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      Parentage verification of South African Angora goats, using microsatellite markers

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          Abstract

          ABSTRACT South African Angora goats are farmed under extensive production systems in relatively large herds. As a result, breeders make use of group and flock-mating systems that limit accurate parentage recording and selection efficiency. In this study the aim was to refine a panel of microsatellite markers suitable for parentage verification in South African Angora goats. The markers were first evaluated based on the number of alleles, allele frequency, PIC, H E, H O and individual exclusion probability, and secondly as part of a panel. Eighteen markers were tested in 192 South African Angora goats representing different family structures with known and unknown parent information. The final set of microsatellite markers, with the strongest exclusion and the least number of microsatellite markers, consisted of 14 microsatellite markers namely BM1258, BM1329, BM1818, BM7160, CSRD247, HSC, INRA63, INRABERN192, MCM527, OarFCB48, SRCRSP5, SRCRSP8, SRCRSP9 and SRCRSP24. This panel had a combined first-parent exclusion probability of 99.7% and it was possible to perform parental identification in a test family.

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          Most cited references30

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          Statistical confidence for likelihood-based paternity inference in natural populations.

          Paternity inference using highly polymorphic codominant markers is becoming common in the study of natural populations. However, multiple males are often found to be genetically compatible with each offspring tested, even when the probability of excluding an unrelated male is high. While various methods exist for evaluating the likelihood of paternity of each nonexcluded male, interpreting these likelihoods has hitherto been difficult, and no method takes account of the incomplete sampling and error-prone genetic data typical of large-scale studies of natural systems. We derive likelihood ratios for paternity inference with codominant markers taking account of typing error, and define a statistic delta for resolving paternity. Using allele frequencies from the study population in question, a simulation program generates criteria for delta that permit assignment of paternity to the most likely male with a known level of statistical confidence. The simulation takes account of the number of candidate males, the proportion of males that are sampled and gaps and errors in genetic data. We explore the potentially confounding effect of relatives and show that the method is robust to their presence under commonly encountered conditions. The method is demonstrated using genetic data from the intensively studied red deer (Cervus elaphus) population on the island of Rum, Scotland. The Windows-based computer program, CERVUS, described in this study is available from the authors. CERVUS can be used to calculate allele frequencies, run simulations and perform parentage analysis using data from all types of codominant markers.
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            A retrospective assessment of the accuracy of the paternity inference program CERVUS.

            CERVUS is a Windows-based software package written to infer paternity in natural populations. It offers advantages over exclusionary-based methods of paternity inference in that multiple nonexcluded males can be statistically distinguished, laboratory typing error is considered and statistical confidence is determined for assigned paternities through simulation. In this study we use a panel of 84 microsatellite markers to retrospectively determine the accuracy of statistical confidence when CERVUS was used to infer paternity in a population of red deer (Cervus elaphus). The actual confidence of CERVUS-assigned paternities was not significantly different from that predicted by simulation.
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              Comparison of microsatellites and amplified fragment length polymorphism markers for parentage analysis.

              This study compares the properties of dominant markers, such as amplified fragment length polymorphisms (AFLPs), with those of codominant multiallelic markers, such as microsatellites, in reconstructing parentage. These two types of markers were used to search for both parents of an individual without prior knowledge of their relationships, by calculating likelihood ratios based on genotypic data, including mistyping. Experimental data on 89 oak trees genotyped for six microsatellite markers and 159 polymorphic AFLP loci were used as a starting point for simulations and tests. Both sets of markers produced high exclusion probabilities, and among dominant markers those with dominant allele frequencies in the range 0.1-0.4 were more informative. Such codominant and dominant markers can be used to construct powerful statistical tests to decide whether a genotyped individual (or two individuals) can be considered as the true parent (or parent pair). Gene flow from outside the study stand (GFO), inferred from parentage analysis with microsatellites, overestimated the true GFO, whereas with AFLPs it was underestimated. As expected, dominant markers are less efficient than codominant markers for achieving this, but can still be used with good confidence, especially when loci are deliberately selected according to their allele frequencies.
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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Journal
                sajas
                South African Journal of Animal Science
                S. Afr. j. anim. sci.
                The South African Society for Animal Science (SASAS) (Pretoria )
                2221-4062
                2011
                : 41
                : 3
                : 250-255
                Affiliations
                [1 ] University of Pretoria South Africa
                Article
                S0375-15892011000300007
                a36148b0-f68b-4455-90b1-87dbb4e78c07

                http://creativecommons.org/licenses/by/4.0/

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                Product

                SciELO South Africa

                Self URI (journal page): http://www.scielo.org.za/scielo.php?script=sci_serial&pid=0375-1589&lng=en
                Categories
                Agriculture, Dairy & Animal Science
                Genetics & Heredity
                Nutrition & Dietetics
                Physiology

                Animal agriculture,Nutrition & Dietetics,Anatomy & Physiology,Genetics
                Pedigree allocation,exclusion probability,DNA technology

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