Number Of Marker Alleles Research Articles

Estimating Relatedness Between Individuals in General Populations With a Focus on Their Use in Conservation Programs

Relatedness estimators are widely used in genetic studies, but effects of population structure on performance of estimators, criteria to evaluate estimators, and benefits of using such estimators in conservation programs have to date received little attention. In this article we present new estimators, based on the relationship between coancestry and molecular similarity between individuals, and compare them with existing estimators using Monte Carlo simulation of populations, either panmictic or structured. Estimators were evaluated using statistical criteria and a diversity criterion that minimized relatedness. Results show that ranking of estimators depends on the population structure. An existing estimator based on two-gene and four-gene coefficients of identity performs best in panmictic populations, whereas a new estimator based on coancestry performs best in structured populations. The number of marker alleles and loci did not affect ranking of estimators. Statistical criteria were insufficient to evaluate estimators for their use in conservation programs. The regression coefficient of pedigree relatedness on estimated relatedness (beta2) was substantially lower than unity for all estimators, causing overestimation of the diversity conserved. A simple correction to achieve beta2 = 1 improves both existing and new estimators. Using relatedness estimates with correction considerably increased diversity in structured populations, but did not do so or even decreased diversity in panmictic populations.

Characterization of a flint maize (Zea mays var. indurata) Italian landrace, II. Genetic diversity and relatedness assessed by SSR and Inter-SSR molecular markers

A comparative characterization of 10 field populations of the maize (Zea mays var. indurata) landrace “Nostrano di Storo” was carried out using different types of PCR-based markers. The inbred line B73 and three synthetics (VA143, VA154 and VA157) selected from as many landraces were also used. Genetic diversity and relatedness were evaluated over 84 SSR and 53 I-SSR marker alleles using a total of 253 individual DNAs. Up to 23 alleles per SSR locus were scored while the average effective number of alleles per population was 6.99. Nei's total genetic diversity as assessed with SSR markers was HT = 0.851 while the average diversity within populations was HS = 0.795. The overall Wright's fixation index FST was as low as 0.066. Thus, more than 93% of the total variation was within population. Unique alleles over all SSR loci were found for six populations. An average of 17.7 marker alleles per I-SSR primer were scored with an effective number of marker alleles per locus of 1.34. The Shannon's diversity information index over all populations and I-SSR loci was 0.332, varying from 0.286 to 0.391. The extent of differentiation between populations was as low as GST = 0.091. Dice's genetic similarity matrices were estimated for both SSR and I-SSR markers. The mean genetic similarity coefficients within and between populations were respectively 0.269 and 0.217, for SSR markers, and 0.591 and 0.564, for I-SSR markers. UPGMA dendrograms displayed all field populations but one clustered into a distinct group, in which the synthetic VA154, selected from the “Marano Vicentino” landrace, was also included. One field population and the other two synthetics were clustered separately as well B73. The matrix correlation assayed by the Mantel's correspondence test was as high as 0.908. Findings suggest that, although a high variability can be found among plants, most plant genotypes belong to the same landrace called “Nostrano di Storo”. Although gene flow from commercial hybrids might have occurred, the large number of polymorphisms and the presence of both unique alleles and alleles unshared with B73 and synthetics are the main factors underlying the value of this flint maize landrace as a source of genetic variation and peculiar germplasm traits. Because of its exclusive utilization for human consumption, such a molecular marker characterization will be a key step for obtaining the IGP mark and so promote the in situ conservation and protection of the landrace “Nostrano di Storo”.

Comparison of Linkage-Disequilibrium Methods for Localization of Genes Influencing Quantitative Traits in Humans

Linkage disequilibrium has been used to help in the identification of genes predisposing to certain qualitative diseases. Although several linkage-disequilibrium tests have been developed for localization of genes influencing quantitative traits, these tests have not been thoroughly compared with one another. In this report we compare, under a variety of conditions, several different linkage-disequilibrium tests for identification of loci affecting quantitative traits. These tests use either single individuals or parent-child trios. When we compared tests with equal samples, we found that the truncated measured allele (TMA) test was the most powerful. The trait allele frequencies, the stringency of sample ascertainment, the number of marker alleles, and the linked genetic variance affected the power, but the presence of polygenes did not. When there were more than two trait alleles at a locus in the population, power to detect disequilibrium was greatly diminished. The presence of unlinked disequilibrium (D'*) increased the false-positive error rates of disequilibrium tests involving single individuals but did not affect the error rates of tests using family trios. The increase in error rates was affected by the stringency of selection, the trait allele frequency, and the linked genetic variance but not by polygenic factors. In an equilibrium population, the TMA test is most powerful, but, when adjusted for the presence of admixture, Allison test 3 becomes the most powerful whenever D'*>.15.

Random model approach for QTL mapping in half-sib families

An interval mapping procedure based on the random model approach was applied to investigate its appropriateness and robustness for QTL mapping in populations with prevailing half-sib family structures. Under a random model, QTL location and variance components were estimated using maximum likelihood techniques. The estimation of parameters was based on the sib-pair approach. The proportion of genes identical-by-descent (IBD) at the QTL was estimated from the IBD at two flanking marker loci. Estimates for QTL parameters (location and variance components) and power were obtained using simulated data, and varying the number of families, heritability of the trait, proportion of QTL variance, number of marker alleles and number of alleles at QTL. The most important factors influencing the estimates of QTL parameters and power were heritability of the trait and the proportion of genetic variance due to QTL. The number of QTL alleles neither influenced the estimates of QTL parameters nor the power of QTL detection. With a higher heritability, confounding between QTL and the polygenic component was observed. Given a sufficient number of families and informative polyallelic markers, the random model approach can detect a QTL that explains at least 15 % of the genetic variance with high power and provides accurate estimates of the QTL position. For fine QTL mapping and proper estimation of QTL variance, more sophisticated

Genome Screens Using Linkage Disequilibrium Tests: Optimal Marker Characteristics and Feasibility

Linkage disequilibrium (LD) testing has become a popular and effective method of fine-scale disease-gene localization. It has been proposed that LD testing could also be used for genome screening, particularly as dense maps of diallelic markers become available and automation allows inexpensive genotyping of diallelic markers. We compare diallelic markers and multiallelic markers in terms of sample sizes required for detection of LD, by use of a single marker locus in a case-control study, for rare monophyletic diseases with Mendelian inheritance. We extrapolate from our results to discuss the feasibility of single-marker LD screening in more-complex situations. We have used a deterministic population genetic model to calculate the expected power to detect LD as a function of marker density, age of mutation, number of marker alleles, mode of inheritance of a rare disease, and sample size. Our calculations show that multiallelic markers always have more power to detect LD than do diallelic markers (under otherwise equivalent conditions) and that the ratio of the number of diallelic to the number of multiallelic markers needed for equivalent power increases with mutation age and complexity of mode of inheritance. Power equivalent to that achieved by a multiallelic screen can theoretically be achieved by use of a more dense diallelic screen, but mapping panels of the necessary resolution are not currently available and may be difficult to achieve. Genome screening that uses single-marker LD testing may therefore be feasible only for young (<20 generations), rare, monophyletic Mendelian diseases, such as may be found in rapidly growing genetic isolates.

A test statistic for the affected-sib-set method.

This paper discusses generalizations of the affected-sib-pair method. First, the requirement that sib identity-by-descent relations be known unambiguously is relaxed by substituting sib identity-by-state relations. This permits affected sibs to be used even when their parents are unavailable for typing. In the limit of an infinite number of marker alleles each of infinitesimal population frequency, the identity-by-state relations coincide with the usual identity-by-descent relations. Second, a weighted pairs test statistic is proposed that covers affected sib sets of size greater than two. These generalizations make the affected-sib-pair method a more powerful technique for detecting departures from independent segregation of disease and marker phenotypes. A sample calculation suggests such a departure for tuberculoid leprosy and the HLA D locus.