Power of selective genotyping in genome-wide association studies of quantitative traits

The selective genotyping approach in quantitative genetics means genotyping only individuals with extreme phenotypes. This approach is considered an efficient way to perform gene mapping, and can be applied in both linkage and association studies. Selective genotyping in association mapping of quantitative trait loci was proposed to increase the power of detecting rare alleles of large effect. However, using this approach, only common variants have been detected. Studies on selective genotyping have been limited to single-locus scenarios. In this study we aim to investigate the power of selective genotyping in a genome-wide association study scenario, and we specifically study the impact of minor allele frequency of variants on the power of this approach. We use the Genetic Analysis Workshop 16 rheumatoid arthritis whole-genome data from the North American Rheumatoid Arthritis Consortium. Two quantitative traits, anti-cyclic citrullinated peptide and rheumatoid factor immunoglobulin M, and one binary trait, rheumatoid arthritis affection status, are used in the analysis. The power of selective genotyping is explored as a function of three parameters: sampling proportion, minor allele frequency of single-nucleotide polymorphism, and test level. The results show that the selective genotyping approach is more efficient in detecting common variants than detecting rare variants, and it is efficient only when the level of declaring significance is not stringent. In summary, the selective genotyping approach is most suitable for detecting common variants in candidate gene-based studies

A Simple Bias Correction in Linear Regression for Quantitative Trait Association Under Two-Tail Extreme Selection

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias

Comparison of methods for analysis of selective genotyping survival data

Survival traits and selective genotyping datasets are typically not normally distributed, thus common models used to identify QTL may not be statistically appropriate for their analysis. The objective of the present study was to compare models for identification of QTL associated with survival traits, in particular when combined with selective genotyping. Data were simulated to model the survival distribution of a population of chickens challenged with Marek disease virus. Cox proportional hazards (CPH), linear regression (LR), and Weibull models were compared for their appropriateness to analyze the data, ability to identify associations of marker alleles with survival, and estimation of effects when all individuals were genotyped (full genotyping) and when selective genotyping was used. Little difference in power was found between the CPH and the LR model for low censoring cases for both full and selective genotyping. The simulated data were not transformed to follow a Weibull distribution and, as a result, the Weibull model generally resulted in less power than the other two models and overestimated effects. Effect estimates from LR and CPH were unbiased when all individuals were genotyped, but overestimated when selective genotyping was used. Thus, LR is preferred for analyzing survival data when the amount of censoring is low because of ease of implementation and interpretation. Including phenotypic data of non-genotyped individuals in selective genotyping analysis increased power, but resulted in LR having an inflated false positive rate, and therefore the CPH model is preferred for this scenario, although transformation of the data may also make the Weibull model appropriate for this case. The results from the research presented herein are directly applicable to interval mapping analyses

A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias. © The Author(s) 2011.published_or_final_versionSpringer Open Choice, 21 Feb 201

Influence of genotyping error in linkage mapping for complex traits – an analytic study

<p>Abstract</p> <p>Background</p> <p>Despite the current trend towards large epidemiological studies of unrelated individuals, linkage studies in families are still thoroughly being utilized as tools for disease gene mapping. The use of the single-nucleotide-polymorphisms (SNP) array technology in genotyping of family data has the potential to provide more informative linkage data. Nevertheless, SNP array data are not immune to genotyping error which, as has been suggested in the past, could dramatically affect the evidence for linkage especially in selective designs such as affected sib pair (ASP) designs. The influence of genotyping error on selective designs for continuous traits has not been assessed yet.</p> <p>Results</p> <p>We use the identity-by-descent (IBD) regression-based paradigm for linkage testing to analytically quantify the effect of simple genotyping error models under specific selection schemes for sibling pairs. We show, for example, that in extremely concordant (EC) designs, genotyping error leads to decreased power whereas it leads to increased type I error in extremely discordant (ED) designs. Perhaps surprisingly, the effect of genotyping error on inference is most severe in designs where selection is least extreme. We suggest a genomic control for genotyping errors via a simple modification of the intercept in the regression for linkage.</p> <p>Conclusion</p> <p>This study extends earlier findings: genotyping error can substantially affect type I error and power in selective designs for continuous traits. Designs involving both EC and ED sib pairs are fairly immune to genotyping error. When those designs are not feasible the simple genomic control strategy that we suggest offers the potential to deliver more robust inference, especially if genotyping is carried out by SNP array technology.</p

AFLPs: genetic markers for paternity studies in newts (Triturus vulgaris)

DNA-based genetic markers can reveal paternity whenever the direct assignment of fathers to offspring is precluded by multiple matings and internal fertilisation. Microsatellites are the current marker of choice in many behavioural studies, and have revealed important insights into genetic mating systems of European amphibians. However, the number of amphibian species for which the time-consuming designing of locus-specific microsatellite primers was successful is still limited, and the cross-utilisation of existing markers to closely related taxa seems to have a particularly low success rate. Allozymes can infer parentage without a species-specific protocol, but, due to their low degree of polymorphism, in mate choice experiments require the a priori screening of individuals. Dominant markers such as RAPDs successfully identified closely-related amphibian species and their hybrids, but might be less suited to distinguish between closely related individuals with a putatively high frequency of shared bands

Genotyping of human and animal isolates of Giardia intestinalis : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Microbiology at Massey University

Giardia intestinalis is an important protozoan parasite that infects humans and animals. It has been suggested that cattle may be a major source of human Giardia infection so a dairy farming region of New Zealand was investigated. This thesis uses three molecular methods to genotype G. intestinalis isolates obtained from human and animal faecal specimens collected in the Waikato region of New Zealand, to determine if giardiasis is a zoonotic disease. Random amplification of polymorphic DNA (RAPD) and amplified fragment length polymorphism (AFLP) fingerprinting techniques were initially assessed for their ability to genotype G. intestinalis isolates. "Clear cut" evidence of zoonosis could not be established by either method, due to a low sample number. To determine the stability of the G. intestinalis genome an axenic culture of G. intestinalis trophozoites was stressed with toxic levels of metronidazole and the survivors, following a number of passages, were examined using AFLP and RAPD analysis. The DNA fingerprints were compared to those of the original wild-type with the results being indicative of an unstable G. intestinalis genome. A third molecular method was employed, which amplifies a portion of the tandemly repeated ribosomal DNA (rDNA). Each cyst contains 512 head to tail tandem repeat copies of the rRNA gene made up of both conserved and variable regions. The use of nested primers increased the sensitivity and specificity of the PCR reaction allowing the amplification of a 505bp rDNA fragment. DNA sequence analysis and alignment of the amplified products facilitated the comparison of G. intestinalis isolates. The relationship of the sequence data was generated and displayed using Splitstree software indicating that zoonosis did occur

Molecular variation of Trypanosoma brucei subspecies as revealed by AFLP fingerprinting

Genetic analysis of Trypanosoma spp. depends on the detection of variation between strains. We have used the amplified fragment length polymorphism (AFLP) technique to develop a convenient and reliable method for genetic characterization of Trypanosome (sub)species. AFLP accesses multiple independent sites within the genome and would allow a better definition of the relatedness of different Trypanosome (sub)species. Nine isolates (3 from each T. brucei subspecies) were tested with 40 AFLP primer combinations to identify the most appropriate pairs of restriction endonucleases and selective primers. Primers based on the recognition sequences of EcoRI and BglII were chosen and used to analyse 31 T. brucei isolates. Similarity levels calculated with the Pearson correlation coefficient ranged from 15 to 98%, and clusters were determined using the unweighted pair-group method using arithmetic averages (UPGMA). At the intraspecific level, AFLP fingerprints were grouped by numerical analysis in 2 main clusters, allowing a clear separation of T. b. gambiense (cluster I) from T. b. brucei and T. b. rhodesiense isolates (cluster II). Interspecies evaluation of this customized approach produced heterogeneous AFLP patterns, with unique genetic markers, except for T. evansi and T. equiperdum, which showed identical patterns and clustered together

Genome scan of Diabrotica virgifera virgifera for genetic variation associated with crop rotation tolerance

Crop rotation has been a valuable technique for control of Diabrotica virgifera virgifera for almost a century. However, during the last two decades, crop rotation has ceased to be effective in an expanding area of the US corn belt. This failure appears to be due to a change in the insect's oviposition behaviour, which, in all probability, has an underlying genetic basis. A preliminary genome scan using 253 amplified fragment-length polymorphism (AFLP) markers sought to identify genetic variation associated with the circumvention of crop rotation. Samples of D. v. virgifera from east-central Illinois, where crop rotation is ineffective, were compared with samples from Iowa at locations that the behavioural variant has yet to reach. A single AFLP marker showed signs of having been influenced by selection for the circumvention of crop rotation. However, this marker was not diagnostic. The lack of markers strongly associated with the trait may be due to an insufficient density of marker coverage throughout the genome. A weak but significant general heterogeneity was observed between the Illinois and Iowa samples at microsatellite loci and AFLP markers. This has not been detected in previous population genetic studies of D. v. virgifera and may indicate a reduction in gene flow between variant and wild-type beetles

A review of evidence on non-invasive prenatal diagnosis (NIPD) : tests for fetal RHD genotype

This report concentrates on three main areas. First and foremost, we set the background context for RhD NIPD in prenatal care. While the methodology chapter describes how the literature review was carried out and how additional information was collected, the second chapter provides an overview of the key issues associated with pregnancy of RhD negative women. We present background information based on publications from 1997 to 2006 which describe the genetic condition and its prevalence (RhD negativity) in populations, as well as the frequency of cases of sensitisation and HDN (haemolytic disease of the newborn). We also discuss current service provision for RhD negative women in a number of European countries and look at how the NIPD test might be set within current service contexts