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PubMed1998

Mapping of serum amylase-1 and quantitative trait loci for milk production traits to cattle chromosome 4.

The present study was undertaken to confirm and refine the mapping of a quantitative trait locus in cattle for milk fat percentage that had earlier been reported to be linked to the serum amylase-1 locus, AM1. Five half-sib families from the previous study and 7 new ones were genotyped for nine microsatellite markers spanning chromosome 4. AM1 was mapped between the microsatellite markers BMS648 and BR6303. In a granddaughter design, interval mapping based on multiple-marker regression was utilized for an analysis of five milk production traits: milk yield, fat percentage and yield, and protein percentage and yield. In the families reported on previously, significant effects for fat and protein percentages were detected. In the new families, an effect on milk and fat yields was found. The most likely positions of the quantitative trait locus in both groups of families were in the same area of chromosome 4 in the vicinity of the obese locus. Direct effects of the obese locus were tested for using polymorphism in two closely linked microsatellites located 2.5 and 3.6 top downstream of the coding sequence. No firm evidence was found for an association between the obese locus and the tested traits.

Amylases↗
PubMed2006

Believe it or not, QTLs are accurate!

It is generally believed that mapping quantitative trait loci (QTLs) does not accurately position genes underlying polygenic traits on the genome, which limits the application of QTL analysis in marker-assisted selection and gene discovery. However, now that a few plant QTLs have been cloned or accurately tagged, it appears that they might be accurate to within 2cM or less. This means that there will be circumstances when map-based cloning using only original mapping data would be a realistic option that avoids time-consuming and expensive fine mapping. Acceptance of this view would enhance the value of past and future mapping experiments, particularly those revealing small and environmentally sensitive QTLs that are often considered intractable at the molecular level.

Chromosome Mapping↗
PubMed2004

The quantitative genetic basis of male mating behavior in Drosophila melanogaster.

Male mating behavior is an important component of fitness in Drosophila and displays segregating variation in natural populations. However, we know very little about the genes affecting naturally occurring variation in mating behavior, their effects, or their interactions. Here, we have mapped quantitative trait loci (QTL) affecting courtship occurrence, courtship latency, copulation occurrence, and copulation latency that segregate between a D. melanogaster strain selected for reduced male mating propensity (2b) and a standard wild-type strain (Oregon-R). Mating behavior was assessed in a population of 98 recombinant inbred lines derived from these two strains and QTL affecting mating behavior were mapped using composite interval mapping. We found four QTL affecting male mating behavior at cytological locations 1A;3E, 57C;57F, 72A;85F, and 96F;99A. We used deficiency complementation mapping to map the autosomal QTL with much higher resolution to five QTL at 56F5;56F8, 56F9;57A3, 70E1;71F4, 78C5;79A1, and 96F1;97B1. Quantitative complementation tests performed for 45 positional candidate genes within these intervals revealed 7 genes that failed to complement the QTL: eagle, 18 wheeler, Enhancer of split, Polycomb, spermatocyte arrest, l(2)05510, and l(2)k02206. None of these genes have been previously implicated in mating behavior, demonstrating that quantitative analysis of subtle variants can reveal novel pleiotropic effects of key developmental loci on behavior.

Animals↗
PubMed1991

Use of recombinant inbred strains to assess vulnerability to drug abuse at the genetic level.

The use of Recombinant Inbred mouse Strains (RIS) to derive information about the complexity of the genetic architecture underlying various traits is increasing in popularity. Behaviors measured to index sensitivity to drug effects and vulnerability to drug abuse are considered here. Potential uses of RIS are identification of major gene effects, mapping of traits to particular chromosomal sites, determining genetic correlations between characters, and identifying behaviorally extreme genotypes. This approach has led to identification of a major gene moderating alcohol acceptance in mice and has revealed a more complex polygenic system influencing morphine consumption.

Alcohol Drinking↗
PubMed2001

Directed isolation and mapping of microsatellites from swine Chromosome 1q telomeric region through microdissection and RH mapping.

Several quantitative trait loci (QTLs) (vertebrate number, birth weight, age at puberty, growth rate, gestation length, and backfat depth) have been independently mapped to the distal region of swine Chromosome (SSC) 1q in several resource populations. In order to improve the map resolution and refine these QTLs more precisely on SSC1q, we have isolated and mapped additional microsatellites (ms), using chromosome microdissection and radiation hybrid (RH) mapping. Five copies of the telomeric region of SSC1q were microdissected from metaphase spreads and pooled. The chromosomal fragment DNA was randomly amplified by using degenerate oligonucleotide primed polymerase chain reaction (DOP-PCR), enriched for ms, and subcloned into a PCR vector. Screening of subsequent clones with ms probes identified 23 unique ms sequences. Fifteen of these (65%) were subjected to radiation hybrid (RH) mapping by using the INRA-University of Minnesota porcine RH panel (IMpRH); and the remaining eight were not suited for the RH mapping. Twelve microsatellites were assigned to SSC1q telomeric region of IMpRH map (LOD >6), and three remain unlinked (LOD <6). Out of the 15 microsatellite markers, 9 were polymorphic in NIAI reference population based on the Meishan and Göttingen miniature pig. In summary, we have used microdissection and radiation hybrid mapping to clone and map 12 new microsatellites to the swine gene map to increase the resolution of SSC1q in the region of known QTLs.

Animals↗
PubMed2006

QTL analysis for flag leaf characteristics and their relationships with yield and yield traits in rice.

Photosynthesis of carbohydrate is the primary source of grain yield in rice (Oryza sativa L.). It is important to genetically analyze the morphological and the physiological characteristics of functional leaves, especially flag leaf, in rice improvement. In this study, a recombinant inbred population derived from a cross between an indica (O. sativa L. ssp. indica) cultivar and a japonica (O. sativa L. ssp. japonica) cultivar was employed to map quantitative traits loci (QTLs) for the morphological (i.e., leaf length, width, and area) and physiological (i.e., leaf color rating and stay-green) characteristics of flag leaf and their relationships with yield and yield traits in 2003 and 2004. A total of 17 QTLs for morphological traits (flag leaf length, width, and area), 6 QTLs for degree of greenness and 14 QTLs for stay-green-related traits (retention-degrees of greenness, relative retention of greenness, and retention of the green area) were resolved, and 10 QTLs were commonly detected in both the years. Correlation analysis revealed that flag leaf area increased grain yield by increasing spikelet number per panicle. However, the physiological traits including degree of greenness and stay-green traits were not or negatively correlated to grain yield and yield traits, which may arise from the negative relation between degree of greenness and flag leaf size and the partial sterility occurred in a fraction of the lines in this population. The region RM255-RM349 on chromosome 4 controlled the three leaf morphological traits simultaneously and explained a large part of variation, which was very useful for genetic improvement of grain yield. The region RM422-RM565 on chromosome 3 was associated with the three stay-green traits simultaneously, and the use of this region in genetic improvement of grain yield needs to be assessed by constructing near-isogenic lines.

Chromosome Mapping↗
PubMed2003

Characterization of QTLs for harvest index and source-sink characters in a DH population of rice (Oryza sativa L.).

A DH population containing 81 DH lines from an indica-japonica cross of rice and an RFLP linkage map consisting of 232 markers were used to map quantitative trait loci(QTLs) for harvest index, biomass, grain yield, sink capacity and plant height by a computer program QTLMapper1.0 based on mixed linear models. A total of 21 significant main-effect QTLs and 9 pairs of epistatic loci were detected. Of these, three detected QTLs for grain yield collectively accounted for 42% of the phenotypic variation with a LOD of 7.10. These three grain yield QTLs were corresponded either to QTLs for harvest index or QTLs for biomass in both locations and directions of additive effects, which sheds light on the genetic basis of the formula 'grain yield = biomass x harvest index'. Four detected QTLs for harvest index collectively explained 46% of the total phenotypic variation and four QTLs for biomass jointly accounted for 64% of the trait variation. No coincidence of harvest index QTLs with any biomass QTLs was found, therefore indicating the possibility of pyramiding favorable alleles for both traits through gene recombination so as to obtain a genotype possessing both high harvest index and heavy plant biomass. Five QTLs for plant height were detected that cumulatively explained 64% of the phenotypic variation with a LOD of 11.62. Among these, three with smaller effects respectively co-located with some of the QTLs for biomass, sink capacity and/or grain yield, but not with any of harvest index QTLs, thus suggesting that plant height was to some extent directly associated with 'source' and 'sink' but not with 'transportation' of the 'source-transportation-sink' concept, at least in this genetic background and environment. In view of a somewhat low resolution of the genetic map used in the study and the fact that when plant height QTLs co-located with those for yield and/or yield related traits, these co-located QTLs were all in the same directions of additive effects, it is more likely that these QTLs co-located in a same chromosomal region might be a single QTL which have effects on multiple traits. If this is true, the above observation have led us to assume that QTLs which have pleotropic effects on yield and/or yield related traits and plant height are very different from those which had relatively large effects only on plant height. The former contribute strongly to yield and/or yield related traits but weakly to plant height while the later contribute mainly to plant height. Obviously, due to that an increase of plant height is always coupled with an increase in lodging susceptibility, discriminating between above two types of QTLs is critical in breaking the traits' undesired association in breeding for improved yield potential of rice. In addition, based on the co-location analysis of main-effect QTLs for the studied traits, five genomic regions were found to be highly associated with harvest index, biomass, sink capacity and grain yield.

Biomass↗
PubMed2000

Detection of QTLs for heading time and photoperiod response in wheat using a doubled-haploid population.

The genetic basis of heading time in wheat (Triticum aestivum L.) was investigated through the study of flowering under normal autumn sown field conditions as well as photoperiod responses under a controlled environment. Quantitative trait loci (QTLs) for these traits were mapped in a doubled-haploid (DH) population derived from a cross between the wheat cultivars 'Courtot' and 'Chinese Spring'. A molecular marker linkage map of this cross that was previously constructed based on 187 DH lines and 380 markers was used for QTL mapping. The genome was well covered (85%) except for chromosomes 1D and 4D, and a set of anchor loci regularly spaced over the genome (one marker each 15.5 cM) was chosen for marker regression analysis. The presence of a QTL was declared at a significance threshold of alpha = 0.005. The population was grown under field conditions in Clermont-Ferrand, France during two years (1994-1995), in Norwich, U.K. over one year (1998), and also under controlled environments in Norwich. For each trait, between 2 and 4 QTLs were identified with individual effects ranging between 6.3% and 44.4% of the total phenotypic variation. Two QTLs were detected that simultaneously affected heading time and photoperiod response. For heading time, these two QTLs were detected in more than one year. One QTL located on chromosome arm 2BS near the locus Xfbb121-2B, co-segregated with the gene Ppd-B1 known to be involved in photoperiod response. This chromosome region explained a large part of the variation (23.4-44.4% depending on the years or the traits). Another region located on chromosome arm 7BS between the loci Xfbb324-7B and Xfbb53-7B also had a strong effect (7.3-15.3%). This region may correspond to a QTL for earliness per se.

Chromosome Mapping↗
PubMed2005

Genetic mapping of maize stripe disease resistance from the Mascarene source.

Maize stripe virus (MStV) is a potentially threatening virus disease of maize in the tropics. We mapped quantitative trait loci (QTLs) controlling resistance to MStV in a maize population of 157 F(2:3) families derived from the cross between two maize lines, Rev81 (tropical resistant) and B73 (temperate susceptible). Resistance was evaluated under artificial inoculations in replicated screenhouse trials across different seasons in Réunion Island, France. Composite interval mapping was employed for QTL detection with a linkage map of 143 microsatellite markers. Heritability estimates across seasons were 0.96 and 0.90 for incidence and severity, respectively, demonstrating a high genotypic variability and a good control of the environment. Three regions on chromosomes 2L, 3 and 5, with major effects, and another region on chromosome 2S, with minor effects, provided resistance to MStV in Rev81. In individual seasons, the chr2L QTL explained 60-65% of the phenotypic variation for disease incidence and 21-42% for severity. The chr3 QTL, mainly associated with incidence and located near centromere, explained 42-57% of the phenotypic variation, whereas the chr5 QTL, mainly associated with severity, explained 26-53%. Overall, these QTLs explained 68-73% of the phenotypic variance for incidence and 50-59% for severity. The major QTLs on chr2 and 3 showed additive gene action and were found to be stable over time and across seasons. They also were found to be included in genomic regions with important clusters of resistance genes to diseases and pests. The major QTL on chr5 appeared to be partially dominant in favour of resistance. It was stable over time but showed highly significant QTL x season interactions. Possible implications of these QTLs in different mechanisms of resistance against the virus or the insect vector are discussed. The prospects for transferring these QTLs in susceptible maize cultivars and combining them with other resistances to virus diseases by conventional or marker-assisted breeding are promising.

Chromosome Mapping↗
PubMed1999

Natural allelic variation at seed size loci in relation to other life history traits of Arabidopsis thaliana.

We have analyzed two Arabidopsis strains differing in the mean seed size and seed number they produced. The accession Cape Verde Islands (Cvi) yielded on average about 40% fewer seeds than the laboratory strain Landsberg erecta (Ler), but Cvi seeds were almost twice as heavy. Maternal and nonmaternal genetic factors were involved in the seed size variation, and interactions between both types of factors presumably occurred. The Ler/Cvi seed size difference increased through seed development from ovule maturation until seed desiccation, suggesting that multiple processes of seed development were affected. In addition, it involved changes in the final cell number and cell size of the seed coat and the embryo. Cell number variation was controlled mainly by maternal factors, whereas nonmaternal allelic variation mostly affected cell size. By using a recombinant inbred line population derived from Ler and Cvi, we mapped quantitative trait loci (QTLs) affecting 12 life history traits related to seed size, fruit size, seed number, and plant resources. Five of the seed size QTLs colocated with QTLs for other traits, suggesting that they control seed size via maternal components affecting ovule number and/or carpel development, ovule development, or reproductive resource allocation in the mother plant. The six remaining putative seed size QTLs did not show a significant effect on any other trait, suggesting that this allelic variation may be involved specifically in seed development processes.

Alleles↗
PubMed2001

Utilization of marker-assisted congenics to map two blood pressure quantitative trait loci in Dahl rats.

A broad Chromosome (Chr) 10 region of the Dahl salt-sensitive (S) rat was shown by linkage and the use of congenic strains to contain a blood pressure (BP) quantitative trait locus (QTL). To further narrow down the region harboring the QTL, four congenic strains carrying smaller segments were made by replacing various segments of the S rats with the homologous segments of the Lewis (LEW) rats. The construction of these congenic strains was facilitated by a genome-wide marker screening. One congenic strain, assigned as S.L4, showed a BP-lowering effect, and the region harboring a BP QTL, designated QTL1, is localized to a segment of about 15 cM. Two other strains, assigned as S.L2 and S.L5, contained an overlapping segment, and both showed a BP-lowering effect. In contrast, the fourth congenic strain, assigned as S.L1, contained a smaller and shared fragment with S.L2 and S.L5, but it did not have a BP-lowering effect. Deducing from the segment in common in S.L2 and S.L5, and not shared between S.L1 and both congenic strains S.L2 and S.L5, the region harboring a QTL, designated as QTL2, was narrowed to about 12 cM. The current work showed the general applicability of the 'speed congenic' approach to map and fine-map BP QTL.

Animals↗
PubMed2002

Genetic control of polyamine-dependent susceptibility to skin tumorigenesis.

Overexpression of an ornithine decarboxylase (ODC) transgene greatly increases the susceptibility of mouse skin to carcinogen-induced tumor development. Like many phenotypes in transgenic models, this enhanced susceptibility phenotype is strongly influenced by genetic background. We have mapped tumor-modifier genes in intraspecific crosses between transgenic K6/ODC mice on a susceptible strain background (C57Bl/6J), a moderately resistant background (FVB), or a highly resistant background (C3H/HeJ). We identified several quantitative trait loci that influenced either tumor multiplicity or predisposition to the development of squamous cell carcinoma, but not both phenotypes. Because we did not use a tumor-promotion protocol to induce tumors, most of the quantitative trait loci mapped in this study are distinct from skin tumor-susceptibility loci identified previously. The use of a combined transgenic-standard strain approach to genetic analysis has resulted in detection of previously unknown genetic loci affecting skin tumor susceptibility.

Animals↗
PubMed2003

QTL architecture of resistance and tolerance traits in Arabidopsis thaliana in natural environments.

Quantitative-genetic approaches have offered significant insights into phenotypic evolution. However, quantitative-genetic analyses fail to provide information about the evolutionary relevance of specific loci. One complex and ecologically relevant trait for plants is their resistance to herbivory because natural enemies can impose significant damage. To illustrate the insights of combined molecular and ecological research, we present the results of a field study mapping quantitative trait loci (QTL) for resistance and tolerance to natural rabbit herbivory in the genetic model, Arabidopsis thaliana. Replicates of the Ler x Col recombinant inbred lines were planted into field sites simulating natural autumn and spring seasonal germination cohorts. Shortly after flowering, herbivores removed the main flowering inflorescence (apical meristem). We found several main-effect QTL for resistance within each seasonal cohort and significant QTL-season interactions, demonstrating that the loci underlying resistance to a single herbivore differ across seasonal environments. The presence of QTL x environment also shows that variation at specific loci is only available to selection in some environments. Despite significant among-line variance components, no QTL for tolerance were detected. The combined results of the quantitative-genetic and QTL analyses demonstrate that many loci of small effect underlie tolerance to damage by rabbits, and counter the hypothesis of locus-specific tradeoffs between resistance and tolerance. The results also provide insights as to the locus-specific nature of evolutionary constraints, i.e. some loci influence flowering time and resistance in both seasonal cohorts. Our results show how linking molecular-genetic tools with field studies in ecologically relevant settings can clarify the role of specific loci in the evolution of quantitative traits.

Arabidopsis↗
PubMed2000

The consistency of the posterior probability of linkage.

When searching for trait loci along the genome, properly incorporating prior genomic information into the analysis will almost certainly increase the chance of success. Recently, we devised a method that utilizes such prior information in the mapping of trait genes for complex disorders (Vieland, 1998; Wang el al. 1999; Vieland et al. 2000). This method uses the posterior probability of linkage (PPL) based on the admixture model as a measure of linkage information. In this paper, we study the consistency of the PPL. It is shown that, as the number of pedigrees increases, the PPL converges in probability to 1 when there is linkage between the marker and a trait locus, and converges to 0 otherwise. This conclusion is shown to be true for general pedigrees and trait models, even, when the likelihood functions are based on misspecified trait models. As part of the effort to prove this conclusion, it is shown that when there is no linkage, the maximum likelihood estimator of the recombination fraction in the admixture model is asymptotically 0.5, even when the admixture model misrepresents the true model.

Computer Simulation↗
PubMed2001

Chromosomal organization of candidate genes involved in cholesterol gallstone formation: a murine gallstone map.

Epidemiologic and family studies indicate that cholesterol gallstone formation is in part genetically determined. The major contribution to our current understanding of gallstone genes derives from animal studies, particularly cross-breeding experiments in inbred mouse strains that differ in genetic susceptibility to cholesterol gallstone formation (quantitative trait loci mapping). In this review we summarize how the combined use of genomic strategies and phenotypic studies in inbred mice has proven to be a powerful means of dissecting the complex pathophysiology of this common disease. We present a "gallstone map" for the mouse, consisting of all genetic loci that have been identified to confer gallstone susceptibility as well as putative candidate genes. Translation of the genetic loci and genes between mouse and human predicts chromosomal regions in the human genome that are likely to harbor gallstone genes. Both the number and the precise understanding of gallstone genes are expected to further increase with rapid progress of the genome projects, and multiple new targets for early diagnosis and prevention of gallstone disease should become possible.

Animals↗
PubMed2004

QTL analysis of resistance to Fusarium head blight in Swiss winter wheat (Triticum aestivum L.).

Fusarium head blight (FHB) of wheat is a widespread and destructive disease which occurs in humid and semi-humid areas. FHB epidemics can cause serious yield and quality losses under favorable climatic conditions, but the major concern is the contamination of grains with mycotoxins. Resistance to FHB is quantitatively inherited and greatly influenced by the environment. Its evaluation is costly and time-consuming. The genetic basis of FHB resistance has mainly been studied in spring wheat. The objective of this study was to map quantitative trait loci (QTLs) for resistance to FHB in a population of 240 recombinant inbred lines (RILs) derived from a cross between the two Swiss winter wheat cultivars Arina (resistant) and Forno (susceptible). The RILs were genotyped with microsatellite and RFLP markers. The resulting genetic map comprises 380 loci and spans 3,086 cM. The 240 RILs were evaluated for resistance to FHB in six field trials over 3 years. Composite interval mapping (CIM) analyses carried out on FHB AUDPC (i.e. mean values across six environments) revealed eight QTLs which altogether explained 47% of the phenotypic variance. The three main QTLs were mapped on the long arms of chromosomes 6D ( R(2)=22%), 5B ( R(2)=14%) and 4A ( R(2)=10%). The QTL detected on 5B originated from the susceptible parent Forno. Other QTLs with smaller effects on FHB resistance were detected on chromosomes 2AL, 3AL, 3BL, 3DS and 5AL.

Analysis of Variance↗
PubMed2004

A unifying statistical model for QTL mapping of genotype x sex interaction for developmental trajectories.

Most organisms display remarkable differences in morphological, anatomical, and developmental features between the two sexes. It has been recognized that these sex-dependent differences are controlled by an array of specific genetic factors, mediated through various environmental stimuli. In this paper, we present a unifying statistical model for mapping quantitative trait loci (QTL) that are responsible for sexual differences in growth trajectories during ontogenetic development. This model is derived within the maximum likelihood context, incorporated by sex-stimulated differentiation in growth form that is described by mathematical functions. A typical structural model is implemented to approximate time-dependent covariance matrices for longitudinal traits. This model allows for a number of biologically meaningful hypothesis tests regarding the effects of QTL on overall growth trajectories or particular stages of development. It is particularly powerful to test whether and how the genetic effects of QTL are expressed differently in different sexual backgrounds. Our model has been employed to map QTL affecting body mass growth trajectories in both male and female mice of an F2 population derived from the large (LG/J) and small (SM/J) mouse strains. We detected four growth QTL on chromosomes 6, 7, 11, and 15, two of which trigger different effects on growth curves between the two sexes. All the four QTL display significant genotype-sex interaction effects on the timing of maximal growth rate in the ontogenetic growth of mice. The implications of our model for studying the genetic architecture of growth trajectories and its extensions to some more general situations are discussed.

Animals↗
PubMed2004

Copulas in QTL mapping.

The standard variance components method for mapping quantitative trait loci is derived on the assumption of normality. Unsurprisingly, statistical tests based on this method do not perform so well if this assumption is not satisfied. We use the statistical concept of copulas to relax the assumption of normality and derive a test that can perform well under any distribution of the continuous trait. In particular, we discuss bivariate normal copulas in the context of sib-pair studies. Our approach is illustrated by a linkage analysis of lipoprotein(a) levels, whose distribution is highly skewed. We demonstrate that the asymptotic critical levels of the test can still be calculated using the interval mapping approach. The new method can be extended to more general pedigrees and multivariate phenotypes in a similar way as the original variance components method.

Analysis of Variance↗