Markers for studying genetic variation in fann animals

Get Complete Project Material File(s) Now! »

CHAPTER THREE Genetic characterization of native fowl in South Africa

 Introduction

Native fowl populations in South Africa have received very little scientific recognition over the years. As described in Chapter One, it was only during 1994, that the « Fowls for Africa » program was established to conserve and promote native fowl populations in South Africa (Joubert, 1996). Although a phenotypic characterization contributes to breed definition and description of their production potential, a genetic characterization of the native chicken based on DNA information, is essential for long term conservation of the genetic resource. Genetic characterization provides information on the relationships and variation in the populations that may determine how the populations should be conserved as a genetic resource.
Various methods for the study of genetic variation in farm animals were reviewed in Chapter Two. Initially, blood protein polymorphisms were applied to estimate genetic variation (Hines, 1999). With the development of molecular techniques during the late eighties, specifically the Polymerase Chain Reaction, it became possible to target the DNA directly in genetic studies, which led to intensive studies of the genome and development of various DNA-markers including RFLP, DFP, mini – and microsatellites. These markers are widely used to describe variation and genetic relationships among and within populations (Zhou & Lamont, 1999). Microsatellites were decided on as the most appropriate DNA- marker for this study, as a large number of microsatellite markers are already mapped on the chicken genome, with a high degree of polymorphism.
This chapter describes the selection of appropriate polymorphic microsatellite markers for the study, the evaluation of the markers in the native populations as well as the application in the genetic characterization ofthe South African native fowl populations.

Material and Methods

Source of DNA

Blood samples were collected from the Potchefstroom Koekoek, New Hampshire, Naked Neck, Lebowa-Venda, Ovambo and the Black Australorp populations kept in the « Fowls for Africa » project at the ARC at Irene. Between forty and fifty venous blood samples of each population were collected in 2 ml tubes containing 80 !!l EDTA (final concentration 0.5 M). Twenty blood samples from native chicken populations were donated by the University of Zimbabwe, Botswana Agricultural College and the Eduardo Mondlane University in Mozambique. The origin of the Potchefstroom Koekoek, New Hampshire, Naked Neck, Lebowa-Venda and Ovambo fowls was described in Chapter Two. The Black Australorp population was only included in the genetic characterization, as these birds were very often used in rural areas as dualpurpose breeds (eggs and meat) and may have genetic similarities with the other native populations. The Australorp was also often applied in upgrading of native fowl in other African countries. The blood samples from Botswana and Mozambique were collected from native populations kept at the respective universities and the samples from Zimbabwe were collected from rural native chicken populations on routine testing for New Castle disease. These chicken populations are not yet described as lines or breeds and vary greatly in colour and conformation.
After collection the blood samples, were frozen in Eppendorf tubes and kept at -70°C. DNA was extracted from the blood samples using a Puregene DNA-isolation kit (Gentra Systems, Minneapolis). Avian blood contains erythrocytes that are nucleated and only a small volume of blood is required for DNA-extraction. The concentration of the DNA was quantitated by spectrophotometry and diluted to a concentration of 10 ng!!!l.

Selection and testing of microsatellite markers

Twenty-seven fluorescently labeled polymorphic microsatellite markers were selected from the collection of markers made available by Dr Martien Groenen (Department of Animal Breeding, Wageningen Agricultural University, The Netherlands). The selection was based on the degree of polymorphism and genome coverage (Crooijmans et aI., 1996a & b; Crooijmans et aI., 1997). The characteristics of the markers used, including the chromosome location, expected range in base pairs and numbers of alleles, as reported by Groenen et al. (1998), are summarized in Table 3.1. These markers were all tested in the reference population kept at the Wageningen Agricultural University.
peR conditions and gel analyses
PCR reactions were carried out in a volume of 12 Ill, containing 30-60 ng target DNA, 200 IlM dNTP’s, 1 mM Tetramethylammoniumchloride (TMAC), 10 mM TrisHCI (pH = 9.0), 1.5 mM MgCh, 50 ml mM KCI, 0.01 % gelatine, 0.1 % Triton X-lOO, 0.2 U, Taq enzyme and 300 ng/Ill of each primer (microsatellite marker). Preparation of samples were followed by thermal cycling in a Thermal Controller (Perkin Elmer) using the following programme: 5 minutes at 94°C followed by 35 cycles consisting of 30 sec at 94°C, 45 sec at 55°C, 90 sec at noc and an extension step of 10 min at 72°C. The microsatellite amplicons were then tested on an agarose gel to ensure a good product before a mix was prepared and analyzed on an automated DNA-sequencer (ABI 373A). Some primers required further optimization and PCR conditions and temperatures were adapted until amplicons of a desirable quality were obtained. Annealing temperatures varied between 50°C and 58°C for the different primers.
In order to make the most economical use of the ABI Automated sequencer, primers were divided into in three sets according to differences in size and fluorescent labels namely HEX (yellow), FAM (blue) or TET (green) (Table 3.1). First, a mix containing the microsatellite amplicons were prepared for each set according to the expected signals. Then a loading buffer containing the GENESCAN-350 T AMRA internal standard and formamide (3.21l1) was mixed with 1III of the pooled PCR amplicons, denaturated and loaded onto a polyacrylamide sequencing gel (ABI 377 sequencing machine). The gel data were transferred for analysis with Genescan software.

READ  Testing Probabilistic Seismic Hazard Estimates Against Observations

Statistical analyses

The Genescan version 2.0 and Genotyper for MacIntosch were used to determine the fragment sizes in base pairs. From Genotyper, data files were exported to Microsoft Xcel, for preparation of input files for statistical analyses. The statistical programs of the SAS Institute (1992) and BIOSYS-1 program package (Swofford & Selander, 1989) were used for calculations of allele frequencies and heterozygosities. Allele frequencies were calculated and a Chi-square test was perfOimed to test for Hardy-Weinberg equilibrium. There were several unique alleles among the populations and therefore, alleles were grouped according to homozygotes for the most common allele, the heterozygotes for the most rare or common alleles and rare homozygotes. Heterozygosity per microsatellite marker was calculated according to Nei (1978):
=[2n/2n-1][1-iOml(pJ/)]
Where:n  the number of individual chickens per population,
ml =  the number of alleles at locus 1
ph =  the frequency of the th allele at locus 1.
The standard error was calculated from the total variance at each locus and total variance over all the loci studied. An analysis of variance (Tukey’s Studentized Range) was performed to test for significant differences in H among the lines (SAS, 1992).
The Polymorphic Information Content (PIC) values were also estimated according to Botstein et al. (1980) using SAS (1992). PIC values were for all the microsatellites per chicken population:
PIC =1 -(1: »-1 P12 ) _  1: »-11: » 2 p? Pi 2
Where:
k = number of different alleles for the specific locus
= the population frequencies ofthe ith and /h allele
FST values were calculated as estimators of genetic subdivision for each microsatellite marker across all the populations. The RsT was calculated as an alternative to F ST for describing population subdivision.
RsT was calculated using MSAT (MICROSAT: hhtp:lllotka.stanford.edu/microsatJ microsat.htm/) based on the fraction of the total variance of allele size between populations as proposed by Slatkin (1995).

Abstract 
Samevatting
List of abbreviations
List of Tables
List of Figures
List of publications and conference proceedings
CHAPTER ONE: Introduction 
CHAPTER TWO: Literature oveIView
2.1 Defmition of indigenous, native & local fowl
2.2 ConseIVation ofnative fowl populations
2.3 Origin of the native fowl in South Africa.
2.4 Markers for studying genetic variation in fann animals
2.4.1 Genetic markers
2.4.2 DNA-based markers
24.2.1 Restricted Fragment Length Polymorphism
2.4.2.2 Microsatellites
2.4.2.3 Minisatellites
2.4.2.4 Random Amplified Polymorphic DNA
2.4.2.5 Amplified Fragment Length Polymorphism
2.4.2.6 Single nucleotide polymorphism
2.5 Mapping ofthe chicken genome
2.6 Genetic markers and variability in chickens
2.7 Measurement of variation
2.7.1 Gene diversity (heterozygosity)
2.7.2 Measures ofpopulation structure
2.7.3 Genetic distance
CHAPTER THREE: Genetic characterization of native fowl in South Africa
3.1 Introduction
3.2 Materials and methods
3.3 Results
3.4 Discussion
CHAPTER FOUR: Phenotypic characterization ofnative fowl popUlations in South Africa
4.1 Introduction
4.2 Materials and methods
4.3 Results
4.4 Discussion
CHAPTER FWE: Critical review and recommendations 
CONCLUSION
REFERENCES
GET THE COMPLETE PROJECT

Related Posts