1. Ø Novel approaches for linkage mapping in dairy cattle
Ø Novel approaches for linkage mapping in dairy cattle. ”Selective DNA pooling”
     Chandra S. Pareek
Dept. of Animal Genetics,
Faculty of Animal Bio-Engineering,
University of Warmia and Mazury,
Olsztyn, Poland.

2. Main sub-headings Ø Definition Ø Principle Ø Experimental design
Ø Experimental design to locate the QTL region through selective DNA pooling.
Ø Microsatellite genotyping
Ø Statistical methods for accurate estimation of gene frequency from pooled samples.
Ø Problems in determination of gene frequency.
Ø Problems in interpreting pooling results by visual inspection.
Ø Application of Selective DNA pooling in farm animals.
Ø Advantages of Selective DNA pooling.
Ø Success of selective DNA pooling in dairy cattle.

3. Definition
“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. 

4. ØPrinciple
¨    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 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).

6. Experimental design
Ø  A well-defined experimental design is an essential prerequisite to perform the selective DNA pooling.
Ø  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.
Ø 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.

7. ØMicrosatellite genotyping
ØThe 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).

8. Ø 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   
By measuring the Allelic Image Pattern (AIP) from the pools:
Method proposed by Daniels et al
  By measuring the Total Allelic content (TAC) from the pools:
Method proposed by Collins et al

9. first Method: Lipkin et al
first Method: Lipkin et al 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:
RIn.i = Dn.i / Dn
Where,
n = is the number of repeats in the native genomic tract of the allele An
I = is the order of the shadow band
RIn.i = is the relative intensity of the ith shadow band derived from the genomic tract of An
Dn = is the densitometric intensity of the main band derived from the genomic tract of An
Dn.i =is the densitometric intensity of the ith shadow band derived from the genomic tract of An

10. 2nd method: Daniels et al
2nd method: Daniels et al 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 X2 values from individual genotyping were compared. The results demonstrated a high correlation between AIPs and X2 values.

12. This is a modified method of Daniels et al.. 1998.
3rd method: Collins et al Measuring Total Allelic content (TAC) from the pools
This is a modified method of Daniels et al
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.

14. 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.

15. 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

17. 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.

19. 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.

20. Ø Success of selective DNA pooling in dairy cattle
¨   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 106 individuals
In case of Pooled G: The genotyping becomes 2000 x 2 = 4000.
Ø 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).