Quantitative trait Loci for glomerulosclerosis, kidney weight and body weight in the focal glomerulosclerosis mouse model.

In 183 male progeny derived from a backcross between the FGS/Kist strain, a new mouse model for focal glomerulosclerosis (FGS) in humans, and the standard normal strain, C57BL/6J, we performed a genome-wide scan for quantitative trait loci (QTLs) affecting the glomerulosclerosis index (GSI) based on histological observation as well as kidney and body weights. Two QTLs for GSI (Gsi1-2) located on chromosomes (Chrs) 8 and 10, a kidney weight QTL (Kdw1) on Chr 19, and a body weight QTL (Bdw1) on Chr 13 were detected at the genome-wide 5% or less level. The allele derived from FGS/Kist increased GSI at Gsi1, but decreased it at Gsi2. The mice homozygous for the FGS/Kist allele decreased body and kidney weights. The identified QTLs accounted for 5-8% of the phenotypic variance.     

Quantitative trait loci in Drosophila

Phenotypic variation for quantitative traits results from the simultaneous segregation of alleles at multiple quantitative trait loci. Understanding the genetic architecture of quantitative traits begins with mapping quantitative trait loci to broad genomic regions and ends with the molecular definition of quantitative trait loci alleles. This has been accomplished for some quantitative trait loci in Drosophila. Drosophila quantitative trait loci have sex-, environment- and genotype-specific effects, and are often associated with molecular polymorphisms in non-coding regions of candidate genes. These observations offer valuable lessons to those seeking to understand quantitative traits in other organisms, including humans.     

Quantitative trait loci for aluminum resistance in wheat

Quantitative trait loci (QTL) for wheat resistance to aluminum (Al) toxicity were analyzed using simple sequence repeats (SSRs) in a population of 192 F₆ recombinant inbred lines (RILs) derived from a cross between an Al-resistant cultivar, Atlas 66 and an Al-sensitive cultivar, Chisholm. Wheat reaction to Al was measured by relative root growth and root response to hematoxylin stain in nutrient-solution culture. After screening 1,028 SSR markers for polymorphisms between the parents and bulks, we identified two QTLs for Al resistance in Atlas 66. One major QTL was mapped on chromosome 4D that co-segregated with the Al-activated malate transporter gene (ALMT1). Another minor QTL was located on chromosome 3BL. Together, these two QTLs accounted for about 57% of the phenotypic variation in hematoxylin staining score and 50% of the variation in net root growth (NRG). Expression of the minor QTL on 3BL was suppressed by the major QTL on 4DL. The two QTLs for Al resistance in Atlas 66 were also verified in an additional RIL population derived from Atlas 66/Century. Several SSR markers closely linked to the QTLs were identified and have potential to be used for marker-assisted selection (MAS) to improve Al-resistance of wheat cultivars in breeding programs.     

Quantitative trait loci for growth trajectories in Populus

Growth trajectories are a biological process important to plant and animal breeding, and to evolutionary genetic studies. In this article, we report the detection of quantitative trait loci (QTLs) responsible for growth trajectories in poplars that are used as a model system for the study of forest biology. These QTLs were localized on a genetic linkage map of polymorphic markers using a statistical mapping method incorporating growth-curve models. The effects of the QTLs on growth are described as a function of age, so that age-specific changes in QTL effects can be readily projected throughout the entire growth process. The QTLs identified display increased effects on growth when trees age, yet the timing of QTL activation is earlier for stem height than diameter, which is consistent with the ecological viewpoint of canopy competition. The implications of the results for breeding and silviculture are discussed.     

Quantitative trait loci for baseline erythroid traits

A substantial genetic contribution underlies variation in baseline peripheral blood counts. We performed quantitative trait locus/loci (QTL) analyses to identify chromosome (Chr) regions harboring genes influencing the baseline erythroid parameters in F₂ intercrosses between NZW/LacJ, SM/J, and C57BLKS/J inbred mice. We identified multiple significant QTL for red blood cell (RBC) count, hemoglobin (Hgb) and hematocrit (Hct) levels, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean cell hemoglobin concentration (CHCM). We identified four RBC count QTL: Rbcq1 (Chr 1, peak LOD score at 62 cM,), Rbcq2 (Chr 4, 60 cM), Rbcq3 (Chr 11, 34 cM), and Rbcq4 (Chr 10, 60 cM). Three MCV QTL were identified: Mcvq1 (Chr 7, 30 cM), Mvcq2 (Chr 11, 6 cM), and Mcvq3 (Chr 10, 60 cM). Single significant loci for Hgb (Hgbq1, Chr 16, 32 cM), Hct (Hctq1, Chr 3, 42 cM), and MCH (Mchq1, Chr 10, 60 cM) were identified. The data support the existence of a common RBC/MCH/MCV locus on Chr 10. Two QTL for CHCM (Chcmq1, Chr 2, 48 cM; Chcmq2, Chr 9, 44 cM) and an interaction between Chcmq2 with a locus on Chr 19 were identified. These analyses emphasize the genetic complexity underlying the regulation of erythroid peripheral blood traits in normal populations and suggest that genes not previously recognized as significantly impacting normal erythropoiesis exist.     

Quantitative trait loci for the circadian clock in Neurospora crassa

Neurospora crassa has been a model organism for the study of circadian clocks for the past four decades. Among natural accessions of Neurospora crassa, there is significant variation in clock phenotypes. In an attempt to investigate natural allelic variants contributing to quantitative variation, we used a quantitative trait loci mapping approach to analyze three independent mapping populations whose progenitors were collected from geographically isolated locations. Two circadian clock phenotypes, free-running period and entrained phase, were evaluated in the 188 F(1) progeny of each mapping population. To identify the clock QTL, we applied two QTL mapping analyses: composite interval mapping (CIM) and Bayesian multiple QTL analysis (BMQ). When controlling false positive rates < or =0.05, BMQ appears to be the more sensitive of the two approaches. BMQ confirmed most of the QTL from CIM (18 QTL) and identified 23 additional QTL. While 13 QTL colocalize with previously identified clock genes, we identified 30 QTL that were not linked with any previously characterized clock genes. These are candidate regions where clock genes may be located and are expected to lead to new insights in clock regulation.     

Quantitative trait loci affecting fatness in the chicken

An F2 chicken population of 442 individuals from 30 families, obtained by crossing a broiler line with a layer line, was used for detecting and mapping Quantitative Trait Loci (QTL) affecting abdominal fat weight, skin fat weight and fat distribution. Within-family regression analyses using 102 microsatellite markers in 27 linkage groups were carried out with genome-wide significance thresholds. The QTL for abdominal fat weight were found on chromosomes 3, 7, 15 and 28; abdominal fat weight adjusted for carcass weight on chromosomes 1, 5, 7 and 28; skin and subcutaneous fat on chromosomes 3, 7 and 13; skin fat weight adjusted for carcass weight on chromosomes 3 and 28; and skin fat weight adjusted for abdominal fat weight on chromosomes 5, 7 and 15. Interactions of the QTL with sex or family were unimportant and, for each trait, there was no evidence for imprinting or of multiple QTL on any chromosome. Significant dominance effects were obtained for all but one of the significant locations for QTL affecting the weight of abdominal fat, none for skin fat and one of the three QTL affecting fat distribution. The magnitude of each QTL ranged from 3.0 to 5.2% of the residual phenotypic variation or 0.2-0.8 phenotypic standard deviations. The largest additive QTL (on chromosome 7) accounted for more than 20% of the mean weight of abdominal fat. Significant positive and negative QTL were identified from both lines.     

Quantitative trait loci for biofortification traits in maize grain

Detecting genes that influence biofortification traits in cereal grain could help increase the concentrations of bioavailable mineral elements in crops to solve the global mineral malnutrition problem. The aims of this study were to detect the quantitative trait loci (QTLs) for phosphorus (P), iron (Fe), zinc (Zn), and magnesium (Mg) concentrations in maize grain in a mapping population, as well as QTLs for bioavailable Fe, Zn, and Mg, by precalculating their respective ratios with P. Elemental analysis of grain samples was done by coupled plasma-optical emission spectrometry in 294 F(4) lines of a biparental population taken from field trials of over 3 years. The population was mapped using sets of 121 polymorphic markers. QTL analysis revealed 32 significant QTLs detected for 7 traits, of which some were colocalized. The Additive-dominant model revealed highly significant additive effects, suggesting that biofortification traits in maize are generally controlled by numerous small-effect QTLs. Three QTLs for Fe/P, Zn/P, and Mg/P were colocalized on chromosome 3, coinciding with simple sequence repeats marker bnlg1456, which resides in close proximity to previously identified phytase genes (ZM phys1 and phys2). Thus, we recommend the ratios as bioavailability traits in biofortification research.     

Quantitative trait loci for body size components in mice

Do body size components, such as weights of internal organs and long bone lengths, with different functions and different developmental histories also have different genetic architectures and pleiotropic patterns? We examine murine quantitative trait loci (QTL) for necropsy weight, four long bone lengths, and four organ weights in the LG/J × SM/J intercross. Differences between trait categories were found in number of QTL, dominance, and pleiotropic patterns. Ninety-seven QTLs for individual traits were identified: 52 for long bone lengths, 30 for organ weights, and 15 for necropsy weight. Results for long bones are typically more highly significant than for organs. Organ weights were more frequently over- or underdominant than long bone lengths or necropsy weight. The single-trait QTLs map to 35 pleiotropic loci. Long bones are much more frequently affected in groups while organs tend to be affected singly or in pairs. Organs and long bones are found at the same locus in only 11 cases, 8 of which also include necropsy weight. Our results suggest mainly separate genetic modules for organ weights and long bone lengths, with a few loci that affect overall body size. Antagonistic pleiotropy, in which a locus has opposite effects on different characteristics, is uncommon.     

Quantitative trait loci for floral morphology in Arabidopsis thaliana

A central question in biology is how genes control the expression of quantitative variation. We used statistical methods to estimate genetic variation in eight Arabidopsis thaliana floral characters (fresh flower mass, petal length, petal width, sepal length, sepal width, long stamen length, short stamen length, and pistil length) in a cosmopolitan sample of 15 ecotypes. In addition, we used genome-wide quantitative trait locus (QTL) mapping to evaluate the genetic basis of variation in these same traits in the Landsberg erecta x Columbia recombinant inbred line population. There was significant genetic variation for all traits in both the sample of naturally occurring ecotypes and in the Ler x Col recombinant inbred line population. In addition, broad-sense genetic correlations among the traits were positive and high. A composite interval mapping (CIM) analysis detected 18 significant QTL affecting at least one floral character. Eleven QTL were associated with several floral traits, supporting either pleiotropy or tight linkage as major determinants of flower morphological integration. We propose several candidate genes that may underlie these QTL on the basis of positional information and functional arguments. Genome-wide QTL mapping is a promising tool for the discovery of candidate genes controlling morphological development, the detection of novel phenotypic effects for known genes, and in generating a more complete understanding of the genetic basis of floral development.     

Quantitative trait loci for inflorescence development in Arabidopsis thaliana

Variation in inflorescence development patterns is a central factor in the evolutionary ecology of plants. The genetic architectures of 13 traits associated with inflorescence developmental timing, architecture, rosette morphology, and fitness were investigated in Arabidopsis thaliana, a model plant system. There is substantial naturally occurring genetic variation for inflorescence development traits, with broad sense heritabilities computed from 21 Arabidopsis ecotypes ranging from 0.134 to 0.772. Genetic correlations are significant for most (64/78) pairs of traits, suggesting either pleiotropy or tight linkage among loci. Quantitative trait locus (QTL) mapping indicates 47 and 63 QTL for inflorescence developmental traits in Ler x Col and Cvi x Ler recombinant inbred mapping populations, respectively. Several QTL associated with different developmental traits map to the same Arabidopsis chromosomal regions, in agreement with the strong genetic correlations observed. Epistasis among QTL was observed only in the Cvi x Ler population, and only between regions on chromosomes 1 and 5. Examination of the completed Arabidopsis genome sequence in three QTL regions revealed between 375 and 783 genes per region. Previously identified flowering time, inflorescence architecture, floral meristem identity, and hormone signaling genes represent some of the many candidate genes in these regions.     

Quantitative trait loci for thermotolerance phenotypes in Drosophila melanogaster

For insects, temperature is a major environmental variable that can influence an individual's behavioral activities and fitness. Drosophila melanogaster is a cosmopolitan species that has had great success in adapting to and colonizing diverse thermal niches. This adaptation and colonization has resulted in complex patterns of genetic variation in thermotolerance phenotypes in nature. Although extensive work has been conducted documenting patterns of genetic variation, substantially less is known about the genomic regions or genes that underlie this ecologically and evolutionarily important genetic variation. To begin to understand and identify the genes controlling thermotolerance phenotypes, we have used a mapping population of recombinant inbred (RI) lines to map quantitative trait loci (QTL) that affect variation in both heat- and cold-stress resistance. The mapping population was derived from a cross between two lines of D. melanogaster (Oregon-R and 2b) that were not selected for thermotolerance phenotypes, but exhibit significant genetic divergence for both phenotypes. Using a design in which each RI line was backcrossed to both parental lines, we mapped seven QTL affecting thermotolerance on the second and third chromosomes. Three of the QTL influence cold-stress resistance and four affect heat-stress resistance. Most of the QTL were trait or sex specific, suggesting that overlapping but generally unique genetic architectures underlie resistance to low- and high-temperature extremes. Each QTL explained between 5 and 14% of the genetic variance among lines, and degrees of dominance ranged from completely additive to partial dominance. Potential thermotolerance candidate loci contained within our QTL regions are identified and discussed.     

Quantitative trait loci for locomotor behavior in Drosophila melanogaster

Locomotion is an integral component of most animal behaviors and many human diseases and disorders are associated with locomotor deficits, but little is known about the genetic basis of natural variation in locomotor behavior. Locomotion is a complex trait, with variation attributable to the joint segregation of multiple interacting quantitative trait loci (QTL), with effects that are sensitive to the environment. We assessed variation in a component of locomotor behavior (locomotor reactivity) in a population of 98 recombinant inbred lines of Drosophila melanogaster and mapped four QTL affecting locomotor reactivity by linkage to polymorphic roo transposable element insertion sites. We used complementation tests of deficiencies to fine map these QTL to 12 chromosomal regions and complementation tests of mutations to identify 13 positional candidate genes affecting locomotor reactivity, including Dopa decarboxylase (Ddc), which catalyzes the final step in the synthesis of serotonin and dopamine. Linkage disequilibrium mapping in a population of 164 second chromosome substitution lines derived from a single natural population showed that polymorphisms at Ddc were associated with naturally occurring genetic variation in locomotor behavior. These data implicate variation in the synthesis of bioamines as a factor contributing to natural variation in locomotor reactivity.     

Quantitative trait loci for steady-state platelet count in mice

Platelet count in humans is a strongly genetically regulated trait, with approximately 85% of the interindividual variance in platelet numbers attributable to genetic factors. Inbred mouse strains also have strain-specific platelet count ranges. As part of a project to identify novel factors that regulate platelet count, we identified two inbred mouse strains, CBA/CaH and QSi5, with substantial differences in platelet count (mean values of 581 vs. 1062 × 10⁹/L). An F₂ intercross resource of 1126 animals was bred from these two parental strains for a genomewide scan for quantitative trait loci (QTL) for platelet count. QTL were identified on MMU1 (LOD 6.8, p < 0.0005) and MMU11 (LOD 11.2, p < 0.0005) by selectively genotyping animals from the extremes of the F₂ platelet count distribution. Three other QTL of suggestive statistical significance were also detected on MMU7, 13, and 17. It is noteworthy that no QTL were detected in the vicinity of the genes encoding thrombopoietin (Thpo), and its receptor (c-Mpl), both known to influence platelet production. Comparison of gene expression levels between the parental mouse strains by microarrays also showed little difference in the mRNA levels of these known candidate genes. These results represent the first published use of a genetic linkage-based approach in a mouse model toward the identification of genetic factors that regulate platelet count.     

Quantitative trait loci for phyllochron and tillering in rice

Morphogenetic processes in sequentially growing leaves and tiller buds are highly synchronized in rice (Oryza sativa L.). Consequently, the appearance of successive leaves in the main tiller acts as the pacemaker for the whole shoot system development. The time interval between the appearance of successive leaves (days/leaf) in the main tiller is called the phyllochron. The objectives of the investigation reported here were: (1) to identify quantitative trait loci (QTLs) that control rice phyllochron and (2) to understand the roles of phyllochron QTLs as an underlying developmental factor for rice tillering. For this purpose we developed a set of recombinant inbred lines derived from a cross between IR36 (indica) and Genjah Wangkal (tropical japonica). Composite interval mapping detected three phyllochron QTLs located on chromosomes 4, 10 and 11, where the presence of a Genjah Wangkal allele increased phyllochron. The largest QTL (on chromosome 4) was located on the genomic region syntenic to the vicinity of the maize Teopod 2 mutation, while the QTL on chromosome 10 was close to the rice plastochron 1 mutation. These three phyllochron QTLs failed to coincide with major tiller number QTLs. However, one tiller number QTL was associated with small LOD peaks for phyllochron and tiller-bud dormancy that were linked in coupling phase, suggesting that linked small effects of phyllochron and tiller-bud dormancy might result in a multiplicative effect on tiller number.     

Quantitative trait loci: a meta-analysis

This article presents a method to combine QTL results from different independent analyses. This method provides a modified Akaike criterion that can be used to decide how many QTL are actually represented by the QTL detected in different experiments. This criterion is computed to choose between models with one, two, three, etc., QTL. Simulations are carried out to investigate the quality of the model obtained with this method in various situations. It appears that the method allows the length of the confidence interval of QTL location to be consistently reduced when there are only very few "actual" QTL locations. An application of the method is given using data from the maize database available online at http://www. agron.missouri.edu/.     

Quantitative trait loci in a bacterially induced model of inflammatory bowel disease

Inflammatory bowel diseases (IBDs) are complex disorders caused by a combination of environmental, microbial, and genetic factors. Genome-wide association studies in humans have successfully identified multiple genes and loci associated with disease susceptibility, but the mechanisms by which these loci interact with each other and/or with environmental factors (i.e., intestinal microbiota) to cause disease are poorly understood. Helicobacter hepaticus-induced intestinal inflammation in mice is an ideal model system for elucidating the genetic basis of IBD susceptibility in a bacterially induced system, as there are significant differences in H. hepaticus-induced disease susceptibility among inbred mouse strains. Infected A/J mice develop acute overexpression of proinflammatory cytokines followed 2?C3?months later by chronic cecal inflammation, whereas infected C57BL/6 mice fail to develop cecal inflammation or increased cytokine expression. The goal of this project was to use quantitative trait locus (QTL) mapping to evaluate genetic factors that contribute to the differential disease susceptibility between these two mouse strains. Using acute cecal IL-12/23p40 expression as a biomarker for disease susceptibility, QTL analysis of H. hepaticus-infected F₂ mice revealed involvement of multiple loci. The loci with the strongest association were located on Chromosome 3 and Chromosome 17, with logarithm of odds (LOD) scores of 6.89 and 3.09, respectively. Cecal expression of IL-12/23p40 in H. hepaticus-infected C57BL/6J-Chr3^A/J/NaJ chromosome substitution mice had an intermediate phenotype, significantly higher than in resistant C57BL/6 but lower than in susceptible A/J mice, confirming the importance of this locus to the immune response to H. hepaticus infection.     

Quantitative trait loci for estrogen-dependent pituitary tumor growth in the rat

Growth control is of fundamental importance to biology in general and of critical importance to cancer research in particular. Tumors develop when control of the normal growth process is lost. The rat pituitary is a model system for control of estrogen-dependent growth. Chronic estrogen treatment induces uncontrolled growth in the pituitaries of Fischer 344 (F344) rats, but not of Brown Norway (BN) rats. We have identified five quantitative trait loci (QTL) for estrogen-dependent pituitary mass (Edpm) in an F₂ intercross of F344 and BN. These QTL reside on rat Chromosomes (Chrs) 2, 3, 5, and 9 and explain a total of 55% of the genetic variance in the F₂. We have also detected suggestive evidence for a QTL on rat Chr 14. For Edpm2-1, Edpm2-2, Edpm3, and Edpm5, the F344 allele corresponds with increased pituitary mass, as expected. Surprisingly, for Edpm9 and the suggested QTL on Chr 14, the BN allele corresponds with increased pituitary mass. We also find evidence for interaction (epistasis) between Edpm3 and Edpm9 and between Edpm5 and the suggested QTL on Chr 14. Received: 3 March 1997 / Accepted: 1 July 1997     

Quantitative trait loci for physical activity traits in mice.

The genomic locations and identities of the genes that regulate voluntary physical activity are presently unknown. The purpose of this study was to search for quantitative trait loci (QTL) that are linked with daily mouse running wheel distance, duration, and speed of exercise. F(2) animals (n = 310) derived from high active C57L/J and low active C3H/HeJ inbred strains were phenotyped for 21 days. After phenotyping, genotyping with a fully informative single-nucleotide polymorphism panel with an average intermarker interval of 13.7 cM was used. On all three activity indexes, sex and strain were significant factors, with the F(2) animals similar to the high active C57L/J mice in both daily exercise distance and duration of exercise. In the F(2) cohort, female mice ran significantly farther, longer, and faster than male mice. QTL analysis revealed no sex-specific QTL but at the 5% experimentwise significance level did identify one QTL for duration, one QTL for distance, and two QTL for speed. The QTL for duration (DUR13.1) and distance (DIST13.1) colocalized with the QTL for speed (SPD13.1). Each of these QTL accounted for approximately 6% of the phenotypic variance, whereas SPD9.1 (chromosome 9, 7 cM) accounted for 11.3% of the phenotypic variation. DUR13.1, DIST13.1, SPD13.1, and SPD9.1 were subsequently replicated by haplotype association mapping. The results of this study suggest a genetic basis of voluntary activity in mice and provide a foundation for future candidate gene studies.     

Quantitative trait loci for fertility traits in Finnish Ayrshire cattle

A whole genome scan was carried out to detect quantitative trait loci (QTL) for fertility traits in Finnish Ayrshire cattle. The mapping population consisted of 12 bulls and 493 sons. Estimated breeding values for days open, fertility treatments, maternal calf mortality and paternal non-return rate were used as phenotypic data. In a granddaughter design, 171 markers were typed on all 29 bovine autosomes. Associations between markers and traits were analysed by multiple marker regression. Multi-trait analyses were carried out with a variance component based approach for the chromosomes and trait combinations, which were observed significant in the regression method. Twenty-two chromosome-wise significant QTL were detected. Several of the detected QTL areas were overlapping with milk production QTL previously identified in the same population. Multi-trait QTL analyses were carried out to test if these effects were due to a pleiotropic QTL affecting fertility and milk yield traits or to linked QTL causing the effects. This distinction could only be made with confidence on BTA1 where a QTL affecting milk yield is linked to a pleiotropic QTL affecting days open and fertility treatments.