Comparing single-nucleotide polymorphism marker-based and microsatellite marker-based linkage analyses

We compared linkage analysis results for an alcoholism trait, ALDX1 (DSM-III-R and Feigner criteria) using a nonparametric linkage analysis method, which takes into account allele sharing among several affected persons, for both microsatellite and single-nucleotide polymorphism (SNP) markers (Affymetrix and Illumina) in the Collaborative Study on the Genetics of Alcoholism (COGA) dataset provided to participants at the Genetic Analysis Workshop 14 (GAW14). The two sets of linkage results from the dense Affymetrix SNP markers and less densely spaced Illumina SNP markers are very similar. The linkage analysis results from microsatellite and SNP markers are generally similar, but the match is not perfect. Strong linkage peaks were found on chromosome 7 in three sets of linkage analyses using both SNP and microsatellite marker data. We also observed that for SNP markers, using the given genetic map and using the map by converting 1 megabase pair (1 Mb) to 1 centimorgan (cM), did not change the linkage results. We recommend the use of the 1 Mb-to-1 cM converted map in a first round of linkage analysis with SNP markers in which map integration is an issue.     

Power calculations for selective genotyping in QTL mapping in backcross mice

Selective genotyping concerns the genotyping of a portion of individuals chosen on the basis of their phenotypic values. Often individuals are selected for genotyping from the high and low extremes of the phenotypic distribution. This procedure yields savings in cost and time by decreasing the total number of individuals genotyped. Previous work by Darvasi et al. (1993) has shown that the power to detect a QTL by genotyping 40-50 % of a population is roughly equivalent to genotyping the entire sample. However, these power studies have not accounted for different strategies of analysing the data when phenotypes of individuals in the middle are excluded, nor have they investigated the genome-wide type I error rate under these different strategies or different selection percentages. Further, these simulation studies have not considered markers over the entire genome. In this paper, we present simulation studies of power for the maximum likelihood approach to QTL mapping by Lander & Botstein (1989) in the context of selective genotyping. We calculate the power of selectively genotyping the individuals from the middle of the phenotypic distribution when performing QTL mapping over the whole mouse genome.     

Powdery mildew resistance in roses: QTL mapping in different environments using selective genotyping

Podosphaera pannosa, the causal agent of rose powdery mildew, hampers the production of cut roses throughout the world. A major tool to control this disease is the use of resistant plant material. Single resistance genes, like Rpp1, may be overcome within a few years by high risk pathogens like powdery mildews. Durable resistance could be achieved using quantitative resistances. Here we describe mapping of QTLs for resistance to P. pannosa in six different environments (artificial and natural infections in the greenhouse over 3 years and natural infections in the field over 2 years). AFLPs, RGAs and other marker types were used to construct an integrated linkage map for the diploid population 97/7 containing 233 markers. In a selective genotyping procedure, marker segregation was analysed for 170 of the up to 270 phenotyped individuals. We identified seven linkage groups with an average length of 60 cM, corresponding to seven rose chromosomes in the haploid set. Using an LOD significance threshold of 3.9 we detected a total of 28 QTLs for the nine powdery mildew disease scores under analysis. Using the data from artificial inoculations with powdery mildew race 9, three resistance QTLs explaining about 84% of the variability were mapped. Twelve and 15 QTLs were detected for resistance to naturally occurring infections in the greenhouse and in the field, respectively, over several years.     

Identification and validation of QTL for Sclerotinia midstalk rot resistance in sunflower by selective genotyping

Midstalk rot, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is an important cause of yield loss in sunflower (Helianthus annuus L.). Objectives of this study were to: (1) estimate the number, genomic positions and genetic effects of quantitative trait loci (QTL) for resistance to midstalk rot in line TUB-5-3234, derived from an interspecific cross; (2) determine congruency of QTL between this line and other sources of resistance; and (3) make inferences about the efficiency of selective genotyping (SG) in detecting QTL conferring midstalk rot resistance in sunflower. Phenotypic data for three resistance (stem lesion, leaf lesion and speed of fungal growth) and two morphological (leaf length and leaf length with petiole) traits were obtained from 434 F₃ families from cross CM625 (susceptible) × TUB-5-3234 (resistant) under artificial infection in field experiments across two environments. The SG was applied by choosing the 60 most resistant and the 60 most susceptible F₃ families for stem lesion. For genotyping of the respective F₂ plants, 78 simple sequence repeat markers were used. Genotypic variances were highly significant for all traits. Heritabilities and genotypic correlations between resistance traits were moderate to high. Three to four putative QTL were detected for each resistance trait explaining between 40.8% and 72.7% of the genotypic variance ( ). Two QTL for stem lesion showed large genetic effects and corroborated earlier findings from the cross NDBLOS_sel (resistant) × CM625 (susceptible). Our results suggest that SG can be efficiently used for QTL detection and the analysis of congruency for resistance genes across populations.     

Selective genotyping for QTL detection using sib pair analysis in outbred populations with hierarchical structures

A simulation study illustrates the effects of the inclusion of half-sib pairs as well as the effects of selective genotyping on the power of detection and the parameter estimates in a sib pair analysis of data from an outbred population. The power of QTL detection obtained from samples of sib pairs selected according to their within family variance or according to the mean within family variance within half sib family was compared and contrasted with the power obtained when only full sib pair analysis was used. There was an increase in power (4–16%) and decrease in the bias of parameter estimates with the use of half-sib information. These improvements in power and parameter estimates depended on the number of the half sib pairs (half sib family size). Almost the same power as that obtained using all the available sib pairs could be achieved by selecting only 50–60% the animals. The most effective method was to select both full and half sib pairs on the basis of high within full sib family variance for the trait in question. The QTL position estimates were in general slightly biased towards the center of the chromosome and the QTL variance estimates were biased upwards, there being quite large differences in bias depending on the selection method.     

Power analysis of QTL detection in half-sib families using selective DNA pooling

Individual loci of economic importance (QTL) can be detected by comparing the inheritance of a trait and the inheritance of loci with alleles readily identifiable by laboratory methods (genetic markers). Data on allele segregation at the individual level are costly and alternatives have been proposed that make use of allele frequencies among progeny, rather than individual genotypes. Among the factors that may affect the power of the set up, the most important are those intrinsic to the QTL: the additive effect of the QTL, and its dominance, and distance between markers and QTL. Other factors are relative to the choice of animals and markers, such as the frequency of the QTL and marker alleles among dams and sires. Data collection may affect the detection power through the size of half-sib families, selection rate within families, and the technical error incurred when estimating genetic frequencies. We present results for a sensitivity analysis for QTL detection using pools of DNA from selected half-sibs. Simulations showed that conclusive detection may be achieved with families of at least 500 half-sibs if sires are chosen on the criteria that most of their marker alleles are either both missing, or one is fixed, among dams.     

Asymptotic variances of QTL estimators with selective DNA pooling

Investigation on QTL-marker linkage usually requires a great number of observed recombinations, inferred from combined analysis of phenotypes and genotypes. To avoid costly individual genotyping, inferences on QTL position and effects can instead make use of marker allele frequencies. DNA pooling of selected samples makes allele frequency estimation feasible for studies involving large sample sizes. Linkage studies in outbred populations have traditionally exploited half-sib family designs; within the animal production context, half-sibships provide large families that are highly suitable for DNA pooling. Estimators for QTL position and effect have been proposed that make use of information from flanking markers. We present formulas derived by the delta method for the asymptotic variance of these estimators.     

Efficient association mapping of quantitative trait loci with selective genotyping

Selective genotyping (i.e., genotyping only those individuals with extreme phenotypes) can greatly improve the power to detect and map quantitative trait loci in genetic association studies. Because selection depends on the phenotype, the resulting data cannot be properly analyzed by standard statistical methods. We provide appropriate likelihoods for assessing the effects of genotypes and haplotypes on quantitative traits under selective-genotyping designs. We demonstrate that the likelihood-based methods are highly effective in identifying causal variants and are substantially more powerful than existing methods.     

Identity-by-descent genomic selection using selective and sparse genotyping

Background

Genomic selection methods require dense and widespread genotyping data, posing a particular challenge if both sexes are subject to intense selection (e.g., aquaculture species). This study focuses on alternative low-cost genomic selection methods (IBD-GS) that use selective genotyping with sparse marker panels to estimate identity-by-descent relationships through linkage analysis. Our aim was to evaluate the potential of these methods in selection programs for continuous traits measured on sibs of selection candidates in a typical aquaculture breeding population.

Methods

Phenotypic and genomic data were generated by stochastic simulation, assuming low to moderate heritabilities (0.10 to 0.30) for a Gaussian trait measured on sibs of the selection candidates in a typical aquaculture breeding population that consisted of 100 families (100 training animals and 20 selection candidates per family). Low-density marker genotype data (~ 40 markers per Morgan) were used to trace genomic identity-by-descent relationships. Genotyping was restricted to selection candidates from 30 phenotypically top-ranking families and varying fractions of their phenotypically extreme training sibs. All phenotypes were included in the genetic analyses. Classical pedigree-based and IBD-GS models were compared based on realized genetic gain over one generation of selection.

Results

Genetic gain increased substantially (13 to 32%) with IBD-GS compared to classical selection and was greatest with higher heritability. Most of the extra gain from IBD-GS was obtained already by genotyping the 5% phenotypically most extreme sibs within the pre-selected families. Additional genotyping further increased genetic gains, but these were small when going from genotyping 20% of the extremes to all phenotyped sibs. The success of IBD-GS with sparse and selective genotyping can be explained by the fact that within-family haplotype blocks are accurately traced even with low-marker densities and that most of the within-family variance for normally distributed traits is captured by a small proportion of the phenotypically extreme sibs.

Conclusions

IBD-GS was substantially more effective than classical selection, even when based on very few markers and combined with selective genotyping of small fractions of the population. The study shows that low-cost GS programs can be successful by combining sparse and selective genotyping with pedigree and linkage information.     

Universal SNP genotyping assay with fluorescence polarization detection

The degree of fluorescence polarization (FP) of a fluorescent molecule is a reflection of its molecular weight (Mr). FP is therefore a useful detection methodfor homogeneous assays in which the starting reagents and products differ significantly in Mr. We have previously shown that FP is a good detection method for the single-base extension and the 5'-nuclease assays. In this report, we describe a universal, optimized single-base extension assay for genotyping single nucleotide polymorphisms (SNPs). This assay, which we named the template-directed dye-terminator incorporation assay with fluorescence polarization detection (FP-TDI), uses four spectrally distinct dye terminators to achieve universal assay conditions. Even without optimization, approximately 70% of all SNP markers tested yielded robust assays. The addition of an E. coli ssDNA-binding protein just before the FP reading significantly increased FP values of the products and brought the success rate of FP-TDI assays up to 90%. Increasing the amount of dye terminators and reducing the number of thermal cycles in the single-base extension step of the assay increased the separation of the FP values benveen the products corresponding to different genotypes and improved the success rate of the assay to 100%. In this study the genomic DNA samples of 90 individuals were typed for a total of 38 FP-TDI assays (using both the sense and antisense TDI primers for 19 SNP markers). With the previously described modifications, the FP-TDI assay gave unambiguous genotyping data for all the samples tested in the 38 FP-TDI assays. When the genotypes determined by the FP-TDI and 5'-nuclease assays were compared, they were in 100% concordance for all experiments (a total of 3420 genotypes). The four-dye-terminator master mixture described here can be used for assaying any SNP marker and greatly simplifies the SNP genotyping assay design.     

Qxpak: a versatile mixed model application for genetical genomics and QTL analyses

MOTIVATION: Current methodology and software for quantitative trait loci (QTL) analyses do not use all available information and are inadequate to deal with the huge amount of QTL analyses to be needed in forecoming genetical genomics' studies. RESULTS: We show that a mixed model statistical framework provides a very flexible tool for QTL modeling in a variety of populations, be it a cross between inbred lines, a within population study, or experiments involving a mixture of populations or crosses. The software allows multitrait and multiQTL analyses, inclusion of infinitesimal genetic value and a batch multitrait option suitable for genetical genomics studies. It also allows massive association studies between single nucleotide polymorphisms and the trait(s) of interest. AVAILABILITY: A software (Qxpak), together with a manual and example files, is freely available for research purposes. So far, the compiled program is available for linux systems, the windows version will follow soon. See http://www.icrea.es/pag.asp?id=Miguel.Perez     

SNP marker detection and genotyping in tilapia

We have generated a unique resource consisting of nearly 175 000 short contig sequences and 3569 SNP markers from the widely cultured GIFT (Genetically Improved Farmed Tilapia) strain of Nile tilapia (Oreochromis niloticus). In total, 384 SNPs were selected to monitor the wider applicability of the SNPs by genotyping tilapia individuals from different strains and different geographical locations. In all strains and species tested (O. niloticus, O. aureus and O. mossambicus), the genotyping assay was working for a similar number of SNPs (288–305 SNPs). The actual number of polymorphic SNPs was, as expected, highest for individuals from the GIFT population (255 SNPs). In the individuals from an Egyptian strain and in individuals caught in the wild in the basin of the river Volta, 197 and 163 SNPs were polymorphic, respectively. A pairwise calculation of Nei’s genetic distance allowed the discrimination of the individual strains and species based on the genotypes determined with the SNP set. We expect that this set will be widely applicable for use in tilapia aquaculture, e.g. for pedigree reconstruction. In addition, this set is currently used for assaying the genetic diversity of native Nile tilapia in areas where tilapia is, or will be, introduced in aquaculture projects. This allows the tracing of escapees from aquaculture and the monitoring of effects of introgression and hybridization.     

Empirical evaluation of selective DNA pooling to map QTL in dairy cattle using a half-sib design by comparison to individual genotyping and interval mapping

This study represents the first attempt at an empirical evaluation of the DNA pooling methodology by comparing it to individual genotyping and interval mapping to detect QTL in a dairy half-sib design. The findings indicated that the use of peak heights from the pool electropherograms without correction for stutter (shadow) product and preferential amplification performed as well as corrected estimates of frequencies. However, errors were found to decrease the power of the experiment at every stage of the pooling and analysis. The main sources of errors include technical errors from DNA quantification, pool construction, inconsistent differential amplification, and from the prevalence of sire alleles in the dams. Additionally, interval mapping using individual genotyping gains information from phenotypic differences between individuals in the same pool and from neighbouring markers, which is lost in a DNA pooling design. These errors cause some differences between the markers detected as significant by pooling and those found significant by interval mapping based on individual selective genotyping. Therefore, it is recommended that pooled genotyping only be used as part of an initial screen with significant results to be confirmed by individual genotyping. Strategies for improving the efficiency of the DNA pooling design are also presented.     

A major QTL associated with Fusarium oxysporum race 1 resistance identified in genetic populations derived from closely related watermelon lines using selective genotyping and genotyping-by-sequencing for SNP discovery

Key message

A major quantitative trait locus (QTL) for Fusarium oxysporum Fr. f. sp. niveum race 1 resistance was identified by employing a “selective genotyping” approach together with genotyping-by-sequencing technology to identify QTLs and single nucleotide polymorphisms associated with the resistance among closely related watermelon genotypes.

Abstract

Fusarium wilt is a major disease of watermelon caused by the soil-borne fungus Fusarium oxysporum Schlechtend.:Fr. f. sp. niveum (E.F. Sm.) W.C. Snyder & H.N. Hans (Fon). In this study, a genetic population of 168 F₃ families (24 plants in each family) exhibited continuous distribution for Fon race 1 response. Using a “selective genotyping” approach, DNA was isolated from 91 F₂ plants whose F₃ progeny exhibited the highest resistance (30 F₂ plants) versus highest susceptibility (32 F₂ plants), or moderate resistance to Fon race 1 (29 F₂ plants). Genotyping-by-sequencing (GBS) technology was used on these 91 selected F₂ samples to produce 266 single nucleotide polymorphism (SNP) markers, representing the 11 chromosomes of watermelon. A major quantitative trait locus (QTL) associated with resistance to Fon race 1 was identified with a peak logarithm of odds (LOD) of 33.31 and 1-LOD confidence interval from 2.3 to 8.4 cM on chromosome 1 of the watermelon genetic map. This QTL was designated “Fo-1.1” and is positioned in a genomic region where several putative pathogenesis-related or putative disease-resistant gene sequences were identified. Additional independent, but minor QTLs were identified on chromosome 1 (LOD 4.16), chromosome 3 (LOD 4.36), chromosome 4 (LOD 4.52), chromosome 9 (LOD 6.8), and chromosome 10 (LOD 5.03 and 4.26). Following the identification of a major QTL for resistance using the “selective genotyping” approach, all 168 plants of the F ₂ population were genotyped using the SNP nearest the peak LOD, confirming the association of this SNP marker with Fon race 1 resistance. The results in this study should be useful for further elucidating the mechanism of resistance to Fusarium wilt and in the development of molecular markers for use in breeding programs of watermelon.     

Power and false-positive rate in QTL detection with near-isogenic line libraries

Libraries of near-isogenic lines (NILs) were used for quantitative trait locus (QTL) detection in model species and economically important crops. The experimental design and genetic architecture of the considered traits determine the statistical properties of QTL detection. The objectives of our simulation study were to (i) investigate the population sizes required to develop NIL libraries in barley and maize, (ii) compare NIL libraries with nonoverlapping and overlapping donor segments and (iii) study the number of QTLs and the size of their effects with respect to the power and the false-positive rate of QTL detection. In barley, the development of NIL libraries with target segment lengths of 10 c and marker distances of 5 c was possible using a BC₃S₂ backcrossing scheme and population sizes of 140. In maize, population sizes larger than 200 were required. Selection for the recipient parent genome at markers flanking the target segments with distances between 5 and 10 c was required for an efficient control of the false-positive rate. NIL libraries with nonoverlapping donor chromosome segments had a greater power of QTL detection and a smaller false-positive rate than libraries with overlapping segments. Major genes explaining 30% of the genotypic difference between the donor and recipient were successfully detected even with low heritabilities of 0.5, whereas for minor genes explaining 5 !or 10%, high heritabilities of 0.8 or 0.9 were required. The presented results can assist geneticists and breeders in the efficient development of NIL libraries for QTL detection.     

QTL analyses of lineage-negative mouse bone marrow cells labeled with Sca-1 and c-Kit

Differences in the number of functionally and/or phenotypically defined bone marrow cells in inbred mouse strains have been exploited to map quantitative trait loci (QTL) that determine the variation in cell frequency. To extend this approach to the differences in the stem/progenitor cell compartment in CBA/H and C57BL/6 mice, we have exploited the resolution of flow cytometry and the power of QTL analyses in 124 F₂ mice to analyze lineage-negative (Lin⁻) bone marrow cells according to the intensity of labeling with Sca-1 and c-Kit. In the Lin⁻ Sca-1⁺ c-Kit⁺ enriched population, six QTL were identified: one significant and five suggestive. Whereas previous in vitro clonogenic, LTC-IC, day 35 CAFC, and flow cytometry each identified different QTL, our approach identified the same or very similar QTL at all three loci (chromosomes 1, 17, and 18) as well as QTL on chromosomes 6 and 10. In silico analyses implicate hematopoietic stem cell homing involving Cxcr4 and Cxcl12 as being the determining pathway. The mapping of the same or very similar QTL in independent studies using different assay(s) suggests a common genetic determinant, and thus reinforces the biological and genetic significance of the QTL. These data also suggest that mouse bone marrow cell subpopulations can be functionally, phenotypically, and genetically defined.     

Functional analysis of minichromosome replication: bidirectional and unidirectional replication from the Escherichia coli replication origin, oriC.

Replicating molecules of minichromosomes pCM959 and pOC24 were analyzed by electron microscopy. Replication of pCM959 proceeded bidirectionally from the replication origin, oriC, in about 60% of the molecules; the rest of the molecules replicated unidirectionally in either direction. pOC24, in which deoxyribonucleic acid to the right (clockwise) of the oriC segment is deleted, seemed to replicate predominantly unidirectionally counterclockwise from oriC.     

QGENE: software for marker-based genomic analysis and breeding

Efficient use of DNA markers for genomic research and crop improvement will depend as much on computational tools as on laboratory technology. The large size and multidimensional character of marker datasets invite novel approaches to data visualization. Described here is a software application embodying two design principles: conventional reduction of raw genetic marker data to numerical summary statistics, and fast, interactive graphical display of both data and statistics. The program performs various analyses for mapping quantitative-trait loci in real or simulated datasets and other analyses in aid of phenotypic and marker-assisted breeding. Functionality is described and some output is illustrated.