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QTL Mapping (qtl + mapping)
Selected AbstractsQTL Mapping Under AscertainmentANNALS OF HUMAN GENETICS, Issue 6 2006J. Peng Summary Mapping quantitative trait loci (QTL) using ascertained sibships is discussed. It is shown that under the standard normality assumption of variance components analysis the efficient scores are unchanged by ascertainment, and two different schemes of ascertainment correction suggested in the literature are asymptotically equivalent. The use of conditional maximum likelihood estimators derived under the normality assumption to estimate nuisance parameters is shown to result in only a small loss of power compared to the case of known parameters, even when the distribution of phenotypes is non-normal and/or the ascertainment criterion is ill defined. [source] A Guide to QTL Mapping with R/qtl by BROMAN, K. W. and SEN, S.BIOMETRICS, Issue 2 2010R. W. Doerge No abstract is available for this article. [source] Single QTL mapping and nucleotide-level resolution of a physiologic trait in wine Saccharomyces cerevisiae strainsFEMS YEAST RESEARCH, Issue 6 2007Philippe Marullo Abstract Natural Saccharomyces cerevisiae yeast strains exhibit very large genotypic and phenotypic diversity. However, the link between phenotype variation and genetic determinism is still difficult to identify, especially in wild populations. Using genome hybridization on DNA microarrays, it is now possible to identify single-feature polymorphisms among divergent yeast strains. This tool offers the possibility of applying quantitative genetics to wild yeast strains. In this instance, we studied the genetic basis for variations in acetic acid production using progeny derived from two strains from grape must isolates. The trait was quantified during alcoholic fermentation of the two strains and 108 segregants derived from their crossing. A genetic map of 2212 markers was generated using oligonucleotide microarrays, and a major quantitative trait locus (QTL) was mapped with high significance. Further investigations showed that this QTL was due to a nonsynonymous single-nucleotide polymorphism that targeted the catalytic core of asparaginase type I (ASP1) and abolished its activity. This QTL was only effective when asparagine was used as a major nitrogen source. Our results link nitrogen assimilation and CO2 production rate to acetic acid production, as well as, on a broader scale, illustrating the specific problem of quantitative genetics when working with nonlaboratory microorganisms. [source] Generalized marker regression and interval QTL mapping methods for binary traits in half-sib family designsJOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 5 2001H. N. Kadarmideen A Generalized Marker Regression Mapping (GMR) approach was developed for mapping Quantitative Trait Loci (QTL) affecting binary polygenic traits in a single-family half-sib design. The GMR is based on threshold-liability model theory and regression of offspring phenotype on expected marker genotypes at flanking marker loci. Using simulation, statistical power and bias of QTL mapping for binary traits by GMR was compared with full QTL interval mapping based on a threshold model (GIM) and with a linear marker regression mapping method (LMR). Empirical significance threshold values, power and estimates of QTL location and effect were identical for GIM and GMR when QTL mapping was restricted to within the marker interval. These results show that the theory of the marker regression method for QTL mapping is also applicable to binary traits and possibly for traits with other non-normal distributions. The linear and threshold models based on marker regression (LMR and GMR) also resulted in similar estimates and power for large progeny group sizes, indicating that LMR can be used for binary data for balanced designs with large families, as this method is computationally simpler than GMR. GMR may have a greater potential than LMR for QTL mapping for binary traits in complex situations such as QTL mapping with complex pedigrees, random models and models with interactions. Generalisierte Marker Regression und Intervall QTL Kartierungsmethoden für binäre Merkmale in einem Halbgeschwisterdesign Es wurde ein Ansatz zur generalisierten Marker Regressions Kartierung (GMR) entwickelt, um quantitative Merkmalsloci (QTL) zu kartieren, die binäre polygenetische Merkmale in einem Einfamilien-Halbgeschwisterdesign beeinflussen. Das GMR basiert auf der Theorie eines Schwellenwertmodells und auf der Regression des Nachkommenphänotyps auf den erwarteten Markergenotyp der flankierenden Markerloci. Mittels Simulation wurde die statistische Power und Schiefe der QTL Kartierung für binäre Merkmale nach GMR verglichen mit vollständiger QTL Intervallkartierung, die auf einem Schwellenmodell (GIM) basiert, und mit einer Methode zur linearen Marker Regressions Kartierung (LMR). Empirische Signifikanzschwellenwerte, Power und Schätzer für die QTL Lokation und der Effekt waren für GIM und GMR identisch, so lange die QTL Kartierung innerhalb des Markerintervalls definiert war. Diese Ergebnisse zeigen, dass die Theorie der Marker Regressions-Methode zur QTL Kartierung auch für binäre Merkmale und möglicherweise auch für Merkmale, die keiner Normalverteilung folgen, geeignet ist. Die linearen und Schwellenmodelle, die auf Marker Regression (LMR und GMR) basieren, ergaben ebenfalls ähnliche Schätzer und Power bei großen Nachkommengruppen, was schlussfolgern lässt, dass LMR für binäre Daten in einem balancierten Design mit großen Familien genutzt werden kann. Schließlich ist diese Methode computertechnisch einfacher als GMR. GMR mag für die QTL Kartierung bei binären Merkmalen in komplexen Situationen ein größeres Potential haben als LMR. Ein Beispiel dafür ist die QTL Kartierung mit komplexen Pedigrees, zufälligen Modellen und Interaktionsmodellen. [source] Genome-wide SNP detection in the great tit Parus major using high throughput sequencingMOLECULAR ECOLOGY, Issue 2010NIKKIE E. M. VAN BERS Abstract Identifying genes that underlie ecological traits will open exiting possibilities to study gene,environment interactions in shaping phenotypes and in measuring natural selection on genes. Evolutionary ecology has been pursuing these objectives for decades, but they come into reach now that next generation sequencing technologies have dramatically lowered the costs to obtain the genomic sequence information that is currently lacking for most ecologically important species. Here we describe how we generated over 2 billion basepairs of novel sequence information for an ecological model species, the great tit Parus major. We used over 16 million short sequence reads for the de novo assembly of a reference sequence consisting of 550 000 contigs, covering 2.5% of the genome of the great tit. This reference sequence was used as the scaffold for mapping of the sequence reads, which allowed for the detection of over 20 000 novel single nucleotide polymorphisms. Contigs harbouring 4272 of the single nucleotide polymorphisms could be mapped to a unique location on the recently sequenced zebra finch genome. Of all the great tit contigs, significantly more were mapped to the microchromosomes than to the intermediate and the macrochromosomes of the zebra finch, indicating a higher overall level of sequence conservation on the microchromosomes than on the other types of chromosomes. The large number of great tit contigs that can be aligned to the zebra finch genome shows that this genome provides a valuable framework for large scale genetics, e.g. QTL mapping or whole genome association studies, in passerines. [source] INVITED REVIEW: Quantitative trait locus mapping in natural populations: progress, caveats and future directionsMOLECULAR ECOLOGY, Issue 2 2005JON SLATE Abstract Over the last 15 years quantitative trait locus (QTL) mapping has become a popular method for understanding the genetic basis of continuous variation in a variety of systems. For example, the technique is now an integral tool in medical genetics, livestock production, plant breeding and population genetics of model organisms. Ten years ago, it was suggested that the method could be used to understand continuous variation in natural populations. In this review I: (i) clarify what is meant by natural population in the QTL context, (ii) discuss whether evolutionary biologists have successfully mapped QTL in natural populations, (iii) highlight some of the questions that have been addressed by QTL mapping in natural populations, (iv) describe how QTL mapping can be conducted in unmanipulated natural populations, (v) highlight some of the limitations of QTL mapping and (vi) try to predict some future directions for QTL mapping in natural populations. [source] Allelopathy in crop/weed interactions , an updatePEST MANAGEMENT SCIENCE (FORMERLY: PESTICIDE SCIENCE), Issue 4 2007Regina G Belz Abstract Since varietal differences in allelopathy of crops against weeds were discovered in the 1970s, much research has documented the potential that allelopathic crops offer for integrated weed management with substantially reduced herbicide rates. Research groups worldwide have identified several crop species possessing potent allelopathic interference mediated by root exudation of allelochemicals. Rice, wheat, barley and sorghum have attracted most attention. Past research focused on germplasm screening for elite allelopathic cultivars and the identification of the allelochemicals involved. Based on this, traditional breeding efforts were initiated in rice and wheat to breed agronomically acceptable, weed-suppressive cultivars with improved allelopathic interference. Promising suppressive crosses are under investigation. Molecular approaches have elucidated the genetics of allelopathy by QTL mapping which associated the trait in rice and wheat with several chromosomes and suggested the involvement of several allelochemicals. Potentially important compounds that are constitutively secreted from roots have been identified in all crop species under investigation. Biosynthesis and exudation of these metabolites follow a distinct temporal pattern and can be induced by biotic and abiotic factors. The current state of knowledge suggests that allelopathy involves fluctuating mixtures of allelochemicals and their metabolites as regulated by genotype and developmental stage of the producing plant, environment, cultivation and signalling effects, as well as the chemical or microbial turnover of compounds in the rhizosphere. Functional genomics is being applied to identify genes involved in biosynthesis of several identified allelochemicals, providing the potential to improve allelopathy by molecular breeding. The dynamics of crop allelopathy, inducible processes and plant signalling is gaining growing attention; however, future research should also consider allelochemical release mechanisms, persistence, selectivity and modes of action, as well as consequences of improved crop allelopathy on plant physiology, the environment and management strategies. Creation of weed-suppressive cultivars with improved allelopathic interference is still a challenge, but traditional breeding or biotechnology should pave the way. Copyright © 2006 Society of Chemical Industry [source] Genetic analysis and QTL mapping of stalk digestibility and kernel composition in a high-oil maize mutant (Zea mays L.)PLANT BREEDING, Issue 3 2010H.-W. Wang With 1 figure and 5 tables Abstract A high-oil maize inbred line Ce03005 derived from ethylmethane-sulphonate mutagenesis was used to study the genetic basis of stalk digestibility and kernel chemical compositions, and evaluate the genetic relationship between traits. Quantitative trait loci (QTL) mapping employed 211 lines of F3 and F4 generations derived from Ce03005 × B73. Nuclear magnetic resonance and near-infrared reflectance spectrometry were used to analyse the following phenotypic traits: stalk digestibility and related traits including in vitro dry matter digestibility (IVDMD), in vitro cell wall digestibility (IVNDFD), neutral detergent fibre (NDF), acid detergent fibre (ADF), water soluble carbohydrate (WSC), and kernel composition including kernel oil content (KOC), kernel protein content (KPC) and kernel starch content (KSC). Correlation analysis indicated that IVDMD, IVNDFD and WSC were significantly (P = 0.01) positively correlated with KOC, while ADF and NDF were negatively correlated with KOC. Six QTL for IVDMD, five for IVNDFD, six for NDF, eight for ADF, three for WSC, eight for KOC, seven for KPC and 10 for KSC were detected in F3 and F4 generations. Five major QTL (R2 > 10) of qIVDMD6, qIVNDFD6, qNDF6, qADF6, qWSC6 andOlicm6 shared the same confidence interval on chromosome 6. The results suggested that KOC may be closely related or share the same QTL for stalk quality traits, and its change may have influences to the stalk components. [source] QTL analysis of crown rust resistance in perennial ryegrass under conditions of natural and artificial infectionPLANT BREEDING, Issue 4 2007B. Schejbel Abstract Crown rust is an economically devastating disease of perennial ryegrass. Both artificial crown rust inoculations, with the possibility of several selection cycles in one year, as well as marker-assisted selection can be used for more efficient breeding of new resistant cultivars. The objective of this study was to map quantitative trait loci (QTL) for response to crown rust infection in perennial ryegrass. In order to identify relevant markers for response to crown rust infection, QTL mapping was performed on a ryegrass mapping population which was evaluated for resistance in the field for two years as well as by artificial pathogen inoculations using a detached leaf assessment. The broad sense heritability values for the field, detached leaf and combined assays were 0.42, 0.56, and 0.64, respectively, indicating a good potential for selection for crown rust resistance. A total of six QTLs were identified and mapped to linkage groups (LG) LG1, LG4 and LG5, explaining between 6.8% and 16.4% of the total phenotypic variation. [source] Linkage and quantitative trait locus mapping of foliage late blight resistance in the wild species Solanum verneiPLANT BREEDING, Issue 3 2006K. K. Sørensen Abstract The global cultivation of potato (Solanum tuberosum) is threatened by epidemics caused by new variants of the late blight pathogen, Phytophthora infestans. New sources of durable late blight resistance are urgently needed and these may be found in wild Solanum species. The diploid wild species, S. vernei, has not previously been subjected to mapping of quantitative trait loci (QTLs) for late blight resistance. Two populations designated HGIHJS and HGG, originating from a cross between a clone of S. vernei and two different S. tuberosum clones were evaluated in field trials for late blight infestation. The relative area under the disease progress curve (RAUDPC) was estimated and used for QTL mapping. A linkage map of S. vernei, comprising 11 linkage groups, nine of which could be assigned to chromosomes, was constructed. Results indicated that the resistance in S. vernei was quantitatively inherited. Significant QTLs for late blight resistance were identified on chromosomes VIII (HGG), VI and IX (HGIHJS). In addition, potential QTLs were detected on chromosomes VII (HGIHJS) and IX (HGG). A putative and a significant QTL for tuber yield were found on chromosomes VI and VII in HGG, but no linkage between yield and resistance was indicated. The QTL for late blight resistance, which mapped to chromosome IX, could be useful for late blight resistance breeding as it was located close to the microsatellite marker STM1051 in both populations. [source] QTL mapping and associated marker selection for the efficacy of green plant regeneration in anther culture of ricePLANT BREEDING, Issue 1 2002Y. S. Kwon Abstract Anther culturability of rice is a quantitative trait controlled by nuclear-encoded genes. The identification of quantitative trait loci (QTL) and associated marker selection for anther culturability is important for increasing the efficiency of green plant regeneration from microspores. QTL associated with the capacity for green plant regeneration in anther culture of rice were mapped on chromosomes 3 and 10 using 164 recombinant inbred (RI) lines from a cross between ,Milyang 23' and ,Gihobyeo'. The quantitative trait locus located on chromosome 10 was detected repeatedly when three anther culture methods were applied and was tightly linked to the markers, RG323, RG241 and RZ400. Associations between these markers and the efficacy of green plant regeneration in 43 rice cultivars and two F2 populations, ,MG RI036'/,Milyang 23', and ,MG RI036';/,IR 36' were analysed. One of these markers, RZ400, was able to identify effectively genotypes with good (> 10.0%) and poor (< 3.0%) regenerability, based on the marker genotypes in the cultivars and two F2 populations. This marker enables the screening of rice germplasm for anther culturability and introgression into elite lines in breeding programmes. [source] Mechanisms of Regulation of Litter Size in Pigs on the Genome LevelREPRODUCTION IN DOMESTIC ANIMALS, Issue 2007O Distl Contents Improvement in litter size has become of great interest in pig industry as good fecundity is directly related to a sow's productive life. Genetic regulation of litter size is complex and the main component traits so far defined are ovulation rate, embryonic survival, uterus capacity, foetal survival and pre-weaning losses. Improvements using concepts of the quantitative genetics let expect only slow genetic progress due to its low heritability of approximately 0.09 for number of piglets born alive. Marker assisted selection allows to dissect litter size in its component traits and using molecular genetic markers for the components of litter size traits promises more progress and advantages in optimum balancing of the different physiological mechanisms influencing litter size. In this review, efforts being made to unravel the genetic determinants of litter size are accounted and discussed. For litter size traits, more than 50 quantitative trait loci (QTL) were mapped and in more than 12 candidate genes associations confirmed. The number of useful candidate genes is much larger as shown by expression profiles and in addition, much more QTL can be assumed. These functional genomic approaches, both QTL mapping and candidate gene analysis, have to be merged for a better understanding of a wider application across different pig breeds and lines. Newly developed tools based on microarray techniques comprising DNA variants or expressed tags of many genes or even the whole genome appear useful for in depth understanding of the genetics of litter size in pigs. [source] QTL for body weight, morphometric traits and stress response in European sea bass Dicentrarchus labraxANIMAL GENETICS, Issue 4 2010C. Massault Summary Natural mating and mass spawning in the European sea bass (Dicentrarchus labrax L., Moronidae, Teleostei) complicate genetic studies and the implementation of selective breeding schemes. We utilized a two-step experimental design for detecting QTL in mass-spawning species: 2122 offspring from natural mating between 57 parents (22 males, 34 females and one missing) phenotyped for body weight, eight morphometric traits and cortisol levels, had been previously assigned to parents based on genotypes of 31 DNA microsatellite markers. Five large full-sib families (five sires and two dams) were selected from the offspring (570 animals), which were genotyped with 67 additional markers. A new genetic map was compiled, specific to our population, but based on the previously published map. QTL mapping was performed with two methods: half-sib regression analysis (paternal and maternal) and variance component analysis accounting for all family relationships. Two significant QTL were found for body weight on linkage group 4 and 6, six significant QTL for morphometric traits on linkage groups 1B, 4, 6, 7, 15 and 23 and three suggestive QTL for stress response on linkage groups 3, 14 and 23. The QTL explained between 8% and 38% of phenotypic variance. The results are the first step towards identifying genes involved in economically important traits like body weight and stress response in European sea bass. [source] Mapping QTL for growth and shank traits in chickens divergently selected for high or low body weightANIMAL GENETICS, Issue 4 2010G. A. Ankra-Badu Summary An F2 population (695 individuals) was established from broiler chickens divergently selected for either high (HG) or low (LG) growth, and used to localize QTL for developmental changes in body weight (BW), shank length (SL9) and shank diameter (SD9) at 9 weeks. QTL mapping revealed three genome-wide QTL on chromosomes (GGA) 2, 4 and 26 and three suggestive QTL on GGA 1, 3 and 5. Most of the BW QTL individually explained 2,5% of the phenotypic variance. The BW QTL on GGA2 explained about 7% of BW from 3 to 7 weeks of age, while that on GGA4 explained 15% of BW from 5 to 9 weeks. The BW QTL on GGA2 and GGA4 could be associated with early and late growth respectively. The GGA4 QTL also had the largest effect on SL9 and SD9 and explained 7% and 10% of their phenotypic variances respectively. However, when SL9 and SD9 were corrected with BW9, a shank length percent QTL was identified on GGA2. We identified novel QTL and also confirmed previously identified loci in other chicken populations. As the foundation population was established from commercial broiler strains, it is possible that QTL identified in this study could still be segregating in commercial strains. [source] Mapping and expression analyses during porcine foetal muscle development of 12 genes involved in histone modificationsANIMAL GENETICS, Issue 2 2009Y. B. Peng Summary Histone modifications (methylation and demethylation) regulate gene expression and play a role in cell proliferation and differentiation by their actions on chromatin structure. In this context, we studied the temporal expression profiles of genes acting on histone methylation and demethylation during skeletal muscle proliferation and differentiation. Quantitative real-time PCR was used to quantify the mRNA levels of CARM1, JARID1A, JMJD2A, LSD1, PRMT2, PRMT5, SMYD1, SMYD2, SMYD3, SETDB1, Suv39h2 and SUZ12 in foetal skeletal muscle. Our results showed that CARM1, JARID1A, JMJD2A, SMYD1 and SMYD2 were differentially expressed in embryonic muscles of 33 days post-conception (dpc), 65 dpc and 90 dpc. These 12 genes were mapped to porcine chromosomes (SSC) 2q21,24, 5q25, 6q35, 6q12,21, 6p15, 7q21, 3q21,27, 9q26, 10p16, 4q15,16, 10q14,16 and 12p12 respectively. Taking into account the reported QTL mapping results, gene expression analysis and radiation hybrid mapping results, these results suggest that five genes (CARM1, JARID1A, JMJD2A, SMYD1 and SMYD2) could be good candidate genes for growth and backfat thickness traits. [source] Quantitative trait loci for leg weakness traits in a Landrace purebred populationANIMAL SCIENCE JOURNAL, Issue 1 2010Yoshinobu UEMOTO ABSTRACT Leg weakness in pigs is a serious problem in the pig industry. We performed a whole genome quantitative trait locus (QTL) analysis to find QTLs affecting leg weakness traits in the Landrace population. Half-sib progeny (n = 522) with five sires were measured for leg weakness traits. Whole genome QTL mapping was performed using a half-sib regression-based method using 190 microsatellite markers. No experiment-wide significant QTLs affecting leg weakness traits were detected. However, at the 5% chromosome-wide level, QTLs affecting leg weakness traits were detected on chromosomes 1, 3, 10 and 11 with QTL effects ranging from 0.07 to 0.11 of the phenotypic variance. At the 1% chromosome-wide level, QTLs affecting rear feet score and total leg score were detected on chromosomes 2 and 3 with QTL effects of 0.11 and 0.13 of the phenotypic variance, respectively. On chromosome 3 and 10, some QTLs found in this study were located at nearby positions. The present study is one of the first reports of QTLs affecting fitness related traits such as leg weakness traits, that segregate within the Landrace population. The study also provides useful information for studying QTLs in purebred populations. [source] Gaussian Process Based Bayesian Semiparametric Quantitative Trait Loci Interval MappingBIOMETRICS, Issue 1 2010Hanwen Huang Summary In linkage analysis, it is often necessary to include covariates such as age or weight to increase power or avoid spurious false positive findings. However, if a covariate term in the model is specified incorrectly (e.g., a quadratic term misspecified as a linear term), then the inclusion of the covariate may adversely affect power and accuracy of the identification of quantitative trait loci (QTL). Furthermore, some covariates may interact with each other in a complicated fashion. We implement semiparametric models for single and multiple QTL mapping. Both mapping methods include an unspecified function of any covariate found or suspected to have a more complex than linear but unknown relationship with the response variable. They also allow for interactions among different covariates. This analysis is performed in a Bayesian inference framework using Markov chain Monte Carlo. The advantages of our methods are demonstrated via extensive simulations and real data analysis. [source] Nonparametric Functional Mapping of Quantitative Trait LociBIOMETRICS, Issue 1 2009Jie Yang Summary Functional mapping is a useful tool for mapping quantitative trait loci (QTL) that control dynamic traits. It incorporates mathematical aspects of biological processes into the mixture model-based likelihood setting for QTL mapping, thus increasing the power of QTL detection and the precision of parameter estimation. However, in many situations there is no obvious functional form and, in such cases, this strategy will not be optimal. Here we propose to use nonparametric function estimation, typically implemented with B-splines, to estimate the underlying functional form of phenotypic trajectories, and then construct a nonparametric test to find evidence of existing QTL. Using the representation of a nonparametric regression as a mixed model, the final test statistic is a likelihood ratio test. We consider two types of genetic maps: dense maps and general maps, and the power of nonparametric functional mapping is investigated through simulation studies and demonstrated by examples. [source] | |||||||||||||