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PubMed2001

Penetrance and expressivity of genes involved in the development of epilepsy in the genetically epilepsy-prone rat (GEPR).

In order to understand the level of complexity of the epileptic phenotype in the two strains of Genetically Epilepsy-Prone Rats (GEPRs), we determined two important measures of genetic complexity, penetrance and expressivity. Penetrance is the percentage of animals of a specific genotype who express the phenotype associated with that underlying genotype. Expressivity refers to the degree that a particular genotype is expressed as a phenotype within an individual. Incomplete penetrance and variable expressivity are caused by genetic and environmental variation. In this paper we have studied the epileptic phenotype for 20,373 rats. Animals were tested on three occasions for audiogenic seizure and given an audiogenic response score (on a scale of 0-9, 0 being no seizure and 9 being the most severe). The GEPR-3 and GEPR-9 animals both show incomplete penetrance and variable expressivity of the underlying genetic predisposition. The GEPR-9 strain has more animals that have variable levels of seizure predisposition (as measured by a scoring system that denotes the severity of generalized tonic/clonic seizures) and a greater percentage of animals that exhibit no susceptibility to such seizures induced by sound. Both strains have a number of animals that are not susceptible to sound-induced GTCSs and that exhibit some variability in seizure severity. The GEPR-9 males show greater differences in expressivity and penetrance compared to GEPR-9 females. The GEPR-3 animals also show sex-associated variable penetrance and expressivity of the epileptic phenotype, although the differences are much smaller. These findings are the first step toward the mapping of the underlying quantitative trait loci (QTL) for seizure in these animals.

Animals↗
PubMed2004

[Stable expression of QTL for grain shape of milled rice (Oryza sativa L. ) using a CSSLs population].

A set of chromosome segment substitution lines (CSSLs), derived from Asominori/IR24 with Asominori as the recurrent parent,was planted and phenotyped for grain length (GL), grain width (GW) and length-width ratio (LWR) of milled rice in two successive years and four sites. QTL for GL,GW and LWR were characterized and stability of their expression was investigated. The phenotypic values for each trait showed a continuous distribution and some transgressive lines were also observed in the CSSLs population. Additionally, a total of 13 QTL for GL, GW and LWR were identified,and six of them were consistently detected in the eight different environments. Phenotypic values were different significantly (P < 0. 001) between the CSSLs harboring any of the six QTL alleles and the genetic background parent, Asominori. Significant phenotypic correlations (r > or = 0.75, r0.05 = 0.67) were detected among different environments for these CSSLs carrying the same target QTL. Also, the results indicated that the six QTL, namely, qGL-3 for GL, qGW-5a and qGW-5b for GW, qLWR-3, qLWR-5a and qLWR-5b for LWR, were stably expressed in different environments. Since QTL qGL-3 and qLWR-3 were mapped in the R19-C1677 interval, qGW-5a and qLWR-5a in the vicinity of RFLP marker C263, qGW-5b and qLWR-5b near R569,the four RFLP markers, R19, C1677, C263 and R569,would be useful for further marker-assisted selection (MAS) in rice quality improvement.

Chromosomes, Plant↗
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↗
PubMed2002

Heart rate and blood pressure quantitative trait loci for the airpuff startle reaction.

The airpuff startle reaction is a probe of sensori-autonomic processing and is useful for studies of genetic control of stress-induced cardiovascular activity. Using a Wistar-Kyoto-Spontaneously Hypertensive Rat F2 cross, we reported an airpuff-elicited strain-dependent and trial-dependent bradycardia, the absence of which cosegregated with hypertension. Here, we use the mapping power of the HXB-BXH recombinant inbred rat strains (n=23) to locate quantitative trait loci (QTL) for this and associated cardiovascular phenotypes. Rats (12 weeks old), with indwelling femoral arterial catheters, were subjected to repeated airpuff startle stimuli (100 ms, 12.5 psi, 28 trials). Basal mean arterial pressure (MAP), delta MAP, and delta heart rate response to airpuff stimuli were analyzed as the average over 28 trials. There was a significant strain effect on the cardiovascular phenotypes measured. One QTL for the bradycardia elicited by the first airpuff stimulus was identified on chromosome 2 (D2rat 62/63; logarithm of odds [LOD] 2.9) mapping near a reported blood pressure locus. Further QTL were identified for basal MAP (RN08), stimulus-elicited tachycardia on trials 2 to 5 (RNO1 and RNO10), and delta MAP (RNO6). Our results indicate that chromosomes 1, 2, and 10 are involved in heart rate responses to airpuff startle stimulus, and chromosomes 6 and 8 are involved in pressor responses. This study is the first to identify stress-related heart rate loci and provides additional support for our prior cosegregation results. Furthermore, we have established the utility of this experimental paradigm to identify loci responsible for cardiovascular regulation during stress in genetic hypertensive models.

Animals↗
PubMed1997

Mapping QTLs for submergence tolerance in rice by AFLP analysis and selective genotyping.

By combining the amplified fragment length polymorphism (AFLP) technique with selective genotyping, we constructed a linkage map for rice and assigned each linkage group to a corresponding chromosome. The AFLP map, consisting of 202 AFLP markers, was generated from 74 recombinant inbred lines (RIL) which were selected from both extremes of the population (250 lines) with respect to the response to complete submergence. Map length was 1756 cM, with an average interval size of 8.5 cM. To assign linkage groups to chromosomes, we used 50 previously mapped AFLP markers as anchor markers distributed over the 12 chromosomes. Other AFLP markers were then assigned to specific chromosomes based on their linkage to anchor markers. This AFLP map is equivalent to the RFLP/AFLP map constructed previously as the anchors were in the same order in both maps. Furthermore, tests with two restriction fragment length polymorphism (RFLP) markers and two sequence-tagged site (STS) markers showed that they mapped in the expected positions. Using this AFLP map, a major gene for submergence tolerance was localized on chromosome 9. Quantitative trait loci (QTL) associated with submergence tolerance were detected on chromosomes 6, 7, 11, and 12. We conclude that the combination of AFLP mapping and selective genotyping provides a much faster and easier approach to QTL identification than the use of RFLP markers.

Chromosome Mapping↗
PubMed2002

A genome scan for quantitative trait loci affecting resistance to Trichostrongylus colubriformis in sheep.

A genome linkage scan was carried out using a resource flock of 1029 sheep in six half-sib families. The families were offspring of sires derived by crossing divergent lines of sheep selected for response to challenge with the intestinal parasitic nematode Trichostrongylus colubriformis. All animals in the resource flock were phenotypically assessed for worm resistance soon after weaning using a vaccination/challenge regime. After correcting for fixed effects using a least squares linear model the faecal egg count data obtained following the first challenge and the faecal egg count data obtained after the second challenge were designated Trait 1 and Trait 2, respectively. A total of 472 lambs drawn from the phenotypic extremes of the Trait 2 faecal egg count distribution were genotyped with a panel of 133 microsatellite markers covering all 26 sheep autosomes. Detection of quantitative trait loci (QTL) for each of the faecal egg count traits was determined using interval analysis with the Animap program with recombination rates between markers derived from an existing marker map. No chromosomal regions attained genome-wide significance for QTL influencing either of the traits. However, one region attained chromosome-wide significance and five other regions attained point-wise significance for the presence of QTL affecting parasite resistance.

Analysis of Variance↗
PubMed2002

Quantitative trait locus mapping of genes that regulate HDL cholesterol in SM/J and NZB/B1NJ inbred mice.

To investigate the quantitative trait loci (QTL) regulating plasma cholesterol, the female progeny of an (SMxNZB/ B1NJ)xNZB/B1NJ backcross were fed an atherogenic diet. After 18 wk, plasma total cholesterol and high-density lipoprotein cholesterol (HDL-C) was measured. HDL-C concentrations were greater in NZB than in SM mice. For standard chow-fed mice, QTL were found near D5Mit370 and D18Mit34. For mice fed an atherogenic diet, a QTL was found near D5Mit239. The QTL for chow-fed and atherogenic-fed mice on chromosome 5 seem to be two different loci. We used a multitrait analysis to rule out pleiotropy in favor of a two-QTL hypothesis. Furthermore, the HDL-C in these strains was induced by the high-fat diet. For inducible HDL-C, one significant locus was found near D15Mit39. The gene for an HDL receptor, Srb1, maps close to the HDL-C QTL at D5Mit370, but the concentrations of Srb1 mRNA and SR-B1 protein and the gene sequence of NZB/B1NJ and SM/J did not support Srb1 as a candidate gene. With these QTL, we have identified chromosomal regions that affect lipoprotein profiles in these strains.

Animals↗
PubMed2004

Quantitative trait loci analysis of nitrate storage in Arabidopsis leading to an investigation of the contribution of the anion channel gene, AtCLC-c, to variation in nitrate levels.

Storage of excess nitrate in the vacuole and its subsequent remobilization is an important aspect of a plant's nitrogen economy, but the genes controlling the underlying processes have not all been identified and characterized. Cape Verdi Island (Cvi)/Landsberg erecta (Ler) and Columbia (Col)/Landsberg erecta recombinant inbred line (RIL) populations of Arabidopsis thaliana were used to identify quantitative trait loci (QTL) controlling natural variation in nitrate concentrations. One major and two minor QTLs were found for the Cvi/Ler population and one minor QTL for the Col/Ler RIL. These were designated NA1 to NA4. The major Cvi/Ler QTL (NA3) was located at the bottom of chromosome 5. No interaction among the QTLs was found by two-way ANOVA. By comparing in silico the locations of the QTLs with a physical map of the Arabidopsis genome, candidate genes for each QTL were identified. Several of these were anion channels of the AtCLC family. One of these, AtCLC-c, coincided with NA3 and its role was investigated using a mutant with a transposon insertion in AtCLC-c. Mutant plants homozygous for the insertion (designated clcc-1) had less than 5% of AtCLC-c mRNA compared with wild-type (WT) shoots. They also had significantly lower nitrate concentrations when grown at a range of external nitrate concentrations. The concentrations of chloride, malate, and citrate were also affected in the mutant. In wild-type plants, expression of AtCLC-c was down-regulated in the presence of nitrate, but ammonium had a much smaller effect while chloride and sulphate did not affect expression. These and published results suggest that multiple genes affect nitrate concentrations in plants and that AtCLC-c and other members of the AtCLC gene family play some role in this.

Amino Acid Sequence↗
PubMed2005

Genetic analysis of anal atresia in pigs: evidence for segregation at two main loci.

Anal atresia is a relatively common congenital malformation that occurs in about 1 out of 5000 infants, caused by abnormal hindgut development of the embryo, often associated with other developmental anomalies (e.g., Currarino, Townes-Brock, Pallister-Hall syndromes, and VATER association). Genetic analysis in human families is exceedingly difficult due to the multifactorial nature of the trait. In pigs, anal atresia occurs at a higher incidence (0.18%) than in humans. A complete genome scan (165 microsatellite markers) was performed using a backcross pedigree previously obtained by crossing affected animals from a partially inbred line, selected for a high incidence of anal atresia, with an unaffected male of a different breed (Meishan). The data set was analyzed with classical linkage (TWOPOINT) and nonparametric genetic methods (NPL, Non-Parametric Linkage, and TDT, Transmission Disequilibrium Test). Both methods support association of the trait with two loci on Chromosomes 9 and 15. GLI2 (GLI-Kruppel family member GLI2) was identified as a positional candidate gene based on comparative mapping; radiation hybrid mapping confirmed that this locus is located within the QTL region.

Animals↗
PubMed2005

SNP detection and genetic mapping of porcine genes encoding enzymes in hepatic metabolic pathways and evaluation of linkage with carcass traits.

We have previously identified and mapped porcine expressed sequence tags (ESTs) derived from genes that are preferentially expressed in liver. The aim of the present study was to identify single nucleotide polymorphisms (SNPs) in porcine genes encoding enzymes in hepatic metabolic pathways and use the SNPs for mapping. Furthermore, these genes, which are involved in utilization and partitioning of nutrients, were examined for their effects on carcass and meat quality traits by linkage analyses. In total, 100 ESTs were screened for SNPs by single strand conformation polymorphism analyses across a diverse panel of animals with a 36% success rate. Twelve of 36 polymorphic loci segregated in a three-generation Duroc x Berlin Miniature Pig (F2) resource population, the DUMI resource population, and were genetically mapped. Interval mapping of the corresponding chromosomes was performed to verify mapping of the genes within quantitative trait loci (QTL) regions detected in this resource population. QTL with genome-wide significance were detected in the vicinity of GNMT, ESTL147 and HGD. These loci therefore are positional candidate genes.

Animals↗
PubMed2002

[Mapping quantitative trait loci for fat deposition in carcass in pigs].

One of the major determining factors in the price of market hogs today is backfat depth. Therefore, identification of regions of the genome affecting this trait is necessary. Gene-mapping technologies have provided scientists the necessary reagents to conduct genomewide searches for genes affecting any phenotype determined in part by the genetic makeup of the animal. Over the past few years, several experimental crosses have been used to detect quantitative triat loci (QTL) for fatness and meat quality traits in pigs. In an intercross between Large White and Meishan pigs, 81 F2 progenies in 1998 were slaughtered and phenotyped for fat deposite traits. F2 animals, their parents, and their grandparents were typed for molecular markers covering chromosomes (SSC) 1,2,3,4,6 and 7, since previous studies had revealed QTL affecting fatness traits on these chromosomes. Linear model and least square analyses were used for mapping these traits. Furthermore, a QTL accounting for imprinting effects was used. A total of 14 QTL at chromosome-wide level were detected on SSC1, 3-4, 6 and 7 for 12 fatness traits. There were evidences for imprinting effects on SSC7 for four traits at 60 cM and nearby. There were QTL for average backfat thickness (BFT) on SSC1, 4 and 7. Among them, BFT QTL on SSC1 and 7 may be the common locus for Sus scrofa. QTL for internal fat percentage was on SSC7 and QTL for average sidefat on SSC6.

Adipose Tissue↗
PubMed2004

Epistasis affecting litter size in mice.

Litter size is an important reproductive trait as it makes a major contribution to fitness. Generally, traits closely related to fitness show low heritability perhaps because of the corrosive effects of directional natural selection on the additive genetic variance. Nonetheless, low heritability does not imply, necessarily, a complete absence of genetic variation because genetic interactions (epistasis and dominance) contribute to variation in traits displaying strong heterosis in crosses, such as litter size. In our study, we investigated the genetic architecture of litter size in 166 females from an F2 intercross of the SM/J and LG/J inbred mouse strains. Litter size had a low heritability (h2 = 12%) and a low repeatability (r = 33%). Using interval-mapping methods, we located two quantitative trait loci (QTL) affecting litter size at locations D7Mit21 + 0 cM and D12Mit6 + 8 cM, on chromosomes 7 and 12 respectively. These QTL accounted for 12.6% of the variance in litter size. In a two-way genome-wide epistasis scan we found eight QTL interacting epistatically involving chromosomes 2, 4, 5, 11, 14, 15 and 18. Taken together, the QTL and their interactions explain nearly 49% (39.5% adjusted multiple r2) of the phenotypic variation for litter size in this cross, an increase of 36% over the direct effects of the QTL. This indicates the importance of epistasis as a component of the genetic architecture of litter size and fitness in our intercross population.

Animals↗
PubMed2004

Quantitative trait loci affecting life span in replicated populations of Drosophila melanogaster. I. Composite interval mapping.

Composite interval mapping was used to identify life-span QTL in F2 progeny of three crosses between different pairs of inbred lines. Each inbred line was derived from a different outbred population that had undergone long-term selection for either long or short life span. Microsatellite loci were used as genetic markers, and confidence intervals for QTL location were estimated by bootstrapping. A minimum of 10 QTL were detected, nine of which were located on the two major autosomes. Five QTL were present in at least two crosses and five were present in both sexes. Observation of the same QTL in more than one cross was consistent with the hypothesis that genetic variation for life span is maintained by balancing selection. For all QTL except one, allelic effects were in the direction predicted on the basis of outbred source population. Alleles that conferred longer life were always at least partially dominant.

Analysis of Variance↗
PubMed2000

Genetic mapping of quantitative trait loci influencing left ventricular mass in rats.

High blood pressure is the leading cause of left ventricular hypertrophy (LVH); however, not all hypertensive patients develop LVH. Genetic factors are important in the development of LVH. With the use of F2 male rats from spontaneously hypertensive rats and Lewis rats, we performed a study to identify the quantitative trait loci (QTL) that influence left ventricular mass (LVM). Mean arterial pressure (MAP) was measured by the direct intra-arterial method in conscious animals, and LVM was determined at 24 wk of age. QTL analysis was done using 160 microsatellite markers for a genome-wide scan. Two loci that influenced body weight-adjusted LVM with logarithm of the odds scores >3.4 were found. One locus on chromosome 17 influenced LVM independently of MAP. Another locus on chromosome 7 influenced LVM and MAP. These findings indicate not only the existence of a gene on chromosome 7 that influences LVM in a manner dependent on blood pressure but also the existence of a gene on chromosome 17 that influences LVM independently of blood pressure.

Animals↗
PubMed2001

Further characterization and high-resolution mapping of quantitative trait loci for ethanol-induced locomotor activity.

Differential sensitivity to the stimulant effects of ethanol on locomotor activity is determined in part by genetic differences. Among inbred strains of mice, moderate doses of ethanol (1-2 g/kg) stimulate locomotor activity in some strains, e.g., the DBA/2J (D2), but only mildly affect activity in other strains, e.g., C57BL/6J (B6) (Crabbe et al., 1982, 1983; Crabbe, 1986; Dudek and Phillips, 1990; Dudek et al., 1991; Dudek and Tritto, 1994). Quantitative trait loci (QTL) for the acute ethanol (1.5 g/kg) locomotor response has been identified in the BXD recombinant inbred (RI) series (N = 25 strains), a C57BL/6J x DBA/2J (B6D2) F2 intercross (N = 1800), and heterogeneous stock (HS) mice (N = 550). QTLs detected (p < .01) in the RI series were found on chromosomes 1, 2, and 6 and these QTLs were expressed in a time-dependent fashion. The QTLs on chromosomes 1 and 2 were confirmed in the F2 intercross at p < 10(-7) or better. HS mice from G32 to G35 were used to fine-map the chromosome 2 QTL. Compared to the consensus map, the genetic map in the HS animals was expanded 10- to 15-fold. Over the region flanked by D2Mit94 to D2Mit304, three separate QTLs were detected in the HS animals. The data obtained confirm the usefulness of HS mice for the fine-mapping of QTLs to a resolution of 2 cM or less.

Animals↗
PubMed2002

Using mouse models to dissect the genetics of obesity.

Mice have proved to be powerful models for understanding obesity in humans and farm animals. Single-gene mutants and genetically modified mice have been used successfully to discover genes and pathways that can regulate body weight. For polygenic obesity, the most common pattern of inheritance, many quantitative trait loci (QTLs) have been mapped in crosses between selected and inbred mouse lines. Most QTL effects are additive, and diet, age and gender modify the genetic effects. Congenic, recombinant inbred, advanced intercross, and chromosome substitution strains are needed to map QTLs finely, to identify the genes underlying the traits, and to examine interactions between them.

Age Factors↗
PubMed2006

QTL analysis of yield traits in an advanced backcross population derived from a cultivated Andean x wild common bean (Phaseolus vulgaris L.) cross.

Advanced backcross QTL analysis was used to identify quantitative trait loci (QTL) for agronomic performance in a population of BC2F(3:5) introgression lines created from the cross of a Colombian large red-seeded commercial cultivar, ICA Cerinza, and a wild common bean accession, G24404. A total of 157 lines were evaluated for phenological traits, plant architecture, seed weight, yield and yield components in replicated trials in three environments in Colombia and genotyped with microsatellite, SCAR, and phaseolin markers that were used to create a genetic map that covered all 11 linkage groups of the common bean genome with markers spaced at an average distance of every 10.4 cM. Segregation distortion was most significant in regions orthologous for a seed coat color locus (R-C) on linkage group b08 and two domestication syndrome genes, one on linkage group b01 at the determinacy (fin) locus and the other on linkage group b02 at the seed-shattering (st) locus. Composite interval mapping analysis identified a total of 41 significant QTL for the eight traits measured of which five for seed weight, two for days to flowering, and one for yield were consistent across two or more environments. QTL were located on every linkage group with b06 showing the greatest number of independent loci. A total of 13 QTL for plant height, yield and yield components along with a single QTL for seed size showed positive alleles from the wild parent while the remaining QTL showed positive alleles from the cultivated parent. Some QTL co-localized with regions that had previously been described to be important for these traits. Compensation was observed between greater pod and seed production and smaller seed size and may have resulted from QTL for these traits being linked or pleiotropic. Although wild beans have been used before to transfer biotic stress resistance traits, this study is the first to attempt to simultaneously obtain a higher yield potential from wild beans and to analyze this trait with single-copy markers. The wild accession was notable for being from a unique center of diversity and for contributing positive alleles for yield and other traits to the introgression lines showing the potential that advanced backcrossing has in common bean improvement.

Chromosome Mapping↗
PubMed1995

QTL analysis of flowering time in Arabidopsis thaliana.

Quantitative trait loci (QTL) analyses based on restriction fragment length polymorphism maps have been used to resolve the genetic control of flowering time in a cross between two Arabidopsis thaliana ecotypes H51 and Landsberg erecta, differing widely in flowering time. Five quantitative trait loci affecting flowering time were identified in this cross (RLN1-5), four of which are located in regions containing mutations or loci previously identified as conferring a late-flowering phenotype. One of these loci is coincident with the FRI locus identified as the major determinant for late flowering and vernalization responsiveness in the Arabidopsis ecotype Stockholm. RLN5, which maps to the lower half of chromosome five (between markers mi69 and m233), only affected flowering time significantly under short day conditions following a vernalization period. The late-flowering phenotype of H51 compared to Landsberg erecta was due to alleles conferring late flowering at only two of the five loci. At the three other loci, H51 possessed alleles conferring early flowering in comparison to those of Landsberg erecta. Combinations of alleles conferring early and late flowering from both parents accounted for the transgressive segregation of flowering time observed within the F2 population. Three QTL, RLN1, RLN2 and RLN3 displayed significant genotype-by-environment interactions for flowering time. A significant interaction between alleles at RLN3 and RLN4 was detected.

Alleles↗