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PubMed2000

Localization of a quantitative trait locus via a Bayesian approach.

A Bayesian approach to the direct mapping of a quantitative trait locus (QTL), fully utilizing information from multiple linked gene markers, is presented in this paper. The joint posterior distribution (a mixture distribution modeling the linkage between a biallelic QTL and N gene markers) is computationally challenging and invites exploration via Markov chain Monte Carlo methods. The parameter's complete marginal posterior densities are obtained, allowing a diverse range of inferences. Parameters estimated include the QTL genotype probabilities for the sires and the offspring, the allele frequencies for the QTL, and the position and additive and dominance effects of the QTL. The methodology is applied through simulation to a half-sib design to form an outbred pedigree structure where there is an entire class of missing information. The capacity of the technique to accurately estimate parameters is examined for a range of scenarios.

Algorithms↗
PubMed2006

[Genetic mapping of loci responsible for milk quality parameters in dairy cattle].

The review presents a definition of loci controlling quantitative traits (quantitative trait loci, QTLs) and localization of all currently known QTLs responsible for milk production traits in dairy cattle. The QTL number and chromosome localization are verified, with special reference to chromosomes 1, 3, 6, 14, 20, and 23. In a number of cases, close location of QTLs for mastitis and for milk production traits was found. Some aspects of QTL pleiotropy and epistasis are discussed and mapping methods of major QTLs are listed.

Animals↗
PubMed2000

Mapping quantitative trait loci for bovine ovulation rate.

An elite, three-generation family from the USDA Meat Animal Research Center twinning population was examined for evidence of ovulation rate quantitative trait loci (QTL). This work was both a continuation of previously reported results suggesting evidence for ovulation rate QTL on bovine Chromosome (Chr) 7 and an extension of a genome-wide search for QTL. Additional markers were typed on Chr 7 to facilitate interval mapping and testing of the hypothesis of one versus two QTL on that chromosome. In addition, 14 other informative markers were added to a selective genotyping genome screening of this family, and markers exhibiting nominal significance were used to identify chromosomal regions that were then subjected to more exhaustive analysis. For Chr 7, a total of 12 markers were typed over a region spanning the proximal two-thirds of the chromosome. Results from interval mapping analyses indicated evidence suggestive of the presence of QTL (nominal P<0.00077) within this region. Subsequent analysis with a model postulating two QTL provided evidence (P<0.05) for two rather than one QTL on this chromosome. Preliminary analysis with additional markers indicated nominal significance (P<0.05) for regions of Chrs 5, 10, and 19. Each of these regions was then typed with additional markers for the entire three-generation pedigree. Significant evidence (P<0.000026) of ovulation rate QTL was found for Chrs 5 and 19, while support on Chr 10 failed to exceed a suggestive linkage threshold (P>0.00077).

Animals↗
PubMed2006

Quantitative trait loci associated with AutoFOM grading characteristics, carcass cuts and chemical body composition during growth of Sus scrofa.

A three-generation full-sib resource family was constructed by crossing two commercial pig lines. Genotypes for 37 molecular markers covering chromosomes SSC1, SSC6, SSC7 and SSC13 were obtained for 315 F2 animals of 49 families and their parents and grandparents. Phenotypic records of traits including carcass characteristics measured by the AutoFOM grading system, dissected carcass cuts and meat quality characteristics were recorded at 140 kg slaughter weight. Furthermore, phenotypic records on live animals were obtained for chemical composition of the empty body, protein and lipid accretion (determined by the deuterium dilution technique), daily gain and feed intake during the course of growth from 30 to 140 kg body weight. Quantitative trait loci (QTL) detection was conducted using least-squares regression interval mapping. Highest significance at the 0.1% chromosome-wise level was obtained for five QTL: AutoFOM belly weight on SSC1; ham lean-meat weight, percentage of fat of primal cuts and daily feed intake between 60 and 90 kg live weight on SSC6; and loin lean-meat weight on SSC13. QTL affecting daily gain and protein accretion were found on SSC1 in the same region. QTL for protein and lipid content of empty body at 60 kg liveweight were located close to the ryanodine receptor 1 (RYR1) locus on SSC6. On SSC13, significant QTL for protein accretion and feed conversion ratio were detected during growth from 60 to 90 kg. In general, additive genetic effects of alleles originating from the Piétrain line were associated with lower fatness and larger muscularity as well as lower daily gain and lower protein accretion rates. Most of the QTL for carcass characteristics were found on SSC6 and were estimated after adjustment for the RYR1 gene. QTL for carcass traits, fatness and growth on SSC7 reported in the literature, mainly detected in crosses of commercial lines x obese breeds, were not obtained in the present study using crosses of only commercial lines, suggesting that these QTL are not segregating in the analysed commercial lines.

Alleles↗
PubMed2026

First genomic insights into the introgression of almond PPV-Marcus resistance into peach.

AIM: Sharka, caused by Plum pox virus (PPV), is one of the most damaging viral diseases of stone fruit crops, with peach among the most susceptible cultivated Prunus species. Almond is a promising source of resistance, but its genetic architecture and expression in a peach genetic background remain largely unknown. This study aimed to construct parental genetic linkage maps and identify genomic regions associated with PPV response in almond &#xd7; peach interspecific populations. METHODS: Progenies derived from the almond cultivars 'Del Cid', 'Garrigues', and 'Mono' were evaluated by RT-PCR after graft inoculation with the PPV-Marcus (PPV-M) strain over consecutive infection cycles. Phenotypic data were summarized for each genotype using best linear unbiased estimates (BLUEs). High-density SNP almond and peach arrays were used to construct parental maps for 'Garrigues' and 'Mono' and perform quantitative trait locus (QTL) analysis. RESULTS: Phenotypic variation was observed among and within families. 'Del Cid'-derived progenies showed the greatest resistance, 'Garrigues'-derived progenies displayed intermediate responses, and 'Mono'-derived progenies showed greater susceptibility and variability. The parental maps covered 546.69 cM in 'Mono' and 521.72 cM in 'Garrigues', with average intervals of 0.61 and 1.26 cM per unique marker position, respectively, and showed strong collinearity with the reference genome. QTL associated with PPV-M response were detected on linkage groups (LG) 1 and 6 in 'Garrigues' and LG2 in 'Mono'. The main QTL in 'Garrigues' peaked near 22.39 Mb on LG1, whereas the 'Mono' QTL was located at 22.27-22.62 Mb on LG2; a weaker QTL was detected near 25.38 Mb on LG6 in 'Garrigues'. The results support a quantitative and genetic-background-dependent architecture of PPV resistance. CONCLUSION: This study provides the first evidence of genomic regions associated with PPV-Marcus response in almond &#xd7; peach populations. The detected QTLs provide an initial basis to support the introgression of almond-derived resistance into peach breeding material.

Prunus↗
PubMed2005

QTL analysis and QTL-based prediction of flowering phenology in recombinant inbred lines of barley.

Combining ecophysiological modelling and genetic mapping has increasingly received attention from researchers who wish to predict complex plant or crop traits under diverse environmental conditions. The potential for using this combined approach to predict flowering time of individual genotypes in a recombinant inbred line (RIL) population of spring barley (Hordeum vulgare L.) was examined. An ecophysiological phenology model predicts preflowering duration as affected by temperature and photoperiod, based on the following four input traits: f(o) (the minimum number of days to flowering at the optimum temperature and photoperiod), theta1 and theta2 (the development stages for the start and the end of the photoperiod-sensitive phase, respectively), and delta (the photoperiod sensitivity). The model-input trait values were obtained from a photoperiod-controlled greenhouse experiment. Assuming additivity of QTL effects, a multiple QTL model was fitted for the model-input traits using composite interval mapping. Four to seven QTL were identified for each trait. Each trait had at least one QTL specific to that trait alone. Other QTL were shared by two or all traits. Values of the model-input traits predicted for the RILs from the QTL model were fed back into the ecophysiological model. This QTL-based ecophysiological model was subsequently used to predict preflowering duration (d) for eight field trial environments. The model accounted for 72% of the observed variation among 94 RILs and 94% of the variation among the two parents across the eight environments, when observations in different environments were pooled. However, due to the low percentage (34-41%) of phenotypic variation accounted for by the identified QTL for three model-input traits (theta1, theta2 and delta), the QTL-based model accounted for somewhat less variation among the RILs than the model using original phenotypic input trait values. Nevertheless, days to flowering as predicted from the QTL-based ecophysiological model were highly correlated with days to flowering as predicted from QTL-models per environment for days to flowering per se. The ecophysiological phenology model was thus capable of extrapolating (QTL) information from one environment to another.

Chromosome Mapping↗
PubMed1999

Interacting quantitative trait loci control phenotypic variation in murine estradiol-regulated responses.

The steroid hormone estradiol (E2) elicits a spectrum of systemic and uterotropic responses in vivo. For example, E2 treatment of ovariectomized adult and sexually immature rodents leads to uterine leukocytic infiltration, cell proliferation, and organ growth. E2-regulated growth is also associated with a variety of normal and pathological phenotypes. Historically, the uterine growth response has been used as the key model to understand the molecular and biochemical mechanisms underlying E2-dependent growth. In this study, genome exclusion mapping identified two quantitative trait loci (QTL) in the mouse, Est2 and Est3 on chromosomes 5 and 11, respectively, that control the phenotypic variation in uterine wet weight. Both QTL are linked to a variety of E2-regulated genes, suggesting that they may represent loci within conserved gene complexes that play fundamental roles in mediating the effects of E2. Interaction and multiple trait analyses using the uterine leukocyte response and wet weight suggest that Est4, a QTL on chromosome 10, may encode an interacting factor that influences the quantitative variation in both responses. Our results show that E2-dependent responses can be genetically controlled and that a genetic basis may underlie the variation observed in many E2-dependent phenotypes.

Animals↗
PubMed2001

New Dyscalc loci for myocardial cell necrosis and calcification (dystrophic cardiac calcinosis) in mice.

Dystrophic cardiac calcinosis (DCC) occurs among certain inbred strains of mice and involves necrosis and subsequent calcification as response of myocardial tissue to injury. Using a complete linkage map approach, we investigated the genetics of DCC in an F(2) intercross of resistant C57BL/6J and susceptible C3H/HeJ inbred strains and identified previously a major predisposing quantitative trait locus (QTL), Dyscalc1, on proximal chromosome 7. Analysis of inheritance suggested, however, that DCC is influenced by additional modifier QTL, which have as yet not been mapped. Here, we report the identification by composite interval mapping of the DCC loci Dyscalc2, Dyscalc3, and Dyscalc4 on chromosomes 4, 12 and 14, respectively. Together, the four Dyscalc loci explained 47% of the phenotypic variance of DCC, which was induced by a high-fat diet. Additive epistasis between Dyscalc1 and Dyscalc2 enhanced DCC. Examining recombinant inbred strains, we propose a 10-cM interval containing Dyscalc1 and discuss potential candidate genes.

Animals↗
PubMed2005

Genetic and physiological architecture of early vigor in Aegilops tauschii, the D-genome donor of hexaploid wheat. A quantitative trait loci analysis.

Plant growth can be studied at different organizational levels, varying from cell, leaf, and shoot to the whole plant. The early growth of seedlings is important for the plant's establishment and its eventual success. Wheat (Triticum aestivum, genome AABBDD) seedlings exhibit a low early growth rate or early vigor. The germplasm of wheat is limited. Wild relatives constitute a source of genetic variation. We explored the physiological and genetic relationships among a range of early vigor traits in Aegilops tauschii, the D-genome donor. A genetic map was constructed with amplified fragment-length polymorphism and simple sequence repeat markers, and quantitative trait loci (QTL) analysis was performed on the F(4) population of recombinant inbred lines derived from a cross between contrasting accessions. The genetic map consisted of 10 linkage groups, which were assigned to the seven chromosomes and covered 68% of the D genome. QTL analysis revealed 87 mapped QTLs (log of the odds >2.65) in clusters, 3.1 QTLs per trait, explaining 32% of the phenotypic variance. Chromosomes 1D, 4D, and 7D harbored QTLs for relative growth rate, biomass allocation, specific leaf area, leaf area ratio, and unit leaf rate. Chromosome 2D covered QTLs for rate and duration of leaf elongation, cell production rate, and cell length. Chromosome 5D harbored QTLs for the total leaf mass and area and growth rate of the number of leaves and tillers. The results show that several physiological correlations between growth traits have a genetic basis. Genetic links between traits are not absolute, opening perspectives for identification of favorable alleles in A. tauschii to improve early vigor in wheat.

Biomass↗
PubMed2005

Mapping quantitative trait loci associated with leaf and stem pubescence in cotton.

Leaf pubescence in cotton have a potential for insect pest management. Varying degrees of leaf trichome density in Gossypium species and cultivars have been associated to a series of five genes, referred to as t(1)-t(5). We used two segregating interspecific G. hirsutum x G. barbadense backcross populations developed in our laboratory to assess qualitatively and quantitatively leaf and stem pubescence. QTL analyses were performed using simple and composite interval mapping. Based on both types of measurements and under both types of QTL analyses, nine QTLs met permutation-based thresholds. The nine QTLs mapped to four different chromosome regions. Highest LOD values corresponded to the QTLs detected on c6 (four colocalized QTLs) and on D03 (two QTLs) for which the higher pubescence in the progeny derived from the pubescent G. hirsutum parent alleles. Conversely, on c17 (one QTL) and A01 (two QTLs), the G. hirsutum parental alleles affected negatively pubescence. These results combined with another published study confirm (1) the location in a center region of chromosome 6 of the t(1) locus as a major locus/gene determining leaf pubescence, and (2) additional genes located on seven additional chromosomes have been shown to impart trichome density either positively or negatively. The existence of a high density of PCR-based loci in most of the regions identified as harboring leaf pubescence QTLs, particularly that on chromosome 6, will facilitate future efforts for map-based cloning.

Chromosome Mapping↗
PubMed2002

Detection of quantitative trait loci for carcass traits in the pig by using AFLP.

For evaluation of the suitability of Amplified Fragment Length Polymorphism (AFLP) for detection of quantitative trait loci in farm animals, a combination of AFLP and selective genotyping has been applied as a rapid screening method for marker-QTL associations. Focusing on loci affecting eye muscle area, six extreme discordant sib pairs were selected from a Duroc x Berlin Miniature Pig F2 experimental cross and examined by using 48 AFLP primer combinations. Two prominent AFLP markers were converted into simple codominant PCR markers ( STS-Bo1 and STS-Bo3) and assigned to Sscr4 by physical and linkage mapping. Single marker analysis indicated association of the STS markers with a putative QTL influencing eye muscle area. Interval mapping confirmed the presence of a significant QTL for eye muscle area (Pgenomewide < 0.01) on the Sscr4, with STS-Bo1 being the closer marker. At the same location, significant effects (Pgenomewide < 0.01) on carcass length and backfat thickness were also detected. Our results demonstrate the capability of the combination of AFLP analysis and selective genotyping as a method for detection of genome regions containing QTL in livestock.

Animals↗
PubMed2003

Mapping quantitative trait loci affecting feather pecking behavior and stress response in laying hens.

In the European Union, legislation concerning animal housing is becoming stricter because of animal welfare concerns. Feather pecking (FP) in large group housing systems is a major problem. It has been suggested that corticosterone (CORT) response to manual restraint as a measure for stress is associated with FP behavior. The aim of the current study was to identify QTL involved in FP behavior and stress response in laying hens. An F2 population of 630 hens was established from a cross between two commercial lines of laying hens differing in their propensity to feather peck. The behavioral traits, measured at 6 and 30 wk of age, were gentle FP, severe FP, and aggressive pecking. Toe pecking was measured at 30 wk of age and CORT response to manual restraint was measured at 32 wk. All animals were genotyped for 180 microsatellite markers. A QTL analysis was performed using a regression interval mapping method. At 6 wk of age, a suggestive QTL on GGA10 was detected for gentle FP. At 30 wk of age, suggestive QTL were detected on GGA1 and GGA2 for gentle FP. A significant QTL was detected on GGA2 for severe FP. At 32 wk of age, a suggestive QTL was detected on GGA18 for CORT response to manual restraint. In addition, a suggestive QTL was detected on GGA5 with possible maternal parent-of-origin effect for CORT response.

Aggression↗
PubMed2002

Marker-assisted introgression of favorable alleles at quantitative trait loci between maize elite lines.

This article reports the marker-assisted introgression of favorable alleles at three quantitative trait loci (QTL) for earliness and grain yield among maize elite lines. The QTL were originally detected in 1992 by means of ANOVA in a population of 96 recombinant inbred lines (RILs). Introgression started from a selected RIL, which was crossed three times to one of the original parents and then self-fertilized, leading to BC(3)S(1) progenies. Markers were used to assist both foreground and background selection at each generation. At the end of the program, the effect of introgression was assessed phenotypically in agronomic trials, and QTL detection was performed by composite interval mapping among BC(3)S(1) progenies. The marker-assisted introgression proved successful at the genotypic level, as analyzed by precision graphical genotypes, although no emphasis was put on the reduction of linkage drag around QTL. Also, QTL positions were generally sustained in the introgression background. For earliness, the magnitude and sign of the QTL effects were in good agreement with those expected from initial RIL analyses. Conversely, for yield, important discrepancies were observed in the magnitude and sign of the QTL effects observed after introgression, when compared to those expected from initial RIL analyses. These discrepancies are probably due to important genotype-by-environment interactions.

Alleles↗
PubMed2000

Congenic rats for hypertension: how useful are they for the hunting of hypertension genes?

1. Linkage studies have revealed quantitative trait loci (QTL) for blood pressure in the rat genome using genetic hypertensive rat models. To identify the genes responsible for hypertension, the construction of congenic rats is essential. 2. To date, several congenic strains have been obtained from spontaneously hypertensive or Dahl salt-sensitive rats. The results of these studies should be interpreted according to whether the rats carry the whole QTL region or not. 3. After establishing congenic strains, three strategies are possible: (i) an orthodox positional cloning in which, using subcongenic strains, the QTL region is cut down to smaller fragments suitable for physical mapping; (ii) a positional candidate strategy in which candidate genes in the QTL regions are studied; or (iii) physiological studies in which intermediate phenotypes directly associated with the hypertension gene are explored. Several other experimental strategies are also available using congenic strains as new animal models for hypertension. 4. To make the most of advances in DNA technology, the precise evaluation of the phenotypic difference between congenic strains carrying different QTL or between a congenic and parental strain is critical.

Animals↗
PubMed2004

Comparative mapping of human chromosome 10 to pig chromosomes 10 and 14.

Identification of predictive markers in QTL regions that impact production traits in commercial populations of swine is dependent on construction of dense comparative maps with human and mouse genomes. Chromosomal painting in swine suggests that large genomic blocks are conserved between pig and human, while mapping of individual genes reveals that gene order can be quite divergent. High-resolution comparative maps in regions affecting traits of interest are necessary for selection of positional candidate genes to evaluate nucleotide variation causing phenotypic differences. The objective of this study was to construct an ordered comparative map of human chromosome 10 and pig chromosomes 10 and 14. As a large portion of both pig chromosomes are represented by HSA10, genes at regularly spaced intervals along this chromosome were targeted for placement in the porcine genome. A total of 29 genes from human chromosome 10 were mapped to porcine chromosomes 10 (SSC10) and 14 (SSC14) averaging about 5 Mb distance of human DNA per marker. Eighteen genes were assigned by linkage in the MARC mapping population, five genes were physically assigned with the IMpRH mapping panel and seven genes were assigned on both maps. Seventeen genes from human 10p mapped to SSC10, and 12 genes from human 10q mapped to SSC14. Comparative maps of mammalian species indicate that chromosomal segments are conserved across several species and represent syntenic blocks with distinct breakpoints. Development of comparative maps containing several species should reveal conserved syntenic blocks that will allow us to better define QTL regions in livestock.

Animals↗
PubMed2000

Strategies for genetic mapping of categorical traits.

The search for efficient and powerful statistical methods and optimal mapping strategies for categorical traits under various experimental designs continues to be one of the main tasks in genetic mapping studies. Methodologies for genetic mapping of categorical traits can generally be classified into two groups, linear and non-linear models. We develop a method based on a threshold model, termed mixture threshold model to handle ordinal (or binary) data from multiple families. Monte Carlo simulations are done to compare its statistical efficiencies and properties of the proposed non-linear model with a linear model for genetic mapping of categorical traits using multiple families. The mixture threshold model has notably higher statistical power than linear models. There may be an optimal sampling strategy (family size vs number of families) in which genetic mapping reaches its maximal power and minimal estimation errors. A single large-sibship family does not necessarily produce the maximal power for detection of quantitative trait loci (QTL) due to genetic sampling of QTL alleles. The QTL allelic model has a marked impact on efficiency of genetic mapping of categorical traits in terms of statistical power and QTL parameter estimation. Compared with a fixed number of QTL alleles (two or four), the model with an infinite number of QTL alleles and normally distributed allelic effects results in loss of statistical power. The results imply that inbred designs (e.g. F2 or four-way crosses) with a few QTL alleles segregating or reducing number of QTL alleles (e.g. by selection) in outbred populations are desirable in genetic mapping of categorical traits using data from multiple families.

Alleles↗
PubMed1999

Single- and multiple-trait mapping analysis of linked quantitative trait loci. Some asymptotic analytical approximations.

Estimating the resolution power of mapping analysis of linked quantitative trait loci (QTL) remains a difficult problem, which has been previously addressed mainly by Monte Carlo simulations. The analytical method of evaluation of the expected LOD developed in this article spreads the "deterministic sampling" approach for the case of two linked QTL for single- and two-trait analysis. Several complicated questions are addressed through this evaluation: the dependence of QTL detection power on the QTL effects, residual correlation between the traits, and the effect of epistatic interaction between the QTL for one or both traits on expected LOD (ELOD), etc. Although this method gives only an asymptotic estimation of ELOD, it allows one to get an approximate assessment of a broad spectrum of mapping situations. A good correspondence was found between the ELODs predicted by the model and LOD values averaged over Monte Carlo simulations.

Chromosome Mapping↗
PubMed2003

Mapping of porcine ESTs obtained from the anterior pituitary.

We report the physical mapping of porcine expressed sequence tags (ESTs) from anterior pituitary clones isolated by differential display PCR in a study using lines selected for reproduction. These ESTs were mapped using a somatic cell hybrid panel (SCHP) and a radiation hybrid panel (IMpRH) as follows (SCHP position, nearest marker on the RH map): SPARCL1 (8q23-q27, SSP1); ATF4 (5p11-p15, AC02); MEF2C [2(1/2q21)-(1/2q22), SW2134]; FTH1 (2p14-p17, SWR783); FRAP1 (6q22-q23, SW1355); PBP (14, SW2508); LOC92004 [13q23-(1/2q41), CP]; and PGRMC1 [Xq22, SW1943]. All RH assignments were at LOD score >6.0 except for PGRMC1 at LOD score 5.4. ESTs TCP1 [12p11-(2/3p13)], SF3B1 (15q23-q26) and Clock (8q11-q12) were assigned using only the SCHP. The map position of SPARCL1 coincides with a quantitative trait loci (QTL) for age at puberty found in the University of Nebraska selection lines. Physical mapping of ESTs reported in the present study contributes to characterization of the transcriptome of anterior pituitary of pigs, adds new information to the public database of the porcine genome expression map, and further develops the porcine-human comparative map.

Animals↗