Mapping quantitative trait loci in selected breeding populations: A segregation distortion approach

Quantitative trait locus (QTL) mapping is often conducted in line-crossing experiments where a sample of individuals is randomly selected from a pool of all potential progeny. QTLs detected from such an experiment are important for us to understand the genetic mechanisms governing a complex trait, but may not be directly relevant to plant breeding if they are not detected from the breeding population where selection is targeting for. QTLs segregating in one population may not necessarily segregate in another population. To facilitate marker-assisted selection, QTLs must be detected from the very population which the selection is targeting. However, selected breeding populations often have depleted genetic variation with small population sizes, resulting in low power in detecting useful QTLs. On the other hand, if selection is effective, loci controlling the selected trait will deviate from the expected Mendelian segregation ratio. In this study, we proposed to detect QTLs in selected breeding populations via the detection of marker segregation distortion in either a single population or multiple populations using the same selection scheme. Simulation studies showed that QTL can be detected in strong selected populations with selected population sizes as small as 25 plants. We applied the new method to detect QTLs in two breeding populations of rice selected for high grain yield. Seven QTLs were identified, four of which have been validated in advanced generations in a follow-up study. Cloned genes in the vicinity of the four QTLs were also reported in the literatures. This mapping-by-selection approach provides a new avenue for breeders to improve breeding progress. The new method can be applied to breeding programs not only in rice but also in other agricultural species including crops, trees and animals.     

A quantitative trait locus analysis of natural genetic variation for Drosophila melanogaster oxidative stress survival

Little is known about natural genetic variation for survival under oxidative stress conditions or whether genetic variation for oxidative stress survival is associated with that for life-history traits. We have investigated survival in a high-oxygen environment at 2 adult densities using a set of recombinant inbred lines (RILs) isolated from a natural population of Drosophila melanogaster. Female and male oxidative stress survival was highly correlated. Quantitative trait loci (QTLs) for oxidative stress survival were identified on both autosomes. These QTLs were sometimes sex or density specific but were most often not. QTLs were identified that colocalize to the same region of the genome as longevity in other studies using the same set of RILs. We also determined early-age egg production and found QTLs for this trait, but there was no support for an association between oxidative stress survival and egg production.     

Mapping and analysis of quantitative trait loci in experimental populations

Simple statistical methods for the study of quantitative trait loci (QTL), such as analysis of variance, have given way to methods that involve several markers and high-resolution genetic maps. As a result, the mapping community has been provided with statistical and computational tools that have much greater power than ever before for studying and locating multiple and interacting QTL. Apart from their immediate practical applications, the lessons learnt from this evolution of QTL methodology might also be generally relevant to other types of functional genomics approach that are aimed at the dissection of complex phenotypes, such as microarray assessment of gene expression.     

Joint linkage and linkage disequilibrium mapping of quantitative trait loci in natural populations

Linkage analysis and allelic association (also referred to as linkage disequilibrium) studies are two major approaches for mapping genes that control simple or complex traits in plants, animals, and humans. But these two approaches have limited utility when used alone, because they use only part of the information that is available for a mapping population. More recently, a new mapping strategy has been designed to integrate the advantages of linkage analysis and linkage disequilibrium analysis for genome mapping in outcrossing populations. The new strategy makes use of a random sample from a panmictic population and the open-pollinated progeny of the sample. In this article, we extend the new strategy to map quantitative trait loci (QTL), using molecular markers within the EM-implemented maximum-likelihood framework. The most significant advantage of this extension is that both linkage and linkage disequilibrium between a marker and QTL can be estimated simultaneously, thus increasing the efficiency and effectiveness of genome mapping for recalcitrant outcrossing species. Simulation studies are performed to test the statistical properties of the MLEs of genetic and genomic parameters including QTL allele frequency, QTL effects, QTL position, and the linkage disequilibrium of the QTL and a marker. The potential utility of our mapping strategy is discussed.     

Survival analysis of life span quantitative trait loci in Drosophila melanogaster

We used quantitative trait loci (QTL) mapping to evaluate the age specificity of naturally segregating alleles affecting life span. Estimates of age-specific mortality rates were obtained from observing 51,778 mated males and females from a panel of 144 recombinant inbred lines (RILs). Twenty-five QTL were found, having 80 significant effects on life span and weekly mortality rates. Generation of RILs from heterozygous parents enabled us to contrast effects of QTL alleles with the means of RIL populations. Most of the low-frequency alleles increased mortality, especially at younger ages. Two QTL had negatively correlated effects on mortality at different ages, while the remainder were positively correlated. Chromosomal positions of QTL were roughly concordant with estimates from other mapping populations. Our findings are broadly consistent with a mix of transient deleterious mutations and a few polymorphisms maintained by balancing selection, which together contribute to standing genetic variation in life span.     

Mapping quantitative trait loci in tetraploid populations

Knowledge of quantitative trait locus (QTL) mapping in polyploids is almost void, albeit many exquisite strategies of QTL mapping have been proposed and extensive investigations have been carried out in diploid animals and plants. In this paper we develop a simple algorithm which uses an iteratively reweighted least square method to map QTLs in tetraploid populations. The method uses information from all markers in a linkage group to infer the probability distribution of QTL genotype under the assumption of random chromosome segregation. Unlike QTL mapping in diploid species, here we estimate and test the compound 'gametic effect', which consists of the composite 'genic effect' of alleles and higher-order gene interactions. The validity and efficiency of the proposed method are investigated through simulation studies. Results show that the method can successfully locate QTLs and separates different sources (e.g. additive and dominance) of variance components contributed by the QTLs.     

Character analysis: an empirical approach applied to advanced snakes

Fifty characters of extant advanced snakes were selected for phyletic analysis, with the primary aim of determining evolutionary paths of the venomous taxa. The characters chosen showed roughly equivalent variation. States of characters were distinguished with reference to range of variation at species and generic levels. The heterogeneous, widespread and abundant family Colubridae was designated as representing the ancestral group. Direction of change in states was then determined by reference to colubrid conditions. Criteria used for judgement of direction were (1) uniqueness, (2) relative abundance, (3) correlation of derived states, (4) morphological specialization, (5) ecological specialization, (6) geographic restriction, (7) closely related taxa, and (8) correlation of applicable criteria. Two other criteria, (9) genetic structure and (10) fossil record, were not applicable.
Characters used as examples of the approach are number of palatine teeth and the pattern of the head shields. In the latter, the derivative states are correlated with particular modes of life (aquatic, fossorial and terrestrial). The familial level taxa show rather different frequency distributions in respect to the four states of this character, with one derived state unique to the viperids.
The second character, number of palatine teeth, was divided into classes by using a span covering most intraspecific variation. The resulting classes were lumped into four states emphasizing the classes of low numbers of teeth. The extreme derived states are correlated in the colubrids with distinctive modes of life (burrowing and digging) and with functional morphological specializations. The distribution of the states shows a trend toward low numbers of teeth in all the venomous families.     

A mixture model approach to the mapping of quantitative trait loci in complex populations with an application to multiple cattle families.

A mixture model approach is presented for the mapping of one or more quantitative trait loci (QTLs) in complex populations. In order to exploit the full power of complete linkage maps the simultaneous likelihood of phenotype and a multilocus (all markers and putative QTLs) genotype is computed. Maximum likelihood estimation in our mixture models is implemented via an Expectation-Maximization algorithm: exact, stochastic or Monte Carlo EM by using a simple and flexible Gibbs sampler. Parameters include allele frequencies of markers and QTLs, discrete or normal effects of biallelic or multiallelic QTLs, and homogeneous or heterogeneous residual variances. As an illustration a dairy cattle data set consisting of twenty half-sib families has been reanalyzed. We discuss the potential which our and other approaches have for realistic multiple-QTL analyses in complex populations.     

Phenotypic variation and natural selection at catsup, a pleiotropic quantitative trait gene in Drosophila

Quantitative traits are shaped by networks of pleiotropic genes . To understand the mechanisms that maintain genetic variation for quantitative traits in natural populations and to predict responses to artificial and natural selection, we must evaluate pleiotropic effects of underlying quantitative trait genes and define functional allelic variation at the level of quantitative trait nucleotides (QTNs). Catecholamines up (Catsup), which encodes a negative regulator of tyrosine hydroxylase , the rate-limiting step in the synthesis of the neurotransmitter dopamine, is a pleiotropic quantitative trait gene in Drosophila melanogaster. We used association mapping to determine whether the same or different QTNs at Catsup are associated with naturally occurring variation in multiple quantitative traits. We sequenced 169 Catsup alleles from a single population and detected 33 polymorphisms with little linkage disequilibrium (LD). Different molecular polymorphisms in Catsup are independently associated with variation in longevity, locomotor behavior, and sensory bristle number. Most of these polymorphisms are potentially functional variants in protein coding regions, have large effects, and are not common. Thus, Catsup is a pleiotropic quantitative trait gene, but individual QTNs do not have pleiotropic effects. Molecular population genetic analyses of Catsup sequences are consistent with balancing selection maintaining multiple functional polymorphisms.     

Selection with recurrent backcrossing to develop congenic lines for quantitative trait loci analysis.

SEWALL WRIGHT suggested that genes of large effect on a quantitative trait could be isolated by recurrent backcrossing with selection on the trait. Loci [quantitative trait loci (QTL)] at which the recurrent and nonrecurrent lines have genes of different large effect on the trait would remain segregating, while other loci would become fixed for the gene carried by the recurrent parent. If the recurrent line is inbred and the backcrossing and selection is conducted in a series of replicate lines, in each of which only one backcross parent is selected for each generation, the lines will become congenic to the recurrent parent except for the QTL of large effect and closely linked regions of the genome, and these regions can be identified using a dense set of markers that differ between the parental lines. Such lines would be particularly valuable for subsequent fine-scale mapping and gene cloning; but by chance, even QTL of large effect will be lost from some lines. The probability that QTL of specified effect remain segregating is computed as a function of its effect on the trait, the intensity of selection, and the number of generations of backcrossing. Analytical formulas are given for one or two loci, and simulation is used for more. It is shown that the method could have substantial discriminating ability and thus potential practical value.     

Pooled analysis of data from multiple quantitative trait locus mapping populations

Quantitative trait locus (QTL) analysis on pooled data from multiple populations (pooled analysis) provides a means for evaluating, as a whole, evidence for existence of a QTL from different studies and examining differences in gene effect of a QTL among different populations. Objectives of this study were to: (1) develop a method for pooled analysis and (2) conduct pooled analysis on data from two soybean mapping populations. Least square interval mapping was extended for pooled analysis by inclusion of populations and cofactor markers as indicator variables and covariate variables separately in the multiple linear models. The general linear test approach was applied for detecting a QTL. Single population-based and pooled analyses were conducted on data from two F_2:3 mapping populations, Hamilton (susceptible) × PI 90763 (resistant) and Magellan (susceptible) × PI 404198A (resistant), for resistance to soybean cyst nematode (SCN) in soybean. It was demonstrated that where a QTL was shared among populations, pooled analysis showed increased LOD values on the QTL candidate region over single population analyses. Where a QTL was not shared among populations, however, the pooled analysis showed decreased LOD values on the QTL candidate region over single population analyses. Pooled analysis on data from genetically similar populations may have higher power of QTL detection than single population-based analyses. QTLs were identified by pooled analysis on linkage groups (LGs) G, B1 and J for resistance to SCN race 2 whereas QTLs on LGs G, B1 and E for resistance to SCN race 5 in soybean PI 90763 and PI 404198A. QTLs on LG G and B1 were identified in both PI 90763 and PI 404198A whereas QTLs on LG E and J were identified in PI 90763 only. QTLs on LGs G and B1 for resistance to race 2 may be the same or closely linked with QTLs on LG G and B1 for resistance to race 5, respectively. It was further demonstrated that QTLs on G and B1 carried by PI 90763 were not significantly different in gene effect from QTLs on LGs G and B1 in PI 404198A, respectively.     

Linkage analysis of molecular markers and quantitative trait loci in populations of inbred backcross lines of Brassica napus L.

Backcross populations are often used to study quantitative trait loci (QTL) after they are initially discovered in balanced populations, such as F(2), BC(1), or recombinant inbreds. While the latter are more powerful for mapping marker loci, the former have the reduced background genetic variation necessary for more precise estimation of QTL effects. Many populations of inbred backcross lines (IBLs) have been developed in plant and animal systems to permit simultaneous study and dissection of quantitative genetic variation introgressed from one source to another. Such populations have a genetic structure that can be used for linkage estimation and discovery of QTL. In this study, four populations of IBLs of oilseed Brassica napus were developed and analyzed to map genomic regions from the donor parent (a winter-type cultivar) that affect agronomic traits in spring-type inbreds and hybrids. Restriction fragment length polymorphisms (RFLPs) identified among the IBLs were used to calculate two-point recombination fractions and LOD scores through grid searches. This information allowed the enrichment of a composite genetic map of B. napus with 72 new RFLP loci. The selfed and hybrid progenies of the IBLs were evaluated during two growing seasons for several agronomic traits. Both pedigree structure and map information were incorporated into the QTL analysis by using a regression approach. The number of QTL detected for each trait and the number of effective factors calculated by using biometrical methods were of similar magnitude. Populations of IBLs were shown to be valuable for both marker mapping and QTL analysis.     

A random model approach to mapping quantitative trait loci for complex binary traits in outbred populations.

Mapping quantitative trait loci (QTL) for complex binary traits is more challenging than for normally distributed traits due to the nonlinear relationship between the observed phenotype and unobservable genetic effects, especially when the mapping population contains multiple outbred families. Because the number of alleles of a QTL depends on the number of founders in an outbred population, it is more appropriate to treat the effect of each allele as a random variable so that a single variance rather than individual allelic effects is estimated and tested. Such a method is called the random model approach. In this study, we develop the random model approach of QTL mapping for binary traits in outbred populations. An EM-algorithm with a Fisher-scoring algorithm embedded in each E-step is adopted here to estimate the genetic variances. A simple Monte Carlo integration technique is used here to calculate the likelihood-ratio test statistic. For the first time we show that QTL of complex binary traits in an outbred population can be scanned along a chromosome for their positions, estimated for their explained variances, and tested for their statistical significance. Application of the method is illustrated using a set of simulated data.     

High efficiency of a double-screening method on single P-element insertion lines to identify quantitative trait mutants in Drosophila melanogaster

Enhancer trap P-element insertion has become a common method for generating new mutations in Drosophila melanogaster. When this method is used to isolate mutants for quantitative traits, an appropriate control must be established to define normal and mutant phenotypes. Considering that enhancer-trap lines are generated by crossing several strains, usually with no homogeneous genetic background, no clear control strain can be selected. Previous reports tried to overcome this problem by homogenizing the genetic background of the original lines. However, this is not the most common scenario, especially when functional phenotypes are studied in previously generated lines. Without such caution, is it possible to identify functional mutants among P-element insertion lines? We tested this for olfactory preference, a quantitative trait. Using as control measurement the average phenotype of 30 simultaneously generated P-element insertion lines with preferential reporter-gene expression in olfactory reception organs, we found that 25 of the lines exhibited mutant phenotypes in response to one or several of 5 tested odorants. Additional tests showed that the efficiency of the method for detecting olfactory mutations exceeded 60% even for such a small number of tested odorants. According to these results this approach greatly facilitates the identification of putative abnormal phenotypes, which must be extensively confirmed afterwards.     

Selfing rates in natural populations of Echium vulgare: a combined empirical and model approach

1. We quantified geitonogamous selfing in Echium vulgare , a self-compatible, bumble-bee pollinated plant. A maximum estimate of selfing was determined using a paternity analysis with RAPDs. In the first experiment, bumble-bees visited a sequence of virgin flowers. The percentage selfing increased rapidly from 12% in the first flower visited, up to 50% in the 15th flower visited in the sequence. In the second experiment, when bees visited plants in a natural population, the average selfing of plants increased with the number of open flowers from 0% to maximally 33%.
2. The results obtained in both experiments are consistently lower than predicted by our model on pollen dynamics ( Rademaker, de Jong & Klinkhamer 1997 ). We modified the model on pollen dynamics to link it more to the field situation with observations on flower stage, flower opening and bumble-bee preference, so that the bumble-bees encounter a variable number of pollen grains per flower. We also adjusted the parameters. If less pollen adheres to the bee (25% instead of 50%) after removal from the anthers, or if bees arrive at a plant with more pollen grains (6000 instead of 4448), the predictions of the model in regard to selfing could be improved but were still high compared with the observed selfing rates measured with RAPDs.
3. We suggest that the model is consistent with pollen dynamics in the field. However, post-pollination processes like selective abortion could play a role in E. vulgare .     

Suppressor genes with gender differences in activity in natural populations of Drosophila robusta: another approach to wild-type

Homozygous or hemizygous expression of an X-linked wing mutant of Drosophila robusta varies from a rudimentary wing that does not reach the tip of the abdomen (called 'club') to forms with full-sized but curled or crumpled wings (called 'curly'). Homozygous club females crossed to flies from natural populations or laboratory stocks derived from wild flies invariably produce significantly less club male progeny than the 100% expected, most of them exhibiting less severe phenotypes: 'curly' forms and wild-type. The male progeny from similar crosses using curly females tend to be predominantly normal. By contrast, the male progeny of outcrossed females homozygous for an X-linked eye colour mutant, vermilion, are all vermilion. The data indicate that natural populations of D. robusta contain suppressors of the wing mutant but not of the eye colour mutant studied. Activity of the suppressors differs by gender: in experiments in which genetic theory expects similar results in the two sexes, males consistently show stronger effects of the suppressors than females.     

Power analysis for quantitative trait locus mapping in populations derived by multiple backcrosses

 Populations derived by multiple backcrosses are potentially useful for quantitative trait locus (QTL) mapping studies. Comparisons of relative power to detect QTL using populations derived by multiple back-crosses are needed to make decisions when mapping projects are initiated. The objective of this study was to theoretically compare the power to detect QTL in populations derived by multiple backcrosses relative to mapping in a recombinant inbred population of equal size. Backcrossing results in a reduction in genetic variance with each generation and also results in an increasing frequency of the recurrent parent marker genotype. The relevant outcome for QTL mapping is a reduction in genetic variance to partition between marker genotype classes and increasing unbalance of the number of individuals contributing to the mean of the marker genotypes. Both of these factors lead to a decrease in the power to detect a QTL as the number of backcross generations increases. Experimental error was held constant with the populations compared. From a theoretical standpoint, backcross-derived populations offer few advantages for QTL detection. If, however, a backcrossing approach is the most efficient method to achieve a desired breeding objective and if QTL detection is an objective of equal or less importance, backcross-derived populations are a reasonable approach to QTL detection. Received: 4 August 1996 / Accepted: 4 April 1997     

Using whole-genome sequence data to predict quantitative trait phenotypes in Drosophila melanogaster

Predicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP) genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ～2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP) model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012) for starvation resistance (startle response). The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP-based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms.