Comparison Of Single Nucleotide Polymorphisms Research Articles

The developmental transcriptome of contrasting Arctic charr ( Salvelinus alpinus) morphs.

Species and populations with parallel evolution of specific traits can help illuminate how predictable adaptations and divergence are at the molecular and developmental level. Following the last glacial period, dwarfism and specialized bottom feeding morphology evolved rapidly in several landlocked Arctic charr Salvelinus alpinus populations in Iceland. To study the genetic divergence between small benthic morphs and limnetic morphs, we conducted RNA-sequencing charr embryos at four stages in early development. We studied two stocks with contrasting morphologies: the small benthic (SB) charr from Lake Thingvallavatn and Holar aquaculture (AC) charr. The data reveal significant differences in expression of several biological pathways during charr development. There was also an expression difference between SB- and AC-charr in genes involved in energy metabolism and blood coagulation genes. We confirmed differing expression of five genes in whole embryos with qPCR, including lysozyme and natterin-like which was previously identified as a fish-toxin of a lectin family that may be a putative immunopeptide.We also verified differential expression of 7 genes in the developing head that associated consistently with benthic v.s.limnetic morphology (studied in 4 morphs). Comparison of single nucleotide polymorphism (SNP) frequencies reveals extensive genetic differentiation between the SB and AC-charr (~1300 with more than 50% frequency difference). Curiously, three derived alleles in the otherwise conserved 12s and 16s mitochondrial ribosomal RNA genes are found in benthic charr. The data implicate multiple genes and molecular pathways in divergence of small benthic charr and/or the response of aquaculture charr to domestication. Functional, genetic and population genetic studies on more freshwater and anadromous populations are needed to confirm the specific loci and mutations relating to specific ecological traits in Arctic charr.

Empirical comparison of single nucleotide polymorphisms and microsatellites for population and demographic analyses of bowhead whales

Interest in bowhead whale stock structure has been high due to the species’ extreme historical depletion, differential rates of recovery, the potential effects of climate change, and the need to set appropriate quotas for aboriginal hunts. We present an analysis of 42 linked and unlinked single nucleotide polymorphisms (SNPs) among 3 bowhead whale stocks and within the Bering/Chukchi/Beaufort Seas (BCB) stock, and compare results with previously published results of mtDNA control region sequences and 22 microsatellites. We performed tests of population structure (FST, χ2, STRUCTURE), population assignment, and estimates of effective population size (Ne), and evaluated different numbers of loci and samples to estimate the relative statistical power of SNPs and microsatellites. Results indicate that this number of SNPs provides similar power to microsatellites to detect low levels of differentiation (FST = 0.005−0.03) between bowhead populations with sample sizes of at least 20 per population. Neither marker performed well for Bayesian analysis of population structure (STRUCTURE) for the strata that had high diversity coupled with low differentiation. This example is valuable in cautioning against use of STRUCTURE to exclude demographic independence of relatively abundant populations. Microsatellites provided greater precision for estimates of Ne and for assignment tests. All 3 genetic marker types are consistent with the BCB stock being a single population. For microsatellites, differences were found between individuals born before 1949 and those born after 1979. SNPs are continuing to prove valuable as tools for understanding structure and demography of populations, and are likely to prove beneficial for long-term monitoring of bowhead whales.

Levels and patterns of population genetic diversity in the red seaweedChondrus crispus(Florideophyceae): a direct comparison of single nucleotide polymorphisms and microsatellites

Single nucleotide polymorphisms (SNPs) are predicted to supersede microsatellites as the marker of choice for population genetic studies in the near future. To date, however, very few studies have directly compared both marker systems in natural populations, particularly in non-model organisms. In the present study, we compared the utility of SNPs and microsatellites for population genetic analysis of the red seaweed Chondrus crispus (Florideophyceae). Six SNP loci yielded very different patterns of intrapopulation genetic diversity compared to those obtained using seven moderately (mean 5.2 alleles) polymorphic microsatellite loci, although Bayesian clustering analysis gave largely congruent results between the two marker classes. A weak but significant pattern of isolation-by-distance was observed across scales from a few hundred metres to approximately 200 km using the combined SNP and microsatellite data set of 13 loci. Over larger scales, however, there was little correlation between genetic divergence and geographical distance. Our findings suggest that even a moderate number of SNPs is sufficient to determine patterns of genetic diversity across natural populations, and also highlight the fact that patterns of genetic variation in seaweeds arise through a complex interplay of short- and long-term natural processes, as well as anthropogenic influence. © 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, ••, ••‐••.

Comparison of single nucleotide polymorphisms and microsatellites in non-invasive genetic monitoring of a wolf population

Single nucleotide polymorphisms (SNPs) which represent the most widespread source of sequence variation in genomes, are becoming a routine application in several fields such as forensics, ecology and conservation genetics. Their use, requiring short amplifications, may allow a more efficient genotyping of degraded DNA. We provide the first application of SNP genotyping in an Italian non-invasive genetic monitoring project of the wolf. We compared three different techniques for genotyping SNPs: pyrosequencing, SNaPshot? and TaqMan? Probe Assay in Real-Time PCR. We successively genotyped nine SNPs using the TaqMan Probe Assay in 51 Italian wolves, 57 domestic dogs, 15 wolf x dog hybrids and 313 wolf scats collected in the northern Apennines. The obtained results were used to estimate genetic variability and PCR error rates in SNP genotyping protocols compared to standard microsatellite analysis. We evaluated the cost, laboratory effort and reliability of these different markers and discuss the possible future use of VeraCode, SNPlex and Fluidigm EP1 system in wild population monitoring.

167-P: Comparison of single nucleotide polymorphism and short tandem repeats in chimerism testing

167-P: Comparison of single nucleotide polymorphism and short tandem repeats in chimerism testing

Comparison of single nucleotide polymorphisms in the human interleukin-10 gene promoter between rheumatoid arthritis patients and normal subjects in Malaysia

Comparison of single nucleotide polymorphisms in the human interleukin-10 gene promoter between rheumatoid arthritis patients and normal subjects in Malaysia

Comparison of single nucleotide polymorphisms in the human interleukin-10 gene promoter between rheumatoid arthritis patients and normal subjects in Malaysia

In this study, three single nucleotide polymorphisms (SNPs) located within the promoter of the human interleukin (IL)-10 gene [rs1800896 (position: -1087G>A), rs1800871 (position: -824C>T) and rs1800872 (position: -597C>A)] were investigated in 84 rheumatoid arthritis (RA) patients and 95 age- and sex-matched healthy subjects using polymerase chain reaction-restriction fragment length polymorphism method. Production of IL-10 by peripheral blood lymphocytes from the RA patients and healthy subjects cultured in the presence of Concanavalin A (Con A) was determined by using enzyme-linked immunosorbent assay. The results show that the distribution of the IL-10 genotypes did not differ significantly between RA patients and healthy subjects (P>0.05). However, a significant difference was observed in allele frequencies of -824CT, -824TT, -597CA, and -597AA between the RA patients and healthy volunteers (P=0.04). The -1087A/-824T/-597A (ATA) haplotype, which comprises all mutant alleles, was associated with lower IL-10 production when compared with the other haplotypes. In contrast, the RA patients who did not display the ATA haplotype produced significantly higher levels of IL-10 when compared with those carrying either one (P=0.012) or two (P=0.005) ATA haplotypes. Our findings suggest that there is an association between SNPs in the promoter of the human IL-10 gene and susceptibility to RA.

“A Re-Evaluation of M. prototuberculosis”: Continuing the Debate

In his Opinion [1], Noel Smith questions that the Mycobacterium tuberculosis complex (MTBC) is a successful clone that emerged from a much broader and ancient mycobacterial species, whose extant representatives are Mycobacterium canettii and other smooth tubercle bacilli [2]. He suggests that our conclusion is weak because he sees it as solely based on comparison of single nucleotide polymorphisms (SNPs) in six housekeeping genes and the 16 sRNA gene, and because some of these genes also showed evidence of horizontal transfer. Smith's criticism mostly comes down to two important assertions: first, MTBC members did not emerge from the smooth strains; second, the smooth strains and MTBC members should not be seen as a single species.

Comparison of single-nucleotide polymorphisms and microsatellites in detecting quantitative trait loci for alcoholism: The Collaborative Study on the Genetics of Alcoholism

BackgroundThe feasibility of effectively analyzing high-density single nucleotide polymorphism (SNP) maps in whole genome scans of complex traits is not known. The purpose of this study was to compare variance components linkage results using different density marker maps in data from the Collaborative Study on the Genetics of Alcoholism (COGA). Marker maps having an average spacing of 10 cM (microsatellite), 0.78 cM (SNP1), and 0.31 cM (SNP2) were used to identify quantitative trait loci (QTLs) affecting maximum number of alcoholic drinks consumed in a 24-hour period (lnmaxalc).ResultsHeritability of lnmaxalc was estimated to be 15%. Multipoint variance components linkage analysis revealed similar linkage patterns among the three marker panels, with the SNP maps consistently yielding higher LOD scores. Robust LOD scores > 1.0 were observed on chromosomes 1 and 13 for all three marker maps. Additional LODs > 1.0 were observed on chromosome 4 with both SNP maps and on chromosomes 18 and 21 with the SNP2 map. Peak LOD scores for lnmaxalc were observed on chromosome 1, although none reached genome-wide statistical significance. Quantile-quantile plots revealed that the multipoint distribution of SNP results appeared to fit the asymptotic null distribution better than the twopoint results.ConclusionIn conclusion, variance-components linkage analysis using high-density SNP maps provided higher LOD scores compared with the standard microsatellite map, similar to studies using nonparametric linkage methods. Widespread application of SNP maps will depend on further improvements in the computational methods implemented in current software packages.

Comparison of single-nucleotide polymorphisms and microsatellites in inference of population structure

Single-nucleotide polymorphisms (SNPs) are a class of attractive genetic markers for population genetic studies and for identifying genetic variations underlying complex traits. However, the usefulness and efficiency of SNPs in comparison to microsatellites in different scientific contexts, e.g., population structure inference or association analysis, still must be systematically evaluated through large empirical studies. In this article, we use the Collaborative Studies on Genetics of Alcoholism (COGA) data from Genetic Analysis Workshop 14 (GAW14) to compare the performance of microsatellites and SNPs in the whole human genome in the context of population structure inference. A total of 328 microsatellites and 15,840 SNPs are used to infer population structure in 236 unrelated individuals. We find that, on average, the informativeness of random microsatellites is four to twelve times that of random SNPs for various population comparisons, which is consistent with previous studies. Our results also indicate that for the combined set of microsatellites and SNPs, SNPs constitute the majority among the most informative markers and the use of these SNPs leads to better inference of population structure than the use of microsatellites. We also find that the inclusion of less informative markers may add noise and worsen the results.

Comparison of single-nucleotide polymorphisms and microsatellite markers for linkage analysis in the COGA and simulated data sets for Genetic Analysis Workshop 14: Presentation Groups 1, 2, and 3

The papers in presentation groups 1-3 of Genetic Analysis Workshop 14 (GAW14) compared microsatellite (MS) markers and single-nucleotide polymorphism (SNP) markers for a variety of factors, using multiple methods in both data sets provided to GAW participants. Group 1 focused on data provided from the Collaborative Study on the Genetics of Alcoholism (COGA). Group 2 focused on data simulated for the workshop. Group 3 contained analyses of both data sets. Issues examined included: information content, signal strength, localization of the signal, use of haplotype blocks, population structure, power, type I error, control of type I error, the effect of linkage disequilibrium, and computational challenges. There were several broad resulting observations. 1) Information content was higher for dense SNP marker panels than for MS panels, and dense SNP markers sets appeared to provide slightly higher linkage scores and slightly higher power to detect linkage than MS markers. 2) Dense SNP panels also gave higher type I errors, suggesting that increased test thresholds may be needed to maintain the correct error rate. 3) Dense SNP panels provided better trait localization, but only in the COGA data, in which the MS markers were relatively loosely spaced. 4) The strength of linkage signals did not vary with the density of SNP panels, once the marker density was approximately 1 SNP/cM. 5) Analyses with SNPs were computationally challenging, and identified areas where improvements in analysis tools will be necessary to make analysis practical for widespread use.