Comparison of information content for microsatellites and SNPs in poultry and cattle

Data were available for 12 poultry microsatellites and 29 poultry single nucleotide polymorphisms (SNPs), and for 34 cattle microsatellites and 36 cattle SNPs. Stochastic permutation was used to determine the number of SNPs needed to obtain the same average information content as a given number of microsatellites. For poultry, the information content averaged 0.71 for the 12 microsatellites compared to 0.72 for the 29 SNPs. For cattle, the information content averaged 0.92 for the 34 microsatellites compared with 0.79 for the 36 SNPs. This study shows that, for each microsatellite, three SNPs are needed to obtain the same average information content.     

High throughput genotyping technologies.

A comprehensive genetic map containing several hundred microsatellite markers resulted from a large microsatellite mapping project. This was the first real study that introduced high throughput methods to the genetic community. This map and the concurrent technological advances, which will briefly be reviewed, led to further numerous mapping investigations of simple and complex diseases. The annotated draft sequence of approximately three billion base pairs (bp) of the human genome has been completed much sooner than many imagined, due to considerable technological advancements and the international enterprise that resulted. This was a major development for the genetics community, but is only the precursor to the next phase of studying and understanding the variation within the human genome. The awareness of the differences may help us understand the effects on the genetics of the variation between individuals and disease. It is these variations at the nucleotide level that determine the physiological differences, or phenotypes of each individual, including all biological functions at the cellular and body level. Single nucleotide polymorphisms (SNPs) will provide the next high density map, and be the genetic tool to study these genetic variations. There are many sources of SNPs and exhaustive numbers of methods of SNP detection to be considered. The focus in this paper will be on the merits of selected, varied SNP typing methodologies that are emerging to genotype many individuals with the required huge number of SNPs to make the study of complex diseases and pharmacogenomics a practical and economically viable option.     

To what extent do microsatellite markers reflect genome‐wide genetic diversity in natural populations?

Microsatellite variability is widely used to infer levels of genetic diversity in natural populations. However, the ascertainment bias caused by typically selecting only the most polymorphic markers in the genome may lead to reduced sensitivity for judging genome-wide levels of genetic diversity. To test this potential limitation of microsatellite-based approaches, we assessed the degree of nucleotide diversity in noncoding regions of eight different carnivore populations, including inbred as well as outbred populations, by sequencing 10 introns (5.4–5.7 kb) in 20 individuals of each population (wolves, coyotes, wolverines and lynxes). Estimates of nucleotide diversity varied 30-fold (7.1 × 10⁻⁵ –2.1 × 10⁻³), with densities of one single nucleotide polymorphism every 112–5446 bp. Microsatellite genotyping (10–27 markers) of the same animals revealed mean multilocus heterozygosities of 0.54–0.78, a 1.4-fold difference among populations. There was a positive yet not perfect ( r ²  = 0.70) correlation between microsatellite marker heterozygosity and nucleotide diversity at the population level. For example, point estimates of nucleotide diversity varied in some cases with an order of magnitude despite very similar levels of microsatellite marker heterozygosity. Moreover, at the individual level, no significant correlation was found. Our results imply that variability at microsatellite marker sets typically used in population studies may not accurately reflect the underlying genomic diversity. This suggests that researchers should consider using resequencing-based approaches for assessing genetic diversity when accurate inference is critical, as in many conservation and management contexts.     

Evaluation of 16 loci to examine the cross‐species utility of single nucleotide polymorphism arrays

Large collections of single nucleotide polymorphisms (SNPs) have recently been identified from a number of livestock genomes. This raises the possibility that SNP arrays might be useful for analysis in related species for which few genetic markers are currently available. To address the likely success of such an approach, the aim of this study was to examine the threshold number and position of flanking mutations which act to prevent genotype calls being produced. Sequence diversity was measured across 16 loci containing SNPs known either to work successfully between species or fail between species. In pairwise comparisons between domestic and wild sheep, sequence divergence surrounding working SNP assays was significantly lower than that surrounding non‐functional assays. In addition, the location of flanking mismatches tended to be closer to the target SNP in loci that failed to generate genotype calls across species. The magnitude of sequence divergence observed for both working and non‐functional assays was compared with the divergence separating domestic sheep from European Mouflon, African Barbary, goat and cattle. The results suggest that the utility of SNP arrays for analysis of shared polymorphism will be restricted to closely related pairs of species. Analysis across more divergent species will, however, be successful for other objectives, such as the identification of the ancestral state of SNPs.     

Comparison of the effectiveness of microsatellites and SNP panels for genetic identification,traceability and assessment of parentage in an inbred Angus herd

During the last decade, microsatellites (short tandem repeats or STRs) have been successfully used for animal genetic identification, traceability and paternity, although in recent year single nucleotide polymorphisms (SNPs) have been increasingly used for this purpose. An efficient SNP identification system requires a marker set with enough power to identify individuals and their parents. Genetic diagnostics generally include the analysis of related animals. In this work, the degree of information provided by SNPs for a consanguineous herd of cattle was compared with that provided by STRs. Thirty-six closely related Angus cattle were genotyped for 18 STRs and 116 SNPs. Cumulative SNPs exclusion power values (Q) for paternity and sample matching probability (MP) yielded values greater than 0.9998 and 4.32E⁻⁴², respectively. Generally 2–3 SNPs per STR were needed to obtain an equivalent Q value. The MP showed that 24 SNPs were equivalent to the ISAG (International Society for Animal Genetics) minimal recommended set of 12 STRs (MP ∼ 10⁻¹¹). These results provide valuable genetic data that support the consensus SNP panel for bovine genetic identification developed by the Parentage Recording Working Group of ICAR (International Committee for Animal Recording).     

Using blocks of linked single nucleotide polymorphisms as highly polymorphic genetic markers for parentage analysis

Single nucleotide polymorphisms (SNPs) are plentiful in most genomes and amenable to high throughput genotyping, but they are not yet popular for parentage or paternity analysis. The markers are bi-allelic, so individually they contain little information about parentage, and in nonmodel organisms the process of identifying large numbers of unlinked SNPs can be daunting. We explore the possibility of using blocks of between three and 26 linked SNPs as highly polymorphic molecular markers for reconstructing male genotypes in polyandrous organisms with moderate (five offspring) to large (25 offspring) clutches of offspring. Haplotypes are inferred for each block of linked SNPs using the programs Haplore and Phase 2.1. Each multi-SNP haplotype is then treated as a separate allele, producing a highly polymorphic, 'microsatellite-like' marker. A simulation study is performed using haplotype frequencies derived from empirical data sets from Drosophila melanogaster and Mus musculus populations. We find that the markers produced are competitive with microsatellite loci in terms of single parent exclusion probabilities, particularly when using six or more linked SNPs to form a haplotype. These markers contain only modest rates of missing data and genotyping or phasing errors and thus should be seriously considered as molecular markers for parentage analysis, particularly when the study is interested in the functional significance of polymorphisms across the genome.     

1 + 1 = 3: Development and Validation of a SNP-Based Algorithm to Identify Genetic Contributions from Three Distinct Inbred Mouse Strains

State-of-the-art, genome-wide assessment of mouse genetic background uses single nucleotide polymorphism (SNP) PCR. As SNP analysis can use multiplex testing, it is amenable to high-throughput analysis and is the preferred method for shared resource facilities that offer genetic background assessment of mouse genomes. However, a typical individual SNP query yields only two alleles (A vs. B), limiting the application of this methodology to distinguishing contributions from no more than two inbred mouse strains. By contrast, simple sequence length polymorphism (SSLP) analysis yields multiple alleles but is not amenable to high-throughput testing. We sought to devise a SNP-based technique to identify donor strain origins when three distinct mouse strains potentially contribute to the genetic makeup of an individual mouse. A computational approach was used to devise a three-strain analysis (3SA) algorithm that would permit identification of three genetic backgrounds while still using a binary-output SNP platform. A panel of 15 mosaic mice with contributions from BALB/c, C57Bl/6, and DBA/2 genetic backgrounds was bred and analyzed using a genome-wide SNP panel using 1449 markers. The 3SA algorithm was applied and then validated using SSLP. The 3SA algorithm assigned 85% of 1449 SNPs as informative for the C57Bl/6, BALB/c, or DBA/2 backgrounds, respectively. Testing the panel of 15 F2 mice, the 3SA algorithm predicted donor strain origins genome-wide. Donor strain origins predicted by the 3SA algorithm correlated perfectly with results from individual SSLP markers located on five different chromosomes (n=70 tests). We have established and validated an analysis algorithm based on binary SNP data that can successfully identify the donor strain origins of chromosomal regions in mice that are bred from three distinct inbred mouse strains.     

A Rapid Genotyping Assay for Segregating Human Olfactory Receptor Pseudogenes

Variation in odor perception between individuals is initiated by binding of “odorant” molecules to olfactory receptors (ORs) located in the nasal cavity. To determine the mechanism for variation in odor perception, identification of specific ligands for a large number of ORs is required. However, it has been difficult to identify specific ligands, and ligands have been identified for only 2–3% of the hundreds of mammalian ORs. One way to increase the number of identified ligands is to take advantage of >60 human OR genes that are segregating as a result of a single nucleotide polymorphism, between a functional intact allele and a nonfunctional pseudogene allele. Potential ligands for these ORs can be identified by correlating odor perception of an individual with their genotype [intact/intact (I/I) vs. pseudogene/pseudogene (P/P)] for an OR gene. For this type of study, genotypes must be determined for a large number of individuals. We have developed a PCR-based assay to distinguish between the intact and pseudogene alleles of 49 segregating human OR genes and to determine an individual''s genotype for these genes. To facilitate rapid determination of genotypes for a large number of individuals, the assay uses a small number of simple steps and equipment commonly found in most molecular biology and biochemistry laboratories. Although this assay was developed to distinguish between polymorphisms in OR genes, it can easily be adapted for use in distinguishing single nucleotide polymorphisms in any gene or chromosomal locus.     

Analysis of population differentiation in North Eurasian cattle (Bos taurus) using single nucleotide polymorphisms in three genes associated with production traits

Single nucleotide polymorphisms (SNPs) in growth hormone 1 (GH1), insulin-like growth factor 1 (IGF1) and leptin (LEP), all candidates for production traits in cattle, were characterized in North Eurasian cattle breeds. Allele frequencies of IGF1 exhibited significant (P < 0.05) deviation from neutral expectation and therefore, might be associated with divergence in North Eurasian cattle because of genetic selection. Allele frequencies and lower heterozygosity of LEP may indicate a recent introduction of an alternative allele in this geographic region. Locus F(ST) estimates were highest for IGF1 (0.151, sigma = 0.042) and lowest for GH (0.062, sigma = 0.020). Our results suggest a slightly higher population differentiation across the candidate genes (FST = 0.108) than across microsatellites (FST = 0.095), possibly because of selection and stochastic effects.     

Multi-locus inference of population structure: a comparison between single nucleotide polymorphisms and microsatellites

Although growing numbers of single nucleotide polymorphisms (SNPs) and microsatellites (short tandem repeat polymorphisms or STRPs) are used to infer population structure, their relative properties in this context remain poorly understood. SNPs and STRPs mutate differently, suggesting multi-locus genotypes at these loci might differ in ability to detect population structure. Here, we use coalescent simulations to measure the power of sets of SNPs and STRPs to identify population structure. To maximize the applicability of our results to empirical studies, we focus on the popular STRUCTURE analysis and evaluate the role of several biological and practical factors in the detection of population structure. We find that: (1) fewer unlinked STRPs than SNPs are needed to detect structure at recent divergence times <0.3 N_e generations; (2) accurate estimation of the number of populations requires many fewer STRPs than SNPs; (3) for both marker types, declines in power due to modest gene flow (N_em=1.0) are largely negated by increasing marker number; (4) variation in the STRP mutational model affects power modestly; (5) SNP haplotypes (θ=1, no recombination) provide power comparable with STRP loci (θ=10); (6) ascertainment schemes that select highly variable STRP or SNP loci increase power to detect structure, though ascertained data may not be suitable to other inference; and (7) when samples are drawn from an admixed population and one of its parent populations, the reduction in power to detect two populations is greater for STRPs than SNPs. These results should assist the design of multi-locus studies to detect population structure in nature.     

Anonymous nuclear markers for the eastern fence lizard,Sceloporus undulatus

We present results from a screen for de novo variable nuclear loci using a genomic library approach in Sceloporus undulatus, the eastern fence lizard. We tested amplification success for 77 primer pairs in S. undulatus, Sceloporus occidentalis and Sceloporus grammicus. Many loci amplified in all three species suggesting that our primers will be useful for developing sequencing or single nucleotide polymorphism (SNP) genotyping markers in other sceloporine lizards. We also sequenced 19 loci, containing 158 variable sites, for 91 S. undulatus individuals. We report high levels of nucleotide variation in this species with an average of 38 SNPs per kilobase.