pens based on
breed and weight. For IBR- Irish BreedingResearch, the

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 ANP 507 MODULE 4

pre-entry isolation period is 30 days and during which the bulls are
weighed if they meet the testing requirements.
2. The bulls are housed primarily indoors and they also have access
to outdoor pen.
3. The bulls are fed ration at a less than ad lib rate until such
time as they have become acclimatized to the meal. This is very
important to maintain the health of the animal with a change in
diet. They are thereafter moved to ad lib feeding, and also given
a ration of hay twice a day. They are however provided with ad
lib water.
4. Health checks of the entire herd are carried out three times daily.
5. Bulls are provided with vitamins and mineral lick, and a
mineral revitalize dose if required‟
6. During the test the animals are weighed on a three-weekly
basis to assess their growth rate.
7. The bulls are washed every four to six weeks during the test,
depending on weather.
8. Bulls are exercised on an open pasture paddock twice a week for
a three-hour period each time if deemed necessary.
All the traits that the animals are been tested for are measured, combined
at the end of the test and stored in the ICBF database‟

3.1.2 a: Advantages of performance testing

1. The results allow a genetic profile of all animals with records and
related to be computed.
2. When performance test commence on the bulls, their new
information can help to improve their indexes in an equal
measure.

3.1.3 b: Disadvantage of Performance Testing

1. Despite the test being carried out under favourable environmental

conditions, the average genetic merit of the group tested
generally remained similar before and after the performance test.

3.2 Progeny testing

Progeny testing is a process by which a sire‟s genetic merit is measured through

the performance of his progeny. When the progeny are evaluated, the
genetic merit of the sire is more accurately assessed and which provide
the opportunity to use the high-ranking sires in the breeding programmes
with confidence. The basis of breeding programmes is the identification
of superior individuals and their widespread use within the population.
It is a two-stage operation in

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

which the superior individuals are first identified and are then used as
seed stock for future generations. Preselection of candidates for
progeny testing can be done by means of individual performance
testing which might increase efficiency and reduce costs in breeding
programmes

Progeny testing in animal breeding is used to determine the true

breeding value of an animal especially males which are used
extensively for propagation of best germplasm. The extensive use of
artificial insemination in domestic animals has helped in increasing the
selection intensity on the male animals. This selection tool is usually
used for characters that are sex-limited, expressed after death (meat
characteristics) and usually with low heritability, for example milk or
egg production in females. A bull for example cannot be assessed for
milk production, however the performance of its female offspring‟s
can be used to determine the use of the animal for future crosses. A
progeny test is performed by mating the male with a number of females
to produce many progenies in different environment and over a long
time period involving different seasons to nullify the impact of season,
management, environment in breeding value estimation. The average
performance of the offspring is then found, giving a measure of
the male's respective value to the breeder.
In animals the progeny testing could be conducted in a large herd or
involving associated herds or in the field in farmers place. The field
based progeny testing is highly required when the selected bulls are to
be distributed in a large area, to many farmers in different environments.

3.2.1 : Progeny Testing Procedure

A typical breeding design for a Progeny Testing Programme that can be

implemented in smallholder production situations as researched and
documented by the National Dairy Development Board is as follows:
A certain number of young sires produced using the very best dams and
sires are put under test. Adequate number of test doses of bulls put to
test are distributed in selected herds/villages to ensure that at least 80
to 100 complete first lactation record of daughters per bull in as
many herds/villages as possible are made available for estimating
breeding values of bulls with a very high reliability. The very best 1-
10% of progeny tested bulls and the very best 1 to 10% of recorded
cows are used for producing the next generation of young bulls. The
young bulls are again put to test and the cycle is repeated. The top 10 to
15% of the progeny tested bulls are usedfor production

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ANP 507 MODULE 4

Figure 1: Main features of progeny testing programmes for dairy cow

bulls (Andrabi and Moran,2007)

3.2.3: Factors that affect the usefulness of Progeny Testing

On the standpoint of genetic progress expected from selection

using progeny testing, the usefulness of progeny testing can be
greatly influenced by some factors and the most important of them are:
Age and Rate of reproduction. These two factors have been reported
to have their effect on the generation interval of the results from the use
of progeny test and which can offset the advantage of more accurate
selection and reduce the rate of improvement obtained.

Advantages of Progeny Testing

1. Genetic merit of sire is more accurately assessed

2. Provide opportunity to use high-ranking sires in the
breeding programme with confidence.

Disadvantages of Progeny Testing

1. Progeny testing programmes are very long-term.

2. It involves high cost
3. It requires high level of technical and professional skills

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 ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

4. Strong field artificial insemination and quality semen

production infrastructure are needed.
5. Could only be entrusted to institutions having requisite
experience and skills and financial resources.

4.0 CONCLUSION

Conducting a field based performance and progeny testing especially in small

holder production systems of Asia and Africa require huge resources both
financial and infrastructural - a large AI network, robust and dynamic
data collection and analysis system. Usually the breeding companies
conduct progeny testing of their bulls so that they can be commercially
promoted. But when the breeding organizations are Government
controlled (eg.India), the onus of conducting the testing also lies with
them if required genetic improvement is to be achieved

5.0 SUMMARY

 Performance and progeny testing are very crucial to any

meaningful animal breeding programmes and leads to more
accurate selection of superior breeding stock
 Preselection of candidates for progeny testing can be done
by means of individual performance testing which might
increase efficiency and reduce costs in breeding programmes
 The trait to evaluate depends on the breeding objectives for
example, beef cattle breeders may select for traits such as coat
colour, shape of horns, etc., while the commercial producer's
focus will be on economically important traits such as fertility
and growth rate
 The progeny test is needed most for traits which cannot be
expressed in one sex and for traits which are but slightly
hereditary.
 The bases for estimating breeding value are pedigree, own
performance, and progeny test. As fast as some selection is
practiced on one of these bases, the possibilities for further
progress by additional selection on the same basis rapidly
diminish and correspondingly increased attention should be given
to one of the other bases.

6.0 TUTOR MARKED ASSIGNMENT

1. Differentiate between progeny and performance testing

2. What are the procedures in performance testing?
3. What are the advantages and disadvantages of progeny testing?

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 ANP 507 MODULE 4

4. Itemise the steps involved in progeny testing using specific

example

7.0 REFERENCES/ FURTHER READING

Ström, H, and Philipsson, J. 1978 Relative importance of performance

tests and progeny tests in horse breeding. Livestock Production
Science, Volume 5 , Issue 3 , 303 – 312

Lush J. L. (1935). Progeny Test and Individual Performance as

Indicators of an Animal's

Breeding Value. Journal of Dairy Science Volume 18, Issue 1, January

1935, Pages 1-19

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

MODULE 5 IDENTIFYING AND INCORPORATING

GENETIC MARKERS AND
MAJOR GENES IN ANIMAL
BREEDING PROGRAMMES.

CONTENTS

1.0 Introduction
2.0 Objectives
3.0 Main Content
3.1 Molecular markers
3.1.1 Identifying molecular markers
3.2 Major genes
3.2.1 Detection and use of major genes
3.2.2 Incorporating genetic markers and major genes in
animal breeding programmes. Marker assisted
selection (MAS)
4.0 Conclusion
5.0 Summary
6.0 Tutor Marked Assignment
7.0 References/ Further Reading

1.0 INTRODUCTION

Recent developments in molecular biology and statistics have

opened the possibility of identifying and using genomic variation
and major genes for the genetic improvement of livestock. During
the last five decades, the application of methods based on population
genetics and statistics allowed the development of animals with a high
productive efficiency.

These systems are based on simplified models of genic actionthat

assume a large number of or genes with small individual effects in
the expression of the phenotype (polygenes) and emphasizes the
average genic effects (additive effects) over their interactions. The
basis is predicting the breeding values of the animals using phenotypic
and genealogical information. Molecular techniques allow detecting
variation or polymorphisms exists among individuals in the population
for specific regions of the DNA. These polymorphisms can be used to
build up genetic maps and to evaluate differences between markers in
the expression of particular traits in a family that might indicate a direct
effect of these differences in terms of genetic determination on the trait.
More probably, the can prove some degree of linkage of the QTL
effecting the trait and the marker. Recently, methods have been

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developed to detect the presence of major genes from the analysis of

pedigreed data in absence of molecular information

2.0 OBJECTIVES

 You will understand molecular markers and major genes

 You will understand different molecular markers
 You will understand how to incorporate molecular markers and
major genes in animal breeding programmes

3.0 MAIN CONTENT

3.1 Molecular markers

A molecular marker is a gene or DNA sequence with a

known location on a chromosome and associated with a particular
gene or trait. It can be described as a variation, which may arise due to
mutation or alteration in the genomic loci that can be observed.
A genetic marker may be a short DNA sequence, such as a
sequence surrounding a single base-pair change (single nucleotide
polymorphism, SNP), or a long one, like mini & micro satellites. Recent
years have witnessed a great interest towards molecular
markers, revealing polymorphism at the DNA level, as they play
an important role in animal genetics studies. When differences in
DNA occur within genes, the differences have the potential to affect
the function of the gene and hence the phenotype of the individual.
Genetic markers which have been used a lot in the past include blood
groups and polymorphic enzymes. We have relatively few such
markers, but this has been overcome with the advent of new types of
markers.

However, most molecular markers are not associated with a visible

phenotype. The main types of molecular markers are VNTRs, RFLPs
and RAPDs, AFLPs and SNPs.

3.1a: Variable number tandem repeat (VNTR‟s ) are scattered at

various locations in the genome and are regions that are highly
variable. These regions contain a type of DNA sequence called Variable
Number Tandem Repeat which are multiple copies of a sequence of
base pairs arranged in head to tail fashion. For example, a frequently
found tandem repeat is CA, and one strand containing this type of repeat
reads CACACA….. , notated as (CA)n. The other strand would read
GTGTGT… In this example, the number of repeating basepairs is two,
but it can be more. When the repeating unit is less than four, the VNTR
is called a microsatellite and when the repeating unit is longer it is a
minisatellite.

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

Microsatellites are DNA regions with variable numbers of short tandem

repeats flanked by a unique sequence. Microsatellites make good
genetic markers because they each have many different 'alleles' - ie.
There can be many different lengths of the repeat region. An allele
is defined by the number of repeats there are at the same location.
With many alleles, most individuals are heterozygous, giving power to
note association between marker allele and performance in progeny
inheriting a favorable linked QTL allele. Through the PCR reaction (see
below), which uses the unique sequences either side of the repeat
sequences as primer binding sites, microsatellite DNA can be
specifically amplified. The alleles an individual carrier at a particular
microsatellite locus can then be determined by accessing the size of the
amplified fragment through agarose gel electrophoresis.

3.1b: Restriction Fragment Length Polymorphisms’ (RFLP's): here

restriction enzymes enzymes cut DNA wherever they find the
appropriate nucleotide sequence (eg. Eco R1 cuts at the 'recognition
sequence' GAATTC). If there is a mutation at this sequence, no cut is
made and the resulting DNA fragment is longer. Also mutation to give
a new recognition sequence gives a pair of shorter fragments. Genetic
differences (polymorphisms) of this type are known as Restriction
Fragment Length Polymorphisms.

3.1c: Random Amplified Polymorphic DNA (RAPD) markers are

DNA fragments generated in PCR reactions that use a single short
primer (in normal PCR a primer-pair is used). The primer must be
complementary to sequences that are on opposite strands within a small
number of base pairs (say 2000). The DNA strand between these two
sites is amplified in a PCR. Polymorphism is determined by individuals
who have mutations at those sites, and therefore will not show a product
on the gel. The advantage of RAPD‟s is that we do not need to know the
DNA sequence of the species studied. A primer has a certain chance
of randomly generate a PCR product. Hence, RAPDs are cheap
markers to develop. The disadvantage is that RAPDs either give or do
not give a product and therefore, we cannot distinguish between homo-
and heterozygotes.

3.1d: Amplified Fragment Length Polymorphism (AFLP) is based

on PCR amplification of selected restriction fragments. Like RAPDs,
AFLPs require no prior knowledge of DNA sequences (unlike
microsatellites). The advantage of AFLPs over RAPDs is that they are
more reliable and reproducible (depend less on DNA quality and lab
conditions). Also, the number of polymorphic loci (molecular markers)
that can be detected is 10-100 times greater with AFLPs than with
microsatellites or RAPDs

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3.1 e: Single Nucleotide Polymorphisms are based on single base pair

polymorphisms. A SNP is a position at which two alternate bases
occur at appreciable frequency. In humans they may number greater
than one in a thousand base pairs. SNPs can be detected by a number of
methods, however a relatively new technology, using DNA chips, can
be used for large scale screening of numerous samples in a minimal
amount of time.

3.1.1 Identifying molecular markers

Molecular techniques (such as polymerase chain reaction (PCR) or

restriction enzyme digestion, followed by gel electrophoresis) can be
used to identifying different alleles resulting from DNA polymorphisms.
Different alleles from a VNTR will have different size and similarly,
RFLP‟s have different sizes (as defined by their name!)
Gel electrophoresis.

Gel electrophoresis separates DNA according to size. A gel is

essentially a slab of gelatinous material. DNA is applied to 'wells' at the
top of the gel (which is submerged in a tank containing some buffer),
and an electrical current applied. DNA is negatively charged and is
drawn towards the positive electrode. Smaller fragments will move
down the gel faster, as it is easier for them to move through the gel
matrix as seen in the figure below.

Southern blot

A southern blot involves the transfer of DNA from a gel (where it has
been separated according to size) to a special type of membrane. The

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

DNA on the membrane (which is in a denatured or single stranded

state) is exposed to a probe. A probe is a short sequence of DNA
that is complimentary to, and thus binds to, a DNA sequence of
interest. Probe bound to the membrane is then visualized: this can be
achieved by labeling the probe with radiation and exposing the
membrane to X-ray film. A Southern Blot will usually show the
alleles of VNTR‟s on all chromosomes, giving a complex pattern
known as a DNA fingerprint as shown in the figure below.

Polymerase chain reaction (PCR)

The polymerase chain reaction (PCR) amplifies a specific region of

DNA as defined by two primer sequences. It can thus be used to
examine one particular region of the genome. Because many copies of
one specific section of the genetic material are generated, it is possible
to use this technique with very, very small amounts of DNA as starting
material (e.g. a single hair root or a small blood stain).PCR is a three
stage process. Firstly the DNA is denatured (made single stranded),
secondly the primers bind or anneal to their complementary sequence,
and thirdly the primers are extended by the addition of nucleotides
complementary to that on the template sequence (this requires the
action of an enzyme called DNA polymerase). This three stage

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ANP 507 MODULE 5

process is then repeated 20-40 times as depicted in the following

diagram.

3.2 Major genes

Major gene is a gene with pronounced phenotype expression and

characterizes common expression of oligogenic series, that is, a small
number of genes that determine the same trait. Major genes control the
discontinuous or qualitative characters in contrast of minor genes or
polygene‟s with individually small effects. Major genes segregate and
may be easily subject to Mendelian analysis. The gene categorization
into major and minor determinants is more or less arbitrary. Both of the
two types are in all probability only end points in a more or less
continuous series of gene action and gene interactions. Recent
developments in molecular biology and statistics have opened the
possibility of identifying and using genomic variation and major genes
for the genetic improvement of livestock. The detection of major
genes using mixture models with segregation analysis can direct the
work of identification of DNA marker genotypes towards
populations and characteristics with greater probability of detecting a
QTL.

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

The present trend indicates that molecular, pedigree and phenotypic

information will be integrated in the future through mixture models of
segregation analysis that might contain QTL effects through the
markers, polygenic inheritance and uses powerful and flexible methods
of estimation such as Gibbs Sampling.

Recently, methods have been developed to detect the presence of major

genes from the analysis of pedigreed data in absence of molecular
information. These methods, based on mixture models and segregation
analysis, allow to direct the potentially expensive and time
consuming genotyping activities towards populations and characteristics
with a greater probability of being controlled by a QTL and to optimize
the collection of molecular data

3.2.1 : Detection and use of major genes

In the last ten years statistical methodologies of detection of major genes

based on pedigree and phenotypic information on populations have been
developed for animal populations. These methods are based on the use
of mixed models and segregation analysis to fit the data to a mixture
genetic model that includes in addition to the polygenic effects, those of
a biallelic major gene. Calculation is performed in two stages; firstly
genotype probabilities are obtained, then major gene, fixed effects and
polygenic effects are fitted and used to recalculate new parameters by
regressing phenotypes on estimated probabilities. Calculation is iterated
upon convergence. Segregation analysis allows inferring the unknown
genotypes from the probabilities of transmission of the gene given the
phenotype of the individual and their relatives.In mixture models,
regression and Gibbs sampling estimation approaches have been
implemented to obtain estimates of the major gene effects and
allelic frequency. Meuwissen and Goddard (1997) evaluated the
effect of including different proportions of individuals genotyped for a
QTL in a mixture model that is based on the analysis of segregation of
Kerr and Kinghorn (1996) and a regression approach which uses the
estimated genotype probabilities as weights in the estimation process.
Unbiased estimates of QTL effect and frequency were obtained in
absence of information on the genotype of the QTL, but some
improvements in the precision of the estimates were observed as the
proportion of genotyped individuals increased. The main limitation of
this method is that the genetic hypothesis is generally limited (one
biallelic locus), thus, the presence of more alleles could not be detected.
Also, the location of the locus in the genome, in absence of markers,
remains unknown. Mixture models can be modified to include markers
associated with the QTL, instead of the direct effect of the QTL in
addition to the information of the pedigree and the phenotype. This is
achieved by modifying the additive numerator relationship matrix (A),

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according to the conditional probabilities of transmission of the given

QTL the information of the markers. These developments can
make possible to evaluate the likelihood of the model or another fitting
criterion, to prove the relation between the markers and the QTL in
population animals with outbreed mating structures. They also may
increase the possibilities of making MAS in animal populations when
incomplete information exists on the genotypes of the animals for the
QTL or markers so that the use of the genomic information is
optimized. Scientist has developed a method to evaluate the amount of
genomic information that it allows maximizing a function of economic
utility for the analysis of QTL with mixture models. Major genes have
been detected using these methods for carcass characteristics in pigs
based on a mixture model of inheritance and Gibbs Sampling. Also,
important effects of major genes have been detected using Findgene
software for several carcass characteristics in cattle and for parasite
resistance in sheep. This methods that make use of information currently
available in many animal populations, are an option for a preliminary
screening for major genes that can contribute to rationalize the use of
expensive QTL-marker linkage estimation experiments.

3.2.2 Incorporating genetic markers and major genes in

animal breeding programmes. Marker assisted
selection (MAS)

The addition of genomic information to phenotypic information to

increase the selection response to the traditional method is known as
Marker-Assisted Selection (MAS). The concept of Marker Assisted
Selection (MAS) utilizing the information of polymorphic loci as an aid
to selection was introduced as early as in 1900. The method where
marker genes used to indicate the presence of desirable genes is called
as marker assisted selection. Marker assisted selection (MAS) is indirect
selection process where a trait of interest is selected not based on the
trait itself but on a marker linked to it. The purpose is to combine all
genetic information at markers and QTL with the phenotypic
information to improve genetic evaluation and selection. The
advantage of using MAS is that the effect of genes on production is
directly measured on the genetic makeup of the animal and not
estimated from the phenotype. The integration of two selection
methods, i.e., traditional or conventional selection methods with
molecular genetics methods beneficial to the selection response.
Multiple estimated QTL effects and multiple trait selection could help to
make better decisions regarding the use of MAS in animal
improvement. Combined with traditional selection techniques, MAS has
become a valuable tool in selecting organisms for desirable traits. MAS
is expected to increase genetic gain compared to traditional breeding
programs and reduce the cost of progeny testing by early selection

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

of the potential young bulls. The application of MAS in breeding

programmes depends on the knowledge of breeders about variable
marker information from animal to animal and the different effects on
multiple traits and his ability to spend in genotypic information that
helps in improve their commercial breeding activities. MAS also
provide an apparently possible approach to selection for genetic disease
resistance animals. In the future to make MAS effective in large
breeding populations, the availability of large-scale genotyping methods
and infrastructure that allows the generation of hundreds of thousands of
molecular data at a reasonable cost will be necessary.

3.2.2a: Marker assisted introgression: An application that has been

mentioned in the literature is the introgression a major gene in another
population by means of backcrosses assisted by molecular markers. In
this case, it does not seem to exist advantage in using single genetic
marker information, in comparison with the use of only phenotypic
information when the characteristic is continuous and the considered
genetic effects are additives. Nevertheless, it seems feasible that using
a dense map that involves many chromosomal regions and with more
than one allele of interest, the time for fixation of the major genes can be
reduced.

An example of introgression in pigs breeding is the introduction of litter

size genes from the Meishan breed into Western pig breeds. The
possible gains from such strategies depend heavily on the gene effect
and the frequency in the commercial lines. Introgression is expensive,
as it involves several generations of backcrossing to the desired
genotype, while keeping a desired haplotype from the introgressed QTL.
At the same time markers can be used to select against haplotypes for
background genes from the imported line. This generally speeds up the
introgression process and reduces the number of generations needed to
arrive at the desired genotype (possibly in two generations).

Marker assisted selection can also be used in crosses of lines of about

equal economic value. In that case, population wide linkage
disequilibrium can be exploited, giving potentially large increases in
response (Lande and Thompson, 1990). Genetic evaluation models can
have a significant effect on the achieved genetic response, models with
random marker (haplotype) effects being superior, because the approach
takes better account of the uncertainty of certain haplotype effects.

4.0 CONCLUSION

A rational use of the molecular methodologies requires thesimultaneous

optimization of selection on all the genes affecting important traits
in the population. The maximum benefit can be obtained when these

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techniques are used in conjunction with reproductive technologies like

the artificial insemination, and collection and production in vitro
ofembryos to accelerate the genetic change.There is a danger
associated with a potentially inadequate use of QTL information,
giving an excessively high emphasis to simple molecular information in
detriment of the overall economic gain through all traits and their
polygenic effects in the population. Dissemination of the information
to the industry is therefore a complexissue concerning QTL effects
and molecular markers

5.0 SUMMARY

 The characteristics on which the application of the MAS canbe

effective are those that are expressed late in the life of theanimal,
or those that are controlled by a few pairs of alleles
 Because of its high cost, the use of MAS could be justified, in
animal nuclei that allow dilution of the costs when germ plasm
is extensively used towards the commercial population. Also in
those characteristics in which the procedures of conventional
selection have reached their limits in efficiency or the results
have been not satisfactory
 Before the molecular information on the QTL which
control the characteristics of economic interest is generated, the
detection of major genes using segregation analysis could direct
the work of identification of genotypes towards
populations and characteristics with greater probability of
detecting a QTL using molecular markers

6.0 TUTOR MARKED ASSIGNMENT

1. What are molecular markers?

2. Describe some molecular markers you know
3. What are major genes?
4. How are these markers incorporated in animal breeding
programmes?

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 ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

7.0 REFERENCES/ FURTHER READING

Kinghorn, B. & van der Werf, J. (2000). IDENTIFYING AND

INCORPORATING GENETIC MARKERS AND MAJOR
GENES IN ANIMAL BREEDING PROGRAMS. University of
New England Armidale, Australia. Chapter 12. Belo Horizonte (Brazil) 31
May –5 June 2000

Montaldo, H. H. and Meza-Herrera, C. A. (1998). Use of molecular

markers and major genes in the genetic improvement oflivestock.
Journal of Biotechnology ISSN: 0717-3458. Vol.1 No.2, Issue of
August 15, 1998.

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ANP 507 MODULE 6

MODULE 6 DNA TESTS

CONTENTS

1.0 Introduction
2.0 Objectives
3.0 Main Content
3.1 DNA tests
3.1.1 Methods and techniques used in genetic
testing
3.2 Segregation Analysis
4.0 Conclusion
5.0 Summary
6.0 Tutor Marked Assignment
7.0 References/ Further Reading

1.0 INTRODUCTION

Almost every cell in every living organism contains a cell-

nucleus that holds the pairs of chromosomes that make up the
genetic material. Each chromosome has within it the DNA
(deoxyribonucleic acid) that makes up hundreds of thousands of
genes. Many of these genes make proteins that have a number of roles
in the body. Some proteins are structural and make up tissues like bones
and muscles. Proteins called enzymes are involved in chemical
reactions like breaking down the ingested food. While others are like
little messengers that send signals around the system, these proteins are
known as hormones.All individuals within a species share the same set
of genes but the precise DNA sequence of these genes differs slightly
between individuals (by about 0.1-0.2%). While these differences
account for things like differing hair, eye and skin colour, they can also
be the cause of genetic disease or disease susceptibility. A disease
causing change in the DNA of a gene is called a mutation. DNA or
genetic tests are such procedures used to uncover mutation or alterations
in genes that could lead to genetic disorders.

Many disorders in animals are observed more frequently in certain

breeds and within breeds more often in the same families.
Familiarity is assumed for a disorder when families are observed
with more than one affected family member. Familial disorders may
have a genetic contribution. The same is often claimed for disorders
which show a breed disposition. On the other hand, genetically caused
diseases may not necessarily lead to breed differences in incidence
but will contribute to variation among families within breeds. A useful
starting point for answering the question whether a disorder is inherited

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

is by drawing pedigrees to provide an initial impression of the

distribution of affected and non-affected animals and how frequently the
disorder is transmitted from one generation to the next.

2.0 OBJECTIVES

 You will understand DNA tests

 You will understand different types of DNA tests
 You will understand segregation analysis

3.0 MAIN CONTENT

3.1 DNA tests

These are diagnostic tests that are used to confirm a diagnosis in a

patient or animals with symptoms suggesting a particular genetic
disease. For example, in human, a person with a movement disorder
may be tested for Huntington‟s disease. The genetic information from
the test is useful in the treatment, management and genetic counseling of
the patient.Some genetic tests are used even when symptoms of a
disease are not seen, but the genetic information may help in predicting
if the person is at risk of developing, or are susceptible to a
particular disease.Genetic screening tests are;

1. Prenatal testing: This type of testing is offered during

pregnancy if there is an increased risk that the baby or progeny
will have a genetic or chromosomal disorder. In some cases,
prenatal testing can lessen a couple's uncertainty or help them
make decisions about a pregnancy. It cannot identify all possible
inherited disorders and birth defects.A good example of this is
the screening in human is for Down syndrome in women over 35.
Screening for Down syndrome is usually carried out by
amniocentesis or chorionic villus sampling at 14 – 20 weeks of
gestation.Prenatal testing is used to detect changes in a fetus's
genes or chromosomes before birth.

1. Newborn screening is used just after birth to identify

genetic disorders that can be treated early in life. In humans,
millions of babies are tested each year in the United States
and Europe especially for phenylketonuria (a genetic disorder
that causes intellectual disability if left untreated) and congenital
hypothyroidism (a disorder of the thyroid gland) and cystic
fibrosis (CF). A blood sample is taken from the newborn; this
blood sample is then sent to a laboratory for testing.

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3. Carrier screening is offered to parents-to-be so that they can

test if they are carriers for diseases such as cystic fibrosis
(CF).Carrier testing is used to identify people who carry one
copy of a gene mutation that, when present in two copies, causes
a genetic disorder. This type of testing is offered to individuals
who have a family history of a genetic disorder and to people in
certain ethnic groups with an increased risk of specific genetic
conditions. If both parents are tested, the test can provide
information about a couple's risk of having a child with a genetic
condition.
4. Diagnostic testing is used to identify or rule out a specific
genetic or chromosomal condition. In many cases, genetic
testing is used to confirm a diagnosis when a particular condition
is suspected based on physical signs and symptoms. Diagnostic
testing can be performed before birth or at any time during a
person's life, but is not available for all genes or all genetic
conditions. The results of a diagnostic test can influence a
person's choices about health care and the management of the
disorder.

5. Preimplantation testing, also called preimplantation genetic

diagnosis (PGD), is a specialized technique that can reduce the
risk of having a progeny with a particular genetic or
chromosomal disorder. It is used to detect genetic changes in
embryos that were created using assisted reproductive techniques
such as in-vitro fertilization. In-vitro fertilization involves
removing egg cells from a woman‟s ovaries and fertilizing
them with sperm cells outside the body. To perform
preimplantation testing, a small number of cells are taken from
these embryos and tested for certain genetic changes. Only
embryos without these changes are implanted in the uterus to
initiate a pregnancy.

1. Predictive and presymptomatic types of testing are used to

detect gene mutations associated with disorders that appear after
birth, often later in life. These tests can be helpful to people who
have a family member with a genetic disorder, but who have no
features of the disorder themselves at the time of testing for
example in dairy industry to guard against occurrence of
mastitis. Predictive testing can identify mutations that
increase a person's risk of developing disorders with a genetic
basis, such as certain types of cancer. Presymptomatic testing can
determine whether a person will develop a genetic disorder, such
as hereditary hemochromatosis (an iron overload disorder),
before any signs or symptoms appear. The results of predictive
and presymptomatic testing can provide information about a

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person‟s risk of developing a specific disorder and help with making

decisions about medical care.

7. Forensic testing uses DNA sequences to identify an individual

for legal purposes. Unlike the tests described above, forensic
testing is not used to detect gene mutations associated with
disease. This type of testing can identify crime or catastrophe
victims, rule out or implicate a crime suspect, or establish
biological relationships between people (for example,
paternity).

3.1.1 Methods and techniques used in genetic testing

Before a genetic test is carried out, clinical examination is carried out

and a detailed family history gotten. This will help in working out which
gene may be responsible for the disease in question. In human, the
patient will be referred to a genetic counsellor who can inform
them about everything that is involved with genetic testing. The genetic
counsellor can tell you what it means to have a particular genetic
change and how this can affect individual or the family. In the case of
animals, these will form a basis of whether to cull the animal or to be
applying symptomatic treatment. Almost all genetic tests require a
DNA sample from the patient; this is usually obtained by either a
blood sample or mouthwash (buccal swab) which is then taken to a
genetic testing lab for analysis.A number of techniques are used in the
process of genetic testing, these include:

1. Polymerase chain reaction (PCR) and DNA sequencing

The polymerase chain reaction (PCR) is a method of amplifying (copying) a

small amount of DNA to a larger amount so that it can be analyzed
closely. The genetic code of the DNA can be determined by a method
called „DNA sequencing‟. This then allows scientists to determine
whether or not there is a change or mutation present in a gene of interest.

2. Indirect gene tracking (linkage analysis)

If the gene associated with a hereditary disease in a family is not

known then linkage analysis can help in identifying the responsible
gene. The technique is based on the fact that special DNA sequences that
flank particular genes will travel with the gene when passed from
parent to child. These DNA sequences are called
„polymorphic markers‟ or „polymorphic repeat sequences‟. The closer
that one of these markers is to gene the more likely it is that it is
travelling with the gene. If a particular polymorphic marker is found

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only in members of a family with a particular disease then it is likely

that a gene located near the marker is associated with the disease.

Advantages of genetic screening

Through genetic testing we may be able to screen populations for

diseases in order to better diagnose, treat and prevent disease. Reducing
the incidence of disease has major impacts on and is of great
importance to:

Families: When a child is born with a particular disease, there may be no

apparent family history. With simple genetic testing for carrier status of
the parents, the birth of a child with disease could have been prevented.

Health resources: The birth of a child with a genetic disorder adds stress
to health systems and resources. Carrier screening programs could act
as important components of the medical system in preventing disease
through offering people informed reproductive choices.

Disadvantages of genetic testing

Many people would rather not know if they have a pre-disposition to a

particular disease. People may have enough stress in their lives already
to have to deal with an oncoming genetic disease, or that they are a
carrier of a particular disease mutation that may affect their future
children. There is also the possibility of some sort of negative stigma
attached to having a carrier status for a particular disease.

If the genetic cause of a disease is identified in a patient, it does not

necessarily guarantee that there is a cure for the disease. A treatment
or therapy may not yet have been developed. The identification of a
disease gene means a large step towards finding a cure; it is often
of no great immediate benefit to the patient.

Ethical issues associated with genetic testing

As carrier screening would involve the screening of a possibly

asymptomatic population, it inevitably raises a number of ethical issues
in terms of consent, privacy and education, which need to be
considered. It is important that all persons involved are appropriately
educated, their consent obtained and the confidentiality of their genetic
information upheld.

Prenatal genetic screening can inform parents of the health status of

their unborn child. In the case of a prenatal diagnosis of disease,
parents are able to assess their options and make decisions

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

accordingly. Foetal genetic testing does however raise the issue of

abortion, often a particularly sensitive and controversial matter.

3.2 Segregation Analysis

General evidence for genetic contribution to a disorder is given when

environmental factors can be excluded as the only responsible causes for
a disorder and a significant proportion of the phenotypic variation of a
disorder can be explained by genetic models. With increasing
molecular genetic data, the type of gene action based on known DNA
sequence variation can be characterized by individual genes and the
nature of complex genetic traits can be understood much
better.Segregation analysis is employed to determine whether familial
data for particular disorders or other traits are compatible with specific
modes of inheritance. Modes of inheritance tested in segregation
analyses include monogenic (Mendelian), digenic or polygenic
models. In addition, age of onset, sex effects and sampling scheme can
be taken into account besides the specific genetic hypothesis under
consideration. Simple segregation analysis tests the segregation
parameter θ under a specified sampling scheme and mating type.
Pedigrees used for segregation analysis may be from specifically
planned mating or randomly sampled pedigrees with arbitrary structure
or sampled through ascertained cases in clinics or veterinary practice.
Arranged mating among animals can be more easily tested for specific
modes of inheritance than pedigrees with arbitrary structure, missing
data and many inbred animals. In the case of a rare disease and an
autosomal dominant hypothesis, the segregation ratio θ is assumed to be
0.5 as families segregating for the trait are most likely composed by
mating of heterozygous affected and homozygous non-carriers. As far
as the segregation ratio is not significantly different from θ = 0.5, this
mode of inheritance is accepted. Different methods for estimating
θ have been developed and are easily applied (Singles Method,
Weinberg's General Proband Method). These simple approaches to
segregation analyses often encounter problems when different mating
types have to be considered and several hypotheses are more or less
likely. Complex segregation analyses have been developed to allow for
more factors to vary and to reduce the restrictions on assumptions to be
made for the model tested. Methods used to solve the likelihood
functions are based on maximum likelihood or Markov chain Monte
Carlo approaches (Gibbs sampling).

COMPLEX SEGREGATION ANALYSIS

Complex segregation analysis is based on a mathematical model that

incorporates several, functionally independent components to
accommodate for arbitrary mating types, different modes of

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monogenic or oligogenic inheritance (major genes), to allow for

polygenic variation and non-genetic variation in addition to major genes
and different data types such as binary, categorical and continuous data.
In addition, age of onset of a disease and sampling scheme (random
pedigrees versus non-randomly selected pedigrees) can be modeled. The
basic model as formulated in the Elston-Stewart algorithm was the basis
for the more complex models. The Elston-Stewart algorithm included a
component describing the joint distribution of genotypes of mating
individuals whereby these genotypic distributions stem from a single
locus with two alleles (monogenotype), a few loci with each two
alleles (oligogenotype) or from a polygenotypic distribution with an
infinite number of genotypes (polygenotype). The second component of
the Elston-Stewart algorithm specified the relationship between the
genotypes and phenotypes, separately for each genotype (penetrance
function). Mathematically, the phenotype investigated is modeled as a
conditional probability on the genotype underlying the model used. The
simplest genetic model for a dichotomous trait and a monogenic
autosomal inheritance of two alleles is then completely defined by the
following genotype to phenotype relationships: gAA(1) = gAa(1) = 1,
gaa(1) = 0 and gAA(0) = gAa(0) = 0, gaa(0) = 1, where the conditional
probability equals unity when for the genotypes AA and Aa the
phenotypic outcome is affected (=1) and for the genotype aa the
phenotypic status is unaffected (=0). Similarly, if a completely penetrant
recessive trait is assumed, we have the following conditional
distributions: gaa(1) = 1, gAa(1) = gAA(1) = 0, gaa(0) = 0, g Aa(0) =
gAA(0) = 1. Two- or three-locus models give raise to much more
models (phenogrammes) how the oligogenotype is related with the
phenotype. If we do not wish to assume complete penetrance we can
introduce for each distinct genotype or groups of genotypes a specific
penetrance. For X-linked loci, the conditional distributions of
phenotypes have to be defined for males and females separately.
Furthermore, traits only expressed in males or females can be modeled
via the penetrance parameter allowing fully expressed traits only for
one sex. Just as the phenotypic distribution may be sex-dependent, so
the disorder considered has a variable age of onset and thus the
observation whether the disorder is expressed, depends upon the age at
examination of each individual. Then the probability that an individual
with a genotype AA, Aa or aa is affected by a specific age depends of
the age- related susceptibility of the genotype to the disorder. When we
turn to polygenotypes, we use normal distribution functions. In the
case of a binary or categorical phenotype, this model corresponds to
the threshold or liability model. The polygenotypes are normally
2 2
distributed with genetic variance σ G and residual variance σ E. An
individual is affected or mildly/severely affected whose liability is

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greater than the threshold. The threshold may also depend upon the
genotype of an additional monogenic locus.

The mode of inheritance can be described how the genetic variability is

passed on from one generation to the next and is summarized
mathematically by the genotypic distributions of the offspring in
dependence upon the parental genotypes. Let us assume that an
individual has parents with genotypes s and t, then the conditional
probabilities for the genotypes of this individual can be viewed as
elements of a stochastic matrix called the genetic transition matrix,
probability (P) for the individual genotype given genotypes of parents s
and t, P(gi|gF,gM). All types of monogenic and oligogenic inheritance
can be parameterized in terms of transmission probabilities. In the
autosomal monogenic model with alleles A and B, the transmission
probabilities are the probabilities that an individual with genotype AA,
AB or BB transmits the allele A to offspring. Using the definitions for
the transmission probabilities τAA=1, τAB=0.5 and τBB=0, the
probabilities for the genotype AA of the individual with parents s and
t are equal to τsτt, the probabilities for the genotype AB with parents s
and t are equal to τs(1-τt) + τt(1-τs) and the probabilities for the
genotype BB with parents s and t are equal to (1-τ s)(1-τt). Extension to
several unlinked loci and linked loci is straightforward. Linked loci
require recombination rates among loci as further parameters. Polygenic
inheritance using an additive model can be modeled through the
transmission of the gamete values being 0.5 for any polygenotype.
The polygenotypes of offspring are produced by the mid-parents´
values of their polygenotypic effects with variance σ2G/2.

Sampling scheme describes the way how individuals were selected from
the population for study. Random sampling means that we take a
random sample of individuals from a population and then augment this
sample by including all or a random sample of relatives up to a certain
degree of relatedness. When well-designed recording schemes are
introduced, random samples of progeny or sibships with their ancestors
can be collected. These samples can be collected in a specific
geographic area which is not critical as long as individuals outside this
area are not selected according to their phenotype or genotype. Rare
conditions are hardly studied in random samples hence many
uninformative families are collected. Typically for this situation,
families are included in the study because at least one member of the
family is affected. The kind of the non-random sampling procedure is
characterized by the type of ascertainment. Complete ascertainment is
given when a sibship enters the sample independently of the
number of additional affected members. The opposite extreme to
complete ascertainment is single ascertainment. The probability for an

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affected individual tends to be zero to be brought into the study when

there is not more than one affected family member. Incomplete multiple
ascertainment is the situation between single and complete
ascertainment. To ensure a valid segregation analysis, the kind of
ascertainment should be identified. Methods of estimation of the
segregation ratio depend on how the families have been brought into the
study. A likelihood function based on the components of the segregation
analysis model can be derived and maximized for the data observed.
Since the likelihood function includes the different types of genetic
models as well non-genetic factors, submodels can be tested against the
most general model. Inferences can be performed for both continuously
and categorically distributed data and genetic models that include
monogenic, digenic, polygenic and mixtures of monogenic and
polygenic as well as oligogenic and polygenic models. A genetic
background of a trait analyses is given when the model explaining
only non-genetic factors can be rejected and models including
genetic components explain a significant proportion of the phenotypic
variation.

A likelihood ratio test statistic is used to compare a specific null

hypothesis (H0) defined by a specific model (restricted model) against a
most general (not restricted) model. The test statistic asymptotically
follows a X2-distribution, and significance levels can be obtained by
using this distribution. Degrees of freedom are given by the difference
of independently estimated parameters for the models compared. The
information criterion of Akaike (AIC) can be used as an additional
measure to choose the sparsest model with the best fit to the data. The
model with the smallest AIC fits the data best with a minimum number
of parameters but all hypotheses that cannot be rejected against the most
general model using the likelihood ratio test must also be considered as
possible. The AIC criterion cannot be used to exclude a hypothesis if
this model was not rejected against the most general model by using the
likelihood ratio test.

Complex segregation analysis is a powerful tool to detect major gene

variation. Quantitative genetic models rely on the assumption of many
(infinite) loci with very small and equal effects. This model is severely
compromised in the presence of segregation of major genes. Extensions
and improvements of algorithms made to the simple segregation models
allow to estimate major genotype effects in the framework of the
methodology developed for quantitative genetic analysis. Gibbs
sampling can be employed to estimate non-genetic effects, genotype
frequencies and their associated genotypic effects and
quantitative genetic variation including all relationships of the
animals. When information for genetic markers in population-wide
linkage disequilibrium or mutations of genes associated with trait

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variation can be included in the analysis, the genotypic distributions

need no longer to be estimated and inferences on the genotypic effects
are much more precise. Such genetic polymorphisms enable us to model
the gene actions and their interactions in networks for complex genetic
traits.

4.0 CONCLUSION

Complex segregation analysis is a powerful tool to detect major gene

variation. Quantitative genetic models rely on the assumption of many
(infinite) loci with very small and equal effects. This model is severely
compromised in the presence of segregation of major genes. Extensions
and improvements of algorithms made to the simple segregation models
allow to estimate major genotype effects in the framework of the
methodology developed for quantitative genetic analysis. Gibbs
sampling can be employed to estimate non-genetic effects, genotype
frequencies and their associated genotypic effects and
quantitative genetic variation including all relationships of the
animals.

5.0 SUMMARY

When information for genetic markers in population-wide linkage

disequilibrium or mutations of genes associated with trait variation
can be included in the analysis, the genotypic distributions need no
longer to be estimated and inferences on the genotypic effects are much
more precise. Such genetic polymorphisms enable us to model the gene
actions and their interactions in networks for complex genetic traits

6.0 TUTOR MARKED ASSIGNMENT

1. What is DNA test?

2. Describe four methods of DNA test
3. What are the advantages of DNA test?
4. What is segregation analysis? Describe any method that you
know

7.0 REFERENCES/ FURTHER READING

Kinghorn, B. DNA tests and segregation analysis for genetic

disorders. Twynam Chair of Animal Breeding Technologies
University of New England

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ANP 507 MODULE 7

MODULE 7 DETERMINING ASSOCIATIONS

BETWEEN GENETIC MARKERS
AND QUANTITATIVE TRAIT LOCUS
(QTL)
CONTENTS

1.0 Introduction
2.0 Objectives
3.0 Main Content
3.1 Quantitative trait
3.2 Principles of genetic mapping population
3.3 Determining associations between genetic markers and
quantitative trait locus (QTL)
4.0 Conclusion
5.0 Summary
6.0 Tutor Marked Assignment
7.0 References/ Further Reading

1.0 INTRODUCTION

The common animal species have a narrow genetic pool due to

domestication. In contrast, theirs wild relatives as a result of genetic
history and selection pressure are becoming in reservoirs of natural
genetic variation. Genes associated with desired productive traits such
as higher yield or disease resistance that could be lost in the breeding
process can be restored using these wild species. The problem for
breeder is to find the genes and find an efficient way to trace the genes
and to incorporate them in breeding populations. A survey of
genetic relationship using molecular markers provides polymorphism
information about a germplasm pool that is useful for developing
mapping and breeding populations. If quantitative traits have also been
evaluated for the same accessions, then statistical associations can be
sought between markers and quantitative traits. Such associations can
be used to select a subset of candidate probes with enhanced
potential for use in subsequent mapping experiments.

2.0 OBJECTIVES

 You will understand quantitative traits and quantitative trait locus

 You will understand methods of determining associations
between genetic markers and quantitative trait locus

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3.0 MAIN CONTENT

3.1 Quantitative trait

A quantitative trait is one that has measurable phenotypic variation within a

population owing to underlying variability in genetic and/or
environmental influences. A QTL is a genetic locus in which allelic
variation affects variation in the observed phenotype. Generally,
quantitative traits are multifactorial, meaning they are influenced by
several polymorphic genes and environmental conditions. To map a
QTL, its influence on a trait must be detected amid considerable “noise”
from other QTLs and non-genetic sources of individual variation. This
has been made feasible through the implementation of technologies to
identify genetic polymorphisms throughout the genome and the
development of statistical methods to map QTLs from specific genetic
marker and phenotypic (i.e., trait) data. The identification of the
chromosomal regions where marker allelic and phenotype variation co
vary implicates the presence of a QTL. Each QTL identifies the
genomic location of a gene or genes (referred to as quantitative
trait genes or QTGs) affecting the trait of interest. The power of this
approach was demonstrated first in plants and later in rodents, and has
been used widely to identify genetic contributions to a wide variety of
complex phenotypes. The observed distributions of quantitative traits
can arise because the traits are influenced by many genes, which result
in many possible genotypes, and also by environments. Thus the
difference between the means of genotypes are unobservable because
of the variability among the environments in which individuals with
any particular genotype live.

Quantitative Trait Locus Mapping

A quantitative trait is a measurable phenotype emerging from genetic and

environmental factors that is distributed in magnitude in a population
rather than all or none. A quantitative trait locus (QTL) is a specific
chromosomal region or genetic locus in which particular sequences of
bases in DNA markers are statistically associated with variation in the
trait. Several polymorphic genes and environmental conditions often
influence these quantitative traits and one or many QTL(s) can influence a
phenotypic trait. Inbred strains, selected lines, and other genetically
specified populations have been used in studies analogous to the human
population association and linkage studies described above.

The goals are first to locate a QTL harboring a gene or genes affecting the
trait to be mapped, and then refine that genomic map until a single
gene or genes can be implicated in the effect on the trait.

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ANP 507 MODULE 7

Currently, QTL fine mapping usually involves the development of

congenic strains. In a congenic strain, a very small sequence of DNA on
a chromosome is moved from one genetic background to another
inbred strain background. An excellent discussion of QTL mapping
methods discusses, in depth, the trait of alcohol withdrawal severity. Of
course, each QTL generally accounts for only a small proportion of the
variability in a complex behavioral trait like addiction, so this is a
difficult task and cautious interpretation is warranted. The probability of
success in QTL mapping depends on:

1) the heritability of the trait;

2) whether the underlying quantitative trait gene (QTG) is dominant,
recessive or additive;
3) the number of genes that affect the trait;
4) whether or not their effects are interactive; and
5) most importantly, the number of subjects that can be tested (i.e.,
the statistical power of the mapping effort).

Many addiction-related traits have been targeted for QTL mapping

studies, although very few of these QTLs have been reduced to QTGs or
quantitative trait nucleotides (QTNs). The recent discovery of the
addiction-relevant QTG, Mpdz, which possesses pleiotropic effects on
the predisposition to severe alcohol and barbiturate withdrawal,
demonstrates the power of this approach. Further studies have shown
that variation in the human MPDZ gene is related to alcohol
drinking. Unfortunately, QTL studies have yet to resolve to a QTG for
drinking, in part, due to problems discussed above. However, three
candidate genes, neuropeptide Y, α-synuclein, and CRFR2 have been
associated with ethanol-seeking. Encouraging evidence shows some
consistencies for alcohol and other substance-dependence phenotypes in
humans and mice. The more long-term goals of QTL mapping
projects are then to move to human populations for studies of the
homologous or orthologous gene, and use information about the
biological effects of the gene‟s product to help design therapeutic agents
or other therapies.

When breeders work with a particular trait in a species, they start to

work with the genetics of the trait. Many agricultural characteristics are
controlled by polygene‟s and are greatly dependent of genetic x
environment interactions. In an aim to work with the patterns of
segregation and inheritance for breeding those traits, we think about the
positions of the traits in a genetic map. Currently, when the position of a
gene controlling traits is inferred we work with tools of genetic or
physical mapping, depending on the information available for the
species and the trait.

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Traditionally it has been a challenge for breeders to work with

quantitative trait loci (QTL), with the development of molecular
markers technology, it has been possible to follow QTL
segregation detecting markers linked to traits of interest and assessing
effects, number and location of QTL in chromosomes. An alternative to
QTL mapping is association mapping also called association genetics,
association studies and linkage disequilibrium mapping. These two
methodologies have been advocated as the method of choice for
identifying loci involved in the inheritance of complex traits.Association
mapping seeks to identify specific functional variants (loci, alleles)
linked to phenotypic differences in a trait to facilitate detection of
trait causing DNA sequence polymorphisms and selection of genotypes
that closely resemble the phenotype (Oraguzie et al., 2007). In order to
identify these functional variants it requires high throughput markers
like single nucleotide polymorphisms (SNPs).

Molecular markers are used not just to generate genetic maps but also to
locate the places of interest in those maps with its incidence in the
expression of the trait. That is because they are used in marker assisted
selection programs. To improve the breeding methods efficiency,
breeders are using markers assisted selection techniques that show great
advantages compared with traditional selection methods based on
phenotypic traits evaluation. Molecular techniques allow accurate
selection in early stages focusing directly in its genetic base.

In order to locate QTL in a genetic map relatively few techniques have

been developed, one of those is linkage mapping. Linkage mapping is
the traditional method for QTL mapping, it implies to generate
simple crosses derived populations and to estimate marker-gene
recombination frequencies. Population mapping is frequently
developed from diploid parental that are originated partially or
completely from wild species. Such populations show only a small
proportion of all the possible alleles. In contrast, another method is
association mapping based on linkage disequilibrium (LD) concept; it
is a method that exploits the diversity observed in existent cultivars and
in breeding lines, without developing new populations.

Most of the important limitations for linkage mapping can be overcome

using association genetics. Association genetics does not require
building segregating populations and it can employ larger germplasm
exploiting the natural variation that exists in the available germplasm
and resolution for association could be of at least of 5 cM depending on
LD decay of the species.

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ANP 507 MODULE 7

3.2 Principles of genetic mapping population

Genetic mapping is mainly employed with two aims: to identify genetic

factors or loci that influence phenotypic traits and to determine
recombination distance among loci. As a condition for mapping the
traits to be studied must be polymorphic. One way for detecting those
polymorphisms is using molecular markers.Genetic mapping by linkage
is supported in genetic recombination, as condition for mapping a
particular trait. This trait should be polymorphic, displaying preferably a
wide variation among the individuals under study. When applying
molecular markers in staid of a phenotypic trait these markers should be
polymorphic as well, showing allelic variation. The selection of
polymorphic markers required for QTL and single trait mapping
depends on the existing knowledge regarding the species to study. In
species without detailed information of its sequence the candidate gene
approach may be used. This approach is based on the production of
markers from gene sequences that they have been observed to take
place or they are suspected that have a functional role in the selected
trait.

QTL mapping begins with the gathering of genotypic and phenotypic

data from a segregating population, and it is followed for a statistical
analysis where all the major loci responsible of the trait variation are
located. This analysis usually referred as primary QTL mapping could
locate a QTL in an interval of approximately 10 to 30 cM, which may
include several hundred of genes. Therefore, the genetic resolution has
to be improved by assigning a QTL to the shortest chromosome
segment including ideally one single gene. The final goal is the
identification of DNA coding or not coding sequences responsible for
QTL (QTL cloning).

3.3 Determining associations between genetic markers and

quantitative trait locus (QTL)

Two methods have been employed for verifying the association between
the shortest possible regions of a chromosome tagged using molecular
markers and the value of the studied trait: positional cloning and
association mapping. QTL cloning is difficult because of the resolution
limitations, even though many QTL had been cloned since 2001 when
the first QTL was cloned in but also in that year one QTL from rice was
cloned as well, since this at least 20 QTL were cloned.

Positional cloning allows QTL resolution but it is necessary to produce

a second and larger mapping population of 2000 or more F2 plants
derived from a cross between two parental nearly isogenic lines with
alleles functionally different in the targeted QTL. These parental lines

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ANP 507 ANIMAL BREEDING AND LIVESTOCK IMPROVEMENT

are called QTL-NILs (quantitative trait loci-nearly isogenic lines). The

generation of these lines can be archived doing marker assisted
backcrosses or iteratively identifying and selfing individuals that are
heterozygous at the QTL region. The production of such NILs can last
several years depending on the plant material. Other important aspects
to consider are the genetic limited variability as a result of the use of
only two parental. The generated population could segregate for just a
fraction of many QTL that may affect the same trait in other
populations. For primary QTL mapping, Monte Carlo simulations
have shown that at least 200 individuals from the segregated
population are required. For higher resolution, as required for positional
cloning, progenies of several thousand plants are needed. For example,
in the Alpert and Tanksley´s work in 1996 more than 3,400
individuals were analyzed to obtain a detailed map around a fruit
weight locus in tomato.

As an alternative to positional cloning, QTL may be determined

using association mapping. This method allows identifying a statistic
association between markers or candidates loci and the overall of an
analyzed phenotype within a set of genotypes (natural populations,
germplasm accessions and cultivars). It is important that the plant
collection contains a wide spectrum for the trait to evaluate, and in
particular it is an advantage for the analysis if the collection shows up
extreme phenotypes.

Five main steps exist for the association studies:

1) Selection of the population's samples,

2) Determination of the level and influence of the structure
population on the sample,
3) Phenotypic characterization of the population for the interest trait,
4) Population genotyping for regions/candidate genes candidates or
as a whole genome scan,
5) Assessment of the association between genotypes and
phenotypes. The selection of the association test is the last step
and it depends on the population's characteristics. Association
mapping uses ancestral recombination and genetic natural
diversity within a population to analyze quantitative traits and
it is built on the base of the LD concept.

It is used to think that the terms linkage and linkage disequilibrium have
similar meanings. However, although they are related, genetic linkage
makes reference to the correlated inheritance of two loci through several
generations because the two loci is at a sufficiently short physical
distance that recombination meiotic events do not show up, and
selection acts in the same way over the two loci, whereas LD refers to

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ANP 507 MODULE 7

the identical frequency in the presence of two alleles of different loci

inside a population, and this non-random association can be caused by
other factors than linkage.

Contrary to linkage mapping, where the genetic maps are created using
generations of well characterized pedigrees generated from simple or
multiple crossings, the LD based association studies can rely on the
variation generated by the segregation in natural populations of non
related individuals. It is expected that the period of time until the most
recent common ancestor between two non related individuals of a
population is bigger than the time presented by a population generated
by a crossing, for this cause the samples used in LD mapping present
more informative meiosis, generated through history, than the meiosis
showed up in a traditional population mapping. Meiosis is considered
informative when effective recombinations are generated, sending
information from one genetic pool to other genetic pool. In this way
ancestral recombination‟s can capture mixing between different
populations and within this when LD is present this is important for the
association assessment.

Factors that affect LD

LD is affected by biological factors, as the recombination and the allelic

frequencies, and for historical factors that affect population size, like the
selection, and bottlenecks with extreme genetic drift, selection for or
against a phenotype controlled by two non linked loci (epitasis). Mating
patterns and gene flow between individuals of genetically distinct
populations followed by intermating can strongly influence LD.

LD decreases faster in out crossing species than selfing species, this is

due to less effective recombination in selfing species where the
individuals are more likely to be homozygous than in out crossing
species.

In presence of a high LD a low density of markers is required in a

target region. With low LD, many markers are required but the
diagnostic markers resolution is higher, potentially until the level of the
gene or of QTN (i.e. the quantitative trait nucleotide polymorphism
responsible for the QTL effect). It is expected high variable levels of
LD through the genome due to variations in recombination rates,
presence of hot spots and selection, variation in recombination rate is a
key factor that contributes to the variance observed in LD patterns.

Possible complications to measure LD and therefore to carry out the

association mapping, can show up due to structure population in the
studied sample. The influence of structure population depends on the

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relationships among sampled individuals. So, populations to be

employed in an association study should be classified according to the
sample individual relationship. Structure population can generate
statistically significant but invalid biologically associations.

Low LD levels are expected when the population is diverse and the
common ancestor within the individual population is too far in time,
also low LD is not distributed uniformly along all the genome and it is
located in short distances around specific loci, which produce only
significant cooccurrences among physically near loci, increasing
mapping resolution.

4.0 CONCLUSION

Breeding, domestication and a limited genetic flow in many wild

species have generated erosion processes and genetic drift that have
produced structured populations (i.e. populations with allelic
frequencies differences among sub-populations). These
populations generate not functional significant associations among
loci or between a marker and a phenotype, even without marker
physically binding to the responsible locus for phenotypic variation.

5.0 SUMMARY

In Summary, different methods have already been generated; these

methods make it possible to interpret results of association tests,
controlling statistically the effects of stratified populations, because
association studies that do not keep in mind the effects of structure
population must be viewed with skepticism. All these methods are based
on the use of independent marker loci to detect and correct stratified
populations.

6.0 TUTOR MARKED ASSIGNMENT

1. What is quantitative trait locus?

2. How do you determine associations between genetic markers and
quantitative trait locus?
3. State steps involved in association studies
4. What are the factors that affect linkage disequilibrium?

7.0 REFERENCES/ FURTHER READING

Beer S, C, et al.,. Associations between molecular markers and

quantitative traits in an oat germplasm pool: Can we infer
linkages?

47