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PubMed2000

Efficient marker-based recurrent selection for multiple quantitative trait loci.

We studied the efficiency of recurrent selection based solely on marker genotypes (marker-based selection), in order to increase favourable allele frequency at 50 previously detected quantitative trait loci (QTLs). Two selection procedures were investigated, using computer simulations: (1) Truncation Selection (MTS), in which individuals are ranked based on marker score, and best individuals are selected for recombination; and (2) QTL Complementation Selection (QCS), in which individuals are selected such that their QTL composition complements those individuals already selected. Provided QTL locations are accurate, marker-based selection with a population size of 200 was very effective in rapidly increasing frequencies of favourable QTL alleles. QCS methods were more effective than MTS for improving the mean frequency and fixation of favourable QTL alleles. Marker-based selection was not very sensitive to a reduction in population size, and appears valuable to optimize the use of molecular markers in recurrent selection programmes.

Alleles↗
PubMed1998

Genotype-environment interaction at quantitative trait loci affecting sensory bristle number in Drosophila melanogaster.

The magnitude of segregating variation for bristle number in Drosophila melanogaster exceeds that predicted from models of mutation-selection balance. To evaluate the hypothesis that genotype-environment interaction (GEI) maintains variation for bristle number in nature, we quantified the extent of GEI for abdominal and sternopleural bristles among 98 recombinant inbred lines, derived from two homozygous laboratory strains, in three temperature environments. There was considerable GEI for both bristle traits, which was mainly attributable to changes in rank order of line means. We conducted a genome-wide screen for quantitative trait loci (QTLs) affecting bristle number in each sex and temperature environment, using a dense (3.2-cM) marker map of polymorphic insertion sites of roo transposable elements. Nine sternopleural and 11 abdominal bristle number QTLs were detected. Significant GEI was exhibited by 14 QTLs, but there was heterogeneity among QTLs in their sensitivity to thermal and sexual environments. To further evaluate the hypothesis that GEI maintains variation for bristle number, we require estimates of allelic effects across environments at genetic loci affecting the traits. This level of resolution may be achievable for Drosophila bristle number because candidate loci affecting bristle development often map to the same location as bristle number QTLs.

Animals↗
PubMed2001

Evidence for a language quantitative trait locus on chromosome 7q in multiplex autism families.

Autism is a syndrome characterized by deficits in language and social skills and by repetitive behaviors. We hypothesized that potential quantitative trait loci (QTLs) related to component autism endophenotypes might underlie putative or significant regions of autism linkage. We performed nonparametric multipoint linkage analyses, in 152 families from the Autism Genetic Resource Exchange, focusing on three traits derived from the Autism Diagnostic Interview: "age at first word," "age at first phrase," and a composite measure of "repetitive and stereotyped behavior." Families were genotyped for 335 markers, and multipoint sib pair linkage analyses were conducted. Using nonparametric multipoint linkage analysis, we found the strongest QTL evidence for age at first word on chromosome 7q (nonparametric test statistic [Z] 2.98; P=.001), and subsequent linkage analyses of additional markers and association analyses in the same region supported the initial result (Z=2.85, P=.002; chi(2)=18.84, df 8, P=.016). Moreover, the peak fine-mapping result for repetitive behavior (Z=2.48; P=.007) localized to a region overlapping this language QTL. The putative autism-susceptibility locus on chromosome 7 may be the result of separate QTLs for the language and repetitive or stereotyped behavior deficits that are associated with the disorder.

Autistic Disorder↗
PubMed1997

Empirical evaluation of genome scans for linkage of a quantitative trait associated with a complex disorder.

Nonparametric sib-pair analysis (Haseman-Elston) was used to search for evidence of linkage between a putative locus for a complex quantitative trait Q1 and genome-wide markers (367 markers from 10 chromosomes) for the first 100 replicates of nuclear family data. The characteristics of the statistically positive linkage results [the magnitude of p-values (p), the number of supporting flanking markers, and the percentage of positive replicates] were compared for true linkage (major and minor genes) and false positive evidence for linkage. Discriminant analysis was used to evaluate which characteristics of these statistically positive linkage results are good indicators to discriminate true linkage from false positive evidence for linkage. Sensitivity and false positive rates of several proposed criteria for linkage, as well as the criteria based on our results were evaluated. The relationship between the map location of the marker with the lowest p-value and the map location of the true underlying gene was also evaluated, which provided useful information for fine mapping and replication studies.

Age Distribution↗
PubMed2003

Candidate gene analysis for quantitative traits using the transmission disequilibrium test: the example of the melanocortin 4-receptor in pigs.

Population-wide associations between loci due to linkage disequilibrium can be used to map quantitative trait loci (QTL) with high resolution. However, spurious associations between markers and QTL can also arise as a consequence of population stratification. Statistical methods that cannot differentiate between loci associations due to linkage disequilibria from those caused in other ways can render false-positive results. The transmission-disequilibrium test (TDT) is a robust test for detecting QTL. The TDT exploits within-family associations that are not affected by population stratification. However, some TDTs are formulated in a rigid form, with reduced potential applications. In this study we generalize TDT using mixed linear models to allow greater statistical flexibility. Allelic effects are estimated with two independent parameters: one exploiting the robust within-family information and the other the potentially biased between-family information. A significant difference between these two parameters can be used as evidence for spurious association. This methodology was then used to test the effects of the fourth melanocortin receptor (MC4R) on production traits in the pig. The new analyses supported the previously reported results; i.e., the studied polymorphism is either causal or in very strong linkage disequilibrium with the causal mutation, and provided no evidence for spurious association.

Alleles↗
PubMed2004

Mouse inbred strain sequence information and yin-yang crosses for quantitative trait locus fine mapping.

The shared ancestry of mouse inbred strains, together with the availability of sequence and phenotype information, is a resource that can be used to map quantitative trait loci (QTL). The difficulty in using only sequence information lies in the fact that in most instances the allelic state of the QTL cannot be unambiguously determined in a given strain. To overcome this difficulty, the performance of multiple crosses between various inbred strains has been proposed. Here we suggest and evaluate a general approach, which consists of crossing the two strains used initially to map the QTL and any new strain. We have termed these crosses "yin-yang," because they are complementary in nature as shown by the fact that the QTL will necessarily segregate in only one of the crosses. We used the publicly available SNP database of chromosome 16 to evaluate the mapping resolution achievable through this approach. Although on average the improvement of mapping resolution using only four inbred strains was relatively small (i.e., reduction of the QTL-containing interval by half at most), we found a great degree of variability among different regions of chromosome 16 with regard to mapping resolution. This suggests that with a large number of strains in hand, selecting a small number of strains may provide a significant contribution to the fine mapping of QTL.

Alleles↗
PubMed2000

Identification and time dependence of quantitative trait loci for basal locomotor activity in the BXD recombinant inbred series and a B6D2 F2 intercross.

A complimentary two-phase strategy was used to detect and map quantitative trait loci (QTLs) associated with the basal locomotor response to a saline challenge (10 ml/kg). In phase 1, putative QTLs, significant at p < 0.01 or better, were identified by analysis of the strain means for 25 strains of the B x D recombinant inbred series. QTLs were identified on chromosomes 1, 3, 5, 9, 10, 16, and 18. Some of these QTLs were detected across the entire experimental period (0-20 min), while others were associated with specific 5-min blocks. Eighteen hundred C57BL/6J (B6) x DBA/2J (D2) F2 intercross animals were phenotyped for the basal locomotor response, and of this group, 500 to 700 individuals, pseudo-randomly selected, were used for a genomewide scan to confirm the RI-generated QTLs and to detect new QTLs. No new QTLs were detected but the QTLs on chromosome 1 were confirmed at p < 10(-5) to p < 10(-9), depending on the time interval. In addition, the QTLs on chromosomes 5 and 9 were confirmed at p < 0.001, providing a combined probability (RI + F2) which exceeds the threshold for a significant association. Two additional phenotypes which showed significant RI strain differences were examined--adaptation and thigmotaxis. Adaptation mapped to the same region of chromosome 9 and thigmotaxis to the same region of chromosome 1 as the distance-traveled QTL. Overall, the data presented here and elsewhere (Flint et al., 1995; Gershenfeld et al., 1997) illustrate that QTLs for basal activity are both robust and reliable.

Animals↗
PubMed2005

[Methodology of mapping quantitative trait loci for discrete traits using maximum likelihood].

The maximum likelihood method was used to compare the efficiency of interval mapping with either the threshold model or the linear model. The irfluencing factors of quantitative trait loci (QTL) detection efficiency (e.g. QTL effect, heritability and incidence of categories) were simulated in our study. Daughter design with multiple families was applied, and the number of segregating population was 500. The results showed that the threshold model was superior in terms of parameter estimation. It was a more efficient and accurate model of QTL mapping for discrete traits. In addition, the accuracy of QTL mapping depended on the effect of the putative QTL, the value of heritability and incidence directly. With an increase of QTL effect, heritability and incidence of categories, the accuracy of QTL mapping improved correspondingly.

Algorithms↗
PubMed1998

Quantitative trait loci disposing for both experimental arthritis and encephalomyelitis in the DA rat; impact on severity of myelin oligodendrocyte glycoprotein-induced experimental autoimmune encephalomyelitis and antibody isotype pattern.

Quantitative trait loci (QTL) controlling inflammatory diseases with different organ specificity may hypothetically either be unique for one disease or shared among different diseases. We have investigated whether five non-MHC QTL controlling susceptibility to experimental arthritis in the DA rat also influence myelin oligodendrocyte glycoprotein (MOG)-induced experimental autoimmune encephalomyelitis (EAE) in an F2 intercross between inbred DA and PVG.RT1a rats. Two of the five chromosome regions affecting arthritis in the DA rat also regulate phenotypes of EAE. The DA allele at markers in Cia3 (collagen-induced arthritis QTL) on chromosome 4 is associated with more severe EAE and high levels of anti-MOG antibodies of the IgG2c subclass. Since production of antibodies of the IgG2c subclass may be stimulated by Th1 cells, and there is previous evidence that such cells promote EAE, it is possible that both of the studied phenotypes are controlled by the same gene or genes regulating Th1/Th2 cell differentiation. Furthermore, we show that Oia2 (oil-induced arthritis QTL) on chromosome 4 regulates levels of anti-MOG antibodies of the IgG1 subclass and of anti-MOG IgE, but that this gene region does not affect clinical disease severity in our study. Since production of IgE and IgG1 may be stimulated by Th2 cells, this QTL may also control Th1/Th2 bias. We conclude that Cia3 and Oia2 regulate MOG-induced EAE in rats. Furthermore, since both EAE and arthritis phenotypes co-localize to these gene regions, they may harbor genes which are key regulators of pathogenic immune responses.

Animals↗
PubMed2005

The non-major histocompatibility complex quantitative trait locus Cia10 contains a major arthritis gene and regulates disease severity, pannus formation, and joint damage.

OBJECTIVE: To construct rats congenic for the chromosome 2 arthritis-regulatory quantitative trait locus Cia10, originally identified in a (DA x ACI)F(2) intercross rat strain that had been assessed for collagen-induced arthritis (CIA), and to determine the effect of this congenic interval on arthritis severity, joint histologic structure, and cytokine transcription in rats with pristane-induced arthritis (PIA). METHODS: A 52.6-MB interval derived from the ACI (CIA- and PIA-resistant) strain and containing the Cia10 interval was introgressed into the DA (arthritis-susceptible) background through genotype-guided congenic breeding. Homozygous male and female DA.ACI(Cia10) congenic rats were studied for their susceptibility to and severity of PIA, and were compared with same-sex DA rats. Histologic analyses were done on hind paws collected on day 32 following the pristane injection. Levels of interleukin-1beta (IL-1beta) and tumor necrosis factor alpha (TNFalpha) messenger RNA (mRNA) were measured with real-time polymerase chain reaction on synovial tissues from day-32 ankles. RESULTS: Both male and female DA.ACI(Cia10) congenic rats developed a significantly milder form of arthritis, with a 95% and 92% reduction in the arthritis severity index compared with DA male and female controls, respectively (males P < or = 0.001 and females P = 0.003). DA.ACI(Cia10) congenic rat synovial tissue was more likely to preserve its normal histologic architecture, including minimal to no cartilage and bone erosions, synovial hyperplasia, and pannus formation, and reduced numbers of vessels (angiogenesis), when compared with DA synovial tissue. There was a 2.7- and 2.4-fold reduction in the amount of IL-1beta and TNFalpha mRNA, respectively, in the synovial tissue of DA.ACI(Cia10) congenic rats compared with DA rats. Sequencing analyses of complementary DNA for the Cia10-predicted candidate gene Ptpn8, the rat homolog of the rheumatoid arthritis (RA)-susceptibility gene PTPN22, revealed no polymorphisms between the DA and ACI strains. CONCLUSION: This study determined that Cia10 harbors a major autoimmune arthritis-regulatory gene. This gene regulates clinical disease severity, histologic damage, and the levels of at least two central proinflammatory cytokines. We are in the process of narrowing down the critical region for positional cloning of the Cia10 gene. The identification of this gene will provide novel targets or pathways for focused candidate-gene studies in RA.

Animals↗
PubMed2006

Quantitative trait analysis of seed yield and other complex traits in hybrid spring rapeseed (Brassica napus L.): 2. Identification of alleles from unadapted germplasm.

Unadapted germplasm may contain alleles that could improve hybrid cultivars of spring oilseed Brassica napus. Quantitative trait loci (QTL) mapping was used to identify potentially useful alleles from two unadapted germplasm sources, a Chinese winter cultivar and a re-synthesized B. napus, that increase seed yield when introgressed into a B. napus spring hybrid combination. Two populations of 160 doubled haploid (DH) lines were created from crosses between the unadapted germplasm source and a genetically engineered male-fertility restorer line (P1804). A genetically engineered male-sterile tester line was used to create hybrids with each DH line (testcrosses). The two DH line populations were evaluated in two environments and the two testcross populations were evaluated in three or four environments for seed yield and other agronomic traits. Several genomic regions were found in the two testcross populations which contained QTL for seed yield. The map positions of QTL for days to flowering and resistance to a bacterial leaf blight disease coincided with QTL for seed yield and other agronomic traits, suggesting the occurrence of pleiotropic or linked effects. For two hybrid seed yield QTL, the favorable alleles increasing seed yield originated from the unadapted parents, and one of these QTL was detected in multiple environments and in both populations. In this QTL region, a chromosome rearrangement was identified in P1804, which may have affected seed yield.

Alleles↗
PubMed2002

Quantitative trait loci affecting a courtship signal in Drosophila melanogaster.

Courtship plays a major role in the sexual isolation of species, yet the genetics underlying courtship behaviour are poorly understood. Here we analyse quantitative trait loci (QTL) for a major component of courtship song in recombinant inbred lines derived from two laboratory strains of Drosophila melanogaster. The total variance among lines exceeds that between parental strains, and is broadly similar to that seen among geographic strains of the Cosmopolitan form of this species. Previous studies of the quantitative genetics of fly song have implied a polygenic additive inheritance with numerous genes spread throughout the genome. We find evidence for only three significant QTLs explaining 54% of the genetic variance in total. Thus there is evidence for a few large effect genes contributing to the genetic variance among lines. Interestingly, almost all of the candidate song genes previously described for D. melanogaster do not coincide with our QTLs.

Animals↗
PubMed2006

Identification of quantitative trait loci associated with egg quality, egg production, and body weight in an F2 resource population of chickens.

Egg production and egg quality are complex sex-limited traits that may benefit from the implementation of marker-assisted selection. The primary objective of the current study was to identify quantitative trait loci (QTL) associated with egg traits, egg production, and body weight in a chicken resource population. Layer (White Leghorn hens) and broiler (Cobb-Cobb roosters) lines were crossed to generate an F2 population of 508 hens over seven hatches. Phenotypes for 29 traits (weekly body weight from hatch to 6 weeks, egg traits including egg, albumen, yolk, and shell weight, shell thickness, shell puncture score, percentage of shell, and egg shell colour at 35 and 55 weeks of age, as well as egg production between 16 and 55 weeks of age) were measured in hens of the resource population. Genotypes of 120 microsatellite markers on 28 autosomal groups were determined, and interval mapping was conducted to identify putative QTL. Eleven QTL tests representing two regions on chromosomes 2 and 4 surpassed the 5% genome-wise significance threshold. These QTL influenced egg colour, egg and albumen weight, percent shell, body weight, and egg production. The chromosome 4 QTL region is consistent with multiple QTL studies that define chromosome 4 as a critical region significantly associated with a variety of traits across multiple resource populations. An additional 64 QTL tests surpassed the 5% chromosome-wise significance threshold.

Animals↗
PubMed2002

Effectiveness of selective genotyping for detection of quantitative trait loci: an analysis of grain and malt quality traits in three barley populations.

Marker genotype data and grain and malt quality phenotype data from three barley (Hordeum vulgare L.) mapping populations were used to investigate the feasibility of selective genotyping for detection of quantitative trait loci (QTLs). With selective genotyping, only individuals with high and low phenotypic values for the trait of interest are genotyped. Here, genotyping of 10 to 70% of each population (i.e., 5 to 35% in each tail of the phenotypic distribution) was considered. Genomic positions detected by selective genotyping were compared to QTL position estimates from interval mapping analysis using marker genotype data from the entire population. Selective genotyping reliably detected almost all of the mapped QTLs, often with only 10% of the population genotyped. Selective genotyping also detected spurious QTLs in regions of the genome where no significant QTL had been mapped. Even with additional genotyping to verify putative QTLs, the total genotyping effort for detection of QTLs for a single trait by selective genotyping was usually less than 30% of that required for conventional interval mapping. Simultaneous investigation of two or more traits by selective genotyping would require additional genotyping effort, but could still be worthwhile.

Genotype↗
PubMed2002

A penalized likelihood method for mapping epistatic quantitative trait Loci with one-dimensional genome searches.

Epistasis is a common and important phenomenon, as indicated by results from a number of recent experiments. Unfortunately, the discovery of epistatic quantitative trait loci (QTL) is difficult since one must search for multiple QTL simultaneously in two or more dimensions. Such a multidimensional search necessitates many statistical tests, and a high statistical threshold must be adopted to avoid false positives. Furthermore, the large number of (interaction) parameters in comparison with the number of observations results in a serious danger of overfitting and overinterpretation of the data. In this article we present a new statistical framework for mapping epistasis in inbred line crosses. It is based on reducing the high dimensionality of the problem in two ways. First, epistatic QTL are mapped in a one-dimensional genome scan for high interactions between QTL and the genetic background. Second, the dimension of the search is bounded by penalized likelihood methods. We use simulated backcross data to illustrate the new approach.

Chromosome Mapping↗
PubMed1999

Genetic dissection of "OLETF," a rat model for non-insulin-dependent diabetes mellitus: quantitative trait locus analysis of (OLETF x BN) x OLETF.

To identify genetic determinants relevant to non-insulin-dependent diabetes mellitus (NIDDM), we performed a genome-wide analysis for quantitative trait loci (QTLs) using 359 backcross progeny of the Otsuka Long-Evans Tokushima Fatty (OLETF) rat. The OLETF strain is a well-studied animal model of obese NIDDM, with features of hyperinsulinemia, hyperglycemia, insulin resistance, and abundant abdominal fat. Our extensive genomic scanning with 218 markers revealed nine significant QTLs, including a strong determinant of obesity on chromosome 1 (Dmo1: LOD = 13.99, for body weight). Two highly significant QTLs for glucose homeostasis were found, one on chromosome 1 (Dmo4 LOD = 7.16, for postprandial glucose level) and the other on chromosome X (Dmo11/Odb1: LOD = 7.81, for postprandial glucose level). These data are comparable to results of our previous studies of the OLETF rat.

Adipose Tissue↗
PubMed2005

New quantitative trait loci that regulate wound healing in an intercross progeny from DBA/1J and 129 x 1/SvJ inbred strains of mice.

Wound healing/regeneration mouse models are few, and studies performed have mainly utilized crosses between MRL/MPJ (a good healer) and SJL/J (a poor healer) or MRL/lpr (a good healer) and C57BL/6J (a poor healer). Wound healing is a complex trait with many genes involved in the expression of the phenotype. Based on data from previous studies that common and additional quantitative trait loci (QTL) were identified using different crosses of inbred strains of mice for various complex traits, we hypothesized that a new cross would identify common and additional QTL, unique modes of inheritance, and interacting loci, which are responsible for variation in susceptibility to fast wound healing. In this study, we crossed DBA/1J (DBA, a good healer) and 129/SvJ (129, a poor healer) and performed a genome-wide scan using 492 (DBA x 129) F2 mice and 98 markers to identify QTL that regulate wound healing/regeneration. Four QTL on chromosomes 1, 4, 12, and 18 were identified which contributed toward wound healing in F2 mice and accounted for 17.1% of the phenotypic variation in ear punch healing. Surprisingly, locus interactions contributed to 55.7% of the phenotype variation in ear punch healing. In conclusion, we have identified novel QTL and shown that minor interacting loci contribute significantly to wound healing in DBA x 129 mice cross.

Animals↗
PubMed2004

Functional mapping of quantitative trait loci underlying growth trajectories using a transform-both-sides logistic model.

The incorporation of developmental control mechanisms of growth has proven to be a powerful tool in mapping quantitative trait loci (QTL) underlying growth trajectories. A theoretical framework for implementing a QTL mapping strategy with growth laws has been established. This framework can be generalized to an arbitrary number of time points, where growth is measured, and becomes computationally more tractable, when the assumption of variance stationarity is made. In practice, however, this assumption is likely to be violated for age-specific growth traits due to a scale effect. In this article, we present a new statistical model for mapping growth QTL, which also addresses the problem of variance stationarity, by using a transform-both-sides (TBS) model advocated by Carroll and Ruppert (1984, Journal of the American Statistical Association 79, 321-328). The TBS-based model for mapping growth QTL cannot only maintain the original biological properties of a growth model, but also can increase the accuracy and precision of parameter estimation and the power to detect a QTL responsible for growth differentiation. Using the TBS-based model, we successfully map a QTL governing growth trajectories to a linkage group in an example of forest trees. The statistical and biological properties of the estimates of this growth QTL position and effect are investigated using Monte Carlo simulation studies. The implications of our model for understanding the genetic architecture of growth are discussed.

Biometry↗