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PubMed2005

Chromosomal mapping of quantitative trait loci controlling elastin content in rat aorta.

Extracellular matrix molecules such as elastin and collagens provide mechanical support to the vessel wall. In addition to its structural role, elastin is a regulator that maintains homeostasis through biologic signaling. Genetically determined minor modifications in elastin and collagen in the aorta could influence the onset and evolution of arterial pathology, such as hypertension and its complications. We previously demonstrated that the inbred Brown Norway (BN) rat shows an aortic elastin deficit in both abdominal and thoracic segments, partly because of a decrease in tropoelastin synthesis when compared with the LOU rat, that elastin gene polymorphisms in these strains do not significantly account for. After a genome-wide search for quantitative trait loci (QTL) influencing the aortic elastin, collagen, and cell protein contents in an F2 population derived from BN and LOU rats, we identified on chromosomes 2 and 14, 3 QTL specifically controlling elastin levels, and a further highly significant QTL on chromosome 17 linked to the level of cell proteins. We also mapped 3 highly significant QTL linked to body weight (on chromosomes 1 and 3) and heart weight (on chromosome 1) in the cross. This study demonstrates the polygenic control of the content of key components of the arterial wall. Such information represents a first step in understanding possible mechanisms involved in dysregulation of these parameters in arterial pathology.

Animals↗
PubMed2004

Mapping of multiple quantitative trait loci affecting bovine spongiform encephalopathy.

A whole-genome scan was conducted to map quantitative trait loci (QTL) for BSE resistance or susceptibility. Cows from four half-sib families were included and 173 microsatellite markers were used to construct a 2835-cM (Kosambi) linkage map covering 29 autosomes and the pseudoautosomal region of the sex chromosome. Interval mapping by linear regression was applied and extended to a multiple-QTL analysis approach that used identified QTL on other chromosomes as cofactors to increase mapping power. In the multiple-QTL analysis, two genome-wide significant QTL (BTA17 and X/Y(ps)) and four genome-wide suggestive QTL (BTA1, 6, 13, and 19) were revealed. The QTL identified here using linkage analysis do not overlap with regions previously identified using TDT analysis. One factor that may explain the disparity between the results is that a more extensive data set was used in the present study. Furthermore, methodological differences between TDT and linkage analyses may affect the power of these approaches.

Animals↗
PubMed2004

Mapping of quantitative trait loci (QTLs) affecting autumn freezing resistance and phenology in Salix.

Quantitative trait locus (QTL) analysis was performed at different time points during cold-acclimation of a tetraploid F(2 ) Salix pedigree. The pedigree ( n=92) was derived from a cross between a frost-susceptible diploid female clone 'Jorunn' ( Salix viminalis) and a frost resistant hexaploid male clone 'SW901290' ( Salix dasyclados). Freezing resistance, height growth increment and number of new leaves were assessed at days 0, 12, 20, 24, 31 and 42 of a short day-low temperature (SD-LT) hardening regime, while the initiation of shoot tip abscission and shoot tip abscission were measured daily. Height increment, dry-to-fresh weight ratio and number of new leaves were also measured in a replicated field trial. Freezing resistance was determined from electrolyte leakage of leaf tissues and from visual injuries on stem segments, after exposure to a predetermined freeze-thaw stress. Using a genetic map of the F(2) composed of 432 single-dose AFLP markers, a total of 19 genomic regions controlling freezing resistance (10) and phenological traits (9) before and during cold-acclimation (SD-LT) were identified. The magnitude of the phenotypic variation explained by each freezing resistance locus varied over acclimation time (0-45%), and there was no time point at which all the QTLs could be detected. The single QTL detected for non-acclimated freezing resistance did not reach significance at any time point during cold-acclimation, suggesting an independent genetic relationship between non-acclimated and acclimated resistance to freezing in Salix. Five of the loci associated with freezing resistance shared common intervals with loci controlling phenological traits. Of the 14 QTLs controlling autumn freezing resistance and/or phenological traits in the indoors experiment, six (43%) were associated with autumn phenology-related traits, i.e. height increment, dry-to-fresh weight ratio and number of new leaves, measured in the field. A major locus with multi-trait association in both indoor and outdoor experiments was detected.

Acclimatization↗
PubMed2004

Genetic mapping of quantitative trait loci affecting body weight, egg character and egg production in F2 intercross chickens.

Phenotypic measurements of chicken egg character and production traits are restricted to mature females only. Marker assisted selection of immature chickens using quantitative trait loci (QTL) has the potential to accelerate the genetic improvement of these traits in the chicken population. The QTL for 12 traits (i.e. body weight (BW), six for egg character, three for egg shell colour and two for egg production) of chickens were identified. An F2 population comprising 265 female chickens obtained by crossing White Leghorn and Rhode Island Red breeds and genotyped for 123 microsatellite markers was used for detecting QTL. Ninety-six markers were mapped on 25 autosomal linkage groups, and 13 markers were mapped on one Z chromosomal linkage group. Eight previous unmapped markers were assigned to their respective chromosomes in this study. Significant QTL were detected for BW on chromosomes 4 and 27, egg weight on chromosome 4, the short length of egg on chromosome 4, and redness of egg shell colour (using the L*a*b* colour system) on chromosome 11. A significant QTL on the Z chromosome was linked with age at first egg. Significant QTL could account for 6-19% of the phenotypic variance in the F2 population.

Analysis of Variance↗
PubMed2003

Mapping of quantitative trait loci controlling trypanotolerance in a cross of tolerant West African N'Dama and susceptible East African Boran cattle.

Trypanosomosis, or sleeping sickness, is a major disease constraint on livestock productivity in sub-Saharan Africa. To identify quantitative trait loci (QTL) controlling resistance to trypanosomosis in cattle, an experimental cross was made between trypanotolerant African N'Dama (Bos taurus) and trypanosusceptible improved Kenya Boran (Bos indicus) cattle. Sixteen phenotypic traits were defined describing anemia, body weight, and parasitemia. One hundred seventy-seven F2 animals and their parents and grandparents were genotyped at 477 molecular marker loci covering all 29 cattle autosomes. Total genome coverage was 82%. Putative QTL were mapped to 18 autosomes at a genomewise false discovery rate of <0.20. The results are consistent with a single QTL on 17 chromosomes and two QTL on BTA16. Individual QTL effects ranged from approximately 6% to 20% of the phenotypic variance of the trait. Excluding chromosomes with ambiguous or nontrypanotolerance effects, the allele for resistance to trypanosomosis originated from the N'Dama parent at nine QTL and from the Kenya Boran at five QTL, and at four QTL there is evidence of an overdominant mode of inheritance. These results suggest that selection for trypanotolerance within an F2 cross between N'Dama and Boran cattle could produce a synthetic breed with higher trypanotolerance levels than currently exist in the parental breeds.

Anemia↗
PubMed2003

WebQTL: web-based complex trait analysis.

WebQTL is a website that combines databases of complex traits with fast software for mapping quantitative trait loci (QTLs) and for searching for correlations among traits. WebQTL also includes well-curated genotype data for five sets of mouse recombinant inbred (RI) lines. Thus, to identify QTLs, users need provide only quantitative trait data from one of the supported populations. The WebQTL databases include both biological traits--neuroanatomical, pharmacological, and behavioral traits--and microarray-based gene expression data from BXD RI lines. A search function finds correlations between RNA expression and biological traits, and mapping functions find QTLs for either type of trait. The WebQTL service is available at http://www.webqtl.org/.

Animals↗
PubMed2000

Mapping of quantitative trait loci (QTL) of differential stress gene expression in rat recombinant inbred strains.

OBJECTIVE: Stress has been shown to be a major environmental contributor to cardiovascular diseases through its effects on blood pressure variability and cardiac function. The cellular stress response is characterized by the expression of specific heat stress genes (hsps), under the transcriptional control of heat shock transcription factors (HSTFs). The levels of hsp mRNA depend on the severity of the stress, with hstf1 acting as a stress sensor. The aim of this work was to evaluate the genetic contribution of the variability in hsp expression, and to identify its putative quantitative trait loci (QTL). METHODS: Twenty recombinant inbred rat strains (RIS) were studied. The animals underwent a standardized, identical 1 h immobilization stress in restraint cages, followed by 1 h of rest before sacrifice. Total RNA was extracted from the heart kidneys and adrenals, and the mRNA levels of hsp27, hsp70, hsp84, hsp86 and hsp105 were measured. The strain distribution pattern (SDP) of hsp expression was correlated with that of 475 polymorphic markers distributed throughout the RIS genome. A polymorphism of rat hstf1 in RIS was used for its mapping in RIS. RESULTS: Despite an identical stress being applied to all strains, hsp expression showed up to a 1 2-fold gradient with little intra-strain variability, indicative of a strong genetic contribution to the trait Heritability ranged from 50 to 77% for most hsp genes in the three target organs. The continuous SDP of stress gene expression indicated the polygenic nature of the trait A common locus on chromosome 7 (at D7Cebrp187s3 marker) was consistently associated with all hsp expression in most of the organs [with a likelihood of odds (LOD) score of 3.0 for hsp27 expression]. We have mapped rat hstf1 on chromosome 7 at the same locus. Finally, the D4Mit19 marker was significantly associated with hsp84 expression in the heart (LOD score of 3.1). CONCLUSION: Two loci were linked with the differential expression of HSPs in response to immobilization stress in target organs of RIS. The chromosome 7 locus unveiled for all HSPs could explain up to 42% of the observed inter-strain variability of hsp levels in response to stress. We propose hstf1 as a positional candidate at this locus.

Adrenal Glands↗
PubMed2006

Association mapping of complex trait loci with context-dependent effects and unknown context variable.

A novel method for Bayesian analysis of genetic heterogeneity and multilocus association in random population samples is presented. The method is valid for quantitative and binary traits as well as for multiallelic markers. In the method, individuals are stochastically assigned into two etiological groups that can have both their own, and possibly different, subsets of trait-associated (disease-predisposing) loci or alleles. The method is favorable especially in situations when etiological models are stratified by the factors that are unknown or went unmeasured, that is, if genetic heterogeneity is due to, for example, unknown genes x environment or genes x gene interactions. Additionally, a heterogeneity structure for the phenotype does not need to follow the structure of the general population; it can have a distinct selection history. The performance of the method is illustrated with simulated example of genes x environment interaction (quantitative trait with loosely linked markers) and compared to the results of single-group analysis in the presence of missing data. Additionally, example analyses with previously analyzed cystic fibrosis and type 2 diabetes data sets (binary traits with closely linked markers) are presented. The implementation (written in WinBUGS) is freely available for research purposes from http://www.rni.helsinki.fi/ approximately mjs/.

Alleles↗
PubMed2001

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.

Animals↗
PubMed2005

Time-related mapping of quantitative trait loci controlling grain-filling in rice (Oryza sativa L.).

Grain-filling is a crucial process that determines final grain yield in rice (Oryza sativa L.). To understand the genetic basis of dynamics of grain-filling, quantitative trait locus (QTL) analysis was conducted using time-related phenotypic data on grain-filling collected from a population of 155 recombinant inbred lines (F12), derived from a cross between Milyang 23 and Akihikari. Two QTLs detected on chromosomes 8 and 12 were strongly associated with increased filling percentage per panicle. These QTLs were not linked with those controlling spikelet numbers per panicle. This result confers the possibility of improving grain-filling together with an enlargement of sink size. The QTL for filling percentage per panicle on chromosome 8 exactly overlapped that for non-structural carbohydrate (NSC) content in the culm and leaf sheaths during grain-filling, and the Milyang 23 allele associated with increased grain-filling percentage per panicle was associated with decreased NSC content. Therefore, this QTL may be directly involved in NSC translocation from the culm and leaf sheaths to panicle. In addition, the Milyang 23 alleles of QTLs associated with greater spikelet number per panicle on chromosomes 1 and 6 were also related with a reduction in NSC content in the culm and leaf sheaths during grain-filling. These results indicate that NSC dynamics during grain-filling is partly dependent on sink size. NSC accumulation in the culm and leaf sheaths at the heading stage was mainly controlled by different genetic regulations from NSC dynamics during grain-filling. Nitrogen dynamics during grain-filling may also be involved in carbohydrate dynamics.

Chromosome Mapping↗
PubMed2002

Mapping epigenetic quantitative trait loci (QTL) altering a developmental trajectory.

Genetic variation in a quantitative trait that changes with age is important to both evolutionary biologists and breeders. A traditional analysis of the dynamics of genetic variation is based on the genetic variance-covariance matrix among different ages estimated from a quantitative genetic model. Such an analysis, however, cannot reveal the mechanistic basis of the genetic variation for a growth trait during ontogeny. Age-specific genetic variance at time t conditional on the causal genetic effect at time t - 1 implies the generation of episodes of new genetic variation arising during the interval t - 1 to t. In the present paper, the conditional genetic variance estimated from Zhu's (1995) conditional model was partitioned into its underlying individual quantitative trait loci (QTL) using molecular markers in an F2 progeny of poplars (Populus trichocarpa and Populus deltoides). These QTL, defined as epigenetic QTL, govern the alterations of growth trajectory in a population. Three epigenetic QTL were detected to contribute significantly to variation in growth trajectory during the period from the establishment year to the subsequent year in the field. It is suggested that the activation and expression of epigenetic QTL are influenced by the developmental status of trees and the environment in which they are grown.

Analysis of Variance↗
PubMed2003

Fine mapping a quantitative trait locus affecting ovulation rate in swine on chromosome 8.

Ovulation rate is an integral component of litter size in swine, but is difficult to directly select for in commercial swine production. Because a QTL has been detected for ovulation rate at the terminal end of chromosome 8p, genetic markers for this QTL would enable direct selection for ovulation rate in both males and females. Eleven genes from human chromosome 4p16-p15, as well as one physiological candidate gene, were genetically mapped in the pig. Large insert swine genomic libraries were screened, clones were isolated and then screened for microsatellite repeats, and informative microsatellite markers were developed for seven genes (GNRHR, IDUA, MAN2B2, MSX1, PDE6B, PPP2R2C, and RGS12). Three genes (LRPAP1, GPRK2L, and FLJ20425) were mapped using genotyping assays developed from single nucleotide polymorphisms. Two genes were assigned since they were present in clones that contained mapped markers (HGFAC and HMX1). The resulting linkage map of pig chromosome 8 contains markers associated with 14 genes in the first 27 cM. One inversion spanning at least 3 Mb in the human genome was detected; all other differences could be explained by resolution of mapping techniques used. Fourteen of the most informative microsatellite markers in the first 27 cM of the map were genotyped across the entire MARC swine resource population, increasing the number of markers typed from 2 to 14 and more than doubling the number ofgenotyped animals with ovulation rate data (295 to 600). Results from the revised data set for the QTL analysis, assuming breed specific QTL alleles, indicated that the most likely position of the QTL resided at 4.85 cM on the new linkage map (F1,592 = 20.5150, genome-wide probability less than 0.015). The updated estimate of the effect of an allele substitution was -1.65 ova for the Meishan allele. The F-ratio peak was closest to markers for MAN2B2 (4.80 cM) and was flanked on the other side by markers for PPP2R2C. Two positional candidate genes included in this study are MAN2B2 and RGS12. These results validate the presence of a QTL affecting ovulation rate on chromosome 8 and facilitate selection of positional candidate genes to be evaluated.

Animals↗
PubMed2003

Mapping of quantitative trait loci associated with ultraviolet-B resistance in rice (Oryza sativa L.).

The detection of quantitative trait loci (QTLs) associated with UV-B resistance in rice should allow their practical application in breeding for such a complex trait, and may lead to the identification of gene characteristics and functions. Considerable variation in UV-B resistance exists within cultivated rice (Oryza sativa L.), but its detailed genetic control mechanism has not been well elucidated. We detected putative QTLs associated with the resistance to enhanced UV-B radiation in rice, using 98 BC(1)F(5) (backcross inbred lines; BILs) derived from a cross between Nipponbare (a resistant japonica rice variety) and Kasalath (a sensitive indica rice variety). We used 245 RFLP markers to construct a framework linkage map. BILs and both parents were grown under visible light with or without supplemental UV-B radiation in a growth chamber. In order to evaluate UV-B resistance, we used the relative fresh weight of aerial parts (RFW) and the relative chlorophyll content of leaf blades (RCC). The BIL population exhibited a wide range of variation in RFW and RCC. Using composite interval mapping with a LOD threshold of 2.9, three putative QTLs associated with both RFW and RCC were detected on chromosomes 1, 3 and 10. Nipponbare alleles at the QTLs on chromosome 1 and 10 increased the RFW and RCC, while the Kasalath allele at the QTL on chromosome 3 increased both traits. Furthermore, the existence of both QTLs on chromosomes 1 and 10 for UV-B resistance was confirmed using chromosome segment substitution lines. Plants with Kasalath alleles at the QTL on chromosome 10 were more sensitive to UV-B radiation than plants with them on chromosome 1. These results also provide the information not only for the improvement of UV-B resistance in rice though marker-associated selection, but also for the identification of UV-B resistance mechanisms by using near-isogenic lines.

Chromosome Mapping↗
PubMed2002

Mapping of quantitative trait loci underlying ethanol metabolism in BXD recombinant inbred mouse strains.

BACKGROUND: Genetic factors are well known to play an important role in determining individual differences in the metabolism of ethanol (EtOH), and several specific polymorphic loci have been identified that significantly contribute to the variability of EtOH metabolism in humans. However, these variant genes are either alcohol or aldehyde dehydrogenases, and the identification of new gene products that contribute to variation in alcohol metabolism would be useful. METHODS: To identify quantitative trait loci (QTLs), we correlated variation in polymorphic markers with blood EtOH concentration and the rate of EtOH metabolism (beta) in C57BL/6J and DBA/2J strains and in 25 of their recombinant inbred strains after 2 and 3 g/kg of EtOH intraperitoneally. RESULTS: A QTL associated with beta values for both doses was definitively mapped to the proximal region of chromosome 17, syntenic with human chromosome 6q25-27. Seven to 12 chromosomal regions were provisionally identified for each phenotype; several were associated with 2 or more phenotypes. Each QTL suggests the location of a gene or genes affecting EtOH pharmacokinetics. Candidate genes suggested by these analyses included several whose gene products are known to be induced by EtOH (e.g., superoxide dismutase, glutathione transferase, and cytochrome P450 2E1), as well as several whose gene products have signaling functions likely to contribute to this induction. CONCLUSIONS: These studies provide evidence for the existence of genes affecting EtOH metabolism in multiple chromosomal regions. Future studies will be required to identify the chromosome 17 gene product. Use of other genetic populations, such as B6D2F2 crosses, will be required to determine which of the provisional loci represent true and which represent false-positive associations.

Animals↗
PubMed2005

Further mapping of quantitative trait loci for postnatal growth in an inter-sub-specific backcross of wild Mus musculus castaneus and C57BL/6J mice.

We performed a quantitative trait locus (QTL) analysis of eight body weights recorded weekly from 3 weeks to 10 weeks after birth and two weight gains recorded between 3 weeks and 6 weeks, and between 6 weeks and 10 weeks in an inter-sub-specific backcross population of wild Mus musculus castaneus mice captured in the Philippines and the common inbred strain C57BL/6J ( M. musculus domesticus ), to elucidate the complex genetic architecture of body weight and growth. Interval mapping identified 17 significant QTLs with main effects on 11 chromosomes. In particular, the main effect of the most potent QTL on proximal chromosome 2 increased linearly with age, whereas other QTLs exerted effects on either the early or late growth period. Surprisingly, although wild mice displayed 60% of the body size of their C57BL/6J counterparts, the wild-derived allele enhanced growth at two QTLs. Interestingly, five of the 17 main-effect QTLs identified had significant epistatic interaction effects. Five new epistatic QTLs with no main effects were identified on different chromosomes or regions. For one pair of epistatic QTLs, mice that were heterozygous for the wild-derived allele at one QTL and homozygous for that allele at another QTL exhibited the most rapid growth in all four possible genotypic combinations. Out of the identified QTLs, several showed significant sex-specific effects.

Animals↗
PubMed1998

Genetic mapping of quantitative trait loci affecting susceptibility to Marek's disease virus induced tumors in F2 intercross chickens.

Marek's disease (MD) is a lymphoproliferative disease caused by the MD virus (MDV), which costs the poultry industry nearly $1 billion annually. To identify quantitative trait loci (QTL) affecting MD susceptibility, the inbred lines 6(3) (MD resistant) and 7(2) (MD susceptible) were mated to create more than 300 F2 chickens. The F2 chickens were challenged with MDV JM strain, moderately virulent) at 1 wk of age and assessed for MD susceptibility. The QTL analysis was divided into three stages. In stage 1, 65 DNA markers selected from the chicken genetic maps were typed on the 40 most MD-susceptible and the 40 most MD-resistant F2 chickens, and 21 markers residing near suggestive QTL were revealed by analysis of variance (ANOVA). In stage 2, the suggestive markers plus available flanking markers were typed on 272 F2 chickens, and three suggestive QTL were identified by ANOVA. In stage 3, using the interval mapping program Map Manager and permutation tests, two significant and two suggestive MD QTL were identified on four chromosomal subregions. Three to five loci collected explained between 11 and 23% of the phenotypic MD variation, or 32-68% of the genetic variance. This study constitutes the first report in the domestic chicken on the mapping of non-major histocompatibility complex QTL affecting MD susceptibility.

Analysis of Variance↗
PubMed2006

Mapping of quantitative trait loci for salt tolerance at the seedling stage in rice.

Salt tolerance was evaluated at the young seedling stage of rice (Oryza sativa L.) using recombinant inbred lines (MG RILs) from a cross between Milyang 23 (japonica/indica) and Gihobyeo (japonica). 22 of 164 MG RILs were classified as tolerant with visual scores of 3.5-5.0 in 0.7% NaCl. Interval mapping of QTLs related to salt tolerance was conducted on the basis of the visual scores at the young seedling stage. Two QTLs, qST1 and qST3, conferring salt tolerance, were detected on chromosome 1 and 3, respectively, and the total phenotypic variance explained by the two QTLs was 36.9% in the MG RIL population. qST1 was the major QTL explaining 27.8% of the total phenotypic variation. qST1 was flanked by Est12-RZ569A, and qST3 was flanked by RG179-RZ596. The detection of new QTLs associated with salt tolerance will provide important information for the functional analysis of rice salt tolerance.

Genotype↗
PubMed1998

Provisional mapping of quantitative trait loci for chronic ethanol withdrawal severity in BXD recombinant inbred mice.

Male mice from C57BL/6J (B6), DBA/2J (D2) and their 25 recombinant inbred (RI) strains were exposed to ethanol (EtOH) vapor (3.0-9.0 mg EtOH/liter of air) for 72 hr. Mice were selected such that each strain averaged 1.34 to 1.59 mg of EtOH/ml of blood on withdrawal. Control groups and EtOH-exposed groups were tested hourly for handling-induced convulsions (HIC) for 10 hr and at hr 24 and 25. Strain withdrawal severity was indexed as the area under the 25-hr HIC curve for the EtOH group minus that strain's equivalent value for the control group. Genome-wide quantitative trait locus (QTL) analyses correlating strain means with allelic status at > 1500 markers identified 10 chromosomal regions at P < .01. These provisionally identified QTLs were on chromosomes 1 (2 QTLs), 3, 9 (2 QTLs), 10, 12, 13, 15 and 18. Multiple regression analysis using the four most influential QTLs revealed that these loci controlled 86% of the genetic variance. A QTL mapped to distal chromosome 1 (P < .001) is in the same region as one previously definitively mapped for acute alcohol withdrawal, as well as one mapped for acute pentobarbital withdrawal. Several of the QTLs map near potential candidate genes. These provisional linkages will now be confirmed or rejected using additional genetically segregating populations.

Animals↗