Chandra S. Pareek

 Novel approaches for linkage

mapping in dairy cattle.

”Selective DNA pooling”

Main sub-headings

 Definition
  Principle
  Experimental design
 
 Experimental design to locate the QTL region through selective

DNA pooling.

 
 Microsatellite genotyping
 
 Statistical methods for accurate estimation of gene frequency from

pooled samples.

 
 Problems in determination of gene frequency.
 
 Problems in interpreting pooling results by visual inspection.
 
 Application of Selective DNA pooling in farm animals.
 
 Advantages of Selective DNA pooling.
 
 Success of selective DNA pooling in dairy cattle.

Definitio

n

•  
“Selective DNA pooling” is an advanced

methodology

for

linkage

mapping

of

quantitative, binary and complex traits in
farm animals.

•  
In human, this methodology is termed as DNA

pooling where it serves as mapping of
complex disease traits.

•  
It is defined as densitometric genotyping of

physically

pooled

samples

from

phenotypically extreme individuals.

•  
The DNA pooling is performed by taking equal

aliquots of DNA from the pooled individuals. 

Principle

•  
     The principle is based on densitometric estimates of marker

allele frequency from the pooled phenotypically extreme

individuals.

•  






   

    In this regards, the marker of choice is:

STR or microsatellite

STR or microsatellite

markers.

markers.

•  
     The microsatellite allele linked to any QTL gene can be

identified by any shift or deviation of allele from the pools.

•  
     The QTL linked allele, and then further tested for its feasibility

by statistical analysis.

•  
     The power of statistics is relied on the accurate estimates of

gene frequency from the pooled samples.

•  
     Several methods have been described for accurate estimation

of gene frequencies (Daniels et al. 1998, Barcellos et al. 1998,

Lipkin et al. 1998, and Collins et al. 2000).

•  

Figure A and B: showing allelic patterns
of a linked marker.

Here figure A is displaying a shift of
marker allelein affected individuals pool.

Figure C and D: showing allelic
patterns of a unlinked marker.

Here both figures are not displaying
any shift or deviation of the alleles.

Affected pool

Unaffected pool

Unaffected pool

Affected pool

Experimental design

  A well-defined experimental design is an essential prerequisite

to perform the selective DNA pooling.

•  
  The experimental design should include the following

conditions.

• 1. Identification of resource families having extreme

phenotypic values for the given analysed trait.

• 2. Systemic selection of highly polymorphic STR markers from

the analysed genome.

•  
 Experimental design to locate the QTL region through

selective DNA pooling

•  

Daughter design: In case of cattle, by utilizing multiple half-
sib families with multiple STR markers.
Granddaughter design: In case of cattle, poultry and swine,
by utilizing F2 full-sib daughters including sire and grand
sire.

Microsatellite

genotyping

•  

The most commonly used touch

down protocol of Don et al. 1991, can
be used for typing of microsatellte
markers, followed by visualisation of
electrophoresis results in any DNA
sequencing machine (Perkin Elmer
ABI-Prism,

Pharmacia

ALF,

and

LICOR genetic analyser).

 Statistical methods for accurate

estimation of gene frequency from

pooled samples

 The following three methods have been

described:

 
  By measuring the relative intensity of

shadow bands (RI):
Method proposed by Lipkin et al. 1998.

  

By measuring the Allelic Image Pattern

(AIP) from the pools:
Method proposed by Daniels et al. 1998.

 
  By measuring the Total Allelic content

(TAC) from the pools:
Method proposed by Collins et al. 2000.

first Method: Lipkin et al. 1998

Measuring relative intensity of shadow
bands (RI)

By giving the densitometric values of main and
shadow bands, the relative intensity of a given
shadow band for a given allele can be calculated
as:
RI

n.i

= D

n.i

/ D

n

Where,

n = is the number of repeats in the native genomic
tract of the allele A

n

I = is the order of the shadow band
RI

n.i

= is the relative intensity of the i

th

shadow

band derived from the genomic tract of A

n

D

n

= is the densitometric intensity of the main

band derived from the genomic tract of A

n

D

n.i

=is the densitometric intensity of the i

th

shadow

band derived from the genomic tract of A

n

2nd method: Daniels et al.. 1998

Measuring Allelic Image Patterns
(AIP) from the pools

• The principle of this method is based on the

analysis of microsatellite allele image patterns
(



AIP) generated from the DNA pools.

• The



AIP statistic is calculated from the

differences in the area between two allele

image pattern expressed as a fraction of total

shared and non-shared area.



AIP = Dif / (Dif + Com)

The



AIPs from the pools and X

2

values from

individual genotyping were compared. The

results demonstrated a high correlation
between



AIPs and X

2

values.

Figure showing overlaid AIPsof two different pools amplified with the

microsatellitemarker. Area ”Dif” and ”Com” are the non-shared and

common areas betweenthe two AIPs.

3rd method: Collins et al.. 2000

Measuring Total Allelic content
(



TAC) from the pools

• This is a modified method of Daniels et al..

1998.

• The principle of this method is based on

simple measurement of total allele
differences by comparing the two pools.

• The pool comparison is done by comparing

the relative peak height differences
between electrophoregrams for each allele
of a microsatellite.

FigureA: Showing peak image profile from individual genotyping
illustrating sutter profile and amplitude variation.
Figure B: showing peak image profiles from pooled genotyping.

Problems in determination of

gene frequency

Feasibility and reliability of selective

DNA pooling is depend upon the

accurate estimates of the gene

frequency from pooled samples,

which is mostly confounded with

Sutter banding and Differential

amplification.

• 1. Sutter banding
• 2. Differential amplification.

Problems in interpretating

pooling results by visual

inspection

Visual inspection of numerous STR
genotyping of pooled samples can
be performed by visual eye balling
of the peak image files.
There are 2 problems encountered
during visual inspection of the
peak image files.

True negative peaks

False positive peaks

Figure1: Showing shifting of
microsatelliteallele in affected group.

This figure represents the True result
with correct peak profile image.

Figure3: Showing no shifting of
microsatellitealleles but there is one
linked marker allele in this locus.

This figure represents a good example of
True Negative peak profile image.

Shifted allele

control

unaffected

False .Shifted allele

Figure2: Showing shifting of
microsatelliteallele in affected group.

This figure represents a good example
of False positive peak profile image.

Example of correct result

Example of false positive result

Example of true negative result

Application of selective DNA pooling

in farm animals

In rapid genome scanning for the identification of

unknown gene or linked gene fragment.

 
In rapid estimation of STR gene frequency. More

recently in estimation of SNP frequencies as well.

In identification of complex gene fragment within

the genome through linkage analysis of STR

marker linked to that gene fragment.

In QTL mapping of the identified gene or gene

fragment.

To detect genes with small effect, for e.g., complex

disease traits in human.

 
 

Figure representing detection of linked allele by comparing affected and
unaffected DNA pools.
In this figure: Marker D5S393 is showing the linked allele to the disease
trait whereas, marker D5S410 showing no allele linked to the disease trait.

Advantages of selective

DNA pooling

 
To detect any linkage between marker and QTL: 
Multiple families with large numbers of daughters

are required to get reasonable statistical power.

 
This requirement leads to genotyping of hundreds of

thousands

individuals

with

high

cost

of

experiment.

 
By means of selective DNA pooling, the cost of

numerous

genotyping

can

be

substantially

reduced.

 
Thus selective DNA pooling is an ideal and potential

approach for analysing multiple large families with

multiple microsatellite markers.

 
 

   Selective DNA pooling reduces not only the

genotype cost by many folds, but also

minimizes the valuable experimental time.

 For example:individual v/s Pooled genotyping
In case of individual G: 2000 markers x 2000

individuals = 4 x 10

6

individuals

In case of Pooled G: The genotyping becomes

2000 x 2 = 4000.

 Success of selective DNA pooling in

dairy cattle

 

  Mapping of QTL genes for milk protein

percentage in Israeli HF cattle (Lipkin et al.

1998).

 
  Detection of loci that affect quantitative traits

like milk production in New Zealand HF and

Jersey cattle population (Spelman et al. 1998).