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PubMed2000

Quantitative trait locus analysis.

Alcoholism is a quantitative disorder that is caused by the combined influences of numerous genes (i.e., quantitative trait loci [QTLs]) and environmental factors. To identify QTLs for alcoholism, researchers compare subject groups (e.g., inbred mouse strains) that differ in both their genetic makeup (i.e., genotype) and alcohol-related trait (e.g., sensitivity to certain alcohol effects). Using statistical tests one can then determine whether a specific gene or DNA region contributes to the trait of interest. This strategy requires that the relevant gene exists in several variants (i.e., is polymorphic). To conduct such QTL analyses, researchers study either a large population of mice that all differ in their genotypes or compare several strains, each of which has a fixed genotype. However, QTL analyses still have several limitations. Nevertheless, such studies already have identified several DNA regions and genes that may affect the response to alcohol and thus may contribute to the risk for alcoholism.

Alcoholism↗
PubMed2006

Results of a whole-genome quantitative trait locus scan for growth, carcass composition and meat quality in a porcine four-way cross.

A whole-genome quantitative trait locus (QTL) scan for 31 phenotypes related to growth, carcass composition and meat quality was conducted using 1187 progeny of a commercial four-way cross. Animals were genotyped for 198 microsatellite markers that spanned the entire porcine genome. QTL analysis was conducted to extract information from paternal and maternal meioses separately using a rank-based nonparametric approach for half-sib designs. Nine QTL exceeded genome-wide significance: one QTL affecting growth (average daily gain on SSC1), two QTL influencing carcass composition (fatness on SSC3 and muscle mass on SSC15) and six QTL influencing meat quality (tenderness on SSC4 and SSC14; colour on SSC5, SSC6 and SSCX; and conductivity on SSC16). All but one of these coincided with previously reported QTL. In addition, we present evidence for 78 suggestive QTL with a combined false discovery rate of 40%.

Animals↗
PubMed2006

Fine mapping of a grain weight quantitative trait locus on rice chromosome 8 using near-isogenic lines derived from a cross between Oryza sativa and Oryza rufipogon.

A quantitative trait locus (QTL) for grain weight (GW) was detected near SSR marker RM210 on chromosome 8 in backcross populations derived from a cross between the Korean japonica cultivar Hwaseongbyeo and Oryza rufipogon (IRGC 105491). The O. rufipogon allele increased GW in the Hwaseongbyeo background despite the fact that O. rufipogon was the small-seeded parent. Using sister BC(3)F(3) near-isogenic lines (NILs), gw8.1 was validated and mapped to a 6.1 cM region in the interval between RM42 and RM210 (P < or = 0.0001). Substitution mapping with eight BC(3)F(4) sub-NILs further narrowed the interval containing gw8.1 to about 306.4 kb between markers RM23201.CNR151 and RM30000.CNR99. A yield trial using homozygous BC(3)F(4) sister sub-NILs and the Hwaseongbyeo recurrent parent indicated that the NIL carrying an O. rufipogon chromosome segment across the entire gw8.1 target region out-yielded its sister NIL (containing Hwaseongbyeo chromosome in the RM42-RM210 interval) by 9% (P=0.029). The higher-yielding NIL produced 19.3% more grain than the Hwaseongbyeo recurrent parent (P=0.018). Analysis of a BC(3)F(4) NIL indicated that the variation for GW is associated with variation in grain shape, specifically grain length. The locus, gw8.1 is of particular interest because of its independence from undesirable height and grain quality traits. SSR markers tightly linked to the GW QTL will facilitate cloning of the gene underlying this QTL as well as marker-assisted selection for variation in GW in an applied breeding program.

Chromosome Mapping↗
PubMed1999

A simulation study of the effects of assignment of prior identity-by-descent probabilities to unselected sib pairs, in covariance-structure modeling of a quantitative-trait locus.

Sib pair-selection strategies, designed to identify the most informative sib pairs in order to detect a quantitative-trait locus (QTL), give rise to a missing-data problem in genetic covariance-structure modeling of QTL effects. After selection, phenotypic data are available for all sibs, but marker data-and, consequently, the identity-by-descent (IBD) probabilities-are available only in selected sib pairs. One possible solution to this missing-data problem is to assign prior IBD probabilities (i.e., expected values) to the unselected sib pairs. The effect of this assignment in genetic covariance-structure modeling is investigated in the present paper. Two maximum-likelihood approaches to estimation are considered, the pi-hat approach and the IBD-mixture approach. In the simulations, sample size, selection criteria, QTL-increaser allele frequency, and gene action are manipulated. The results indicate that the assignment of prior IBD probabilities results in serious estimation bias in the pi-hat approach. Bias is also present in the IBD-mixture approach, although here the bias is generally much smaller. The null distribution of the log-likelihood ratio (i.e., in absence of any QTL effect) does not follow the expected null distribution in the pi-hat approach after selection. In the IBD-mixture approach, the null distribution does agree with expectation.

Alleles↗
PubMed1991

Maximum likelihood estimation of linkage between a marker gene and a quantitative trait locus. II. Application to backcross and doubled haploid populations.

The algorithm for estimating both the recombination fraction between a marker gene and a locus affecting a quantitative trait, and also the means and variances of the QTL genotypes, is extended to backcross and doubled haploid populations. The simulation experiments show that estimates of these parameters can be obtained with acceptable accuracy and results are compared with those obtained using F2 populations studied previously (Luo & Kearsey, 1989).

Algorithms↗
PubMed2001

Trans-ethnic fine mapping of a quantitative trait locus for circulating angiotensin I-converting enzyme (ACE).

Circulating angiotensin I-converting enzyme (ACE) levels are influenced by a major quantitative trait locus (QTL) that maps to the ACE gene. Phylogenetic and measured haplotype analyses have suggested that the ACE-linked QTL lies downstream of a putative ancestral breakpoint located near to position 6435. However, strong linkage disequilibrium between markers in the 3' portion of the gene has prevented further resolution of the QTL in Caucasian subjects. We have examined 10 ACE gene polymorphisms in Afro-Caribbean families recruited in JAMAICA: Variance components analyses showed strong evidence of linkage and association to circulating ACE levels. When the linkage results were contrasted with those from a set of British Caucasian families, there was no evidence for heterogeneity between the samples. However, patterns of allelic association between the markers and circulating ACE levels differed significantly in the two data sets. In the British families, three markers [G2215A, Alu insertion/deletion and G2350A] were in complete disequilibrium with the ACE-linked QTL. In the Jamaican families, only marker G2350A showed strong but incomplete disequilibrium with the ACE-linked QTL. These results suggest that additional unobserved polymorphisms have an effect on circulating ACE levels in Jamaican families. Furthermore, our results show that a variance components approach combined with structured, quantitative comparisons between families from different ethnic groups may be a useful strategy for helping to determine which, if any, variants in a small genomic region directly influence a quantitative trait.

Black People↗
PubMed1999

Disequilibrium mapping of a quantitative-trait locus in an expanding population.

Linkage disequilibrium (LD) mapping can be successful if there is strong nonrandom association between marker alleles and an allele affecting a trait of interest. The principles of LD mapping of dichotomous traits are well understood, but less is known about LD mapping of a quantitative-trait locus (QTL). It is shown in this report that selective genotyping can increase the power to detect and map a rare allele of large effect at a QTL. Two statistical tests of the association between an allele and a quantitative character are proposed. These tests are approximately independent, so information from them can be combined. Analytic theory is developed to show that these two tests are effective in detecting the presence of a low-frequency allele with a relatively large effect on the character when the QTL is either already a candidate locus or closely linked to a marker locus that is in strong LD with the QTL. The latter situation is expected in a rapidly growing population in which the allele of large effect was present initially in one copy. Therefore, the proposed tests are useful under the same conditions as those for successful LD mapping of a dichotomous trait or disease. Simulations show that, for detection of the presence of a QTL, these tests are more powerful than a simple t-test. The tests also provide a basis for defining a measure of association, gamma, between a low-frequency allele at a putative QTL and a low-frequency allele at a marker locus.

Genetics, Population↗
PubMed1998

Successful isolation of a rat chromosome 1 blood pressure quantitative trait locus in reciprocal congenic strains.

Linkage analyses in experimental crosses of hypertensive and normotensive rats have strongly suggested the presence of a quantitative trait locus (QTL) influencing blood pressure on rat chromosome 1, at or near the Sa gene. To confirm the presence of such a locus and move toward identification of the causative gene, we have developed, through targeted breeding over 10 generations using an Sa gene polymorphism to select breeders at each generation, 2 congenic strains, 1 containing a segment of spontaneously hypertensive rat (SHR) chromosome 1 in a Wistar-Kyoto rat (WKY) genetic background (WKY.SHR-Sa), and the other a segment of WKY chromosome 1 in an SHR background (SHR.WKY-Sa). WKY.SHR-Sa contains at least approximately 26 cM of SHR chromosome 1, between markers mD7mit206 and D1Mit2 (and including the SHR allele of the Sa gene), and SHR.WKY-Sa carries at least approximately 15 cM of WKY chromosome 1, between mD7mit206 and D1Wox34 (and including the WKY allele of the Sa gene). Blood pressure of WKY.SHR-Sa rats measured at 16, 20, and 25 weeks of age was significantly higher than that of WKY, whereas blood pressure of SHR.WKY-Sa rats was significantly lower than that of SHR. At 25 weeks, the mean differences in systolic and diastolic blood pressure between WKY.SHR-Sa and WKY were +11.5 mm Hg (P=0.001) and +11.6 mm Hg mm Hg (P<0.001), respectively. The corresponding differences between SHR.WKy-Sa and SHR were -11.3 mm Hg (P=0.002) and -9.1 mm Hg (P=0.005), respectively. The differences represent about one fifth of the blood pressure difference between SHR and WKY. Renal Sa mRNA levels in the congenic strains reflected their Sa allele with a high level in WKY. SHR-Sa and a low level in SHR.WKY-Sa, consistent with previous data suggesting that the level of Sa expression is primarily determined by cis-acting elements in or near the Sa gene. Our results show that we have successfully isolated a major rat chromosome 1 blood pressure QTL located in the vicinity of the Sa gene in reciprocal congenic strains derived from SHR and WKY. The strains can now be used to further define the region containing the QTL and also to characterize intermediary mechanisms through which the QTL influences blood pressure. In addition, comparison of the regions introgressed in our congenic strains with the location of the peak LOD score for chromosome 1 blood pressure QTL in second filial generation progeny derived from our SHRxWKY cross suggests that there may be at least 1 further QTL influencing blood pressure on this rat chromosome.

Animals↗
PubMed2001

Consequences of recombination rate variation on quantitative trait locus mapping studies. Simulations based on the Drosophila melanogaster genome.

We examine the effect of variation in gene density per centimorgan on quantitative trait locus (QTL) mapping studies using data from the Drosophila melanogaster genome project and documented regional rates of recombination. There is tremendous variation in gene density per centimorgan across this genome, and we observe that this variation can cause systematic biases in QTL mapping studies. Specifically, in our simulated mapping experiments of 50 equal-effect QTL distributed randomly across the physical genome, very strong QTL are consistently detected near the centromeres of the two major autosomes, and few or no QTL are often detected on the X chromosome. This pattern persisted with varying heritability, marker density, QTL effect sizes, and transgressive segregation. Our results are consistent with empirical data collected from QTL mapping studies of this species and its close relatives, and they explain the "small X-effect" that has been documented in genetic studies of sexual isolation in the D. melanogaster group. Because of the biases resulting from recombination rate variation, results of QTL mapping studies should be taken as hypotheses to be tested by additional genetic methods, particularly in species for which detailed genetic and physical genome maps are not available.

Animals↗
PubMed2002

Dissecting the architecture of a quantitative trait locus in yeast.

Most phenotypic diversity in natural populations is characterized by differences in degree rather than in kind. Identification of the actual genes underlying these quantitative traits has proved difficult. As a result, little is known about their genetic architecture. The failures are thought to be due to the different contributions of many underlying genes to the phenotype and the ability of different combinations of genes and environmental factors to produce similar phenotypes. This study combined genome-wide mapping and a new genetic technique named reciprocal-hemizygosity analysis to achieve the complete dissection of a quantitative trait locus (QTL) in Saccharomyces cerevisiae. A QTL architecture was uncovered that was more complex than expected. Functional linkages both in cis and in trans were found between three tightly linked quantitative trait genes that are neither necessary nor sufficient in isolation. This arrangement of alleles explains heterosis (hybrid vigour), the increased fitness of the heterozygote compared with homozygotes. It also demonstrates a deficiency in current approaches to QTL dissection with implications extending to traits in other organisms, including human genetic diseases.

Alleles↗
PubMed2006

Characterization of Cq3, a quantitative trait locus that controls plasma cholesterol and phospholipid levels in mice.

Cq3 was identified in C57BL/6J (B6) x KK-Ay F2 mice as a quantitative trait locus (QTL) that controls plasma cholesterol and phospholipid levels, and normolipidemic B6 allele was associated with increased lipids. Cq3 was statistically significant in F2-a/a, but not in F2-Ay/a; probably because the Cq3 effect was obscured by introduction of the Ay allele, which in itself has a strong hyperlipidemic effect. Because the peak LOD score for Cq3 was identified near D3Mit102 (49.7 cM) on chromosome 3, linkage analyses with microsatellite markers located at 49.7 cM were performed in KK x RR F2, B6 x RR F2, and KK x CF1 F2. However, even a suggestive QTL was not identified in any of the three F2. By testing all pairs of marker loci, I found a significant interaction between Cq3 and the Apoa2 locus, and F2 mice with the Apoa2(KK)/Apoa2(KK); D3Mit102(B6)/D3Mit102(B6) genotype had significantly higher cholesterol levels than did F2 mice with other genotypes. The results showed that the ;round-robin' strategy was not always applicable to the search for QTL genes; probably because specific gene-to-gene interaction limited the validity of the strategy to the utmost extent.

Alleles↗
PubMed1999

A quantitative-trait locus on chromosome 6p influences different aspects of developmental dyslexia.

Recent application of nonparametric-linkage analysis to reading disability has implicated a putative quantitative-trait locus (QTL) on the short arm of chromosome 6. In the present study, we use QTL methods to evaluate linkage to the 6p25-21.3 region in a sample of 181 sib pairs from 82 nuclear families that were selected on the basis of a dyslexic proband. We have assessed linkage directly for several quantitative measures that should correlate with different components of the phenotype, rather than using a single composite measure or employing categorical definitions of subtypes. Our measures include the traditional IQ/reading discrepancy score, as well as tests of word recognition, irregular-word reading, and nonword reading. Pointwise analysis by means of sib-pair trait differences suggests the presence, in 6p21.3, of a QTL influencing multiple components of dyslexia, in particular the reading of irregular words (P=.0016) and nonwords (P=.0024). A complementary statistical approach involving estimation of variance components supports these findings (irregular words, P=.007; nonwords, P=.0004). Multipoint analyses place the QTL within the D6S422-D6S291 interval, with a peak around markers D6S276 and D6S105 consistently identified by approaches based on trait differences (irregular words, P=.00035; nonwords, P=.0035) and variance components (irregular words, P=.007; nonwords, P=.0038). Our findings indicate that the QTL affects both phonological and orthographic skills and is not specific to phoneme awareness, as has been previously suggested. Further studies will be necessary to obtain a more precise localization of this QTL, which may lead to the isolation of one of the genes involved in developmental dyslexia.

Adolescent↗
PubMed2000

fw2.2: a quantitative trait locus key to the evolution of tomato fruit size.

Domestication of many plants has correlated with dramatic increases in fruit size. In tomato, one quantitative trait locus (QTL), fw2.2, was responsible for a large step in this process. When transformed into large-fruited cultivars, a cosmid derived from the fw2.2 region of a small-fruited wild species reduced fruit size by the predicted amount and had the gene action expected for fw2.2. The cause of the QTL effect is a single gene, ORFX, that is expressed early in floral development, controls carpel cell number, and has a sequence suggesting structural similarity to the human oncogene c-H-ras p21. Alterations in fruit size, imparted by fw2.2 alleles, are most likely due to changes in regulation rather than in the sequence and structure of the encoded protein.

Alleles↗
PubMed1998

Quantitative trait locus mapping in dairy cattle by means of selective milk DNA pooling using dinucleotide microsatellite markers: analysis of milk protein percentage.

"Selective DNA pooling" accomplishes quantitative trait locus (QTL) mapping through densitometric estimates of marker allele frequencies in pooled DNA samples of phenotypically extreme individuals. With poly(TG) microsatellites, such estimates are confounded by "shadow" ("stutter") bands. A correction procedure was developed on the basis of an observed linear regression between shadow band intensity and allele TG repeat number. Using this procedure, a selective DNA pooling study with respect to milk protein percentage was implemented in Israel-Holstein dairy cattle. Pools were prepared from milk samples of high and low daughters of each of seven sires and genotyped with respect to 11 markers. Highly significant associations with milk protein percentage were found for 5 of the markers; 4 of these markers confirmed previous reports. Selective DNA pooling accessed 80.6 and 48.3%, respectively, of the information that would have been available through individual selective genotyping or total population genotyping. In effect, the statistical power of 45,600 individual genotypings was obtained from 328 pool genotypings. This methodology can make genome-wide mapping of QTL accessible to moderately sized breeding organizations.

Animals↗
PubMed2006

Functional implication of an Arg307Gly substitution in corticosteroid-binding globulin, a candidate gene for a quantitative trait locus associated with cortisol variability and obesity in pig.

We previously reported that corticosteroid-binding globulin gene (Cbg) may be the causal gene of a quantitative trait locus associated with cortisol levels, fat deposition, and muscle content in a pig intercross. Sequence analysis of parental animals allowed us to identify four amino-acid substitutions. Here we have examined if any of these single amino acid substitutions could be responsible for the difference in CBG binding and affinity for cortisol between the parental breeds, using in vitro assays of Cbg variants after transfection of mammalian cells. Additionally, the Cbg coding region was analyzed in samples from a synthetic pig line to study association between polymorphism and CBG biochemical properties, carcass composition, and meat quality. Both in vitro transfection assays and the association studies suggest a role of the Arg307Gly mutation in increasing CBG capacity (by >70%) and decreasing CBG affinity for cortisol (by 30%). The Ile265Val substitution may also have an effect on decreasing CBG affinity for cortisol by 25%. The mutations Ser15Ile and Thr257Met do not seem to have an effect on CBG parameters. The Arg307Gly substitution was the only mutation associated with a parameter of meat quality and no mutation was linked to carcass composition.

Amino Acid Substitution↗
PubMed2004

The genetic basis of adaptive population differentiation: a quantitative trait locus analysis of fitness traits in two wild barley populations from contrasting habitats.

We used a quantitative trait locus (QTL) approach to study the genetic basis of population differentiation in wild barley, Hordeum spontaneum. Several ecotypes are recognized in this model species, and population genetic studies and reciprocal transplant experiments have indicated the role of local adaptation in shaping population differences. We derived a mapping population from a cross between a coastal Mediterranean population and a steppe inland population from Israel and assessed F3 progeny fitness in the natural growing environments of the two parental populations. Dilution of the local gene pool, estimated as the proportion of native alleles at 96 marker loci in the recombinant lines, negatively affected fitness traits at both sites. QTLs for fitness traits tended to differ in the magnitude but not in the direction of their effects across sites, with beneficial alleles generally conferring a greater fitness advantage at their native site. Several QTLs showed fitness effects at one site only, but no opposite selection on individual QTLs was observed across the sites. In a common-garden experiment, we explored the hypothesis that the two populations have adapted to divergent nutrient availabilities. In the different nutrient environments of this experiment, but not under field conditions, fitness of the F3 progeny lines increased with the number of heterozygous marker loci. Comparison of QTL-effects that underlie genotype x nutrient interaction in the common-garden experiment and genotype x site interaction in the field suggested that population differentiation at the field sites may have been driven by divergent nutrient availabilities to a limited extent. Also in this experiment no QTLs were observed with opposite fitness effects in contrasting environments. Our data are consistent with the view that adaptive differentiation can be based on selection on multiple traits changing gradually along ecological gradients. This can occur without QTLs showing opposite fitness effects in the different environments, that is, in the absence of genetic trade-offs in performance between environments.

Adaptation, Biological↗
PubMed2000

A quantitative-trait locus controlling peripheral B-cell deficiency maps to mouse Chromosome 15.

Peripheral B-lymphocyte homeostasis is determined through incompletely defined positive and negative regulatory processes. The A/WySnJ mouse, but not the related A/J strain, has disturbed homeostasis leading to peripheral B-lymphocyte deficiency. B lymphopoeisis is normal in A/WySnJ mice, but the B cells apoptose rapidly in the periphery. This B cell-intrinsic defect segregated as a single locus, Bcmd, in (A/WySnJxA/J)F2 mice. Here we mapped a quantitative-trait locus (QTL) that contributes to the A/WySnJ B-cell deficiency by examining the F2 progeny of a cross between strains A/WySnJ and CAST/Ei. In this cross, minimally 1.9 QTLs controlling peripheral B lymphocyte deficiency segregated. The (A/WySnJxCAST/Ei)F2 mice were phenotyped for splenic B-cell percentage and the DNA from progeny with extreme phenotypes was used to map the QTL by the simple-sequence length polymorphism method. A genome scan showed linkage between peripheral B-cell deficiency and Chromosome (Chr) 15 markers. When closely spaced Chr 15 markers were analyzed, the 99% confidence interval for the QTL map position extended along the entire chromosome length. The peak lod scores >17 occurred between 30 and 45 cM. We conclude that a significant QTL segregating in (A/WySnJxCAST/Ei)F2 mice resides in this middle region of Chr 15.

Animals↗
PubMed2004

Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice.

Here we present a strategy to determine the genetic basis of variance in complex phenotypes that arise from natural, as opposed to induced, genetic variation in mice. We show that a commercially available strain of outbred mice, MF1, can be treated as an ultrafine mosaic of standard inbred strains and accordingly used to dissect a known quantitative trait locus influencing anxiety. We also show that this locus can be subdivided into three regions, one of which contains Rgs2, which encodes a regulator of G protein signaling. We then use quantitative complementation to show that Rgs2 is a quantitative trait gene. This combined genetic and functional approach should be applicable to the analysis of any quantitative trait.

Animals↗