Merging microsatellite data

Wolf genetic diversity compared across Europe using the yardstick method

Integrating data across studies with traditional microsatellite genetic markers requires careful calibration and represents an obstacle for investigation of wide-ranging species where populations require transboundary management. We used the "yardstick" method to compare results published across Europe since 2002 and new wolf (Canis lupus) genetic profiles from the Carpathian Mountains in Central Europe and the Dinaric Mountains in Southeastern Europe, with the latter as our reference population. We compared each population with Dinaric wolves, considering only shared markers (range 4-17). For each population, we calculated standard genetic diversity indices plus calibrated heterozygosity (Hec) and allelic richness (Ac). Hec and Ac in Dinaric (0.704 and 9.394) and Carpathian wolves (0.695 and 7.023) were comparable to those observed in other large and mid-sized European populations, but smaller than those of northeastern Europe. Major discrepancies in marker choices among some studies made comparisons more difficult. However, the yardstick method, including the new measures of Hec and Ac, provided a direct comparison of genetic diversity values among wolf populations and an intuitive interpretation of the results. The yardstick method thus permitted the integration of diverse sources of publicly available microsatellite data for spatiotemporal genetic monitoring of evolutionary potential.

A continent-wide high genetic load in African buffalo revealed by clines in the frequency of deleterious alleles, genetic hitchhiking and linkage disequilibrium

A high genetic load can negatively affect population viability and increase susceptibility to diseases and other environmental stressors. Prior microsatellite studies of two African buffalo (Syncerus caffer) populations in South Africa indicated substantial genome-wide genetic load due to high-frequency occurrence of deleterious alleles. The occurrence of these alleles, which negatively affect male body condition and bovine tuberculosis resistance, throughout most of the buffalo's range were evaluated in this study. Using available microsatellite data (2-17 microsatellite loci) for 1676 animals from 34 localities (from 25°S to 5°N), we uncovered continent-wide frequency clines of microsatellite alleles associated with the aforementioned male traits. Frequencies decreased over a south-to-north latitude range (average per-locus Pearson r = -0.22). The frequency clines coincided with a multilocus-heterozygosity cline (adjusted R2 = 0.84), showing up to a 16% decrease in southern Africa compared to East Africa. Furthermore, continent-wide linkage disequilibrium (LD) at five linked locus pairs was detected, characterized by a high fraction of positive interlocus associations (0.66, 95% CI: 0.53, 0.77) between male-deleterious-trait-associated alleles. Our findings suggest continent-wide and genome-wide selection of male-deleterious alleles driven by an earlier observed sex-chromosomal meiotic drive system, resulting in frequency clines, reduced heterozygosity due to hitchhiking effects and extensive LD due to male-deleterious alleles co-occurring in haplotypes. The selection pressures involved must be high to prevent destruction of allele-frequency clines and haplotypes by LD decay. Since most buffalo populations are stable, these results indicate that natural mammal populations, depending on their genetic background, can withstand a high genetic load.

Linkage disequilibrium matches forensic genetic records to disjoint genomic marker sets

Combining genotypes across datasets is central in facilitating advances in genetics. Data aggregation efforts often face the challenge of record matching-the identification of dataset entries that represent the same individual. We show that records can be matched across genotype datasets that have no shared markers based on linkage disequilibrium between loci appearing in different datasets. Using two datasets for the same 872 people-one with 642,563 genome-wide SNPs and the other with 13 short tandem repeats (STRs) used in forensic applications-we find that 90-98% of forensic STR records can be connected to corresponding SNP records and vice versa. Accuracy increases to 99-100% when ∼30 STRs are used. Our method expands the potential of data aggregation, but it also suggests privacy risks intrinsic in maintenance of databases containing even small numbers of markers-including databases of forensic significance.

Population structure in a comprehensive genomic data set on human microsatellite variation

Over the past two decades, microsatellite genotypes have provided the data for landmark studies of human population-genetic variation. However, the various microsatellite data sets have been prepared with different procedures and sets of markers, so that it has been difficult to synthesize available data for a comprehensive analysis. Here, we combine eight human population-genetic data sets at the 645 microsatellite loci they share in common, accounting for procedural differences in the production of the different data sets, to assemble a single data set containing 5795 individuals from 267 worldwide populations. We perform a systematic analysis of genetic relatedness, detecting 240 intra-population and 92 inter-population pairs of previously unidentified close relatives and proposing standardized subsets of unrelated individuals for use in future studies. We then augment the human data with a data set of 84 chimpanzees at the 246 loci they share in common with the human samples. Multidimensional scaling and neighbor-joining analyses of these data sets offer new insights into the structure of human populations and enable a comparison of genetic variation patterns in chimpanzees with those in humans. Our combined data sets are the largest of their kind reported to date and provide a resource for use in human population-genetic studies.

Combining US and Brazilian microsatellite data for a meta-analysis of sheep (Ovis aries) breed diversity: facilitating the FAO Global Plan of Action for Conserving Animal Genetic Resources

Microsatellites are commonly used to understand genetic diversity among livestock populations. Nevertheless, most studies have involved the processing of samples in one laboratory or with common standards across laboratories. Our objective was to identify an approach to facilitate the merger of microsatellite data for cross-country comparison of genetic resources when samples were not evaluated in a single laboratory. Eleven microsatellites were included in the analysis of 13 US and 9 Brazilian sheep breeds (N = 706). A Bayesian approach was selected and evaluated with and without a shared set of samples analyzed by each country. All markers had a posterior probability of greater than 0.5, which was higher than predicted as reasonable by the software used. Sensitivity analysis indicated no difference between results with or without shared samples. Cluster analysis showed breeds to be partitioned by functional groups of hair, meat, or wool types (K = 7 and 12 of STRUCTURE). Cross-country comparison of hair breeds indicated substantial genetic distances and within breed variability. The selected approach can facilitate the merger and analysis of microsatellite data for cross-country comparison and extend the utility of previously collected molecular markers. In addition, the result of this type of analysis can be used in new and existing conservation programs.

Susceptibility loci for adiposity phenotypes on 8p, 9p, and 16q in American Samoa and Samoa

Obesity is a complex phenotype affected by genetic and environmental influences such as sociocultural factors and individual behaviors. Previously, we performed two separate genome-wide investigations for adiposity-related traits (BMI, percentage body fat (%BF), abdominal circumference (ABDCIR), and serum leptin and serum adiponectin levels) in families from American Samoa and in families from Samoa. The two polities have a common evolutionary history but have lately been influenced by variations in economic development, leading to differences in income and wealth and in dietary and physical activity patterns. We now present a genome-wide linkage scan of the combined samples from the two polities. We adjust for environmental covariates, including polity of residence, education, cigarette smoking, and farm work, and use variance component methods to calculate univariate and bivariate multipoint lod scores. We identified a region on 9p22 with genome-wide significant linkage for the bivariate phenotypes ABDCIR-%BF (1-d.f. lod 3.30) and BMI-%BF (1-d.f. lod 3.31) and two regions with genome-wide suggestive linkage on 8p12 and 16q23 for adiponectin (lod 2.74) and the bivariate phenotype leptin-ABDCIR (1-d.f. lod 3.17), respectively. These three regions have previously been reported to be linked to adiposity-related phenotypes in independent studies. However, the differences in results between this study and our previous polity-specific studies suggest that environmental effects are of different importance in the samples. These results strongly encourage further genetic studies of adiposity-related phenotypes where extended sets of carefully measured environmental factors are taken into account.

Genetic diversity and gene flow in collapsed and healthy abalone fisheries

Overexploitation of marine species invariably results in population decline but can also have indirect effects on ecological processes such as larval dispersal and recruitment that ultimately affect genetic diversity and population resilience. We compared microsatellite DNA variation among depleted and healthy populations of the black-lip abalone Haliotis rubra from Tasmania, Australia, to determine if over-fishing had affected genetic diversity. We also used genetic data to assess whether variation in the scale and frequency of larval dispersal was linked to greater population decline in some regions than in others, and if larval dispersal was sufficient to facilitate natural recovery of depleted populations. Surprisingly, allelic diversity was higher in depleted populations than in healthy populations (P < 0.05). Significant subdivision across hundreds of metres among our sampling sites (F(ST) = 0.026, P < 0.01), coupled with assignment tests, indicated that larval dispersal is restricted in all regions studied, and that abalone populations across Tasmania are largely self-recruiting. Low levels of larval exchange appear to occur at the meso-scale (7-20 km), but age estimates based on shell size indicated that successful migration of larvae between any two sites may happen only once every few years. We suggest that genetic diversity may be higher in depleted populations due to the higher relative ratio of migrant to self-recruiting larvae. In addition, we expect that recovery of depleted abalone populations will be reliant on sources of larvae at the meso-scale (tens of km), but that natural recovery is only likely to occur on a timescale unacceptable to fishers and resource managers.

Merging microsatellite data: enhanced methodology and software to combine genotype data for linkage and association analysis

Background

Correctly merged data sets that have been independently genotyped can increase statistical power in linkage and association studies. However, alleles from microsatellite data sets genotyped with different experimental protocols or platforms cannot be accurately matched using base-pair size information alone. In a previous publication we introduced a statistical model for merging microsatellite data by matching allele frequencies between data sets. These methods are implemented in our software MicroMerge version 1 (v1). While MicroMerge v1 output can be analyzed by some genetic analysis programs, many programs can not analyze alignments that do not match alleles one-to-one between data sets. A consequence of such alignments is that codominant genotypes must often be analyzed as phenotypes. In this paper we describe several extensions that are implemented in MicroMerge version 2 (v2).

Results

Notably, MicroMerge v2 includes a new one-to-one alignment option that creates merged pedigree and locus files that can be handled by most genetic analysis software. Other features in MicroMerge v2 enhance the following aspects of control: 1) optimizing the algorithm for different merging scenarios, such as data sets with very different sample sizes or multiple data sets, 2) merging small data sets when a reliable set of allele frequencies are available, and 3) improving the quantity and 4) quality of merged data. We present results from simulated and real microsatellite genotype data sets, and conclude with an association analysis of three familial dyslipidemia (FD) study samples genotyped at different laboratories. Independent analysis of each FD data set did not yield consistent results, but analysis of the merged data sets identified strong association at locus D11S2002.

Conclusion

The MicroMerge v2 features will enable merging for a variety of genotype data sets, which in turn will facilitate meta-analyses for powering association analysis.

A cautionary tale: Lack of consistency in allele sizes between two laboratories for a published multilocus microsatellite typing system

For species with low genetic diversity, typing using the differences in PCR fragment length resulting from variations in numbers of short tandem repeats has been shown to provide a high level of discrimination. This technique has been called multilocus microsatellite typing (MLMT) or multiple-locus variable-number tandem repeat analysis, and studies usually employ genetic or sequence analyzers to size PCR fragments to a high degree of precision. We set out to validate one such system that has been developed for Aspergillus fumigatus (H. A. de Valk, J. F. G. M. Meis, I. M. Curfs, K. Muehlethaler, J. W. Mouton, and C. H. W. Klaassen, J. Clin. Microbiol. 43:4112-4120, 2005). The sizes of the alleles were compared both by sequencing and from two genotyping laboratories, where they used capillary electrophoresis (CE) for sizing. Size differences of up to 6 bases were found between the actual sizes reported by sequencing and the sizes reported by CE. In addition, because the two genotyping laboratories used different machines and running conditions, differences of up to 3 bases were identified between them. As the microsatellite markers used differ by repeat units of 3 or 4 bases, it was not possible to assign PCR fragments to the correct alleles without confirming the sizes of a range of alleles by direct sequencing. Lines of best fit were plotted for each CE machine against actual sizes and will therefore enable unsequenced PCR fragments to be assigned to the correct alleles. This study highlights the care required to ensure that an MLMT system undergoes a suitable correction procedure before data can be merged between different laboratories involved in the typing of individual species.

Accommodating chromosome inversions in linkage analysis

This work develops a population-genetics model for polymorphic chromosome inversions. The model precisely describes how an inversion changes the nature of and approach to linkage equilibrium. The work also describes algorithms and software for allele-frequency estimation and linkage analysis in the presence of an inversion. The linkage algorithms implemented in the software package Mendel estimate recombination parameters and calculate the posterior probability that each pedigree member carries the inversion. Application of Mendel to eight Centre d'Etude du Polymorphisme Humain pedigrees in a region containing a common inversion on 8p23 illustrates its potential for providing more-precise estimates of the location of an unmapped marker or trait gene. Our expanded cytogenetic analysis of these families further identifies inversion carriers and increases the evidence of linkage.